Mathematics Average Formulas, Tricks with Examples - EduDose

batting average formula problems

batting average formula problems - win

State of baseball scorebug designs (As of Feb 11, 2021) - A more detailed writeup

State of baseball scorebug designs (As of Feb 11, 2021) - A more detailed writeup
So apparently I’ve found my calling on this sub as a scorebug connoisseur - So let’s review all the scorebugs all the regional and national channels has used for MLB for 2020, and I’ll give them a score on a scale from 1 to 10. Mostly I’ll speak on the design, but I’ll bring up some points on legibility.
This will be a more detailed writeup for every scorebug, so this will be a long post.
If you want to see the score bug’s design again as a refresher, just click the network name, I’ve capped them all for your convenience.
Hope I beat the buzzer for offseason posts and if I miss a scorebug I’ll amend this post. Won’t do MLB International bug because I literally can’t access that.
TBS
https://preview.redd.it/rmsj6n26fqg61.png?width=402&format=png&auto=webp&s=f37752163485f8e70058898fcf164ae14a51860d
It’s still the industrial-metallic style they’ve used since 2018. I’m very slightly annoyed of batter-pitcher info asymmetry, where the batting average/tonight’s batting results isn’t on the same footing as the pitch count and is not shown. To be fair the pitch count indicator is clear, and TBS has obviously found the winning formula since they haven’t budged from 2018’s design at all. It has enough info and it presents them decently, still no radar gun info tho, that was kicked after the 2017 experiment.
Only thing of note is that for 2020, the bug is placed in the lower third now, and third outs have now discarded the special “MID/END 8” splash, opting for the same TBS/MLB logo fly-in with the exact “scorebug initiation” animations when it returns from commercial but in reverse. Not the best, I prefer the special third out splashes as it highlights the physical scoreboard metaphor where it’s imperfect, and I find the metallic design to be just a tad outdated for 2021, but it’s readable, and certainly better than the humongous brick for 2016. Ugh.
It’s alright. 6/10
ESPN
https://preview.redd.it/gx52uyb7fqg61.png?width=1760&format=png&auto=webp&s=6bf616116efaa0dccf38d19379def7ecd7049e77
The same 2018 endeavor returns with the oversized bug with one extra addition for the playoffs - The series scoreline. It’s oversized, but it does manage to feature BOTH batter and pitcher info, even if pitch counts are in its own box which makes the drawers of the players below the team boxes look like an afterthought and just slapped on. Extra credit tho: They included the batting order of the player AB!
Speaking of afterthoughts, you know how the team boxes as a whole, aka the colored rectangles have the same height as the play action boxes in black? Well, stupidly, ESPN just shoved the series scoreline ONLY for the two team boxes, so the dumb pitcher and batter info juts out the bottom like a sore thumb. I mean, you could pull the bar all the way across to at least make the whole thing a tidy rectangle right? Or hell, do it like the out-of-town tracker on the right where they found something to occupy the space so it’s even. Uh. I prefer the original 2016 Helvetica SNB design, at least that thing doesn’t take up 1/3 of the screen.
You tried. 4/10
Fox (ARI, DET, MIA, KC, ATL, STL, MIN, CIN, SD, TEX, LAA, CLE, MIL, TB)
https://preview.redd.it/88pjinl4fqg61.png?width=412&format=png&auto=webp&s=31a041f63a4ac48644679beed1671c8935cc61dd
Hallmark of just good design. From the neatly ordered rectangle in the lower-right-hand corner, to the timeless home run splash with concise info, to the right-positioned base indicator that transforms into line scores at will, to the rich and neatly-stacked pitcher-batter duel with radar guns and the batting order, need I say more? Fonts are high contrast, legible, and stunning beautiful to look at while not being distracting.
One thing to note tho, during the playoffs they switched the yellow base lights to white for the indicators for a game or two and because of how everything is black and white in the side panels, I thought the bases loaded indicators were bases empty for a half-second. Clear highlight color like yellow solves the issue. Don’t play with fire again.
Timeless. 10/10
NBC Sports (OAK, SF, PHI, CHW)
https://preview.redd.it/zj2uuuv2fqg61.png?width=614&format=png&auto=webp&s=f45dbcbd35fc6353ca694cd028a70b3e77507096
NBC is always one step behind on these things. Still obnoxious (for 2020) skeuomorphic and glossy team bars, and the complete absence of much pitcher-batter info. All you get is a pitch count and a radar flash for every new pitch. It’s passable for some year like 1998, that’s for sure, but when other stations have freaking leap-frogged your designs and became more informative, maybe spruce it up a little?
I suspect heavily that NBC saves a lot of manpower by not having their crews work extra to throw up the new pitcher and batter every 3 minutes, but I mean, you have the pitcher splashes for every bullpen summon. Come on. Your home run splash is still epic though.
Works but should try harder. 6/10
AT&T SportsNet (HOU, COL, SEA, PIT)
https://preview.redd.it/gekpj541fqg61.png?width=626&format=png&auto=webp&s=9d715c2044521d51cb52dace21f69a8567e6936a
Very, very weird. First of all, I’d just like to say how much I hate when scorebugs are one-sided. Play-by-play? Fine. When you can’t even award the courtesy of popping a home run splash to your opponent, that’s low. Such is the ballad of AT&T’s graphics. Seriously, it just ticks up the runs and empties the base lights. It’s a weird design where the ball-strike count is inexplicably shoved into the corner next to the giant bar for the pitcher and his pitch count. No batter info anywhere.
There are so many weird elements, like the vertically-aligned out lights that confuses me for a good five seconds before I realized they are out lights. A redo is necessary, but a rethinking is where it’s at.
Change it. 2/10
SportsNet LA (LAD)
https://preview.redd.it/xg45mskzeqg61.png?width=524&format=png&auto=webp&s=d16c1a55b149adbb7844c35a97a0ec9cde1d477b
I’ve always had a soft spot for the Dodgers’ scorebug. First of all, they do innovate, this year, their scorebug has adopted a new flatter design. Their base indicators are LIVE, and update immediately instead of after the play, and the run odometecounter design as players score and it updates is cool af. It’s also the ONLY scorebug where you get extremely-detailed batter info, including the results for his last AB! Why aren’t we all doing this? But the pitcher is unnamed as a result and his count shoved into a corner.
It is really pleasing, BUT it falls into the AT&T trap on not offering your opponents the home run graphics. Oh well, for a regional bug it can only do so much. Also they ditched the third out light for a lowly cross-dissolve. Why?
Be impartial. 8/10
MASN (BAL, WSH)
https://preview.redd.it/6jai38zxeqg61.png?width=470&format=png&auto=webp&s=729d7e5083acc9f63f5d748a071b6472da4c79d6
Do you only want the bare minimum? Do you absolutely hate any form of design? Do you want ZERO home run graphics, no names anywhere, and barely any pitch counting? I mean, when your infamous 2012 bug for the 30-run TEX showing has its own HR splashes, you gotta look into the mirror and figure out why the regression in design. Idk, is this a fucking PowerPoint slideshow all this time? Small W on the design tho, your bases are faux 3D! Yay!
Too visually drab, this is so bad. AT LEAST it’s clear, but it’s not informative at all really. Death knell: your radar gun OBSCURES the ball-strike count!
Some graphics won’t kill you. 2/10
Sportsnet (TOR)
https://preview.redd.it/3wh942queqg61.png?width=430&format=png&auto=webp&s=04796fbb3c70c7588a3b082e4c24de933666e4a0
Because this is a straight copy of Fox’s bug, like seriously, even down to where the inning, outs, and ball-strike count are placed, I’ll only focus on the differences. The immediate disappearance of the ball-strike count once the ball is in play is novel, you’re the only people who did it and it makes a huge amount of sense. It is unneeded and I might have yoinked it for my own design. But the pitcher is still active on the mound after a ball put in play, so why take that away?
Seriously though, your home run splash where the text flies in, truly rock.
Unique spin with very, very minor complaints. 9/10
SNY (NYM)
https://preview.redd.it/uenzs05teqg61.png?width=406&format=png&auto=webp&s=de98e3bd39b1dd9d60e92db0ab065771e9932428
After years of the godawful, bland, and extremely-outdated blue box, we get this. Still an evolution with the same home run animations, but everything is flatter, slimmer, and a little more colorful. Something about how sanitized it is still make it drab, but at least we don’t have to stare at that blue blob again, even if Large Attractive homered under it.
No batter info anywhere tho.
Decent evolution. 6/10
YES (NYY)
https://preview.redd.it/1w4oaj4qeqg61.png?width=420&format=png&auto=webp&s=2499f6c0113106cf3a6f24860b282285f4d85101
Now this is a scorebug I’ll have to say NO too. First of all, low-hanging fruit, no names anywhere. Fine, that’s also an NBC problem. But why on God’s Green Earth is the active play indicators (bases, outs, ball-strike count) split BETWEEN two sides? I literally have to dart my eyes around to even catch up on occupied bases and THEN see the count.
Also wth is with the semantics of “Pitch x” for the pitch count? I know it is semantics but it looks like the next pitch is x, instead of x+1 pitches. Small complaint, but does clarity not matter any more?
Needs a redesign. 4/10
NESN (BOS)
https://preview.redd.it/cu189xmneqg61.png?width=350&format=png&auto=webp&s=8ed197dd5597180b9a0a12e62d7f05bee8530f18
Welcome to MS Paint: The Scorebug. I know people meme flat design as being created with MS Paint — But this? This is actually MS Paint, not even kidding. NEW this year is finally, a pitcher name. Wowwee, gotta wait several millennia before they bring the hitter name in. They finally decoupled the pitch counter from the main element.
But somehow this isn’t bare minimum. Whatever happened to the 3D one in 2011? AT least that one IS a design. This one just had some spotlight transition, there is literally no design. Not even 3D bases.
No design. 1/10
Marquee Sports Network (CHC)
https://preview.redd.it/uhf4kspleqg61.png?width=788&format=png&auto=webp&s=b69008256de7a9e79b524030ab2d37aa425e8df3
I’ve saved the worst for last. Here’s some homework for you, take a look at the scorebug image, and tell me how many outs there are for this current play in the image. Answer: There are two. If I can quiz you on what a scorebug is supposed to represent, you have COMPLETELY failed. Even though, you have actual batter-pitcher info! With names! The fact I can’t tell how many outs because of your dumb neutral colors design deserves a zero.
And also wholly inflexible too, can’t even put up a graphic in real-time for Alec Mills’ no-hitter, just zero runs and some weird “Final” graphic where it sits on top of the bug for a few seconds after the final out before it descends. Also, the only network to use “2-run homer” as a nomenclature for your splashes.
The graphic wants to be good but it isn’t. Your network is solely dedicated to baseball. You can’t get baseball info right. Your radar blocks out the ball-strike count for a good few seconds.
Biggest L ever. 0/10

IN CONCLUSION - Just copy what Fox is doing. Even I did.
EDIT - Some paragraph spacing fixes, and finally fixed the network name for TOR. Sorry Jays fans.
submitted by iconredesign to baseball [link] [comments]

Reverse Engineering the ICC Test Batting Rankings

Reverse Engineering the ICC Test Batting Rankings
TLDR: I tried to replicate the ICC Test Batting Ratings formula from a 30-year-old book and got decently accurate results.
Skip to Results for the graphs
Link to spreadsheet where I did all my calculations
Link to sections of the book that describes the algorithm
For a while now I’ve been interested in finding the formula for how the ICC Player Ratings are calculated. I figured that, although it might be quite complex, there would be some complete formula or algorithm specified somewhere online. But alas, after quite a few google searches, I couldn’t find exactly what I was looking for. The most information I could find was from this site, which is either old and has been superseded by the more current site or was never official in the first place. So eventually, I decided it would be fun try to reverse engineer them for myself.
Disclaimer: This was really just a proof of concept, the method I used was inexact and often not very scientific. If I wanted to do this properly, I’d probably need use a lot more sophisticated tools and software that I’m unaware of. All of this is to say that this is largely just to get the jist of the formula and I could be talking out my arse at points, but hopefully it is still interesting!
The Ancient Sacred Texts
In order for this to be remotely possible I needed data in the right format I needed to know what variables were actually taken into account. I had some idea of that from the aforementioned FAQ but I eventually found myself asking around on the member forums of the ACS (which if you haven’t heard of, I strongly suggest you check it out). They very kindly pointed me to this book, which provided almost all the information I needed to try to replicate the rankings. The final section of the book very handily gives a fairly detailed description of the algorithm used by the Deloitte Ratings, which went on to become the official ICC Ratings. However, it was written all the way back in 1990 and it is very possible that the rankings have changed quite a bit in the past 30 years. As well as this, there are some aspects that are left out that I had to guess/figure out for myself, which we’ll get onto later
The Data
Of course, I also needed to have all the data, from the description in the book I knew the raw data I needed to calculate the change in rankings after a match were as follows:
· The scores of each batsman in each innings
· Whether or not the batsman was not out at the end of his innings
· The bowling rating of each bowler at the start of the match
· The number of overs bowled by each bowler
· The batting rating of all batsmen before the match
· The winner of the match
· The number of innings played by the batsman before the match
Most of these things can be taken from the scorecard of a given match. I used CricketArchive because it seemed more consistent and easier to parse than cricinfo scorecards. Thankfully, you can also find the batting and bowling rankings at any given date in the history of Test Cricket online pretty easily here. So after messing around in Power Query for a few days I was able to fumble together a script that could take the scorecard link as input and then combine all this data together for all the batsmen involved in the match and spit it out. My dodgy script only worked completely on about half the matches I gave it and the webpages only show the top 100 at any given time (meaning you had to be in the top 100 batsmen both before and after the match for me to be able to find your rating), so after throwing it around 35 test matches since the start of 2017 I was left with 218 individual match performances as data points with which to experiment.
The Algorithm
Deriving the Match Score
The ratings are a weighted average of scores given to each individual innings, and the book provides this equation for getting the new rating after an innings

https://preview.redd.it/nxnloha7my061.png?width=572&format=png&auto=webp&s=ab24a8304af9aa5dd9ed523c204ef888a91a1fb9
*After looking at the book I tried to confirm the derivation of this formula but kept on ending up with (k * Old Rating * (1-k) instead of (k * Old Rating * (1-k^(n)). However, that through the numbers off so I think what is in the book is correct and not a typo. It would be really appreciated if someone could double check this though, and point to where I’m wrong if I am.
Where k is the decay constant that they set at 0.95 (I assumed it hasn’t been change since then) and n is the number of innings played by that batsman before that innings. We only have the ratings before and after each match as that is when they are updated, but we can make an approximation that I will call Derived Match Score (DMS), by manipulating the equation to get


https://preview.redd.it/52ktfva9my061.png?width=696&format=png&auto=webp&s=f729efc3b8ab1ce49505087147aecd0d046a81df
In theory, DMS should be equal to the weighted average of the first and second innings scores given to the batsman in that match, so I can define Match Run Value (MRV) as follows, and then plot it against DMS to verify my results

