Putter Fine-Tuning Methods and Putter Manufacturing Methods

Abstract

A method for fine-tuning a putter and a method for manufacturing a putter are described herein. More specifically, it is an application (app) used for analyzing static and dynamic data points, along with an algorithm that best determines how to set the properties of the putter to maximize the consistency of the user's putter stroke and ball roll. Based on the output data of the app, a personalized customized putter is manufactured, and within it, the putter's fitting system is capable of multiple adjustments.

Description

Technology Field

[0001] A method for fine-tuning a putter and a method for manufacturing a putter are described herein. More specifically, it is an application (app) used for analyzing static and dynamic data points, along with an algorithm that best determines how to set the properties of the putter to maximize consistency in the user's putter stroke and ball roll. Based on the output data of the app, a personalized customized putter is manufactured, and within it, the putter's fitting system is capable of multiple adjustments. Background Technology

[0002] In modern society, an increasing number of consumer products are being custom-made for individuals to better suit their specific tasks. As technology continues to advance at a rapid pace, this trend is becoming increasingly widespread and commercially viable. The trend is shifting from a "one-size-fits-all" approach to one where individuals seeking better performance and results find what fits them best. For example, in the golf equipment industry, manufacturers now offer various fitting applications to customers to improve their equipment selection. By tailoring equipment to an individual golfer's swing type, skill level, and other factors, the golfer realizes they have been given the best opportunity to succeed on the course.

[0003] However, available custom-made techniques and tools are somewhat limited in that they are primarily used to analyze the work performed by the club based on gyro measurements or sensors. These techniques do not lead to specific fitting processes or custom-made fitting systems. For example, Ping Golf offers putting handicaps, putting practice, and iPING TM 'iPING', designed to focus on the user's putting stroke measurables and improve consistency through app features that include the use of a cradle. TMWe developed a putting app. The Putting Handicap (PHCP) feature analyzes a series of five putts to determine a consistency score, which is equivalent to a patterned handicap following the existing handicap system (lower is better). Each five-putt session is saved for comparison when the user attempts to lower their PHCP. Based on the user's PHCP, PING recommends a putter type suited to the user's stroke type (straight, slight arc, or strong arc) after the session and suggests the appropriate lie angle and loft. In practice mode, users can also isolate specific aspects of inconsistent putting, such as tempo and closing angle (the degree to which the club face opens or closes at impact). iPING TM The app secures the user's mobile device and the iPING attaches a clip to the putter shaft just below the grip. TM It works with a cradle. However, there are a few drawbacks associated with the app mentioned above. First, it relies on the user's technical skills; even though it analyzes and recommends equipment through measurements, it only analyzes club movement and lacks input regarding the player's static or other tendencies. Additionally, the PING app secures the user's mobile device as described above, and the iPING attaches to the putter shaft below the grip. TM Use a cradle. These devices / cradles make the putter heavier and affect the overall feel of the putter in use.

[0004] Srixon Golf is Swingbyte ® Z Swing Analyzer connected to the sensor TM They developed an app called [App Name]. In each swing, the app's proprietary formula analyzes over 12 key variables, such as swing path, efficiency, impact angle, and attack angle. The Srixon app uses sensor integration to measure, analyze, and recommend equipment, but as mentioned earlier, it only analyzes club movement and does not take into account the player's statics or tendencies.

[0005] TaylorMade Golf has developed an interactive putter and app through real-time stroke analysis that includes a BLAST motion sensor embedded in the grip. The app automatically synchronizes stroke data directly to the mobile app, allowing users to analyze metrics and correct their putting. However, TaylorMade Interactive is primarily a technique for player improvement and does not utilize the data for club fitters to recommend products.

[0006] As can be seen from the above, there is a need for an app based on technique, static position, and dynamic moment analysis that not only measures the player himself but also records important information about the club fitting process for recommending and making custom / bespoke equipment and how the player responds to given equipment specifications and / or at least provides useful choices to the public.

[0007] Additional aspects and advantages of the method, device, and its manufacture will become apparent from the following description, provided merely as an example.

[0008] A method for fine-tuning a putter and a method for manufacturing the same are described herein. More specifically, it is an application (app) used for analyzing static and dynamic data points in conjunction with an algorithm to best determine how to set the properties of the putter to maximize the consistency of the user's putter stroke and ball roll. Based on the output data of the app, a personalized custom-made putter is manufactured, and the putter's fitting system allows for multiple adjustments.

[0009] In a first aspect, a method for fine-tuning a putter is provided, said method:

[0010] a) Step of inputting user data into the app,

[0011] b) preferably, a step of collecting additional data obtained from static and dynamic motions obtained from high-speed cameras and computer analysis and / or other measurement variables obtained from optional sensors;

[0012] c) A step of packaging and comparing the data within the above app;

[0013] d) a step of outputting the above data; and

[0014] e) includes the step of analyzing at least one algorithm and applying it to the data set to determine how the attributes of the putter are best correlated with predetermined algorithm values ​​for a putter set to maximize the consistency of the user's stroke and the roll of the ball during putting, and to determine the exact specification of the user's putter.

