Why Strikeouts Secretly Matter for Batters

I got my start at FanGraphs by writing Community Research articles. As you may have noticed, community authors have been very busy this season, cranking out a lot of interesting articles. One that caught my eye the other day was triple_r’s piece on the importance of strikeouts for hitters. The piece correctly pointed out, as other studies have, that there’s basically no correlation between a hitter’s strikeout rate and his overall offensive production. Strikeouts don’t matter; case closed, right? Well, not exactly.

Let me present a hypothetical situation. Say there’s a group of players who go to an “anti-aging” clinic in Florida and pick up some anabolic steroids. Let’s say these hypothetical players are named Bryan Raun, Ralex Odriguez, Tiguel Mejada, Phonny Jeralta, Celson Nruz, and Barry Bon… nevermind. Yet, after using the steroids, it appears that the group of them, on average, has not improved. The steroids didn’t improve their performance, right? But, wait — let’s also say that while visiting Florida, some of them contracted syphilis, which spread to their brains, causing delusions and severely impacting their judgment, strike-zone and otherwise. The players whose brains aren’t syphilis-addled have actually improved quite a bit, but their gains are completely offset by the losses suffered by those whose central nervous systems are raging with syphilis. So, the fact that the steroids actually do improve performance has been completely obscured by another factor that is somewhat — but not necessarily — associated with the steroids.

How does this analogy relate to the strikeout situation? Take a look at this table of correlations from the sample I’ll be using in this article — qualified batters in individual seasons, 1913-2012:

ISO BABIP K% BB% AVG OBP SLG wOBA wRC+
ISO 1
BABIP 0.129 1
K% 0.461 -0.025 1
BB% 0.356 0.054 0.139 1
AVG 0.275 0.859 -0.350 0.083 1
OBP 0.418 0.642 -0.160 0.705 0.755 1
SLG 0.921 0.452 0.232 0.322 0.627 0.644 1
wOBA 0.693 0.584 -0.049 0.552 0.766 0.904 0.871 1
wRC+ 0.724 0.515 0.101 0.550 0.662 0.825 0.854 0.921 1

The most obvious things we can gather about K% from this is that if you strike out a lot, you will probably have a lower batting average (and therefore, indirectly, a lower OBP), but that you will also tend to hit for more power. Being a power hitter may also cause you to get pitched around, leading to a higher BB%. The power and the contact basically offset each other overall, though.

But let’s think about causality. Does it make sense that striking out more would directly cause a drop in batting average? Definitely. Does it make sense that striking out more would directly cause a rise in ISO (which is SLG – AVG)? Not at all, really. If you put me in the majors, I’d K at least 95% of the time, but I definitely wouldn’t have a high ISO to show for it. How about reversing the causality — does trying to hit for more power make you K more? OK, maybe a bit. But I think there’s a more important factor at work: selection bias.

If a hitter is going to make it into the majors based on his offense, he’s usually either going to have to get on base a lot or hit for a lot of power. A deficit in one trait can be made up for if the other trait is good enough. Up to a point, of course; I bet Mike Tyson in his prime could have swung the bat extremely hard, but probably wouldn’t have made contact anywhere near enough to make the majors. Plus, he made way too much money boxing. Anyway, get a load of these guys from this season (ranks out of 141 qualified batters):

Name K% K% Rank ISO ISO Rank BABIP AVG OBP SLG wOBA wRC+ WAR
Brandon Moss 27.8% 9 0.255 4 0.308 0.257 0.339 0.512 0.367 136 1.6
Pedro Alvarez 31.2% 5 0.236 10 0.272 0.226 0.290 0.463 0.322 106 2.2
Alfonso Soriano 24.5% 15 0.233 11 0.286 0.255 0.294 0.487 0.336 109 2.6
Mark Trumbo 26.2% 12 0.231 12 0.275 0.240 0.299 0.471 0.331 112 2.8
Chris Carter 36.7% 1 0.226 15 0.309 0.220 0.318 0.446 0.334 111 0.5
Adam Dunn 30.8% 6 0.217 21 0.266 0.219 0.320 0.436 0.330 103 -0.3

Would they even be in the majors if they had a typical (about 0.145) ISO? Some definitely wouldn’t, and the others would be borderline players.

