Race Classification

When a new cycling session is uploaded, Vekta’s machine learning classification algorithm analyzes the session's power data to determine if it’s a training session or a race. This classification is based on the stochastic patterns in the power data, capturing the unique demands of racing.

Once a session is identified as a race, Vekta’s model further categorizes it by type—such as Individual Time Trial (ITT), flat, hilly, or mountain stage.

For race sessions, Vekta performs additional analyses to extract key metrics, including:

• Number of Climbs: Detects and counts significant climbs within the race.

• Climb Statistics: Provides a detailed breakdown of all detected climbs, such as length, elevation gain, and average grade.

These metrics allow you to instantly access relevant statistics and compare similar events in greater detail (for more, see Race Comparison).

With Vekta’s race classification, understanding race demands and comparing events becomes seamless.