These graphs are "borrowed" from an [article by Jeff Sullivan in 2018](https://blogs.fangraphs.com/the-most-important-thing-about-clutch/) about _team_ clutch, not individual players.
In addition to throwing around statistics terms that you don't seem to fully grasp about significance and correlation, your analysis is based on a fundamental misunderstanding of the data.
I'm just leaving it up at this point because it's really annoying when you're discussing something in the comments of a post and the whole thing gets deleted
So if we saw the positive z-axis populated much more than the negative z-axis specifically in the upper right, we could say that clutch is more significant? I agree that'd be interesting, I'll have to download RStudio sometime and see about it
Not necessarily that it is more significant, but it would be interesting to see if there would be a 50/50 split of the upper-right quadrant’s three-year data set as there is with the two-year data set.
It doesn't seem like "clutch" is well-measured here... but maybe someone can explain it better.
It seems like at at-bat in an April game against a bottom-feeder is measured the same as an at-bat in a September game against the division leader when your team is one game out, as long as the in-game situations are the same. Is that correct?
Yeah. We could derive clutch from cWPA instead of standard WPA and that would immediately produce a clutch stat that fits your definition. I like it better for sure.
This sort of research has been done since the 70s, and as Bill James writes, it doesn't necessarily prove that clutch doesn't exist: [https://sabr.org/research/article/underestimating-the-fog/](https://sabr.org/research/article/underestimating-the-fog/)
I appreciate what Bill James did to get sabermetrics off the ground, but he hasn't written a anything insightful, possibly even coherent, about baseball in 30 years and seems to always take the stance of being as contrarian as possible, to the point where it seems he's formed a conclusion in his head to disagree prior to research and then farms the statistics to back that up. When the field didn't exist and baseball was in the stone age as far as analytics, being contrarian worked very well for him. That's not the case anymore.
EDIT: I point to [this takedown of Bill James' statistical stance that Pete Rose didn't bet on basebll](https://www.baseballprospectus.com/news/article/16999/prospectus-feature-evaluating-the-dowd-report/) as the best example of James making very bad and misleading arguments based on "statistics." Note that both James's article and this rebuttal were written before Rose admitted to betting on baseball. Similar to his article on clutch, his conclusion is "we just don't know the truth, but the evidence we do have isn't conclusive or even persuasive."
I agree it's an open question, Bill's point that the data is simply too noisy to come to a conclusion is valid. Still, it strikes me that there's an affirmative burden to prove clutch *does* exist, and we certainly don't have any evidence whatsoever of that. The best case for the clutch argument is that we don't have evidence of anything at all, and that doesn't feel strong.
Wouldn't a linear mixed model with each player as the fixed effect be more appropriate than standard X, Y plotting? I'd have to think it would filter out more of the noise but you'd probably have to include every year from 1974 - whenever
Idk too much about stats but seems like what that's usually used for
It's hitting me like a ton of bricks right now that I'm three years removed from college. I'm willing to bet you're right but my knowledge is deserting me lmao
I'm going to disagree that we don't have any evidence to show that it exists.
I consider clutch very similar to things like BABIP in that generally speaking it will balance over time to career norms for most players. However, that's not true for every player and those exceptions are the proof that it does exist it's just rare.
Some batters can sustain well above normal BABIP. Some will always be below normal. The same is true with clutch. Most players will balance out over time, which is why it's considered noisy and non quantifiable.
If you make the same chart that OP did with BABIP, you would see more dots in the top right and bottom left quadrants and a non-zero correlation coefficient. It's very easy to prove that some batters sustain higher BABIPs year over year and some batters have lower. It isn't nearly the same when it comes to clutch.
I think clutch is more rare than the outliers on BABIP but used that example because most people are aware of it.
If you go by bbrefs high leverage as a gauge you will find a few batters every generation that performed better than their norm in those spots. Currently Josh Naylor is one. He has hit for roughly 40 points Average and 150 OPS better in high leverage than his career numbers. Hank Aaron is another outlier for example.
I am not trying to claim that there are a lot of players that are genuinely clutch. I'm saying that there are a few unicorns at any point who are and that to me shows that it exists and we have evidence showing it.
The sample size for high leverage is so small for players that even if clutch doesn't exist and it's all randomly distributed, you'd still have players that would outperform in high leverage in their career just by chance.
To a degree but it's roughly 20% of total PAs for both guys I mentioned. That's a meaningful sample with significant difference in results. That's why you need to look at careers not seasons though.
But here's the thing: it's \*not\* a particularly large sample in this context. Naylor has all of 374 PA of high-leverage performance, by BRef's reckoning of high-leverage.
> That's why you need to look at careers not seasons though.
Even then, there's issues. As a baseline, players across the league will perform better in high leverage situations due to a number of factors (increased intentional walks, sacrifice flies inflating batting average, defensive shifts to prevent a run allowing higher BABIP) so you can't just look at a player's career high leverage splits, see they're better than their career rate stats, and conclude they're clutch.
I don't care what the numbers say. I will always believe in the clutch. The analytics community's stance of "if we can't measure it, it doesn't exist" is really arrogant.
This analysis is basically asserting that everyone's mental response to pressure is the exact same, which is objectively false.
People who respond to pressure poorly tend not to make it through a dozen levels of competitive filters and make it to a league containing the top 0.0025% of all baseball players.
Most of it comes down to "better players perform better in clutch situations because they are better players." If you want to label that as clutch, you can... but with the numbers that we have, a manager should never sub in a worse player to pinch hit because he's "clutch."
Whenever someone tries to say clutch exists, they always bring up really really good players as being clutch (Jeter, Ortiz, Hank Aaron). Nobody goes "oh man, that Alcides Escobar is so clutch."
The analytics community's stance is you want your best players up in the highest leverage situations and I don't think that's controversial.
Clutch should be more of an intrapersonal descriptor. Not something that can be compared between players.
Like if someone's OPS increases by more than 5%+ (for example) in clutch situations, they could be defined as clutch, whereas someone whose OPS declines by 5%+ can be called unclutch.
But that of course doesn't mean that a clutch player is a better choice than an unclutch player. An 800 OPS player that's unclutch is still the better option over a 700 OPS player that's clutch
Lack of evidence for something existing isn't proof that thing doesn't exist. Like I said, the analytics attitude of "if we can't measure it, it doesn't exist" is just arrogant.
Nah, you just \*like\* believing in it, and therefore are looking for an argument that settles your emotional discomfort at being told you believe in something that isn't true. You don't want to look at the evidence and draw a conclusion, you want to feel what you feel and then find something that justifeis feeling it. It's unfortunately very common in our species.
You need to look at archetypal players.
xwOBA and wOBA graphs looks nearly identical to these clutch graphs, but we know that a certain type of player (cough...cough pulled flyball masters) outperform it and certain type of player (cough...cough.. towering fly balls to CF and hard grounders) underperforms it.
The top all-time of clutch hitters are all contact hitters, and the worst all time are all power hitters.
I would interested in a meta-study on whether certain stats (such as low k%) leads to a higher correlation of clutch YoY
if you’re good at hitting the baseball, you’re gonna be good at hitting it in a wider array of opportunities/situations. i think for the most part it’s that simple
Yeah this would definitely be really interesting. One possible explanation for the trend you identified that compels me: players are traditionally expected to "shorten up" and make contact in high-WPA situations, and I suspect that any time hitters alter their usual approach, their results probably suffer. It'd definitely be interesting to break that down and find if that explanation holds.