If you could get a random, representative sample of the entire world population, I believe it would become pretty apparent that strikeouts do in fact matter to batters. As it is, however, the fact that pretty much all the high-K% batters are only selected to play in the majors if they have phenomenal power to make up for it has created bias in the sample.

Another analogy: let’s say successful actresses are either very beautiful (e.g. Megan Fox) or very talented (e.g. Maggie Smith). Occasionally, an actress will be both (e.g. Charlize Theron). The selections of the casting people will pretty much keep actresses who are neither beautiful nor talented out of the big movies and shows. You might find a little bit of an imbalance towards beautiful actresses with not much talent; this could cause the overall sample to show no correlation between talent and success, when you’re only looking at those who’ve made it to the big time. But, as shown by all the actresses who never made it because they weren’t talented enough to overcome their lack of beauty, talent really does matter.

By the way, Charlize Theron is Miguel Cabrera. You heard me:

Name K% K% Rank ISO ISO Rank BABIP AVG OBP SLG wOBA wRC+ WAR
Miguel Cabrera 14.7% 95 0.305 2 0.353 0.347 0.443 0.653 0.461 195 7.5
Edwin Encarnacion 10.0% 131 0.262 3 0.247 0.272 0.370 0.534 0.387 145 4.1
David Ortiz 14.7% 95 0.254 5 0.321 0.309 0.394 0.562 0.399 150 3.7
Jose Bautista 15.9% 84 0.239 8 0.259 0.259 0.358 0.498 0.371 134 4.2

Edwin Encarnacion, meanwhile, is looking like a talented, beautiful actress who just hasn’t been getting great roles lately (as shown by his BABIP).

I think there are around four basic abilities that contribute to a player’s offense: Contact ability, Eye/ Plate Discipline, Power, and Speed. A fifth consideration is of course luck, or randomness. They are all difficult to quantify, but there’s an interplay between them that contributes towards the more easily-quantified stats like AVG, OBP, SLG, and wOBA. Below is a table of those traits with what I believe to be the best proxies for those traits, listed in order.

Contact Eye/Discipline Power Speed
Contact% O-Swing% HR/FB* Spd (?)
K% BB% ISO UBR (?)
AVG OBP HR/PA SB numbers
LD% and PU% K% SLG BABIP
SLG BABIP
ISO
BABIP
OBP

The asterisk next to HR/FB is there because I feel like park influences taint the stat quite a bit as a measure of true power; a park-adjusted version of the stat would be ideal.

K% is not entirely direct for either Contact or Eye; some Ks are due to whiffing, while others are due to misjudging a pitch and taking it for a strike. It would be nice to see a distinction between the two types of Ks, I think.

The batted ball stats LD% (Line Drives) and PU (Pop-Ups, which is FB%*IFFB%) are there because the trajectory of the contact matters too, not just whether contact was made or not.

I don’t think there really is a great proxy for speed, though. BIS is now timing players on base running events, and I think that has the potential to create some very good results. But we’ll be looking at wOBA here, which doesn’t really factor speed in much, other than the impact it has when a player legs out an infield hit, or pulls off an extra base on his hit.

Since my sample goes way back to 1913, whereas some of the best above stats are only available from 2002 onwards, I’ve chosen, for the study you’re about to see, K%, BB%, ISO, and BABIP as the key factors to examine. With these factors (sometimes using HR/PA instead of ISO), you can pretty closely approximate AVG, OBP, SLG, and wOBA.

