Race Time Predictor

The exponent 1.06 in Riegel's formula represents the fatigue factor—how much slower you run per unit distance as race distance increases. Pete Riegel analyzed thousands of world records in his 1981 research and found that performance degrades predictably as distance increases, with 1.06 being the statistically optimal value across most runners. This means doubling your race distance results in slightly more than double the time. The exponent accounts for glycogen depletion, accumulated muscle fatigue, and the body's shift from aerobic to increasingly anaerobic energy systems. Elite runners may have a lower fatigue factor (around 1.04-1.05), while recreational runners often experience higher values.

Riegel's formula was calibrated primarily on races from 1,500 meters to the marathon. Beyond marathon distance, additional variables significantly impact performance: mandatory rest stops, nutrition and hydration management, sleep deprivation in longer events, and psychological factors become dominant. The linear fatigue assumption breaks down as muscle damage accumulates non-linearly and gastrointestinal issues become more prevalent. Ultra-marathons also involve more walking, terrain navigation, and weather exposure. For distances beyond 50K, predictions may underestimate finishing times by 10-30%.

Environmental conditions can significantly alter race performance beyond what Riegel's formula predicts. Altitude above 1,500 meters reduces oxygen availability—expect 3-6% slower times per 1,000 meters of elevation. Heat impacts performance substantially: temperatures above 15°C (59°F) slow marathon times by approximately 1-2% per 5°C increase. High humidity compounds heat stress by impairing sweat evaporation. Wind resistance affects shorter races more proportionally. For accurate predictions, use race times from similar conditions, or apply adjustment factors based on expected conditions.

Use your most recent race time from the past 8-12 weeks for the most accurate predictions, provided it reflects your current fitness level. Your all-time personal best may no longer represent your capabilities due to age, training changes, or fitness fluctuations. However, if your recent race was affected by illness, poor conditions, or pacing errors, it may underestimate your potential. The ideal input is a well-executed race where you finished strong and felt you maximized effort. Consider averaging your last 2-3 comparable performances for stability.

Several factors can cause half marathon performance to exceed 5K-based predictions. First, you may have undertrained for the 5K's demands—shorter races require more speed work and anaerobic capacity than many distance runners develop. Second, some runners are naturally "endurance-oriented," with muscle fiber composition and aerobic systems that favor longer distances, resulting in a lower personal fatigue exponent. Third, race execution matters: 5Ks are harder to pace optimally and easier to start too fast. Finally, training specificity plays a role—if your training emphasizes long runs and tempo work over intervals, your 5K won't fully reflect your aerobic fitness.

Riegel's formula assumes flat, paved courses with minimal elevation change. Hilly courses typically add 12-15 seconds per mile per 100 feet of elevation gain, though strong hill runners may lose less. Trail running introduces additional variables: technical terrain requiring slower foot placement, softer surfaces reducing running economy by 5-10%, and cumulative elevation changes. A trail half marathon may take 20-40% longer than a road equivalent. When using predictions, ensure your input race and target race have similar terrain profiles.