Baseball demands speed, power, and quickness. To perform at a high level, and avoid injuries that are common among baseball players, an evaluation of current trends in strength and conditioning practices is helpful. Based on the demands of the sport and the injury risks, qualified strength and conditioning professionals can develop effective baseball-specific conditioning programs. This commentary briefly covers historical aspects of baseball conditioning, recent injury trends, current practices among elite baseball professionals, and provides suggestions for future improvements in training.
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Baseball-Specific Conditioning
Matthew R. Rhea and Derek Bunker
Predictors of Fielding Performance in Professional Baseball Players
Gerald T. Mangine, Jay R. Hoffman, Jose Vazquez, Napoleon Pichardo, Maren S. Fragala, and Jeffrey R. Stout
The ultimate zone-rating extrapolation (UZR/150) rates fielding performance by runs saved or cost within a zone of responsibility in comparison with the league average (150 games) for a position. Spring-training anthropometric and performance measures have been previously related to hitting performance; however, their relationships with fielding performance measures are unknown.
Purpose:
To examine the relationship between anthropometric and performance measurements on fielding performance in professional baseball players.
Methods:
Body mass, lean body mass (LBM), grip strength, 10-yd sprint, proagility, and vertical-jump mean (VJMP) and peak power (VJPP) were collected during spring training over the course of 5 seasons (2007–2011) for professional corner infielders (CI; n = 17, fielding opportunities = 420.7 ± 307.1), middle infielders (MI; n = 14, fielding opportunities = 497.3 ± 259.1), and outfielders (OF; n = 16, fielding opportunities = 227.9 ± 70.9). The relationships between these data and regular-season (100-opportunity minimum) fielding statistics were examined using Pearson correlation coefficients, while stepwise regression identified the single best predictor of UZR/150.
Results:
Significant correlations (P < .05) were observed between UZR/150 and body mass (r = .364), LBM (r = .396), VJPP (r = .397), and VJMP (r = .405). Of these variables, stepwise regression indicated VJMP (R = .405, SEE = 14.441, P = .005) as the single best predictor for all players, although the addition of proagility performance strengthened (R = .496, SEE = 13.865, P = .002) predictive ability by 8.3%. The best predictor for UZR/150 was body mass for CI (R = .519, SEE = 15.364, P = .033) and MI (R = .672, SEE = 12.331, P = .009), while proagility time was the best predictor for OF (R = .514, SEE = 8.850, P = .042).
Conclusions:
Spring-training measurements of VJMP and proagility time may predict the defensive run value of a player over the course of a professional baseball season.
Automatic Detection of Pitching and Throwing Events in Baseball With Inertial Measurement Sensors
Nick B. Murray, Georgia M. Black, Rod J. Whiteley, Peter Gahan, Michael H. Cole, Andy Utting, and Tim J. Gabbett
Purpose:
Throwing loads are known to be closely related to injury risk. However, for logistic reasons, typically only pitchers have their throws counted, and then only during innings. Accordingly, all other throws made are not counted, so estimates of throws made by players may be inaccurately recorded and underreported. A potential solution to this is the use of wearable microtechnology to automatically detect, quantify, and report pitch counts in baseball. This study investigated the accuracy of detection of baseball pitching and throwing in both practice and competition using a commercially available wearable microtechnology unit.
Methods:
Seventeen elite youth baseball players (mean ± SD age 16.5 ± 0.8 y, height 184.1 ± 5.5 cm, mass 78.3 ± 7.7 kg) participated in this study. Participants performed pitching, fielding, and throwing during practice and competition while wearing a microtechnology unit. Sensitivity and specificity of a pitching and throwing algorithm were determined by comparing automatic measures (ie, microtechnology unit) with direct measures (ie, manually recorded pitching counts).
Results:
The pitching and throwing algorithm was sensitive during both practice (100%) and competition (100%). Specificity was poorer during both practice (79.8%) and competition (74.4%).
Conclusions:
These findings demonstrate that the microtechnology unit is sensitive to detect pitching and throwing events, but further development of the pitching algorithm is required to accurately and consistently quantify throwing loads using microtechnology.
Measuring Circadian Advantage in Major League Baseball: A 10-Year Retrospective Study
W. Christopher Winter, William R. Hammond, Noah H. Green, Zhiyong Zhang, and Donald L. Bliwise
Purpose:
The effect of travel on athletic performance has been investigated in previous studies. The purpose of this study was to investigate this effect on game outcome over 10 Major League Baseball (MLB) seasons.
Methods:
Using the convention that for every time zone crossed, synchronization requires 1 d, teams were assigned a daily number indicating the number of days away from circadian resynchronization. With these values, wins and losses for all games could be analyzed based on circadian values.
