TWI870326B - Method and system for analyzing pickleball players' hitting performance and grading pickleball players - Google Patents

Abstract

The present invention discloses a method for analyzing the hitting performance of a pickleball player and grading the pickleball player, comprising the following steps: S1: obtaining hitting information of at least one player to be analyzed in a game, and quantifying it to obtain analysis data; S2: importing the analysis data into an analysis module that conforms to the age grouping according to the age of the player to be analyzed, and obtaining a plurality of winning factor grading information for the player to be analyzed; S3: assessing a hitting performance grade of the player to be analyzed according to the winning factor grading information; S4: calculating a comprehensive grade of the player to be analyzed based on the hitting performance grade. Accordingly, the present invention can quickly and accurately calculate the corresponding rating based on specific winning factor rating information, and comprehensively average the player's rating to obtain an objective and fair evaluation result.

Description

Method and system for analyzing pickleball players' hitting performance and grading pickleball players

The present invention relates to sports data analysis, and more particularly to a method and system for analyzing the hitting performance of pickleball players and grading pickleball players.

The most common pickleball grading system is as follows:

1. USAP Subjective Rating System

The system classifies players into eight levels, from beginner (1.0-2.0) to professional (5.5), based on their forehand, backhand, serve/return, dink, third shot, volley, and tackling abilities. However, since the system relies on the subjective judgment of the graders, players may have different ratings in different environments. For example, a player rated 5.0 by a coach in country A may only be rated 4.0-4.5 by a coach in country B.

2. International Professional Pickleball Teaching Association (IPTPA) test grading system

The system divides players into six levels from beginner (2.0) to top (4.5) based on the test results. The IPTPA's grading items and content are more detailed and specific. The test can quantify the actual technical ability of the players, so the grading can be more objective. However, the testing process is time-consuming and labor-intensive, and players who fail the grading assessment need to pay to retake the test. In addition, this grading method usually requires the support of coaching courses, which reduces the willingness of players to accept this grading, and it is ultimately classified as teaching grading.

3. DUPR (Dynamic Universal Pickleball Rating)

The system collects the results of pickleball games between members and uses the difference in scores to determine the level. The system organizes members to play in pairs regardless of age, so it is impossible to hold large-scale formal competitions. In addition, if a player attaches too much importance to the level, he may refuse to play because he does not want to play with a partner of a lower level, thereby avoiding a drop in level after losing. Since the data of the grading system is manually input, there is a risk of data falsification and the credibility is low.

4. Classification of major events

In large-scale competitions, the top three players in individual competitions will be promoted to the next level. However, in order to get the next medal, players often choose to ignore the fact that they have already received a medal and underreport their level, causing confusion and complaints from the organizers in dealing with the players' level cognition.

Therefore, the main purpose of the present invention is to provide a method for analyzing the hitting performance of pickleball players and grading pickleball players, which can quickly and accurately calculate the corresponding grades based on specific winning factor grading information, and comprehensively average the player's grade grades, thereby obtaining objective and fair evaluation results compared to the traditional grading system.

Therefore, in order to achieve the above-mentioned purpose, the method of analyzing the hitting performance of pickleball players and grading the pickleball players disclosed in the present invention includes the following steps: S1: obtaining hitting information of at least one player to be analyzed in a game, and quantifying it to obtain analysis data; S2: importing the analysis data into an analysis module that conforms to the age grouping according to the age of the player to be analyzed, and obtaining a plurality of winning factor grading information for the player to be analyzed; S3: assessing a hitting performance grade of the player to be analyzed based on the winning factor grading information; S4: calculating a comprehensive grade of the player to be analyzed based on the hitting performance grade.

In one embodiment, in step S1, an image recognition technology is used to analyze the player to be analyzed from an image of the game and obtain the hitting information.

In one embodiment, in step S1, the player to be analyzed is numbered, and the batting information includes a player code that matches the player to be analyzed.

In one embodiment, in step S1, the batting skills used by the player to be analyzed in different batting stages are recorded, so that the batting information includes the batting stages and the batting skills. The batting stages are serving, receiving serve, long dink, short dink, low (flat) net attack, volley, mid-backcourt strong drive, smash, offensive (starting near the non-volley line) high lob backcourt, off-court round-the-post drive, defensive (starting in the mid-backcourt) high lob backcourt, short lob, or average number of seconds to the net after returning the serve. The batting skills are forehand shot, backhand shot, forehand topspin, forehand backspin, forehand flat shot, forehand side spin, backhand topspin, backhand backspin, backhand flat shot, or backhand side spin.

In one embodiment, in step S1, each of the hitting phases and the corresponding hitting skills are quantified as the analysis data, and the analysis data includes a normal hitting record based on the player code, a tracking unforced error number record, a tracking forced error number record, a tracking forced defense success number record, a tracking average number of seconds to the net after returning the serve, and a topspin, backspin, side spin and flat shot record.

In one embodiment, in step S2, the analysis module is divided into a first age-level analysis module, a second age-level analysis module, a third age-level analysis module and a fourth age-level analysis module according to age. The age range of the first age-level analysis module is between 16 and 34 years old, the age range of the second age-level analysis module is between 35 and 49 years old, the age range of the third age-level analysis module is between 50 and 64 years old, and the age range of the fourth age-level analysis module is above 65 years old.

In one embodiment, in step S2, different winning factor graded information are respectively a serve winning factor, a return serve winning factor, a long dink winning factor, a long dink defense success rate winning factor, a short dink winning factor, a short dink defense success rate winning factor, a low (flat) net attack winning factor, a volley winning factor, a middle and backcourt strong drive winning factor, a smash winning factor, an offensive (frontcourt) lob winning factor, a defensive (middle and backcourt) lob winning factor, an outside post drive winning factor, a lob short ball winning factor, an attack phase winning factor, an attack phase forced defense success rate winning factor, and an average number of seconds to the net after a return serve winning factor.

In one embodiment, in step S2, the serve winning factor, the return serve winning factor, the long dink winning factor, the short dink winning factor, the low (flat) net attack winning factor, the volley winning factor, the mid-back court strong drive winning factor, the smash winning factor, the offensive (front court) lob winning factor, the defensive (mid-back court) lob winning factor, the off-court post drive winning factor, the lob short ball winning factor, and the attack phase winning factor are respectively calculated to obtain an unforced error rate using the following formula:

Unforced error rate = number of unforced errors / (total number of shots - number of high-pressure forced shots).

In one embodiment, in step S2, the long DINK defense success rate winning factor, the short DINK defense success rate winning factor, and the attack phase forced defense success rate winning factor are respectively calculated to obtain a forced defense force using the following formulas:

Forced defense = number of successfully defended balls when forced / number of forced balls under high pressure.

In one embodiment, in step S3, each unforced error rate, each forced defense force and the average number of seconds to the net after a serve are used for evaluation, so that the batting performance level includes a serve level, a serve level, a long dink level, a long dink defense success rate level, a short dink level, a short dink defense success rate level, a low (flat) net power attack level, a volley level, a middle and backcourt power drive level, a smash level, an offensive (frontcourt) lob level, a defensive (middle and backcourt) lob level, an outside post drive level, a lob short ball level, an attack phase level, an attack phase forced defense success rate level, and an average number of seconds to the net after a serve level.

In one embodiment, in step S4, the comprehensive grade is calculated based on the serve grade, the return serve grade, the long dink grade, the long dink defense success rate grade, the short dink grade, the short dink defense success rate grade, the low (flat) net attack grade, the volley grade, the mid-backcourt strong drive grade, the smash grade, the offensive (frontcourt) lob grade, the defensive (mid-backcourt) lob grade, the off-court drive grade, the lob short ball grade, the attack phase grade, the forced defense success rate grade in the attack phase, and the average number of seconds to the net after the return serve grade.