[0015] In a second aspect, a fine-tuned or custom-made putter manufactured for each individual is provided based on the output data of the app and method as described herein.

[0016] In a third aspect, a fitting system for manufacturing a multi-adjustable putter is provided, and said putter is:

[0017] shaft;

[0018] Putter head;

[0019] Includes adjustable and / or replaceable striking face plates; and

[0020] The adjustable / replaceable striking plate maintains the loft-to-sole relationship of the putter head so that when the loft of the striking plate is adjusted, the putter head is maintained on a neutral axis relative to the shaft.

[0021] The aforementioned advantages include an app that collects and processes static and dynamic data, along with user tendencies and attributes, to best determine the correct specifications for a putter. By combining high-speed camera and computer analysis, the app applies and compares algorithmic values ​​and scores them on a scale of extremes based on body and club position, thereby best determining whether the putter's attributes need to be set to maximize consistency in the stroke and ball roll during putting. Based on the app data and analysis, custom-made putters can be produced for individuals. The putter fitting system is not only dexterity-neutral and suitable for both left-handed and right-handed users, but also allows for multiple adjustments that maintain the loft-to-sole relationship of the putter head when the loft of the striking face plate is adjusted using adjustable / replaceable face plates. Brief explanation of the drawing

[0022] Further aspects of the method, apparatus, and manufacture thereof will become apparent from the following description, provided merely as an example with reference to the attached drawings: Figure 1 illustrates a schematic flowchart of a fine-tuning app. Figure 2 shows an exemplary screenshot of the home page 1 of the fine-tuning app. Figure 3 shows an exemplary screenshot of player information page 2 of the fine-tuning app. Figure 4 shows an exemplary screenshot of page 3 of the initial setup analysis of the fine-tuning app. Figure 5 shows an exemplary screenshot of page 4 of the initial setup photos of the fine-tuning app. Figure 6 shows an exemplary screenshot of page 5 of the settings classification (hand position) of the fine-tuning app. Figure 7 shows an exemplary screenshot of the settings classification (shaft and forearm plane) of the fine-tuning app. Figure 8 shows an exemplary screenshot of page 7 of the settings classification (view) of the fine-tuning app. Figure 9 shows an exemplary screenshot of page 8 of the settings classification (details) of the fine-tuning app. FIG. 10 illustrates an exemplary screenshot of page 9 of the initial setup photo (face-on image capture) of the fine-tuning app. Figure 11 shows an exemplary screenshot of page 10 of the settings classification (ball position face on) of the fine-tuning app. Figure 12 shows an exemplary screenshot of page 11 of the settings classification (Shaft Lin) of the fine-tuning app. Figure 13 shows an exemplary screenshot of page 12 (top of the screen) of the settings fitting (head, length and lie) of the fine-tuning app. FIG. 14 shows an exemplary screenshot of page 12 (bottom of the screen) of the settings fitting (dynamic evaluation) of the fine-tuning app. Figure 15 shows an exemplary screenshot of a fine-tuned setting photo of Down the line on page 13 of the fine-tuning app. FIG. 16 illustrates an exemplary screenshot of page 14 of the fine-tuned settings photo of the fine-tuning app to re-analyze the position with the recommended putter configuration performed on pages 4 through 11 (pages 15 through 21 of the app). Figure 17 shows an exemplary screenshot of page 23 of the putter configuration page of the fine-tuning app. Figure 18 illustrates an exemplary summary of user putter fitting details and specifications in CSV format. Figure 19 illustrates an exemplary brief PDF summary of the user's putter fitting details and specifications. Figure 20 illustrates an exemplary comprehensive email summary of the user's putter fitting details and specifications. Figure 21 illustrates an exemplary fitting algorithm (length) for data analysis of an app. FIG. 22 illustrates an exemplary fitting algorithm (LI) for data analysis of an app. FIG. 23 illustrates an exemplary fitting algorithm (hozel) for data analysis of an app. FIG. 24 illustrates an exemplary fitting algorithm (loft) for data analysis of an app. FIG. 25 illustrates an exemplary fitting algorithm (head selection) for data analysis of an app. FIG. 26 illustrates an exemplary fitting algorithm (Head Weight) for data analysis of an app. FIG. 27 illustrates an exemplary chart for configuring head weight for a hosel. FIG. 28 illustrates an exemplary fitting system and adjustable components of a putter manufactured from the data output of an app. FIG. 29 illustrates an exemplary perspective adjustment embodiment of a putter manufactured from the data output of an app. FIG. 30 illustrates an exemplary putter head embodiment having an adjustable Center of Gravity (COG) manufactured from the data output of an app. FIG. 31 illustrates an exemplary face-on striking plate of putter head embodiments having various milling depths; A) an even toe-to-heel speed mill (square stroke); B) a faster toe or higher rotational speed mill (push stroke); and C) a manual or negative rotation (cut stroke) produced from the data output of an app. FIG. 32 illustrates an exemplary putter head embodiment having various milling depths; A) a conventional square putter face (the surface is completely flat); B) a bulge putter face (correcting toe strike push misses and heel strike pull misses); C) a negative bulge putter face (correcting push misses off toe strikes and pull misses off heel strikes stroke); D) a negative bulge on the heel (suitable for push strokers with overspin, heel strikes and pull misses); and E) a negative bulge on the toe manufactured from the data output of an app (suitable for pull strokers with manual spin, toe strikes and push misses). FIG. 33 illustrates an exemplary screenshot of optional player information based on the midpoint drill of the fine-tuning app. Specific details for implementing the invention

