Systems, methods, and computer-program products for assessing athletic ability and generating performance data

1. A computer-implemented method for generating athlete performance data using computer-vision analysis and identifying athletes with desired characteristics, the method comprising:

accessing a video, the video comprising a plurality of frames depicting an athlete, each of the plurality of frames having an associated time-stamp;

identifying, using a computer-vision system, a location of the athlete in each frame of the plurality of frames;

identifying, using the computer-vision system, a location of a reference element in each frame of the plurality of frames;

identifying, using the computer-vision system, a number of pixels between the athlete and the reference element in each frame of the plurality of frames to thereby determine a pixel-distance between the athlete and the reference element in each frame;

converting, using the computer-vision system, each pixel-distance to a corresponding physical distance;

generating performance data for the athlete using the converted physical distance at each time-stamp;

updating an athlete profile associated with the athlete to include the generated performance data;

receiving one or more inputs comprising athlete data;

updating the athlete profile associated with the athlete to include the athlete data;

receiving a plurality of user-selected parameters associated with at least one desired characteristic;

selecting the athlete profile from a plurality of athlete profiles based on a comparison of the user-selected parameters and the athlete profile including the athlete data thereof and the generated performance data thereof; and

identifying the athlete profile as a best-fit match with the user-selected parameters.

2. The computer-implemented method of claim 1 , wherein the reference element is a fixed object in an environment.

3. The computer-implemented method of claim 2 , wherein the performance data is a maximum speed achieved by the athlete over a period of time.

4. The computer-implemented method of claim 2 , wherein the performance data is a maximum acceleration achieved by the athlete over a period of time.

5. The computer-implemented method of claim 2 , wherein the performance data comprises a transition time for the athlete over a period of time.

6. The computer-implemented method of claim 1 , wherein the reference element comprises one of:

a solid line,

a dashed line, or

a geometric shape.

7. The computer-implemented method of claim 1 , wherein the athlete is a first athlete, wherein the plurality of frames further depict a second athlete, and wherein the reference element is the second athlete.

8. The computer-implemented method of claim 7 , wherein the performance data comprises an average physical separation between the first athlete and the second athlete.

9. The computer-implemented method of claim 7 , wherein the performance data is a closing speed of the first athlete relative to the second athlete over a period of time.

10. The computer-implemented method of claim 1 , wherein the athlete data comprises one or more test scores of the athlete.

11. The computer-implemented method of claim 1 , wherein the athlete data comprises a grade point average (“GPA”) for the athlete.

12. The computer-implemented method of claim 1 , wherein the athlete data comprises a location of the athlete.

13. The computer-implemented method of claim 1 , wherein the athlete data comprises a sport and a position played by the athlete.

14. The computer-implemented method of claim 1 , wherein the athlete data comprises a number of visits to recruiting organizations.

15. The computer-implemented method of claim 1 , wherein the athlete data comprises one or more offers to join a school, team, or organization.

16. The computer-implemented method of claim 1 , wherein the athlete data comprises a number of followers on social media.

17. The computer-implemented method of claim 1 , wherein the best-fit match comprises a plurality of percentage matches each associated with one of the plurality of user-selected parameters.

18. A computer system configured for generating athlete performance data using computer-vision analysis and identifying athletes with desired characteristics, the system comprising:

at least one processor; and

one or more computer-readable media having computer-executable instructions stored thereon that, when executed by the at least one processor, perform a method comprising:

accessing a video, the video comprising a plurality of frames depicting an athlete, each of the plurality of frames having an associated time-stamp;

identifying, using a computer-vision system, a location of the athlete in each frame of the plurality of frames;

identifying, using the computer-vision system, a location of a reference element in each frame of the plurality of frames;

identifying, using the computer-vision system, a number of pixels between the athlete and the reference element in each frame of the plurality of frames to thereby determine a pixel-distance between the athlete and the reference element in each frame;

converting, using the computer-vision system, each pixel-distance to a corresponding physical distance;

generating performance data for the athlete using the converted physical distance at each time-stamp;

updating an athlete profile associated with the athlete to include the generated performance data;

receiving one or more inputs comprising athlete data;

updating the athlete profile associated with the athlete to include the athlete data;

receiving a plurality of user-selected parameters associated with at least one desired characteristic;

selecting the athlete profile from a plurality of athlete profiles based on a comparison of the user-selected parameters and the athlete profile including the athlete data thereof and the generated performance data thereof; and

identifying the athlete profile as a best-fit match with the user-selected parameters.

19. A computer-implemented method for generating athlete performance data using computer-vision analysis and identifying athletes with desired characteristics, the method comprising:

accessing a video, the video comprising a plurality of frames depicting an athlete during gameplay, each of the plurality of frames having an associated time-stamp;

identifying, using a computer-vision system, a location of the athlete in each frame of the plurality of frames;

identifying, using the computer-vision system, a location of a reference element in each frame of the plurality of frames;

identifying, using the computer-vision system, a number of pixels between the athlete and the reference element in each frame of the plurality of frames to thereby determine a pixel-distance between the athlete and the reference element in each frame;

converting, using the computer-vision system, each pixel-distance to a corresponding physical distance;

generating performance data for the athlete using the converted physical distance at each time-stamp, wherein the generated performance data comprises a plurality of athlete metrics;

generating an athleticism score for the athlete, wherein the athleticism score comprises a weighted combination of the plurality of athlete metrics associated with the performance data, and wherein the athleticism score is associated with a particular sport position;

updating an athlete profile associated with the athlete to include the athleticism score;

receiving a plurality of user-selected parameters for at least one desired characteristic; and

identifying the athlete profile based at least in part on the athleticism score.

20. The computer-implemented method of claim 19 , wherein the plurality of athlete metrics included in the weighted combination comprise:

maximum speed,

time to maximum speed,

maximum acceleration,

closing speed,

transition time, and

average separation distance between the athlete and another athlete.