In addition, the present invention also provides a system for analyzing the hitting performance of pickleball players and grading pickleball players, including a processing unit for executing the aforementioned method.

Unless otherwise specifically defined, all technical and scientific terms used in this invention have the same meaning as those generally understood by persons of ordinary skill in the field to which this invention belongs. For example, the relevant records of pickleball in this invention can be found in the pickleball competition rules published by the American Pickleball Association in 2020, which should be known to persons of ordinary skill, such as:

The term "Dink ball" in the present invention refers to the rule that players are prohibited from entering the non-volley zone to volley the opponent's ball. Therefore, players can use this point to hit the ball into the non-volley zone and make the ball fall to the ground, so that the opponent cannot immediately attack us. This ball route is called Dink ball.

The term "unforced error rate" in the present invention refers to the number of unforced errors of the hitting side as the numerator and the number of unforced incoming balls as the denominator. The result obtained according to this formula is called the unforced error rate.

The term "forced defensive power" in the present invention refers to the number of successfully defended balls when forced as the numerator and the total number of high-pressure forced balls as the denominator. The result obtained by this formula is called unforced defensive power.

The present invention defines: as shown in FIG. 3 , the total hit types during the game are classified into “unforced” and “forced under high pressure”, and each ball is classified into five categories: “winning ball”, “normal shot”, “unforced error ball”, “successful defense when forced” and “forced error ball”.

The present invention further defines that when the defending player is attacked by the attacking player and is "forced by high pressure", there are three situations: "successful defense", "forced error ball" and "forced high rise"; "successful defense" is defined as: "saving the ball that the attacking player should have scored, and the saved ball also prevents the attacking player from launching a fatal attack again", and successful defense also allows the defending side to return to the "double net stage" or "short dink stage" to continue the game; and the "forced high rise" ball over the net depends on the attacking player's hitting situation. If the attacking player can grasp the high ball and make a fatal shot, this shot will be recorded as a "forced error" for the defending player, and at the same time, a "winning shot" or "normal shot" will be recorded for the attacking player. If the attacking player cannot grasp the rare high ball, resulting in the subsequent normal shots with the defending player, this shot will be recorded as a "normal shot" for the attacking player. If the attacking player cannot grasp the rare high ball and makes a mistake in the shot, it will be judged as an "unforced error" for the attacking player.

Please refer to FIG. 1 , which is a method for analyzing the hitting performance of a pickleball player and grading the pickleball player according to a preferred embodiment of the present invention, including the following steps:

S1: obtaining a shot information of at least one player to be analyzed in a game, and quantifying it to obtain an analysis data;

S2: according to the age of the player to be analyzed, the analysis data is introduced into an analysis module that matches the age group, so as to obtain the multiple winning factor grading information of the player to be analyzed;

S3: Assessing the batting performance level of the player to be analyzed based on the winning factor grading information;

S4: Calculating a comprehensive level of the player to be analyzed based on the batting performance level.

In detail, these steps include at least the following:

In step S1, an image recognition technology is used to analyze the player to be analyzed from an image of the game and obtain the hitting information. The image recognition technology is AI image recognition (i.e., a technology that uses a machine to automatically recognize an image and accurately and effectively describe the image) or manual recognition, and the image is a video record of a historical event.

In step S1, the players to be analyzed are numbered so that the batting information includes a player code that matches the player to be analyzed, such as 1, 2, 3, 4. In other words, the number of players to be analyzed can be 1, 2, or 4, and different players to be analyzed are given corresponding numbers.

In step S1, the batting skills used by the player to be analyzed in different batting stages are recorded, so that the batting information includes the batting stages and the batting skills. The batting stages are serving, receiving serve, long dink, short dink, low (flat) net attack, volley, mid-backcourt strong drive, smash, offensive (starting near the non-volley line) high lob backcourt, off-court round-the-post drive, defensive (starting in the mid-backcourt) high lob backcourt, lob short ball, or average number of seconds to the net after returning the serve. The batting skills are forehand shot, backhand shot, forehand top spin, forehand underspin, forehand flat shot, forehand side spin, backhand top spin, backhand underspin, backhand flat shot, or backhand side spin.

In step S1, each of the hitting phases and the corresponding hitting skills are quantified as the analysis data, and the analysis data includes a record of tracking winning balls, a record of tracking normal hitting balls (e.g., 1, 2, 3, 4), a record of tracking the number of unforced errors (e.g., 1.5, 2.5, 3.5, 4.5), and a record of tracking the number of forced errors (e.g., 1.5, 2.5, 3.5, 4.5) recorded based on the player code. such as 1.55, 2.55, 3.55, 4.55), one record to track the number of successful forced defense balls (such as 1.6, 2.6, 3.6, 4.6), one record to track the average number of seconds to the net after returning a serve (such as 1.95 seconds, 2.01 seconds), one record of topspin, backspin, side spin and flat shots (for example, different colors are used to distinguish topspin, backspin, side spin and flat shots).

In step S2, the analysis module is divided into a first age-level analysis module, a second age-level analysis module, a third age-level analysis module and a fourth age-level analysis module according to age. The age range of the first age-level analysis module is between 16 and 34 years old, the age range of the second age-level analysis module is between 35 and 49 years old, the age range of the third age-level analysis module is between 50 and 64 years old, and the age range of the fourth age-level analysis module is above 65 years old.

In step S2, different winning factor classification information are respectively a serving winning factor, a return serving winning factor, a long dink winning factor, a long dink defense success rate winning factor, a short dink winning factor, a short dink defense success rate winning factor, a low (flat) net attack winning factor, a volley winning factor, a middle and back court strong drive winning factor, a smash winning factor, an offensive (front court) lob winning factor, a defensive (middle and back court) lob winning factor, an outside post drive winning factor, a lob short ball winning factor, an attack phase winning factor, an attack phase forced defense success rate winning factor, and an average number of seconds to the net after a return serving winning factor.

In step S2, the serve winning factor, the return serve winning factor, the long dink winning factor, the short dink winning factor, the low (flat) net attack winning factor, the volley winning factor, the mid-back court strong drive winning factor, the smash winning factor, the offensive (front court) lob winning factor, the defensive (mid-back court) lob winning factor, the off-court post drive winning factor, the lob short ball winning factor, and the attack phase winning factor are respectively calculated to obtain an unforced error rate using the following formula:

Unforced error rate = number of unforced errors / (total number of shots - number of high-pressure forced shots).

In step S2, the long DINK defense success rate winning factor, the short DINK defense success rate winning factor, and the attack phase forced defense success rate winning factor are respectively calculated to obtain a forced defense force using the following formulas;

Forced defense = number of successfully defended balls when forced / number of forced balls under high pressure.

Among them, different forced defense capabilities

In step S3, the evaluation is performed based on each unforced error rate, each forced defense power, or the average number of seconds to the net after serving back, so that the batting performance level includes a serving level, a serving back level, a long dink level, a long dink defense success rate level, a short dink level, a short dink defense success rate level, a low (flat) net power attack level, a volley level, a middle and backcourt power drive level, a smash level, an offensive (frontcourt) lob level, a defensive (middle and backcourt) lob level, an outside drive level, a short lob level, an attack phase level, an attack phase forced defense success rate level, and an average number of seconds to the net after serving back level.

Specifically, the following describes each of these levels in more detail:

The value of the serve rating is 2, 2.5, 3, 3.5, 4, 4.5, or 6, and is applicable to all age levels (i.e., the first age level analysis module, the second age level analysis module, the third age level analysis module, and the fourth age level analysis module). The relationship between the value of the serve rating and the unforced error rate is shown in Table 1, and the error range of the unforced error rate is ±15%, with a minimum of 0%.

