Some things are great by themselves, but together they are even better. Peanut butter and chocolate: Reese Cups. Chips and cheese: nachos. Vodka and tomato juice: Bloody Mary. Man and spouse: chicka-chicka-bow-bow. Well, today I will take two of favorite baseball topics, aging curves and injuries for hitters, and combine them in an aging curve based on injury history.
A few years ago, I found one issue with projections, they did not know if a player played through an injury during the season. If a batter played through an injury, the next season the player would, on average, exceed his projection. The player was most likely to see an improvement in the power department.
Instead of collecting information on hitters who may have played through an injury, I just decided to look at players who were or weren’t on the DL over a matched season pair. I looked at four samples:
- Hitters who did not go on the DL in either season.
- Hitters who were on the DL in Year1, but not in Year2
- Hitters who were not on the DL in Year1, but in Year2
- Normal aging curves
I looked at the players’ wRC+ between the 2002 and 2013 season because my disabled list data only goes back that far. And finally, the curves with my normal aging curve disclaimer:
Note: The aging curve was created by the delta method by weighting plate appearances using their harmonic means. With this method, there’s a small survivor bias summarized by Mitchel Lichtman at the Hardball Times:
… survivor bias, an inherent defect in the delta method, which is that the pool of players who see the light of day at the end of a season (and live to play another day the following year) tend to have gotten lucky in Year 1 and will see a “false” drop in Year 2 even if their true talent were to remain the same. This survivor bias will tend to push down the overall peak age and magnify the decrease in performance (or mitigate the increase) at all age intervals.
The healthy and normal aging curves have the same shape with the healthy one having more up and down. It is not surprising the healthy-to-hurt curve is just a downward slope. Players perform worse when hurt and have the downward effects of aging working on them.
The key to the above data, for me at least, is the hurt-to-healthy curve. After age 25, the normal player aging pattern is a decline. Players who were hurt, but then healthy, recover just enough to deny aging, but not enough health to overtake the downward trend. The data shows that once the average player is hurt, they aren’t able to go back up to their old aging curve. Instead they have a new talent baseline which will start aging.
In the future, I plan on breaking down which injuries cause players to age more or less then others. Until, then enjoy some nachos, Reeses, a Boody Mary and some chicka-chicka-bow-bow. And most importantly, the DL aging curve.
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