[0023] As described above, a method for fine-tuning a putter and a method for manufacturing the same are described in this specification. More specifically, it is an application (app) used for analyzing static and dynamic data points, along with an algorithm that best determines how to set the properties of the putter to maximize the consistency of the user's putter stroke and the roll of the ball. Based on the output data of the app, a customized putter is manufactured, and within it, the putter's fitting system is capable of multiple adjustments.

[0024] For the purposes of this specification, the terms “about” or “approximately” and their grammatical variations mean a quantity, level, angle, value, number, frequency, percentage, dimension, size, amount, weight, or length that varies by 30, 25, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1% compared to a reference quantity, level, angle, value, number, frequency, percentage, dimension, size, amount, weight, or length.

[0025] The term 'substantially' or its grammatical variations mean about 50% or more, for example, 75%, 85%, 95%, or 98%.

[0026] The term 'includes' and its grammatical variations must have an inclusive meaning, that is, they are considered to include not only the listed components directly referenced but also other unspecified components or elements.

[0027] The term 'fine-tuned,' or its grammatical variations, refers to slightly adjusting a putter to be tailored and custom-made for the individual user to achieve optimal or desired performance, thereby maximizing consistency in the ball's stroke and roll.

[0028] The term 'algorithm' should be understood as a series of manual and / or computer-implemented processes or a series of instructions to be followed in computation or other problem-solving tasks.

[0029] In a first aspect, a method for fine-tuning a putter is provided, said method:

[0030] a) Step of inputting user data into the app,

[0031] b) preferably, a step of collecting additional data obtained from static and dynamic motions obtained from high-speed cameras and computer analysis and / or other measurement variables obtained from optional sensors;

[0032] c) A step of packaging and collating the data within the above app;

[0033] d) a step of outputting the above data; and

[0034] e) A step of analyzing at least one algorithm and applying it to the data set to determine how the attributes of the putter best correlate with predetermined algorithm values ​​for a putter set to maximize consistency of the user's stroke and the roll of the ball during putting, and to determine the exact specification of the user's putter.

[0035] This app can be used to identify and report on a golfer's tendencies and how this can particularly influence the selection of putter equipment.

[0036] In a preferred embodiment, the app enables the user to capture and analyze specific parameters, including but not to be understood as being limited to any one of the following: wrist-to-ground measurement, height, eye dominance, current putter length, aiming tendency, miss tendency, face rotation (rotation speed), posture (eyeline position, hand position relative to shoulder, relative angle to shaft and forearm, degree of spine angle), ball position face on, shaft lean face on, roll launch and spin, and stroke direction.

[0037] Preferably, based on the data collected from the above parameters, each data point may have a numerical value used by an algorithm to determine the accurate putter specifications for the player. It appears that within the app, after the user adjusts the specifications, it may be possible to report what choices can be made to achieve the desired result.

[0038] In this way, putters produced with non-standard specifications can be manufactured. The inventor found that while most golf supply stores are likely to end up with a 35-inch, 70-degree lie, 4-degree loft, and 350g head weight, this is unlikely to be optimal for most players.

[0039] In a preferred embodiment, the app may be based on an analysis of technique, static position, dynamic movement, and equipment recommendations. In this way, the app can not only measure the player himself but also record insightful information about the fitting process and how the player responds to given putter specifications.

[0040] As described above, the app can check static and dynamic analyses, which can primarily be visual. However, this should not be considered a limitation, as the app can be connected to other technologies for data point analysis. In this way, other technologies such as MATLAB, the Quintic Ball Roll Research System, high-speed cameras, and computer analysis can be used to compare specific traits of the corresponding data point positions for use in algorithm(s). In this manner, the app can check body / club positions and score them on extreme scales, thereby providing values ​​for the algorithms.

