Predicting Time Lost to DL for Starting Pitchers

Before the beginning of the season several authors and readers did a no-transaction (even for injuries) WAR-based fantasy draft. I searched high and low for any kind of projection of time lost and found nothing. I had been thinking of creating a DL database and this goal finally put me over the edge and got me working on it. I didn't think the database would have generated the interested it created, but it is nice to know all those Google searches to determine what part of who's arm is got hurt was worth it. Now I am back looking into predicting time lost to injury and I will start with starting pitching.

I took all pitchers from 2002 to 2008 that pitched over 120 innings in one season and looked at the time lost to the DL in the next season. I looked at the player's age, BMI (Body Mass Index), innings pitched and if the player was on the DL the previous season.

 

I initially broke these categories individually up into small increments and then began to combine them into larger groups. I found that innings pitched the previous season didn't matter. I know that Tom Verducci found a small segment of young pitchers that increases in innings pitched can cause problems, but I was looking for more general trends.

 

Processing the data:

I ran many different queries on the data and ran many times into sample size issues. I ended up using just a few categories. I found that the average time spent for a pitcher on the DL after throwing 120 innings was 23.5 days. I divided the data into age, BMI and if there was an injury the previous season and here are the results:

 


Healthy Hurt 26 or less 27 to 33 34 or greater Low BMI High BMI
Average Days Lost per Season 22.39 30.57 22.83 23.03 31.62 23.37 25.83
Difference from Average Time on DL -1.10 7.08 -0.66 -0.46 8.13 -0.12 2.34

As it can be seen the most important factors were being 34 or older or hurt the previous season. Then I added the differences for all the above categories to the average number of days lost and got the following matrix to predict days on the DL:

 


26 and less Healthy 27 to 33 Healthy 34 or greater Healthy 26 and less Injured 27 to 33 Injured 34 and greater Injured
High BMI 24.07 24.27 32.86 32.24 32.44 41.03
Low BMI 21.62 21.81 30.4 29.79 29.99 38.58

 

Legend (Number of pitchers in the category are in parentheses. )

 

Age Categories

26 and less (187)

27 to 33 (382)

34 and older (112)

 

BMI categories (((weight)/(height*height))*703)

Low BMI < 25.5 (400)

High BMI >=25.5 (281)

 

Healthy = No no time on DL the previous season (515)

Hurt = Spent time on DL previous season (166)

 

Besides days lost, a team might need to know the chance of losing a pitcher for an extended period of time.

 

Here is the percent chance that a player will miss over 100 days in a season in each category with 8.1% the average chance of missing 100 days.

 


Healthy Hurt 26 or less 27 to 33 34 or greater Low BMI High BMI
% Chance to be on the DL for more than 100 days 6.4% 13.3% 6.4% 7.1% 14.3% 8.0% 8.2%
Difference from Average % Chance -1.7% 5.2% -1.7% -1.0% 6.2% -0.1% 0.1%

 

Combining each of the differences and adding them to the average time lost results in the following matrix showing percent chance of missing significant time.

 


26 and less Healthy 27 to 33 Healthy 34 or greater Healthy 26 and less Injured 27 to 33 Injured 34 and greater Injured
High BMI 4.9% 5.5% 12.7% 11.7% 12.4% 19.6%
Low BMI 4.7% 5.3% 12.5% 11.5% 12.2% 19.4%

 

Observations
  1. These numbers can be used to help predict how much pitching help a team will need during a season.

  2. It can also be used to see how luck or unlucky a team has been with injuries (or state how well a training staff is doing).

  3. I know that it is not rocket science saying that old,"big boned", injured players are going to spend more time on the DL than young, thin, healthy players. Now you know it will be on average 20 more days on the DL and there is a 15% greater chance they will spend significant time on the DL.

Of course I am open to comments and suggestions and come the 2010 Ball on a Budget draft, I will be armed with the data I need (along with everyone else, unfortunately.)

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