7 Reasons the WorldTour Moved to Vekta

Coach

Coach

Coach

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Henry Latimer

Henry Latimer

Henry Latimer

Reading the Story of a Race

Reading the Story of a Race

What the Data Really Tells Us

What the Data Really Tells Us

Henry Latimer, coach and founder of Cycling Coach Henry, brings a decade of experience working across road, track, cyclocross and ultra-endurance. He has coached national champions, Invictus Games gold medallists, and Great Britain Cycling Team athletes and he races himself.

We asked Henry to share how he approaches race analysis with Vekta. What he wrote isn't a product walkthrough. It's a philosophy, one that we think cuts to the heart of why data exists in sport. Not to replace judgement, but to sharpen it.

Over to Henry.

Reading the Story of a Race: What the Data Really Tells Us

By Henry Latimer

We live in a data-rich world, especially in performance cycling. It's easy to believe that numbers alone can win races. Sure, for the very best in the world, their physiology can make them almost unbeatable. But for 90% of high-level racers, the nuance lies within the art of racing.

How efficient were they in the bunch? Did they manage their effort before key climbs? Did they hide well enough before launching their big attack? These questions don't just shape tactics. They shape outcomes.

The art of racing does, however, leave its mark within the data. The data helps us understand the picture and examine in-race decisions with objective clarity. When we look at a race file alongside subjective feedback, it tells us how a race really unfolded.



Power and Heart Rate Only Tell Part of the Story

When we review a race, we need to interpret information and identify decisive moments. We look for both output and cost within different metrics in a file, aiming to understand the efforts of a rider during key moments. As we start to identify these elements within the data, we also overlay subjective feedback to help us build greater context.

Traditional post-race analysis has been driven by power and heart rate. Power has always shown us the output; heart rate helps us understand the internal cost. These metrics are important, but do they help us understand the story of a race? Power traces can hide key efforts, and heart rate often lags behind during decisive moments.



Intensity Stream: The Data Has Chapters

The Intensity stream within Vekta tells a much clearer story. We now start to see how the race unfolded. Where did the early efforts occur? Were there clusters of surges before the race settled into its natural rhythm? The Intensity stream doesn't just show effort, it reveals structure. It gives the race its chapters.

What we still don’t understand is the cost of these efforts, and how they affect a rider's available energy… Enter W’ balance.

W′ Balance Tells Us When the Race Was Really Won or Lost

W′ balance is a real-time reflection of your work capacity above critical power. Think of it as your high-intensity battery. If we go too hard for too long, we need to drop below critical power in order to recharge and push hard again. It is a modelled reflection showing the physiological cost of high-intensity efforts. W′ balance can also help us understand where the rider was under the most cognitive stress, giving important context to decisions at key moments.

In our case study rider, you can see exactly this dynamic playing out. Watch how W′ depletes through the hilly middle section of the race, recovers during the mid-race lull, and is held in reserve, deliberately for the winning move in the finale.

We've now identified where the race got hard and how that affected our rider. The key context is added when we start to understand our rider's subjective feedback. How did they feel early in the race? Did they recover sufficiently after surges in the first hour? Did they stick to their pre-race strategy?

Combining all these tools gives us powerful insight into a race.

So Would You Like Me to Tell You a Story?



Chapter 1: In the beginning

The early part of this race was fast, with a high level of effort from our rider due to lots of teams attacking to try and form an early breakaway. Our rider managed her effort well and, despite having to push hard, she recovered effectively and had plenty of energy left in the tank for Chapter 2.

Chapter 2: Burning matches

This was the hardest part of the race, a hilly section of the course with repeated efforts at close to max. We can see that our rider was pretty empty on two occasions during this phase, but managed her effort well and recovered after each climb. She told me that she was well positioned on all of these sections, and this was important in helping her recover quickly between efforts.

Chapter 3: A mid-race lull

After 90 minutes the race had settled. Lots of attacks were attempted by multiple riders, to no avail. The race stagnated and our rider had an opportunity to recover. There was a short burst of intensity around two hours, but with tired legs in the bunch it could not be sustained for long. Our rider was preparing for her final move.

