Semester

Spring

Date of Graduation

2026

Document Type

Dissertation

Degree Type

PhD

College

College of Applied Human Sciences

Department

Not Listed

Committee Chair

William Hornsby

Committee Member

Kristen Dieffenbach

Committee Member

Sean Bulger

Committee Member

Emidio Pistilli

Abstract

Utilizing a CMJ to test athlete physical abilities and training program efficacy is popular, as it is simple, noninvasive, and has significant relations with sport qualities. However, assessments often use discrete outcome measures. This research explored strategy-based measures accounting for eccentric power and time and may explain athlete status more effectively. The research objectives are to analyze the use of the mean power rate of the CMJ to compare athletes' playing ability and its usefulness in monitoring during off-season training. Additionally, power-time curve analysis added location and timing of effects due to fatigue or fitness adaptation. Proper testing and monitoring are essential for planning and preparing athletes for competition, avoiding unplanned fatigue, and increasing performance. A quantitative investigation incorporating a descriptive and observational exploration sampled 79 NCAA Division 1 football athletes throughout their off-season training. Force-time data was collected from CMJ testing throughout a 30-week off-season, including general to specific subperiods with 8 and 20-hour training weeks. A cross-sectional analysis of playing and position factors using MPR was measured using a 2x3 factorial ANOVA in a multiple regression framework. A second longitudinal study analyzed individual MPR measurements with x-bar process controls and waveform analysis. Waveform analysis was done with SPM on testing sessions that depicted training phases. Primary findings include a significant (p < 0.05) main effect of playing factor but not positional factor or interaction on MPR. Process control of 4 individuals chosen by the coaching staff yields no practical important changes greater than z = 2.0 or less than z = -2.0. Waveform analysis observed that 1 participant's power curve significantly altered during the preseason-specific training subphase (p < 0.01). The findings suggest MPR may be helpful in team testing and worth further investigation with more context-specific criteria for change. Waveform analysis may be best used for lesser-trained individuals and during acute-based interventions. Future research should consider time series analysis with baseline periods, if possible, sensitive measures of effect, and raw power-time analysis preserving data and time of movement.

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