Little League pitch counts -- data vs decisions revisited

I posted recently on the new rules in pitch counts for Little League. I've had to defend my comments recently (in a polite way on this blog, and a bit more strenuously in person with friends who have sons pitching in LL), but was struck again about this issue while watching the LL World Series on ESPN.

On the ESPN web site I read this article on pitch counts, and found this comment on point:

What's interesting here is that the 20-pitch specialist is the residue of a change that did not, strictly speaking, emanate from problems within Little League itself. Around the coaching community, it is widely understood that the advent of nearly year-round travel (or "competitive") ball is one of the primary reasons for the rise in young arm problems. In some ways, Little League has made a pitch-count adjustment in reaction to forces that are beyond its control.

Travel ball has become an almost de facto part of a competitive player's baseball life -- just as it has in soccer, basketball and several other youth sports. An alphabet soup of sponsoring organizations, from AAU to USSSA, BPA and well beyond, offers the opportunity to play baseball at levels -- and sheer numbers of games -- that a previous generation of players would have found mind-boggling.

But travel ball is here to stay -- and so too, apparently, is a new approach by Little League to containing the potential damage to young arms. So get used to the 20-pitch kid. He's a closer on the shortest leash imaginable.

In other words, coaches know that it isn't pitch counts per se that cause the problems, but rather the number of months of the year the kids are pitching.

Interestingly, there is no ban on breaking pitches, though when I talk to coaches, there is speculation that these cause arm problems. In fact, on the Little League web site, they state:

While there is no medical evidence to support a ban on breaking pitches, it is widely speculated by medical professionals that it is ill-advised for players under 14 years old to throw breaking pitches,” Mr. Keener said. “Breaking pitches for these ages continues to be strongly discouraged by Little League, and that is an issue we are looking at as well. As with our stance on pitch counts, we will act if and when there is medical evidence to support a change.

I'm glad they are studying it, but the decision not to act to ban breaking pitches due to a lack of data is interesting since there is also a lack of data with pitch counts, but it didn't stop the officials from making rules there! Hopefully with the new pitch count rules, and the new data collected, we can see of the data bears out this hypothesis.

When Data and Decisions Don't Match--Little League Baseball

Maybe it's because I used to pitch in Little League when I was a kid, but this article in the July 1 Union Tribune really struck me. It describes how injuries to Little League pitchers has increased significantly over the past 10 years from one a week to 3-4 a day with elbow and/or shoulder injuries from baseball. What's the cause? Apparently, as the article indicates, it is from "overuse" (i.e., pitchers pitching too much). And here is the key statistic:

young pitchers who pitch more than 8 months a year are 5 times as likely to need surgery as those who pitch 5 1/2 months a year.

In San Diego, where I'm located, this can be a big problem because there is baseball going on all year round (even in Little League, where there are summer and fall leagues, plus the ever-present year-round traveling teams).

So what's the solution? A year ago or so they instituted an 85 pitch limit per game. Now, this may a good thing to do, but I have great difficulty seeing a direct connection. Here's why.

With any decision inferences (classification), there are two questions to be asked:
1) what patterns are related to the outcome of interest
2) are there differences between patterns related to the outcome of interest and those related to another outcome?

Here's my problem: I have seen no data (in the article) to indicate that pitchers today throw more pitches than boys did 10 years ago. And I see no evidence in particular that boys today throw more than 85 pitches more frequently that boys did 10 years ago. If this isn't the case, then why would the new limit have any effect at all? It can only be due to a cause that is not directly addressed here. If by limited pitches in a game (and therefore in any given week), the boys throw fewer pitches in a year, there might be an effect.

But based on the evidence that is known and not speculation, wouldn't it make more sense to limit pitchers to five months of pitching per calendar year? That after all has direct empirical evidence of tangible results.

I see this happen in the business world as well, where despite empirical evidence that indicate "Procedure A", the decision makers go with "Procedure B" for a variety of reasons unrelated to the data. And sometimes there is good reason to do so despite the data, but at least we should know that in these cases we are ignoring the data.

ENDNOTE:
I suspect one reason this strikes me is that I used to pitch on traveling teams in my Little League years, back before one cared about pitch counts (30+ years ago). I'm sure I pitched games well over 85, and probably 100+ pitches on a regular basis. One difference was that I lived in New England where you were fortunate to play March through August, and so we all had a good period of time to recover.

Quotes from Moneyball

I know it took me too long to do it, but I finally have read through Moneyball and thoroughly enjoyed it. There are several quotes from it that I thought captures aspects of the data mining attitude I think should be adopted.

On a personal note, I suppose my fascination with data analysis started when I was playing baseball in Farm League, and later with playing Strat-o-matic baseball. I received all the 1972 teams, and proceeded to try to play every team's complete schedule--needless to say, I didn't get too far. But more than playing the games, what I enjoyed most of all was computing the statistics and listing the leaders in the hitting and pitching categories. Once a nerd, always a nerd...

Here is the first quote:

Intelligence about baseball statistics had become equated in the public mind with the ability to recite arcane baseball stats. What [Bill] James's wider audience had failed to understand was that the statistics were beside the point. The point was understanding; the point was to make life on earth just a bit more intelligible; and that point, somehow, had been lost. 'I wonder,' James wrote, 'if we haven't become so numbed by all these numbers that we are no longer capable of truly assimilating any knowledge which might result from them.'