A tennis serve technique training method and a tennis training system

Abstract

The application discloses a tennis serving skill training method and a tennis training system, relates to the technical field of tennis, and comprises the following steps: S1, acquiring court data; S2, acquiring serving data of a sports person, comprising the following steps: S21, acquiring three-dimensional coordinate values of a hitting point during serving; S22, acquiring a rotation angle of a racket during a hitting process during serving; S23, acquiring a rotation angular velocity of the racket during serving; S24, acquiring an instantaneous swing speed of the racket during hitting; S3, acquiring a landing point position and a ball speed of each serving in the step S2; S4, repeatedly performing the steps S2 and S3 to acquire multiple groups of serving data; S5, calculating and acquiring a regression equation of landing point deviation, a regression equation of landing point depth and a regression equation of the ball speed; S6, making serving action optimization suggestions by presetting the landing point position and the ball speed and utilizing the regression equations to calculate and compare. The application has the effect that serving skills can be improved through optimization measures of the landing point depth, the landing point deviation and the ball speed during serving.

Description

Technical Field

[0001] This application relates to the technical field of tennis, and in particular to a tennis serve technique training method and tennis training system. Background Technology

[0002] In tennis, you often hear terms like "landing point," which refers to the point where the ball hits the court. When serving, you need to pay attention to the depth of the landing point, the deviation of the landing point, and the ball speed. The depth of the landing point is the shortest distance from the service player's baseline. The deviation of the landing point is the shortest distance from the service player's baseline. The ball speed is the speed at which the ball travels.

[0003] Serving is a crucial skill in tennis. A good serve can score points directly, influence the quality of the receiver's return, and control the game. Mastering the serve often has a significant impact on winning the match. However, controlling the depth, angle, and speed of the serve is also essential.

[0004] In related technologies, guidance and training for serving usually rely on the coach's experience. There is room for improvement in how to systematically optimize athletes' serving techniques by training in landing depth, landing deviation, and ball speed. Summary of the Invention

[0005] In order to improve serving technique by optimizing the depth, deviation, and speed of the ball during the serve, this application provides a tennis serving technique training method and a tennis training system.

[0006] Firstly, this application provides a tennis serve technique training method, which adopts the following technical solution:

[0007] A tennis serve technique training method includes the following steps:

[0008] S1: Obtain stadium data;

[0009] S2: Obtain the serve data of the athletes, specifically including:

[0010] S21: Obtain the three-dimensional coordinates of the point of contact when serving;

[0011] S22: Obtain the rotation angle of the racket during the ball's impact when serving;

[0012] S23: Obtain the racket's rotational angular velocity at the time of the serve;

[0013] S24: Obtain the instantaneous swing speed of the racket at the moment of impact;

[0014] S3: Obtain the landing point and ball speed of each serve in step S2;

[0015] S4: Repeat steps S2 and S3 multiple times to obtain multiple sets of serve data;

[0016] S5: Calculate and obtain the regression equations for the skewness of the landing point, the depth of the landing point, and the ball speed;

[0017] S6: By setting the landing point and ball speed, and using regression equations for calculation and comparison, it makes suggestions for optimizing the serving action.

[0018] By adopting the above technical solution, the serve data of athletes can be obtained in advance. The athletes can be athletes or professionals. By obtaining the data of athletes and the data of hitting the ball, regression equations for the landing point skewness, landing point depth, and ball speed can be calculated to obtain the relationship between the serve landing point and ball speed and the measured data. When the trainee wants to obtain a specific range of landing point position and ball speed, the data of each serve can be calculated in reverse and fed back to the trainee to provide suggestions for standardized training.

[0019] Optionally, the coordinates of the hitting point in the data obtained in step S2 include the X-axis coordinate, Y-axis coordinate, and Z-axis coordinate;

[0020] The rotation angles during a shot include the X-axis rotation angle, the Y-axis rotation angle, and the Z-axis rotation angle;

[0021] The rotational angular velocity of a racket includes the X-axis angular velocity, Y-axis angular velocity, and Z-axis angular velocity;

[0022] The swing speed of a racket includes the X-axis swing speed, Y-axis swing speed, and Z-axis swing speed.