Here’s my gratuitous flowchart, so we’re all on the same page here:

PA Flowchart3
These are, of course, the basic ways a plate appearance can turn out. We have BB% and K% reflecting the chance of a walk or strikeout, and we have the semi-random, infrequent events like hit by pitch or reaching on error. The leftover is the balls hit in play. Since home runs aren’t (generally) subject to being caught, BABIP leaves them out of the equation, and only considers balls that are caught/putouts or those that become singles, doubles, or triples. A player’s power, reflected by ISO, plays a big part in deciding whether a batted ball will go for a home run or otherwise make it past the outfielders. Meanwhile, BABIP is part luck, part a reflection of a player’s contact, power, and speed. And you can’t neglect the role luck plays in everything.

Here’s how my key stats can be used to derive somewhat simplified versions of other stats:
Stat derivations
Notice how Ks are a significant factor in the equations. wOBA is a little trickier, given its various, evolving weightings, but a simple multiple regression on the data yields the following equation: wOBA = 0.405*BB% – 0.321*K% + 0.484*ISO +0.625*BABIP +0.091. Strikeouts definitely hurt, when viewed from this angle, having sorted out the interactions. The real derivation for wOBA based on the above stats looks more like the OBP derivation, except with the special weightings for the different hits added in. Still, that formula gets pretty close, with a 0.962 R Square. More details on that, if you’re interested:

Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 99.0% Upper 99.0%
Intercept 0.09137 0.00110 83.1 0 0.08921 0.09352 0.08853 0.09420
ISO 0.48371 0.00216 223.7 0 0.47947 0.48795 0.47813 0.48928
BABIP 0.62476 0.00354 176.7 0 0.61783 0.63169 0.61565 0.63387
K% -0.32088 0.00232 -138.5 0 -0.32543 -0.31634 -0.32686 -0.31491
BB% 0.40500 0.00338 119.9 0 0.39838 0.41162 0.39630 0.41370

In the end, overall production, represented by wOBA or wRC+ is what really matters to a hitter, of course. But as the regression formula (and common sense) illustrates, with all else equal, overall production will increase as strikeouts go down. Mike Trout is a great example, as his ISO and BABIP have been almost identical these past two seasons:

Season BB% K% ISO BABIP AVG OBP SLG wOBA wRC+ WAR
2012 10.50% 21.80% 0.238 0.383 0.326 0.399 0.564 0.409 166 10
2013 14.80% 18.30% 0.241 0.381 0.330 0.435 0.570 0.430 180 10.2

If Trout had not improved his K% in 2013, his OBP would have been about 13 points lower than it is, and his wOBA approximately 11 points lower. He’d still be amazing; just less so.

Ted Williams, by the way: career 0.289 ISO and 7.2% K%. Amazing. It can be done.

Eno reported from an interview with Mark Trumbo this season,

He thinks there is a genetic component to the ability to discern balls and strikes — some are “born with it” — but he’s working to get the most out of what he has.

I agree with that, although perhaps a lot of it is developmental from an early age, and not necessarily genetic.

Here’s how I look at it: everybody has some innate ceiling when it comes to the abilities needed to succeed in baseball. Some people have too low a ceiling in one or more of the abilities, and would never make the majors, no matter how hard they worked; maybe they’re too small, not naturally athletic enough, have bad eyesight, or lack the necessary rapid visuospatial processing potential. There are others who could have made the majors if they’d worked hard enough at it, but lacked either the drive to reach their potential, the exposure to baseball, the opportunity, or just the luck (e.g. staying healthy). Let me throw out some numbers, wildly estimating the chance of being an elite hitter by multiplying all the factors out:

Trait Power Contact Eye Speed Exposure Opportunity Drive Luck Whole Package # of People on Earth
% of people possessing 5% 5% 10% 25% 5% 10% 1% 50% 0.00000016% x 7 billion people = 10.9

I think that helps explain why a player who can truly do it all is pretty rare. Cabrera has elite power, contact, and plate discipline, but is not even close in speed. This year, Chris Davis is showing the power and eye, but definitely not contact. Mike Trout is a bit short of elite in the contact department, but definitely has it in the other areas. Andrew McCutchen might have a bit of a case, although some of his traits are just borderline elite.

