Hybrid method of assessing and predicting athletic performance

Abstract

Exemplary systems, apparatus, and methods for evaluating and predicting athletic performance are described. Systems may include a receiver that gathers non-deterministic data on one or more aspects of athletic performance, a deterministic model of the athletic performance, a hybrid processor that creates a conditional probabilistic model from these elements, and a display presenting the evaluated or predicted performance. The system may include sensors affixed to an athlete or their equipment to convey position, acceleration, heart rate, respiration, biomechanical attributes, and detached sensors to record video, audio, and other ambient conditions. Apparatus may include a hybridization processor that communicates the output of conditional probabilistic models directly to athletes, coaches, and trainers using sound, light, or haptic signals, or to spectators using audiovisual enhancements to broadcasts. The methods enable more accurate evaluations and predictions of athletic performance than are possible with either statistical or deterministic methods alone.

1 . A system for evaluating or predicting athletic performance of an individual at an athletic event, comprising:
 one or more sensors located on an individual, athletic equipment, or in an athletic environment measuring at least one aspect of the athletic performance of the individual;   a receiver located remotely from the sensors that receives non-deterministic data from the sensors for use with a deterministic model of the athletic performance; and   a processor located remotely from the sensors configured to hybridize the deterministic model of the athletic performance with the non-deterministic data from said receiver to generate a conditional probabilistic model.   
     
     
         2 . The system of  claim 1  wherein the processor is configured to perform iteratively to generate a corrected conditional probabilistic model. 
     
     
         3 . The system of  claim 2 , wherein the processor is configured as:
 one or more standalone microprocessors;   one or more application specific integrated circuits;   one or more field programmable gate array;   a set of microprocessors, application specific integrated circuits or field programmable gate arrays running concurrently over a local network; or   a cloud processing environment wherein data and results are conveyed over a wide area network.   
     
     
         4 . A system for evaluating or predicting athletic performance of a group of athletes at an athletic event, comprising:
 one or more sensors located on more than one individual, athletic equipment, or in an athletic environment measuring at least one aspect of the athletic performance of the individuals;   a receiver located remotely from the sensors that receives non-deterministic data from the sensors for use with a deterministic model of the athletic performance; and   a processor located remotely from the sensors configured to hybridize the deterministic model of the athletic performance with the non-deterministic data from said receiver to generate a conditional probabilistic model.   
     
     
         5 . The system of  claim 4  wherein the processor is configured to perform iteratively to generate a corrected conditional probabilistic model. 
     
     
         6 . The system of  claim 5 , wherein the processor is configured as one or more standalone microprocessors;
 one or more application specific integrated circuits;   one or more field programmable gate array;   a set of microprocessors, application specific integrated circuits or field programmable gate arrays running concurrently over a local network; or   a cloud processing environment wherein data and results are conveyed over a wide area network.   
     
     
         7 . The system of  claim 1 , wherein the deterministic physical model and the non-deterministic data are hybridized using one or more of analog computing, maximum entropy filtering, neural networks, nonlinear regression, and maximum likelihood estimation. 
     
     
         8 . The system of  claim 1 , wherein the non-deterministic data are hybridized with a plurality of deterministic models to generate conditional probabilistic models. 
     
     
         9 . The system of  claim 8  wherein the non-deterministic data consists of a data set derived from the non-deterministic data. 
     
     
         10 . The system of  claim 1 , further comprising:
 a video enhancement processor configured to apply a graphical enhancement to said generated conditional probabilistic model.   
     
     
         11 . The system of  claim 10 , wherein the audible, visible, or haptic output is conveyed during an athletic competition by at least one of a wireless, wired, visual, or acoustic device. 
     
     
         12 . The system of  claim 1 , further comprising:
 an audio enhancement processor configured to apply an audio enhancement to said generated conditional probabilistic model.   
     
     
         13 . The system of  claim 12 , wherein the audible, visible, or haptic output is conveyed during an athletic competition by at least one of a wireless, wired, visual, or acoustic device. 
     
     
         14 . The system of  claim 1 , further comprising:
 a haptic enhancement processor configured to apply a haptic output to said generated conditional probabilistic model.   
     
     
         15 . The system of  claim 14 , wherein the audible, visible, or haptic output is conveyed during an athletic competition by at least one of a wireless, wired, visual, or acoustic device. 
     
     
         16 . An apparatus for concurrently evaluating and executing an athletic performance of an athlete or athletes:
 a processor pre-configured with a conditionally probabilistic model of athletic performance;   sensors configured to provide non-deterministic measurements to said processor; and   audio, visual, or haptic output components that convey evaluations of the conditionally probabilistic model to the athlete or athletes for enabling the athlete or athletes to make adjustments to their athletic performance.   
     
     
         17 . The apparatus of  claim 16  herein the processor is configured as one or more standalone microprocessors;
 one or more application specific integrated circuits; 
 one or more field programmable gate array; 
 a set of microprocessors, application specific integrated circuits or field programmable gate arrays running concurrently over a local network; or 
 a cloud processing environment wherein data and results are conveyed over a wide area.