Method and system to assist in player development

• US 10,603,569 B2
• Filed: 08/07/2017
• Issued: 03/31/2020
• Est. Priority Date: 11/17/2013
• Status: Active Grant

• Current Assignee: Team Sport IP, LLC
• Original Assignee: Team Sport IP, LLC
• Inventors: Campana Aguilera, Jose, Garcia del Castillo, Alejandro, Keppeln, Joseph
• Primary Examiner(s): Laneau, Ronald
• Application Number:
  US15/670,413
• Publication Number:
  US 20180178106A1
• Time in Patent Office: 967 Days
• Field of Search: None
• CPC Class Codes: A63B 71/06 Indicating or scoring devices for games or players , or for other sports activities
• CPC Class Codes: G06Q 10/063 Operations research, analysis or management
• CPC Class Codes: G06Q 10/0631 Resource planning, allocation, distributing or scheduling for enterprises or organisations
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations

Abstract

A system for assisting in player development is disclosed. The system includes a server maintaining a database including a plurality of player development records, each player development record including at least training data, competition data, and biographic data. The system also includes an application hosted by the server, the application including a user interface and an automated player performance application, the automated player performance application being configured to generate a player development profile for display in the user interface, the player development profile being based at least in part on performance trends in the player development record and also including one or more recommendations or comparisons.

Claims

1. A method for assisting in player development, the method comprising:

receiving input data from a first user at a server computing system;

storing the input data associated with a player development record in a player development database communicatively connected to the server computing system, the player development database storing a plurality of player development records, each player development record aggregating player data over time and each player development record including player attributes in a plurality of data categories including at least;

education data, competitor data, competition schedule data, competition results data, training data, nutrition data, medical data, and social media data;

comparing, via the server computing system, a plurality of the player attributes in the player development record to a corresponding plurality of target player attributes, wherein the corresponding plurality of target player attributes are based on a corresponding plurality of player attributes of a relevant player population; and

generating, via the server computing system, a recommendation regarding at least one of education or behavioral change, the recommendation being selected based on a difference between a current one or more of the plurality of player attributes and the corresponding target player attributes.

2. The method of claim 1, wherein the data categories included in each player development record further include:

team data, shopping data, entertainment data, expense data, travel data, public media data, sponsorship data, licensing data, research and development data, multimedia data, employment data, hobby data, interest data, player ranking data, and philanthropic data.

3. The method of claim 1, wherein the target player attributes include education data, team data, competitor data, shopping data, entertainment data, competition schedule data, competition results data, expense data, travel data, training data, nutrition data, medical data, social media data, public media data, sponsorship data, licensing data, research and development data, multimedia data, employment data, hobby data, interest data, player ranking data, and philanthropic data.

4. The method of claim 1, wherein the recommendation is based on a difference between two or more of the plurality of player attributes and corresponding target player attributes.

5. The method of claim 1, wherein comparing the plurality of player attributes in the player development record to the corresponding plurality of target player attributes comprises comparing each of the player attributes in the player development record to target player attributes.

6. The method of claim 5, wherein the target player attributes are attributes of another player in the player development database.

7. The method of claim 6, wherein the another player is selectable by the first user.

8. The method of claim 1, wherein the first user comprises a player associated with the player development record.

9. The method of claim 8, wherein the first user is a person other than the player associated with the player development record.

10. The method of claim 9, wherein the first user is at least one of a coach, trainer, first user parent, and other third party.

11. The method of claim 1, wherein the recommendation is in the form of a training video.

12. The method of claim 1, wherein the education data of the target player attribute includes known scholarship criteria.

13. The method of claim 1, wherein the nutrition data of the target player attribute includes a nutritional plan.

14. The method of claim 1, wherein the competition results data of the player development record includes past performance data of a player.

15. The method of claim 1, wherein input data is received from the first user at the server computing system from a mobile application on a mobile device.

16. The method of claim 1, wherein the first user has a permissions profile defined by the identity of the first user, the permissions profile defines a portal by which access is defined, wherein the permissions profile is different for at least one of a player, a coach, a trainer, and a third party.

17. A system for assisting in player development, the system comprising:

a server maintaining a database including a plurality of player development records, each player development record including player attributes in a plurality of data categories including at least;

education data, competitor data, competition schedule data, competition results data, training data, nutrition data, medical data, and social media data; and

an application including a user interface configured to be displayed on a user device communicatively connected to the server, the application being configured to, cooperatively with the server;

compare a plurality of the player attributes in the player development record to a corresponding plurality of target player attributes, the application being configured to generate a recommendation regarding at least one of education or behavioral change, the recommendation being selected based on a difference between a current one or more of the plurality of player attributes and the corresponding target player attributes,

wherein the corresponding plurality of target player attributes are based on a corresponding plurality of player attributes of a relevant player population.

18. The system of claim 17, wherein the user interface of the application is configured to receive identification and login information associated with a user account.

19. The system of claim 17, further comprising an output display signal including a command to display the player development profile and recommendation.

20. The system of claim 17, wherein the data categories included in each player development record further include:

team data, shopping data, entertainment data, expense data, travel data, public media data, sponsorship data, licensing data, research and development data, multimedia data, employment data, hobby data, interest data, player ranking data, and philanthropic data.

21. The system of claim 17, wherein the target player attributes include education data, team data, competitor data, shopping data, entertainment data, competition schedule data, competition results data, expense data, travel data, training data, nutrition data, medical data, social media data, public media data, sponsorship data, licensing data, research and development data, multimedia data, employment data, hobby data, interest data, player ranking data, and philanthropic data.

22. The system of claim 17, wherein the recommendation is based on a difference between two or more of the plurality of player attributes and corresponding target player attributes.