Table 1. Relationship between serve rating and unforced error rate Unforced Error Rate Serve Grading Unforced error rate ≤ 5% Level 6 5% ＜ Unforced error rate ≤ 10% 4.5 10% ＜ Unforced error rate ≤ 20% Level 4 20% ＜ Unforced error rate ≤ 30% Level 3.5 30% ＜ Unforced error rate ≤ 40% Level 3 40% ＜ Unforced error rate ≤ 50% Level 2.5 Unforced error rate ≥ 50.1% Level 2

The return serve grade is 2, 2.5, 3, 3.5, 4, 4.5, or 6. Table 2 illustrates that different return serve grade values are based on analysis modules of different age groups and are obtained according to different unforced error rate ranges. The error range of the unforced error rate is ±15%, and the minimum value is 0%.

Table 2. Relationship between serve return rating and unforced error rate Analysis Module Unforced Error Rate Serve return rating value First Age Level Analysis Module Unforced error rate ≤ 5% Level 6 5% ＜ Unforced error rate ≤ 10% 4.5 10% ＜ Unforced error rate ≤ 20% Level 4 20% ＜ Unforced error rate ≤ 30% Level 3.5 30% ＜ Unforced error rate ≤ 40% Level 3 40% ＜ Unforced error rate ≤ 50% Level 2.5 Unforced error rate ≥ 50.1% Level 2 Second Age Analysis Module Unforced error rate ≤ 10% Level 6 10% ＜ Unforced error rate ≤ 15% 4.5 15% ＜ Unforced error rate ≤ 25% Level 4 25% ＜ Unforced error rate ≤ 35% Level 3.5 35% ＜ Unforced error rate ≤ 45% Level 3 45% ＜ Unforced error rate ≤ 55% Level 2.5 Unforced error rate ≥ 55.1% Level 2 Third Age Analysis Module Unforced error rate ≤ 15% Level 6 15% ＜ Unforced error rate ≤ 20% 4.5 20% ＜ Unforced error rate ≤ 30% Level 4 30% ＜ Unforced error rate ≤ 40% Level 3.5 40% ＜ Unforced error rate ≤ 50% Level 3 50% ＜ Unforced error rate ≤ 60% Level 2.5 Unforced error rate ≥ 60.1% Level 2 Fourth-year age group analysis module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 35% Level 4 35% ＜ Unforced error rate ≤ 45% Level 3.5 45% ＜ Unforced error rate ≤ 55% Level 3 55% ＜ Unforced error rate ≤ 65% Level 2.5 Unforced error rate ≥ 65.1% Level 2

The values of the Long Dink rating are 2, 2.5, 3, 3.5, 4, 4.5, or 6. Table 3 shows that different Long Dink rating values are based on analysis modules of different age groups and are obtained according to different unforced error rate ranges. The error range of the unforced error rate is ±15% and the minimum value is 0%.

Table 3. Relationship between the value of Long Dink rating and unforced error rate Analysis Module Unforced Error Rate Long Dink Rating Value First Age Level Analysis Module Unforced error rate ≤ 15% Level 6 15% ＜ Unforced error rate ≤ 20% 4.5 20% ＜ Unforced error rate ≤ 30% Level 4 30% ＜ Unforced error rate ≤ 40% Level 3.5 40% ＜ Unforced error rate ≤ 50% Level 3 50% ＜ Unforced error rate ≤ 60% Level 2.5 Unforced error rate ≥ 60.1% Level 2 Second Age Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 35% Level 4 35% ＜ Unforced error rate ≤ 45% Level 3.5 45% ＜ Unforced error rate ≤ 55% Level 3 55% ＜ Unforced error rate ≤ 65% Level 2.5 Unforced error rate ≥ 65.1% Level 2 Third Age Analysis Module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 40% Level 4 40% ＜ Unforced error rate ≤ 50% Level 3.5 50% ＜ Unforced error rate ≤ 60% Level 3 60% ＜ Unforced error rate ≤ 70% Level 2.5 Unforced error rate ≥ 70.1% Level 2 Fourth-year age group analysis module Unforced error rate ≤ 30% Level 6 30% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 45% Level 4 45% ＜ Unforced error rate ≤ 55% Level 3.5 55% ＜ Unforced error rate ≤ 65% Level 3 65% ＜ Unforced error rate ≤ 75% Level 2.5 Unforced error rate ≥ 75.1% Level 2

The long DINK defense success rate grading values are 2, 2.5, 3, 3.5, 4, 4.5, or 6, and Table 4 illustrates that different long DINK defense success rate grading values are based on analysis modules of different age groups and are obtained according to different forced defense force ranges, and the error coverage range of the forced defense force is ±15%, with a minimum of 0%.

Table 4. Relationship between the value of the long DINK defense success rate rating and the forced defense capability Analysis Module Forced Defense Long Dink Defense Success Rate Grade Value First Age Level Analysis Module Forced defense ≧ 80% Level 6 70% ≤ Forced Defense Capability＜ 80% 4.5 60% ≤ Forced Defense Capability＜ 70% Level 4 50% ≤ Forced Defense Capability＜ 60% Level 3.5 40% ≤ Forced Defense Capability＜ 50% Level 3 30% ≤ Forced Defense Capability＜ 40% Level 2.5 Forced defense ≤ 29.9% Level 2 Second Age Analysis Module Forced defense ≧ 75% Level 6 65% ≤ Forced Defense Capability＜ 75% 4.5 55% ≤ Forced Defense Capability＜ 65% Level 4 45% ≤ Forced Defense Capability＜ 55% Level 3.5 35% ≤ Forced Defense Capability＜ 45% Level 3 25% ≤ Forced Defense Capability＜ 35% Level 2.5 Forced defense ≤ 24.9% Level 2 Third Age Analysis Module Forced defense ≧ 70% Level 6 60% ≤ Forced Defense Capability＜ 70% 4.5 50% ≤ Forced Defense Capability＜ 60% Level 4 40% ≤ Forced Defense Capability＜ 50% Level 3.5 30% ≤ Forced Defense Capability＜ 40% Level 3 20% ≤ Forced Defense Capability＜ 30% Level 2.5 Forced defense ≤ 19.9% Level 2 Fourth-year age group analysis module Forced defense ≧ 65% Level 6 55% ≤ Forced Defense Capability＜ 65% 4.5 45% ≤ Forced Defense Capability＜ 55% Level 4 35% ≤ Forced Defense Capability＜ 45% Level 3.5 25% ≤ Forced Defense Capability＜ 35% Level 3 15% ≤ Forced Defense Capability＜ 25% Level 2.5 Forced defense ≤ 14.9% Level 2

The values of the short DINK rating are 2, 2.5, 3, 3.5, 4, 4.5, or 6, and Table 5 illustrates that different short DINK rating values are based on analysis modules of different age levels and are obtained according to different unforced error rate ranges, and the error range of the unforced error rate is ±15% and the minimum value is 0%.

Table 5. Relationship between the value of short DINK rating and unforced error rate Analysis Module Unforced Error Rate Short Dink Rating Value First Age Level Analysis Module Unforced error rate ≤ 10% Level 6 10% ＜ Unforced error rate ≤ 20% 4.5 20% ＜ Unforced error rate ≤ 30% Level 4 30% ＜ Unforced error rate ≤ 40% Level 3.5 40% ＜ Unforced error rate ≤ 50% Level 3 50% ＜ Unforced error rate ≤ 60% Level 2.5 Unforced error rate ≥ 60.1% Level 2 Second Age Analysis Module Unforced error rate ≤ 15% Level 6 15% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 35% Level 4 35% ＜ Unforced error rate ≤ 45% Level 3.5 45% ＜ Unforced error rate ≤ 55% Level 3 55% ＜ Unforced error rate ≤ 65% Level 2.5 Unforced error rate ≥ 65.1% Level 2 Third Age Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 40% Level 4 40% ＜ Unforced error rate ≤ 50% Level 3.5 50% ＜ Unforced error rate ≤ 60% Level 3 60% ＜ Unforced error rate ≤ 70% Level 2.5 Unforced error rate ≥ 70.1% Level 2 Fourth-year age group analysis module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 45% Level 4 45% ＜ Unforced error rate ≤ 55% Level 3.5 55% ＜ Unforced error rate ≤ 65% Level 3 65% ＜ Unforced error rate ≤ 75% Level 2.5 Unforced error rate ≥ 75.1% Level 2

The short DINK defense success rate grading values are 2, 2.5, 3, 3.5, 4, 4.5, or 6, and Table 6 illustrates that different short DINK defense success rate grading values are based on analysis modules of different age groups and are obtained according to different forced defense force ranges, and the error coverage range of the forced defense force is ±15%, with a minimum of 0%.