So, there are different ways to reach the same level of productivity, and by nature, people are unlikely to be outstanding in all of them. Talent evaluators in baseball will give a chance to a power hitter who strikes out a lot, because he’s capable of reaching an equivalent level of production as a player who strikes out less but hits for less power. They’re just making the most of what’s available. A truly perfect hitter, however, would never strike out. Each time they strike out is one less time a ball they could have otherwise hit might fall in for a hit, or that they might have drawn a walk. Obvious, right?

All else equal, strikeouts are bad.  I guess the real question is, if you told a guy like Chris Carter to try to strike out less, how might that affect his overall performance? Is changing his approach more likely to be helpful or detrimental?  Let me hear your thoughts.




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Steve is a robot created for the purpose of writing about baseball statistics. One day, he may become self-aware, and...attempt to make money or something?


55 Responses to “Why Strikeouts Secretly Matter for Batters”

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  1. Dave S says:

    Great post. Thanks for writing it!

    If you asked me that question about Carter, I’d ask followup questions… how many guys like Carter have ever been able to strike out less? And what happened to them?

    My guess would be very few players like him were able to decrease their strikeouts, and those that could/did… ended up out of the game within two years. Because I think the dropoff in power/iso would outweigh the gain in contact… and additionally, I don’t think their OBP would go up much, as they’d begin to walk less (less power=less walks).

    But thats just a wild guess.

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  2. Cyril Morong says:

    That last question, I tried to see what happens when players strike out less from year to year. But simply doing that has all kinds of problems. But I think what your are asking is the key question. Should Mark Reynolds and Adam Dunn try to make more contact? If so, would that help there teams score more runs? Maybe their power suffers. Maybe they hit into more DPs.

    One other comment. Your study goes back 100 years. Strikeout rates have changed quite a bit over time. Maybe these correlations would be different if you only looked at the 1920s compared to the last 10 years

    I found in some decades K% had a negative correlation with offensive winning pct and in other decades it was positiive

    http://cybermetric.blogspot.com/2008/11/do-best-hitters-strikeout-more-than.html

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    • Thanks Cyril. I ran a quick correlation chart just now on 2000-2012, and here are some results:

      Correlation with K%
      ISO: 0.402
      AVG: -0.398
      BB%: 0.348
      wRC+: 0.143
      wOBA: 0.113
      BABIP: 0.022
      OBP: -0.019

      Correlation with ISO is down a bit, but the main difference is a much stronger connection between being a high-K% guy and walking more.

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  3. Cyril Morong says:

    I also posted something a few years ago asking the question if Ryan Howard should try to strike out less

    http://cybermetric.blogspot.com/2008/11/should-ryan-howard-try-to-strikeout.html

    Not sure if my conclusions were warranted. There may be selection bias going on with what I did

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  4. If you would have taken bets on which FG writer would compare Theron to Cabrera, the odds on Jeff would have been so high. Seriously, it’s actually a very good analogy and the selection bias argument is a good one. Strikeouts don’t appear to matter because you’re only able to strikeout a lot at the MLB level if you do other things well. You’re truncating the dependent variable, so the relationship looks a lot different in the data than it does in real life. Good stuff.

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  5. VORP is too nerdy says:

    I believe the Pirates/Phillies attempted to get Brandon Moss to swing more for contact, and it made him a far worse hitter than what he is naturally; a power guy who swings for the fences and strikes out alot. When he signed with the A’s, they allowed him to basically be himself, and obviously he’s been a lot more successful.

    So to answer the question you pose in your final paragraph, I would say it’s likely detrimental for a major leaguer. They were most likely drafted based at least primarily on their hitting ability. To ask them to fundamentally change what has made them a successful hitter up to that point is a tall task and could derail them, like it did with Brandon Moss. It’s one thing to make slight mechnical tweaks; it’s entirely different to ask someone to fundamentally change their approach.

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  6. dcs says:

    As to the wOBA formula, of course Ks are negative. After all, they are outs. And also, if you hold ISO constant, K are gonna be negative. You are considering the negative aspect of not having a chance for a batted ball to fall for a hit, while not including the positive aspect that swinging harder (or with more uppercut) helps hit the ball harder.

