Contents

1 The Question That Never Changed: What Do I Do Today?

Kona, 1990: a nineteen-year-old Paul watches Pauli Kiuru glance at the heart-rate number on his wrist, and 35 years of measurement later every athlete still wakes up asking the same question: What do I do today? The opening now rests on Kiuru’s own account, given to the author, of what that number was and was not doing.

2 Sports Science 1.0: The Lab

The lab era, from the 1920s to the 1990s, pinned down physiology that still holds, from VO2max to Banister’s fitness-and-fatigue model, yet it could never quite reach the athlete in the field, where the same threshold power produced wildly different results.

3 Sports Science 2.0: The Dashboard

Wearables measured everything and decided nothing. The bottleneck was never the sensors but one human trying to turn 30 athletes and hundreds of data streams into the right call. This was the era that rebuilt Mahe Drysdale for Olympic gold and let Karen Hanlen down.

4 Content Is King, But Context Is God

The real coaching problem is context, not content, because the same power number is a steady session for a fresh athlete and a failed race for an athlete who has cooked themselves.

5 What AI Can Actually Do

Andrea Zignoli’s VO2-predicting network in Caen in 2016 revealed the four things a machine genuinely adds--pattern recognition, memory, integration and scale--and made clear that human input still plays a role.

6 The Athlete Is Not a Dataset

The signal dashboards throw away is language, because the words an athlete uses, like “felt sick afterward” or “no power today,” reach the part of the response no sensor can measure and often move before the numbers do. A system that remembers every note can hand the early word back.

7 Sports Science 3.0: Choosing Better

Beyond a plan and a data point, Sport Science 3.0 presents a decision. A teenage mountain runner and Marius Bakken’s morning quad-squeeze teach essential stopgaps alongside the athlete dashboard, where the plan recommended threshold intervals but the recovery signals overruled it. The final call: an easy aerobic ride.

8 The Number on the Wrist

Your key thresholds can now be read straight from ordinary training with no lab test. Andi Böcherer’s Ironman Lanzarote win shows the method holding up in wind and lava heat, a 2015 study shows well-trained runners burning roughly three times the fat at the same effort, and Kiuru’s 141 finally gets its meaning: the top of Zone 2, sitting on his aerobic threshold.

9 The Consultant

The answer to “but I’m not Paul” is a coach you can argue with, one that reasons from real physiology and hands you the call, and whose most valuable move in Marjaana Rakai’s cardiac scare was a refusal: stop and see your doctors, while the rest of the app was still cheering her on.

10 The Engineer

Luke Evans went from a 2-minute walk-run in lockdown to winning an Ironman five years later, self-coached on the platform, proving the tools work for the everyman and that the athlete’s own read of his body is pivotal.

11 Coaches Don’t Disappear, They Scale

Luke’s maple-syrup stomach disaster was the one problem AI could not solve, and fixing it by hand reveals the division of labor: AI is the better scientist, the coach is the better human, and a coach’s judgment can now reach far more athletes.

Epilogue A New Contract Between Athlete and Science

Back to Kiuru one last time: the number was always an input, not an instruction, and the new contract is a partnership where AI holds everything it can while the athlete keeps the one signal only they can feel and the one decision only they can make.