Table 6. Relationship between the value of the short-term defense success rate rating and the forced defense capability Analysis Module Forced Defense Short DINK defense success rate rating value First Age Level Analysis Module Forced defense ≧ 80% Level 6 70% ≤ Forced Defense Capability＜ 80% 4.5 60% ≤ Forced Defense Capability＜ 70% Level 4 50% ≤ Forced Defense Capability＜ 60% Level 3.5 40% ≤ Forced Defense Capability＜ 50% Level 3 30% ≤ Forced Defense Capability＜ 40% Level 2.5 Forced defense ≤ 29.9% Level 2 Second Age Analysis Module Forced defense ≧ 75% Level 6 65% ≤ Forced Defense Capability＜ 75% 4.5 55% ≤ Forced Defense Capability＜ 65% Level 4 45% ≤ Forced Defense Capability＜ 55% Level 3.5 35% ≤ Forced Defense Capability＜ 45% Level 3 25% ≤ Forced Defense Capability＜ 35% Level 2.5 Forced defense ≤ 24.9% Level 2 Third Age Analysis Module Forced defense ≧ 70% Level 6 60% ≤ Forced Defense Capability＜ 70% 4.5 50% ≤ Forced Defense Capability＜ 60% Level 4 40% ≤ Forced Defense Capability＜ 50% Level 3.5 30% ≤ Forced Defense Capability＜ 40% Level 3 20% ≤ Forced Defense Capability＜ 30% Level 2.5 Forced defense ≤ 19.9% Level 2 Fourth-year age group analysis module Forced defense ≧ 65% Level 6 55% ≤ Forced Defense Capability＜ 65% 4.5 45% ≤ Forced Defense Capability＜ 55% Level 4 35% ≤ Forced Defense Capability＜ 45% Level 3.5 25% ≤ Forced Defense Capability＜ 35% Level 3 15% ≤ Forced Defense Capability＜ 25% Level 2.5 Forced defense ≤ 14.9% Level 2

The value of the low (flat) net attack grade is 2, 2.5, 3, 3.5, 4, 4.5, or 6. Table 7 illustrates that different low (flat) net attack grade values are based on analysis modules of different age groups and are obtained according to different unforced error rate ranges, and the error range of the unforced error rate is ±15%, and the minimum value is 0%.

Table 7. Relationship between the value of low (flat) net attack rating and unforced error rate Analysis Module Unforced Error Rate Low (flat) net attack rating value First Age Level Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 30% Level 4 30% ＜ Unforced error rate ≤ 35% Level 3.5 35% ＜ Unforced error rate ≤ 40% Level 3 40% ＜ Unforced error rate ≤ 45% Level 2.5 Unforced error rate ≥ 45.1% Level 2 Second Age Analysis Module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 35% Level 4 35% ＜ Unforced error rate ≤ 40% Level 3.5 40% ＜ Unforced error rate ≤ 45% Level 3 45% ＜ Unforced error rate ≤ 50% Level 2.5 Unforced error rate ≥ 50.1% Level 2 Third Age Analysis Module Unforced error rate ≤ 30% Level 6 30% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 40% Level 4 40% ＜ Unforced error rate ≤ 45% Level 3.5 45% ＜ Unforced error rate ≤ 50% Level 3 50% ＜ Unforced error rate ≤ 55% Level 2.5 Unforced error rate ≥ 55.1% Level 2 Fourth-year age group analysis module Unforced error rate ≤ 35% Level 6 35% ＜ Unforced error rate ≤ 40% 4.5 40% ＜ Unforced error rate ≤ 45% Level 4 45% ＜ Unforced error rate ≤ 50% Level 3.5 50% ＜ Unforced error rate ≤ 55% Level 3 55% ＜ Unforced error rate ≤ 60% Level 2.5 Unforced error rate ≥ 60.1% Level 2

The value of the volley rating is 2, 2.5, 3, 3.5, 4, 4.5, or 6, and Table 8 illustrates that different low volley rating values are obtained based on different age-level analysis modules and according to different unforced error rate ranges, and the error coverage of the unforced error rate (the first age-level analysis module, the second age-level analysis module, and the third age-level analysis module) is ±15%, with a minimum value of 0%, and the error coverage of the unforced error rate of the fourth age-level analysis module is ±20%.

Table 8. Relationship between the value of volley rating and unforced error rate Analysis Module Unforced Error Rate Intercept rating value First Age Level Analysis Module Unforced error rate ≤ 10% Level 6 10% ＜ Unforced error rate ≤ 20% 4.5 20% ＜ Unforced error rate ≤ 25% Level 4 25% ＜ Unforced error rate ≤ 30% Level 3.5 30% ＜ Unforced error rate ≤ 35% Level 3 35% ＜ Unforced error rate ≤ 40% Level 2.5 Unforced error rate ≥ 40.1% Level 2 Second Age Analysis Module Unforced error rate ≤ 15% Level 6 15% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 30% Level 4 30% ＜ Unforced error rate ≤ 35% Level 3.5 35% ＜ Unforced error rate ≤ 40% Level 3 40% ＜ Unforced error rate ≤ 45% Level 2.5 Unforced error rate ≥ 45.1% Level 2 Third Age Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 35% Level 4 35% ＜ Unforced error rate ≤ 40% Level 3.5 40% ＜ Unforced error rate ≤ 45% Level 3 45% ＜ Unforced error rate ≤ 50% Level 2.5 Unforced error rate ≥ 50.1% Level 2 Fourth-year age group analysis module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 40% Level 4 40% ＜ Unforced error rate ≤ 45% Level 3.5 45% ＜ Unforced error rate ≤ 50% Level 3 50% ＜ Unforced error rate ≤ 55% Level 2.5 Unforced error rate ≥ 55.1% Level 2

The value of the mid-to-back field strong draw grade is 2, 2.5, 3, 3.5, 4, 4.5, or 6, and Table 9 illustrates that different mid-to-back field strong draw grade values are based on analysis modules of different age levels and are obtained according to different unforced error rate ranges, and the error coverage of the unforced error rate (the first age level analysis module, the second age level analysis module, and the third age level analysis module) is ±15%, with a minimum value of 0%, and the error coverage of the unforced error rate of the fourth age level analysis module is ±20%.

