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Chiang Mai Thailand by UTMB - Elephant 100

Elephant 100 Finish Time Predictor

Elephant 100 race stats pre-loaded (100 km, 5,500 m D+). Enter a known race result to get an elevation-adjusted finish time estimate.

100km5,500m D+Winner: ~9h15Cutoff: 28h

Full Chiang Mai Thailand by UTMB - Elephant 100 course data: aid stations, cutoffs, course profile

1. Your race

Elephant 100
100 km · 5500 m D+ · 5545 m D-
Different race?

Have the GPX? Measure the exact course in the GPX Explorer

2. How should we estimate you?

3. Your predicted finish

155.0 km-effort (ITRA, gain only)192.0 km-effort

Add a past race or your index to get a finish time.

Predict your Elephant 100 finish time from a reference race result, adjusted for the course's 100 km and roughly 5,500 m of elevation gain. The overall cutoff is 28h.

About Chiang Mai Thailand by UTMB - Elephant 100

Chiang Mai Thailand by UTMB - Elephant 100 covers 100 km with around 5,500 m of elevation gain, starting in Mae Taeng, Thailand. The overall cutoff is 28 hours.

Checkpoint data approximate - verify against the current official race guide at chiangmai.utmb.world before your race.

Why one fixed exponent fails for trail

The classic Riegel formula (T2 = T1 × (D2/D1)^1.06) was derived from road race data. It assumes distance is the only factor in fatigue - ignoring elevation, terrain friction, and ultra-specific physiological degradation. The exponent is the whole model, and 1.06 is a road number.

This tool used to patch that with a stepped ladder - 1.06 up to marathon, rising to 1.15 beyond 100 km - stacked on top of ITRA km-effort and a terrain multiplier. Three heuristics on a road model. Nobody had fitted any of them.

What it does now. Your result becomes a performance index on a 0-1000 scale, and that index is mapped onto the target course - the same calibrated model as the ITRA / UTMB Index Estimator, so the two tools cannot contradict each other. The model is fitted by ordinary least squares to public UTMB Index profiles, each anchor recorded with its source and the date it was read. It is a transparent approximation of a proprietary system, not an official ITRA or UTMB number.

It is still a power law - that is worth being honest about. Solving the fit for time gives T ∝ km-effort^1.24. So the change is not that we abandoned Riegel; it is that the exponent is now fitted to public trail results instead of assumed from road ones. That single change is worth over three hours on a UTMB projection, in the direction of what the field actually runs.

Where it stops. Below 50 km-effort - roughly a road marathon - the calibrated model has too few verified results to score honestly, so the tool scales with that same fitted exponent instead and labels the answer as the rougher estimate it is. There is no terrain setting, because the model has no terrain variable: a global average of technicality is inside the curve, but nothing in it can distinguish one course's ground from another's. There is no altitude, heat or night term either. Those are named limitations, not hidden ones - run your number through the Race Conditions Simulator before you commit to it.

km-effort, twice. The index is scored on ITRA's public definition, distance + gain/100, which ignores descent. The km-effort figure shown beside your prediction is TrailMath's own, distance + gain/100 + loss/150, which does not - steep descent causes eccentric muscle damage (Minetti, 2002) that is not free. For UTMB those are 274 and 341. Both are labelled on screen so neither is mistaken for the other.

ITRA. km-effort formula. International Trail Running Association. Riegel PS. (1977). Athletic records and human endurance. American Scientist. Minetti AE et al. (2002). J Appl Physiol. 93(3):1039-46. Hoffman MD. (2014). Pacing by winners of a 161-km mountain ultramarathon. Int J Sports Physiol Perform. Millet GY et al. (2011). Neuromuscular consequences of an extreme mountain ultra-marathon. PLoS ONE - a pre/post study of neuromuscular alteration, which is what it is cited for here.

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