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CC Sabathia‘s recent decline is looking more and more like Tim Lincecum’s also-much-scrutinized decline.  To make the point, here are some key year-by-year stats for each.

The velocity loss is perhaps the most publicized common aspect.  Yet, while acknowledging that year 2 of Sabathia’s decline is only about 10% (19 innings) in, it’s shaping up as though there may be many other commonalities:

• ERA above FIP when it wasn’t the case before
• Sudden (and permanent?) spikes in HR/FB%
• An apparent loss in ability to strand runners
• (BABIP might also be trending up for each, but this is harder to tell, due to the regular noisiness of year-to-year BABIP.  Lincecum also saw his LD% spike, which might not be true for Sabathia.)

Having also been thinking about Nathan Eovaldi lately — who has both elite fastball velocity and an apparent ability to suppress HR/FB (7.0% in 279.2 IP) — I couldn’t help but wonder if these things are systematically related.

I remember there was some attention paid to these things when SIERA was being introduced.  But it turns out most of the attention there was on strikeouts, rather than velocity.  Obviously velocity and strikeouts are positively related.  But (1) Lincecum and Sabathia are actually still pretty good/decent at strikeouts, and this hasn’t prevented their recent struggles; (2) Eovaldi has only elite velocity, and pretty pedestrian strikeouts.  So the real question is: Does velocity itself matter, in addition to strikeouts?

(In the subsequent analysis, I’ll be looking primarily at effects on HR/FB%, LOB%, and ERA-FIP, since those seem to be problems plaguing both of the high-profile cases that prompted this line of thinking.  But there’s otherwise no reason to think those are the only intermediate outcomes where velocity may matter directly.

Also, it turns out that great velocity isn’t required for HR/FB suppression, as a look at the leaderboard in recent years includes some notable non-flamethrowers like Stults, Weaver, and Fister.  Obviously the ballpark matters a lot, too.  But there are also hard throwers near the top, and overall I remained intrigued enough to keep digging.)

Realistically, if there is something there, Sabathia and Lincecum are probably on the more extreme end of the spectrum.  Probably there have been other guys who lost similar velocity but that we didn’t hear as much about because they were better able to adapt or otherwise did not see their overall results decline so dramatically.

What do the results indicate?  By and large, it does appear that velocity matters directly, in addition to strikeouts.  (Regression results below)

* = significant at 10%; ** = significant at 5%; *** = significant at 1%

I use 3 different estimation techniques for each outcome:

• Plain-old OLS
• Fixed effects (“FE”): estimates results within player, essentially comparing each pitcher’s own years of higher velocity/strikeouts against his years of lower velocity/strikeouts
• First difference (“FD”): the outcome is now the one-year change in HR/FB% (etc.) for Pitcher A, while the explanatory variables are the one-year change in K/9 and FBv for Pitcher A

Of these, methods 2 and 3 are probably more convincing, since they give results for the same player, where anything else that’s distinct to the player (but invariant over time) gets washed out.  OLS doesn’t do this, and instead mostly compares across players, who may have many differences besides strikeouts and velocity.  In an exaggerated illustration, if our full sample consisted only of Tim Hudson and Felix Doubront, the fact that Hudson is altogether a better pitcher, but sort of a “pitch-to-contact soft tosser,” can make it look like strikeouts/velocity are bad, using OLS, even if having more strikeouts/more velocity is actually good for either player.

Some technical notes:

• Sample includes player-seasons between 2010 and 2013 with at least 30 innings pitched
• Standard errors (not displayed) are clustered by player
• Don’t look too much into the fact that “FE” always gives the highest R2.  Most of this is from all the “specific player indicators” that are now present, rather than the “within-player” aspect, which is the actual point of using FE
• Starters and relievers are both included.  Part of me prefers to look at just starters, but this allows for much more observations and statistical power.  I’m also not controlling for starter/reliever status, so you’d need to believe that that only matters through its effects on strikeouts and velocity.

