Forecasting of Injuries in Ethiopia Premier League: Time Series Model Analysis

Abstract

<i>Background</i>: Sport injury is an injury which is occurs in playing field maybe in training or competition. Epidemiology of sports injury on male footballer has been documented that injury incidences were 10-35 injuries per 1000 game hours. The main objective of our study is predicting the number of injuries for coming specific time by analyzing historical injury data obtained from team physicians. <i>Methods</i>: We collected historical injury data from the Ethiopia Premier League which is collected for 50 weeks, including the number of injuries, types of injuries, affected players, and duration of absence from play. We then selected an appropriate time series model for forecasting injuries based on the nature of the data and its patterns, considering potential models such as ARIMA (AutoRegressive Integrated Moving Average). After training the selected time series model using historical injury data and validating its performance by comparing predicted values with actual injury occurrences, we used it to forecast injuries for the upcoming seasons of the Ethiopia Premier League. <i>Results</i>: In Ethiopia the weekly average increment in sport injury from week 1to week 50 was 4.4. The maximum number of sport injury occurred on week 30. The series is not stationary at level, but the series is stationary at first difference. The selected model in this study was ARIMA (3,0,0) that has small AIC and BIC. Based on ARIMA (3,0,0) model the new sport injury in Ethiopia premier league was 13 injuries in week 51, and the forecasted number of injuries for the following weeks were 12, 12, 13, 11, 11, 10, 10, 10, and 10, respectively, up to week 60. <i>Conclusion</i>: our research finding indicates that, occurrence of sport injury will increase for coming weeks so that teams should implement injury prevention programs, prioritize rest and recovery, and ensure access to qualified medical staff for immediate care and rehabilitation.