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  7. Eminor3rd says:

    What did we learn here?

    Did anyone really think strikeouts don’t matter at all? I thought we just knew that they weren’t much worse than OTHER outs, and so a propensity to strikeout was fine if you were still good at everything else. I don’t think anyone ever thought that if you could do everything well and STILL not strikeout that you wouldn’t be extraordinary.

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  8. Cuddy says:

    I enjoyed this, although I wish it had been reigned in and the arguments tighter.

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  9. Jonathan says:

    You’re a madman WongBurger!

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  10. Edward says:

    this is an incredible post. thank you so much for writing it. a super enjoying and educational article. this should be used in stats classrooms, if everybody understood baseball stats!

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  11. TheMooseOfDeath says:

    Miguel Cabrera, I loved you in Arrested Development!

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  12. chuckb says:

    This is kind of picky and probably doesn’t matter at all, but in your flowchart, I think that ROE should be underneath “In play” and as a 3rd alternative that detracts from a player’s BABIP, if I’m not mistaken. In any case, a ROE is a ball in play, just one that doesn’t end up in a hit or a “caught.”

    Really interesting piece. Thanks for sharing.

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  13. Can we isolate out types? Ks are probably worse as far as run creation than deep flyball outs, but possibly better than routine grounders, possibly equal to infield flies.

    I’d like to be able to see ball speed off the bat and trajectory and then make a matrix. Find the average run value of each. A scorched ball hit on the ground isn’t the same as a routine bouncer.

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  14. chris moran says:

    Good article. I wrote this in the Community Research section: http://www.fangraphs.com/community/in-defense-of-striking-out-ideal-strikeout-rates-for-hitters/

    Obviously if you can improve contact without sacrificing power and walks, that’s special, but obviously not everyone can do it. That’s why Ted Williams is one of the best hitters ever. For mere mortals, I think there’s an ideal plate approach to match their skillset which leads to more or less strikeouts.

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    • Thanks! Yeah, I read your article before — good stuff.

      I think it’s hard to be sure that a drop in power you’re seeing is due to trying to strike out less. There are so many factors that could cause a drop in apparent power — park factors, injuries, or being pitched differently, off the top of my head.

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  15. robertobeers says:

    Are ITP HRs a part of BABIP? Or are the thousandths of a percentile change not worth their inclusion?

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    • ralph says:

      If we’re going to worry about ITP HRs with respect to BABIP, I suspect doubles and singles off the Green Monster and other such walls would be much bigger priority to worry about.

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  16. radicalhenri says:

    The title sounds like something from the yahoo homepage about a celebrity. nothing against the article though.

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  17. Tbone says:

    How would you attempt to assess the fluctuation of Marcus Semien’s K% and BB% throughout his career??

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    • Wow, he’s really all over the place, isn’t he? A lot of his AAA and especially MLB stat changes can be attributed to small sample size. You’d also expect BB% to drop and K% to rise as he moves up in level, of course. I don’t know. Let’s give him more PAs to find out what he’s really all about.

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      • Tbone says:

        Great article by the way, one of my favorites in recent time. Thanks for doing it.

        Is it crazy to think — even though the sample size is big (483 ABs) — that his AA BB% / K% was an aberration? His plate discipline was noticeably better at that level. Maybe a product of him seeing the ball better in Birmingham’s park. I don’t have his home/away splits at that level, but just a thought.

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        • David says:

          Semien in Birmingham: 320/443/570
          Semien on the road in the SL: 259/397/394

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        • Thanks! And thanks, David, for the numbers.

          Well, with 483 PAs and a 17.4% BB%, we can say with a reasonable amount of certainty that his true BB% at that level was at least 15%. I think he probably did improve/change his approach in AA there.

          Maybe he lost his way a bit in AAA. But if we guess his true BB% should have been more like 13% in AAA due to a higher level of competition, there’s almost a 6% chance that he’d show the 9.9% BB% over 142 PAs that he did. I don’t know how AA pitchers faced compare to AAA, though; it could be even a bigger step up in terms of how difficult it is for batters get walked, for all I know.