You can maybe argue that there are other explanatory variables that should have been included, or perhaps that one needs to be more judicious about the sample to consider.   (I must admit that I threw this together fairly quickly.)  But even if the current analysis is somewhat imperfect, it appears at least plausible that velocity matters directly (for various outcomes), in addition to the rate of strikeouts.

It’s a little too bad, because coming into this season I’d thought there was a decent chance of a Sabathia bounceback, given his partial velocity rebound as 2013 went along.  But that seems to have been only temporary.  While he still may wind up bouncing back when all is said and done, I’m definitely less optimistic than I was a week ago.  Will CC be this year’s version of 2013 Lincecum, who might even tease by FIP/xFIP but continue to underwhelm?

Leading into the currently-young 2014 season, one of the biggest stories in baseball was the rash of pitcher injuries — with UCL injuries and Tommy John surgery seeming unusually frequent this year.

For Patrick Corbin’s case, in particular, my immediate thought was “Hm, I recall he increased his velocity last year”… which of course led me to wonder if the velocity increase actually caused his injury in some way.

I don’t know how common this line of thinking is.  So far as I can tell, the discussion of velocity and injury more frequently goes the other way, that a velocity decrease may be the first sign that something is wrong.  Or maybe this is actually a more common suspicion than I realize.  If nothing else, it seems to merit a closer look/increased discussion.

The logic here is simple: for most players, velocity only seems to decrease from year to year (although it may increase within a season).  So when a player bucks the usual pattern and increases velocity between years, you have to wonder what exactly he did.  At least some of the time, guys may be cheating a little (doing something not entirely sound, mechanically) to get that extra “oomph.”  This is of course is where the injury part enters.  If indeed some guys are cheating, maybe it’s only a matter of time before they blow out an elbow (or shoulder).

So can a velocity increase be a sign that a guy’s cheating and thus a future injury risk?  Answering this thoroughly takes some time and effort, more than I can probably spare this week, but I thought I’d at the very least get some reader thoughts.  Eventually I hope to look at guys from many different seasons,  comparing the injury rate of guys who did vs. did not see a notable velocity increase the preceding season.  (I’ll be using this list of TJ patients, which seems fairly complete.  Probably it would be better to add shoulder injuries, too, if someone has a list.)

For those curious, here are the 2012 and 2013 velocities for the five big names of this year’s “Tommy John cohort.”  Unfortunately there’s hardly anything that can be taken away from such a small list.  Harvey and Corbin had velocity increases (consistent with the conjecture), while the others did not.  But Beachy was coming off a previous Tommy John surgery performed in 2012, while Medlen’s 2012 was partially in the bullpen, so it’s not exactly clear what to make of their 2012 vs. 2013 velocities.

(Overall FB velocities in this table.  Maybe it would have been better to just compare 4-seam vs. 4-seam, but I didn’t want to have to worry about composition for now.)

It might be a few weeks before I myself have time for a closer look.  BUT, if anyone else wants to spearhead the effort sooner, please feel free to do so, and I’m of course happy to help.  As always, reader thoughts and feedback are welcome!

From Opening Day to April 20th, Red Sox pitchers posted a 7.14 ERA when Jarrod Saltalamacchia was behind the plate versus a 2.40 ERA when Jason Varitek started. The resulting hubbub about this split made one fact extremely clear, when comparing the influence of different catchers, sample size is really really important.

Already by June 24th, Varitek and Salty’s split has been greatly reduced, with pitchers now throwing a 3.44 ERA to the veteran captain and a 4.36 ERA to the new guy. I would bet that these numbers will continue to converge as the season drags on, but even after 182 games it’s unlikely that either catcher will have enough innings to statistically test whether one is calling a better game. This is the difficulty of assessing catcher performance: comparing catchers between teams is near impossible (because the pitching staffs are different), and comparing catchers within teams is difficult (because sample sizes are small and different pitchers use different catchers). Nevertheless, many still believe that catchers do influence pitcher performance. Where can we find the data to support this hypothesis?

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