A dashboard built for women's racing

Datashift built a dedicated stage-by-stage BI dashboard for AG Insurance–Soudal's women's team, shaped around how the women’s team actually races. After each stage, coaches get an updated view of rider performance and recovery, giving sport directors the insights they need to make informed decisions between stages of a multi-stage race.
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New metrics

The dashboard pulls finish positions and results from Pro Cycling Stats, the online database that tracks rankings live. It combines this with TrainingPeaks data to surface the key performance and training metrics a trainer needs to assess the team’s performance such as the training stress score, variability index, ... . Together with the trainers, we also designed a new metric: Matches Burned, counting how often a rider spikes above the desired boundaries, a proxy for wasted energy the coach used to judge ad hoc or by eye.

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Putting effort into context

For Matches Burned, we also chose to show where those efforts happened during the race. This provides visibility into what happened during the early part of a race, when broadcast coverage may not yet be available, and allows coaches to compare riders with similar roles in the team.

Instead of simply seeing that a rider burned a certain number of matches, coaches can see when those efforts happened and how that pattern compares with other riders.

The result is a more complete picture of how a rider used their energy throughout the race.

Recovery signals that weren't there before

Performance is only one part of the picture. How a rider recovers from one stage can be just as important when preparing for the next.  

The dashboard brings recovery indicators such as heart rate variability and sleep into the same view as performance data. Rather than checking these signals ad hoc, coaches can follow them per rider over the course of a race week.

Data from the days before a race provide an individual baseline, giving the coaching staff context when interpreting changes in a rider's signals.

A deviation from a rider's normal pattern can then provide an additional signal for coaches to investigate when assessing fatigue, recovery or readiness.