TrackIQ Proof: Two IRONMAN® courses, identical assumptions — clear time gains

TrackIQ computes a physics-based pacing strategy along a course. To do this, thousands of possible power-distribution profiles are simulated and benchmarked against each other — under the fixed constraint that Normalized Power (NP) / Weighted Power (WP) stays the same. Using modern simulation techniques, TrackIQ finds the combination that minimizes total ride time at the same physiological load.

In other words: you don’t just get “a profile” — you get the best solution out of many, all sharing the same load. That’s exactly why TrackIQ is so valuable for long-distance racing, where the goal is not only to get off the bike fast, but to do so in a controlled way.

Setup (identical for both courses)

  • Weight (rider + bike): 80 kg
  • Rolling resistance: c_r = 0.003
  • Aerodynamics: c_wA / CdA = 0.30
  • FTP: 250 W
  • Intensity: 80%
  • Target power: 200 W

We compared: - Baseline (GREEN): constant 200 W for the entire course - TrackIQ (RED): same target load, but optimized power distribution

Important for the proof: Normalized Power (NP) / Weighted Power (WP) is identical between Baseline and TrackIQ. That means the physiological load in the model is the same — TrackIQ gains time not by “pushing harder,” but by distributing effort more effectively.

Result 1: Frankfurt / Langen (182.9 km)

  • Baseline (GREEN):
  • Time: 05:40:00

  • Energy: 4081.8 kJ

  • TrackIQ (RED):

  • Time: 05:31:44

  • Energy: 4088.5 kJ

  • Difference (TrackIQ vs. Baseline):

  • Time gain: −08:16
  • Energy: +6.7 kJ (effectively identical in the context of ~4.1 MJ total work)

This example shows that TrackIQ can still find meaningful time gains even under strict constraints: same NP/WP, virtually the same total work — yet a clearly faster overall time.

Result 2: Klagenfurt (178.0 km)

  • Baseline (GREEN):
  • Time: 05:41:49

  • Energy: 4103.8 kJ

  • TrackIQ (RED):

  • Time: 05:31:37

  • Energy: 4090.1 kJ

  • Difference (TrackIQ vs. Baseline):

  • Time gain: −10:12
  • Energy: −13.7 kJ

Here the effect is even clearer: TrackIQ is not only faster, it also requires slightly less energy. That’s exactly what optimization is about — distributing power so it’s applied where it translates into real speed.

Combined takeaway

On both courses, TrackIQ (RED) is faster than a constant 200 W strategy — with the same Normalized/Weighted Power. The energy differences are tiny, while the time gains are substantial:

  • Frankfurt/Langen: 8:16 minutes faster
  • Klagenfurt: 10:12 minutes faster

That’s the core value of TrackIQ: not more load, but the best solution out of many — at the same NP.

Works on any course — and it’s immediately usable

These two courses are just examples. TrackIQ can run on any route — whether it’s a training GPX, your local loop, or a full race course. The result doesn’t stay in “simulation mode”; it becomes a plan you can actually execute.

That’s why TrackIQ lets you export the optimized strategy directly:

  • as a FIT file (e.g., for Garmin/Wahoo as structured targets or on-device guidance)
  • as a ZWO file (a Zwift workout, ideal for practicing pacing indoors)

So a theoretical model turns into a practical tool: you simulate the best strategy, export it as a workout or device file, and then practice it reproducibly in training — and execute it on race day.