Batter Injuries and Future Performance

Predicting hitter injuries has been a fool’s errand for me. Besides players with chronic injuries (e.g. Albert Pujols and Ryan Braun), others and myself have made little headway in the field. With few guidelines, many fantasy analysts and owners handle hitter injuries differently. Previously, I focused on a hitter’s recent injury history. This time I attempted a different approach and used the hitter’s career IL days. In the end, I found a useful and easy to remember injury threshold.

For the study, I examined hitters from the 2010 to 2018 seasons. I have IL data going back to 2002, so I hoped the preceding eight years of data would get most of the hitter’s 2010 career total. Additionally, I needed the next season (e.g. 2019) to compare results. Additionally, I set a minimum hitting threshold (100 PA) to include at least some semi-regulars. I know I may miss a hitter who is out the whole season, but the two-week callups were diluting the results. In all, I ended up with a sample of 2365 player seasons.

I had no idea where to start, so I split the hitters at 30-years-old and then bucketed them into 100 IL day bins.

Hitter Production & Playing Risk for Accumulated IL Days
Under 30 Average Diff Median Diff
Avg Age Total IL Days Avg wRC+ wRC+ PA IL Days wRC+ PA IL Days
27.5 >= 400 87.0 2.8 -34.8 15.4 2.8 14.0 15.0
27.9 300-399 93.1 -18.5 -99.6 41.0 -13.8 -143.0 16.0
27.9 200-299 94.5 0.0 27.5 17.1 -2.3 21.0 11.0
27.3 100-199 94.0 -4.4 17.0 19.4 1.1 8.5 0.0
26.2 <100 90.2 -5.8 -6.9 14.0 -4.0 -7.0 0.0
30 & over Average Diff Median Diff
Avg Age Total IL Days Avg wRC+ wRC+ PA IL Days wRC+ PA IL Days
33.8 >= 400 85.8 -13.0 -82.2 29.6 -13.5 -85.0 20.0
33.0 300-399 91.0 -12.1 -51.7 24.1 -12.4 -53.0 12.5
33.3 200-299 90.0 -9.8 -54.5 21.4 -8.4 -41.0 10.0
33.0 100-199 90.6 -9.8 -43.6 14.6 -6.5 -39.5 0.0
32.3 < 100 86.3 -11.3 -67.6 11.6 -7.1 -39.0 0.0

The results for the over-30 crowd are nice and clean with gradual changes as the IL days increase. The year-to-year changes are almost twice as bad for the over 400 IL day group compared to the 100 to 199-day group.

As for the younger hitters, what a mess. The over 400 days can almost be ignored based on a small sample size. The average IL days are a rollercoaster up and down. There needs to be more bundling to find anything useful here.

I changed the threshold around a bit and found an ideal split to be around 280 accumulated IL days. I decided to round up to 300 days and here are the results.

Hitter Production & Playing Risk for Accumulated IL Days
Under 30 Average Diff Median
Avg Age Total IL Days Avg wRC+ wRC+ PA IL Days wRC+ PA IL Days
27.7 >= 300 90.5 -9.4 -72.1 30.1 -5.8 -49.0 15.5
26.4 < 300 90.9 -5.4 -2.4 14.8 -3.5 -5.0 0.0
30 & Over Average Diff Median
Avg Age Total IL Days Avg wRC+ wRC+ PA IL Days wRC+ PA IL Days
33.3 >= 300 88.6 -12.5 -65.8 26.6 -12.9 -59.0 16.0
32.7 < 300 88.3 -10.5 -57.5 14.3 -8.8 -46.5 0.0

I’m not surprised but the hitters under 30 are experiencing the same production decline and playing time reduction as their older counterparts. The 300-day threshold doesn’t discriminate. Once a player reaches the 300 game threshold, he is likely to at least spend at least some time on the IL.

Remember, the decline doesn’t start exactly at the 300 game threshold. Hitters in the 200 to 299 range are seeing their skills and playing time degrade at an increasing rate. There is always a grey area … always.

