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.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method to predict an injury for a target player on a target date, the method comprising: determining, by executing an instruction with a processor, a first probability of injury of the target player based on probabilities of injuries of second players having similarities with the target player; determining, by executing an instruction with the processor, a second probability of injury of the target player based on injuries of the target player; determining, by executing an instruction with the processor, 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. 2. The method as defined in claim 1, wherein the first, second, and third probabilities of injuries of the target player are based on data collected between a start of a sport's season and the target date. 3. The method as defined in claim 1, wherein the second players are selected from an associative database, the second players having similarities with the target player by the target player being more similar to the second players than to third players in the associative database based on a priority ranking of performance data parameters. 4. The method as defined in claim 3, wherein the performance data parameters include at least one of a physiological load, a mechanical load, a mechanical intensity, a physical intensity, a number of games played, average running seconds, average field goals, or previous injuries. 5. The method as defined in claim 1, wherein determining the first probability of injury of the target player based on the probabilities of injuries of the second players is based on dividing (a) a sum of weighted probabilities of injuries for ones of the second players by (b) a sum of similarity factors of the second players. 6. The method as defined in claim 5, wherein the probabilities of injuries for the ones of the second players are based on a number of games played and a number of injuries for each of the ones of the second players between a start of a sport's season and the target date. 7. The method as defined in claim 5, wherein the sum of similarity factors is a sum of percentages representative of amounts of similarity between performance data parameters of the second players and the target player. 8. An apparatus to predict an injury for a target player on a target date, the apparatus comprising: a predictor to: determine a first probability of injury of the target player based on probabilities of injuries of second players having similarities with the target player; determine a second probability of injury of the target player based on injuries of the target player; and determine 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 a report generator to generate 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. 9. The apparatus as defined in claim 8, wherein the first, second, and third probabilities of injuries of the target player are based on data collected between a start of a sport's season and the target date. 10. The apparatus as defined in claim 8, further including a data interface to query an associative database to select the second players in the associative database, the second players having similarities with the target player by the target player being more similar to the second players than to third players in the associative database based on a priority ranking of performance data parameters. 11. The apparatus as defined in claim 10, wherein the performance data parameters include at least one of a physiological load, a mechanical load, a mechanical intensity, a physical intensity, a number of games played, average running seconds, average field goals, or previous injuries. 12. The apparatus as defined in claim 8, wherein the predictor is to perform the determining of the first probability of injury of the target player based on the probabilities of injuries of the second players by dividing (a) a sum of weighted probabilities of injuries for ones of the second players by (b) a sum of similarity factors of the second players. 13. The apparatus as defined in claim 12, wherein the probabilities of injuries for the ones of the second players are based on a number of games played and a number of injuries for each of the ones of the second players between a start of a sport's season and the target date. 14. The apparatus as defined in claim 12, wherein the sum of similarity factors is a sum of percentages representative of amounts of similarity between performance data parameters of the second players and the target player. 15. A tangible machine readable storage medium comprising instructions that, when executed, cause a processor to at least: determine a first probability of injury of the target player based on probabilities of injuries of second players having similarities with the target player; determine a second probability of injury of the target player based on injuries of the target player; determine 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 generate a report of a predicted probability of injury of the target player for a target date based on the third probability of injury of the target player. 16. The tangible machine readable storage medium as defined in claim 15, wherein the first, second, and third probabilities of injuries of the target player are based on data collected between a start of a sport's season and the target date. 17. The tangible machine readable storage medium as defined in claim 15, wherein the instructions are to further cause the processor to query an associative database to select the second players, the second players having similarities with the target player by the target player being more similar to the second players than to third players in the associative database based on a priority ranking of performance data parameters. 18. The tangible machine readable storage medium as defined in claim 17, wherein the performance data parameters include at least one of a physiological load, a mechanical load, a mechanical intensity, a physical intensity, a number of games played, average running seconds, average field goals, or previous injuries. 19. The tangible machine readable storage medium as defined in claim 15, wherein determining the first probability of injury of the target player based on the probabilities of injuries of the second players is based on dividing (a) a sum of weighted probabilities of injuries for ones of the second players by (b) a sum of similarity factors of the second players. 20. The tangible machine readable storage medium as defined in claim 19, wherein the probabilities of injuries for the ones of the second players are based on a number of games played and a number of injuries for each of the ones of the second players between a start of a sport's season and the target date. 21. The tangible machine readable storage medium as defined in claim 19, wherein the sum of similarity factors is a sum of percentages representative of amounts of similarity between performance data parameters of the second players and the target player. 22. An apparatus to predict an injury for a target player on a target date, the apparatus comprising: means for determining a first probability of injury of the target player based on probabilities of injuries of second players having similarities with the target player; means for determining a second probability of injury of the target player based on injuries of the target player; means for 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 means for generating 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. 23. The apparatus as defined in claim 22, wherein the first, second, and third probabilities of injuries of the target player are based on data collected between a start of a sport's season and the target date. 24. The apparatus as defined in claim 22, further including means for querying an associative database to select the second players in the associative database, the second players having similarities with the target player by the target player being more similar to the second players than to third players in the associative database based on a priority ranking of performance data parameters. 25. The apparatus as defined in claim 24, wherein the performance data parameters include at least one of a physiological load, a mechanical load, a mechanical intensity, a physical intensity, a number of games played, average running seconds, average field goals, or previous injuries. 26-28. (canceled)