Flexible modelling of time-varying exposures and recurrent events to analyse training load effects in team sports injuries

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Abstract

We present a flexible modelling approach to analyse time-varying exposures and recurrent events in team sports injuries. The approach is based on the piece-wise exponential additive mixed model where the effects of past exposures (i.e. high-intensity training loads) may accumulate over time and present complex forms of association. In order to identify a relevant time window at which past exposures have an impact on the current risk, we propose a penalty approach. We conduct a simulation study to evaluate the performance of the proposed model, under different true weight functions and different levels of heterogeneity between recurrent events. Finally, we illustrate the approach with a case study application involving an elite male football team participating in the Spanish LaLiga competition. The cohort includes time-loss injuries and external training load variables tracked by Global Positioning System devices, during the seasons 2017–2018 and 2018–2019.

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Zumeta-Olaskoaga, L., Bender, A., & Lee, D. J. (2025). Flexible modelling of time-varying exposures and recurrent events to analyse training load effects in team sports injuries. Journal of the Royal Statistical Society. Series C: Applied Statistics, 74(2), 391–405. https://doi.org/10.1093/jrsssc/qlae059

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