[0041] The ability to accurately determine putter specifications for an individual or user can be derived from a consistent analysis of a dataset derived from grouped data of golfers that can determine their trends. Since the grouped data is formed by aggregating individual observations of variables into groups, the frequency distribution of the groups can serve as a convenient means for summarizing or analyzing the data.

[0042] When examining golfers' putting techniques, it is evident that there are various styles and tendencies, making it difficult to categorize the variables. However, the inventor has developed a unique solution in the form of an app and related algorithms. Since the app can evaluate all styles and tendencies, it can determine a putter fit that is accurate to a certain degree within a predetermined range, even if it is individual and uncommon, with a fit that can be a more textbook-like and ideal parameter.

[0043] Without being bound by theory, the app can use algorithms based on statistical analysis derived from the binomial distribution. The binomial distribution can be derived from the Galton board (also known as Qincunx), a physical model of the binomial distribution that explains the central limit theorem—that when independent random variables are added, their sum tends to follow a normal distribution.

[0044] Furthermore, in this way, the app can support consumer-driven research by leveraging grouped data from golfers collected and analyzed. For example, Original Equipment Manufacturers (OEMs) of golf putters typically manufacture putters with standard shaft lengths that can vary between 34 and 35 inches. However, grouped data collected from golfers and entered into the app can determine that the most common or intermediate shaft length a golfer should use is approximately 32 inches. Based on this new insight, OEMs should manufacture 'off-the-shelf' putters with a minimum shaft length of 32 inches. Doing so reduces manufacturing costs and allows them to target sales of putters with shaft lengths suitable for most golfers around the normal distribution curve. It should be understood that this analysis can also be applied to shaft weight, head and hosel configurations, and more. Favorably, this type of app data collection and analysis contrasts with current sales-based research, where manufacturers can assign club dimensions and configurations based on actual sales volume. For example, even if OEMs assume that the statistically median golfer uses a 32-inch putter as determined by data collected within the app, they can manufacture more 34- to 35-inch length putters based on sales volume.

[0045] The algorithm within the app utilizes data points or parameters taken from the measurement, selection, or classification of images (manually or automatically using software) to determine a rating scale or code to be input into the algorithm. Relative positions (e.g., ball-to-body position) may be arbitrarily rated on a scale from 1 to 5 to generate a number for the code. For example, there may be a player's line of sight position (E1). A player who is 2 inches too far from the ball is evaluated and rated and given a code value of 1, while other extreme values ​​such as directly above the ball (code value 3) or 2 inches inside the ball (code value 5) are given. These codes may be used in the algorithm and may be input in relation to other variables to generate recommendations derived from the algorithm.

[0046] In a second aspect, a fine-tuned or custom-made putter manufactured for each individual based on the output data of the app and method described in this specification is provided.

[0047] In a third aspect, as a fitting system for manufacturing a multi-adjustable putter, the putter is:

[0048] shaft;

[0049] Putter head;

[0050] Includes adjustable and / or replaceable striking face plates;

[0051] The adjustable / replaceable striking plate maintains the loft-to-sole relationship of the putter head so that when the loft of the striking plate is adjusted, the putter head is maintained on a neutral axis with respect to the shaft.

[0052] As described above, the Fine Tuning Fitting App is a comprehensive fitting and analysis tool that utilizes a player's static and dynamic measurements, tendencies, and attributes to best determine the precise specifications for a putter. It has been found that golfers can become highly predictable about how they will move or operate when accurate data is taken into account. In this way, the App records and analyzes this data to improve putting success by enabling golfers to have optimal putter specifications that maximize the consistency of their stroke and roll.

[0053] The fitting process can be structured to examine all aspects that contribute to how a golfer hits the putter. It has been found that various settings can affect a golfer's goals, strokes, strikes, and consequently, their putting method.

[0054] Because golfers differ in body size and proportions, the optimal club fit varies from person to person. For example, the angle of the club head relative to the shaft or lie is one of the aspects that must be determined and maintained, along with the loft-to-sole relationship of the putter head.

[0055] Therefore, the fine-tuned fitting matrix can have more than 30,000 configurations selected from head shape and adjustment lines, head and total weight, neck offset and rotation axis, lie angle, loft, length and / or grip.

[0056] In one embodiment, sight markings on the top line of the putter and on the line on the back of the flange of the putter can be used to create a perspective alignment tool. In this way, the fitting process uses an evaluation of the player's perception of straight lines, which can be directed toward the inside of the ball, so that the putter can be configured such that the top line sight dot, machined closer to the heel of the putter, aligns with the back flange line when the sole is substantially parallel to the ground.