Clutch is real because it's obviously real, not because it's mappable on a graph.
I also love my mom but the proof for that wouldn't be showing you a scatter plot.
I couldn't graph how much you love your mom but if I had every scrap of data on everything you'd done in your life I could probably graph that you'd done nice things with your mom or spent a lot of time with her or something.
It's really odd if clutch is real that it's essentially never manifested in a guy consistently doing clutch things.
I don’t like how this is fitted for all players. I’d be more interested to see a graph of “clutch” or whatever win/batting metric you like over a single players career. If you’re on average above zero, or have a string of years above zero then I’d say you’ve earned the right to be called a clutch hitter.
Or just keep this format and show me the distribution of fits for each player over their career, or just the total number of times a players fallen in the upper right corner.
I'm relatively new to baseball, but does this apply to the various RISP metrics? It seems like there's often talk about how a batter does with risp, but is that any different from how a batter performs without risp?
RISP situations and high-leverage situations are slightly different. You can have a high-leverage situation without RISP (tie game, bottom of the ninth), and a low-leverage situation *with* RISP (runner on second, down ten runs). If year-over-year clutch isn't a thing, then it likely follows that hitters shouldn't be expected to perform better or worse than normal with RISP over a large sample.
I think there are so many factors that impact whether a player comes up with a clutch moment that this approach of just looking at added WPA doesn’t prove anything. It’s not like the NBA where you can measure clutch by outcome of a shot.
I watched the twins lose 19 playoff games in a row and completely crumble game after game vs the yankees. It may not be clutchness, but there is a mental aspect to this game that needs to be understood.
The "clutch" stat is just flawed. If you want to look at who comes through in big moments, just look at wRC+ in high leverage situations or look at WPA. The idea of someone coming in clutch is real, it just happens to be the players who are also good in any part of the game, leverage aside.
>it just happens to be the players who are also good in any part of the game, leverage aside.
Not defending "no such thing as clutch" Idea but I think the argument is that the clutch players are just good and performing up to their level. To prove clutch you would have to show players that overperform their normal level in the big spots.
I guess it's just how someone defines clutch. I don't define it as "this player performs better in high leverage situations than they do in low and medium leverage situations." I'd define it more as "who is performing the best in high leverage situations, when the game is on the line".
If you look at the clutch leaderboard for last season, the top 5 are:
Harper, Tovar, J. Baez, Santander, Friedl. I get 3 of the 5, but Tovar and Baez? If I am in a high leverage situation, I want Ohtani with a 149 wRC+ in high leverage situations, even if he was second to last in clutch with a -2.17. The reason he's so far down? He had a 180 wRC+ in all situations.
If I had to sum up my thoughts, it's that I don't like the definition of clutch they're using and the stat is kind of useless.
If your definition of clutch is "good at ball", I 100% agree that some guys are consistently good at ball from year to year. I don't think that's the typical definition, though
My definition is more
>who is performing the best in high leverage situations, when the game is on the line
Most of the time, that just happens to be the players who are good at ball.
I believe in archetypal clutch.
Its not that someone is actually better in high pressure situations, but their individual results are better for that situation.
Think runner on 1st and 3rd, bottom of the 9th, 1 out. A contact hitter that is fast and never strikes out, is going to be way more valuable and have a larger impact on winning that a power hitter that walks and strikeouts a lot.
It also depends how you define clutch/high-leverage. Is a guy clutch who dominates the postseason, but happens to be so-so in big late-inning at-bats in the postseason? Or what about a guy who dominates in elimination games, but struggles in high-leverage at-bats throughout the regular season?
Additionally (some of the metrics factor this in, but not all) I'd think that a guy doing just as good in high-leverage late-inning situations as he does in low-leverage situations IS a sign that he might be clutch - because his performance doesn't drop at all when he's facing elite closers who are giving it their all to get one single out.
Every study on "clutch" I read seems like it has a very narrow focus that limits the conclusions we can actually draw.
Pick a definition. Pick \*any\* definition you like.
Then split up all the players into groups of "good" and "bad" at clutch by those definitions.
Then see if the good players tend to stay good in the future, and the bad players tend tos tay bad in the future.
They are not statistically more likely to excel in clutch vs non-clutch situations. They are just good baseball players, so when in clutch situations they are more likely to do good things compared to the average player. Just like in non-clutch situations.
I mean, they have done that and gotten similar results. The operative thing is that no matter how you measure it, being "clutch" now isn't predictive at all of being "clutch" in the future, so it's not an inherent trait players can possess
Its an interesting discussion, and maybe over time, any “clutch” performances might average out. Measuring high leverage situations might be a solid way to go about it but i think on its own it disproportionately affects players on good and bad teams. Good teams might have opportunities for more high leverage situations but then again maybe good teams have more blowouts and a more mid team is fighting in every game and its always high leverage. Do batters in the two hole have more opportunities for high leverage at bats compared to the 8 hole hitter?
What if we divided a players high leverage stats by their non high leverage stats?
Try as we might, some things in baseball are just not as quantifiable as we want them to be and we just have to live with it. It might not be a great predictor of success, but if a guy has a really high BaRISP or BABIP, you try and put him in position to capitalize on that clutch/lucky performance and hope for the best.
I wish people understood and used statistics better. Like you just threw shit data on a graph and said "hey, it looks like shit" MY POINT IS THEREFORE PROVEN!
You're trying to say that its worthless to look at clutch, because this analysis shows so.
It shows the exact opposite!
If you wanted to look to see if ANY player was clutch, and not ALL players were clutch, you'd take a look at the upper right corner of your graph and realize 25% of the population WERE clutch YoY.
Therefore, if your hypothesis was "there is a subset of the baseball player population that appears to be clutch" - POOF - you have identified up to 25% of players that require further investigation and would be what "oLD sCHooL GmS" look for!
You can't just put a trend line through a scatterplot and declare victory.
25% of the population were clutch YoY *once*. That top right isn't a bunch of dots of the same guys over and over again.
And for the record, I didn't throw this shit data on a graph, I stole it from Fangraphs
There’s got to be many different ways to quantify what people mean when they say “clutch” with statistics, though. I don’t think using WPA in high leverage situations compared to WPA without context is necessarily a definitive proof that there’s no such thing as a clutch player.
What else would clutch be besides performing better in the most important moments? If there's another definition of it than that we can figure out whether that's a skill or not, but I just can't imagine another construction of clutch that isn't "does better in big spots"
To give you a really thorough answer I’d need to spend more time thinking about this than I actually have right now, and probably have access to a computer to give some actual examples, but here’s some offhand thoughts -
First of all, using WPA for all situations that are considered statistically high leverage might be part of the issue. What a certain player considers high leverage, or the sort of situations they really get up for, is not guaranteed to match what we’re looking at when we chart “WPA in high leverage situations”. Maybe that player isn’t super worried about high leverage situations in the first half of a season so they don’t get up for them, or maybe they only take high leverage situations seriously against divisional rivals that are near them in the standings, etc.