https://preview.redd.it/cuzvdlsamy061.png?width=479&format=png&auto=webp&s=dc61ca82ff458ba73d8967eb785251e61e00a393
Which leads us on to the meat of the problem…
Calculating the Innings Scores
This is the actual formula that gives a score to each innings, the book denotes this as Runs Value (RV) and the crux of the formula is as follows

https://preview.redd.it/esjmnvzbmy061.png?width=544&format=png&auto=webp&s=6be7944fe125c654d7287f3cb5399c8ae1711d4f
So what are all these variables? Runs is simply the number of runs scored in the innings. Average is the average runs per wicket over all of test cricket (the book states this as “approximately 31”, however I used 30.5 as it is closer to that now)
MPF, IPF and Quality require a bit more explaining. MPF, or Match Pitch Factor can be thought of as the average runs per wicket during the match, however there is some nuances that I will get to later. Similarly, IPF is Innings Pitch Factor and can be thought of as the average runs per wicket of that innings (with the same caveats as MPF). Quality is a sort of expected average runs per wicket, which is derived as some function of the weighted average of the bowling ratings of the opposition bowlers (weighted by the number of overs each bowler bowled in that innings).
You can sort of think of this formula as taking the runs scored by a batsman, making an adjustment for how difficult it was for the average batsman in that match, making a smaller adjustment for how difficult it was for the average batsman in that specific innings, and making a much bigger adjustment for the quality of opposition bowling. Also note that these adjustments are multiplicative, and that we’re still ending up with a score on the scale of runs. A batsman up against a perfectly average attack, in a perfectly average innings in a perfectly match will have the same Runs Value as the runs he made in that innings.
Innings Pitch Factor and Match Pitch Factor
This is the first place where there is a major lack of information in the book. Regarding the ratio of runs to wickets in a match, it states:
“Incomplete innings have to be adjusted first, as 180 for 2 would very rarely be equivalent to 900 all out. A separate formula thus transforms the simple ratio of runs per wicket to the much more important sounding ‘match pitch factor’ (although, it should be stressed, the actual pitch is not being assessed in any way)”
The only problem is that they don’t give any formula for this, so I was stuck. Ultimately, with no information on the functional form of said formula, the only way I could treat this was to guess a reasonable function and continue from there.
I decided the most reasonable assumption to make was that MPF was simply the average of the IPF for each innings, and that I would calculate “my” IPF as follows. Consider the average percentage of innings runs scored by the fall of the nth wicket, and denote it as C(n). I found data for partnerships in this paper, and used it as a proxy (I know that adding all the means and finding the cumulative percentage is not necessarily the same thing, but I figured it was a good enough approximation for my purposes).
Wicket Average Runs By Fall of Wicket C(W)
1 36.6 0.122
2 72.9 0.242
3 114.3 0.380
4 157.9 0.525
5 192.5 0.640
6 225.6 0.750
7 250 0.831
8 271.5 0.903
9 287 0.954
10 300.7 1
Then calculate IPF by projecting what the completed innings score of an incomplete innings was likely to be, after considering this table, and dividing by 10. So if an innings is declared on R runs and W wickets, then

https://preview.redd.it/puv3nkezeu061.png?width=162&format=png&auto=webp&s=2af97a43c02011d1faf8edd9ea7da1fd5adc3a88
This IPF isn’t perfect, but it made a slight increase to the accuracy of the results
Quality
After sorting out the IPF and MPF I still had to figure out how to calculate the Quality variable. As with the other 2, the book doesn’t give a formula or really any hints towards it other than it uses the weighted average of bowler’s ratings. So I made the assumption that it could be approximated by the basic formula

https://preview.redd.it/jfojiclemy061.png?width=407&format=png&auto=webp&s=c4023f84034d8a5c4092f4ed3d362d73f1d8d7b7
Where a and b were parameters to be estimated. I thought I could use a simple linear regression on this with the data I had, but I couldn’t easily extract the quality rating from the derived match score (for reasons I’ll get too soon). I considered trying to make this estimation based on a regression predicting the actual innings totals in the matches from the bowler’s ratings - that is what the Quality variable is supposed to account for – but the data for that would be too noisy to do it properly. So I ended up to resorting to the, not very scientific, method of using Excel's solver to find values that best fit the data, then rounding them to correct significant figures. I was left with a = 1800 and b = 30.
Adjustments
The book then describes adjustments made taking into account the result of the match. I won't cover them in detail here because this post is already massively long and they are in the pages of the book I linked to above if you are interested. Basically, batsmen with high scores in winning games have their score for that innings increased proportionally to how well they did, whilst low scores in losing efforts get quite severely punished. It was all described completely which was nice as it meant I didn't have to do any guesswork but the fact the adjustments were there meant that it wasn't simple to directly work out Quality as a function of the oppositions bowling ratings.
There are also adjustments made for if a batsman finishes not out but they aren't described at all beyond a brief mention so I decided to omit them from this.
Dampening First Innings
In order that a player doesn't reach the top of the rankings immediately if they have a particularly good debut. The book puts it like this:
"The system works for all but the newest Test players, who for the first few games of their career have their ratings damped by gradually decreasing percentages to stop them rising too high and too quickly.
But after ten innings (for a batsman) or 40 wickets (for a bowler), ratings are no longer damped - after then, players are on their own
It is unclear here whether or not this means that their real rating is kept and used to calculate new ratings, which then reduced by a different percentage after each match, or if a player's first innings simply gets counted for less forever. As it was simpler to implement, I chose the later. So now a player only ever receives a given percentage -p- of points for his first inning, and the percentage of points he receives for his second and third innings, and so on, are increased linearly until his -n-th inning, at which point all innings are worth full points in the ratings. So we have parameters p and n to consider
Using the same method as that used to estimate the a and b parameters for Quality, I determined that p = 50% and n = 10. In other words, a players first inning is worth 50%, and this increases until his 10th Inning which is worth 100%.
Results
So how does my hacked together approximation of the ratings compare? As mentioned, the MRV should be equivalent to DMS (up to a transformation). If we plot them together we see that they agree pretty well with each other. In fact MRV can explain roughly 90% of the variation in DMS
https://preview.redd.it/9m0k8fmlmy061.png?width=500&format=png&auto=webp&s=ce4a5a3dc88509129fcc7227b800f81d4dc27454
You may wonder why this isn't a trendline with equation y = x, but rather y = 22.2x +79.9. This was to be expected as the ratings (and therefore DMS) are all based on a scale of 0 to 1000 whereas Innings Scores (and therefore MRV) are still always on the scale of runs. But we can use the information from this graph to convert each Innings Score into the correct scale. Then we can use the first equation of this post to work out the rating after the first innings, given the rating before the match and the newly converted innings score for a batsman's first inning. We can then predict what the rating should've been after the match using the calculated rating after the first innings and the second innings score. This gives us a set of ratings that we calculated using our algorithm, along with the actual ratings calculated by the ICC after the match. Plotting them together looks like this

https://preview.redd.it/r99idlynmy061.png?width=453&format=png&auto=webp&s=7994b26a8a98377ec7dcdda91c7db765ce034a75
That's an incredibly close fit, but can be a bit misleading, as ratings after a match would be close to the rating before the match, which we use in our calculations anyway. It would be more informative to take a look at the change in the ratings compared to the predicted change in the ratings.

https://preview.redd.it/ls3xc45qmy061.png?width=487&format=png&auto=webp&s=4b7f8e23822c46227fecc40ef8209b92edec76b7
So this is still a good fit. In fact, this algorithm can explain nearly 92% of the variance in the change in official ratings after a test match. Is that good? I'll leave that for you to decide.
In theory it should be possible to get it pretty close to 100% as we're trying to predict a process which is itself driven by an algorithm and completely non-random. Still I think this shows we have an algorithm who's results tend to line-up pretty well with those of the official ratings, and I think it was not too bad for a first try.
Where do the uncertainties lie?
I think the biggest uncertainties are in that we don't really know what sort of function the Quality, MPF and IPF variables follow, and it seems impossible to ever know that with certainty. Similarly, there are a lot of parameters to be determined. There were at least 4 that were determined here and hey are all linked together in complicated ways its impossible to take one in isolation and determine its value. Even more parameters were taken as given and could've been changed since the book came out. The nonlinear weights for each factor as well as the decay constant were examples. If I had not considered them fixed I don't think I would've had enough data to confidently determine every parameter. So next time more data and more sophisticated parameter estimation techniques would be required.
What next?
The first thing I wanna do with this is to forecast the changes in ratings after each test in India's tour of Australia. That way I can test if it actually works on new data it hasn't seen before, or if its complete junk.
Also, now that we have a similar process for determining rankings as that used in test. We could use it to make our own batting rankings for first class competitions. I think that would be really cool and interesting, if say we had a complete rankings table for the County Championship
The obvious next step is to work out the bowlers ratings, but they are even more hideous than this algorithm, so I'll leave it a bit for now. Would be interesting to come back to some time in the future though.
If someone who actually knows what they're can pick this apart or point out a flaw in what I've done, I'd love to hear from you. I'm genuinely curious as to how someone would go about doing this sort of thing, and I'd love to learn more (even if it necessitates telling me this is complete garbage)!
If you made it this far thanks for taking the time to read this!
submitted by TekkogsSteve to Cricket [link] [comments]

One letter to rule them all (W’s guide)

One letter to rule them all (W’s guide)
The second limited unit in this game arrived! As an AoE Sniper, she’s automatically one of my favorite units, no question asked. I’m not even hiding my bias, that’s right. But in the interest of making a guide I swear I will try to keep things objective. So get your snacks and drinks ready, since this is the longest post I've ever made and I apologize for the wall. I'll bold up the part that I think is important though, so look out for those.


I know she's a Sarkaz, but is that a bat on the top right of the background? Is she a Vampire like Warfarin and Closure?

Overview

AoE Sniper is actually better than what people give them credit for, but that’s just relativity and the people’s tendency for extreme/exaggeration statement. They share one or two weaknesses as AoE Caster but have enough of other stuffs to make up for them partially. With long range, splash damage, high evasion, team support damage amplifier, hard crowd control, consistent damage, and a big burst capable to rival that of Firewatch, W enters the Arknights world as a playable operator.

Stats

- Offensive stats:
Of all snipers, AoE Sniper’s base ATK is one of the highest, losing only to Wide Range Sniper, and whatever Rosa’s archetype is. And because W is a 6* unit, she will have the highest ATK among the AoE Snipers, and as a quick note, losing to Ambriel by only 40 ATK at max. As with high base ATK units though, their attack rate often is reduced to compensate. AoE Snipers attack once every 2.8s, which is just longer than Wide Range Sniper (2.7s), and just faster than Medics (2.85s), and AoE casters (2.9s). Control Specialists are their own thing we don’t count them.
- Defensive stats:
Despite that high ATK, their HP isn’t that massively shafted to balance it out. AoE Snipers’ HP is actually among the highest of the Snipers, but W’s HP isn’t necessarily notable among her kin. She lost out to Shirayuki by 25HP at max, lost out to May(!) and Exu. As for DEF, she’s average among the sniper, if not below average. Now that’s for base stats only, W has something else to offer her even more survivability with her kit, which we will get into later on.
- Cost:
As with any AoE unit in this game, their cost is higher in respect, and for AoE Sniper, it’s quite bad for one other reason as well. For W specifically, she gets hit by 1 other reason, she’s a 6* unit, the highest rarity in the game. Starting at 25 base, she can get as high as 29, gaining 2 extra DP per promotion level. AoE sniper is one of the archetypes that gain additional DP at E2, but there are always justifications for it, which we will get into it right now.

Range

AoE Sniper has the second longest range in the game, losing only to Ifrit, and tied with Wide Range Sniper and Rosa, excluding the side range. They are also the only archetype so far to gain extra range at E2, which is one of the main reasons for the extra increased cost at E2.
From left to right: AoE Sniper's range at E0, E1, and E2.
Now the extra range at E2 is the more important part, at least in my eyes. The little range at E1 rarely comes into play, as it is rarely that you would be able to let a range unit to look straight into an enemy lane. Usually, the range tile will be on the side of the route, and so the range on the side matters more often than the middle one. If you can use that middle range at E1, it’s either an Ifrit spot (Aak put that medicine gun down), or you’re looking in perpendicular from the path and the extra range at E2 still help you cover the area much further.

Trait

Deal AoE Physical damage.
This is why they are called AoE Sniper. Whenever they fire their projectile, at impact it explodes and deal damage in a certain radius around the impact location. This radius is 1. If the enemy died while their projectile is midair, it will still do AoE damage at the dead enemy’s location, the effect is just not shown (as I have (not) seen from Meteorite’s effect). AoE casters attack enemies instantly, so it doesn’t work there.

Talent

Available at E1 – Ambush:

After being deployed for 10 seconds, gain 40% Physical and Arts Evasion, and become less likely to be targeted by enemies.
At E2, upgraded to 60% Evasion.
An indicator that the talent is working: some red mist appear around W
The first talent is amazing for her survivability, and adding to all of her defensive stats earlier, which turns it from average to good. 40% is admittedly low enough to make the chance inconsistent, but 60% is more than enough. Additionally, W also reduces her target priority from the enemies, means that they will only target her if she’s the only one in her range (or if she’s deployed last along with Ethan and Manticore and other people with the same thing). So with the two of them combined, where W is less targeted from enemies, AND also dodges 60% of the attack that do come her way, W becomes more “tankier” than her stats suggest. Like this meme by ucky
Now, it may sound like some stupid anti-synergy, since enemies will target her less, making the Evasion redundant. But afraid not, as you can also place her closer to the enemies, and take the hits as the enemy approaches, but stop once the enemies find your other allies. That way, it put less strain on your frontline blocker. Or it can be used to solo a lane with less healing needed.
It’s even more amazing when you consider the fact that, with W’s deploy cost, she’s more likely to be the second last or last unit deployed. Unless your vanguards can handle the waves up until you have enough for both W and your dedicated lane blocker to shift the aggro from W to that blocker. Well, with W’s talent, now you don’t have to do that, as you can just plop W after anyone and she will still be the lowest priority target, just ensure that she lives for 10s first, and bam, problems solved.
You can’t play this talent quite like Firewatch’s S1 or April’s S2 (woah spoiler alert!), as even though 60% Evasion is a huge number, it’s still ultimately a chance. You also can’t drop straight down in the middle of a bunch of ranged enemies like April too, as it need 10s to activate, while Firewatch can just straight up avoid any attack if her skill is up. (no it’s not my Firewatch bias… kinda). You can put her alone in a lane with minimal support though, like with someone who has global regen, or just time it in a way that she’ll end up with a little HP left, because it’s not like she has to stay at full health to deal full damage. The talent allows her to solo in a lane in that way, and you can practically save a healer slot when carefully calculated. (just reset the stage til you get the correct RNG roll lul)
However, if you’re like me, and abused AoE Sniper long range to it’s limit, their location is probably going to be away from the frontline by like a large distance, a distance that not many enemies can reach without walking through the blockers, then the talent is admittedly not as useful. Of course not all map is just 1 lane funneling type, so it doesn’t work like that all the time (it does work against large/global range enemy like Mortar or Faust though). Basically, all of that is just to say, this talent really covers most issues that come with her archetype.
The talent is also good at dodging everyone who are pulling for her.
cough... anyway

