Author(s): TUBAGI POLITO, L.F., SOLER, P., GONÇALVES, P., PIGNATA JUNIOR, W., SAKANO, R., CARNEIRO, Y., MONTENEGRO, C., SESMA, E., BRANDÃO, M., Institution: SÃO JUDAS TADEU UNIVERSITY OF SÃO PAULO, Country: BRAZIL, Abstract-ID: 2547

INTRODUCTION:
The load control and monitoring are strategies applied for optimizing performance and reducing the risk of injuries and any other medical complications resulting from excessive training. This way, there were a lot of instruments scientifically validated which proposed to provide important information to physical coaches about the readiness, fatigue, sleep, recovery, stress, and pain of the athletes. Nonetheless, despite the large amount of available parameters for athletes’ analysis, its integration in the training and match routine is a hard task. Thus, the purpose of the current research is to provide preliminary validation evidence of Risk and Performance Circumplex Model (RPCM).
METHODS:
Sixteen highly trained futsal athletes (age: 17 + 0.65 years; total body mass: 73 + 8,49kg; height: 1,74 + 0,06m; workout weekly minimal volume: 720min) were evaluated during one week of a Futsal National League. The evaluations involved: (1) Hooper Index; Total Quality of Recovery; Muscles and Joints Pain; (2) Heart Rate Variability (HRV); (4) Countermovement Jump (CMJ). The RPCM was calculated through the integrated values of Hooper Index and Total Quality of Recovery. The statistical analysis was done using the GraphPad Prism Software (version 8.0). After data exclusion of those who did not complete all the data collect (less than 25% of the entire sample), and the identification of the outliers, using the Rout Test, the normality of data was tested using the Shapiro-Wilk Test. Thus, besides the descriptive statistical analysis, to analyze the relation among RPCM and the other objective variables (HRV, TBM and CMJ), it was used the Spearman’s Correlation (p < 0.05).
RESULTS:
For sleep, stress, fatigue, pain, total quality of recovery, risk index and performance index, the following data were found, respectively: 4.09 + 0.73; 4.08 + 0.80; 4.06 + 0.89; 3.75 + 1.01; 16.45 + 2.24; -5.14 + 3.13; 5.04 + 3.29. For the objective variables, the following data were found, respectively: 34.87 + 4.84 (CMJ); 89.45 + 42.87 (HRV - RMSSD); 1.12 + 0.64 (HRV - LF/HF); 79.89 + 29.95 (HRV - SDNN).
CONCLUSION:
Although no significant correlations between the risk and performance indices (calculated through the RPCM), and the objective variables (CMJ and HRV) were found, some characteristics of RPCM provide preliminary scientific evidence of its validation, including: (1) the integration of the subjective and objective variables on just one instrument provided a practical instrument to be analyzed faster during the training routine, enabling more accurate decision-making; (2) the performance and risk index (both calculated by the RPCM) were enough to minimize the risk of injuries, and therefore, in order to improve the active and healthy participation of the athletes in the tournament, In which the team were the champion without a single injured athlete.