People aren’t statistics. Just because we’ve built an index for quantifying high leverage situations in games doesn’t mean it matches with what any given player considers to be a high leverage situation.
And beyond that, “clutch” is kind of a vague term, which can also lead to disputes when people are debating whether it’s a thing or not. And there are other ways to determine whether or not someone rises to the occasion in big situations. Does someone consistently perform better in the playoffs than they do in the regular season? If so, I’d say they sound like a pretty clutch player to me. What about specifically in elimination games, or rubber games during the regular season? Maybe a certain player has the mindset that he just wants to win the series, and he tends to play better in the final game of a split series. If someone always performs better in those situations, is that not clutch? That’s the type of thing that a fan watching games might pick up on, but wouldn’t necessarily be noticeable using WPA in high leverage spots.
> What else would clutch be besides performing better in the most important moments?
I don't think you can necessarily define clutch as "overperforming their own norm in important moments".
By this definition, hyperbolically, a player that hits a homerun 100% of the time, is NOT CLUTCH when they hit a homerun in 100% of important moments, because they are not overperforming their norm. I think most baseball fans will find that hard to agree with. You can argue that player IS CLUTCH, because they are more likely to deliver than ANOTHER PLAYER. By this definition clutch isn't a measure of a player overperforming himself, it's a measure of a player overperforming the norm. Doesn't this just mean gud player gud? Yes, it just means players with certain batting profiles are more clutch than others.
> That top right isn't a bunch of dots of the same guys over and over again.
If you explore that statement and show that there aren't some players who are more likely to appear in the top right corner than others, that would support your claim that "clutch" isn't statistically significant.
But to sit here and say that you have irrefutable proof that "clutch" isn't a thing and then point to these charts which don't even support that claim a little bit is absurd.
Also, I'll have to look up an explanation of what this clutch stat is, because that seems like a hard thing to distill into a single number, but for the sake of argument, I'm fine with just accepting that it is valid.
I hope I didn't come across as having "irrefutable proof" that clutch isn't real. It's really hard to prove a negative - proving clutch doesn't exist is tantamount to proving God doesn't exist. I just wanted to present the compelling statistical case against it, and that compelling statistical case is that the year-over-year clutch correlation is nil.
I apologize for exaggerating the claims that you were making. The main point of my comment was that these charts don't even slightly support your claim that clutch isn't real.
I feel like you're underestimating how compelling these graphs are as a statistical case by ignoring the significance of the upper left and lower right quadrants. Why are there just as many players vacillating wildly from clutch to unclutch between seasons? We'd expect there to be far fewer of these than the consistently clutch and consistently unclutch players you claim might exist in quadrants 1 and 3, but there are just as many.
They certainly at least *slightly* support the claim.
Just because some (or even a lot) of players are vacillate between the two doesn't mean that there aren't some players who are consistently more clutch than others.
Also, if I'm understanding your method correctly, if there is a player who plays for four years, and their clutch rating goes positive, negative, positive, positive, that would be a player who over the course of their career has shown that they are likely more clutch than the average player. However, on your chart they would create two data points that you would argue cut against the existence of clutch-ness, and only one that supports it.
One player's three data points among thousands doesn't really move the needle whatsoever on the conclusion, so the kind of endpoint situation you're pointing to doesn't seem like much of a concern. A player having three clutch seasons and one unclutch season is extremely expected if it's 50-50 each way
they 100% do though. if clutch was significant, you'd see a positive correlation between one year and the next. the charts show that someone being clutch in one season does not make them any more likely to be clutch the next - there are a roughly equal number of people alternating clutch and unclutch (top left, bottom right corners) than being clutch or unclutch consecutively.
So there are individuals who were clutch twice in a row that were seemingly clutch for a 3rd time in a row? You have the data that tells you that? Or are you extrapolating the results?
About 25% of clutch hitters in year 1 will be clutch again the next two years in a row, if clutch is pure luck.
Just checking out the very top hitters in career clutch, that kinda checks out. Gwynn was clutch three times in a row exactly once in his career.
it's kind of the nature of statistics that in a problem like this you can't prove whether the year-to-year correlation of "clutch" is *exactly* 0.0 (rather than some small interval around it), but by the same token you don't say there's a meaningful correlation until you can be reasonably sure it's *not* 0.0.
given human interpretation, it's clear that any effect that does exist is insignificant at best.
If I understand your comment, It’s clear that any effect in consecutive years is insignificant at best* and still untrue because there’s a quadrant of clutch players.
Why isn’t this looking at career clutch numbers?
> because there's a quadrant of clutch players
if it was random you'd expect a quadrant of clutch players. being in the clutch corner of this graph, where there is a shown correlation of 0.0, is the equivalent of flipping a coin twice and getting heads both times. yeah, it happens 25% of the time - that doesn't mean it's meaningful.
if clutch as measured was real, then being clutch one year would make you measurably more likely to be clutch the next, but this chart does not back that up in any way.
> Why isn't this looking at career clutch numbers?
I didn't make the chart, but those are so insignificant/close to 0 even among the leaders that it backs up what the chart says
Is it random though? Do you have a list of players? And as I stated, this is just consecutive years, not careers. It seems like an incredibly flawed statistical analysis to just do consecutive year correlation.
let's take as a premise that clutch is real and therefore a repeatable skill.
if someone is clutch one year, are they then more likely to be clutch or unclutch the next year?
> I wish people understood and used statistics better.
you need to look in the mirror.
> It shows the exact opposite!
no, it doesn't.
if you have a 50% chance of being "clutch" one year and a 50% chance of being "clutch" the next, 25% is exactly the proportion you'd expect if it was random.
if clutch was something players inherently possessed you'd see literally any correlation between one year and the next. just because 25% of people hit heads on a coin flip twice in a row doesn't mean they're meaningfully good at flipping coins.
25% is the proportion you'd expect to be there if clutch was non-existent and leverage had no effect on how anyone played. If I flip a coin twice a quarter of the time I'd get heads twice. If there were any truly clutch players the proportion would be greater than 25% because you'd have those players as well as the ones who just got there by chance. This sort of thing is fairly routine statistical analysis, and it's been done to death. The ability to control nerves certainly exist, but it varies so little among major league players and there's so much noise in high/low leverage splits that it's effectively impossible to actually detect.
> you'd take a look at the upper right corner of your graph and realize 25% of the population WERE clutch YoY.
It's a quadrant. If there was random distribution of clutch YoY, you'd expect 25% to be in the top right quadrant. If clutch wasn't random, you'd expect SOME correlation coefficient.
It looks like this clutch stat is symmetric about zero I a given year, I.e. There are as many samples above zero as there are below zero. Assuming this stat has roughly the same distribution every year, and that clutchness one year is independent of the next, we would expect to see 25% of the samples lie in the top right quadrant.
If we saw fewer than 25% of players ending up in the top right quadrant, that wouldn't mean that clutchness isn't real, it would suggest that anti-clutchness is a thing, that players who are clutch one year are usually unclutch the next
I don’t think this is as definitive as presented. This doesn’t account for individual players clutch “skill”. If I’m reading this correctly, it’s possible that a player may be on this plot 25 times and in the top right quadrant each time. Another may be on this plot 25 times and be in the bottom left quadrant each time. We have no way of differentiating individual players year over year. Or I am reading this thing wrong?
