US 12,403,372 B2
Golf club fitting based on machine learning
Brian Rahman, Carlsbad, CA (US); Peter Roberts, Carlsbad, CA (US); and Todd Beach, San Diego, CA (US)
Assigned to TAYLOR MADE GOLF COMPANY, INC., Carlsbad, CA (US)
Filed by Taylor Made Golf Company, Inc., Carlsbad, CA (US)
Filed on Dec. 29, 2023, as Appl. No. 18/401,320.
Claims priority of provisional application 63/436,326, filed on Dec. 30, 2022.
Prior Publication US 2024/0216774 A1, Jul. 4, 2024
Int. Cl. A63B 69/36 (2006.01); A63B 71/06 (2006.01); G06N 20/00 (2019.01)
CPC A63B 69/3605 (2020.08) [A63B 71/0622 (2013.01); G06N 20/00 (2019.01); A63B 2225/50 (2013.01)] 22 Claims
OG exemplary drawing
 
1. An apparatus, comprising:
a processor; and
a memory that stores code executable by the processor to:
receive a first set of golf swing data for a user, the first set of golf swing data representative of one or more characteristics of a golf swing of the user, the first set of golf swing data comprising sensed data, survey data, or a combination thereof;
determine one or more optimal specifications of at least one hypothetical golf club that is a best fit for the user using a property prediction machine learning model based on the first set of golf swing data, wherein the property prediction machine learning model is specially trained using a second set of golf swing data to analyze golf swing data; and
determine at least one pre-existing golf club, comprising predefined specifications, that is a best match for the user based on a comparison of the determined one or more optimal specifications of the at least one hypothetical golf club to the predefined specifications of a plurality of different pre-existing golf clubs.