The Influence of Different Training Load Quantification Methods on the Fitness-Fatigue Model

Int J Sports Physiol Perform. 2021 Sep 1;16(9):1261-1269. doi: 10.1123/ijspp.2020-0662. Epub 2021 Mar 10.

Abstract

Purpose: Numerous methods exist to quantify training load (TL). However, the relationship with performance is not fully understood. Therefore the purpose of this study was to investigate the influence of the existing TL quantification methods on performance modeling and the outcome parameters of the fitness-fatigue model.

Methods: During a period of 8 weeks, 9 subjects performed 3 interval training sessions per week. Performance was monitored weekly by means of a 3-km time trial on a cycle ergometer. After this training period, subjects stopped training for 3 weeks but still performed a weekly time trial. For all training sessions, Banister training impulse (TRIMP), Lucia TRIMP, Edwards TRIMP, training stress score, and session rating of perceived exertion were calculated. The fitness-fatigue model was fitted for all subjects and for all TL methods.

Results: The error in relating TL to performance was similar for all methods (Banister TRIMP: 618 [422], Lucia TRIMP: 625 [436], Edwards TRIMP: 643 [465], training stress score: 639 [448], session rating of perceived exertion: 558 [395], and kilojoules: 596 [505]). However, the TL methods evolved differently over time, which was reflected in the differences between the methods in the calculation of the day before performance on which training has the biggest positive influence (range of 19.6 d).

Conclusions: The authors concluded that TL methods cannot be used interchangeably because they evolve differently.

Keywords: impulse response model; influence curves; performance modeling; performance prediction; training monitoring.

MeSH terms

  • Exercise
  • Fatigue
  • Heart Rate
  • Humans
  • Physical Conditioning, Human* / methods
  • Physical Exertion