For reference, here are the hitters who have reached the 200 IL day threshold along with their age and average NFBC ADP (top-100 picks highlighted).

2020 Hitters with 200 or More IL Days
Name Age IL Days NFBC ADP
Jed Lowrie 36 701 601
Greg Bird 27 526 601
Ryan Zimmerman 35 524 576
Travis d’Arnaud 31 496 267
Francisco Cervelli 34 487 600
Howie Kendrick 36 480 389
Pablo Sandoval 33 436 601
A.J. Pollock 32 409 332
Jason Castro 33 408 395
Alex Dickerson 30 396 569
Wilson Ramos 32 369 173
Jurickson Profar 27 364 431
Matt Duffy 29 364 601
Giancarlo Stanton 30 350 65
Adam Eaton 31 346 198
Hunter Pence 37 341 522
Cameron Maybin 33 328 484
Shin-Soo Choo 37 320 212
Franchy Cordero 25 316 426
Daniel Murphy 35 296 264
Matt Wieters 34 285 587
Aaron Hicks 30 282 476
Robinson Chirinos 36 281 294
Michael Brantley 33 274 121
Wil Myers 29 272 259
Avisail Garcia 29 267 206
Ehire Adrianza 30 258 591
Eric Sogard 34 257 533
Jorge Soler 28 256 83
Tommy Pham 32 256 77
David Peralta 32 254 240
Edwin Encarnacion 37 252 153
Christian Vazquez 29 249 212
Brandon Nimmo 27 248 385
Jake Lamb 29 243 452
Mitch Moreland 34 240 523
Nelson Cruz 39 240 68
Corey Dickerson 31 239 254
Tommy La Stella 31 238 358
Jose Iglesias 30 237 532
David Dahl 26 231 139
Elias Diaz 29 230 570
Alex Avila 33 225 584
Alex Gordon 36 225 539
Garrett Cooper 29 225 468
Brock Holt 32 220 599
Evan Longoria 34 219 420
Stephen Vogt 35 219 505
Brett Gardner 36 215 366
Tim Beckham 30 215 601
Yadier Molina 37 214 232
Kevan Smith 32 212 601
Joey Votto 36 210 278
Dexter Fowler 34 209 550
Brian McCann 36 200 599

Most of these hitters have been declining for years and are being rostered late in drafts. Not all though. Four hitters are being taken in the top-100. Nelson Cruz was able to stay healthy once he became a full-time DH, so he’s been an exception to the general decline. Maybe Jorge Soler won’t decline since he’s primarily a DH now. Giancarlo Stanton and Tommy Pham are the two early picks who owners will be counting on for production and may end up with less than expected. Both need to be rostered at a discount.

Overall, I’m happy with the results. I have an actionable range and expected decline. With the drop being around three points of wRC+, an owner can drop the hitter’s prorated production by 3% across the board along with the playing time. The adjustment doesn’t mean the hitter is undraftable, they just need to come at a discount.

After diving back into the IL work, I saw a couple of other areas to improve on.

A one-off study that might work is weighting the recent seasons more than the others. I’m not sure what is the best method to approach the problem. I have too much on my plate right now (i.e. 2021 version of The Process) to just fart around making up numbers.

Another factor that I’m not able to take into account but I believe is important is surgeries. A hitter could have played through an injury, sat most of September (no IL needed), and then had offseason surgery. They would not be included in the preceding analysis. The problem is collecting the surgery information.

That’s it for now. I may come back to this topic soon but I want to take a stab at pitcher injuries again along and hopefully start prepping for the season’s start.

We hoped you liked reading Batter Injuries and Future Performance by Jeff Zimmerman!

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Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won three FSWA Awards including on for his MASH series. In his first two seasons in Tout Wars, he's won the H2H league and mixed auction league. Follow him on Twitter @jeffwzimmerman.

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dl80
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dl80

Jeff, great article here. Really interesting and useful analysis. Thanks!