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Lower Extremity Biomechanics Predicts Major League Baseball Player Performance

BACKGROUND: Although lower extremity biomechanics has been correlated with traditional metrics among baseball players, its association with advanced statistical metrics has not been evaluated. PURPOSE: To establish normative biomechanical parameters during the countermovement jump (CMJ) among Major...

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Autores principales: Teske, Lucas G., Beck, Edward C., Bullock, Garrett S., Nicholson, Kristen F., Waterman, Brian R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: SAGE Publications 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8274116/
https://www.ncbi.nlm.nih.gov/pubmed/34291115
http://dx.doi.org/10.1177/23259671211015237
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author Teske, Lucas G.
Beck, Edward C.
Bullock, Garrett S.
Nicholson, Kristen F.
Waterman, Brian R.
author_facet Teske, Lucas G.
Beck, Edward C.
Bullock, Garrett S.
Nicholson, Kristen F.
Waterman, Brian R.
author_sort Teske, Lucas G.
collection PubMed
description BACKGROUND: Although lower extremity biomechanics has been correlated with traditional metrics among baseball players, its association with advanced statistical metrics has not been evaluated. PURPOSE: To establish normative biomechanical parameters during the countermovement jump (CMJ) among Major League Baseball (MLB) players and evaluate the relationship between CMJ-developed algorithms and advanced statistical metrics. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: MLB players in 2 professional organizations performed the CMJ at the beginning of each baseball season from 2013 to 2017. We collected ground-reaction force data including the eccentric rate of force development (“load”), concentric vertical force (“explode”), and concentric vertical impulse (“drive”) as well as the Sparta Score. The advanced statistical metrics from each baseball season (eg, fielding independent pitching [FIP], weighted stolen base runs [wSB], and weighted on-base average) were also gathered for the study participants. The minimal detectable change (MDC) was calculated for each CMJ variable to establish normative parameters. Pearson coefficient analysis and regression trees were used to evaluate associations between CMJ data and advanced statistical metrics for the players. RESULTS: A total of 151 pitchers and 138 batters were included in the final analysis. The MDC for “load,” “explode,” “drive,” and the Sparta Score was 10.3, 8.1, 8.7, and 4.6, respectively, and all demonstrated good reliability (intraclass correlation coefficient > 0.75). There was a weak but statistically significant correlation between the Sparta Score and wSB (r = 0.23; P = .007); however, there were no significant correlations with any other advanced metrics. Regression trees demonstrated superior FIP with higher Sparta Scores in older pitchers compared with younger pitchers. CONCLUSION: There was a positive but weak correlation between the Sparta Score and base-stealing performance among professional baseball players. Additionally, older pitchers with a higher Sparta Score had statistically superior FIP compared with younger pitchers with a similar Sparta Score after adjusting for age.
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spelling pubmed-82741162021-07-20 Lower Extremity Biomechanics Predicts Major League Baseball Player Performance Teske, Lucas G. Beck, Edward C. Bullock, Garrett S. Nicholson, Kristen F. Waterman, Brian R. Orthop J Sports Med Article BACKGROUND: Although lower extremity biomechanics has been correlated with traditional metrics among baseball players, its association with advanced statistical metrics has not been evaluated. PURPOSE: To establish normative biomechanical parameters during the countermovement jump (CMJ) among Major League Baseball (MLB) players and evaluate the relationship between CMJ-developed algorithms and advanced statistical metrics. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: MLB players in 2 professional organizations performed the CMJ at the beginning of each baseball season from 2013 to 2017. We collected ground-reaction force data including the eccentric rate of force development (“load”), concentric vertical force (“explode”), and concentric vertical impulse (“drive”) as well as the Sparta Score. The advanced statistical metrics from each baseball season (eg, fielding independent pitching [FIP], weighted stolen base runs [wSB], and weighted on-base average) were also gathered for the study participants. The minimal detectable change (MDC) was calculated for each CMJ variable to establish normative parameters. Pearson coefficient analysis and regression trees were used to evaluate associations between CMJ data and advanced statistical metrics for the players. RESULTS: A total of 151 pitchers and 138 batters were included in the final analysis. The MDC for “load,” “explode,” “drive,” and the Sparta Score was 10.3, 8.1, 8.7, and 4.6, respectively, and all demonstrated good reliability (intraclass correlation coefficient > 0.75). There was a weak but statistically significant correlation between the Sparta Score and wSB (r = 0.23; P = .007); however, there were no significant correlations with any other advanced metrics. Regression trees demonstrated superior FIP with higher Sparta Scores in older pitchers compared with younger pitchers. CONCLUSION: There was a positive but weak correlation between the Sparta Score and base-stealing performance among professional baseball players. Additionally, older pitchers with a higher Sparta Score had statistically superior FIP compared with younger pitchers with a similar Sparta Score after adjusting for age. SAGE Publications 2021-07-08 /pmc/articles/PMC8274116/ /pubmed/34291115 http://dx.doi.org/10.1177/23259671211015237 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by-nc-nd/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 License (https://creativecommons.org/licenses/by-nc-nd/4.0/) which permits non-commercial use, reproduction and distribution of the work as published without adaptation or alteration, without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage).
spellingShingle Article
Teske, Lucas G.
Beck, Edward C.
Bullock, Garrett S.
Nicholson, Kristen F.
Waterman, Brian R.
Lower Extremity Biomechanics Predicts Major League Baseball Player Performance
title Lower Extremity Biomechanics Predicts Major League Baseball Player Performance
title_full Lower Extremity Biomechanics Predicts Major League Baseball Player Performance
title_fullStr Lower Extremity Biomechanics Predicts Major League Baseball Player Performance
title_full_unstemmed Lower Extremity Biomechanics Predicts Major League Baseball Player Performance
title_short Lower Extremity Biomechanics Predicts Major League Baseball Player Performance
title_sort lower extremity biomechanics predicts major league baseball player performance
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8274116/
https://www.ncbi.nlm.nih.gov/pubmed/34291115
http://dx.doi.org/10.1177/23259671211015237
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