[0023] By adopting the above technical solution, the obtained serve data is calculated using coordinate scores, which facilitates data collection, processing, and calculation, thereby quickly obtaining calculation results.

[0024] Optionally, in step S4, the data can be obtained by selecting multiple athletes for testing and recording the data, with each athlete being tested at least twice.

[0025] By adopting the above technical solution, there may be situations where athletes perform poorly during the test. Therefore, testing at least two groups can improve the authenticity and stability of the data recorded by each person. Furthermore, by testing with different people, the amount of data that can be used for calculation is larger, and the calculated results can be closer to the average level.

[0026] Optionally, S6 also includes:

[0027] S61: The range of expected landing points and ball speeds;

[0028] S62: By using regression equations, obtain the range of the required hitting point coordinates, the range of the racket's rotation angle during the hitting process, the range of the racket's instantaneous rotational angular velocity during the hitting process, and the range of the racket's instantaneous swing speed during the hitting process;

[0029] S63: Based on the data from S62, provide reference suggestions and improvement plans for the trainees' movements.

[0030] By adopting the above technical solution, when obtaining the regression equations for the landing point skewness, landing point depth, and ball speed, the required serving data indicators can be calculated. This allows trainees to practice serving and obtain data, which can then be compared with the required serving data indicators to identify deficiencies in their serving and provide targeted guidance.

[0031] Optionally, step S2 may also include:

[0032] The athletes' height, arm length, and swing speed were collected, and the data were grouped according to the above data. Regression equations were calculated separately for the serve data, serve landing point, and ball speed data in different groups.

[0033] By adopting the above technical solution, the differences in gender, physical condition, and physical fitness result in significant variations in the range of data obtained. Therefore, the data can be grouped during measurement, and each group can be calculated separately. Furthermore, the corresponding equations can be matched to calculate the data based on the different physical conditions and data of the trainees.

[0034] On the other hand, this application provides a tennis serve training system, which uses any of the tennis serve technique training methods described above, and adopts the following technical solution:

[0035] A tennis serve training system, comprising:

[0036] The data acquisition module is used to collect the athlete's serve data, body data, and serve landing point and ball speed data;

[0037] The data processing module is used to process the data collected by the data acquisition module.

[0038] The data calculation module is used to calculate the data processed by the data processing module to obtain calculation results, and can compare the calculation results with the collected and processed data.

[0039] The feedback module can provide feedback on the results of the data calculation module's comparison with the data.

[0040] By adopting the above technical solution, the training method for tennis serve technique can be put into practice. The data acquisition module of the training system can be used to collect the required data. The data processing module and data calculation module can process and calculate the collected data to obtain the corresponding equations. The data can be compared with the data collected by the trainees. The feedback module can promptly compare the calculation results with the data collected by the trainees and provide feedback to the trainees, thereby providing improvement suggestions.

[0041] Optionally, the data acquisition module includes a high-speed camera acquisition module and a sensor acquisition module;

[0042] The high-speed camera acquisition module includes multiple cameras capable of high-speed movement installed on the court. The high-speed camera module is used to acquire the three-dimensional position of the hitting point of each serve by the athlete, as well as the landing point and ball speed of the corresponding serve.

[0043] The sensor acquisition module is installed on the racket and / or the athlete to collect the racket's rotation angle during the serve, as well as the racket's rotational angular velocity and swing speed at the moment of impact.

[0044] By adopting the above technical solution, the data acquisition module can collect the swing data of athletes and trainees through the sensor acquisition module, and the high-speed camera module can collect the trajectory of the tennis ball and the speed of the tennis ball.

[0045] Optionally, the data calculation module calculates the landing point skewness regression equation, landing point depth regression equation, and ball speed regression equation based on the acquired initial data.

[0046] The data calculation module also includes a data input module, which can be used to input data.

[0047] By adopting the above technical solution and setting up a data input module, data can be recorded not only through acquisition, but also by inputting data through the data input module when it is necessary to set a predetermined landing point range and a predetermined ball speed range.

[0048] Optionally, the feedback module includes an image display module and / or a voice broadcast module.

