Quantifying the Training-Intensity Distribution in Middle-Distance Runners: The Influence of Different Methods of Training-Intensity Quantification
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Purpose: To compare the training-intensity distribution (TID) across an 8-week training period in a group of highly trained middle-distance runners employing 3 different methods of training-intensity quantification. Methods: A total of 14 highly trained middle-distance runners performed an incremental treadmill test to exhaustion to determine the heart rate (HR) and running speed corresponding to the ventilatory thresholds (gas-exchange threshold and respiratory-compensation threshold), as well as fixed rating of perceived exertion (RPE) values, which were used to demarcate 3 training-intensity zones. During the following 8 weeks, the TID (total and percentage of time spent in each training zone) of all running training sessions (N = 695) was quantified using continuous running speed, HR monitoring, and RPE. Results: Compared with the running-speed-derived TID (zone 1, 79.9% [7.3%]; zone 2, 5.3% [4.9%]; and zone 3, 14.7% [7.3%]), HR-demarcated TID (zone 1, 79.6% [7.2%]; zone 2, 17.0% [6.3%]; and zone 3, 3.4% [2.0%]) resulted in a substantially higher training time in zone 2 (effect size ± 95% confidence interval: −1.64 ± 0.53; P < .001) and lower training time in zone 3 (−1.59 ± 0.51; P < .001). RPE-derived TID (zone 1, 39.6% [8.4%]; zone 2, 31.9% [8.7%]; and zone 3, 28.5% [11.6%]) reduced time in zone 1 compared with both HR (−5.64 ± 1.40; P < .001) and running speed (−5.69 ± 1.9; P < .001), whereas time in RPE training zones 2 and 3 was substantially higher than both HR- and running-speed-derived zones. Conclusion: The results show that the method of training-intensity quantification substantially affects computation of TID.
Bellinger, Arnold, and Minahan are with Griffith Sports Physiology and Performance, Griffith University, Gold Coast, QLD, Australia. Bellinger is also with Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia.
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