Actual status | ||||

Injured | Not injured | |||

Predicted status | Predicted injury | True positive | False positive | Positive predictive value |

N=121 | N=20 | 85.8% | ||

Predicted no injury | False negative | True negative | Negative predictive value | |

N=18 | N=1589 | 98.9% | ||

Sensitivity | Specificity | |||

87.1 (80.5 to 91.7)% | 98.8 (98.1 to 99.2)% | |||

Likelihood ratio positive70.0 (45.1 to 108.8) | ||||

Likelihood ratio negative0.1 (0.1 to 0.2) |

‘

*True Positive*’—predicted injury and player sustained injury; ‘*False Positive*’*—*predicted injury but player did not sustain injury; ‘*False Negative*’—no injury predicted but player sustained injury; ‘*True Negative*’*—*no injury predicted and player did not sustain injury. ‘*Sensitivity*’*—*proportion of injured players who were predicted to be injured;*Specificity*—proportion of uninjured players who were predicted to remain injury-free. ‘*Likelihood ratio positive*’*—*sensitivity/(1−specificity); ‘*Likelihood ratio negative*’*—*(1−sensitivity)/specificity.While there were 91 players in the sample, injury predictions based on the training loads performed by individual players were made on a weekly basis, so that within the total cohort, there was a total number of true positive and negative predictions, and a total number of false positive and negative predictions. Sensitivity and specificity data, and positive and negative likelihood ratios are expressed as rates (and 95% CIs).

Reproduced from Gabbett.42