[0049] By adopting the above technical solution, the acquired data and comparison results can be displayed to the trainees through the image display module and the voice broadcast module, or one of the two. The trainees' improvement plans and suggestions can also be fed back through the above feedback module.

[0050] In summary, this application includes at least one of the following beneficial effects:

[0051] 1. By obtaining the serve and hit data of athletes in advance, regression equations for the skewness of the landing point, the depth of the landing point, and the ball speed can be calculated to obtain the relationship between the serve landing point and ball speed and the measured data. When trainees want to obtain a specific range of landing point position and ball speed, the data of each serve can be calculated in reverse to provide feedback to the trainees and provide suggestions for standardized training.

[0052] 2. Testing with at least two groups can improve the authenticity and stability of the data recorded by each person. Furthermore, testing with different people results in a larger amount of data that can be used for calculations, and the calculated results can be closer to the average level.

[0053] 3. By collecting serve data and athlete body data, the athlete's data is grouped, and the serve data, landing point data, and ball speed data collected in each group are calculated separately. The system can match the corresponding equations for calculation based on the different physical conditions and body data of the trainees.

[0054] 4. By setting up a serve training system, training methods for tennis serve techniques can be put into practice. Attached Figure Description

[0055] Figure 1 This is a flowchart of the operation of the tennis serve training system in Embodiment 1 of this application;

[0056] Figure 2 This is a schematic diagram of the steps in Embodiment 2 of this application;

[0057] Figure 3 This is a schematic diagram showing a portion of the data to be collected in this application;

[0058] Figure 4 This is a schematic diagram showing another part of the data to be collected in this application.

[0059] Explanation of reference numerals in the attached diagram: 1. Data acquisition module; 11. High-speed camera module; 12. Sensor acquisition module; 2. Data processing module; 3. Data calculation module; 31. Data input module; 4. Feedback module; 41. Image display module; 42. Voice broadcast module; 5. Landing point skewness X-coordinate; 6. Landing point depth Y-coordinate. Detailed Implementation

[0060] The following is in conjunction with the appendix Figure 1-4 This application will be described in further detail.

[0061] Example 1:

[0062] This application discloses a tennis serve training system, which is installed on and around a tennis court. (Refer to...) Figure 1 The system includes a data acquisition module 1, which includes a high-speed camera module 11 and a sensor acquisition module 12. The high-speed camera module 11 includes cameras that can move and run at high speed around the tennis court and on the top of the tennis court. This application sets up eight cameras. The high-speed camera module 11 establishes three-dimensional coordinates in the court space and can collect data on the tennis ball's movement, the athletes' movement, and the racket's movement.

[0063] The sensor acquisition module 12 includes multiple sensors installed on the racket and the court, and may also include wearable equipment with sensors for athletes when necessary. The sensor module and the high-speed camera module 11 can record various data from the racket during the serve. Both the high-speed camera module 11 and the sensor acquisition module 12 are conventional methods, and their specific implementations will not be detailed here.

[0064] Reference Figure 1 The tennis serve training system also includes a data processing module 2 and a data calculation module 3. The data processing module 2 and the data calculation module 3 are computers used to collect and process the data collected by the data acquisition module 1 and use the collected data for calculation. The data calculation module 3 also includes a data input module 31, which allows data to be supplemented and used for calculation by manual input via the keyboard.

[0065] The tennis serve training system also includes a feedback module 4, which includes an image display module 41 or a voice broadcast module 42, or both. The image display module 41 can display the calculation results and comparison data, which can be implemented by a display screen or a projector. The voice broadcast module 42 can broadcast the calculation results and comparison results, thereby feeding back the data information.

[0066] The implementation principle of a tennis serve training system according to an embodiment of this application is as follows: the data acquisition module 1 collects the athlete's serve data as well as the data of the tennis ball landing point and ball speed during the serve, and the data is processed by the data processing module 2 and calculated by the data calculation module 3 to obtain the corresponding calculation results. Then, the training data of the trainees is collected by the data acquisition module 1 and compared. The comparison results are fed back to the trainees through the feedback module 4, thereby obtaining optimization suggestions for serves.

