PURPOSE: To compare the dose-response relationship between traditional arbitrary speed thresholds versus an individualized approach, with changes in aerobic fitness in professional youth soccer players. METHODS: A total of 14 youth soccer players completed a 1500-m time trial to estimate maximal aerobic speed (MAS, km·h-1) at the start and at the end of a 6-week period. Training load was monitored on a daily basis during this study. External load measures were total distance covered and total acceleration and deceleration distance >2 m·s-2. Arbitrary high-speed running measures were meters covered and time spent at >17 km·h-1 (m > high-speed distance, t > high-speed distance) and 21 km·h-1 (m > very-high-speed distance, t > very-high-speed distance). Individualized high-speed running measures were meters covered and time spent at >MAS km·h-1 (m > MAS, t > MAS) and 30% anaerobic speed reserve (m > 30ASR, t > 30ASR). In addition, internal load measures were also collected: heart rate exertion and rating of perceived exertion. Linear regression analysis was used to establish the dose-response relationship between mean weekly training load and changes in aerobic fitness. RESULTS: Very large associations were found between t > MAS and changes in aerobic fitness (R2 = .59). Large associations were found for t > 30ASR (R2 = .38) and m > MAS (R2 = .25). Unclear associations were found for all other variables. CONCLUSION: An individualized approach to monitoring training load, in particular t > MAS, may be a more appropriate method than using traditional arbitrary speed thresholds when monitoring the dose-response relationship between training load and changes in aerobic fitness.
PURPOSE: To compare the dose-response relationship between traditional arbitrary speed thresholds versus an individualized approach, with changes in aerobic fitness in professional youth soccer players. METHODS: A total of 14 youth soccer players completed a 1500-m time trial to estimate maximal aerobic speed (MAS, km·h-1) at the start and at the end of a 6-week period. Training load was monitored on a daily basis during this study. External load measures were total distance covered and total acceleration and deceleration distance >2 m·s-2. Arbitrary high-speed running measures were meters covered and time spent at >17 km·h-1 (m > high-speed distance, t > high-speed distance) and 21 km·h-1 (m > very-high-speed distance, t > very-high-speed distance). Individualized high-speed running measures were meters covered and time spent at >MAS km·h-1 (m > MAS, t > MAS) and 30% anaerobic speed reserve (m > 30ASR, t > 30ASR). In addition, internal load measures were also collected: heart rate exertion and rating of perceived exertion. Linear regression analysis was used to establish the dose-response relationship between mean weekly training load and changes in aerobic fitness. RESULTS: Very large associations were found between t > MAS and changes in aerobic fitness (R2 = .59). Large associations were found for t > 30ASR (R2 = .38) and m > MAS (R2 = .25). Unclear associations were found for all other variables. CONCLUSION: An individualized approach to monitoring training load, in particular t > MAS, may be a more appropriate method than using traditional arbitrary speed thresholds when monitoring the dose-response relationship between training load and changes in aerobic fitness.
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