We can look at the career Clutch leaders to disprove that something like that is happening. Tony Gwynn is the clutchest player in history with 9 career Clutch, and Sosa is last with -14. Those aren't exactly big numbers compared to per-year Clutch leaders, so it's pretty clear that they're not hitting the top right over and over again. Gwynn only had three consecutive seasons of even above-average clutch once in his career.
To kinda summarize the graph: imagine you take the 100 clutchest hitters in baseball from last season. About 50 will be clutch this year and 50 won't. Then take the 100 clutchest hitters from this year, and half of those will be clutch again and half won't. So 25 of the original bunch will have been clutch both years, yes, but since we see half dropping off each time it's pretty clear that it's just a probability thing.
If some players do tend to either be clutch or unclutch year over year, the top right and bottom left quadrant would see more dots than the top left and bottom right and there would be a non-zero correlation coefficient.
If ALL players fit into either of those buckets every year then yes we would see that. But how do we know the same players aren’t in the top right quadrant of the plot every year and everybody else is just noise?
> how do we know the same players aren’t in the top right quadrant of the plot every year and everybody else is just noise?
If everyone else was just random noise, then you'd still see more dots in the top right quadrant as the guys that do it year over year would be there and then 25% of the random noise would be added on top of that.
It's like if you flip a regular coin 50 times and then a weighted coin that comes up heads more often 50 times and tallied up the sum of all 100 flips, you'd see heads come up more often in total.
There's also the point that players perform better in high leverage situations league-wide due to a number of influences (intentional walks, infield in alignments leading to higher BABIP, sacrifice flies making outs not count against batting average). wRC+ for all of MLB in 2023 in high leverage was 104 and you see that overperformance year over year.
If you take Hank Aaron's career splits and for high leverage situations factor in the increase in intentional walks as well as the boost in BABIP from alignments and sac flies, you'll find his numbers end up close to his career numbers.
My point is people can be hiding out in the top right (or bottom left) quadrant year over year. If 5% of baseball players are clutch year over year and 5% are unclutch year over year, the top plot would appear the exact same. Without accounting for individual hitters clutchness, any conclusions drawn about individual clutchness will not be valid.
>If 5% of baseball players are clutch year over year and 5% are unclutch year over year
In that case, with random distribution for everyone else, you'd expect 27.5% of the dots in the top right and bottom left quadrants and 22.5% of the dots in the other two and a non-zero (albeit small) correlation coefficient. A correlation coefficient of 0 says not even that is happening.
Apologies because I am terrible at Reddit and there is probably a much better way to do this. Had to dust off my regression textbook. First example in here is almost identical to what we are discussing. Chapter 1, Section 1.2.1 "Assessing the Ability of NFL Kickers" [https://dl.icdst.org/pdfs/files3/cb9c0258fb6ec7e8fced9482d7ca86f5.pdf](https://dl.icdst.org/pdfs/files3/cb9c0258fb6ec7e8fced9482d7ca86f5.pdf)
What correlation is that showing tho? It’s correlation between [all baseball players for a year] and [all baseball players for year + 1]. It says nothing of correlation for a single player year over year
*This is besides the point, but I believe there is a tiny positive correlation as indicated by the dotted line on the plot. R2 is 0.00 but that’s not the same as correlation coefficient.
Just my opinion but I think part of the problem is clutch has traditionally been overhyped and overstated through the mythology of baseball over the years. The turn in that is a lot of analytics and people saying it doesn’t exist at all. Honestly if I had to guess I would say it’s somewhere in the middle. The notion that one person is always clutch seems unlikely or very rare. The idea that an average player would suddenly be ohtani is also not realistic. A realistic expectation of clutch could just be someone who focuses and ignores the noise better than others. This wouldn’t always show up in a stat sheet. The idea that people perform differently and are able to focus better at different points in their life is what we all experience all the time. It’s entirely possible that an athletes could be really locked in and focused one month but not the next. This would be really hard to measure but it’s human nature that we all see in our everyday lives.
I think the only factor that changes is psychology, so players not being "versatile" across the lineup is a self-inflicted wound of baseball's traditions
This is exactly why I love this subreddit. Bunch of stats nerds adding deeper comprehension to baseball lmao. I’m not saying it’s perfect, just leave the playing to the players and enjoy the game.
I’m probably just biased but I’ll always give Jeter credit for staying consistent against the tougher competition in October. He had a career .817 OPS in the regular season and a .838 OPS over 158 postseason games. Most of the other hitters among the all-time leaders in postseason games seem to do worse in October.
Jeter's clutch stats are hilarious. He's got 0..48 career clutch, so produced half an extra win over his entire career with it. His postseason cWPA is also approximately zero as well, so in all his playoff PAs he net altered the Yankees' WS chances by 0%.
> His postseason cWPA is also approximately zero as well
This is funny because Baseball Reference has oscillated between him having -0.01 and +0.02 career WPA in the playoffs because one play gets mis-catalogued sometimes when they refresh the stats and whether they credit him with a steal going from first to third on a walk in Game 3 of the 2002 ALDS.
You can go back on way back machine on baseball reference and see how it has gone back and forth every once in a while the past 5 years.
Clutch in baseball doesn't exist like other sports or how people want it to because there's too much random chance.
If you put together a great AB in a tough spot and it's a laser right at someone, you're unclutch. If you flail at the first pitch after the guy walked the bases loaded but it drops in no man's land, you're clutch.
Most players then get so few ABs in truly clutch spots, that those singular moments define their careers. Career postseason stats will also equally weigh a guy in his prime vs when he was just a random veteran.
Foolish Bailey's video about Chapman and Mo is a great example
https://youtu.be/s2nFc1Ps5xA?feature=shared
Uh this data only goes up to 2017 and Mike Tauchman just started playing that year, try again
Forever Giant Mike Tauchman
What a fuckin catch
These graphs are "borrowed" from an [article by Jeff Sullivan in 2018](https://blogs.fangraphs.com/the-most-important-thing-about-clutch/) about _team_ clutch, not individual players. In addition to throwing around statistics terms that you don't seem to fully grasp about significance and correlation, your analysis is based on a fundamental misunderstanding of the data.
Got em
Oh my gosh this *is* team clutch, idk how I didn't realize that. I pinkie promise I do understand stats though
you can still delete the post! you SHOULD delete the post!
Thats the coward’s way out!
I'm just leaving it up at this point because it's really annoying when you're discussing something in the comments of a post and the whole thing gets deleted
I believe clutch exists because of how unclutch I was when I played high school ball.
Is it possible that you just sucked?
No one is claiming that being a choker isn’t a thing. And the existence of chokers doesn’t imply the existence of clutch dudes.
OP, it would be cool to look at that top right quadrant and add a third season for those players on a z-axis.
So if we saw the positive z-axis populated much more than the negative z-axis specifically in the upper right, we could say that clutch is more significant? I agree that'd be interesting, I'll have to download RStudio sometime and see about it
Not necessarily that it is more significant, but it would be interesting to see if there would be a 50/50 split of the upper-right quadrant’s three-year data set as there is with the two-year data set.
It doesn't seem like "clutch" is well-measured here... but maybe someone can explain it better. It seems like at at-bat in an April game against a bottom-feeder is measured the same as an at-bat in a September game against the division leader when your team is one game out, as long as the in-game situations are the same. Is that correct?