Table 9. Relationship between the mid-court and back-court power-pushing ratings and the unforced error rate Analysis Module Unforced Error Rate The value of the midfield strong draw First Age Level Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 30% Level 4 30% ＜ Unforced error rate ≤ 35% Level 3.5 35% ＜ Unforced error rate ≤ 40% Level 3 40% ＜ Unforced error rate ≤ 45% Level 2.5 Unforced error rate ≥ 45.1% Level 2 Second Age Analysis Module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 35% Level 4 35% ＜ Unforced error rate ≤ 40% Level 3.5 40% ＜ Unforced error rate ≤ 45% Level 3 45% ＜ Unforced error rate ≤ 50% Level 2.5 Unforced error rate ≥ 50.1% Level 2 Third Age Analysis Module Unforced error rate ≤ 30% Level 6 30% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 40% Level 4 40% ＜ Unforced error rate ≤ 45% Level 3.5 45% ＜ Unforced error rate ≤ 50% Level 3 50% ＜ Unforced error rate ≤ 55% Level 2.5 Unforced error rate ≥ 55.1% Level 2 Fourth-year age group analysis module Unforced error rate ≤ 35% Level 6 35% ＜ Unforced error rate ≤ 40% 4.5 40% ＜ Unforced error rate ≤ 45% Level 4 45% ＜ Unforced error rate ≤ 50% Level 3.5 50% ＜ Unforced error rate ≤ 55% Level 3 55% ＜ Unforced error rate ≤ 60% Level 2.5 Unforced error rate ≥ 60.1% Level 2

The value of the spike level is 2, 2.5, 3, 3.5, 4, 4.5, or 6, and Table 10 illustrates that different mid-spiking level values are based on analysis modules of different age levels and are obtained according to different unforced error rate ranges, and the error coverage of the unforced error rate (the first age level analysis module, the second age level analysis module, and the third age level analysis module) is ±15%, with a minimum value of 0%, and the error coverage of the unforced error rate of the fourth age level analysis module is ±20%.

Table 10. Relationship between the value of smash rating and unforced error rate Analysis Module Unforced Error Rate Deduction level value First Age Level Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 30% Level 4 30% ＜ Unforced error rate ≤ 35% Level 3.5 35% ＜ Unforced error rate ≤ 40% Level 3 40% ＜ Unforced error rate ≤ 45% Level 2.5 Unforced error rate ≥ 45.1% Level 2 Second Age Analysis Module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 35% Level 4 35% ＜ Unforced error rate ≤ 40% Level 3.5 40% ＜ Unforced error rate ≤ 45% Level 3 45% ＜ Unforced error rate ≤ 50% Level 2.5 Unforced error rate ≥ 50.1% Level 2 Third Age Analysis Module Unforced error rate ≤ 30% Level 6 30% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 40% Level 4 40% ＜ Unforced error rate ≤ 45% Level 3.5 45% ＜ Unforced error rate ≤ 50% Level 3 50% ＜ Unforced error rate ≤ 55% Level 2.5 Unforced error rate ≥ 55.1% Level 2 Fourth-year age group analysis module Unforced error rate ≤ 35% Level 6 35% ＜ Unforced error rate ≤ 40% 4.5 40% ＜ Unforced error rate ≤ 45% Level 4 45% ＜ Unforced error rate ≤ 50% Level 3.5 50% ＜ Unforced error rate ≤ 55% Level 3 55% ＜ Unforced error rate ≤ 60% Level 2.5 Unforced error rate ≥ 60.1% Level 2

The offensive high-back grading value is level 2, level 2.5, level 3, level 3.5, level 4, level 4.5, or level 6, and Table 11 illustrates that different offensive high-back grading values are based on analysis modules of different age levels and are obtained according to different unforced error rate ranges, and the error coverage of the unforced error rate (the first age level analysis module, the second age level analysis module, and the third age level analysis module) is ±15%, with a minimum value of 0%, and the error coverage of the unforced error rate of the fourth age level analysis module is ±20%.

Table 11. Relationship between the offensive high-backcourt grade and the unforced error rate Analysis Module Unforced Error Rate Offensive high-hanging backcourt rating value First Age Level Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 30% Level 4 30% ＜ Unforced error rate ≤ 35% Level 3.5 35% ＜ Unforced error rate ≤ 40% Level 3 40% ＜ Unforced error rate ≤ 45% Level 2.5 Unforced error rate ≥ 45.1% Level 2 Second Age Analysis Module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 35% Level 4 35% ＜ Unforced error rate ≤ 40% Level 3.5 40% ＜ Unforced error rate ≤ 45% Level 3 45% ＜ Unforced error rate ≤ 50% Level 2.5 Unforced error rate ≥ 50.1% Level 2 Third Age Analysis Module Unforced error rate ≤ 30% Level 6 30% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 40% Level 4 40% ＜ Unforced error rate ≤ 45% Level 3.5 45% ＜ Unforced error rate ≤ 50% Level 3 50% ＜ Unforced error rate ≤ 55% Level 2.5 Unforced error rate ≥ 55.1% Level 2 Fourth-year age group analysis module Unforced error rate ≤ 35% Level 6 35% ＜ Unforced error rate ≤ 40% 4.5 40% ＜ Unforced error rate ≤ 45% Level 4 45% ＜ Unforced error rate ≤ 50% Level 3.5 50% ＜ Unforced error rate ≤ 55% Level 3 55% ＜ Unforced error rate ≤ 60% Level 2.5 Unforced error rate ≥ 60.1% Level 2

The value of the defensive high-hang backcourt grade is level 2, level 2.5, level 3, level 3.5, level 4, level 4.5, or level 6. Table 12 illustrates that different defensive high-hang backcourt grade values are based on analysis modules of different age levels and are obtained according to different unforced error rate ranges, and the error coverage of the unforced error rate (the first age-level analysis module, the second age-level analysis module, and the third age-level analysis module) is ±15%, with a minimum value of 0%, and the error coverage of the unforced error rate of the fourth age-level analysis module is ±20%.

Table 12. Relationship between the defensive high-lofted backcourt rating and the unforced error rate Analysis Module Unforced Error Rate Defensive Lofted Backcourt Rating Values First Age Level Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 30% Level 4 30% ＜ Unforced error rate ≤ 35% Level 3.5 35% ＜ Unforced error rate ≤ 40% Level 3 40% ＜ Unforced error rate ≤ 45% Level 2.5 Unforced error rate ≥ 45.1% Level 2 Second Age Analysis Module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 35% Level 4 35% ＜ Unforced error rate ≤ 40% Level 3.5 40% ＜ Unforced error rate ≤ 45% Level 3 45% ＜ Unforced error rate ≤ 50% Level 2.5 Unforced error rate ≥ 50.1% Level 2 Third Age Analysis Module Unforced error rate ≤ 30% Level 6 30% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 40% Level 4 40% ＜ Unforced error rate ≤ 45% Level 3.5 45% ＜ Unforced error rate ≤ 50% Level 3 50% ＜ Unforced error rate ≤ 55% Level 2.5 Unforced error rate ≥ 55.1% Level 2 Fourth-year age group analysis module Unforced error rate ≤ 35% Level 6 35% ＜ Unforced error rate ≤ 40% 4.5 40% ＜ Unforced error rate ≤ 45% Level 4 45% ＜ Unforced error rate ≤ 50% Level 3.5 50% ＜ Unforced error rate ≤ 55% Level 3 55% ＜ Unforced error rate ≤ 60% Level 2.5 Unforced error rate ≥ 60.1% Level 2

The value of the off-court post drive grading is level 3, level 3.5, level 4, level 4.5, or level 6, and Table 13 illustrates that different off-court post drive grading values are based on analysis modules of different age levels and are obtained according to different unforced error rate ranges, and the error coverage of the unforced error rate (the first age level analysis module, the second age level analysis module, and the third age level analysis module) is ±15%, with a minimum value of 0%, and the error coverage of the unforced error rate of the fourth age level analysis module is ±20%.