Chapter 4: Endgame

Our rider had identified two possible climbs in the finale where she would launch her attack. The race had stayed together, and everything was aligning to allow this strategy to come to fruition. We can clearly see the attack at 2h41, where our rider emptied her W′ balance to get away. A short recovery on a descent saw the battery recharge before it was full gas to the finish line and the race win.

A Rider Who Understands the Cost of Their Choices

A data-informed approach to race analysis, supported by subjective feedback, is the most effective way to understand how races unfold. In our example the rider was victorious, but often we learn most from our least impressive results. Understanding why we failed and where we can make changes is the secret sauce. This gives coaches a powerful tool to help riders reflect on decisions and improve their performance in future.

A rider who understands the cost of their choices in races is a dangerous rider. They race with intention, they make better decisions, they control the narrative.



Henry Latimer is a British Cycling Level 3 Road & Time Trial Coach, Association of British Cycle Coaches Level 3 Coach, and British Cycling Coaching Scholarship Graduate. He has coached athletes across road, track, cyclocross and ultra-endurance disciplines, from beginners to national champions and beyond. You can find out more at cyclingcoachhenry.com.

Henry Latimer, coach and founder of Cycling Coach Henry, brings a decade of experience working across road, track, cyclocross and ultra-endurance. He has coached national champions, Invictus Games gold medallists, and Great Britain Cycling Team athletes and he races himself.

We asked Henry to share how he approaches race analysis with Vekta. What he wrote isn't a product walkthrough. It's a philosophy, one that we think cuts to the heart of why data exists in sport. Not to replace judgement, but to sharpen it.

Over to Henry.

Reading the Story of a Race: What the Data Really Tells Us

By Henry Latimer

We live in a data-rich world, especially in performance cycling. It's easy to believe that numbers alone can win races. Sure, for the very best in the world, their physiology can make them almost unbeatable. But for 90% of high-level racers, the nuance lies within the art of racing.

How efficient were they in the bunch? Did they manage their effort before key climbs? Did they hide well enough before launching their big attack? These questions don't just shape tactics. They shape outcomes.

The art of racing does, however, leave its mark within the data. The data helps us understand the picture and examine in-race decisions with objective clarity. When we look at a race file alongside subjective feedback, it tells us how a race really unfolded.



Power and Heart Rate Only Tell Part of the Story

When we review a race, we need to interpret information and identify decisive moments. We look for both output and cost within different metrics in a file, aiming to understand the efforts of a rider during key moments. As we start to identify these elements within the data, we also overlay subjective feedback to help us build greater context.

Traditional post-race analysis has been driven by power and heart rate. Power has always shown us the output; heart rate helps us understand the internal cost. These metrics are important, but do they help us understand the story of a race? Power traces can hide key efforts, and heart rate often lags behind during decisive moments.



Intensity Stream: The Data Has Chapters

The Intensity stream within Vekta tells a much clearer story. We now start to see how the race unfolded. Where did the early efforts occur? Were there clusters of surges before the race settled into its natural rhythm? The Intensity stream doesn't just show effort, it reveals structure. It gives the race its chapters.

What we still don’t understand is the cost of these efforts, and how they affect a rider's available energy… Enter W’ balance.

W′ Balance Tells Us When the Race Was Really Won or Lost

W′ balance is a real-time reflection of your work capacity above critical power. Think of it as your high-intensity battery. If we go too hard for too long, we need to drop below critical power in order to recharge and push hard again. It is a modelled reflection showing the physiological cost of high-intensity efforts. W′ balance can also help us understand where the rider was under the most cognitive stress, giving important context to decisions at key moments.

In our case study rider, you can see exactly this dynamic playing out. Watch how W′ depletes through the hilly middle section of the race, recovers during the mid-race lull, and is held in reserve, deliberately for the winning move in the finale.

We've now identified where the race got hard and how that affected our rider. The key context is added when we start to understand our rider's subjective feedback. How did they feel early in the race? Did they recover sufficiently after surges in the first hour? Did they stick to their pre-race strategy?

Combining all these tools gives us powerful insight into a race.

So Would You Like Me to Tell You a Story?



Chapter 1: In the beginning

The early part of this race was fast, with a high level of effort from our rider due to lots of teams attacking to try and form an early breakaway. Our rider managed her effort well and, despite having to push hard, she recovered effectively and had plenty of energy left in the tank for Chapter 2.

