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CC BY-NC-ND 4.0 · Sports Med Int Open 2024; 08: a24016234
DOI: 10.1055/a-2401-6234
Training & Testing

Win Your Race Goal: A Generalized Approach to Prediction of Running Performance

Sandhyarani Dash
1   Electrical and Computer Engineering, Portland State University, Portland, United States
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Abstract

We introduce a novel approach for predicting running performance, designed to apply across a wide range of race distances (from marathons to ultras), elevation gains, and runner types (front-pack to back of the pack). To achieve this, the entire running logs of 15 runners, encompassing a total of 15,686 runs, were analyzed using two approaches: (1) regression and (2) time series regression (TSR). First, the prediction accuracy of a long short-term memory (LSTM) network was compared using both approaches. The regression approach demonstrated superior performance, achieving an accuracy of 89.13% in contrast, the TSR approach reached an accuracy of 85.21%. Both methods were evaluated using a test dataset that included the last 15 runs from each running log. Secondly, the performance of the LSTM model was compared against two benchmark models: Riegel formula and UltraSignup formula for a total of 60 races. The Riegel formula achieves an accuracy of 80%, UltraSignup 87.5%, and the LSTM model exhibits 90.4% accuracy. This work holds potential for integration into popular running apps and wearables, offering runners data-driven insights during their race preparations.

Keywords

running performance prediction - deep learning - running logs - ultramarathon - marathon


Publication History

Received: 20 May 2024
Received: 30 July 2024

Accepted: 31 July 2024

Article published online:
09 October 2024

© 2024. The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Georg Thieme Verlag KG
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Bibliographical Record
Sandhyarani Dash. Win Your Race Goal: A Generalized Approach to Prediction of Running Performance. Sports Med Int Open 2024; 08: a24016234.
DOI: 10.1055/a-2401-6234
 

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