The potential impact of advanced footwear technology on the recent evolution of elite sprint performances

Can the recent sex-specific evolutions in elite running performances be attributed to advanced footwear technology?

Recent improvements in elite running performances across all distances have been largely attributed to the introduction of advanced footwear technology (AFT), which features a curved and stiff plate working synergistically with a new generation of midsole foams demonstrating enhanced resilience and compliance. These recent improvements appear to be considerably more pronounced in women's events, highlighted by improvements in road racing world records by an average of 3.7% (range: 2.6%-5.2%) compared to mean progressions of 1.5% (range: 1.3%-1.9%) in the same men's events. Although there is a growing body of research investigating the mechanisms underpinning running performance enhancements derived from AFT, there remains no explanation for potential sex-based differences in their benefits. We overview the currently available evidence and highlight why the recent direction of AFT research provides a barrier to progress by focusing primarily on male athletes. We subsequently provide our perspective on why women may be benefiting from the new generation of shoes more than men, suggest potential mechanisms leading to hypotheses that need to be further investigated in upcoming studies, and finally propose that factors outside of footwear innovation may have concurrently driven the recently observed performance evolutions.

Advancing 100m sprint performance prediction: A machine learning approach to velocity curve modeling and performance correlation

This study presents a novel approach to modeling the velocity-time curve in 100m sprinting by integrating machine learning algorithms. It critically addresses the limitations of traditional speed models, which often require extensive and intricate data collection, by proposing a more accessible and accurate method using fewer variables. The research utilized data from various international track events from 1987 to 2019. Two machine learning models, Random Forest (RF) and Neural Network (NN), were employed to predict the velocity-time curve, focusing on the acceleration phase of the sprint. The models were evaluated against the traditional exponential speed model using Mean Squared Error (MSE), with the NN model demonstrating superior performance. Additionally, the study explored the correlation between maximum velocity, the time of maximum velocity occurrence, the duration of the maximum speed phase, and the overall 100m sprint time. The findings indicate a strong negative correlation between maximum velocity and final time, offering new insights into the dynamics of sprinting performance. This research contributes significantly to the field of sports science, particularly in optimizing training and performance analysis in sprinting.

Does Advanced Footwear Technology Improve Track and Road Racing Performance? An Explorative Analysis Based on the 100 Best Yearly Performances in the World Between 2010 and 2022

Advanced footwear technology (AFT) is currently being debated in sports. There is a direct evidence that distance running in AFT improves running economy. In addition, there is indirect evidence from competition performance for improved running performance from using AFTs in middle- and long-distance running and sprinting events. However, the extent to which world-class performance is affected across the full range of track and road racing events between genders has not been systematically analyzed. This study examined publicly available performance datasets of annual best track and road performances for evidence of potential systematic performance effects following the introduction of AFT. The analysis was based on the 100 best performances per year for men and women in outdoor events from 2010 to 2022, provided by the world governing body of athletics (World Athletics). We found evidence of progressing improvements in track and road running performances after the introduction of AFT for road races in 2016 and AFT for track racing in 2019. This evidence is more pronounced for distances longer than 1500 m in women and longer than 5000 m in men. Women seem to benefit more from AFT in distance running events than men. For the sprint events (100 m to 400 m hurdles), the peak performance gains in 2021 and 2022 compared to the pre-AFT period ranged from 0.6 to 1.1% and from 0.4 to 0.7% for women and men, respectively. For middle-distance events (400 m to 3000 m steeplechase), peak performance gains ranged from 0.6 to 1.9% and from 0.6 to 0.7% for women and men, respectively. For distances from 5000 m to the marathon, performance gains ranged from 2.2% to 3.5% and 0.7% to 1.4% for women and men, respectively. While the observational study design limits causal inference, this study provides a database on potential systematic performance effects after introducing advanced shoes/spikes in track and road running events in world-class athletes. Further research is needed to examine the underlying mechanisms and, in particular, potential gender differences in the performance effects of AFT.