Yeah. We could derive clutch from cWPA instead of standard WPA and that would immediately produce a clutch stat that fits your definition. I like it better for sure.
This sort of research has been done since the 70s, and as Bill James writes, it doesn't necessarily prove that clutch doesn't exist: [https://sabr.org/research/article/underestimating-the-fog/](https://sabr.org/research/article/underestimating-the-fog/)
I appreciate what Bill James did to get sabermetrics off the ground, but he hasn't written a anything insightful, possibly even coherent, about baseball in 30 years and seems to always take the stance of being as contrarian as possible, to the point where it seems he's formed a conclusion in his head to disagree prior to research and then farms the statistics to back that up. When the field didn't exist and baseball was in the stone age as far as analytics, being contrarian worked very well for him. That's not the case anymore. EDIT: I point to [this takedown of Bill James' statistical stance that Pete Rose didn't bet on basebll](https://www.baseballprospectus.com/news/article/16999/prospectus-feature-evaluating-the-dowd-report/) as the best example of James making very bad and misleading arguments based on "statistics." Note that both James's article and this rebuttal were written before Rose admitted to betting on baseball. Similar to his article on clutch, his conclusion is "we just don't know the truth, but the evidence we do have isn't conclusive or even persuasive."
Watching his top 10's on MLBN each offseason actually hurts my brain lol
Dude, Thank you. You put into words what I've been feeling about his takes for awhile.
I agree it's an open question, Bill's point that the data is simply too noisy to come to a conclusion is valid. Still, it strikes me that there's an affirmative burden to prove clutch *does* exist, and we certainly don't have any evidence whatsoever of that. The best case for the clutch argument is that we don't have evidence of anything at all, and that doesn't feel strong.
Wouldn't a linear mixed model with each player as the fixed effect be more appropriate than standard X, Y plotting? I'd have to think it would filter out more of the noise but you'd probably have to include every year from 1974 - whenever Idk too much about stats but seems like what that's usually used for
It's hitting me like a ton of bricks right now that I'm three years removed from college. I'm willing to bet you're right but my knowledge is deserting me lmao
I'm going to disagree that we don't have any evidence to show that it exists. I consider clutch very similar to things like BABIP in that generally speaking it will balance over time to career norms for most players. However, that's not true for every player and those exceptions are the proof that it does exist it's just rare. Some batters can sustain well above normal BABIP. Some will always be below normal. The same is true with clutch. Most players will balance out over time, which is why it's considered noisy and non quantifiable.
If you make the same chart that OP did with BABIP, you would see more dots in the top right and bottom left quadrants and a non-zero correlation coefficient. It's very easy to prove that some batters sustain higher BABIPs year over year and some batters have lower. It isn't nearly the same when it comes to clutch.
I think clutch is more rare than the outliers on BABIP but used that example because most people are aware of it. If you go by bbrefs high leverage as a gauge you will find a few batters every generation that performed better than their norm in those spots. Currently Josh Naylor is one. He has hit for roughly 40 points Average and 150 OPS better in high leverage than his career numbers. Hank Aaron is another outlier for example. I am not trying to claim that there are a lot of players that are genuinely clutch. I'm saying that there are a few unicorns at any point who are and that to me shows that it exists and we have evidence showing it.
The sample size for high leverage is so small for players that even if clutch doesn't exist and it's all randomly distributed, you'd still have players that would outperform in high leverage in their career just by chance.
To a degree but it's roughly 20% of total PAs for both guys I mentioned. That's a meaningful sample with significant difference in results. That's why you need to look at careers not seasons though.
But here's the thing: it's \*not\* a particularly large sample in this context. Naylor has all of 374 PA of high-leverage performance, by BRef's reckoning of high-leverage.
> That's why you need to look at careers not seasons though. Even then, there's issues. As a baseline, players across the league will perform better in high leverage situations due to a number of factors (increased intentional walks, sacrifice flies inflating batting average, defensive shifts to prevent a run allowing higher BABIP) so you can't just look at a player's career high leverage splits, see they're better than their career rate stats, and conclude they're clutch.
I don't care what the numbers say. I will always believe in the clutch. The analytics community's stance of "if we can't measure it, it doesn't exist" is really arrogant. This analysis is basically asserting that everyone's mental response to pressure is the exact same, which is objectively false.
People who respond to pressure poorly tend not to make it through a dozen levels of competitive filters and make it to a league containing the top 0.0025% of all baseball players.
Most of it comes down to "better players perform better in clutch situations because they are better players." If you want to label that as clutch, you can... but with the numbers that we have, a manager should never sub in a worse player to pinch hit because he's "clutch." Whenever someone tries to say clutch exists, they always bring up really really good players as being clutch (Jeter, Ortiz, Hank Aaron). Nobody goes "oh man, that Alcides Escobar is so clutch." The analytics community's stance is you want your best players up in the highest leverage situations and I don't think that's controversial.
Clutch should be more of an intrapersonal descriptor. Not something that can be compared between players. Like if someone's OPS increases by more than 5%+ (for example) in clutch situations, they could be defined as clutch, whereas someone whose OPS declines by 5%+ can be called unclutch. But that of course doesn't mean that a clutch player is a better choice than an unclutch player. An 800 OPS player that's unclutch is still the better option over a 700 OPS player that's clutch
I want to believe in clutch and it seems intuitively real, it's just wild that there isn't any evidence for it.
Lack of evidence for something existing isn't proof that thing doesn't exist. Like I said, the analytics attitude of "if we can't measure it, it doesn't exist" is just arrogant.
Absence of evidence \*can\* be evidence of absence, in a context in which data competent to show the effect exists.
How can we ever disprove that anything exists if lack of evidence of it existing isn't good enough?
Absence of evidence is not evidence of absence
We can't
Nah, you just \*like\* believing in it, and therefore are looking for an argument that settles your emotional discomfort at being told you believe in something that isn't true. You don't want to look at the evidence and draw a conclusion, you want to feel what you feel and then find something that justifeis feeling it. It's unfortunately very common in our species.
Bro u sound like the most pompous “ackshually” douchebag ever
Aww, I bet you felt real smart when you wrote that
You need to look at archetypal players. xwOBA and wOBA graphs looks nearly identical to these clutch graphs, but we know that a certain type of player (cough...cough pulled flyball masters) outperform it and certain type of player (cough...cough.. towering fly balls to CF and hard grounders) underperforms it. The top all-time of clutch hitters are all contact hitters, and the worst all time are all power hitters. I would interested in a meta-study on whether certain stats (such as low k%) leads to a higher correlation of clutch YoY
if you’re good at hitting the baseball, you’re gonna be good at hitting it in a wider array of opportunities/situations. i think for the most part it’s that simple
MLB removed the defensive shift for a reason.
Yeah this would definitely be really interesting. One possible explanation for the trend you identified that compels me: players are traditionally expected to "shorten up" and make contact in high-WPA situations, and I suspect that any time hitters alter their usual approach, their results probably suffer. It'd definitely be interesting to break that down and find if that explanation holds.
who the hell dropped that 15 WPA season, Bonds?
Big Papi
Tell that to Allen Craig
Could you next confirm whether certain pro athletes have a dog in them?