[0057] It can also be said that the above-described embodiments are extensively composed of parts, elements, and features mentioned or indicated in the specification of this invention, individually or collectively, and any or any combination of any two or more of said parts, elements, or features.

[0058] An embodiment of a putter head with custom fitting may allow for the alignment of the center of gravity (COG) adjusted to the individual when, for example, the head, hosel, etc. In this way, based on stroke and strike tendencies, the COG can be substantially adjusted to align in order to achieve the most neutral spin axis of the golf ball for the player by allowing the player to hit the optimal position of the head's striking plate (known in the prior art as the 'sweet spot'). In this way, this configuration allows for the complete customization of the putter head, in which the putter is manufactured to have a more toe-weighted bias—where it is found that the player consistently needs weight to position to provide an effective sweet spot.

[0059] The inventors have discovered that the variable milling depth of the striking plate can be used to control the speed of the ball. Without being bound by theory, the deeper the milling, the more the ball is compressed by the striking plate pattern, and the slower its speed becomes. There exists a concept of this aspect that allows for the dispersion of the milling pattern to compensate for the loss of ball speed caused by a poor strike. For example, this is suitable for robots where the heel and toe move at the same speed.

[0060] Preferably, the milling pattern can be custom-milled based on the player's tendency. For example, a player who slices the ball (cut across the ball) spins the toe faster or slower.

[0061] Milling of the striking face plate should not be limited to bulge and roll, but can also be used to offset mishits. In this way, the depth of milling can also cause the closed face of a toe strike to be offset by a relieved bulge that starts the ball further to the right than a square face. Based on data collected from a custom fitting app, it can be determined whether a player who misses a putt from the toe is slicing the ball, which often causes a pull. The milling can then be individually matched to help correct the missed putt. The advantage of custom-making a milled striking face plate is that the putter can still retain the feel of a square face while offsetting mishits.

[0062] Additionally, where specific complete embodiments having equivalents known in the relevant technical field are mentioned herein, such known equivalents are deemed to be included herein as individually described.

[0063] Operation example

[0064] The aforementioned method, apparatus, and manufacture thereof are now described with reference to specific examples.

[0065] As previously mentioned, the algorithm within the app utilizes data points derived from the measurement, selection, or classification of images (manually or automatically using software) to determine the rating scale or code to be input into the algorithm. Relative positions, such as body position relative to the ball, are rated on a scale from 1 to 5, and a number for the code is generated from this scale. A given example could be a player's gaze position (E1). We will rate this player as being too far from the ball (Code Value 1), directly above the ball (Code Value 3), or 2 inches inside the ball (Code Value 5)—refer to Figure 8 for the gaze evaluation where Code 2 (1 inch above the ball) is assigned to the position that looks most similar to the captured image. This is subsequently used in the overall working example and exemplary algorithm (Table 1 below) for determining the optimal shaft length, as illustrated in Figure 21, regarding its relationship with other variables to generate putter recommendations derived from the algorithm.

[0066]

[0067] Table 1 - An exemplary algorithm for determining the recommended length of a putter using the line of sight (E1) as one of the variables for determining the accurate putter specifications using the above formula.

[0068] Example 1

[0069] Referring to FIG. 1, a schematic flowchart of the fine-tuning app is described, showing the entire process performed during a custom putter fitting evaluation specifically tailored to the end user, calculated using non-standard putter specifications. A logical description of each screenshot or page of the app is described in detail below.

[0070] Homepage 1 (Fig. 2)

[0071] Users can select "New Fitting Session" or "New Specification Form." The New Fitting Session feature is described below. The New Specification Form is a creation-only form used to copy specifications or process orders.

[0072] Player Information Page 2 (Fig. 3)

[0073] Enter the information as follows:

[0074] Name: Publish as PDF (Portable Document Format Files) Report

[0075] Name: Published as PDF report

[0076] Email: Publish as PDF report

[0077] Contact: Publish as PDF report

[0078] Handicap: Published as PDF report

[0079] Height: Publish as PDF report / CSV (Comma-separated values) file

[0080] Wrist to Ground: Publish as PDF report / Use in algorithms

[0081] Dexterity: Publish as PDF report / Used in algorithms (limited to photo set determination)

[0082] Initial setup analysis page 3 (Fig. 4)

[0083] Enter the information as follows:

[0084] Current Putter Model: Published as PDF Report

[0085] Current Putter Category (CPC): Published as PDF report

[0086] Current Putter Length (CPL): Published as PDF report

[0087] Current Shaft Plane Angle (CSP): Publish as PDF report / Use in algorithm

[0088] Dominant Eye (DE): Published as PDF report

[0089] Aim (A1) Tendency (A1): Publish as PDF report / Use in algorithm

[0090] Distance from the ball (DFB): Published as a PDF report / Formula Tempo (T1): As one of the variables to determine accurate specifications using face rotation (R1) Gaze (E1): Published as a PDF report / Used in the algorithm

[0091] Face Rotation (R1): Publish as PDF report / Use in algorithm

[0092] Miss Trend (M1): Publish as PDF report / Use in algorithm

[0093] (Fig. 21 illustrates the setting algorithm)

[0094] Initial setup photo page 4

[0095] A down-the-line image published in a PDF report is captured (see Fig. 5).

