Mathieu Heijboer

Team Jumbo-Visma · Performance

We present a personalized approach for frequent fitness monitoring in road cycling solely relying on sensor data collected during bike rides and without the need for maximal effort tests. We use competition and training data of three world-class cyclists of Team Jumbo–Visma to construct personalised heart rate models that relate the heart rate duri...

In sports, athlete monitoring is important for preventing injuries and optimizing performance. The multitude of relevant factors during the exercise sessions, such as weather conditions, makes proper individual athlete monitoring labour intensive. In this work, we develop an automated approach for athlete monitoring in professional road cycling tha...

With the recent explosive developments in sensoring capabilities and ubiquitous computing in road cycling, large quantities of detailed data about performance are becoming available. In this paper, we will demonstrate that this rich data in cycling offers several non-trivial data science challenges. The primary task that we focus on is a regression...

With the recent explosive developments in sensoring capabilities and ubiquitous computing in road cycling, large quantities of detailed data about performance are becoming available. In this paper, we will demonstrate that this rich data in cycling offers several non-trivial data science challenges. The primary task that we focus on is a regression...

This study aims to describe the intensity and load demands of different stage types within a cycling Grand Tour. Nine professional cyclists, whom are all part of the same World-Tour professional cycling team, participated in this investigation. Competition data were collected during the 2016 Giro d’Italia. Stages within the Grand Tour were classifi...

This study examined if short-duration record power outputs can be predicted with the Anaerobic Power Reserve (APR) model in professional cyclists using a field-based approach. Additionally, we evaluated if modified model parameters could improve predictive ability of the model. Twelve professional cyclists (V̇O2max 75 ± 6 ml∙kg⁻¹∙min⁻¹) participate...

This study evaluated the changes in ratios of different intensity (rating of perceived exertion; RPE, heart rate; HR, power output; PO) and load measures (session-RPE; sRPE, individualized TRIMP; iTRIMP, Training Stress Score™; TSS) in professional cyclists. RPE, PO and HR data was collected from twelve professional cyclists (VO2max 75 ± 6 ml∙min∙k...

Purpose: To assess if short duration (5 to ~300 s) high-power performance can accurately be predicted using the anaerobic power reserve (APR) model, in professional cyclists. Method: Data from four professional cyclists from a World Tour cycling team were used. Using the maximal aerobic power, sprint peak power output and an exponential constant...

Background: There is conflicting literature on the effect of strength training on road cycling performance, with the most recent literature showing a positive effect with maximal strength training (Rønnestad & Mujika, 2013: Scan J Med Sci Sports, Aug 5. doi: 10.1111/sms.12104). Most of these studies are flawed in that they compare strength training...