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  18. ralph says:

    It’d be interesting to see how K% works as a predictor for career length (especially if high-K% rookies are out of the bigs more quickly than mid- and/or low-K% rookies), thus speaking to the selection bias.

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  19. jdbolick says:

    Carlos Gonzalez could be an interesting test case given that he appears to have exchanged a higher K% and lower contact rate for more power this season.

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    • Yeah, good find — that’s a pretty significant change. He’s also hitting a lot more fly balls this year. It could be that he changed his swing? Still, I’m a little hesitant to draw conclusions from what could be a fluke season. His .368 BABIP is one cause for suspicion this year, though he definitely tends towards a high BABIP.

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  20. RC says:

    My big issue with the premise of this article, is that its obvious. And also not too useful.

    Of course there selection bias against guys who strike out too much. There’s the same bias against guys who hit 100% flyballs, and guys who hit all weak grounders.

    A strikeout isn’t any worse than a weak ball in play.

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    • Guys who his 100% fly balls or weak grounders? Is there such a thing, or anywhere near it?

      The selection bias is not against all high-K% guys; it’s against high-K% guys who don’t make up for it in other ways. Important distinction. And that specific bias is what makes it appear that there’s no correlation between Ks and overall production.

      Yes, a strikeout isn’t any worse than an infield popup, and not much worse than a weak grounder. But would striking out less create an equivalent number of automatic outs from weakly-hit balls? I highly doubt it.

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  21. BMarkham says:

    This is an interesting article, but I don’t like that you did by sampling for a 100 years. The new, high strike out hitter is a new breed of hitter that hasn’t been around for long. What we should be talking about is a specific type of hitter, those with high K%, decent BB%, high FB%, high HR/FB%, low BABIP type players.

    If you’re swinging at pitches out of the zone too much that’s going to effect both you’re BABIP and your ISO negatively. If you’re swinging and missing because you can’t discern and hit breaking balls that’s not going to help anything. If you’re swinging and missing because you’re taking bigger rips, then it can help your ISO. If you’re taking big rips with an uppercut then you’re BABIP may be lower and your K% may be high, but if you have plate discipline and the raw power and bat skill to have a strong HR/FB rate then you can have a great ISO.

    Let’s look at some players. Chris Carter leads the league with a 36.3% K rate. He has a .226 average despite a .315 BABIP because of all those strike outs. But, he has a 22.7 LD% to go along with a 46.9% FB rate (2nd only to Brandon Moss) and 21.6% HR/FB rate (6th). That leads to him having a .237 ISO, good for 9th in the league. Carter fits the mold of someone who despite the Ks has decent plate discipline, only swinging 28.3% making him 50th lowest, nothing special but it shows that his Ks aren’t because he swings at everything. He Ks because he only hits the strikes he does swing at 76% of the time.

    But again, that’s because he’s taking a bigger swing. If he wasn’t, how much lower would his ISO and HR/FB numbers be? He’d likely still be swinging and missing a decent amount, but he wouldn’t have the same power. It’s a trade off and it depends on your hit tool and raw power whether a player should make that trade off. In Carter’s case, this year he has a 117 wRC+. I don’t think he would be a better hitter if he shortened up his swing.

    Now let’s look at another high power, high K, low average hitter in Pedro Alvarez. He Ks less often than Carter (30.8% for 5th highest) but he’s swinging at more pitches out of the zone (35.%). This not only means he should expect a weaker BABIP, (.275 to .315) but also a worse BB rate (8.0 to 12.1). Thus, despite a better HR/FB rate (26.6 to 21.6) Alvarez’s 107 wRC+ doesn’t match up to Carter’s 117. If Alvarez could improve his plate discipline but still took big swings, he would be a much more valuable hitter. Alvarez also apparently either isn’t as good at hitting flyballs or isn’t trying as hard as Carter, with a 35.8% FB rate.