Results:
19,079 of the 24,121 games (79.1%) were played between teams at an equal circadian time. The remaining 5,042 games consisted of teams playing at different circadian times. The team with the circadian advantage won 2,620 games (52.0%, P = .005), a winning percentage that exceeded chance but was a smaller effect than home field advantage (53.7%, P < .0001). When teams held a 1-h circadian advantage, winning percentage was 51.7% (1,903–1,781). Winning percentage with a 2-h advantage was 51.8% (620–578) but increased to 60.6% (97–63) with a 3-h advantage (3-h advantage > 2-hadvantage = 1-h advantage, P = .036). Direction of advantage showed teams traveling from Western time zones to Eastern time zones were more likely to win (winning percentage = .530) than teams traveling from Eastern time zones to Western time zones (winning percentage = .509) with a winning odds 1.14 (P = .027).
Conclusion:
These results suggest that in the same way home field advantage influences likelihood of success, so too does the magnitude and direction of circadian advantage. Teams with greater circadian advantage were more likely to win.
Changes in a Starting Pitcher’s Performance Characteristics Across the Duration of a Major League Baseball Game
David Whiteside, Douglas N. Martini, Ronald F. Zernicke, and Grant C. Goulet
Purpose:
With a view to informing in-game decision making as it relates to strategy and pitcher health, this study examined changes in pitching-performance characteristics across 9 innings of Major League Baseball (MLB) games.
Methods:
129 starting MLB pitchers met the inclusion criteria for this study. Pitch type, speed, ball movement, release location, and strike-zone data—collected using the MLB’s ball-tracking system, PITCHf/x—were obtained for 1,514,304 pitches thrown from 2008 to 2014.
Results:
Compared with the 1st inning, the proportion of hard pitches thrown decreased significantly until the 7th inning, while the proportions of breaking and off-speed pitches increased. Significant decreases in pitch speed, increases in vertical movement, and decreases in release height emerged no later than the 5th inning, and the largest differences in all variables were generally recorded between the 1st inning and the late innings (7–9). Pitchers were most effective during the 2nd inning and significantly worse in innings 4 and 6.
Conclusion:
These data revealed that several aspects of a starting pitcher’s pitching characteristics exhibited changes from baseline as early as the 2nd or 3rd inning of an MLB game, but this pattern did not reflect the changes in his effectiveness. Therefore, these alterations do not appear to provide reasonable justification for relieving a starting pitcher, although future work must address their relevance to injury. From an offensive standpoint, batters in the MLB should anticipate significantly more hard pitches during the early innings but more breaking and off-speed pitches, with decreasing speed, as the game progresses.
Influence of the Reactive Strength Index Modified on Force– and Power–Time Curves
John J. McMahon, Paul A. Jones, Timothy J. Suchomel, Jason Lake, and Paul Comfort
greater for soccer athletes than baseball athletes, despite the baseball athletes jumping higher due to their significantly longer TTT. 5 The latter example illustrates that CMJ height and RSImod are distinct variables. With this in mind, the mechanisms that underpin a higher RSImod by achieving a higher
Marathon Specialization in Elites: A Head Start for Africans
Tyler J. Noble and Robert F. Chapman
, swimming, baseball, tennis, and golf . J Gerontol . 1988 ; 43 : 113 – 120 . PubMed doi:10.1093/geronj/43.5.P113 10.1093/geronj/43.5.P113 19. Tanaka H , Seals DR . Endurance exercise performance in masters athletes: age-associated changes and underlying physiological mechanisms . J Physiol . 2008
An Integrated, Multifactorial Approach to Periodization for Optimal Performance in Individual and Team Sports
Iñigo Mujika, Shona Halson, Louise M. Burke, Gloria Balagué, and Damian Farrow
approach called “decision training,” which is essentially the opposite of the behavioral training approach. That is, the instructions started with greater complexity, practice was more random/variable, and reduced levels of delayed feedback were provided. Baseball batters reflective of novice, intermediate
Effects of Performing Isometric Bench Press Training at Single Versus Multiple Joint Positions on Strength and Power Performance
Danny Lum, Swee Keng Soh, Cheryl J.H. Teo, Olivia Q.H. Wong, and Marcus J.C. Lee
showed that a sample size of at least n = 16 was required to obtain a statistical power of 0.85. Sixteen male competitive softball and baseball athletes (age: 24.1 [3.6] y, height: 1.73 [4.0] m, body mass: 76.4 [11.4] kg; pitchers: n = 4, position players: n = 12) who have been participating in
The Effects of Modified-Implement Warm-Ups on Cricket Pace-Bowling Skill
Simon A. Feros, Kris Hinck, and Jake Dwyer
speed in baseball, 5 , 6 javelin, 7 shot put, 8 and discus. 9 Modified-implement training has predominantly featured in the physical training literature of pace bowling, 10 – 12 with increases in bowling speed of 3.5 to 4 km/h reported after 8 to 10 weeks; albeit equivocal results surrounding
