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Validity of a Field-Based Critical Velocity Test on Predicting 5,000-Meter Running Performance

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2019, Master of Education (MEd), Bowling Green State University, Human Movement, Sport and Leisure Studies /Kinesiology.
Statement of Problem: Quantifying adaptations and predicting performance are important aspects of an endurance training program. Thus, the purpose of this investigation was to assess the validity of a field-based critical velocity (CV) test on predicting 5,000 m running performance. This study examined the agreement between predicted and actual 5,000 m running performance, as well as the agreement between CV and actual 5,000 m velocity. Methods: Five runners (VO2peak 60.14 ± 4.96 ml•kg-1•min-1) completed a graded exercise test to determine VO2peak, a CV test to predict performance, and a 5,000 m time-trial. The CV assessment protocol included three time-trials of 3,600 m, 2,400 m, and 1,200 m at maximal exertion on a standard 200 m indoor track. Running performance was predicted using the distance-time model where CV was given by the slope and the anaerobic work capacity (D’) was given by the intercept from linear regression analysis of distance covered against time for each of the three time-trials. Results: Results indicated no significant difference between predicted 5,000 m performance (18.28 ± 4.38 min) and actual 5,000 m performance (18.17 ± 4.07 min), t(4) = 0.58, p = 0.594, d = 0.26. The mean difference in performance was 0.11 ± 0.42 min [LoA, -0.71 min, 0.93 min]. CV (4.59 ± 0.88 m•sec-1) was significantly slower than actual 5,000 m velocity (4.73 ± 0.82 m•sec-1), t(4) = -3.081, p < 0.05, d = -1.37. The mean difference in velocity was -0.14 m•sec-1 ± .10 m•sec-1 [LoA, -0.34 m•sec-1, 0.06 m•sec-1]. Conclusion: 5,000 m running performance can be accurately predicted using a field-based approach to measure CV and D’. This finding demonstrates that a valid performance prediction and fitness assessment can be made in a relatively short period of time without the need for access to expensive laboratory equipment.
Adam Fullenkamp, Ph.D. (Advisor)
Jessica Kiss, Ph.D. (Committee Member)
Matt Laurent, Ph.D. (Committee Member)
72 p.

Recommended Citations

Citations

  • Voth, N. (2019). Validity of a Field-Based Critical Velocity Test on Predicting 5,000-Meter Running Performance [Master's thesis, Bowling Green State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu155838890107422

    APA Style (7th edition)

  • Voth, Nicholas. Validity of a Field-Based Critical Velocity Test on Predicting 5,000-Meter Running Performance. 2019. Bowling Green State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=bgsu155838890107422.

    MLA Style (8th edition)

  • Voth, Nicholas. "Validity of a Field-Based Critical Velocity Test on Predicting 5,000-Meter Running Performance." Master's thesis, Bowling Green State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu155838890107422

    Chicago Manual of Style (17th edition)