Predictions are most accurate when the known distance is close to the target. Predicting a marathon from a 5K has wider confidence intervals than predicting from a half marathon. Training specificity, nutrition, and terrain also affect real-world results.

The Riegel model uses a single power-law exponent (typically 1.06). The Cameron model applies a distance-dependent correction that tends to be more optimistic for longer distances and more conservative for shorter ones.

Advanced runners maintain a higher percentage of their short-distance pace over longer distances due to superior aerobic capacity and running economy. Beginners typically slow more as distance increases.