The Strava app logo (Image credit: Getty Images)
By Tom Davidson
published 24 February 2025
Exercise tracking app Strava has clamped down on “unrealistic” performances being uploaded to its leaderboards, as part of a new update.
The company is now using machine learning to analyse activities, taking into account “57 factors” such as speed and acceleration.
Among its goals, Strava said in a statement, is to determine if any portion of an activity was recorded in a vehicle, in a bid to improve the integrity of its leaderboards.
“Strava has improved leaderboard quality and identifies unrealistic speeds, GPS errors and other anomalies that could skew leaderboard results,” the statement said. “This aims to keep the competition on the app fair for all athletes by removing outliers and potential rule violations.“If the system detects a vehicle, the activity is flagged, and the user is prompted to crop it or make it private.”Strava users collect crowns, known as KOMs and QOMs , for posting the fastest time on segments. If a person believes a certain performance is not credible, they are encouraged to flag the activity within the app.According to Strava, users are now flagging 72% fewer activities as suspected to have been carried out “in a vehicle” since the update rolled out. Get The Leadout Newsletter The latest race content, interviews, features, reviews and expert buying guides, direct to your inbox!Contact me with news and offers from other Future brandsReceive email from us on behalf of our trusted partners or sponsorsBy submitting your information you […]
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