Identifying the ideal weekly training load for in-game performance in an elite Brazilian soccer team

Luís Branquinho; Elias de França; José E Teixeira; Adriano Titton; Luís Fernando Leite de Barros; Pedro Campos; Daniel A Marinho; Pedro Forte; Erico Chagas Caperuto; Ronaldo Vagner Thomatieli Dos Santos; Ricardo Ferraz

doi:10.3389/fphys.2024.1341791

Identifying the ideal weekly training load for in-game performance in an elite Brazilian soccer team

Front Physiol. 2024 Mar 5:15:1341791. doi: 10.3389/fphys.2024.1341791. eCollection 2024.

Authors

Luís Branquinho^{1

2

3}, Elias de França⁴, José E Teixeira^{3

5

6}, Adriano Titton⁷, Luís Fernando Leite de Barros⁷, Pedro Campos⁷, Daniel A Marinho^{3

8}, Pedro Forte^{2

3

5

9

10}, Erico Chagas Caperuto¹¹, Ronaldo Vagner Thomatieli Dos Santos⁴, Ricardo Ferraz^{3

8}

Affiliations

¹ Agrarian School of Elvas, Polytechnic Institute of Portalegre, Portalegre, Portugal.
² CI-ISCE-ISCE Douro, Penafiel, Portugal.
³ Research Center in Sports Sciences, Health Sciences and Human Development, Covilhã, Portugal.
⁴ Department of Biosciences, Federal University of São Paulo, São Paulo, Brazil.
⁵ Sport Sciences and Physical Education Department, Polytechnic Institute of Bragança, Bragança, Portugal.
⁶ Sport Department, Polytechnic Institute of Guarda, Guarda, Portugal.
⁷ São Paulo Futebol Clube, São Paulo, Brazil.
⁸ University of Beira Interior, Covilhã, Portugal.
⁹ Sport Department, Higher Institute of Educational Sciences of the Douro, Penafiel, Portugal.
¹⁰ LiveWell-Research Centre for Active Living and Wellbeing, Polytechnic Institute of Bragança, Bragança, Portugal.
¹¹ Human Movement Laboratory, São Judas University, São Paulo, Brazil.

Abstract

Introduction: The purpose of this study was to investigate the ideal training load to be applied during periods of fixture congestion to ensure an adequate dose-response effect for performance maintenance. Methods: Match performance data and corresponding pre-match training load sessions (both N = 498 match performance cases and training-block session cases) were collected (with the catapult system, VECTOR7) from 36 male professional soccer players (23.5 ± 5.2 years; 178 ± 4 cm; 75.5 ± 6.0 kg) belonging to the Brazilian First Division team during the 2022 season. The following data were collected in match and training sessions: jump, acceleration, deceleration, and change of direction (COD); running distance producing metabolic power at different intensities (>20, >20-35, >35-45, >45-55, and >55 W kg^-1), total distance (m), relative distance (m/min), running distance at different speeds (>20, >25, and >30 km/h), number of sprints (running >25 km/h), and maximum speed (km/h). Mixed linear model (MLM), decision tree regression (DTR), and cluster K means model (SPSS v.26) approach were performed to identify the most critical variables (and their respective load) in the training sessions that could explain the athlete's match performance. Results: MLM and DTR regression show that training load significantly affects game performance in a specific way. According to the present data, an interference phenomenon can occur when a high load of two different skills (running in a straight line vs COD, deceleration, and jumping) is applied in the same training block of the week. The cluster approach, followed by a chi-squared test, identified significant associations between training load and athlete match performance in a dose-dependent manner. Discussion: The high load values described here have a beneficial effect on match performance, despite the interference between stimuli discussed above. We present a positive training load from a congested season from the Brazilian First Division team. The study suggests that an interference effect occurs when high physical training loads are applied to different specific physical skills throughout the season.

Keywords: fixture congestion; load; match demands; soccer; training.

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work is supported by national funding through the Portuguese Foundation for Science and Technology, I.P., under project UID04045/2020 and Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP—Grant number: 2021/03601-1).