Heat across five editions of an ultra-distance ride
Finished
Which edition of the Madrid-Barcelona by Pedalma was the hottest, and where on the route does the heat hit? A comparison built from my own GPS files.
Data science, applied maths and modelling for professional cycling.
velodata answers the questions of cycling teams, brands, race organisers and sports-tech companies with data: how hard a stage is for each rider, whether a product claim holds, why riders abandon a race.
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What velodata does
01
Race and course analysis
Stage and course difficulty, heat and weather along the route, and who abandons a race, when and why.
02
Equipment testing
Statistical comparison of bikes, wheels and tyres, and review of product claims: what a test can really prove.
03
Prediction and rider selection
Expected results stage by stage, and support for deciding who to line up.
04
Modelling and machine learning
Made-to-measure projects: mathematical and statistical modelling, prediction, reinforcement learning and computer vision.
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Behind velodata
velodata is the work of Juanfran Garamendi: a PhD in Computer Science & Mathematical Modelling, 15+ years in data science and applied mathematics, 35+ scientific publications and 3 patents. More in About.
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