Available at E2 – Insult to injury:

Stunned enemies in W’s range takes 18% extra physical damage.
tl;dr at ends of this section
Now the second talent is also amazing. It’s just like Sesa’s talent except more useful more flexible/accessible. Any enemies that is stunned inside her range will take 118% of any physical damage during the stunned duration, and no spoilers intended, but W’s skills can cause quite a lot of stuns.
This talent is a Final Damage Multiplier, which is a multiplier that is calculated after all enemy’s defense stat. Which sounds awful, given that the physical damage formula is (ATK – DEF) * Final Multiplier, which lessen the effect of the multiplication. The good news is all Final Damage Multiplier stack multiplicatively, i.e. if we have, say, E2 Pramanix talent working, that’s 118% * 130% = 153.4%. It can snowball fast, if we give Sesa’s talent with 14% as well, that’s 174.876% multiplier to the final damage. You’re not necessarily going to have all of that multipliers all the time, so we’re just having 18% for now. It’s still quite good even if it’s affected by DEF though, as I will argue in S3 section.
Considering that it’s a Final Damage Multiplier though, that means it can increase the minimum damage from 5% to… 5.9% yay. But the more important thing is, this is a debuff to the enemies, which means all allies will benefit from W’s talent, making her a team player as well. Well, okay, just the physical damage allies though, but the physical damage dealing allies are more numerous than the arts one, as also stated in my old Sesa guide, and unlike Sesa, W can combo with every physical damage ally, unlike Sesa who can’t really teamwork with long range units, and SA (I mean, who would stay alive to be blocked while SA is S3-ing amirite?). Even if it only boosts physical damage, people like Mostima can still benefit from this talent, assuming if the rest of the squad still deals physical damage.
As spoiled above, W’s skills cause stuns herself, so this is where it gets even better. The stun is applied before the damage instance is dealt (just like any other debuff), which means, W get the bonus damage herself, so at E2 she basically has free bonus damage to all of her skills. It is still not a guaranteed damage buff always, as you need the enemies to be inside W’s range to achieve this, and those skills has quite a bit of an explosion radius.
Now I know what you’re thinking, Suzuran also has something similar and it doesn’t work with her own attack, why is that? Well there are actually 2 layers to her talent, she causes sluggish to hit enemies, and then applies Weakening to sluggish-ed enemies in her range, but it kicks in a little too late, even if the slow is applies before the damage. I mean, I’m no HG members, but I assume it’s to avoid the simple fact that if it works like that, any of Suzuran’s basic attack is automatically amplified, which sounds strong, while anyone else with a similar Final Damage Multiplier debuff has some other working attached to it (below 40% HP, blocked with allies, stunned through skills or allies,…) which doesn’t amplifies their basic attack all the time. But those are all conjectures and guesses, just know that this talent amplifies all of W’s skills if she hits enemies inside her range, and boost all physical allies at the same time.
That was quite a lot for just 2 talents… now on to her skills.

Skills

- RIIC Skills – always available – Patience: When W is a trainer, increase mastery SPEED for all Sniper by 30%.
Upgraded at E2: if the training is for mastery 3, further increases the training speed by 65%
Available at E2, separated skill – Insipid: When W is a trainer, increases morale consumption by 1 per hour when training a Sniper skill to mastery 3.
This is still a problem for some people, but this type of base skill increases training speed, not reduces training time. A speed increases of 30% led to about 23% reduction in training time, like Ptilopsis’ talent. But unlike Ptilopsis’ talent, any unit in the training room already gains 5% training speed, so it’s actually 35%, which is about 25.92% time reduced.
At E2, the speed remains the same for any masteries except the third one, where it is boosted to 95% (I mean, I hope it is that good, since the drawbacks of double morale consumption attached at E2 is quite bad.
I shouldn’t diddle around much with base skills, so let’s continue.

First skill: King of Heart

Btw if you want the TL;DR for all 3 skills, look for the bolded line in each mini section, or something ;-;
- Description:
Immediately launches a grenade, dealing physical damage to all enemies in explosion radius and stuns them.
- Stats at level 7:
310% AoE physical damage, stuns for 2.1s, costs 19 SP, no initial SP, Auto Recovery, manual activation.
- Masteries:
M3 increases the damage to 350%, stun duration to 3s, and reduces SP cost to 16.
- Further details:
This skill functions essentially like Meteorite S2. Upon clicking the skill, she will launch an attack with the stats mentioned above. This attack does not affect attack interval… in a way.
W (and Meteorite), performs an attack every 2.8s with no other ATK SPD buffs. Using W’s S1 or Meteorite’s S2 will not change that interval but will interrupt the normal attack that comes with those intervals. Let me put it this way, after they launch an attack, you can wait 2.5s, use the skill, and W/Meteorite will immediately launch the next attack that comes at 2.8s. It will cancel any attack animation currently ongoing, so be careful with that. The video will hopefully clarify what I mean.
Don't use it when she's about to make a normal attack though
The explosion has a radius of 1.2 tile. While that increased area sounds not that significant compared to the basic radius of 1, it is 44% larger in area covered, which is more significant than it seems.
- Usage:
Don’t.
.
Let me backtrack though. The skill is actually just fine, even without the trick I mentioned. You can think of it as if W is shooting out Projekt Red’s S2 but without Red’s talent, which is actually better than it sounds. A bit spoiler again, but it is the only skill in W’s kit that is a near instant AoE stun.
The problem is, if you need this skill from W, something has already gone wrong. The delayed stun from S2 and S3 don’t matter 95% of the time. Her S2 has less stun duration, but also less cost, her S3 has longer cooldown, but is 5 levels stronger, and so, the time where you need her S1, is when you need to deal with a clump of drones (will explain in S2 section), in less than 33-39s and more than 16-19s, constantly. For that, a suggestion to replace W with an AA sniper is valid, and this is one of the few cases where Meteorite is better, since her S1 blast damage is just too good at not caring who’s in the radius.

Second skill: Jack in the Box

- Description:
The next attack instead set a mine that last 2 minutes in a deployable tile (both ranged and melee tiles). The mine will detonate when an enemy is nearby, dealing AoE physical damage and stuns for a duration.
- Stats at level 7:
250% physical damage, 1.8s stun, 10 SP cost, no initial SP, Auto Recovery, auto activation.
- Masteries:
M1 reduces the SP cost to 9, damage to 260%.
M3 reduces SP cost again to 8, damage to 280%, stuns duration to 2.2s
- Further details:
The mine can only be placed inside W’s range, but on any deployable tile. If there are no enemies in range, W will place mine randomly on any valid tile. The mine can be “retreated”, if you don’t like the random targeting because it’s blocking an important spot for your other operator, just click on the mine, then retreat it like any other operator. (It also works for Silence’s drone and Shamare’s doll).
As long as there is an enemy in range, W will plant a mine in their place. She will auto aim the mine at the tile of the enemies is on with the same priority as her normal attack. That is to say, whoever she’s attacking, when the skill is up, she will put the mine on that guy… if possible. What if she cannot place a mine on that tile, but other tiles are free? Well then it’s random as you can see from the clip below, where both valid enemies are on top of another ally, and thus she cannot place the mine. It’s treated as if there are no enemies in her range, because she wouldn’t even attempt to place a mine nearby that tile. Look at this for example
If there is a valid place on an enemy that is not her current priority, then the mine goes to that guy. In that clip, if I retreat Myrtle, then the mine is always placed there, regardless of her target priority. In this case, it’s probably the next valid enemy that is mine-able that also fit her target priority. In the CN wiki, they said something about if there are 2 enemies in range that is the same priority (least path left to blue box), then it goes to the one with higher HP (if I’m reading the google translate correctly). The mine priority also ignores the Guerilla Defender aggro, from what I’ve seen.
The skill converts W’s next attack into planting a mine, and so she will not perform the normal attack for that interval when the skill is up. It is important in a sense that, if the skill is done charging when W just finished her normal attack, she will have to wait for that 2.8s interval to pass before using it. It can be important at times, especially considering that…
The mine takes 1.5s to explode after triggered. It’s a considerable amount of time in conjunction with that attack time earlier.
The triggering range is 1.35 tiles away from the center. Incidentally, the explosion radius is also 1.35 tiles. This means 2 (or 2.5) things.
  • The mines can trigger on someone who’s diagonally away from the tile but not too far. It’s not exactly like 8 tiles around itself like Waai Fu S2 or Phantom S3, but it’s close enough. Quick video to see how bad it can potentially be
  • That also means fast enemies can outrun the explosion as well. To outrun a mine in the longest route, they need to cover 2.7 tiles in 1.5s. Only Sarkaz Lancer so far in this game is able to do so, and only when they gained max speed.
I am speed
But the more important part of fast enemies is that, if they are just slightly fast enough, they can run enough distance to reach a different mine and thus triggering more mines than needed in order to kill them. Especially if 2 mines are close together, as someone can just go up to the first one, trigger it, go to the second one, trigger that one as well, and died from the first mine because it was delayed. That means if your other DPS is not enough, you can easily waste a lot of mine after all those times spent stacking them up. The enemies only need to cover at maximum 1.35 tiles per 1.5s, that’s a movement rate of 0.9. Do you know how many enemies have at least 0.9 mvm spd? I don’t actually, please tell me. That of course doesn’t matter if there is no mine stacked and W is just using each one as it comes.
thanks to 777ucky for the clip since I was getting lazy when I get to this part lul
Another important part of the trigger radius is that, despite being confined in W’s range only, it can still be triggered by enemies outside her range. Effectively, with this skill, W has an extra layer of damagin range outside of her base range, which is nothing to scoff at, especially considering that she can use this skill with or without enemies.
Or, if you want to be cheeky, you can find maps where there are non-deployable tiles and point W to that area. This forces the mines to be in a few specific locations only, with some working from your other operators. That way you can guaranteed that there is always a mine in your selected location. And speaking of which, if there are no valid tile in her range at all and she gain a charge for the mine, she will just hold it forever, until a valid tile shows up. That can be good or bad, depends on how you play your cards (no not the King of Heart card).
If you still remember what I said back in her first skill, you’d be asking why her S1 is used for drones. Well, it’s because the mines cannot hit drones. They cannot be triggered by drone, and they cannot damage drone if triggered by someone else. An explanation is that since the mine is on the ground, its explosion cannot hit drone. Which is a bad explanation, because Sesa’s S2 bombs also stay on the ground, and they hit drones just fine. Sesa is good confirmed???
Some miscellaneous infos about the mines:
  • The mines actually have stats, apparently. None of the stats matter though, since it’s invincible, cannot be attacked, cannot block, and all damages are calculated using W’s ATK.
  • You can see if a mine is triggered or not. When triggered it will start flashing red.
  • If W is retreated, all of the mines are instantly gone, without any damage (same for the 2mins timer).
  • Once a mine is out, it is instantly ready and can be instantly triggered (important for those who plays Techies a lil bit too much).
- Usage: look for the → for the most important part
Best for when you want to deal with constant wave of enemies that is a little bit stronger than trash mobs without paying your mind to W. And if they are just trash mobs, her auto attack couple with other operators would be more than enough to clean those. The stacking mines strat doesn’t work that well either given the waste usage against enemy’s speed, but it still works fine more often than not, and is a great way to make use of downtime between wave.
The triggeexplosion radius can be used to extend her range, true, but it should not a strat to be based around, while still worth it to remember when you’re trying to find space to put W. And speaking of space, since the mine need a deployable tile to work, sometimes you may find W not able to bunch up mines together due to the map’s layout, and so it is kinda map dependent. Technically her allies are also fighting for location as well, but as the commander, you should be able to pacify them and plan around it.
very quick 2 examples of maps with enemies on a lane with undeployable tiles
Oh and regarding the extend range through the mine’s explosion radius, if a mine is at the edge of W’s range, the enemy that trigger it has a chance to be damaged and stunned from outside of her range, and thus not receiving the damage amp from her E2 talent, which is also not that great.
This skill is usually compared to Meteorite’s S1, and in the general calculation, W wins out by a little bit (W slightly loses out in ideal conditions for Meteorite, which neve… rarely happen). Technically, Meteorite is still better to deal with drones, as her massive splash doesn’t really care who she’s targeting.
→ Remember what I said about holding a lane solo back in her first talent? This skill is the best to work with it. Usually, when we’re talking about solo-ing a lane, it’s assumed that the lane’s enemies’ density will be light. Enemies will be appearing in a small amount over an amount of time. The evasion chance then is helpful for not needing much babysitting, maybe for even the whole run, and the fact that the lane has low density means that W will have all the time to stack up mine, and so the extra loss of mine per enemy doesn’t matter either.
For running alongside with other ops, do remember the limitation of deployable tile. To maximize the amount of available mine, it’s generally considered best to place W as forward as possible, as her long range will cover more area. In that case, her first talent will be fully used. As a ranged enemy approaching, they will attack her, since they see her first, where it will miss 60% of the time, but as those enemies move a little further, they will face other operators, by then they will stop attacking W due to the lower priority. It can spread the damage out to multiple operators, making them less likely to be in a low enough HP that they’ll die in the next hit.
→ If you want to use the long range to push W in the backline to save space for shorter range unit, this skill still works, but in a different way. If there’s no available tile in her range left, but a mine is in 1 of those tiles, you can chain stun the enemy that triggers that mine. Since W has to hold her charge until a space is available, once a mine is gone, W will instantly replace it. Effectively, you get double the stun duration (well it depends on her attack interval at the time, but still), and double damage, making it a pseudo burst damage of sort.
really great for when you can force the mine to be where you want it to be
This skill gives consistent and automated damage for an operator that lacks said consistent damage (because of her innate stats). However, covering weaknesses is for the weak-minded fool! Okay calm down just a joke. But if you’re not familiar with AoE Sniper, or any archetype with slow but powerful strike, consistent DPS skill is the way for you to start stepping into learning how to use them, and this skill give you the most stun uptime for all of W’s skill (note: not stun duration, stun uptime).
→ There are more issues with S2 than you’d expect, but nothing too major individually. And hey not like every other operator have no issues with their consistent skills.
But if you want a little more explosive, you’ll come to love her third skill, which is intricated, interesting, and is what I’d recommend to master, for a variety of reasons.

