Monitoring training load in beach volleyball players: a case study with an Olympic team

Abstract

Aim: Describe and compare training load dynamics of two Olympic beach volleyball players. Methods: Two Olympic beach volleyball players participated in this study (specialist defender and blocker: both aged 34 years, holding 14 years of competitive experience, height: 1.74 m and 1.81 m, weight: 69 kg and 65 kg, respectively). Internal training load (ITL), total weekly training load (TWTL), monotony and strain were obtained through the session rating of perceived exertion (session-RPE) for three training mesocycles (10 weeks). Lower limb explosive power was assessed through the counter movement jump (CMJ). Results: Mean ITL, TWTL, monotony and strain during the 10week period were: 370 ± 156; 1997 ± 838; 2.7 ± 1.3; 5621 ± 1802 arbitrary units (AU) (Defender) and 414 ± 153; 2392 ± 892; 2.7 ± 1.1; 6894 ± 3747 (AU) (Blocker). Mean of CMJ height was 47.0 ± 1.3 and 40.3 ± 1.6 cm, for the defender and blocker, respectively. The defender player presented higher ITL in the second (effect size (ES) = 0.90; 92/5/3, likely) and in the third (ES = 0.91; 94/4/2, likely) mesocycles when compared to the first. Monotony raised from the first to the third mesocycle (ES = 2.91; 98/1/1, very likely). Blocker's ITL was higher in the third mesocycle than the first (ES = 1.42. 98/1/1, very likely) and the second (ES = 1.49; 98/1/1, likely) ones. Conclusion: ITL magnitude increased from the first to the third mesocycle, in both players.

Current Approaches to the Use of Artificial Intelligence for Injury Risk Assessment and Performance Prediction in Team Sports: a Systematic Review

“…In beach volleyball players, the monitoring data from wearable sensors has been used to model the injury risk via artificial neural network [68]. These studies highlight the importance of adequate management of training load in these sports too [99–101] along with the use of technology and innovative approaches in data management in order to protect the athletes’ health [102, 103].…”

External training load and the effects on training response following three different training sessions in young elite beach volleyball players

“…Works analyzing ITL in beach volleyball 7,15 with the use of s-RPE refer to an imbalance between loading and recovery to evolve non-functional overreaching and overtraining. 7 These authors moreover suggest sudden changes in training load (Acute-Chronic ratio) as risk factor but omit marker or load specifications for training monitoring. In this investigation, the number of total actions and total time under action was similar between the different session types.…”

“…8,9 The reduced number of players and larger area to cover increase the individual stress level during training and competition compared to regular volleyball settings. 10,7 In order to monitor internal training response, different markers (session rate of perceived exertion [s-RPE], Delayed onset of muscle soreness [DOMS] and creatinkinase [CK]) were analyzed for indoor volleyball 8,11,12 but only one work evaluated elite beach volleyball players. 7 The authors identified different levels of s-RPE among blockers and defenders and between different mesocycles within a 10 week observation in a case study of 2 elite players.…”

“…10,7 In order to monitor internal training response, different markers (session rate of perceived exertion [s-RPE], Delayed onset of muscle soreness [DOMS] and creatinkinase [CK]) were analyzed for indoor volleyball 8,11,12 but only one work evaluated elite beach volleyball players. 7 The authors identified different levels of s-RPE among blockers and defenders and between different mesocycles within a 10 week observation in a case study of 2 elite players. 7 ETL quantification in volleyball recently evolved from video-based 13–15 to sensor-based procedures, 16–19 aiming to record jump events during training or competition.…”

“…7 The authors identified different levels of s-RPE among blockers and defenders and between different mesocycles within a 10 week observation in a case study of 2 elite players. 7 ETL quantification in volleyball recently evolved from video-based 13–15 to sensor-based procedures, 16–19 aiming to record jump events during training or competition. Thus, jump volume was object to many works about external training load determination in indoor volleyball.…”