AUTHOR=Croteau Félix , Gaudet Sylvain , Briand Jeremy , Clément Julien TITLE=Case study of IMU loads and self-reported fatigue monitoring of water polo goalkeepers preparing for the Olympic games JOURNAL=Frontiers in Sports and Active Living VOLUME=5 YEAR=2023 URL=https://www.frontiersin.org/journals/sports-and-active-living/articles/10.3389/fspor.2023.1198003 DOI=10.3389/fspor.2023.1198003 ISSN=2624-9367 ABSTRACT=Introduction

Measurement of training in water polo goalkeepers has focused first on psycho-physiological variables, but also on external volume estimated with wearable sensors. However, there are limited studies exploring training monitoring in water polo goalkeepers longitudinally.

Methods

Three female senior national team goalkeepers participated in this study from May to August 2021. Internal loads were defined using session rating of perceived exertion (sRPE). Tri-axial accelerations and angular velocities were measured with an inertial measurement unit (IMU) placed on the lower back to measure external loads. Relationships between self-reported and IMU-derived metrics were explored using Spearman correlations. Two-way ANOVAs were used to assess differences between session types and between athletes.

Results

In total, 247 sessions were collected (159 practices, 67 matches and 21 game warm up), with 155 sessions having complete data. IMU metrics, such as number of kicks, number of jumps or player-load showed high correlation with each other (ρ = 0.80–0.88). There was also a moderate correlation (ρ = 0.47, 95% CI = 0.33–0.58) between sRPE and player-load measured with the IMU. ANOVA tests showed that there were significant differences between athletes for sRPE (p < 0.01) but not for player load (p = 0.47). There were no interactions between athletes and training types, except for index score (p < 0.01).

Conclusions

This study shows that monitoring of training loads can be performed successfully in water polo goalkeepers using a combination of self-reported and IMU measures. Self-reported outcomes can be expected to vary significantly across athletes within the same session, while IMU metrics vary across training situations. Finally, coaches should be mindful of missing data, as they can skew the interpretation of training loads.