Third skill: D12

- Description:
Place bomb on a few enemies in range, prioritizing enemies with highest current HP. After 3 seconds, the bombs explode, each one dealing AoE Physical damage and stun for a duration
- Stats at level 7:
Target 3 enemies, dealing 280% damage, stuns 4s, cost 39 SP, 17 initial SP, Auto Recovery, manual activation.
- Masteries:
M1 target 4 enemies, 290% damage, cost 37 SP, 18 initial SP.
M3 deal 310% damage, stuns 5s, cost 33 SP, 20 initial SP.
- Further details:
3 bombs that deals 280% damage eh? I wonder if I have heard something similar somewhere… No Wind, you must not lose focus, you’re better than this.
As described, once the bombs latched, it will explode after 3 seconds. This skill has the longest delay from skill activation to stun of all of W’s kit, about 3.5s from tapping the skill to when it explodes.
The bomb has an explosion radius of 1.2, just like her first skill.
If an enemy with a bomb attached die before 3s is up, the bomb immediately explodes and deals the damage and stun. It’s quite hard to actually do it where it matters, because it targets enemies with highest current HP, so one of the enemies has to have the 4th lowest HP among them, but also higher than all of the non-selected enemies, and to be easily killed from that HP amount too.
Regarding her E2 talent, since there is a 3 seconds delay, you’ll find that W may target a bomb on an enemy, but then they walk out of her range before it goes off. Fast enemies are one thing, but it also applies for cases where W is facing perpendicular to the enemies’ path, where her width of range is only 3 tiles, unlike the amazing 5 tiles of length.
All of the damage stacks completely, if all 4 bombs are close together, all 4 affected enemies will take 4 times the damage (or 3 each before mastery). That is a yuuuge burst of damage that not many will survive. If someone survived, they will proceed to be stunned for a long duration afterward, and this skill has the longest stun of all of W’s skills.
Unlike Firewatch, you can easily aim all bombs close together, because it doesn’t have the 1 bomb per tile restriction and enemy tends to clump together when blocked by your frontline. But like Firewatch, I will advocate that stacking all the bombs together is not the only way to use the skill. You can just as well drop this to a scatter group of enemies and expand the stun area massively, split up between 2 lanes (check the enemies’ HP first though) and basically cover 2 lanes at once. What I have said about using Firewatch’s S2 can still apply here, albeit slightly differently.
The bomb’s damage is actually determined on cast, not on hit! What that means is, if you are buffing W in order to get one of those orgasm-worthy explosions, you need to buff W first before using the skill. Then the bomb’s base damage is finally determined, and thus dealing that damage after the 3s delay. This may be why the bomb do not show any red number when exploded, unlike the other skills that also has a high multiplier, like Firewatch, but also Meteorite, Sesa… This video will make it clearer.
Remember: Buff before skill!
Thanks to ucky with the W nuke video that helped me realized this lul. I know, it won’t matter most of the time, since people seem to associate buffing with meme-ing, but it’s worth putting it in the back of your mind when you are going for it.
Also, you can also see the effect of W’s E2 talent, as staying on the field will obliterate the Defender, while going off field will only kill the middle guy. Yes, if it’s calculated before DEF, then it’s going to be even more destructive, but as a team support effect, this is probably the better way to balance it, I supposed.
- Usage:
As you can already guess from the description, the skill is best for annihilating a group of enemies close together. It can kill even the tankiest of enemies, or at the very least, badly wounded them. Take the new Guerilla defender with 1300 DEF and 15k HP, at S3M3 lv56, 4 bombs leave the guy with ((935*310%)-1300)*4*1.18 = 7544.9, that’s like half of his HP already.
But I have also said that you shouldn’t feel like you can only use the skill that way. The cooldown is pretty long before masteries, true, so if you just want to delete big group of things, keep doing it. I usually do that too. I just also wouldn’t hesitate to use it for other cases where I really need it. Example cases like where you need this guy down faster, but he’s not with 3 other enemies, or even if he’s alone inside W’s range, you can still use this skill for a 4-5s stun after a 3s delay. It’s not the best way to use this skill, but it’s not terrible too.
Because of the manual activation, you can be in control of when you want to blow enemies up, as with the many cases to use this skill I have presented. A controllable burst of damage and long duration stun is just that amazing. What that really mean is, this skill is more flexible to use than people give it credit for. The only problem is the long cooldown before M3, and even at M3, it still has a long enough cooldown to force you to make every use count. (I mastered nuking with Firewatch 50SP cost, what does 33SP cost even means lul). You can use E2 Ptilopsis to make it faster though!
→ You can combo with other allies to make a huge explosion too, you don’t have to time it yourself with enemies’ waves. The best allies are one that can easily clump enemies together, like Magallan, Suzuran, FEater, Weedy S2 (not S3 because enemies will just die). DEF reduction allies also work, like Pramanix and Shamare. Late shoutout to Manticore S2, but it stuns enemies every hit, and guess what W’s E2 talent can do?
→ Just remember the most important thing, timing. Every time you use the skill, you have to ask, “are those guys I’m about to blow up the most dangerous threat for the next 40s?”. If yes, blow them up. If no, ask yourself “will my other units able to handle those upcoming guys if W isn’t ready yet?”. If you’re going blind in a map so you can’t tell ahead, then make sure you can answer yes to the second question before using the skill. When you can answer yes to that question, do whatever. You can also ask “can I hold them long enough to allow W the time to recharge her skill?” Depends on which type of enemies, you can actually freely use the skill when you feel like it, if you have a great block squad. You may also ask “if I save this skill too much and missed the chance to use the skill and failed the run, then what?” Then you live and you learn. As said above, nuking a bunch of enemies isn’t the only way to use the skill, and so you can make it a panic button to stun/kill 1 guy that is about to leak, even that is a not terrible usage of the skill, just learn the tempo better so you don’t have to panic yourself with leaks next time.

Some conclusions/thoughts

You may have heard “M1 both S2 and S3 first and see which one you like better” in the megathread a “few” times. I’m not sure if I want to make a definitive answer, but if I have to make one, I’ll have to say “S2 if you’re unfamiliar with AoE Snipers or any slow attacking unit, S3 if you are used to, or prefer, precise timing and decision making”. It still depends on situation, of course, and M1 both skills are certainly a great stop point, as it is both cheap, and unlocks a major breakpoint of each skill.
Each skill has their own way to be abused to fit what you need, but remember, W alone won’t the only damage operator in your squad, so you can just adjust the team, and expands your tools’ variety, rather than adjust how a tool is used just to fit what you need.
If you are questioning whether or not to invest in W or other lower rarity AoE Sniper, just go with W. A 6* investment is costly, but it’s also worth the price more. There will be cases where Shirayuki, Meteorite, or even Sesa can be better, but before those cases show up, you would already use W enough time before that, and as said, W’s skill is still flexible enough to partially fill whatever you’d need of those lower rarity AoE Snipers. Just don’t be like me and build all of them, well unless you want to.
AoE Snipers might not be great for general usage, because AA Sniper can shoot faster and cheaper to deploy. But if you can work for it, you can beat all of the game with only AoE Snipers and 1 or 2 supportive units (and a little bit of overleveling and bruteforcing). So if you want to start using AoE Sniper, but are afraid of the learning curve, don’t be. You can just slowly learn about them by adding them to your squad that you're already used to play with. And as said in the first talent section, it can cover a major weakness of AoE Sniper, and couple with many hard crowd control abilities, W is a great starting location to step in to the world of slow but powerful nuke damage units.
Now all that left is to pull W, ezpz.
.
How are you guys doing in this banner? Oh wait wrong question, if you have W and built her, how did you find her? Is there anything I missed, since I’m pretty sure I always miss something? And biased, don’t forget biased, which is strange since I don’t like W as a character that much, but for gameplay, one of the best, nearly on par with Firewatch (you’re still the #1 pls put that radio down). Anyway, jokes aside, hope you enjoy the post, and hope to see you next time for… someone, idk yet.

Sellout section kek

Other guide posts that is gathered in this post by u/LastChancellor
And Indra guide by u/Boelthor since the other dood didn't update his post yet lul.
Completely unrelated to the sellout, below is my biased opinion, tread carefully.
Why do I think S3 is flexible? I consider instant nuke skills are one of the hardest skill types to use, but it is also one of the most intriguing because of its possibilities. If you find yourself worry about the future threat too much, you will easily find situations where when those threats do show up, enough time has passed that if you used it earlier, the skill would have been up by now anyway. So you find yourself constantly have to ask 1 big question “can I use it now and still be fine before it comes back up?” Answering that question is the best part of these nuke skills, as whenever you can answer yes to it, depends on how the skill functions, people’s playstyle, strategy, team lineup, map, and enemies’ route and composition. And that’s why I think it’s the most flexible type of skill. Because if you just switch up a few things, and the way to use the skill change, or the timing change, and it can fit the playstyle of anyone who’s willing to go with it.
submitted by Windgesang_ to arknights [link] [comments]

