Race Time Predictor
Enter one race result and predict your finish time at any other distance. Uses three prediction formulas with confidence ratings for every prediction.
Enter Your Race Result
Select a race distance and enter your finish time
Predicted Times for All Distances
Select a race distance and enter your time above to see predictions
Prediction Confidence Guide
High Confidence
Target distance is 1x to 4x your input distance. Predictions are typically accurate within 1 to 3 percent for trained runners. Example: predicting 10K from a 5K result.
Medium Confidence
Target distance is 4x to 8x your input distance. Predictions may be off by 3 to 8 percent. Training specificity matters more. Example: predicting a marathon from a 5K result.
Low Confidence
Target distance is more than 8x your input distance, or you are predicting a much shorter race from a longer one. Use these as rough estimates only. Your actual time will depend heavily on specific training.
Factors That Affect Prediction Accuracy
Training Volume
Runners with higher weekly mileage tend to outperform predictions at longer distances. If you run 20 miles per week, your marathon prediction from a 5K will likely be too optimistic. If you run 50+ miles per week, you may beat the prediction.
Course Terrain
Predictions assume a flat course with ideal conditions. A hilly race or trail race will be slower than predicted. Conversely, a downhill-net course (like the Boston Marathon) may produce faster results than predicted, though not always due to the quad-punishing descents.
Weather Conditions
Heat and humidity degrade performance significantly at longer distances. A 5K is short enough that heat has minimal impact, but a marathon in 80F weather could add 10+ minutes to your time. Wind, rain, and altitude also affect results.
Race Experience
First-time racers at a new distance often underperform predictions because they lack pacing experience and mental familiarity with the distance. After completing the distance once, subsequent attempts are typically much closer to predicted times.
How Race Prediction Formulas Work
The Riegel formula, published by Peter Riegel in 1977, is the most widely used race prediction model. The formula is T2 = T1 x (D2/D1)^1.06, where T1 is your known time, D1 is the known distance, D2 is the target distance, and 1.06 is the fatigue exponent. This exponent was derived from analysis of world records across distances and represents the rate at which performance declines as distance increases.
The Cameron formula, developed by Dave Cameron, uses a more complex approach with empirically derived coefficients for each distance. Instead of a single exponent, Cameron calculated specific conversion factors from large datasets of race results. This can produce slightly different predictions, especially at the extremes (very short or very long distances).
The adjusted prediction shown on this page is the average of both formulas. This averaging approach tends to smooth out the biases of each individual formula. Neither formula accounts for training specificity, weather, terrain, or individual physiology, which is why the confidence ratings are important context for interpreting your results.
Predict Your Time, Then Prove It on the Map
Race predictions tell you what is possible. Motera gives you a reason to go prove it. Every run captures territory, clears fog from your city map, and earns XP toward your runner level. Your predicted pace becomes your weapon for capturing more land per run.
Track every split, see your progress over time, and compete with runners in your area. The leaderboard is waiting.
MoteraFrequently Asked Questions
How do race time prediction formulas work?
Race prediction formulas use the mathematical relationship between distance and fatigue. The Riegel formula (T2 = T1 x (D2/D1)^1.06) assumes that for every doubling of distance, you slow down by about 6 percent. The Cameron formula uses empirically derived tables from real race data. Both assume you are equally well-trained for both distances, which is the main source of error.
Which race prediction formula is most accurate?
No single formula is universally most accurate. The Riegel formula works well for distances between 5K and the marathon for trained runners. The Cameron formula tends to be slightly more conservative for longer distances. Averaging both formulas usually gives the most realistic prediction. The key factor is not which formula you use, but whether your training matches the target distance.
Can I predict a marathon time from a 5K?
You can, but the prediction will be less reliable than predicting from a half marathon. The further apart the distances, the more assumptions the formula makes about your endurance. A 5K to marathon prediction assumes you have the aerobic base and long-run training for 26.2 miles. Many runners who are fast at 5K do not have the marathon-specific endurance, so the prediction is often optimistic.
Why are my race predictions different from my actual times?
Several factors cause predictions to differ from reality. Training specificity is the biggest one: a runner who trains mostly short intervals will outperform predictions at shorter distances and underperform at longer ones. Weather, course terrain, elevation, race experience, fueling strategy, and mental toughness all affect the outcome but are not accounted for in the formulas.
What is the Riegel exponent and why does it matter?
The Riegel exponent (1.06) represents the rate at which performance declines as distance increases. A higher exponent means more slowdown per unit of distance. The standard value of 1.06 was derived from world-class performance data. Some researchers suggest using 1.07 for recreational runners, since less-trained athletes fatigue more quickly at longer distances.
How recent should my input race be?
For the most accurate predictions, your input race should be from the last 6 to 8 weeks. Older results may not reflect your current fitness. The race should also be a genuine all-out effort on a standard course with fair weather. A time trial or a very hilly race will produce less reliable predictions.
Are predictions more accurate for shorter or longer distances?
Predictions are most accurate when the input and target distances are within a 2x to 4x ratio. Predicting a 10K from a 5K (2x) is more reliable than predicting a marathon from a 5K (8.4x). Predictions get progressively less reliable as the distance ratio increases. For best results, use the closest race distance you have as your input.
What is the difference between this tool and a race pace calculator?
A race pace calculator converts a known distance and time into a pace per mile or kilometer. A race time predictor takes a known race performance and uses formulas to estimate what you could achieve at a different distance. The predictor accounts for the natural fatigue that occurs as distance increases, while a pace calculator simply divides.
Related Tools and Guides