Table 13. Relationship between the value of the off-court drive around the post and the unforced error rate Analysis Module Unforced Error Rate Off-court drive rating First Age Level Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 40% Level 4 40% ＜ Unforced error rate ≤ 50% Level 3.5 Unforced error rate ≥ 50.1% Level 3 Second Age Analysis Module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 45% Level 4 45% ＜ Unforced error rate ≤ 55% Level 3.5 Unforced error rate ≥ 55.1% Level 3 Third Age Analysis Module Unforced error rate ≤ 30% Level 6 30% ＜ Unforced error rate ≤ 40% 4.5 40% ＜ Unforced error rate ≤ 50% Level 4 50% ＜ Unforced error rate ≤ 60% Level 3.5 Unforced error rate ≥ 60.1% Level 3 Fourth-year age group analysis module Unforced error rate ≤ 35% Level 6 35% ＜ Unforced error rate ≤ 45% 4.5 45% ＜ Unforced error rate ≤ 55% Level 4 55% ＜ Unforced error rate ≤ 65% Level 3.5 Unforced error rate ≥ 65.1% Level 3

The lob rating value is 3.5, 4, 4.5, or 6, and Table 14 illustrates that different lob rating values are based on analysis modules of different age levels and are obtained according to different unforced error rate ranges, and the error coverage of the unforced error rate (the first age level analysis module, the second age level analysis module, and the third age level analysis module) is ±15%, with a minimum value of 0%, and the error coverage of the unforced error rate of the fourth age level analysis module is ±20%.

Table 14. Relationship between the value of the lob rating and the unforced error rate Analysis Module Unforced Error Rate Lob grading value First Age Level Analysis Module Unforced error rate ≤ 15% Level 6 15% ＜ Unforced error rate ≤ 20% 4.5 20% ＜ Unforced error rate ≤ 40% Level 4 Unforced error rate ≥ 40.1% Level 3.5 Second Age Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 45% Level 4 Unforced error rate ≥ 45.1% Level 3.5 Third Age Analysis Module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 50% Level 4 Unforced error rate ≥ 50.1% Level 3.5 Fourth-year age group analysis module Unforced error rate ≤ 30% Level 6 30% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 55% Level 4 Unforced error rate ≥ 55.1% Level 3.5

The attack phase rating value is level 2, level 2.5, level 3, level 3.5, level 4, level 4.5, or level 6. Table 15 illustrates that different attack phase rating values are based on analysis modules of different age levels and are obtained according to different unforced error rate ranges, and the error coverage range of the unforced error rate (the first age level analysis module, the second age level analysis module, and the third age level analysis module) is ±15%, with a minimum value of 0%, and the error coverage range of the unforced error rate of the fourth age level analysis module is ±20%.

Table 15. Relationship between attack phase rating and unforced error rate Analysis Module Unforced Error Rate Attack Phase Rating Value First Age Level Analysis Module Unforced error rate ≤ 15% Level 6 15% ＜ Unforced error rate ≤ 20% 4.5 20% ＜ Unforced error rate ≤ 30% Level 4 30% ＜ Unforced error rate ≤ 40% Level 3.5 40% ＜ Unforced error rate ≤ 50% Level 3 50% ＜ Unforced error rate ≤ 60% Level 2.5 Unforced error rate ≥ 60.1% Level 2 Second Age Analysis Module Unforced error rate ≤ 20% Level 6 20% ＜ Unforced error rate ≤ 25% 4.5 25% ＜ Unforced error rate ≤ 35% Level 4 35% ＜ Unforced error rate ≤ 45% Level 3.5 45% ＜ Unforced error rate ≤ 55% Level 3 55% ＜ Unforced error rate ≤ 65% Level 2.5 Unforced error rate ≥ 65.1% Level 2 Third Age Analysis Module Unforced error rate ≤ 25% Level 6 25% ＜ Unforced error rate ≤ 30% 4.5 30% ＜ Unforced error rate ≤ 40% Level 4 40% ＜ Unforced error rate ≤ 50% Level 3.5 50% ＜ Unforced error rate ≤ 60% Level 3 60% ＜ Unforced error rate ≤ 70% Level 2.5 Unforced error rate ≥ 70.1% Level 2 Fourth-year age group analysis module Unforced error rate ≤ 30% Level 6 30% ＜ Unforced error rate ≤ 35% 4.5 35% ＜ Unforced error rate ≤ 45% Level 4 45% ＜ Unforced error rate ≤ 55% Level 3.5 55% ＜ Unforced error rate ≤ 65% Level 3 65% ＜ Unforced error rate ≤ 75% Level 2.5 Unforced error rate ≥ 75.1% Level 2

The values of the forced defense success rate grading in the attack phase are 2, 2.5, 3, 3.5, 4, 4.5, or 6. Table 16 shows that the forced defense success rate grading values in different attack phases are based on the analysis modules of different age groups and are obtained according to different forced defense force ranges. The error range of the forced defense force is ±15%, and the minimum is 0%.

Table 16. Relationship between the value of forced defense success rate rating in the attack phase and forced defense capability Analysis Module Forced Defense Forced defense success rate rating value during the attack phase First Age Level Analysis Module Forced defense ≥ 60% Level 6 50% ≤ Forced Defense Capability＜ 60% 4.5 40% ≤ Forced Defense Capability＜ 50% Level 4 35% ≤ Forced Defense Capability＜ 40% Level 3.5 30% ≤ Forced Defense Capability＜ 35% Level 3 25% ≤ Forced Defense Capability＜ 30% Level 2.5 Forced defense ≤ 24.9% Level 2 Second Age Analysis Module Forced defense ≥ 55% Level 6 45% ≤ Forced Defense Capability＜ 55% 4.5 35% ≤ Forced Defense Capability＜ 45% Level 4 30% ≤ Forced Defense Capability＜ 35% Level 3.5 25% ≤ Forced Defense Capability＜ 30% Level 3 20% ≤ Forced Defense Capability＜ 25% Level 2.5 Forced defense ≤ 19.9% Level 2 Third Age Analysis Module Forced defense ≥ 50% Level 6 40% ≤ Forced Defense Capability＜ 50% 4.5 30% ≤ Forced Defense Capability＜ 40% Level 4 25% ≤ Forced Defense Capability＜ 30% Level 3.5 20% ≤ Forced Defense Capability＜ 25% Level 3 15% ≤ Forced Defense Capability＜ 20% Level 2.5 Forced defense ≤ 14.9% Level 2 Fourth-year age group analysis module Forced defense ≥ 45% Level 6 35% ≤ Forced Defense Capability＜ 45% 4.5 25% ≤ Forced Defense Capability＜ 35% Level 4 20% ≤ Forced Defense Capability＜ 25% Level 3.5 15% ≤ Forced Defense Capability＜ 20% Level 3 10% ≤ Forced Defense Capability＜ 15% Level 2.5 Forced defense power ≤ 9.9% Level 2

The average number of seconds to the net after a serve return is graded as 2, 2.5, 3, 3.5, 4, 4.5, or 6. Table 17 shows that different grading values of the average number of seconds to the net after a serve return are based on analysis modules of different age groups and are obtained according to different ranges of the average number of seconds to the net, and the average number of seconds to the net error range is ±1.5 seconds.