Rebuilding the Pirates - Year 8: Ahead of Schedule

Welcome back to season eight of the Pittsburgh Pirates rebuild! Here are the links to the previous entries if you want to catch up: 2020, 2021, 2022, 2023, 2024, 2025, 2026.
We bounced back last year after a few tough seasons, finishing 2nd in the division with a record of 81-81. Even though we missed the playoffs, the team looks poised to make a run sooner than later. We’re flush with talented young players and the minor league system has never been better.
The owner is good with my performance at the moment, but I’m on a one-year deal, so can’t get complacent. I won’t make any moves that sacrifice our future position, but hopefully a few moves around the edges can push us into the playoffs. As with the previous entries, I’ll list the moves I made, the rationale behind those moves, the season results, and the future outlook.
Here are the salaries heading into the offseason (part 1, part 2).
Departures:
Batters:
Willy Adames
I still can’t believe Adames fell off so fast. He was trending down his last few years in Tampa, but I figured that was just at the plate and his defense would continue to be elite. He was unplayable by the end of last season and doesn’t have the ratings to get signed again. He should retire soon.
Osvaldo Gavilan
This was one of those “it’s not you, it’s me” type situations. Gavilan was passable his first season with the team, and probably would’ve been better this year, but I preferred the other available options. Gavilan spent the season in AAA and could get called up again if injuries arise.
Didi Gregorius
I still think Gregorius could’ve been good for us if I built the rest of the roster better. I’ve gotten solid production from players like him in the past, but those teams didn’t feature the league’s largest collection of over-the-hill stars.
Gregorius gracefully retired once his contract expired.
Jesus Salgado
I brought Salgado up one year too early, and I’m now hoping I didn’t leave him in the minors one year too long. He would’ve gotten the call-up if someone got injured, but it never happened. There’s a very good chance he has a major league role next season.
Pitchers:
Michael Burrows
Burrows had one excellent start last season, but I still haven’t forgotten what he did in 2025, so I did my best to keep him out of the majors. I know this is just a bunch of numbers on a screen, but I took his 2025 performance personally.
He had season ending surgery in August. Good riddance.
Blake Cederlind
This is one of those situations where I wish there was more depth to contract negotiations. As is, it’s mostly just “this number is higher than that one, so I’m going there”, but there are so many other factors that could come in to play. Cederlind is a good but not great pitcher, but in my system he’s elite. His ERA+ hovered around 150 the past three seasons, then plummeted to 74 this year with the Brewers. I wish I could’ve told him, “Hey Blake, take a bit less to sign with us because you’re going to do great here, and there’s a good chance you don’t elsewhere. Is the unhappiness that comes with poor performance worth a couple extra million? You know it’s probably not,” but that wasn’t an option, so he took the money from Milwaukee.
Ben Hernandez
Hernandez was once a prized pitching prospect, but injuries have robbed him of most of his potential. He’s still in the system but spent the year in AAA. I might give him a look as a reliever but his days as a major league starter are probably over.
Additions:
Batters:
Dave Castro
Minor league call-up.
Frank Mesa
Minor league call-up.
Will Shirah
Minor league call-up.
Josh VanMeter
See move #5 below.
Pitchers:
Carlos Campos
Minor league call-up.
Lewys Guzman
Minor league call-up.
Christian MacLeod
See move #3 below.
JoJo Romero
See move #2 below.
Move #1:
The first move doesn’t involve any players but it’s the one I’m most excited about. We replaced our old scoutwith a new one that’s rated Legendary in amateur and minor league scouting, and Great in international and major league scouting. This should really help with identifying future young stars.
Move #2:
Pirates Receive: Jojo Romero (100% retained)
Cubs Receive: $1
That’s not a typo, the Cubs are giving me Romero in exchange for one dollar, and they’re paying 100% of his salary this season. The only way this is bad for us is if Romero murders another player. Anything short of that, I can just release him and be no worse off.
He has a fragile injury rating, which is always a concern, but I’m willing to take a risk with his talent. I can see him posting a strong season in our system.
Move #3:
We’re a bit thin in the starting pitching department, so I decided to take a chance on Christian Macleod in the Rule 5 Draft. He’ll be one of the six spring training starters, with a chance of starting the regular season.
Move #4:
Luke Jackson wanted 3/$24m at the start of free agency, which was way out of my price range, but I waited him out and got the deal I wanted. He’s been great for me the past two years and hopefully will continue to perform well. If things go bad, I can release him after the year and only have to eat $4m.
Move #5:
Pirates Receive: Josh VanMeter (80% retained), $270k Cash
Reds Receive: Alex Mendez, Austin Roberts, Alex Milazzo, Sam Bianco, Blake Dunn
This is one of my go-to moves. Trade a dead-end prospect and a bunch of minor league cannon fodder for a one-year rental with salary retained by the other team. The asking price was higher at the beginning of the offseason but dropped to my liking by the beginning of the pre-season.
Mendez might have an MLB future, but I’m willing to bet he’s nothing special. He looks like he could be a decent hitter, but his range will keep him from being anything more than an average defender. The rest of the players going their way look like career minor leaguers.
In return I’m getting VanMeter and enough retained salary and cash to bring his cost this year to $4.25m. If things go right, I’ll get another serious bat to protect Guerrero in the lineup, and a compensation pick at years end. His defense is concerning, but we should have enough elsewhere to cover for him. Come playoffs we can move Guerrero to first, but I want to preserve him during the regular season by keeping him out of the field.
Final Financial Situation:
Heading into the season we have about $20m in available funds, which should allow us to sign our two first-round picks and an international amateur free agent. Here are the salaries to start the year.
Batters:
Primary Lineup vs. RHP when Healthy (\DH enabled in both leagues)*
RF – Mike Sanchez
Sanchez struggled last year but there was nothing in his ratings to suggest he wouldn’t bounce back, which is exactly what he did. He hit 44 homers and stole 36 bases, while providing plus defense at three positions. I should’ve tried to lock him up after his down year but didn’t feel I could afford to take any long-term risks. He will be back next season.
LF – Will Shirah
Shirah took over for Gavilan in left field and performed well. He’s nothing special but provided league average offense, plus defense, and his switch hitting makes for easier lineup construction.
DH – Vladimir Guerrero Jr.
Vlad didn’t have quite the year he did last season but was still a monster at the plate. He led the league in hits, finished fourth in MVP voting, was named an all-star starter, and was the top hitter for the month of July. He only has one guaranteed year remaining on his contract, so I’ll have a tough decision to make on whether to keep him.
1B – Josh VanMeter
When I acquired VanMeter right before the season I had no idea he’d be this good. He started off scorching hot, winning batter of the month for May, and never really slowed down. He led the league in batting average, on base percentage, slugging percentage, OPS, and WAR, and was named MVP at seasons end. He was also the top vote getter for the all-star team and won the platinum stick award at first base.
He’s an upcoming free agent that wants 6/$210m, so he will be signing elsewhere, and I will be getting a compensation pick.
Thank you for your service Josh VanMeter.
SS – Marcelo Mayer
Mayer had another great year, providing elite defense and league average offense from the short stop position. He missed two weeks in September but was back in time for the playoffs. His arbitration estimate is still low, so he will return.
2B – Michael Brooks
Brooks won his third straight gold glove, while providing his typical below average offense. This was his first season without injury, so hopefully he can keep off the IL going forward. He should return next year.
3B – Frank Mesa
Mesa had a pretty quick rise, going from unknown international free agent to MLB starter in one season. I imagine he would’ve won gold glove at third if not for spending a decent amount of time backing up second and short. His offense is nothing to get excited about, but I’ll take the tradeoff for his defense. He’ll return next season.
C – Drew Romo
Romo missed five weeks in June with a hamstring strain, making this his second season in a row missing significant time to injury. He was good when healthy, playing gold glove defense while not being a complete black hole on offense.
CF – Manny Duenas
Duenas was pretty pedestrian at the plate last year, leading me to put him in the 9 spot this season, but he ended up performing more like a number three hitter. He posted an OPS+ of 132 while winning his second straight gold glove, making him one of the most valuable players in the game. I debated moving him up in the lineup but decided “if it’s not broke, don’t fix it.”
I approached him about an extension early in the season and he asked for 8/$78m. I countered with 10/$120m with two team options, then he countered back a week later with 10/$190m, so I decided to table discussions until later. I don’t think he was particularly offended by my 10/$120m deal, I think I just caught him at the wrong time. He was surging at that point in the season and on pace for 9+ WAR. I might’ve missed my opportunity for a $10m AAV deal but might be able to get him for $14-15m AAV if I catch him at the right time next year.
Bench
C – Jayden Melendez
Melendez is still upset about his role on the team and it’s starting to affect his performance. His defense remains excellent, but I know he can do better than an OPS+ of 47. Depending on his value, I might move him and promote Yoshinaga to the backup catcher role.
IF – Luis Tejada
Tejada started at third against lefties and backed up 2B, SS, and 3B against righties. I’m really not sure how he’s doing as well as he is at the plate, but hopefully it continues. As with all good bench players, he now thinks he should be a starter and is upset about his role. Too bad there’s not an “appreciate what you have, or I’ll option you to the minors for the next three years” option to get him to reconsider his position.
OF – Christian Moore
Moore seems to have finally figured out major league pitching and probably deserves a full-time starting role. With the probable departure of VanMeter and possible departure of Guerrero, there should be a spot for him next season.
Injury Replacements
IF – Isaias Dipre
Dipre filled in for Mayer when he was out for two weeks in September, collecting 3 hits in 31 at bats. He was brought in to play defense though, and he did just fine there. He will probably remain as minor league depth next season.
IF – Dave Castro
One of the crown jewels of the minor league system, Castro was called up when rosters expanded to get a taste of major league action. He should be a starter next season but I’m not sure where yet. I feel comfortable starting him at first or third, but he might take the primary DH role due to the fielding ability of the rest of the roster. Either way, he’ll get some reps in the field to stay in practice.
C – Manzo Yoshinaga
Yoshinaga didn’t perform well at the plate in his limited appearances, but his ratings suggest he would be fine if given a backup role next year.
Pitchers:
Pitching Staff when Healthy
SP – Jacob Smith
Smith was a late bloomer but has established himself as one of the top pitchers in the game. He was named to his first all-star team and finished second in the Cy Young voting. The only question is, how long can I continue to afford him?
SP – Rio Britton
Britton continues to improve and should be even better next year, despite leading the league in WAR this season. He was named pitcher of month in June and finished fifth in the Cy Young voting. I would extend him, but it’s not worth the risk for a non-durable pitcher. He’ll continue to play on one-year deals until he becomes too expensive, reaches free agency, or his arm explodes.
SP – Giuseppe Benedetti
I keep hoping Benedetti figures things out but it’s probably time to face reality. He’s an average pitcher with below average movement and isn’t going to do well in my system. I probably could’ve gotten a lot for him in a deal a few years ago, but my only real option at this point is to just hope he gets better.
He missed five weeks in June with an elbow sprain and another five weeks later in the year with shoulder bursitis, so he might not even be able to stay healthy long enough to figure things out.
SP – Christian MacLeod
I rolled the dice on MacLeod in the Rule 5 draft and after a strong spring training decided to give him a spot in the rotation. He performed well and will probably be back next season.
SP – Brennan Malone
Malone missed a lot of time to injury last year and was underwhelming when on the field. I wanted to replace him, but no affordable options emerged, and he got another shot this season. He proved his worth by posting a strong season and should be back next year.
CL – Luke Jackson
Jackson missed four weeks during spring training and then tore his UCL in April. He suffered an 8-month setback in September, meaning he won’t return until after the start of next season. He can’t be traded since he’s injured, so there’s really nothing to do but hope he comes back strong next year.
SU – Easton McMurray
McMurray was named the closer after Jackson’s injury and made the most of his opportunity. He was nearly unhittable the second half of the season and ending up winning Reliever of the Year. Unfortunately, this raised his arbitration estimate from ~ $2m to $5.8m, but this is a good problem to have.
MR – Miguel Toribio
Toribio doesn’t look like an MLB pitcher but finds a way to survive. He could be back if better options don’t emerge.
MR – Caden O’Brien
O’Brien missed another five weeks this year with an elbow strain but pitched well when healthy. He should return.
MR – Gabriel Moya
Moya is like The Little Engine that Could. He doesn’t have the most talent, but he keeps at it and finds a way to get the job done. He’s an upcoming free agent but I doubt he’ll have many suitors.
MR – Jeremy Rivera
Rivera had another solid year and should return, especially since lefties are scarce at the moment.
MR – Josh Nifong
Nifong struggled but his ratings suggest he’ll be fine going forward.
MR – Brandon Williams
Williams was bumped up to the set-up role when McMurray was promoted to closer and performed well, but not as good as his ratings suggest. I expect him to be better next season.
LR – JoJo Romero
Romero gave us 93 innings of sub 4 ERA pitching and was named an all-star. I’d say that’s well worth one dollar. Thanks Cubs.
To make it even better he thinks he’s a starting pitcher now and wants a 6/$80m deal. I’m leaning towards extending the qualifying offer and possibly getting a compensation pick.
LR – Christian Moore
Our bullpen was overworked last year, and Moore was underworked in the field, so I decided to let him pitch some garbage time innings. He pitched 34 innings and gave up 40 runs, which is pretty much what I expected. I think the important part is that the rest of the bullpen pitched 34 less innings.
He’ll probably be a full-time starter in the field next year and leave the bullpen.
Injury Replacements
MR – Lewys Guzman
Guzman was brought up as an injury replacement in May but tore his meniscus not long after being called up. He spent the remainder of the season in AAA when he returned.
I like his ratings, so might give him a shot next season.
SP – Travis MacGregor
MacGregor filled in when Benedetti went down early in the year and did really well. He was sent back down to AAA upon his return but came back multiple times as an emergency starter. He’ll probably start next season at AAA.
MR – Carlos Campos
Campos did well in the couple of innings he pitched and will be in consideration for a role next year.
MR – Luis Faringthon
Faringthon started the year on the IL and was sent for a rehab assignment upon his return. When returning to the majors he continued his hot streak from last season. Hopefully he can remain healthy.
Season Results:
As you can probably guess from the player profiles above, we had a really good season. We finished first in the division with a 99-63 record, which was also good enough for the best record in baseball. We probably could’ve won more games but let off the gas late to keep everyone fresh for the playoffs.
In the divisional round we faced off against the Rockies, who had a record of 86-76 and finished second in their division. They took the first game, but we rallied back to take the series 3-1. Manny Duenas was named series MVP.
The Atlanta Braves were our opponent in the NLCS. They had a record of 86-76 and finished first in their division. We jumped out to a 2-0 series lead, walloping them 17-3 in game two, but they fought back to win games three and five, before bowing out in game six. Manny Duenas was named series MVP once again.
We faced Guerrero and Mayer’s former team, the Blue Jays, in the World Series. The Jays took a 3-2 lead after five games, with four games being decided by one run, but our guys rallied back to win two straight and take the World Series. Former Blue Jay Guerrero was named World Series MVP.
Here are the playoff results.
The formula for success was pretty simple with this team: two smashers in the middle of the lineup, elite defenders that hopefully do something at the plate, and a hoard of groundball pitchers. Our overall talent level still isn’t that high, but all of the pieces fit together. We have a lot of high character players that accept their roles.
The owner is good with my performance and provided me with a 3-year extension after the season. We got a bump in fan interest from winning the World Series and our budget has increased to $128m. Also, I was named manager of the year.
Top Prospects:
We have a lot of elite talent at the top, but it was a struggle to fill out the list at the end. Our new scout has a different opinion on a lot of our guys, but I think most of the big-time ratings drops below are real.
1.) Pietro Bonaccorsi
Bonaccorsi is number one on the list for the fourth straight year. He no longer looks to have greatest hitter of all time potential but still projects to be well above average. He moved to first this season, preparing him for his eventual MLB debut. He’ll start next season at AA but could get called up if injuries demand it.
2.) Brad Thoen
Thoen continues to rise up the list, moving all the way from number five last season. He had a solid season in AA and claims he’s ready for the majors, but I hope to start him at AAA next year. If he does well, I’ll promote him midseason, or when rosters expand.
His ratings have progressed nicely since last year, and as an added bonus his personality trait was revealed as Fan Favorite.
3.) Bobby Dennis
Dennis moves up from number six last year and continues a nice trajectory toward the majors. He performed well in A+ and will start next year in AA, with an expected MLB debut in 2029. His ratings have progressed significantly since last season.
4.) Jeff Hatchell
Hatchell was selected with the fourth pick in this year’s draft and has the potential to be a top of the rotation starter. He has good ratings across the board, durable injury proneness, and great character. He performed well in rookie ball and will begin next season at A+.
I’m very happy with Hatchell but really wish this guy would’ve fell to me. Gray looks like a future Cy Young winner.
5.) Sergio Pardo
Pardo moves up from number eight last year and looks to be on track towards becoming an MLB contributor. He picked up some experience at the two most demanding outfield positions and saw his offensive ratings increase across the board. His offensive production wasn’t what I would like, so he’ll begin next season at A+.
He suffered an injury that cost him six weeks at the end of the year but kept his durable injury rating. Hopefully, it was a one-time thing.
6.) Juan Espinoza
Espinoza made his minor league debut this year and saw his potential decrease from potential Cy Young winner to middle of the rotation starter. I’m not out on him completely, but I wouldn’t be surprised to see him flame out in the next few years. He’ll repeat rookie ball next season.
7.) Mike Mueller
Mueller remains at number seven this year. He saw his ratings increase across the board from last year but probably needs another year before promotion to AA. I’ll start him at A+ and keep a close eye on his performance early in the season.
8.) Josh Breeden
Coming in at number eight, Breeden had a good year in A- and looks primed to continue his success next season in A+. I’m not completely sold on him as an MLB starter, but his durability should keep him healthy long enough for us to find out if he has what it takes.
9.) Chris Simpson
There are a lot of things to like about Simpson but he’s not the same caliber player that we’ve had in years past on this list. His ratings have increased since last season, but he probably needs another season in rookie league.
10.) Vincent Guevara
I really couldn’t find anyone I liked for this spot, so Guevara come in at number ten by default. He has the ratings profile of a solid starter but he’s still 17 and my scout doesn’t really know much about him. We’ll find out more when he makes his minor league debut next season.
Promoted to MLB:
Dave Castro, Frank Mesa
Dropped from list:
Hector Garza
If you thought Espinoza’s ratings took a dive, check out Garza’s as compared to last year. He started racking up injuries immediately and looks like he’ll be out of baseball sooner than later.
Bobby Bosman
Bosman’s ratings didn’t drop as much as Garza’s, but that’s only due to them not having as far to fall. He posted a strong season in rookie ball but doesn’t have the ratings to continue at the higher levels.
Future Outlook:
We just won the World Series but we’re still not where I want to be as a franchise. We have the 29th lowest budget, fan interest is only 70, and fan loyalty is below average. If I get complacent, we’ll be right back where we were a few years ago. We need to continue to make moves with an eye towards the future.
We have a really tough decision to make with Guerrero. He has one guaranteed year left on his deal and it’s looking like he’ll opt out after next season. We really need his bat, but also can’t afford to lose him for nothing. I could always chance it and hope he opts in, but I don’t think we can afford that kind of risk. I’m leaning towards moving him, but the importance of his offense can’t be understated.
If we lose VanMeter and Guerrero this offseason, we’ll probably take a big step back next year. They provided a combined 88 homers and 232 RBIs, and I have no real path towards replacing that production. I like Castro’s potential, but I don’t see a rookie hitting 40 homers and driving in 100 runs. I could maybe get a comparable player in return for Guerrero but more than likely the best value will be to trade him for prospects. VanMeter is a free agent, so I’ll only get a compensation pick for his departure.
I think the playoffs are possible next year, but we won’t be able to make a real push unless we get some surprise offensive performances.
Here is the budget and salaries heading into the offseason.
2023 Review:
\Players without a 2027 screenshot were deleted due to retiring before reaching the majors*
2023 Move #1:
Pirates Receive: Gabriel Moya (2023, 2027), $1.4m Cash
Tigers Receive: Aaron Shackelford
Despite his limited ratings, Moya has provided us with 5 solid years out of the bullpen. Sure, he’s not a star, but he provides solid production at minimal cost.
On the other hand, the Tigers got a player that never reached the majors and sent out an additional $1.4m cash.
This deal might not have been a home run, but we were the clear winners.
Final Grade: B+
2023 Move #2:
Pirates Receive: Aaron Nola (100% retained) (2023, 2027), $5m Cash
Phillies Receive: Adam Haseley (2023, 2027)
I was pretty disappointed with Nola during his lone season with the team. He wasn’t bad but his ratings suggested he should’ve been so much more. I was really expecting a 4-6 WAR season. He pitched well enough to get a big deal in free agency though, so I scored a compensation pick upon his signing.
Haseley has been solid for the Phillies for multiple years and was relatively cheap through his arbitration years. I think this kind of corner outfield production is replaceable, but the real issue is he had significant trade value to a lot of teams. I should’ve gotten something better than Nola, a compensation pick, and some cash.
Final Grade: C
2023 Move #3:
Pirates Receive: Ryan Pressley (100% retained) (2023, 2027)
Tigers Receive: Oneil Cruz (100% retained) (2023, 2027), Jake Wright, Ethan Paul
Pressley spent a lot of time injured during his two years with the team, and when he wasn’t injured, he was complaining about his role. We didn’t give up anything useful in return, but the problem is the same as with the Haseley deal: we could’ve gotten something better for those players. Injuries happen, but I took an unnecessary risk on an older player.
Final Grade: D
2023 Move #4:
Pirates Receive: Archie Bradley (85% retained) (2023, 2027)
Cardinals Receive: Jared Triolo (2023, 2027), Jake Snider
Bradley was great for us in 2023 but missed most of 2024 to injury. I think the value he provided in 2023 was more than enough to justify his cost for both years (~ $3m), and we didn’t give up anything of value in return, so I’m happy with this deal.
Final Grade: B
2023 Move #5:
Signed FA Christian Vazquez (2023, 2027) to a one year $1.5m contract
Vazquez provided gold glove defense and league average offense from the backup catcher position, which is definitely worth $1.5m. Great signing.
Final Grade: A
2023 Top Prospects
1.) Dave Castro (2023, 2027)
Castro finally made his MLB debut after six years in the system and looks to have fully realized his potential from five years ago. He doesn’t have the performance to back up the ratings yet, but I don’t anticipate him having any issues.
2.) Rio Britton (2023, 2027)
Rio was selected at the end of the first round in 2023 and debuted at number two on this list. At the time I said that Britton was everything I could want in a starting pitcher, and it’s looking like he’s living up to my expectations.
3.) Alex Mendez (2023, 2027)
Mendez was my second international amateur free agent signing and I thought he had a similar profile to Castro. He still might make the majors but has fizzled out a bit the last couple of seasons.
4.) Sal Stewart (2023, 2027)
This was Stewart’s second season on the list and I still had high hopes for him as a batter. He appears to have stalled out in AA, but I could see him contributing as a role player at some point.
5.) Christian Moore (2023, 2027)
I predicted Moore could become an above average corner outfielder with a well-rounded skillset and he appears to have become just that. He will more than likely have a full-time starting role next season.
6.) Ben Hernandez (2023, 2027)
Hernandez finished 2023 with a strong performance in AA and looked primed to become an MLB starter sooner than later, but a torn rotator cuff late in 2024 robbed him of much of his potential. He’s spent most of the past few years in AAA or on the injured list.
7.) Easton McMurray (2023, 2027)
McMurray didn’t have a great showing at AA in 2023 but his ratings seemed too good to keep him down. I went with my scout’s suggestion, calling him up in 2024, and was rewarded with a solid rookie campaign. He’s gradually improved to become one of the top relievers in the game.
8.) Luuk Ter-Beek (2023, 2027)
I was skeptical about Ter-Beek’s ability to bounce back from a torn UCL but kept him on the list due to his tremendous upside. It turns out I was right to be worried. He’s steadily regressed and has stalled out as a AA depth piece.
9.) Drew Romo (2023, 2027)
I was lukewarm on Romo in 2023 and it looks like he’s become exactly what I expected, an ace defensive catcher that struggles to bat his weight.
10.) Jayden Melendez (2023, 2027)
I was undecided on Melendez in 2023 but he’s found his way to the majors due to his defense and character.
Honorable mention:
Felipe Mezquita (2023, 2027)
Mezquita had the ratings profile on an MLB starter but a torn labrum made me skeptical of his future. He spent part of one season as a starter for us but was sent back down to AAA due to his poor performance. I shipped him to New York after the season, where he struggled his first year, but he seems to have figured things out this season.
2023 Minor League System Grade: C+
This year’s list was a real mixed bag. Castro, Britton, and McMurray all look like top contributors; Mezquita, Moore, Romo, and Melendez all look to be solid but not great; and Mendez, Stewart, Ter-Beek, and Hernandez are all just meh. This was my fourth year with the team, so it’s not a real surprise the minor league system was still average.
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ModiFluff creation process and genotypes. (By Twist3e)