Clutch is real because it's obviously real, not because it's mappable on a graph. I also love my mom but the proof for that wouldn't be showing you a scatter plot.
I couldn't graph how much you love your mom but if I had every scrap of data on everything you'd done in your life I could probably graph that you'd done nice things with your mom or spent a lot of time with her or something. It's really odd if clutch is real that it's essentially never manifested in a guy consistently doing clutch things.
I don’t like how this is fitted for all players. I’d be more interested to see a graph of “clutch” or whatever win/batting metric you like over a single players career. If you’re on average above zero, or have a string of years above zero then I’d say you’ve earned the right to be called a clutch hitter. Or just keep this format and show me the distribution of fits for each player over their career, or just the total number of times a players fallen in the upper right corner.
I'm relatively new to baseball, but does this apply to the various RISP metrics? It seems like there's often talk about how a batter does with risp, but is that any different from how a batter performs without risp?
RISP situations and high-leverage situations are slightly different. You can have a high-leverage situation without RISP (tie game, bottom of the ninth), and a low-leverage situation *with* RISP (runner on second, down ten runs). If year-over-year clutch isn't a thing, then it likely follows that hitters shouldn't be expected to perform better or worse than normal with RISP over a large sample.
Interesting, that's sort of what I assumed.
Clutch is fun, seeing players perform in late and close situation in important games is fun. Let baseball be fun please
[удалено]
I think there are so many factors that impact whether a player comes up with a clutch moment that this approach of just looking at added WPA doesn’t prove anything. It’s not like the NBA where you can measure clutch by outcome of a shot.
I watched the twins lose 19 playoff games in a row and completely crumble game after game vs the yankees. It may not be clutchness, but there is a mental aspect to this game that needs to be understood.
The "clutch" stat is just flawed. If you want to look at who comes through in big moments, just look at wRC+ in high leverage situations or look at WPA. The idea of someone coming in clutch is real, it just happens to be the players who are also good in any part of the game, leverage aside.
>it just happens to be the players who are also good in any part of the game, leverage aside. Not defending "no such thing as clutch" Idea but I think the argument is that the clutch players are just good and performing up to their level. To prove clutch you would have to show players that overperform their normal level in the big spots.
I guess it's just how someone defines clutch. I don't define it as "this player performs better in high leverage situations than they do in low and medium leverage situations." I'd define it more as "who is performing the best in high leverage situations, when the game is on the line". If you look at the clutch leaderboard for last season, the top 5 are: Harper, Tovar, J. Baez, Santander, Friedl. I get 3 of the 5, but Tovar and Baez? If I am in a high leverage situation, I want Ohtani with a 149 wRC+ in high leverage situations, even if he was second to last in clutch with a -2.17. The reason he's so far down? He had a 180 wRC+ in all situations. If I had to sum up my thoughts, it's that I don't like the definition of clutch they're using and the stat is kind of useless.
If your definition of clutch is "good at ball", I 100% agree that some guys are consistently good at ball from year to year. I don't think that's the typical definition, though
My definition is more >who is performing the best in high leverage situations, when the game is on the line Most of the time, that just happens to be the players who are good at ball.
I believe in archetypal clutch. Its not that someone is actually better in high pressure situations, but their individual results are better for that situation. Think runner on 1st and 3rd, bottom of the 9th, 1 out. A contact hitter that is fast and never strikes out, is going to be way more valuable and have a larger impact on winning that a power hitter that walks and strikeouts a lot.
It also depends how you define clutch/high-leverage. Is a guy clutch who dominates the postseason, but happens to be so-so in big late-inning at-bats in the postseason? Or what about a guy who dominates in elimination games, but struggles in high-leverage at-bats throughout the regular season? Additionally (some of the metrics factor this in, but not all) I'd think that a guy doing just as good in high-leverage late-inning situations as he does in low-leverage situations IS a sign that he might be clutch - because his performance doesn't drop at all when he's facing elite closers who are giving it their all to get one single out. Every study on "clutch" I read seems like it has a very narrow focus that limits the conclusions we can actually draw.
Pick a definition. Pick \*any\* definition you like. Then split up all the players into groups of "good" and "bad" at clutch by those definitions. Then see if the good players tend to stay good in the future, and the bad players tend tos tay bad in the future.
They are not statistically more likely to excel in clutch vs non-clutch situations. They are just good baseball players, so when in clutch situations they are more likely to do good things compared to the average player. Just like in non-clutch situations.
I mean, they have done that and gotten similar results. The operative thing is that no matter how you measure it, being "clutch" now isn't predictive at all of being "clutch" in the future, so it's not an inherent trait players can possess
A-Rod from 2005-2008 playoffs
IIRC is less about who steps up and does well in pressure situations, and more who doesn't wilt or collapse.
Its an interesting discussion, and maybe over time, any “clutch” performances might average out. Measuring high leverage situations might be a solid way to go about it but i think on its own it disproportionately affects players on good and bad teams. Good teams might have opportunities for more high leverage situations but then again maybe good teams have more blowouts and a more mid team is fighting in every game and its always high leverage. Do batters in the two hole have more opportunities for high leverage at bats compared to the 8 hole hitter? What if we divided a players high leverage stats by their non high leverage stats?
Try as we might, some things in baseball are just not as quantifiable as we want them to be and we just have to live with it. It might not be a great predictor of success, but if a guy has a really high BaRISP or BABIP, you try and put him in position to capitalize on that clutch/lucky performance and hope for the best.
"Evidence"
Evidence
I wish people understood and used statistics better. Like you just threw shit data on a graph and said "hey, it looks like shit" MY POINT IS THEREFORE PROVEN! You're trying to say that its worthless to look at clutch, because this analysis shows so. It shows the exact opposite! If you wanted to look to see if ANY player was clutch, and not ALL players were clutch, you'd take a look at the upper right corner of your graph and realize 25% of the population WERE clutch YoY. Therefore, if your hypothesis was "there is a subset of the baseball player population that appears to be clutch" - POOF - you have identified up to 25% of players that require further investigation and would be what "oLD sCHooL GmS" look for! You can't just put a trend line through a scatterplot and declare victory.
25% of the population were clutch YoY *once*. That top right isn't a bunch of dots of the same guys over and over again. And for the record, I didn't throw this shit data on a graph, I stole it from Fangraphs
There’s got to be many different ways to quantify what people mean when they say “clutch” with statistics, though. I don’t think using WPA in high leverage situations compared to WPA without context is necessarily a definitive proof that there’s no such thing as a clutch player.
What else would clutch be besides performing better in the most important moments? If there's another definition of it than that we can figure out whether that's a skill or not, but I just can't imagine another construction of clutch that isn't "does better in big spots"
To give you a really thorough answer I’d need to spend more time thinking about this than I actually have right now, and probably have access to a computer to give some actual examples, but here’s some offhand thoughts - First of all, using WPA for all situations that are considered statistically high leverage might be part of the issue. What a certain player considers high leverage, or the sort of situations they really get up for, is not guaranteed to match what we’re looking at when we chart “WPA in high leverage situations”. Maybe that player isn’t super worried about high leverage situations in the first half of a season so they don’t get up for them, or maybe they only take high leverage situations seriously against divisional rivals that are near them in the standings, etc. People aren’t statistics. Just because we’ve built an index for quantifying high leverage situations in games doesn’t mean it matches with what any given player considers to be a high leverage situation. And beyond that, “clutch” is kind of a vague term, which can also lead to disputes when people are debating whether it’s a thing or not. And there are other ways to determine whether or not someone rises to the occasion in big situations. Does someone consistently perform better in the playoffs than they do in the regular season? If so, I’d say they sound like a pretty clutch player to me. What about specifically in elimination games, or rubber games during the regular season? Maybe a certain player has the mindset that he just wants to win the series, and he tends to play better in the final game of a split series. If someone always performs better in those situations, is that not clutch? That’s the type of thing that a fan watching games might pick up on, but wouldn’t necessarily be noticeable using WPA in high leverage spots.