Table 17. Relationship between the average seconds at the net after serving and the average seconds at the net Analysis Module Average Internet access time (seconds) Average seconds to net after serve return First Age Level Analysis Module Average number of seconds online ≤ 2.0 Level 6 2.0 ＜ Average number of seconds online ≤ 2.1 4.5 2.1 ＜ Average number of seconds online ≤ 2.2 Level 4 2.2 ＜ Average number of seconds online ≤ 2.3 Level 3.5 2.3 ＜ Average number of seconds online ≤ 2.4 Level 3 2.4 ＜ Average number of seconds online ≤ 2.5 Level 2.5 Average number of seconds online ≥ 2.51 Level 2 Second Age Analysis Module Average number of seconds online ≤ 2.1 Level 6 2.1 ＜ Average number of seconds online ≤ 2.2 4.5 2.2 ＜ Average number of seconds online ≤ 2.3 Level 4 2.3 ＜ Average number of seconds online ≤ 2.4 Level 3.5 2.4 ＜ Average number of seconds online ≤ 2.5 Level 3 2.5 ＜ Average number of seconds online ≤ 2.6 Level 2.5 Average number of seconds online ≥ 2.61 Level 2 Third Age Analysis Module Average number of seconds online ≤ 2.2 Level 6 2.2 ＜ Average number of seconds online ≤ 2.3 4.5 2.3 ＜ Average number of seconds online ≤ 2.4 Level 4 2.4 ＜ Average number of seconds online ≤ 2.5 Level 3.5 2.5 ＜ Average number of seconds online ≤ 2.6 Level 3 2.6 ＜ Average number of seconds online ≤ 2.7 Level 2.5 Average number of seconds online ≥ 2.71 Level 2 Fourth-year age group analysis module Average Internet access seconds ≤ 2.5 Level 6 2.5 ＜ Average number of seconds online ≤ 2.6 4.5 2.6 ＜ Average number of seconds online ≤ 2.7 Level 4 2.7 ＜ Average number of seconds online ≤ 2.8 Level 3.5 2.8 ＜ Average number of seconds online ≤ 2.9 Level 3 2.9 ＜ Average number of seconds online ≤ 3.0 Level 2.5 Average number of seconds online ≥ 3.01 Level 2

For example, Tables 18 to 30 record various data of the player to be analyzed in the actual competition and their calculation results.

Table 18. Serving data table Tactics Serve Phase Players to be analyzed Serve to forehand Sender Serve to backhand Total of three games 15 27 0 Proportion 35.71% 64.29% 0 Total hits 42 Forced error 0 0 0 Unforced Error 0 0 0 Forced defense success 0 0 0 Unforced Error Rate 0% 0% 0% Unforced error rate (total) 0% Serve Grading 6

Table 19. Serve return data Tactics Postback phase Players to be analyzed Forehand return Backhand return Total of three games 0 3 Proportion 0% 100% Total hits 3 Forced error 0 0 Unforced Error 0 0 Forced defense success 0 0 Unforced Error Rate 0% 0% Unforced error rate (total) 0% Serve Return Grading 6

Table 20. Long Dink Data Table Tactics Dual Internet access stage Players to be analyzed Forehand long dink left field Forehand long dink midfield Forehand long dink right field Backhand long dink left field Backhand long dink midfield Backhand long dink right field Total of three games 9 9 45 twenty four 33 51 Proportion 5.26% 5.26% 26.32% 14.04% 19.30% 29.82% Total hits 171 Forced error 0 0 0 3 0 0 Unforced Error 0 0 0 0 3 0 Forced defense success 0 0 9 9 0 0 Unforced Error Rate 0% 0% 0% 0% 9.09% 0% Long DINK error rate 2.00% Long Dink Rating 6 Long Dink Defense 86% Long Dink Defense Rating 6

Table 21. Short Dink Data Table Tactics Dual Internet access stage Players to be analyzed Forehand short dink left field Forehand short dink midfield Forehand dink right field Backhand short dink left field Backhand short dink midfield Backhand short dink right field Total of three games 48 42 102 15 27 0 Proportion 20.51% 17.93% 43.59% 6.41% 11.54% 0% Total hits 234 Forced error 0 0 9 0 0 0 Unforced Error 3 0 0 0 0 0 Forced defense success 12 0 6 0 0 0 Unforced Error Rate 8.33% 0% 0% 0% 0% 0% Short DINK error rate 1.45% Short Dink Rating 6 Short DINK defense 67% Short DINK defense rating 4

Table 22. Low (flat) network attack data table Tactics Players to be analyzed Forehand low (flat) net attack Backhand low (flat) net attack Total of three games 0 3 Proportion 0% 100% Total hits 3 Forced error 0 0 Unforced Error 0 0 Forced defense success 0 0 Unforced Error Rate 0% 0% Unforced error rate (total) 0% Low (flat) net attack rating 6

Table 23. Interception data table Tactics Players to be analyzed Forehand volley Backhand volley Total of three games 15 6 Proportion 71.43% 28.57% Total hits twenty one Forced error 0 0 Unforced Error 0 0 Forced defense success 0 0 Unforced Error Rate 0% 0% Unforced error rate (total) 0% Intercept rating 6

Table 24. Data table of strong shots in the middle and back fields Tactics Players to be analyzed Forehand backcourt strong shot Backhand mid-court shot Total of three games twenty one 6 Proportion 77.78% 22.22% Total hits 27 Forced error 0 0 Unforced Error 0 0 Forced defense success 0 0 Unforced Error Rate 0% 0% Unforced error rate (total) 0% Midfield and backfield strong draw grading 6

Table 25. Smash data table Tactics Players to be analyzed Forehand Smash Backhand Smash Total of three games 33 51 Proportion 39.29% 60.71% Total hits 84 Forced error 0 0 Unforced Error 0 0 Forced defense success 0 0 Unforced Error Rate 9.09% 0% Unforced error rate (total) 3.57% Smash rating 6

Table 26. Offensive (frontcourt) lob data Tactics Attack phase Players to be analyzed Forehand high lob backcourt Backhand high lob Total of three games 48 42 Proportion 53.33% 46.67% Total hits 90 Forced error 0 0 Unforced Error 3 0 Forced defense success 12 0 Unforced Error Rate 8.33% 0% Unforced error rate (total) 3.85% Offensive (frontcourt) lob rating 6

Table 27. Defensive (midfield and backfield) lob data Tactics Players to be analyzed Forehand defensive lob Backhand defensive lob Total of three games twenty one 48 Proportion 69.57% Total hits 69 Forced error 0 0 Unforced Error 0 3 Forced defense success 0 12 Unforced Error Rate 0% 8.33% Unforced error rate (total) 5.26% Defensive (midfield and backcourt) lob rating 6

Table 28. Off-court drive data Tactics Players to be analyzed Forehand drive Backhand drive Total of three games 42 33 Proportion 56.00% 44.00% Total hits 75 Forced error 3 0 Unforced Error 0 3 Forced defense success 0 0 Unforced Error Rate 0% 9.09% Unforced error rate (total) 4.17% Off-court drive grading 6

Table 29. Drop ball data table Tactics Players to be analyzed Forehand short Backhand short Total of three games twenty four 75 Proportion 24.26% 75.76% Total hits 99 Forced error 0 12 Unforced Error 0 3 Forced defense success 0 0 Unforced Error Rate 0% 4.76% Unforced error rate (total) 3.45% Drop ball grading 6

Table 30. Average seconds to net after serving a serve Online time 1 (seconds) Online time 2 (seconds) Online time 3 (seconds) Online time 4 (seconds) 1.72 1.59 1.84 1.59 1.73 1.77 2.75 1.77 1.49 1.32 2.52 1.62 1.68 1.56 1.6 1.43 1.5 2 2.05 2.08 1.95 1.65 1.56 1.91 2.07 1.69 1.95 2.1 1.59 1.87 1.83 2.01 1.62 1.5 1.86 1.96 1.96 2.16

Finally, in step S4, based on the serve grade, the return serve grade, the long dink grade, the long dink defense success rate grade, the short dink grade, the short dink defense success rate grade, the low (flat) net power attack grade, the volley grade, the mid-backcourt power drive grade, the smash grade, the offensive (frontcourt) lob grade, the defensive (mid-backcourt) lob grade, the off-court drive grade, the lob short ball grade, the attack phase grade, the attack phase forced defense success rate grade, and the average number of seconds to the net after the return serve grade included in the hitting performance grade, the value of the comprehensive grade is between 2 and 6.