Shortly after the Chimera Virus crisis The Fluffy Control centres of the newly founded Governor Warden cities found themselves innundated by the sheer volume of the number of Fluffies attempting to claim the cities for themselves, the outlying wastelands driving them into the Human strongholds in search of food, water and shelter. Initially, Human personnel alone were used to quell these invasions, however overtime it became apparent that FC operatives alone would not be enough to protect the cities from the encroaching infestations.
Fluffy Control operatives found themselves overwhelmed and working around the clock to cull the Fluffy population, becoming exhausted and demoralized. Therefore it became paramount that the FCs were supplemented with additional support in order to be able to fulfill their quotas and mandates.
Multiple approaches were considered and executed, the defensive walls known as 'Trenches' were constructed in strategic locations around the Governor Warden cities, in order to filter smaller numbers into the cities, this method had to be employed as walls themselves proved to be too costly to both man and maintain, mechanical measures were devised and implemented, such as the 'Foals for nummies' machine, however, problems arose with both maintainence and overall effectiveness overtime.
In time the solution became obvious, the Fluffies themselves, the most abundant resource available.
Within every Fluffy exists a chimeric blueprint that comprises their genetic structure, while a baseline Fluffy alone is little more than a nuisance in terms of individual capacity for the ability to cause physical harm, the DNA of the creatures that were combined in order to create them contains far greater potential.
In order to create a ModiFluff, A Fluffy must be taken from a juvenile stage (the 'walkie-talkie' stage as it is referred to by the Fluffy mothers) and immediately place into a sensory deprivation chamber, a 'Foal Hole' as they are commonly referred to. The Foal hole requires two Foals to be effective, as a mental deconstructing is required alongside the physical deconstruction.
Within the 'Foal hole' it is expected for the two foals to both befriend each other and comfort each other, this relationship is paramount to the mental restructuring that will occur later. They will find patches of Fluffy blood within the hole and will usually begin to imbibe it as hunger sets in. Overtime the Foals physiology will change in accordance with their development, in order to allow them to digest the blood their bodies will begin the preliminary modification and express their usually dormant predator genes. This initial, minor mutation is only possible in the early stages of a Foal's life, fully grown Fluffies cannot be used in this process.
The first stage will end invariably with the death of one of the Foals, it is then expected that the remaining Foal will then consume the flesh of the deceased or die, thus cementing the Foal's perception of itself as a 'Munstah' and preparing the Foal's body for the modification process. At this point the Foal must immediately be removed from the hole.
Once removed, a post hole interview must be conducted by the one who placed them within who is to become their 'Handler'. Any measures may be taken by the ModiFluff handler but they must end the interview with a confirmation that the Foal is now identifying itself as a 'Munstah'. This is to be encouraged, as this fosters a detachment from the rest of the Fluffy species in the Foal.
Once it has been confirmed, the Foal is to be taken for Modification immediately. Five injections of catalyst solution are to administered to the Foal, the first always being a direct infusion to the heart to begin the process. The rest evenly distributed across the body.
The Foal will then enter a state of delirium as its body undergoes mutation, having consumed Fluffy tissues the body will now believe itself to be one of a number of potential predators within its genetics and will now begin the process of mutation in order to express the most prominent genes within the Fluffies genetic make up.
The process can take any time between a week to a month, the Fluffies DNA will reconstruct itself from the unstable state brought on by the first stage of modification, as it metabolizes the catalyst solution, it is during this process that the final outcome will be predictable. Fluffies commonly experience a great deal of REM during this stage of modification as they drift in and out of consciousness.
Once the process is complete, the newly formed ModiFluff will be ready to be collected by their appointed handler, it is imperative that the handler comes for them as soon as possible if they are unable to be there when they wake up, as the early stages of awakening are the best time to imprint bonds and trust with them.
From this point on the handler is expected to spend as much time as possible with their ModiFluff, at this stage the ModiFluff is feeling disconnected from thier original identity and requires guidance to become an effective piece of equipment and develop their new identity. A successful Handler will teach their charges how to hunt, challenge them to improve themselves and instill an undying loyalty within them.
Once sufficiently trained, the final test is to give the ModiFluff a 'live' meal of a Foal. This final test will cement the ModiFluff's self perception of being a 'Munstah' and effectively sever any lingering ties to its race and former self and it is now ready to work alongside its handler.
MODIFLUFF GENOTYPES
Fluffy dog, CanisFluff- A common genotype form, as the name implies this form resembles a dog, the CanisFluff is exceptionally loyal and steadfast to their Handler, they have sharp teeth and a powerful bite, they are also curious and fun loving and have an insatiable appetite for Foal meat. When hunting they chase down their prey with superior speed and tear them apart with violent savaging actions. A handler must be affectionate and engaged with their FluffHound, as a FluffHound can become easily depressed if they are ignored or understimulated. CanisFluffs often develop and obsession for their handlers, which can often develop into jealousy or protectiveness. They are always eager to please their handlers.
Puffy Griffin- A peculiar, yet still common genotype form, the catalyst solution has expressed both the feline and avian aspects of the Fluffy and created a strange parody of the mythical griffin. Puffies, surprisingly, are actually capable of flight despite the seemingly unbalanced nature of their bodies. They typically have a stoic, superior air about them, reminiscent of the Feline and Avian counterparts, they consume their Foal prey whole and when hunting they fly overhead and divebomb their targets to slash at them with their talons, they are even capable of lifting up smaller Fluffies and drop them from a height to kill them. Puffy Griffins are fairly independent and often refuse to remain with their handler unless they have a well formed connection, therefore Aeries are constructed throughout the cities to house them while they are not hunting. They are capable of speech, but often do not employ the ability, instead they usually squawk or coo, in the rare instances when they do speak they no longer have a unique voice, they instead mimic the voices of other creatures, similar to a Parrot or a Raven.
Fluffy Snake 'FluffSnek'- A rare varient, The FluffSnek is a strange genotype form that stretches out the Fluffy's body, Fluff Sneks are sedate, low energy ModiFluffs that are no longer capable of speech, they are useful for sliding into compact areas and flushing out hidden Fluffies. Fluff Sneks are capable of performing constrictions, administering a venomous bite or even spitting venom, they typically swallow their prey whole and only require feeding around once a week. Due to their now reptilian nature, FluffSneks are cold blooded, they enjoy seeking out hot spots to bask in and despise cold weather, even going so far as to enter a hibernative state in the winter season. FluffSneks like to leech on their Handlers body warmth and typically ride on their handler, usually looping themselves around the neck or concealing themselves under their clothes. Since FluffSneks are not capable of speech they must communicate using other methods, such as blinking, hissing or squeezing. One enterprising handler even succeeded in teaching their FluffSnek rudimentary sign language and later go on to design a collar-mounted voice synthesizer that detected the movements of the now ineffective vocal cords and translated them into understandable language.
BullFluff/Fluffalo- The BullFluff or Fluffalo is a rare genotype, horned and muscular, it resembles a small mountain of muscle. Fluffalos are not carnivorous, however they can be taught to dislike Fluffies for the impact they have on the environment, which in turn deprives the Fluffalo of food. Fluffalos are stoic and quiet, and their droppings can be made into extremely potent fertilzer. They do not 'hunt' as other ModiFluffs do but are capable of crushing a baseline Fluffy easily with their muscualar frame. BullFluffs can typically reach a height of three feet in stature, making them one of the larger variants.
FluffRaptor- The FluffRaptor is an exceptionally rare genotype, resembling something similar to a dinosaur, thus sparking rumours that Fluffies were partially created with DNA derived from palaeontology digs (A rumour I can neither confirm or deny). The FluffRaptor is a compact, powerful hunter with two muscular legs and a powerful maw, they are not capable of speech and instead screech or roar. Befriending a FluffRaptor is difficult as they appear to suffer from some mental degredation, a Handler must instead dominate them, installing themselves as a 'pack leader'. An instance has been noted of an operative with homunculism using a FluffRaptor as a mount, riding their ModiFluff and chasing down Fluffies with startling proficiency and efficiency.
UTERINE MODIFLUFF GENOTYPES
In my studies and experimentation with catalyst solution I discovered that applying the Formula to the unborn Foetus of a Fluffy can fundamentally alter the genetic structure of what will come out, effectively creating an entirely new species. While these genotypes are still derived from Fluffies they possess far greater potential in terms of intelligence and strength, on occasion even rivalling humans. The creation of a 'Uterine' ModiFluff, involves injecting catalyst solution directly into one of the forming Fluffy foetuses within a pregnant Mare, once done, the other Foetuses will be absorbed into the modified Foetus, adding their biomass to the overall creature and vastly extending the pregnancy time of the Mother. Overtime the Mother will be gradually consumed as the ModiFluff grows within its womb, around the clock feeding and bowel evacuation is required during this stage as the ModiFluff is grown, lest it completely devour the nutrients of its host and kill itself in the process. Once the ModiFluff reaches full term, a live dissection cesarean must be performed to remove the offspring, unfortunately the recipient of the dissection cesarean must be live to ensure a proper 'birth', attempts to euthanise the host beforehand resulted in the deaths of the ModiFluff. Once removed, the Uterine ModiFluff must be cared for immediately, as they possess a somewhat longer maturation time compared to baseline Fluffies, a byproduct of their greatly extended life time.
Fluffy Satyr- The Fluffy Satyr genotype is a ModiFluff with the Humanity aspect of its genetic structure fully expressed, Satyrs exhibit heightened levels of intelligence and strength compared to their Fluffy counterparts and are useful for simple work. Like their namesake, Fluffy Satyrs resemble Humans closely, but still retain a good deal of their originally intended visage, their ears droop from the sides of their head, can be moved and often display the Saytr's current emotive state, thus making it almost impossible for them to be able to lie. Satyrs, like Fluffies have tails and hooves that walk upright on, but they instead possess a hard, keratine hoof, far more suitable than the soft, leathery hooves of a baseline Fluffy, fur grows from the hooves to just below the knees. Satyrs have dextrous hands, but they lack a fourth finger, this does not greatly affect their capability. Satyr hair and eyes comes in the variety that Fluffies are capable of, some even achieving tones of purple or pink. Attempts to use Fluffy Satyrs in FC operations met with failure, as it turns out they have far greater empathy than even some Humans and they do not like to cause harm to others, instead choosing to help and support them as best they can. Ironic that they seem to possess a greater level of humanity than a good deal of Mankind.
'Stunted' Fluffy Satyr- The stunted form of a Fluffy Satyr will peak at a height of around three to four foot in height, they closely resemble human children and will always do so, this version of the Fluffy Satyr is often used for farm work, as they possess high levels of energy and are easily controlled, due to their cowardly nature and lowered strength, unfortunately stunted Satyrs possess a fundamental flaw in their genetics, which can lead to a degredation in their bodies and make them enter a weakened state, fortunately this can be offset through the consumption of Fluffy meat, rejuvenating them with its hormones and proteins.
'Full grown' Fluffy Satyr- Full growns Satyrs can be created through the ModiFluff process by adding the DNA of a Human to the blood of subject [--REDACTED--]. The resultant solution can then be added to catalyst solution and injected into the unborn foetus. A full grown Satyr will closely resemble whoever the DNA was harvested from, but will not possess and memory or personality of the donor. Full growns do not possess the flaw that causes the stunted Satyr's need to consume Fluffy flesh, in fact they seem to have an aversion to it, suffering from nauseua if it is presented to them. Full growns can reach a height of five to six foot and usually have a more mature visage compared to their stunted counterparts, their strength and intelligence is far higher too, but not enough to rival a humans. Full growns can be trusted to perform more complex tasks and following a suitable education are often used as assistants in offices and businesses.
AnthroFluff- AnthroFluffs are strange, skewed versions of Satyrs, I believe them to be what occurs when the solution fails to fully express the Human traits, resulting in a peculiar hybrid that still possesses a great deal of the original Fluffy traits (at this time I am unsure as to what causes the phenomenon of this failure.) AnthroFluffs, like Full Grown Satyrs, lack the genetic flaw of Stunted Satyrs, possess an anthropomorphized body and walk upright on two hooves and possess hands, and reach a height of five to six foot, but their entire body is still covered in fur and their faces resemble a Fluffy's more closely than a Humans. But most notably is their mental state, they are far more like Fluffies than any other ModiFluff genotype, just placed within a vastly different vessel. AnthroFluffs are mischievous and unsuitable for work, unable to focus on such things, instead wanting to only fulfill their desires by any means necessary, their intelligence is heightened, but hidden behind a veneer of Fluffspeak and childish impudence. Once mature, they are highly sexual and frequently crave 'good feews'. Due to this sexual nature coupled with the 'uncanny valley' nature of their appearance they often make most people extremely uncomfortable. Investigation into the potential uses of AnthroFluffs is ongoing, but it is believed that they could be used as a mature version of the Fluffy Pony biotoy pet in the event of the world stabilizing and returning to a pre chimera state. However further research is required to quell their oversexualized nature, perhaps hormone therapy can be used to offset these traits, or enhance them.
Minotaur AnthroFluff- This variant of the Uterine AnthroFluff was a peculiar and highly dangerous genotype, the Minotaur AnthroFluff was similar to its counterpart but exhibited additional traits such as horns and heightened muscle mass alongside intense aggression, like Farm Satyrs and the Minotaurs of greek legend, this ModiFluff craved meat for its development and was fed on a strict diet of Fluffy tissue, devouring up to four Fluffies in a day. Initially, it was believed that the Minotaur would be an effective Fluffy Hunter, however, as it reached maturity, this hunger was replaced by an even deeper craving, one for the flesh of other ModiFluffs, particularly for Uterine ModiFluffs. The Minotaur AnthroFluff was a dangerous individual and was required to be kept in isolation, as its strength rivalled a Human's easily and could even peak it when enraged, after a time it was deemed too costly and dangerous to keep on site and scheduled for termination, it was removed from FC404 at the behest of myself and Governor Warden Mercy and removed to a detention centre to be contained, examined, researched and disposed of safely. The Minotaur was a creature of around six foot in height when slouched and seven foot when standing up straight, its skin was coated in a layer of thin brown fur and it possessed startling reserves of power and stamina, had it been controllable it would have been an excellent Fluffy hunter given its natural physical prowess and hunger for Fluffy meat, but after its maturation it became completely unruly, ongoing research hopes to perfect this genotype for use in the future, if the Fluffy Minotaurs could be tamed they could be extremely useful.
Subject 1N [--REDACTED--]- [--ENTRY REDACTED--]
ZOANFLUFFS
The ZoanFluffs seen during the attack on New Cleveland were a strange breed, the true nature of their mutation is strictly classified. The ZoanFluffs appear to be similar to ModiFluffs but far stronger, some even capable of taking down full grown humans. The sheer extent to the mutations available to the ZoanFluffs have yet to reached by FC ModiFluff cultivators, strangely there are several forms that have never been produced by catalyst solution, suggesting that an intelligence of some description is behind the designs. ZoanFluffs are capable of reaching sizes far beyond their original baseline Fluffy form, how this is possible and how it can be done is such a short time has yet to be discovered. ZoanFluffs hardly resemble the Fluffies they once were, the only indication of what they once were being the residual Fluffy babble when they speak. At this time it is believed that the ZoanFluffs were all killed during the attack on New Cleveland.
Ursine- These large ZoanFluffs resemble enormous, muscular bears. Their muscle mass has increased so exponentionally it has torn their skin open in places, revealing the powerful muscles underneath. The Ursine has a large maw with a powerful bite, capable of crushing bone and even metal. Their original hooves have broken apart and become vicious claws, capable of slashing and grabbing. Ursine were reported to have overpowered their victims, using both their strength and weight to overwhelm them and pull them down, leaving them at their mercy to bite and slash to pieces. The Ursine ZoanFluffs reportedly had a hunger for human flesh and a sexual appetite, proving to be downright peverse. Ursines are strong but appear to have trouble multitasking in altercations, reports say that they were taken down most easily by attaacking them from multiple angles, one on one proved to be fatal for the Human or ModiFluff in most cases.
Vespine- These ZoanFluffs were reminiscent in appearance to overgrown vampire Bats, it is believed that this form is a recessive holdover from HASBIO's attempts to produce a 'Bat Pony' varient in the original line of Fluffy Ponies, The Vespines have lost a great deal of their former Fluffy form and are blind, compensating for this loss sense with heightened senses of smell and hearing. Vespine have wings and are capable of flight, similar to Puffies, however their wings are not limbs of their own, but rather flaps of skin connected to their front and rear legs. Their rear legs have claws and they can use them to grab hold of their victims and pull them into the air, or use them to hang upside down. The Vespines seem to have a taste for blood and are capable of sensing it through scent alone, in combat they determine the location of their quarry through a combination of scent and hearing, they also seem to detect their current location and their immediate surroundings through a form of rudimentary echo location. One individual managed to confuse them by spreading blood and remaining silent, thus nullifying their senses.
Leo- The Leo was a large, agile varient of ZoanFluff, somewhat resembling a large, predatory cat. Leos were reported to be eager, independent hunters and stalked their victims throughout the alleys of the city. They ambushed their targets and would attempt to bite weak spots to incapacitate and devour them. The Leos all appeared to have somewhat of a mean streak, revelling in the bloodshed of each kill they exacted. The Leos were also adept climbers, capable of climbing and jumping down from great heights that would harm other creatures of various sizes. However they appeared to be too focused on the kill, failing to see other dangers as they eagerly attempted to land fatal attacks. They were weaker than the Ursines and more or less stood on equal footing to the average Human. Therefore they relied on stalking and ambush strategies, striking when the prey least expected it, when tired or wounded.
Bovine- The only Bovine seen in New Cleveland was an individual known as 'Aurochs', Aurochs was an exceptionally large ZoanFluff, similar to a giant Bull in appearance. Aurochs was extremely strong, even for a ZoanFluff's standards. Aurochs had enormous horns, which appeared to be capable of growing back in a short period. In combat Aurochs employed charges and stomps, crushing his opponents with his massive weight alone. Aurochs, unlike other ZoanFluffs seemed to not possess the bloodlust the others displayed and far more capable of rational thought, it is believed that is is due to the herbaceous nature of the creature he resembled. For Aurochs' service to New Cleveland he has been named a citizen of Ohio, and is therefore subject to all the rights and protections of a citizen of the USA, harming him or his properties is rightly considered a crime.
Alcine- The Alcines were reminscent of large Elk deer, they had large antlers, hardened hooves and a surprising level of strength. They employed similar tactics like that of the Bovine varient. However they appeared to suffer from a fundamental flaw and were easily taken down by several FC personnel, it is believed that they were not suitable for combat and had another kind of role outside the invasion.
CattleSnake- A mysterious creature that seemed to be an amalgamation of feline and serpent genetics, the creature that called itself Felubra was one of a kind, it claimed to have a connection to the overall network that linked the ZoanFluffs together. Felubra had the body of a housecat, but also had a strange addition of serpentine body melded into it, like a snake sunk into a cat, Felubra had a venomous bite, could spit venom and constrict objects and people with its rattle tail. At the clima of the invasion Felubra mutated, becoming a strange parody of a chimera, fortunately it was killed, felled by a brave ModiFluff, slain by its own venom. However, it somehow managed to continue on, despite its brain being reduced to a venomous protein sludge, fortunately after the events that transpired in SkettiLand it reportedly collapsed, finally dead.
With the advent of ModiFluffs and their partnerships withe handlers, the FCs were able to rally their efforts and push back the Fluffy intrusions, at this time the Wardens cities have achieved a delicate balance.
This list will be modified as new ModiFluff genotypes are discovered and researched.
-Dr Michael Bendall-
submitted by Twist3e to fluffycommunity [link] [comments]