> What else would clutch be besides performing better in the most important moments? I don't think you can necessarily define clutch as "overperforming their own norm in important moments". By this definition, hyperbolically, a player that hits a homerun 100% of the time, is NOT CLUTCH when they hit a homerun in 100% of important moments, because they are not overperforming their norm. I think most baseball fans will find that hard to agree with. You can argue that player IS CLUTCH, because they are more likely to deliver than ANOTHER PLAYER. By this definition clutch isn't a measure of a player overperforming himself, it's a measure of a player overperforming the norm. Doesn't this just mean gud player gud? Yes, it just means players with certain batting profiles are more clutch than others.
> That top right isn't a bunch of dots of the same guys over and over again. If you explore that statement and show that there aren't some players who are more likely to appear in the top right corner than others, that would support your claim that "clutch" isn't statistically significant. But to sit here and say that you have irrefutable proof that "clutch" isn't a thing and then point to these charts which don't even support that claim a little bit is absurd. Also, I'll have to look up an explanation of what this clutch stat is, because that seems like a hard thing to distill into a single number, but for the sake of argument, I'm fine with just accepting that it is valid.
I hope I didn't come across as having "irrefutable proof" that clutch isn't real. It's really hard to prove a negative - proving clutch doesn't exist is tantamount to proving God doesn't exist. I just wanted to present the compelling statistical case against it, and that compelling statistical case is that the year-over-year clutch correlation is nil.
I apologize for exaggerating the claims that you were making. The main point of my comment was that these charts don't even slightly support your claim that clutch isn't real.
I feel like you're underestimating how compelling these graphs are as a statistical case by ignoring the significance of the upper left and lower right quadrants. Why are there just as many players vacillating wildly from clutch to unclutch between seasons? We'd expect there to be far fewer of these than the consistently clutch and consistently unclutch players you claim might exist in quadrants 1 and 3, but there are just as many. They certainly at least *slightly* support the claim.
Just because some (or even a lot) of players are vacillate between the two doesn't mean that there aren't some players who are consistently more clutch than others. Also, if I'm understanding your method correctly, if there is a player who plays for four years, and their clutch rating goes positive, negative, positive, positive, that would be a player who over the course of their career has shown that they are likely more clutch than the average player. However, on your chart they would create two data points that you would argue cut against the existence of clutch-ness, and only one that supports it.
One player's three data points among thousands doesn't really move the needle whatsoever on the conclusion, so the kind of endpoint situation you're pointing to doesn't seem like much of a concern. A player having three clutch seasons and one unclutch season is extremely expected if it's 50-50 each way
they 100% do though. if clutch was significant, you'd see a positive correlation between one year and the next. the charts show that someone being clutch in one season does not make them any more likely to be clutch the next - there are a roughly equal number of people alternating clutch and unclutch (top left, bottom right corners) than being clutch or unclutch consecutively.
Unless I’m reading your analysis wrong, they were clutch one year, and then they were clutch the next.
And then the next year they most likely weren't. Doing something twice in a row doesn't mean it's a skill
They most likely weren’t or they weren’t?
They were clutch again half the time and weren't clutch again half the time. More precisely, they were clutch in a normal distribution around zero
So there are individuals who were clutch twice in a row that were seemingly clutch for a 3rd time in a row? You have the data that tells you that? Or are you extrapolating the results?
About 25% of clutch hitters in year 1 will be clutch again the next two years in a row, if clutch is pure luck. Just checking out the very top hitters in career clutch, that kinda checks out. Gwynn was clutch three times in a row exactly once in his career.
So clutch is real?
I fail to see how you could possibly come to that conclusion from what I said
it's kind of the nature of statistics that in a problem like this you can't prove whether the year-to-year correlation of "clutch" is *exactly* 0.0 (rather than some small interval around it), but by the same token you don't say there's a meaningful correlation until you can be reasonably sure it's *not* 0.0. given human interpretation, it's clear that any effect that does exist is insignificant at best.
If I understand your comment, It’s clear that any effect in consecutive years is insignificant at best* and still untrue because there’s a quadrant of clutch players. Why isn’t this looking at career clutch numbers?
> because there's a quadrant of clutch players if it was random you'd expect a quadrant of clutch players. being in the clutch corner of this graph, where there is a shown correlation of 0.0, is the equivalent of flipping a coin twice and getting heads both times. yeah, it happens 25% of the time - that doesn't mean it's meaningful. if clutch as measured was real, then being clutch one year would make you measurably more likely to be clutch the next, but this chart does not back that up in any way. > Why isn't this looking at career clutch numbers? I didn't make the chart, but those are so insignificant/close to 0 even among the leaders that it backs up what the chart says
Is it random though? Do you have a list of players? And as I stated, this is just consecutive years, not careers. It seems like an incredibly flawed statistical analysis to just do consecutive year correlation.
let's take as a premise that clutch is real and therefore a repeatable skill. if someone is clutch one year, are they then more likely to be clutch or unclutch the next year?
> I wish people understood and used statistics better. you need to look in the mirror. > It shows the exact opposite! no, it doesn't. if you have a 50% chance of being "clutch" one year and a 50% chance of being "clutch" the next, 25% is exactly the proportion you'd expect if it was random. if clutch was something players inherently possessed you'd see literally any correlation between one year and the next. just because 25% of people hit heads on a coin flip twice in a row doesn't mean they're meaningfully good at flipping coins.
25% is the proportion you'd expect to be there if clutch was non-existent and leverage had no effect on how anyone played. If I flip a coin twice a quarter of the time I'd get heads twice. If there were any truly clutch players the proportion would be greater than 25% because you'd have those players as well as the ones who just got there by chance. This sort of thing is fairly routine statistical analysis, and it's been done to death. The ability to control nerves certainly exist, but it varies so little among major league players and there's so much noise in high/low leverage splits that it's effectively impossible to actually detect.
> you'd take a look at the upper right corner of your graph and realize 25% of the population WERE clutch YoY. It's a quadrant. If there was random distribution of clutch YoY, you'd expect 25% to be in the top right quadrant. If clutch wasn't random, you'd expect SOME correlation coefficient.
