Golf equipment identification and fitting system
A system and method for generating at least one golf swing recommendation for a golfer is disclosed herein. In one aspect, the present disclosure is directed to using a machine-learning model to generate at least one modification or recommendation associated with a golfer's swing.
1. A system for generating at least one golf swing recommendation for a golfer, the system comprising:
at least one performance tracking device configured to track at least one of: a golf club swing to thereby generate golf club swing characteristics of the golf club swing, or a golf ball flight to thereby generate golf ball flight characteristics of the golf ball flight;
a display operatively connected to the at least one performance tracking device;
at least one input device for receiving static input; and
at least one processor and memory operatively connected to the at least one performance tracking device, the display, and the at least one input device,
the memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations comprising:
receiving the static input via the at least one input device;
receiving dynamic input via the at least one performance tracking device, the dynamic input comprising at least one of: (i) the golf club swing characteristics, or (ii) the golf ball flight characteristics, generated by the at least one performance tracking device after a golf ball is struck by a first swing;
executing, by the at least one processor, a trained machine-learning model based on the static input and the dynamic input for the first swing to generate a first output, wherein the trained machine-learning model has been trained from shot data comprising prior static inputs and prior dynamic inputs for a plurality of golf shots; and
displaying, on the display, the first output, wherein the first output includes at least one recommendation associated with a golfer's swing characteristics.
2. The system according to claim 1 , wherein the static input includes at least one golf-equipment characteristic or at least one golfer characteristic.
3. The system according to claim 1 , wherein the at least one performance tracking device includes at least one of an optical sensor system or a radar sensor system for tracking at least one of the golf club swing or the golf ball flight.
4. The system according to claim 1 , wherein the dynamic input includes swing data.
5. The system according to claim 4 , wherein the swing data comprises at least one of: club speed, attack angle, path, dynamic loft, face angle, droop, face and loft spin, or impact location.
6. The system according to claim 1 , wherein the dynamic input includes force data.
7. The system according to claim 6 , wherein the force data comprises at least one of: vertical force for a left foot, vertical force for a right foot, vertical weight shift, vertical force magnitude, toe force, heel force, torque for a right foot, torque for a left foot, torque, center of pressure, center mass, or moment arm.
8. The system according to claim 1 , wherein the dynamic input includes motion-capture data.
9. The system according to claim 8 , wherein the motion-capture data comprises at least one of: wrist rotation, hip angle, hip translation, torso angle, torso translation, spine rotation, or upper body position.
10. The system according to claim 1 , wherein the dynamic input includes electromyography data.
11. The system according to claim 10 , wherein the electromyography data comprises at least one of: leg muscle group electromyography data, torso muscle group electromyography data, arm muscle group electromyography data, integrated electromyography data, root-mean square electromyography data, peak amplitude electromyography data, or median power frequency electromyography data.
12. The system according to claim 1 , wherein the first output comprises at least one recommendation associated with a dynamic weight shift pattern of the golfer.
13. A method of generating at least one golf swing recommendation for a golfer, the method comprising:
receiving static input and dynamic input associated with a first swing striking a golf ball by a golfer;
executing, by at least one processor, a trained machine-learning model based on the static input and the dynamic input, wherein the trained machine-learning model has been trained from shot data comprising prior static inputs and prior dynamic inputs for a plurality of golf shots;
generating, by the at least one processer, a first output based on the trained machine-learning model executing on the static input and the dynamic input associated with the first swing; and
displaying, on a display, the first output, wherein the first output is comprised of a recommendation associated with a golfer's swing characteristics.
14. The method according to claim 13 , wherein the dynamic input is comprised of at least one of: swing data, force data, motion-capture data, or electromyography data.
15. The method according to claim 13 , wherein the first output comprises a recommendation associated with a dynamic weight shift pattern of the golfer.