Data-Dump: When Do Coaches Leave & How Long To Turn Around A Program

Foreword

This is a long-winded post and is full of a bunch of data I assimilated from sources when I was bored. This post is not to pitch my opinion or to convince anybody. It is simply a data dump of information publicly available to stimulate conversation and contribute to the community. I am not attempting to peddle my opinion regardless of the data. I collected it to simply gauge what it says.

This is a two-part post I put into one. This first segment is rather shoddy as I wrote it up in about 25 minutes during the absolute shellacking we took this week against Illinois. If you want to skip the first section I don't blame you. It's haphazardly put together. I will post a TL;DR at the bottom of each section.

Part 1: When Do Universities Dump Coaches?


I will commence my data-dump of seemingly useless information regarding an assortment of teams and when they fire coaches. I started this endeavor once the "Fire Scott Frost" train started picking up some localized steam in the Nebraska fanbase.

Before we begin let me set the criteria for my selection of teams. I am taking a look at an assortment of 30 teams across the varied power landscape that is CFB. I have three groups:

The Greats:

Teams: Winning Percentage
Ohio State .730
Notre Dame .729
Michigan .728
Alabama .728
Oklahoma .725
Texas .704
USC .699
Nebraska .689
Penn State .687
Tennessee .673

Average Joes:

Team: Winning Percentage
North Carolina .559
Navy .555
California .551
Missouri .545
Ole Miss .545
Iowa .540
TCU .539
Oklahoma State .520
Virginia .520


Bottom-Dwellers:
Team: Winning Percentage:
Mississippi State .492
Vanderbilt .490
Kansas .472
Oregon State .471
Iowa State .455
Kansas State .455
Northwestern .452
Tulane .452
Indiana .423
Wake Forest .415


How these teams were chosen: I wanted an array of teams that covered the elite, the middle-class, and those that just are not very good. We have 10 teams per category. The entire collection of teams across CFB were sorted based on their overall winning percentage as seen on Winsipedia. Before I sorted the teams I had already thought to myself I didn't want to use teams like App State, Boise State, Coastal Carolina, et al, that have few wins at the Division 1-FBS level. I decided to add up all teams' total amount of games played and found the median: 1163. For a team to be selected they must have a greater than or equal amount of wins to this number. After that, I simply selected the top-10 teams for the first group. The second group was selected as the middle-ground number of 65, which was Ole Miss. They are the 65th highest winning percentage team in CFB out of 131 teams. I used them as the center and selected an even amount of teams above them and below them that also had a greater than or equal amount of games played as compared to the median figure of 1163. Next, we go to the bottom of the list and work our way up. We get rid of teams like Charlotte, Georgia State, Kent State, et al, who have not played the required total of 1163 games.

A quick note: There are several teams I could have included that were almost at the 1163 mark, or within a handful but I chose not to. Why? Just because. No rhyme or reason really. As an example: Rice has 1135 wins and could have been included in the Bottom-Dwellers but I decided to stick with a requirement of 'more' than the median for a larger game n= sample.

I also had to deal with the fact that season length is not the same for every year. How do you value a year in 1910 when a team may have only played 8 games, but in 2010 they may have played 12? My shoddy solution: judge coaches based on total games and then simply define a "year" as 12 games. The problem with this is the fact the "years of good coaching" may not actually line up with the total amount of years said "good coaching" may have actually been with the team. It still however matches the total amount of games if you simply multiple the "year" value by 12. Bottom line: A "year" is 12 games. Enough said about that.

Next, we have to determine what "good" and "bad" are. I once again went back to Winsipedia and sorted the teams once by winning percentage and picked the top-25 as my barometer. If a team is inside the top-25 we usually consider them to be "good", yes? So why not here. Thanks, Texas A&M, for setting our "good" baseline. If a team has a winning percentage equal to or higher than Texas A&M's (.604) we will consider them to be good.

A quick note: I lowered the bar to .600 instead of their actual .604 mark. Why? Because the team below them is at .599 and .600 makes my brain happy. Don't judge me.

To be an average team they must be above .500, but below .600. To be bad the team must be below .500 with no floor. This gives us the three groupings of:


Good >= .600
Average >= .500 & < .600
Bad < .500

With the pageantries out of the way let's get to the data. What does it tell us? Absolutely nothing we could not have already figured out with 5 seconds of critical thinking.

The short and skinny: Good teams hire good coaches and minimize years with bad coaches. Average teams are average in terms of having good/average/bad coaches. They tend to hold onto "bad" coaches longer, however. Bad teams: Bad. They tend to hold onto bad coaches the longest and have good coaches for fewer amount of years due to varying reasons.
Quick Note: This does not differentiate between firings, retirements, poached coaches, or other varying reasons a coach and school may part ways. This includes any and all forms of parting.

Here's the data!


The teams are sorted by overall winning percentage to give us a quick look at overall power. We can immediately notice that there is only one team that is in the "elite" category of winning percentage (>.600) that has historically held onto bad coaching for more than 3 years and that would be Notre Dame. With that one exception noted, there is not a single elite-level team that would hold onto a coach with a below .500 record for 3 years or longer. In short: Good teams do not put up with bad coaching and that is the reason they are historically good.

On the opposite end of the spectrum, we see the inverse is true. Bad teams almost exclusively hold onto bad coaches for 3 years at a minimum. They "ride or die" with their coaches and thus it costs them more wins over a longer period of time. Hence, an overall worse winning percentage due to having worse coaches for longer. Who would of thunk it?

WAIT A MINUTE! This is taking into account the early 1900s where the game had completely different rules! Coaching was sometimes done by player-coaches, and it wasn't taken as seriously as it was now! This is bad data!

.....you got me. You are right. Let's then look at only the "modern era' of college football and see how that changes the data. To do so, we must first define what the modern era is. The general consensus is that it's undoubtedly after WWII, and most say at around the late '70s, or early '80s. This is when the transition to scholarship limits and the transition to Div 1 and Div 2 (FBS/FCS) took place. Combine this with the fact that television rights took off in the '80s and programs started to actually take the game seriously points to a common answer being the year of 1982 to be the unofficial "Modern Era of College Football". With this in mind, we must account for coaches who coached both during the year 1982, after, and of course, before. I haphazardly decided to let the entire coach's tenure count as long as they coached during the 1982 season. This means coaches like Bear Bryant of Alabama get their entire tenure counted even though his last year was...1982. This happens a few times and it does alter the data slightly but not enough for me to change the implementation. So here is the data if we are only counting coaches who coached during the modern era of college football (and all their games prior) in the years 1982 and after!

The Modern Era Version


Quick Note: This version is sorted by bad years instead of winning percentage.

