A recent article published in Sports Illustrated cited a trend in Major League Baseball where pitchers are throwing a higher percentage of breaking and other off-speed pitches than ever before. The rational for this trend is largely based on opponent batting average against different pitches (Figure 1). Breaking pitches are proving more effective at getting batters out and thus, are getting thrown more.
Figure 1. Opponents batting average by pitch type
The merit of this pitching strategy can be debated but it does bring up another question…
Could a change in pitch selection have an effect on the rate of Tommy John injuries?
Counter to common perception, every biomechanical analysis relating elbow torque to different pitch types has found that the fastball is the MOST stressful pitch [1,2,3]. This has included studies on both adults (Figure 2) and youth pitchers (Figure 3). Additionally open access data from Driveline Baseball, of pitchers throwing bullpens with the Motus sleeve, also supports this assertion [4]. Granted, this understanding of the effect of a pitch on an athlete’s elbow is based on what current analysis methods are able to calculate and does not fully characterize what is going on with specific ligaments or muscles. But based on what we know now, the fastball places the most load on pitchers elbow.
Note: Some studies have found that there is a correlation in youth pitchers between throwing breaking pitches and reported joint pain [5] while others have found no relationship [6]. The effect of breaking pitchers on a skeletally immature athlete is still not clearly understood, and for this reason, this analysis is ONLY intended to apply to adult pitchers.
Based on this information it stands to reason, If UCL tears are a result of repeated stress and micro-trauma on the elbow, would throwing less of the pitch causing the most stress reduce the risk of a pitcher having an elbow injury?
Although the difference between some pitches is small, even a small decrease in joint torque per pitch could make a significant impact in the cumulative load on the pitcher over the course of a game or season.
Procedure
To test my assumption, I created two groups of pitchers. One group is comprised of MLB starting pitchers who have undergone Tommy John surgery in the last year. The other group served as a control and had no history of Tommy John injury.
Nine starting pitchers at the MLB level were identified to have undergone Tommy John surgery in the last year (August 2017 – August 2016) from the online database maintained by Jon Roegele [7]. These pitchers made up the “Tommy John Injury” group (Table 1). Pitch data from this group was downloaded from Baseball Savant. If they had at least 5 starts in 2017, then 2017 pitching data was used, otherwise their 2016 data was used.
Table 1. Tommy John Group
Pitcher | Team | Age | Reconstruction Date |
Edison Volquez | MIA | 33 | 8/4/17 |
Joe Ross | WAS | 24 | 7/19/17 |
Michael Pineda | NYY | 28 | 7/18/17 |
Shelby Miller | ARI | 26 | 5/10/17 |
Cody Anderson | CLE | 26 | 3/27/17 |
Alex Reyes | STL | 22 | 2/16/17 |
Colin Rea | SD | 25 | 11/10/16 |
Nathan Eovaldi | NYY | 26 | 8/19/16 |
Nick Tropeano | LAA | 25 | 8/16/16 |
The control group was selected by choosing a starting pitcher, from the same team as each injured pitcher, who had the highest innings total in 2016 and had no previous Tommy John injury. The pitching data from 2016 for each of these pitchers was used for the analysis. Its important to note that this control group was selected based on no previous Tommy John reconstruction and does not take into account other injury history.
Non-Tommy John Group (Control Group)
Pitcher | Team | Age | 2016 Innings Pitched |
Tom Koehler | MIA | 31 | 176.2 |
Max Scherzer | WAS | 33 | 228.1 |
Masahiro Tanaka | NYY | 28 | 199.2 |
Robbie Ray | ARI | 25 | 174.1 |
Corey Kluber | CLE | 31 | 215.0 |
Carlos Martinez | STL | 25 | 195.1 |
Luis Perdomo | SD | 24 | 146.2 |
CC Sabathia | NYY | 37 | 179.2 |
Matt Shoemaker | LAA | 30 | 160.0 |
The downloaded data was analyzed in Python. All pitches in the analyzed season for each pitcher were separated into fastball or off-speed categories. The proportion of the total pitches that were fastballs and the average fastball velocity for each pitcher was recorded. The averages for the two groups are shown below (Table 3).
Results
Table 3. Tommy John vs Non- Tommy John group comparison
Tommy John Group | Non-Tommy John Group | |
Proportion Fastballs | 0.64 | 0.59 |
Avg. Fastball Velocity | 93.35 |
92.98 |


Discussion and Conclusion
The “Tommy John group” did in fact throw a higher proportion of fastballs and had a slightly higher average fastball velocity, however both results are within a reasonable range of error. For the injured group 64% of their pitches were fastballs compared to 59% for the “Non-Tommy John group”. The Tommy John group did have a slightly higher average velocity, however with the variance between subjects, the velocity between the groups is very comparable and likely isn’t a large factor between these two subject populations.
These results indicate that there might be some merit to the hypothesis that throwing more fastballs could increase the likelihood for injury. If the groups had comparable velocities, the group who threw more fastballs may be subjected to greater cumulative workloads. This is independent of any difference in pitch volume or biomechanical differences, and only accounts for official pitches thrown in a game.
Acute tears of the UCL, are believe to be caused by repetitive micro-trauma caused by the cumulative workload on a pitcher over a game, year, and career [6,8]. One study did investigate how pitcher workload related to injury risk but did not find a significant relationship [8]. This study didn’t take into account differences in biomechanics between the pitchers or types of pitches thrown which both affect the torque on the elbow. Certainly the biomechanics or pitching technique of the pitcher plays a large role in their risk for injury, however, this analysis does provide some preliminary evidence that pitch selection may be a factor that affects an athlete’s risk for injury as well. A larger investigation into how pitch selection affects both cumulative workload on the shoulder and elbow and its relationship to injury risk could yield valuable information.
This analysis is only intended to be a “pilot study” to see if the hypothesis has merit to be investigated more. The small group sizes creates opportunity for variant values to affect the mean, although none of the pitchers sampled had values that seemed too extreme. Additionally, although I was systematic in choosing the control group, without a true random pool, there could be some unintended selection bias.
References
- Fleisig, Glenn S., et al. “Kinetic comparison among the fastball, curveball, change-up, and slider in collegiate baseball pitchers.” The American journal of sports medicine 34.3 (2006): 423-430.
- Dun, Shouchen, et al. “A biomechanical comparison of youth baseball pitches: is the curveball potentially harmful?.” The American journal of sports medicine 36.4 (2008): 686-692.
- Nissen, Carl W., et al. “A biomechanical comparison of the fastball and curveball in adolescent baseball pitchers.” The American journal of sports medicine 37.8 (2009): 1492-1498.
- O’CONNELL, MICHAEL. “Fastballs vs. Offspeed Pitches – Comparative and Relative Elbow Stress.” Driveline Baseball, 11 July 2017. Web.
- Lyman, Stephen, et al. “Effect of pitch type, pitch count, and pitching mechanics on risk of elbow and shoulder pain in youth baseball pitchers.” The American journal of sports medicine 30.4 (2002): 463-468.
- Fleisig, Glenn S., and James R. Andrews. “Prevention of elbow injuries in youth baseball pitchers.” Sports health 4.5 (2012): 419-424.
- Roegele, Jon. Tommy John Surgery List. https://docs.google.com/spreadsheets/d/1gQujXQQGOVNaiuwSN680Hq-FDVsCwvN-3AazykOBON0/edit#gid=0
- Karakolis, Thomas, Shivam Bhan, and Ryan L. Crotin. “An inferential and descriptive statistical examination of the relationship between cumulative work metrics and injury in Major League Baseball pitchers.” The Journal of Strength & Conditioning Research 27.8 (2013): 2113-2118.