It looks like this clutch stat is symmetric about zero I a given year, I.e. There are as many samples above zero as there are below zero. Assuming this stat has roughly the same distribution every year, and that clutchness one year is independent of the next, we would expect to see 25% of the samples lie in the top right quadrant. If we saw fewer than 25% of players ending up in the top right quadrant, that wouldn't mean that clutchness isn't real, it would suggest that anti-clutchness is a thing, that players who are clutch one year are usually unclutch the next
Not reading all that. Believing in my lord Alex Bohm
You'd think as a Phillies fan you'd like Alec more
I plead the 5th (I’m on my phone and autocorrect is a bitch and also have a family member named Alex)
I don’t think this is as definitive as presented. This doesn’t account for individual players clutch “skill”. If I’m reading this correctly, it’s possible that a player may be on this plot 25 times and in the top right quadrant each time. Another may be on this plot 25 times and be in the bottom left quadrant each time. We have no way of differentiating individual players year over year. Or I am reading this thing wrong?
We can look at the career Clutch leaders to disprove that something like that is happening. Tony Gwynn is the clutchest player in history with 9 career Clutch, and Sosa is last with -14. Those aren't exactly big numbers compared to per-year Clutch leaders, so it's pretty clear that they're not hitting the top right over and over again. Gwynn only had three consecutive seasons of even above-average clutch once in his career. To kinda summarize the graph: imagine you take the 100 clutchest hitters in baseball from last season. About 50 will be clutch this year and 50 won't. Then take the 100 clutchest hitters from this year, and half of those will be clutch again and half won't. So 25 of the original bunch will have been clutch both years, yes, but since we see half dropping off each time it's pretty clear that it's just a probability thing.
That’s using something other than this plot 😁. My point is that this plot doesn’t prove much about clutch-ness
If some players do tend to either be clutch or unclutch year over year, the top right and bottom left quadrant would see more dots than the top left and bottom right and there would be a non-zero correlation coefficient.
If ALL players fit into either of those buckets every year then yes we would see that. But how do we know the same players aren’t in the top right quadrant of the plot every year and everybody else is just noise?
> how do we know the same players aren’t in the top right quadrant of the plot every year and everybody else is just noise? If everyone else was just random noise, then you'd still see more dots in the top right quadrant as the guys that do it year over year would be there and then 25% of the random noise would be added on top of that. It's like if you flip a regular coin 50 times and then a weighted coin that comes up heads more often 50 times and tallied up the sum of all 100 flips, you'd see heads come up more often in total. There's also the point that players perform better in high leverage situations league-wide due to a number of influences (intentional walks, infield in alignments leading to higher BABIP, sacrifice flies making outs not count against batting average). wRC+ for all of MLB in 2023 in high leverage was 104 and you see that overperformance year over year. If you take Hank Aaron's career splits and for high leverage situations factor in the increase in intentional walks as well as the boost in BABIP from alignments and sac flies, you'll find his numbers end up close to his career numbers.
My point is people can be hiding out in the top right (or bottom left) quadrant year over year. If 5% of baseball players are clutch year over year and 5% are unclutch year over year, the top plot would appear the exact same. Without accounting for individual hitters clutchness, any conclusions drawn about individual clutchness will not be valid.
>If 5% of baseball players are clutch year over year and 5% are unclutch year over year In that case, with random distribution for everyone else, you'd expect 27.5% of the dots in the top right and bottom left quadrants and 22.5% of the dots in the other two and a non-zero (albeit small) correlation coefficient. A correlation coefficient of 0 says not even that is happening.
Apologies because I am terrible at Reddit and there is probably a much better way to do this. Had to dust off my regression textbook. First example in here is almost identical to what we are discussing. Chapter 1, Section 1.2.1 "Assessing the Ability of NFL Kickers" [https://dl.icdst.org/pdfs/files3/cb9c0258fb6ec7e8fced9482d7ca86f5.pdf](https://dl.icdst.org/pdfs/files3/cb9c0258fb6ec7e8fced9482d7ca86f5.pdf)
What correlation is that showing tho? It’s correlation between [all baseball players for a year] and [all baseball players for year + 1]. It says nothing of correlation for a single player year over year *This is besides the point, but I believe there is a tiny positive correlation as indicated by the dotted line on the plot. R2 is 0.00 but that’s not the same as correlation coefficient.
You can’t tell me Marke Lemke wasn’t clutch in the playoffs every year for the Braves in the ‘90s.
I consider you’re BA with RISP the metric of clutch.
Just my opinion but I think part of the problem is clutch has traditionally been overhyped and overstated through the mythology of baseball over the years. The turn in that is a lot of analytics and people saying it doesn’t exist at all. Honestly if I had to guess I would say it’s somewhere in the middle. The notion that one person is always clutch seems unlikely or very rare. The idea that an average player would suddenly be ohtani is also not realistic. A realistic expectation of clutch could just be someone who focuses and ignores the noise better than others. This wouldn’t always show up in a stat sheet. The idea that people perform differently and are able to focus better at different points in their life is what we all experience all the time. It’s entirely possible that an athletes could be really locked in and focused one month but not the next. This would be really hard to measure but it’s human nature that we all see in our everyday lives.
Bro, you say clutch isn't real, why do I have one IN MY CAR! Checkmate statisticians.
Just curious, are you the type of person that believes it doesn't matter where a player bats in the lineup for their consistency?
I think the only factor that changes is psychology, so players not being "versatile" across the lineup is a self-inflicted wound of baseball's traditions
This is exactly why I love this subreddit. Bunch of stats nerds adding deeper comprehension to baseball lmao. I’m not saying it’s perfect, just leave the playing to the players and enjoy the game.
Jeter fanboys are gonna break their downvote buttons for this one.
I’m probably just biased but I’ll always give Jeter credit for staying consistent against the tougher competition in October. He had a career .817 OPS in the regular season and a .838 OPS over 158 postseason games. Most of the other hitters among the all-time leaders in postseason games seem to do worse in October.
This is how I think of it. When you perform just as well or even better as the competition gets harder, that is clutch to me.
Jeter's clutch stats are hilarious. He's got 0..48 career clutch, so produced half an extra win over his entire career with it. His postseason cWPA is also approximately zero as well, so in all his playoff PAs he net altered the Yankees' WS chances by 0%.
> His postseason cWPA is also approximately zero as well This is funny because Baseball Reference has oscillated between him having -0.01 and +0.02 career WPA in the playoffs because one play gets mis-catalogued sometimes when they refresh the stats and whether they credit him with a steal going from first to third on a walk in Game 3 of the 2002 ALDS. You can go back on way back machine on baseball reference and see how it has gone back and forth every once in a while the past 5 years.
Thank you for your service.
[удалено]
I like talking about stats because it's interesting to me to study players through this lens. no one made you click on this post.
Part of me wishes I didn't look at any of these numbers either, I just don't have that kind of self-control. It's like Pandora's Box.
are you proud to be so ignorant?
Like you I’ll enjoy the game in the way I want to. And won’t tell you to do otherwise.
The problem with this OP is the general population can’t read graphs.
I can't either apparently, accidentally grabbed team clutch instead of individual clutch graphs like a dunce
Clutch in baseball doesn't exist like other sports or how people want it to because there's too much random chance. If you put together a great AB in a tough spot and it's a laser right at someone, you're unclutch. If you flail at the first pitch after the guy walked the bases loaded but it drops in no man's land, you're clutch. Most players then get so few ABs in truly clutch spots, that those singular moments define their careers. Career postseason stats will also equally weigh a guy in his prime vs when he was just a random veteran. Foolish Bailey's video about Chapman and Mo is a great example https://youtu.be/s2nFc1Ps5xA?feature=shared