Chapter 2: Burning matches

This was the hardest part of the race, a hilly section of the course with repeated efforts at close to max. We can see that our rider was pretty empty on two occasions during this phase, but managed her effort well and recovered after each climb. She told me that she was well positioned on all of these sections, and this was important in helping her recover quickly between efforts.

Chapter 3: A mid-race lull

After 90 minutes the race had settled. Lots of attacks were attempted by multiple riders, to no avail. The race stagnated and our rider had an opportunity to recover. There was a short burst of intensity around two hours, but with tired legs in the bunch it could not be sustained for long. Our rider was preparing for her final move.

Chapter 4: Endgame

Our rider had identified two possible climbs in the finale where she would launch her attack. The race had stayed together, and everything was aligning to allow this strategy to come to fruition. We can clearly see the attack at 2h41, where our rider emptied her W′ balance to get away. A short recovery on a descent saw the battery recharge before it was full gas to the finish line and the race win.

A Rider Who Understands the Cost of Their Choices

A data-informed approach to race analysis, supported by subjective feedback, is the most effective way to understand how races unfold. In our example the rider was victorious, but often we learn most from our least impressive results. Understanding why we failed and where we can make changes is the secret sauce. This gives coaches a powerful tool to help riders reflect on decisions and improve their performance in future.

A rider who understands the cost of their choices in races is a dangerous rider. They race with intention, they make better decisions, they control the narrative.



Henry Latimer is a British Cycling Level 3 Road & Time Trial Coach, Association of British Cycle Coaches Level 3 Coach, and British Cycling Coaching Scholarship Graduate. He has coached athletes across road, track, cyclocross and ultra-endurance disciplines, from beginners to national champions and beyond. You can find out more at cyclingcoachhenry.com.

Frequently asked questions

Henry Latimer is a cycling coach and the founder of Cycling Coach Henry. He brings a decade of experience working across road, track, cyclocross, and ultra-endurance disciplines. He has coached national champions, Invictus Games gold medallists, and Great Britain Cycling Team athletes, and he races himself. He coaches with Vekta and writes on race analysis through the lens of data and judgement.
The Intensity stream is a Vekta metric that reveals the structural shape of a race or session. Where power and heart rate show output and cost, Intensity shows how effort was actually distributed. It identifies clusters of surges, the early efforts, the lulls, and the decisive moments. The Intensity stream gives a race its chapters by surfacing the rhythm of effort rather than the raw numbers.
W' Balance is a real-time reflection of an athlete's work capacity above Critical Power. Each time an athlete goes above CP, W' depletes. Each time they drop below CP, W' begins to recharge. W' Balance shows how much of the high-intensity battery is available at any moment, giving coaches and athletes a way to understand the physiological cost of decisions during racing.
Power and heart rate tell only part of the story. Power traces can hide key efforts, and heart rate often lags behind during decisive moments. They show output and internal cost but not structure or context. The Intensity stream and W' Balance fill that gap, revealing how the race actually unfolded and where cognitive and physiological stress was highest.
Henry Latimer's chapters framework treats a race as a narrative with distinct phases: the opening (early efforts and breakaway attempts), the hard middle (decisive climbs or surges where W' is burned), the lull (recovery in the bunch), and the endgame (final attacks and decisive moments). Reading data through this structure turns numbers into a story coaches and athletes can learn from.
W' Balance shows in real time how much anaerobic work capacity remains. Athletes who understand their W' Balance can decide when to attack, when to sit in, and when to recover. Coaches reviewing W' Balance after a race can identify exactly where the athlete emptied the tank, whether that was deliberate, and whether better timing would have produced a different result.
Data shows what happened physiologically. Subjective feedback explains why decisions were made and how they felt. A rider who felt boxed in, mentally cooked, or sharp at a key moment gives context that no power file captures. Combining both creates a complete picture of the race, supporting more accurate analysis and better preparation for future events.
Vekta provides the Intensity stream, W' Balance, automatic interval detection, and the workflow to overlay subjective notes with objective data. Coaches can move through the chapters of a race with clarity, identifying decisive moments and their cost. The goal is not to replace coaching judgement but to sharpen it, giving the conversation a foundation of evidence.
Dominic Valerio
Henry Latimer
Henry Latimer

Cycling Coach Henry