How does this change our perspective of the data? It really doesn't. We can still see the teams who have never had a good coach are near the bottom right where we expected them to be. Teams at the top who have never had bad coaches are also expected like Alabama, Notre Dame, USC, and even Penn State who had Penn State for an eon; instances like Paterno are also seen at Iowa who is seemingly the "top team" at retaining elite level coaching. In reality, it's because their number of coaches is a grand total of 2 since 1982. Fry followed by Ferentz. No one else. That's it. However, the previous data statements still hold true: Good teams have good for longer while minimizing time with average or bad coaches.

Overall what this data really tells me is that teams must not hire bad coaches; and if they do, do not hold onto them for more than about 3 years. Once again, not a single team with a winning percentage above .600 is seen having a bad coach for much longer than 3 years. This also shows us that parting ways with a coach after 3-4 years is not as uncommon as many fans think it is. I see a lot of speak about "give them time" but in reality that isn't what is done. The teams who hold onto their bad coaching for longer are statistically at the bottom of every list I find. While it begins with hiring good coaches in the first place, it also transitions into minimizing time with the worst.

You can see additional data from BannerSociety that also shows coaches stay 3.9 years on average (Data: 2005-2014). Saturday Down South collected data on SEC coaches since the start of their programs and you can once again see the most dominant conference in college football has had coaches for...~4 years on average.

What really matters is hiring the right coach. I am currently putting together an actual analysis that isn't shoddily put together in 25 minutes about the top tier coaches and how we identify them. Stay turn for that either later tonight, or tomorrow (hopefully).

TL;DR Teams will dump coaches roughly every 4 years. Good teams hold onto good coaches, bad teams hold onto bad coaches. Moral of the story: Hire a good coach to begin with.


Part 2: How Quickly Does A Coach Turn A Program Around?

This post is an actual review of coaching talent and how we can identify it, if at all. It is an addendum to my previous post about how long coaches are at their universities. Once again, we will be looking only at coaches in the "modern era" which we previously defined as 1982; however, we will only be viewing seasons from 1982 and not the coaches' previous seasons like we did last time.

The Set Up:

Here is a list of all coaches and their overall winning records for all Division 1 FBS teams since the 1982 season. If this information is inaccurate I apologize. My source for this data is the absolutely fantastic CollegeFootballData API located here. If you have never used that API I highly recommend it, although it is not perfectly accurate at all times.

Quick Note: This list is sorted by overall winning percentage. We can effectively ignore the individuals at the top of the list who have never coached a game, or have only coached a few and won them. The green "YES" next to their name indicates whether they have coached for at least 48 games or 4 years' worth. With this in mind, we can notice the greatest coach in terms of overall winning percentage that has coached for at least 4 years is....Coach Tom Osborne of Nebraska fame.

Next, we want to determine which coaches we're going to take an in-depth review of. We'll eliminate coaches like Day of Ohio State, Drinkwitz of App. State/Missouri, Riley of Oklahoma, et al because they simply do not have a large dataset to go off of. We're going to be looking at those coaches with a high overall winning percentage and we'll look at some of the top coaches since 1982, some middling coaches, and a few...not so good ones.

The Metrics:

We will compare the coaches to their predecessors and determine whether the increased, decreased, or maintained the status quo of their programs during their runs. We will also keep a note of how quickly we can objectively say they were improving. In other words, how many years until we saw the win total go up!

Up to bat first is good 'ol Urban Meyer! Come on down!

URBAN "HEART ACHE" MEYER

Mr. Meyer got his first start as a head coach with the Bowling Green Falcons. Bowling Green has a total winning percentage of .572 including Meyer's time. Urban took over the head coaching vacancy in 2001 following the work done by Gary Blackney who coached with them from '91-'00. Blackney is an interesting starting point because he took over for Moe Ankney. Mr. Moe had a winning percentage (hereby noted as WP) of .398. Blackney immediately improved upon that by winning 11 and then 10 games in his first two seasons. However, he would finish with a WP of .544. A decent clip, but below Bowling Green's historical figure and far from elite. His hot start would end in shame and he would ultimately quit his duties. Meyer enters for two years and accomplishes 8 and 9 wins for a WP of .739. While not as elite as Blackney's start, it is still really good considering where Blackney left the program and was in an immediate improvement. Winning as many games in just two years as Blackney accomplished in the previous 4 and a half years. This qualifies as an immediate improvement and it did not even take a transition period.
The Fighting Bowling Green Meyers:
Transition: None
Improvement: Yes
Length: 2 Years
WP: .739
Continued: No
Meyer's success would be noted by Utah where he would move on to be the new head coach. Meyer is replacing Ron McBride who coach at Utah for 13 years with a WP of .582. Utah has a historical WP of .593 so McBride's figure is nothing to write home about. Meyer enters and immediately wins 10 and then 12 games in his two years at Utah for a WP of .917. Once again, Meyer strikes.
The Raging Utah Meyers
Transition: None
Improvement: Yes
Length: 2 Years
WP: .917
Continued: No
Note: Meyer's successes at BGSU and Utah were not followed up with success by his successors. The drop was instant and noticeable once he left. This gives credence to the fact that Meyer was responsible.
Meyer is finally on the big-boy radar and gets picked up by Florida. The year is 2002 and Florida is coming off a coaching high that was Spurrier. Stevie posted a WP of .817 and a national championship. He is followed by Ron Zook and his .605 WP. While not terrible, it is an extreme reduction in what UF is used to, so after 3 years he is replaced by Meyer. In his first year, Meyer wins 9 games which are more than Zook managed in his 3-year stint. Meyer follows this up with a national championship in year 2 and finishes his heart-filled career at Florida with two national titles and a WP of .850. This figure is an immediate and drastic improvement upon both Zook and the legendary Spurrier. Also noted is the fact that Florida's historical WP is .633. Meyer would be followed by Will Muschamp who posts a WP of .580 while at Florida. This means his success was his own and not continued by his successor.
Hearty Florida Meyer's
Transition: 1 year
Improvement: Yes
Length: 6 Years
WP: .850
Continued: No

Meyer isn't done yet.. He takes a gap year and then returns to coaching with Ohio State following in the footsteps of Jim Tressel. Tressel posted a WP of .828 and is above their historical WP of .730. (Counting vacated wins). Urban boat races his competition and goes undefeated in his first year and never loses more than 2 games in his 7 year OSU career. He finishes with a WP of .905. An improvement on both Tressel, and the interim Luke Fickell and is well above the OSU historical WP.
Poisonous Ohio State Meyer's
Transition: None
Improvement: Yes
Length: 7 years
WP: .905
Continued: TBD (Only 1-year post-Meyer)
We can plainly see Meyer is elite. No one is really questioning that. However, it does set up a sort of upper limit of achievements. Meyer has turned around every program he has ever been to and done so immediately, or with very little amounts of transition years. Meyer shows that elite coaches will immediately improve a team and start to win games.
---

Additional Elite Coaches

To save you the boredom of having to listen to my spiel about every single coach (as well as save me time) I will now do the same for some more top-tier coaches but only with the metrics we listed. Here they are:


Coach Team Improvement Transition Years Tenure WP Continued
Pete Carroll USC Yes 1 9 .789 No
Jim Tressel Ohio State Yes 1 10 .828 Yes1
Gene Stallings Alabama Yes 1 7 .810 Push
Dabo Swinney Clemson Yes 3 13+ .811 -
Bob Stoops Oklahoma Yes 1 18 .798 Yes
Chris Petersen Boise State Push 0 8 .885 Yes
Nick Saban Alabama Yes 1 14+ .874 -
Kirby Smart Georgia Slight 1 5+ .774 -
Bob Pruett Marshall Yes 0 9 .803 No
Jimmy Johnson Miami Yes 1 5 .852 Yes
Bryan Harsin Boise State Push 0 7+ .788 -
Gary Moeller Michigan No - 5 .733 -
Jimbo Fisher Florida State Yes 0 8 .783 No
LLoyd Carr Michigan Slight 2 13 .753 No
Vince Dooley Georgia Yes 2 25 .715 No
1 - There was continued success after Luke Fickell's interim year
What does this tell us? These are the top-16 coaches in college football history by WP (not including coaches prior to the 1982 season). Every single one of these coaches took 3 transition years or fewer to turn their programs around completely, increase their status, or maintain the status quo. Only one coach, Moeller, is someone I'd consider to not have "improved" his team's situation. Smart and Carr slightly improved their already good teams. Petersen and Harsin of Boise State I don't believe really improved their programs - they were already good and remained good. Half of the coaches left the program and they got worse immediately following. Short point: Elite coaches do not need more than a few years to show you why they are elite. The turn-around will be near immediate and it will be grand as all these coaches have a WP of .715 or higher with their respective programs. All these coaches also have a career WP of .750 or higher.

Mid-Tier Coaches


How about non-elite coaches? Let's take a look at some above-average, or average coaches and see how they fare.


Coach Team Improvement Transition Years Tenure WP Continued
Bo Pelini Nebraska Yes 0 8 .713 No
Tom Herman Texas Yes 1 3+ .625 -
Les Miles LSU No - 12 .770 -
Paul Chryst Wisconsin Yes 0 5+ .761 -
Mike Gundy Oklahoma State Yes 3 15+ .673 -
Bill Snyder Kansas State Yes 1 27 .647 No / Push2
Mark Dantonio Michigan State Yes 0 13 .667 N/A3
Dan Mullen Mississippi State Yes 1 8 .600 No
Dan Mullen Florida Yes 0 2+ .818 -
Ken Niumatalolo Navy Slight 0 14+ .612 -
Luke Fickell Cincinnati Yes 1 3+ .723 -
Matt Campbell Iowa State Yes 1 4+ .543 -
Matt Campbell Toledo Yes 0 3 .700 No
Art Briles Houston Yes 1.5 5 .548 Yes
Art Briles Baylor Yes 2 8 .637 N/A4
Jeff Brohm Purdue Yes 0 3+ .452 -
Jeff Brohm Western Kentucky Yes 1 3 .750 No
Paul Johnson Georgia Southern Yes 0 5 .861 No
Paul Johnson Navy Yes 1 6 .608 Push
Paul Johnson Georgia Tech Yes 0-15 11 .573 No
Scott Frost Nebraska No - 3+ .375 -
Scott Frost UCF No6 1 2 .684 Yes
2 - Snyder had two separate stints at Kansas State. Opinions for 1st and 2nd stint listed.
3 - Dantonio and Michigan State only separated ways in 2019.
4 - Art Briles scandal at Baylor. An odd situation to judge; however, I'd say no. It was reinvented by Rhule.
5 - Subjective. I do believe he transitioned smoothly without a gap year.
6 - Subjective. UCF had a coach retire mid-season and they went 0-12 to make the turn-around look more impressive.
So it seems the truth is still the same for mid-tier coaches. If they will turn around teams then they will do so within 2-3 years. None of the coaches I selected took more than 3 years to turn their programs around. These coaches were chosen at random going down my list. There was no rhyme or reason to choosing their names outside of a few selects being chosen simply based on name popularity.
If we combine this information with the information we already know being that teams part ways with their coaches on average every 4 years or so it makes sense; because teams will see improvement or not within those 4 years and be able to decide if a coach is worth keeping or ditching.

TL;DR It takes 3 years or less (usually less) to turn a program around. If success is not seen within 3 years it usually will not happen. There are of course outliers but I found NONE in the random couple dozen coaches I chose to look at.

---
This post is NOT to call for a firing of Head Coach Scott Frost. It is simply a data-dump of my boring weekend to stimulate conversation in this sub. I do have an opinion on whether Frost is the answer but this information was simply gathered to see what it showed - not to prove a point. If there are any data errors please let me know. There probably is as both the API I use to scrape information from is sometimes inaccurate and I am only one man and make errors. I also know there are already some errors, especially in the coaching section as the API did NOT pull all head coaches in the early years. Alas, I didn't fix it as the resulting data change was negligible for a simple Reddit post.

---

If you would like to analyze the data yourself I have uploaded both the historical and 1982+ versions to Google Drive for your viewing and analysis. They are available here. You are free to download, utilize, and change it. Keep in mind these were made using Microsoft Excel and use formulas and interactions specific to Excel and it will more than likely NOT look accurate in Google Sheets. Specifically nestled functions such as the VLookup nestled Matrix function I used for the coaching section. You have been advised.
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batting average formula problems video

Aptitude Made Easy - Problems on Average -1, Basics and ... Batting Average  Baseball Explained - YouTube Average Introduction Class  Basic Concepts  Problems ... BATTING & BOWLING AVERAGE-9AVERAGE Concepts and Tricks ...

Compute the value of batting average and assign the value in variable BatAvg. // compute the batting average for the player and assign // the result in variable BatAvg. Set BatAvg = (Hits / AtBats) Lastly, the computed value is displayed using Write statement. // display the result. Write "The batting average of the player is: " + BatAvg This is the aptitude questions and answers section on "Average" with explanation for various interview, competitive examination and entrance test. Solved examples with detailed answer description, explanation are given and it would be easy to understand. When figuring or calculating batting average of a baseball player, just use the following formula: Batting average = (Number of hits)/(Number of official at bats) As you can see, the batting average is just a ratio of the "number of times the player hit the ball" to "at bats" ... If you can solve these problems with no help, you must be a genius! Also called the mean average. Sums of data divided by the number of items in the data will give the mean average. The mean average is used quite regularly to determine final math marks over a term or semester. Averages are often used in sports: batting averages which means number of hits to number of times at bat. Call batting average “BA”; call hits “H”; and call at bats “B”. • Figure out Josie’s batting average. Using Formulas To Solve Pr You try it! A baseball player’s batting average is the number of hits the player gets divided by the number of times she was at bat. Josie was at bat 12 times and got 3 hits. • Write a formula for ... Batting Average Worksheet Answers - dev.destinystatus.com 11. Explain that a batting average is calculated by first counting the number of times that a batter reaches base by getting a hit. This number of hits is then divided by the number of times that he gets a chance to hit (an “At Bat”). 12. Write down the formula for batting average on ... Type 2: How to solve Problems on average marks and scores. Question 1: The batting average of Sachin in 15 innings is 55. The difference between the runs of his best and worst innings is 65. Excluding the best and the worst innings the average of 13 innings played by Sachin is 50. Calculating Batting Average in Baseball. Baseball is full of math, and one of the most common numbers in baseball is batting average. It's a great example of the division learned in 4th grade being used in the real world. See if your young slugger can figure it out and complete this fun worksheet. Batter up! The formula is: Hits / At Bats = Batting Avg. That's all there is to it. For example, if Justin Upton gets 155 hits in a season and has 554 at bats, his batting average would be 155/554, or .280. The batting average is usually represented not as a percentage (i.e. 28.0%), but instead as a decimal number with three places after the decimal. Let's use the formula to see which one has the best batting average. Homerun Harry had 9 hits out of 49 at bats. We can plug these numbers into the formula to calculate his batting average. A batting average is always rounded to three decimal places. Slugger Sam had 8 hits out of 38 at bats.

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Aptitude Made Easy - Problems on Average -1, Basics and ...

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batting average formula problems

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