Context: Tennis athletes are often exposed to rigorous training workloads. Recently, authors have used rate of perceived exertion (RPE) to track internal training load in athletes using a metric known as the acute to chronic workload ratio (ACWR). Research reported on team sports have determined that if the acute workload is higher than the chronic workload athletes are likely to sustain injury. No studies, however, have attempted to investigate internal workload and injury in a tennis population despite the rigorous training loads. Therefore, the purpose of this study was to determine if high chronic workloads compared to small spikes in acute workloads decrease the risk of injury in adolescent tennis players. Methods: Thirty-two junior tennis players (11 Female; 21 male, 15±2years) were recruited from one tennis academy to participate in a 23-week cohort study. Rate of perceived exertion workload data were collected every day after training/match sessions. Players were instructed to provide a subjective rating of RPE (range:0-10) as an estimate of training intensity. Session RPE (sRPE), a measure of internal workload was calculated by multiplying the training/ match session RPE by the session duration in minutes. Players self-reported their injuries using Athlete Monitoring Software; however, the research team was actively involved in following up with all players in regard to any documented injuries. Injury was defined as any non-contact injury that resulted in 1 or more missed training sessions, or a loss of match time. The ACWR was the primary independent variable and was categorized into weekly blocks running from Monday to Sunday. Acute workload was determined as the total sRPE for one week, while a 4-week rolling average sRPE represented chronicqworkload. A Cox proportional hazard model was used to determine if ACWR from the previous week was a significant predictor of injury the following week when controlling for age, sex, previous injury history, and years of experience. The SPSS complex sampling procedures was used to control for violations of independent observations that are unavoidable with longitudinal injury data. Results: Sixteen participants sustained injuries during the observation period. The model indicated that ACWR from the previous week and previous history of injury were significant predictors of injury the following week (Wald F 130 = 9.407;p<0.01 and Wald F 130 = 5.028; p=0.03, respectively). In the week preceding injury, the average ACWR was 1.57±0.90. Conclusions: Our study indicates that injured players did 1.5 times more work in the past week due to the previous 4 weeks. Thus, the players that went on to sustain an injury were not prepared for the workload endured. These results were similar to previous studies investigating ACWR where large change in workload were associated with increased injury risk.
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