Methods and apparatus to predict sports injuries

Abstract

A disclosed example method to predict an injury for a target player on a target date includes determining a first probability of injury of the target player based on probabilities of injuries of second players having similarities with the target player; determining a second probability of injury of the target player based on injuries of the target player; determining a third probability of injury of the target player based on the first probability of injury of the target player and the second probability of injury of the target player; and generating, by executing an instruction with the processor, a report of a predicted probability of injury of the target player for the target date based on the third probability of injury of the target player.

1 . (canceled) 
     
     
         2 . An apparatus to predict an injury for a target person on a target date, the apparatus comprising:
 instructions;   processor circuitry to execute the instructions to:
 determine a first probability of injury of the target person based on probabilities of injuries of second persons by dividing (a) a sum of weighted probabilities of injuries for ones of the second persons by (b) a sum of similarity factors of the second persons, the second persons selected based on attributes of the second persons and the target person; 
 determine a second probability of injury of the target person based on injuries of the target person; 
 determine a third probability of injury of the target person based on the first probability of injury of the target person and the second probability of injury of the target person; and 
 generate a report of a predicted probability of injury of the target person for the target date based on the third probability of injury of the target person; and 
   computer memory to store the report.   
     
     
         3 . The apparatus of  claim 2 , further including a data interface to access an associative database that identifies the second persons based on the attributes. 
     
     
         4 . The apparatus of  claim 2 , wherein the attributes include at least one of age, an electrocardiogram measure, or blood pressure. 
     
     
         5 . The apparatus of  claim 2 , wherein the attributes include at least one of a physiological load, a mechanical load, a mechanical intensity, a physical intensity, or a previous injury. 
     
     
         6 . The apparatus of  claim 5 , wherein the physiological load represents at least one of distance traveled, average speed, or weight. 
     
     
         7 . The apparatus of  claim 5 , wherein the mechanical load represents at least one of acceleration or deceleration. 
     
     
         8 . The apparatus of  claim 2 , wherein the report includes the predicted probability of injury of the target person for a prediction window, the prediction window being a range of time extending between a date on which the predicted probability of injury is determined and the target date. 
     
     
         9 . The apparatus of  claim 2 , wherein the processor circuitry is to execute instructions to determine a similarity factor as a percentage representative of a complexity analysis of a difference between first ones of the attributes of the target person and second ones of the attributes of the second persons. 
     
     
         10 . A tangible machine readable storage medium comprising instructions that, when executed, cause processor circuitry to at least:
 determine a first probability of injury of a target person based on probabilities of injuries of second persons by dividing (a) a sum of weighted probabilities of injuries for ones of the second persons by (b) a sum of similarity factors of the second persons, the second persons selected based on attributes of the second persons and the target person;   determine a second probability of injury of the target person based on injuries of the target person;   determine a third probability of injury of the target person based on the first probability of injury of the target person and the second probability of injury of the target person;   generate a report of a predicted probability of injury of the target person for a target date based on the third probability of injury of the target person; and   store the report in memory.   
     
     
         11 . The tangible machine readable storage medium of  claim 10 , wherein the instructions, when executed, cause the processor circuitry to access an associative database that identifies the second persons based on the attributes. 
     
     
         12 . The tangible machine readable storage medium of  claim 10 , wherein the attributes include at least one of age, an electrocardiogram measure, or blood pressure. 
     
     
         13 . The tangible machine readable storage medium of  claim 10 , wherein the attributes include at least one of a physiological load, a mechanical load, a mechanical intensity, a physical intensity, or a previous injury. 
     
     
         14 . The tangible machine readable storage medium of  claim 13 , wherein the physiological load represents at least one of distance traveled, average speed, or weight. 
     
     
         15 . The tangible machine readable storage medium of  claim 13 , wherein the mechanical load represents at least one of acceleration or deceleration. 
     
     
         16 . The tangible machine readable storage medium of  claim 10 , wherein the instructions, when executed, cause the processor circuitry to determine the predicted probability of injury of the target person for a prediction window, the prediction window being a range of time extending between a date on which the predicted probability of injury is determined and the target date. 
     
     
         17 . The tangible machine readable storage medium of  claim 10 , wherein the instructions, when executed, cause the processor circuitry to determine an accuracy of the third probability based on a comparison between an injury prediction and a date of an actual injury of the target person. 
     
     
         18 . A method comprising:
 determining, by executing an instruction with processor circuitry, a first probability of injury of a target person based on probabilities of injuries of second persons by dividing (a) a sum of weighted probabilities of injuries for ones of the second persons by (b) a sum of similarity factors of the second persons, the second persons selected based on attributes of the second persons and the target person;   determining, by executing an instruction with the processor circuitry, a second probability of injury of the target person based on injuries of the target person;   determining, by executing an instruction with the processor circuitry, a third probability of injury of the target person based on the first probability of injury of the target person and the second probability of injury of the target person; and   generating, by executing an instruction with the processor circuitry, a report of a predicted probability of injury of the target person for a target date based on the third probability of injury of the target person; and   storing the report in memory.   
     
     
         19 . The method of  claim 18 , further including accessing an associative database that identifies the second persons based on the attributes. 
     
     
         20 . The method of  claim 18 , wherein the attributes include at least one of age, an electrocardiogram measure, or blood pressure. 
     
     
         21 . The method of  claim 18 , wherein the attributes include at least one of a physiological load, a mechanical load, a mechanical intensity, a physical intensity, or a previous injury. 
     
     
         22 . The method of  claim 18 , further including determining the predicted probability of injury of the target person for a prediction window, the prediction window being a range of time extending between a date on which the predicted probability of injury is determined and the target date. 
     
     
         23 . The method of  claim 18 , further including determining an accuracy of the third probability based on a comparison between an injury prediction and a date of an actual injury of the target person.