ORIGINAL RESEARCH article
Front. Sports Act. Living
Sec. Sports Science, Technology and Engineering
Volume 7 - 2025 | doi: 10.3389/fspor.2025.1681444
This article is part of the Research TopicEmerging technologies in sports performance: data acquisition and analysisView all 10 articles
Early Marathon Running Metrics from Inertial Measurement Units Predict Significant Pace Reduction
Provisionally accepted
- 1Institute of Sport Science, ASICS, Kobe, Japan
- 2Faculty of Data Science, Shiga University, Hikone, Japan
- 3Faculty of Education, Wakayama University, Wakayama, Japan
- 4Data Science and AI Innovation Research Promotion Center, Shiga University, Hikone, Japan
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Marathon runners occasionally experience significant pace reduction in the latter stages of races, a phenomenon known as 'hitting the wall'. This study aimed to develop an interpretable model to predict this performance decline using biomechanical variables collected during the early stages of marathons. We analyzed data from 1,437 runners collected during official marathon events held in Japan from August 2022 to May 2025. Biomechanical variables were measured using inertial measurement unit attached to the runners' lower back. 'Hitting the wall' was defined as maintaining a pace exceeding 125% of the average pace from 5 to 20 km continuously for more than 5 km after the 25 km point. Conversely, runners were classified as 'NOT hitting the wall' if their pace remained less than 110% of the average pace for more than 10 km. Cases not meeting either criterion were excluded from analysis, resulting in 306 positive cases and 359 negative cases. We applied functional principal component analysis to efficiently handle time-series data and developed a functional logistic regression model using data from the first half of marathons to predict the severe pace reduction. Our model achieved 73.9% accuracy, 75.8% recall, and 70.1% precision. Analysis of coefficient functions in the functional logistic regression model revealed that step length, ground contact time, and vertical stiffness were the strongest predictors of subsequent performance decline. The identified biomechanical signatures could inform personalized training strategies aimed at preventing the 'hitting the wall' phenomenon during marathon races.
Keywords: hitting the wall, Inertial measurement unit, Marathon, Pacing strategy, Functionaldata analysis
Received: 07 Aug 2025; Accepted: 30 Sep 2025.
Copyright: © 2025 Miyazaki, Matsui, Zushi and Fukui. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Yosuke Miyazaki, yosuke.miyazaki@asics.com
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.