Accordingly, the present invention can quickly and accurately grasp the hitting habits, good playing styles, common weaknesses, and hitting skills that need to be strengthened of pickleball players, and calculate the current level of the player based on specific winning factor grading information, so as to achieve the objective and fair evaluation purpose. Furthermore, the present invention can also collect data from multiple competitions of the same player to make the calculated comprehensive level more accurate. In addition, the hitting information, the analysis data, the winning factor grading information, or related setting parameters can be adjusted or modified according to the actual situation to obtain a more accurate calculation result. In addition, analysts can create relevant visual charts based on the comprehensive grades or related data, calculation results, etc., to facilitate coaches and players in training and game tactical planning.

In addition, the present invention further provides a system for analyzing the hitting performance of pickle ball players and grading pickle ball players, including a processing unit 11 for executing various operations in the aforementioned method. In short, the processing unit 11 is but not limited to a central processing unit (CPU), a micro control unit (MCU), a microprocessor (microprocessor), a digital signal processor (DSP), a programmable controller, an application specific integrated circuit (ASIC), a graphics processing unit (GPU), an arithmetic logic unit (ALU), a complex programmable logic device (CPLD), a field programmable gate array (FPGA) or other similar components with computing capabilities.

As shown in FIG. 2 , the processing unit 11 can be attached to a computing device A (such as a mobile phone, a computer tablet or a computer host), and the processing unit 11 is also connected to a database 12 preset on the computing device A. The database 12 can be, but is not limited to, a phase change memory (PRAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a flash memory disk, a read-only memory (ROM), a random access memory (Random Access Memory) Memory; RAM) is used to store relevant data, information, various calculation results, the analysis module 13 or other programs. The processing unit 11 can access and execute the analysis module 13 stored in the database 12, or access data, information, various calculation results, etc.

The above is only a detailed description of the present invention through each example. Any simple modification or change made by a person familiar with the technical field to the embodiments in the specification without departing from the spirit of the present invention should be covered by the scope of the patent application of this case.

S1, S2, S3, S4: Steps A: Computing device 11: Processing unit 12: Database 13: Analysis module

FIG. 1 is a flow chart of a method for analyzing a pickleball player's hitting performance and grading a pickleball player according to a preferred embodiment of the present invention. FIG. 2 is a block diagram of a system for analyzing a pickleball player's hitting performance and grading a pickleball player according to a preferred embodiment of the present invention. FIG. 3 is a classification diagram of all hitting types.

S1, S2, S3, S4: Steps

Claims (12)

A method for analyzing the hitting performance of a pickleball player and grading the pickleball player includes the following steps: S1: obtaining hitting information of at least one player to be analyzed in a game, and quantifying it to obtain an analysis data; S2: importing the analysis data into an analysis module that matches the age group according to the age of the player to be analyzed, and obtaining multiple winning factor grading information for the player to be analyzed; S3: assessing a hitting performance grade of the player to be analyzed based on the winning factor grading information; S4: calculating a comprehensive grade of the player to be analyzed based on the hitting performance grade. The method for analyzing the hitting performance of pickleball players and grading pickleball players as described in claim 1, wherein in step S1, an image recognition technology is used to analyze the player to be analyzed from an image of the game and obtain the hitting information. The method for analyzing the hitting performance of pickleball players and grading pickleball players as described in claim 1, wherein in step S1, the player to be analyzed is numbered, and the hitting information includes a player code that matches the player to be analyzed. The method for analyzing the hitting performance of a pickleball player and grading the pickleball player as described in claim 3, wherein in step S1, the hitting skills used by the player to be analyzed in different hitting stages are recorded, and the hitting information includes the hitting stages and the hitting skills, and the hitting stages are serving, receiving, long dink, short dink, low (flat) net attack, volley, mid The average number of seconds to the net after a backcourt drive, smash, offensive (starting near the non-volley line) high lob backcourt, off-court drive around the post, defensive (starting in the middle backcourt) high lob backcourt, lob short ball, or return serve. The hitting technique is forehand, backhand, forehand topspin, forehand underspin, forehand flat shot, forehand side spin, backhand topspin, backhand underspin, backhand flat shot, or backhand side spin. As described in claim 4, the method for analyzing the hitting performance of pickleball players and grading pickleball players, wherein, in step S1, each hitting phase and the corresponding hitting skills are quantified as the analysis data, and the analysis data includes a normal hitting record based on the player code, a tracking unforced error number record, a tracking forced error number record, a tracking forced defense success number record, a tracking average number of seconds to the net after returning the serve, and a topspin, backspin, side spin and flat hit record. As described in claim 1, the method for analyzing the hitting performance of pickleball players and grading pickleball players, wherein in step S2, the analysis module is divided into a first age-level analysis module, a second age-level analysis module, a third age-level analysis module and a fourth age-level analysis module according to age, the age range of the first age-level analysis module is between 16 and 34 years old, the age range of the second age-level analysis module is between 35 and 49 years old, the age range of the third age-level analysis module is between 50 and 64 years old, and the age range of the fourth age-level analysis module is over 65 years old. As described in claim 6, the method for analyzing the hitting performance of pickleball players and grading pickleball players, wherein in step S2, the different winning factor grading information are respectively a serving winning factor, a return serving winning factor, a long dink winning factor, a long dink defense success rate winning factor, a short dink winning factor, a short dink defense success rate winning factor, a low (flat) net attack winning factor, a volley winning factor, a middle and back court strong drive winning factor, a smash winning factor, an offensive (front court) lob winning factor, a defensive (middle and back court) lob winning factor, an outside court drive winning factor, a lob short ball winning factor, an attack phase winning factor, an attack phase forced defense success rate winning factor, and an average number of seconds to the net after a return serving winning factor. The method for analyzing the hitting performance of pickleball players and grading pickleball players as described in claim 7, wherein, in step S2, the serve winning factor, the return serve winning factor, the long dink winning factor, the short dink winning factor, the low (flat) net attack winning factor, the volley winning factor, the mid-back court strong drive winning factor, the smash winning factor, the offensive (front court) lob winning factor, the defensive (mid-back court) lob winning factor, the off-court round-the-post drive winning factor, the lob short ball winning factor, and the attack phase winning factor are respectively calculated to obtain an unforced error rate using the following formula: unforced error rate = number of unforced error balls/(total number of hits - number of high-pressure forced balls). As described in claim 8, the method for analyzing the hitting performance of pickleball players and grading pickleball players, wherein, in step S2, the long dink defense success rate winning factor, the short dink defense success rate winning factor, and the attack phase forced defense success rate winning factor are respectively calculated by the following formula to obtain a forced defense force: Forced defense force = number of successful defense balls when forced / number of high-pressure forced balls. The method for analyzing the hitting performance of a pickleball player and grading the pickleball player as described in claim 9, wherein in step S3, each unforced error rate, each forced defense force, and the average number of seconds to the net after a serve are used for evaluation, so that the hitting performance grade includes a serve grade, a serve grade, a long dink grade, a long dink defense success rate grade, a short dink grade, One short dink defense success rate rating, one low (flat) net power attack rating, one volley rating, one mid-backcourt power drive rating, one smash rating, one offensive (frontcourt) lob rating, one defensive (mid-backcourt) lob rating, one outside post drive rating, one lob short ball rating, one attack phase rating, one attack phase forced defense success rate rating, and one average number of seconds to the net after a serve. The method for analyzing the hitting performance of pickleball players and grading pickleball players as described in claim 10, wherein in step S4, the comprehensive grade is calculated based on the serving grade, the return serve grade, the long dink grade, the long dink defense success rate grade, the short dink grade, the short dink defense success rate grade, the low (flat) net attack grade, the volley grade, the mid-back court strong drive grade, the smash grade, the offensive (front court) lob grade, the defensive (mid-back court) lob grade, the off-court drive grade, the lob short ball grade, the attack phase grade, the forced defense success rate grade in the attack phase, and the average number of seconds to the net after the return serve grade. A system for analyzing the hitting performance of pickleball players and grading pickleball players, including a processing unit for executing any one of the methods in claim 1 to claim 11.

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