[0096] Settings Classification (Hand Position) Page 5

[0097] For analysis, the most appropriate image that emulates the user (see Fig. 6) is selected. Each image is associated with a numeric value used in the algorithm. This is published as a PDF report.

[0098] Settings Classification (From Shaft to Forearm Plane) Page 6

[0099] For analysis, the most appropriate image that emulates the user (see Fig. 7) is selected. Each image is associated with a numeric value used in the algorithm. This is published as a PDF report.

[0100] Settings Classification (Perspective) Page 7

[0101] Select the most appropriate image for analysis or one that emulates the user (see Fig. 8). Each image is associated with a numerical value used in the algorithm. This is published as a PDF report.

[0102] Settings Classification (Details) Page 8

[0103] Select the most appropriate image for analysis or one that emulates the user (see Fig. 9). Each image is associated with a numerical value used in the algorithm. This is published as a PDF report.

[0104] Initial setup photo (Face-on image capture) Page 9

[0105] Capture the user as a face-on image (Image 2 in Fig. 10) and publish as a PDF report.

[0106] Settings Classification (Ball Position Face On) Page 10

[0107] For analysis, the most appropriate image that emulates the user (see Fig. 11) is selected. Each image is associated with a numeric value used in the algorithm. This is published as a PDF report.

[0108] Settings Classification (Shaft Lynn) Page 11

[0109] Select the most appropriate image for analysis or one that emulates the user (see Fig. 12). Each image is associated with a numeric value used in the algorithm. This is published as a PDF report.

[0110] Fitting Settings (Head, Hosel (Neck), Length, Lie, Loft, and Grip) Page 12 (Top of screen)

[0111] Referring to Fig. 13, Head: The recommendation will use a new algorithm page for initial setup recommendations including head, hosel, length, lie, loft, and grip.

[0112] Recommended specifications (length): Based on the current putter configuration page with length and lie derived from the initial setup classification algorithm on pages 1 and 2 (Fig. 21) and the stickman analysis of the images on pages 3 to 10.

[0113] Recommended specifications (lie): Based on the current putter configuration page with length and lie derived from the initial setup classification algorithm of pages 1 and 2 (Fig. 22) and the stickman analysis of the images on pages 3 to 10.

[0114] FIGS. 23, FIGS. 24, FIGS. 25, FIGS. 26, and FIGS. 27 illustrate the corresponding algorithm calculations for the hosel, loft, head, and head weight, respectively.

[0115] Fitting Settings (Dynamic Evaluation) Page 12 (Bottom of screen)

[0116] An exemplary screenshot of a configuration fitting (dynamic evaluation) with the following data inputs as shown in Fig. 14:

[0117] Aiming Tendency (A1): Used in the algorithm (Stroke and Strike Algorithm Sheet - see Figs. 22 and 23)

[0118] Stroke Direction Down the Line (SD): Used in the algorithm (Stroke and Strike Algorithm Sheet - See Figs. 22 and 23)

[0119] Rotational Speed ​​(R): Used in the algorithm (Stroke and Strike Algorithm Sheet - See Figs. 22 and 23)

[0120] Start Direction (ST): Used in the algorithm (Stroke and Strike Algorithm Sheet - See Figs. 22 and 23)

[0121] Launch (LN): Used in algorithms (Launch Algorithm Sheet - See Fig. 26)

[0122] Photo Settings Page 13

[0123] As can be seen in Fig. 15, the club fitter will take a photo and analyze the position with a new putter configuration, and then re-analyze the position with the recommended putter configuration as performed on pages 4 through 11 (pages 15 through 21 of the app, not shown).

[0124] Putter Components Page 23

[0125] As can be seen in Fig. 17, this page provides the club fitter with the option to adjust the settings and review the fitting process on page 14 (Fig. 16), namely "New Configuration Classification" or "Fitting Result Approval," which will then issue the putter specifications as a CSV (Fig. 18), a PDF summary page (Fig. 19), and an email (Fig. 20).

[0126] Example 2

[0127] Referring to FIG. 28, an exemplary component fitting system for manufacturing a multi-adjustable putter is illustrated, comprising a shaft; a putter head; and an adjustable and / or replaceable striking surface plate, based on the app data and analysis.

[0128] As described above, the putter fitting system is texture-neutral, meaning it is suitable for both left-handed and right-handed users, and also maintains the loft-to-sole relationship of the putter head when the loft of the hitting face plate is adjusted using an adjustable / replaceable hitting face plate.

