The purposes of this study were to determine the reliability of the bat swing (BS) and rotational medicine ball throw (RMBT) load-velocity profiling (LVP) methods and the relationships between LVP variables and batting performance in NCAA Division I softball players. Current NCAA Division I softball athletes participated in this study. Bat velocity was tracked with a swing sensor during the BS method. An inertial measurement unit (IMU) tracked forearm velocity during the BS and RMBT methods. Two-way intraclass correlation coefficients (ICC) were used for relative reliability and coefficient of variation (CV) was used for absolute reliability. For the BS method with the swing sensor, relationships between the multiple- and two-load models and between LVP variables and batting variables were examined using Pearson's correlation coefficients. During the RMBT method and BS method using the IMU, no LVP variables were reliable (ICC = 0.7; CV = 15%). For the BS method with the swing sensor, all bat loads and V0 had acceptable reliability using peak velocity (PV) and average peak velocity (PVavg) (ICC > 0.7; CV < 15%). All LVP variables were highly related between the multiple- and two-load models when utilizing PV and PVavg (r = 0.915-0.988; p < 0.01). There were significant relationships (r = 0.603-0.671; p < 0.05) between PV using the 0.99 kg bat load and slugging percentage and on-base plus slugging, and between V0 and doubles, runs batted in, and total bases. Neither the RMBT method nor the BS method using the IMU provided reliable LVP variables. All bat velocities were highly reliable during the BS method using the swing sensor, while only V0 provided acceptable reliability. Practitioners may utilize the two-load model when utilizing the BS method using the swing sensor, although further research is needed to examine the relationship between LVP variables and batting performance.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1694 |
| Date | 01 January 2021 |
| Creators | Herring, Chad |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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