Patent Publication Number: US-2019168095-A1

Title: Systems and methods for golf ball selection

Description:
RELATED APPLICATIONS INFORMATION 
     The application claims priority to U.S. patent application Ser. No. 15/918,882, filed on Mar. 12, 2018, which claims priority to U.S. patent application Ser. No. 12/492,116, filed Jun. 25, 2009, now U.S. Pat. No. 9,914,038 issued on Mar. 13, 2018, which claims priority under 35 U.S.C. 119(e) to U.S. Provisional Patent Application Ser. No. 61/075,334, filed Jun. 25, 2008, and entitled “System for Interactively Determining the Optimal Golf Ball for a Golfer,” which is incorporated herein by reference in its entirety. 
    
    
     BACKGROUND 
     1. Technical Field 
     The embodiments described herein generally relate to automated fitting techniques for golf equipment, and more particularly to an automated technique for selecting a golf ball. 
     2. Related Art 
     The golf ball industry has seen tremendous growth and technological advances in the manufacturing of golf balls since 1999. The introduction and adaptation of multiple piece solid core golf balls to the various world professional golf tours at that time has driven manufacturers to explore the limits of golf ball construction and performance. While these developments have seen much advancement, the industry has seen little advancement in the approach to optimally fitting a golfer with the correct golf ball for their game. The golf ball manufacturers each provide golfers with systems that recommend golf balls within their brand but none of these systems address the entire golf ball selection across brands and in an independent manner which unifies a golfer&#39;s playing characteristics and preferences with specific performance characteristics of golf balls. 
     SUMMARY 
     A system that correlates ballistics and material measurement data against a golfer profile in order to select a golf ball is disclosed herein. 
     According to one aspect, a system for selecting a golf ball comprises a ballistics data input configured to receive ballistics data for a plurality of golf balls and for a plurality of launch conditions; a material data input configured to receive material measurement data for each of the plurality of golf balls; a data structure generation module configured to generate a data structure for each of the plurality of golf balls based on the ballistics data and measurement data; an indexing module configured to index the data structures relative to each other; a interactive feedback module configured to solicit and receive launch monitor data and preferences; a modeling module configured to generate a performance model based on the launch monitor data and preferences; and a selection module configured to select one of the plurality of golf balls based on the index and the performance model. 
     These and other features, aspects, and embodiments are described below in the section entitled “Detailed Description.” 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Features, aspects, and embodiments are described in conjunction with the attached drawings, in which: 
         FIG. 1  is a flow chart illustrating an example process for selecting an optimized golf ball in accordance with one embodiment; and 
         FIG. 2  is a diagram illustrating an example system for carrying out the process of  FIG. 1 . 
     
    
    