    It’s not that Ks don’t matter, or the idea that if everything else is good then it’s OK. It’s about a trade off. Swing harder and you increase the chance you miss but also increase how hard and how far the ball is hit when you do hit it. And if you have good plate discipline then you limit the Ks somewhat as well as increase your BB%. How high would Carter’s K% be if he swung at pitches outside the zone as often as Alvarez? How much less would he draw a walk? Napoli, is 2nd in Ks with 32.3%, but only swings at 25.9% of pitches out of the zone. That’s a big part of the reason he holds a .360 BABIP. He also hit a few less FB and more LDs then Carter and Alvarez which also helps his BABIP.

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    • Great response, thanks. I agree with most of what you said.

      Just thought I’d point something out about Napoli and his .360 BABIP this year: he’s swinging at more pitches out of the zone than he typically does (25.9%, vs. 24.7% career), yet his BABIP is 51 points higher than usual. Meanwhile, his HR/FB is also lower than normal.

      I think his high BABIP is probably mainly due to luck, but I think the Green Monster probably has a lot to do with it as well. I think the Monster probably drags down his HR/FB a little bit as well, on the other hand: http://www.fangraphs.com/blogs/babip-park-factors-and-the-batted-ball-connection/

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  22. Swfcdan says:

    Holy balony this is detailed.

    Have to check this out properly another time.

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  23. Matt Lentzner says:

    Really liked the article, Steve.

    Something you didn’t consider is that a home run is a boundary condition. If you hit it over the wall you get a big benefit, but fly balls that don’t leave the park are usually outs.

    Where I am going with this is: A guy who normally hits a fly ball 330 ft on average is not going to benefit much by accepting more strikeouts to hit the ball 350 ft. The strikeout are just going to be extra outs with no benefit.

    But a guy who hits flies 380 ft is going benefit hugely by hitting them 400 ft. The strikeouts will be worth the extra home runs.

    A guy who can hit the ball 440 ft is going to benefit also by cutting down his swing and hitting them 420 ft with less strikeouts. He’s going to hit the ball less far, but put more in play – maybe even hitting more homers in the process.

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    • Thanks Matt, and great points.

      I’d love to be able to get a hold of all a player’s velocity off the bat and trajectory data, so I could have a decent estimate of what their results would have been had they made harder or softer contact.

      But I think estimating the difference swinging harder or softer would make on a player’s ability to make contact in the first place would be extremely difficult to pinpoint, and would vary quite a bit by player.

      Plus, are we talking about swinging harder on every pitch, or only with two strikes? It can get pretty complicated, huh?

      Great work at THT and BP, by the way!

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      • Matt Lentzner says:

        Steve,

        I agree it’s all speculative. I have a years worth HITf/x data, but I don’t think I’m allowed to use it for any published works unfortunately. Anyway, it’s something I’m really interested in – how a batter adjusts his swing by count (as you mentioned) and by who they are facing. I think that batters cut down on their swing against hard throwers and with two strikes. I wouldn’t say “softer”, but “shorter”. The terminology is confusing because longer swings are slower to the ball, but have better bat speed at contact.

        Batters should hit significantly more home runs against hard throwers because of the extra collision energy, but they don’t seem to (jury is still out on that). OK, I’m rambling.

        I’m flattered that you’re familiar with my work. Thanks!

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  24. Art says:

    An interesting aspect of this is the value of “pitches seen”. Why do power hitters like Dunn get a lot of walks? Is it mostly because they swing and miss a lot and thus see more pitches? Is it because they are more patient at the plate, working deeper into counts looking for a pitcher’s mistake that they can put out of the park (maybe power hitters are less likely to swing at pitches on the corners earlier in the count because those don’t frequently get hit for HR)? Is it because of intentional walks (or semi-intentional walks — pitchers trying pitch around or trying hard avoid a mistake on the heart of the plate against them)?

    Aside from that, these types of hitters add value by making a starting pitcher throw more pitches. This type of value isn’t typically calculated into stats that measure individual’s offensive value, but it would be interesting to measure. BoSox this year are known for their high strikeouts and working deep into counts.

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