Title

Sparta Testing and Vertical Jump Co-Predict Fastball Speed in Collegiate Pitchers

ORCID

J. Mark Van Ness: 0000-0001-5902-8735

Document Type

Conference Presentation

Department

Health, Exercise, and Sport Sciences Department

Conference Title

2018 ACSM National Conference

Organization

American College of Sports Medicine (ACSM)

Location

Minneapolis, MN

Conference Dates

May 29 - June 2, 2018

Date of Presentation

5-31-2018

Journal Publication

Medicine & Science in Sports & Exercise

ISSN

1530-0315

DOI

10.1249/01.mss.0000536546.60482.4b

Volume

50

Issue

5s

Publication Date

2018-05-01

First Page

445

Abstract

In competitive baseball, the most common pitch is the fastball; its velocity associates with strikeout rate and fielding-independent pitching values. The most effective predictors of pitch velocity are currently debated. Coaches and trainers are increasingly relying on advanced systems of assessment, such as Sparta Performance Science (SPS); fewer are relying on simple assessments, such as the vertical jump (VJ). Data supporting the added value of complex assessments are limited.

PURPOSE: To test the effect of VJ and SPS performances on fastball velocity among collegiate pitchers.

METHODS: We enrolled 30 pitchers at a Division 1 athletics program in Northern California. Every pitcher on the team’s roster between 2014 and 2017 was tested. During collection, heights and body weights were documented; an SPS force plate measured Load, Explode, and Drive data; and VJ height was recorded as the best of 3 performances. Fastball velocity was quantified as the mean mph of the fastest 3 in-game pitches at the time of testing. Multiple linear regression tested the effect of VJ and SPS data on pitch speed, controlling for appropriate confounders.

RESULTS: Players were evenly distributed throughout year in school. Average VJ was 19.8 ± 2.5 inches, fastball velocity was 87.4 ± 4.0 mph, SPS Load was 54.2 ± 8.6, Explode was 51.5 ± 8.4, and Drive was 54.2 ± 8.8. Multiple linear regression, holding the players’ height and grade constant, found each additional inch of VJ predicted a 0.5 mph increase in pitch velocity (p<0.001; 95% CI: 0.21-0.70). The collection of predictors explained 56% of the variance in speed (p<0.001). In this model, each additional unit of Load predicted a 0.2 mph decrease in speed (p<0.001) while each additional unit of Explode predicted a 0.2 mph increase (p<0.001). The most powerful predictor was year in school: for each additional year, fastball velocity increased by 2.1 mph (p<0.001). SPS Drive was not a significant predictor (p=0.491).

CONCLUSION: In the age of sophisticated analytics equipment, the VJ remains a compelling predictor of fastball velocity, but it predicts in tandem with the SPS technology. The information gathered from a comprehensive athletic evaluation can help coaches evaluate the athleticism of their athletes and inform decisions regarding individualized conditioning programs.

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