     DETAILED DESCRIPTION 
     The embodiments described herein allow the interactive determination of an optimal golf ball for a golfer; improving the golfer&#39;s experience and allocation of money for value in purchasing the balls and in validating manufacturer claims of performance and moving towards better standards for measurement of such performance claims. The embodiments described below allow for the creation of a golfer a unique profile through a series of interactive questions regarding their playing characteristics and preferences. The system matches this profile to a golf ball data model comprising of distance, spin, compression, cover hardness, hotness, and acoustics predictions of all golf balls available. The system identifies and recommends a set of golf balls that best fits the golfer&#39;s profile thus identifying the optimal golf ball(s) for the golfer. The golfer is then presented with value-for-money comparisons and options for obtaining the set of optimal golf balls in an economical manner. Additionally, the system can be adjusted to only present golf balls that are available within a retailer&#39;s existing inventory. 
     The embodiments described herein are based on the application of a standardized method of ballistics and materials performance measurements and evaluation techniques to index the relative performance of each registered ball in the system, to each and every other ball in the system, and then across multiple profiles of potential golfer types.  FIG. 1  is a flow chart illustrating an example process for automatically selecting a golf ball in accordance with the one embodiment. In step  102 , ballistic measurements are made for each ball registered with the system. The ballistics measurements are based on performance testing protocols that are standardized and consider a variety of differences in ball speed, launch angles, and spin rates. These testing methods also measure ball performance using a plurality of clubs, such as the driver, 6-iron, pitching wedge, and putter to create a true full game composition. Swing robots, can be used to generate the ballistics information. Robot swing speeds and profile/set-ups can be established to replicate the swings of senior/low ball speed golfers; average golfers; and tour caliber/high ball speed players. 
     Individual ball ballistics are measured on parameters of ball speed, launch angle and spin rate using, e.g., the Max Out Golf™ IGMS System, which is a camera-based launch monitor capture and reporting system using color-dot convention to best measure golf ball spin. The IGMS™ system allows the determination of optimal flight characteristics using internal ball flight optimization equations, including lift/drag parameters that influence aerodynamic flight characteristics of each ball, which are used to confirm the standard set-up conditions prior to testing. 
     In step  104 , material measurements are made for each registered ball. Materials and golf ball construction parameters are evaluated on the dimensions of compression; cover hardness, and a relative “hotness” of a ball relative to other balls that influences the feel tendencies a golfer experiences when striking the golf ball. 
     The ballistics and material measurement data are then stored as a data structure in step  106 . The data structures are then used to index each registered golf ball relative to the other registered golf balls in step  108 . For example, a prediction model can be generated for each registered golf ball that considers each golf balls&#39; relative performance with respect to each and every other ball in the system base don the data structures. Such a prediction model can consider any combination of feasible ball speed, launch angle, and spin rate a golfer may consider/generate using, e.g., the driver, 6-iron, or pitching wedge. 
     It will be understood that by measuring the ballistics and material data related to the golf ball construction and aerodynamic properties can also be captured. For example, information related to whether the ball is a 2, 3, or 4 piece design and information related to different types and uses of cover material can be captured. 
     In step  110 , a plurality of golfer profiles are created and stored. Considering multiple profiles of potential golfer types is important for optimally fitting a single golf ball or set of like golf balls to a golfer, because the performance result a golfer achieves from any given golf ball depends on how well the ball performance characteristics are matched to that individual golfer&#39;s swing characteristics. These critical characteristics include the speed of the club head imparted on ball at impact; the specific golfer&#39;s angle of attack in striking the ball; the launch angle of the ball at impact; and the spin rate of the ball that all combine to affect distance; and control in a golf ball. 
     Golfer profiles are generated based on swing data for a golfer. In other words, an individual data model is generated for each golfer based on any combination of feasible ball speed, launch angle, and spin rate. This includes data models generated for the golfer using, e.g., the driver, 6-iron, pitching wedge, and putter. Statistical processing and optimization techniques, such as Ordinary Least Squares Regression (OLSQ), are used to generate one-stage and multi-stage prediction models for each of the golf clubs/conditions considered in the interactive profiling system for each golfer. These models are dynamically generated by inputs provided by the golfer, e.g., launch data information, or by proxies generated from questions asked of the golfer to approximate their ball flight and performance set-up. These models are also dynamically linked to each other and are used to generate golfer-specific data models that underlay the algorithmic fitting methodology. 
     For example, in certain embodiments, a golfer is queried on various ball flight characteristics to allow generation of performance proxies when actual launch monitor data is not available. The data prediction models also consider subtle differences in golfer swing style, such as angle of attack; and are designed to optimize the result based on environmental conditions, such as temperature. 
     In certain embodiments, an Analytical Hierarchal Processing (AHP) general methodology can be used to support the processing of interactive profiling questions in the system. Other multi-factor models can then be used to index and rank order performance in support of other elements of the processing. The AHP uses the results of a series of pair-wise comparisons to ascribe weights to the nodes on the AHP decision tree, with a result generated using matrix multiplication. 
     Further, algorithms within the AHP can consider the tradeoff of key performance factors the golfer might consider when evaluating a golf ball. These performance factors recognize tradeoffs, e.g., in distance, control, and feel that are important characteristics in choosing one golf ball over another. The algorithms also consider how feel and control might be considered depending on how close to the hole a golfer is; and how important a factor such as feel is given putting, chipping, or pitching. Algorithms also control and normalize for absolute measures of golf ball measures, such as compression or cover hardness. 
     The proprietary ballistics and materials measurement data is raw data that constitutes an array of possible performance outcomes for many combinations of golf ball and player profile. By collecting performance data on a cross-sectional basis of set up conditions (and with different club types), a gradation of performance across multiple factors or frontiers can be measured and estimated. 
     Since each data model is a unique performance gradient; and the aforementioned algorithms are unique and specific to the golfers profile and to the specific weightings applied during the interactive profiler; then each and every fitting session is unique and custom-tailored to each and every golfer using the system. The combination of these data models and weighting schema generate a rank-order result of golf balls in the system considering the preferences applied to the performance optimization by the golfer, and not determined by any outside expert system or fixed benchmark. 
     Further, in some embodiments, the system may present the golfer with a mixed golf ball trial set that identifies golf balls that most closely match the golfer&#39;s top recommendations for best fit in balls and packaged as a set of those best fit balls (of various brand and model types) in an assembled (economical) offering that allows further on-the-course player and practice testing and optimizations of the selection. 
       FIG. 2  is a diagram illustrating an example system  200  configured to implement the process described above with respect to  FIG. 1 . System  200  comprises a profile authority  202  configured to create the data structures and models described above and to perform the indexing and golfer feedback routines necessary to generate the golfer specific selection of a golf ball. Thus, profile authority  202  can be configured to receive ballistics and material measurement data  212  for each registered golf ball in system  200 . A data structure generation module can then cause profile authority  202  to generate the data structures for each golf ball and store them in database  204 . Authority  202  can then index the golf balls relative to each other using the data structures and store the index information. Interactive feedback  210  can then be provided to authority  202 , comprising launch data, proxy responses to interactive questions, preferences, tendencies, etc., or some combination thereof. An interactive profiling module can then cause profile authority  202  to generate the performance models that allows the selection of the optimum golf ball. These models can also be stored in database  204 . For example, the models can then be used to rank the golf balls based on the indexing. 
     The term “authority” is intended to refer to the software and hardware required to perform the functions described herein. As such, the term authority can comprise one or more servers, routers, processors, API&#39;s, user interfaces, and software modules. 
     While certain embodiments have been described above, it will be understood that the embodiments described are by way of example only. Accordingly, the systems and methods described herein should not be limited based on the described embodiments. Rather, the systems and methods described herein should only be limited in light of the claims that follow when taken in conjunction with the above description and accompanying drawings.