Ribeiro Guilherme, De Aguiar Rafael Alves, Tramontin Artur Ferreira, Martins Eduardo Crozeta, Caputo Fabrizio
Human Performance Research Group, College of Health and Sport Science, Santa Catarina State University, Florianópolis, Brazil.
Physical Effort Laboratory, Sports Center, Federal University of Santa Catarina, Florianópolis, Brazil.
Percept Mot Skills. 2024 Aug;131(4):1274-1290. doi: 10.1177/00315125241247858. Epub 2024 Apr 18.
We investigated fatigue and performance rates as decision-making criteria in pacing control during CrossFit. Thirteen male regional-level competitors completed conditions of all-out (maximum physical work from beginning to end) and controlled-split (controlled physical work in the first two rounds but maximum work in the third round) pacing throughout the workout separated by one week. We assessed benchmarks, countermovement jumps and ratings of fatigue after each round. Benchmarks were lower in round 1 (99 vs. 114, < .001) but higher in rounds 2 (98 vs. 80, < .001) and 3 (97 vs. 80, < .001) for controlled-split compared with all-out pacing. Reductions in countermovement jumps were higher after rounds 1 (-12.6% vs. 1.6%, < .001) and 2 (-12.7% vs. -4.0%, = .014) but similar after round 3 (-13.2% vs. -11.3%, = .571) for all-out compared with controlled-split pacing. Ratings of fatigue were higher after rounds 1 (7 vs. 5 a.u., .001) and 2 (8 vs. 7 a.u, = .023) but similar after round 3 (9 vs. 9 a.u., = .737) for all-out compared with controlled-split pacing. During all-out pacing, countermovement jump reductions after round 2 correlated with benchmark drops across rounds 1 and 2 ( = .78, = .002) and rounds 1 and 3 ( = -.77, = .002) and with benchmark workout changes between pacing strategies ( = -.58, = .036), suggesting that the larger the countermovement jump reductions the higher the benchmark drops across rounds and workouts. Therefore, benchmarks, countermovement jumps and ratings of fatigue may assess exercise-induced fatigue as decision-making criteria to improve pacing strategy during workouts performed for as many repetitions as possible.
我们研究了疲劳和表现率，将其作为CrossFit训练中节奏控制的决策标准。13名男性地区级选手在为期一周的训练中，分别完成了全力（从头到尾进行最大强度体力活动）和控制拆分（前两轮进行控制强度的体力活动，但第三轮进行最大强度活动）两种节奏的训练。我们在每轮训练后评估了基准成绩、反向纵跳和疲劳评分。与全力节奏相比，控制拆分节奏在第1轮的基准成绩较低（99对114，<0.001），但在第2轮（98对80，<0.001）和第3轮（97对80，<0.001）较高。与控制拆分节奏相比，全力节奏在第1轮（-12.6%对1.6%，<0.001）和第2轮（-12.7%对-4.0%，=0.014）后反向纵跳的下降幅度更大，但在第3轮后相似（-13.2%对-11.3%，=0.571）。与控制拆分节奏相比，全力节奏在第1轮（7对5任意单位，<0.001）和第2轮（8对7任意单位，=0.023）后的疲劳评分更高，但在第3轮后相似（9对9任意单位，=0.737）。在全力节奏训练中，第2轮后的反向纵跳下降与第1轮和第2轮（=0.78，=0.002）以及第1轮和第3轮（=-0.77，=0.002）的基准成绩下降相关，并且与不同节奏策略之间的基准训练成绩变化相关（=-0.58，=0.036），这表明反向纵跳下降幅度越大，各轮和整个训练中的基准成绩下降越高。因此，基准成绩、反向纵跳和疲劳评分可作为评估运动引起的疲劳的决策标准，以改善在尽可能多轮次训练中的节奏策略。