[0129] With this configuration, the putter head remains on the shaft's neutral axis when the loft of the striking face plate is adjusted.

[0130] Example 3

[0131] Referring to FIG. 29, an embodiment of a putter head intended to be placed flat on the sole to create a consistent setting position is illustrated. It has been found that when the sole is substantially parallel to the ground, the player can correct the position of their eyes and the distance from the ball to where the putter is located. To enable this setting position, sight markings on the topline and the back of the flange of the putter are used to form a perspective adjustment tool.

[0132] Since the app fitting process uses the player's feel evaluation of a straight line that places the gaze on the inside of the ball (red dot or to the right of the center), for example, the putter is configured to have a topline sight point machined closer to the heel of the putter so that it aligns with the rear flange line when the sole is substantially parallel to the ground.

[0133] Example 4

[0134] Referring to FIG. 30, the modular characteristics of a putter head embodiment are illustrated, which allow for individual adjustment of the center of gravity (COG) when custom fitting, for example, by replacing the head, hosel, etc. In this way, based on stroke and strike tendencies, the COG can be substantially adjusted to align to achieve the most neutral spin axis of the golf ball for the player by enabling the player to hit the sweet spot of the striking plate of the head.

[0135] This configuration allows for the complete customization of the putter head, in which the putter is manufactured to have a greater toe-weighted bias—when it is found that the player consistently needs weight to position themselves to provide the sweet spot. For example, the blue dot (center left) in Fig. 30 indicates that the toe weight has increased by 10g and the heel has decreased by 10g.

[0136] Example 5

[0137] Referring to FIGS. 31A, B, C and FIGS. 32A, B, C, D, and E, the variable milling depth of the striking surface plate is illustrated. This configuration is used to control the speed of the ball.

[0138] The milling pattern is tailored according to the player's tendency. For example, a player who slices the ball spins the toe faster or slower.

[0139] Additionally, milling of the striking face plate is used to offset mis-shots. In this way, the milling depth can also offset the closed face of a toe strike due to a softened protrusion that starts the ball further to the right than the square face. Based on data collected from the custom fitting app, it can be determined whether a player who mis-hit a putt from the toe is slicing the ball, which often results in a pull. Subsequently, the milling is individually matched to help correct the missed putt, as shown in FIGS. 32 A, B, C, D, and E.

[0140] Example 6

[0141] Referring to Fig. 33, an optional screenshot or page of the app is shown. This is an additional parameter to be checked by the player and is another consideration when adjusting the player's adjustment characteristics. The player is instructed to set the ball approximately 12 feet above the hole. The app operator pushes the ball into the midpoint of the putt, and the player must inform the operator when to stop when crossing the putt. This process has been found to correlate with factors such as the dominant eye, distance from the ball, and alignment of the ball with the hole. For example, variations in these factors, such as choosing a ball further to the left, a farther, longer putter, and being more upright, will determine the type of correction that must be entered into the app.

[0142] It should be understood that aspects of the invention have been described merely by way of example, and that modifications and additions may be made without departing from the claims of this specification.

