Life in the Fast Lane: Performance Predictions for the Newest 50-m Events on the Olympic Games Swimming Schedule

Abstract

Purpose: We aimed to (1) generate performance predictions for the new 50-m backstroke, breaststroke, and butterfly events, recently added to the Olympic Games swimming schedule, for both the Singapore 2025 World Aquatics Championships and the Los Angeles 2028 Olympic Games and (2) evaluate the accuracy of this already-established predictive model for these new events, using performances at the Singapore 2025 World Aquatics Championships as the criterion.

Methods: Race data from the 2011 to 2025 World Aquatics Championships were extracted and categorized into 3 performance categories: medalists (rank first to third), finalists but not medalists (rank fourth to eighth), and semifinalists but not finalists (rank ninth to 16th). An exponential-smoothing forecasting method in Microsoft Excel was used to predict future performances. Model accuracy was assessed by comparing predicted versus actual results from the Singapore 2025 World Aquatics Championships, using mean absolute error (MAE).

Results: The model demonstrated high predictive accuracy, with an overall average MAE of 0.94% (±0.58%). The lowest error was observed in the women's 50-m butterfly (rank first to third, MAE = 0.04%), with the highest error observed in the men's 50-m butterfly (rank first to third, MAE = 2.02%).

Discussion: These results confirm the utility of predictive analytics in elite swimming, supporting evidence-based decision making for coaches and national swimming federations. The model's high accuracy across the new 50-m form stroke events reinforces its value as a planning tool through the Los Angeles Olympic cycle.

Keywords: analytics; benchmarking; high-performance sport; modeling.