Starting Pitcher Disabled List Analysis (1 of 3)

This is the first in what will be a series on the disabled list. Here’s a link to the data.

I recently posted a projection formula (here and here) that estimated the chance of a starting pitcher spending time on the disabled list. To say the least, it generated several questions.

So I’m going to take a step back and show historic DL numbers for starting pitchers. For the purpose of this post, I’m only looking at pitchers with 20-plus starts and more than 120 innings from the previous season.

Going back to 2001, there were 947 pitchers who didn’t retire and met the criteria for starts and innings. In addition to basic DL information (trips to the disabled list, days on the list), I collected data on other non-game-related statistics, including height, weight, college, high school and even country of origin. It was an exhaustive compilation.

The primary drawback with DL data is pretty obvious: there aren’t many seasons of it. Nine, to be exact – from 2002 to 2010. For my research, I want at least three years of disabled-list data on each player but since I only have nine seasons of that information that means I can only look at six years of samples. (I won’t have sufficient DL statistics for pitchers from 2002 to 2004.)

Height and weight numbers were collected to get an idea of the pitcher’s frame. Teams most-certainly bias those values to make players appear bigger and stronger, and they don’t account for changes over a career. But even with this bias, they give a good, rough estimate of the player’s frame. With this in mind, I calculated each pitcher’s body mass index. This gave me a general idea about how their individual weight is distributed across their bodies.

As part of this experiment, I’m introducing what I call “Average Disabled List Expectancy.” ADLE is the number of expected DL days for a pitcher. It’s a simple calculation that takes the percent chance of a player going on the disabled list and multiplying that by the average number of days for each DL trip.

Here’s what I discovered:

The key numbers here is that 39% of all starting pitchers will end up on the DL the following season after being a starter in the league the year before. Those injuries will result in an average of 66.3 days lost per trip, which calculates to an ADLE of 25.9.

Three other values stick on from this list. Younger pitchers average fewer days on the DL, which shouldn’t be surprising. Perhaps the most obvious part of this research is that the older a player gets, the higher the chance of a that player getting hurt. Also, players who weigh more than 210 lbs (BMI greater than 26.5 for the average height of 74.8”) are more likely to find themselves on the DL.

To get an understanding of how the days lost on the DL are distributed, here’s a chart grouping the days lost into 15-day intervals.

That is all for today. Tomorrow I will look at each attribute separately.

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Jeff writes for FanGraphs, The Hardball Times and Royals Review, as well as his own website, Baseball Heat Maps with his brother Darrell. In tandem with Bill Petti, he won the 2013 SABR Analytics Research Award for Contemporary Analysis. Follow him on Twitter @jeffwzimmerman.

6 Responses to “Starting Pitcher Disabled List Analysis (1 of 3)”

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  1. S.X.M. says:

    The DL average days doesn’t seem very instructive. There’s obviously a lot of long term injuries like Tommy John surgery or shoulder injuries like Brandon Webb. The better solution than a simple average would be to break it down by injury and expected loss. Most of what you’re saying here was said at BPro here:

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  2. Wally says:

    To me, the obvious first place to start is trying to ask the question of: Do DL trips in the past predict DL trips in the future?

    You could subdivide this basic question a lot of ways, like setting up cut offs for 50+ day DL trips predicting 50+ day DL trips, various other young vs. old comparisons, and like SXM said, if certain types of initial injuries predict more injuries of the same kind or even different ones, in the future.

    Lots to be done here. And building a good data base from which you can launch all these different types of questions is often greatly under-appreciated.

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  3. shthar says:

    the only sure indicator of future injuries, is past injuries.

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  4. B N says:

    While I’m not convinced this is a very good way to predict factors that underlie DL trips, I do think that this gives a decent idea of things that DON’T affect DL trips actually. Looking at these things, height and weight at least don’t seem to be particularly important- which is something I’ve seen claimed before.

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