Claims

Claim 1 A method for fine-tuning a putter comprises: a) inputting user data into an app, wherein the user data includes data corresponding to attributes of the putter selected from one or more of the putter head, hosel, head weight, toe, heel, length, lie, loft, and grip; b) collecting additional data obtained from other putting measurement variables obtained from optional sensors, and from at least one of static and dynamic putting motion measurements obtained from a high-speed camera and computer analysis; c) packaging and collating the user data and the additional data within the app; and d) outputting the packaged and collated user data and the additional data from the app. and e) a step of analyzing and applying at least one algorithm to determine how the properties of said putter are correlated with a predetermined algorithm value for said putter set to maximize the consistency of the user’s stroke and the roll of the ball during putting, and to determine the exact specification of said properties of said putter for the user’s putter—said that the app generates a lookup table representing a normal distribution, said lookup table is physically calibrated using an n-column Galton board as a physical model of a binomial distribution, and only lookup values ​​from said Galton board calibrated normal distribution table are provided to a fitting routine—a method comprising. Claim 2 A method according to claim 1, wherein the app enables a user to capture and analyze a specific parameter selected from any one of the following: wrist-to-ground measurement, height, eye dominance, current putter length, aiming tendency, miss tendency, face rotation, posture, ball position face on, shaft lean face on, roll launch and spin, and stroke direction. Claim 3 A method according to claim 2, wherein the data collected from the specific parameters has a value for each data point used in an algorithm to determine the accurate putter specifications for a player. Claim 4 A method according to claim 2, wherein the face rotation is measured as the rotational speed of the face. Claim 5 A method according to claim 2, wherein the posture is measured based on any one of an eyeline position, a hand position relative to the shoulder, a relative angle between the shaft and the forearm, and the degree of the spine angle. Claim 6 A method according to any one of claims 1 to 3, wherein the app allows the user to adjust the specifications and report what choices should be made to achieve the desired result of manufacturing a player's putter that calculates the specifications. Claim 7 A method according to any one of claims 1 to 3, wherein the app is based on an analysis selected from any one of techniques, static position, dynamic movement and equipment recommendation. Claim 8 In claim 7, the static analysis check and dynamic analysis check performed by the app are visual methods. Claim 9 A method according to any one of claims 1 to 3, wherein the app is configured to operate with another technique for data point analysis selected from any one of MatLab, a Quintic Ball Roll Research System, a high-speed camera, and computer analysis; and wherein such technique is used to compare specific traits of the corresponding data point positions for use in the algorithm. Claim 10 A method according to any one of claims 1 to 3, wherein the app checks the relative position of the body to the club based on a statistical analysis derived from the binomial distribution and scores the position as an extreme value scale for a predetermined median scale in the binomial distribution to provide a value for the algorithm. Claim 11 A method according to any one of claims 1 to 3, wherein the putter specifications for an individual or user are derived from a consistent analysis of a data set from grouped data of a golfer to determine the trend; and since the grouped data is formed by aggregating individual observations of variables into groups, the frequency distribution of the groups serves as a means for summarizing or analyzing the data. Claim 12 A method according to any one of claims 1 to 3, wherein the app utilizes grouped data of golfers collected and analyzed to support consumer-driven research. Claim 13 A method according to any one of claims 1 to 3, wherein the algorithm within the app determines a rating scale or code to be input into the algorithm by utilizing data points or parameters taken from the measurement, selection, or classification of an image. Claim 14 A method according to claim 13, wherein the rating scale is arbitrarily rated from a scale of 1 to 5 that generates a number for a code; and such code is used in an algorithm and additionally input in relation to other variables to generate a recommendation derived from the algorithm. Claim 15 A method according to any one of claims 1 to 3, wherein the fitting matrix comprises at least 30,000 configurations selected from at least one of head shape and alignment line, head and total weight, hosel offset and rotation axis, lie angle, loft, length, and grip. Claim 16 The method of any one of claims 1 to 3, wherein the method further comprises: f) manufacturing a putter comprising a shaft, a putter head, and an adjustable, replaceable, adjustable and replaceable striking face plate based on output data of the app, wherein the adjustable, replaceable, adjustable and replaceable striking face plate maintains a loft-to-sole relationship of the putter head such that the putter head is maintained on a neutral axis with respect to the shaft when the loft of the striking face plate is adjusted. Claim 17 A method according to any one of claims 1 to 3, wherein the method further comprises: f) for each captured parameter, grading said parameter on an ordinal grading scale from 1 to 5 referencing a predetermined median value, thereby generating a set of coded values ​​for the user; and g) examining a multidimensional fitting matrix comprising at least 30,000 individual putter configurations defined by combinations of said coded parameter values ​​to select a putter specification corresponding to said coded values ​​for the user. Claim 18 A fine-tuned putter manufactured for each individual based on the output data of the method and app described in any one of claims 1 to 3. Claim 19 A fine-tuned putter according to claim 18, wherein sight markings on the topline of the putter and on the line on the rear surface of the flange of the putter are used to create a perspective alignment tool; and the putter is configured to have a topline sight dot machined closer to the heel of the putter so as to line up with the rear flange line when the sole is parallel to the ground. Claim 20 A fine-tuned putter according to claim 18, wherein the striking face plate is milled to a variable milling depth to control the speed of the ball. Claim 21 A fine-tuned putter according to claim 20, wherein the milling is custom-milled based on the player's tendency to reduce misit putts. Claim 22 A fitting system for manufacturing a multi-adjustable putter, wherein the putter comprises: a shaft; a putter head; and an adjustable, replaceable, adjustable and replaceable striking face plate; wherein the adjustable, replaceable, adjustable and replaceable striking face plate is configured to maintain a loft-to-sole relationship of the putter head such that the putter head is maintained on a neutral axis relative to the shaft when the loft of the striking face plate is adjusted; wherein the putter head comprises a groove configured to accommodate a complementary insert, and wherein the insert and the striking face plate are indexable according to a 0.5-degree loft increase so that the striking face plate can be mounted at different loft angles while the sole plane of the putter head remains constant; wherein the putter head allows for an alignment of the center of gravity (COG) of the putter tailored to the individual, wherein the COG is aligned with the center of the striking face plate to obtain the most neutral spin axis of the golf ball, thereby enabling the individual to strike the golf ball at the optimal position of the striking face plate of the putter head. A fitting system that allows for this.

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