Objective:​ We address 4 frequently misunderstood and important statistical ideas in the construction of injury risk functions. These include the similarities of survival analysis and logistic regression, the correct scale on which to construct pointwise confidence intervals for injury risk, the ability to discern which form of injury risk function is optimal, and the handling of repeated tests on the same subject.

Methods:​ The statistical models are explored through simulation and examination of the underlying mathematics.

Results:​ We provide recommendations for the statistically valid construction and correct interpretation of single-predictor injury risk functions.

Conclusions:​ This article aims to provide useful and understandable statistical guidance to improve the practice in constructing injury risk functions.