[0067] Example 2:

[0068] This application also discloses a tennis serve technique training method, using the tennis serve training system in Example 1, with reference to... Figure 1 and Figure 2 Specifically, it includes the following steps:

[0069] S1: Acquire court data, such as the length and width of various areas inside the court, and use the tennis serve training system to establish three-dimensional coordinates on the court so as to record data at various locations on the court.

[0070] S2: Obtain serve data from athletes. These athletes can be professionals who regularly participate in sports and competitions on the field, or professionals invited or hired specifically to provide serve data; (Refer to...) Figure 3 and Figure 4 The data acquisition module 1 of the tennis serve training system collects the position of the hitting point during the serve, namely the X-axis, Y-axis, and Z-axis coordinates of the hitting point; obtains the rotation angle of the racket at the moment of hitting, including the values ​​of the X-axis rotation angle, Y-axis rotation angle, and Z-axis rotation angle; obtains the angular velocity value of the racket at the moment of hitting the ball, including the values ​​of the X-axis angular velocity, Y-axis angular velocity, and Z-axis angular velocity; and obtains the instantaneous swing velocity of the racket at the moment of hitting the ball, including the X-axis swing velocity, Y-axis swing velocity, and Z-axis swing velocity. After processing, the data can be input into the data calculation module 3 for calculation.

[0071] S3: During each serve in step S2, the data acquisition module 1 can acquire the landing point coordinates and ball speed for each serve, as referenced. Figure 3 The landing point coordinates include the X-coordinate of the landing point deviation (5) and the Y-coordinate of the landing point depth (6), so that all data of each serve can be completely collected. After being processed by the data processing module 2, the data is input into the data calculation module 3 for calculation.

[0072] S4: Repeat steps S2 and S3 multiple times, select multiple athletes for testing and record data, and test each athlete at least twice.

[0073] To reduce the influence of gender and factors such as height and arm length, when collecting data in step S2, athletes can be grouped based on the factors of height, arm length, and gender collected by data collection module 1. The serve data, serve landing point, and ball speed data of different groups are statistically analyzed separately.

[0074] S5: The collected data is processed by computer. Statistical software can be used to perform regression analysis on the data to obtain regression equations for skewness, depth, and ball speed. In this embodiment, SPSS software can be used for data calculation.

[0075] S6: After deriving the regression equations for the skewness of the landing point, the depth of the landing point, and the ball speed, the required range of the hitting point coordinates, the range of the racket's rotation angle during the hitting process, the range of the racket's instantaneous rotational angular velocity during the hitting process, and the range of the racket's instantaneous swing speed during the hitting process are derived in reverse from the predetermined range of the landing point and the ball speed at the landing point. Trainees can conduct multiple serving experiments according to the given reference requirements. The data acquisition module 1 collects various data of the trainees' serves, and the data input module 31 inputs the predetermined landing point position and landing point ball speed data of the trainees for comparison. The feedback module 4 generates images or voice broadcasts to provide feedback on the trainees' serving performance.

[0076] Finally, by comparing specific data, we can provide reference suggestions and improvement plans for the trainees' movements, thereby optimizing their serving movements and improving their serving level.

[0077] The implementation principle of a tennis serve technique training method in this application embodiment is as follows: multiple athletes are divided into different groups based on data such as height and arm length. Each group's serve data is measured separately. The data acquisition module 1 acquires the serve data of each group for each serve, specifically including the coordinates of the hitting point, the rotation angle of the racket during the hitting process, the rotational angular velocity of the racket, the instantaneous swing speed of the racket, and the landing point and ball speed of each serve.

[0078] The data calculation module 3 calculates and obtains the regression equations for each set of landing point skewness, landing point depth, and ball speed.

[0079] Based on the range of expected landing points and ball speeds of the trainees, the range of the hitting point coordinates, the range of the racket's rotation angle during the hitting process, the range of the racket's instantaneous rotational angular velocity at the time of hitting, and the range of the racket's instantaneous swing speed at the time of hitting are derived and calculated in reverse.

[0080] Based on the specific data range obtained above, the trainers are guided to perform serving actions, practice serving, and acquire various serving data, as well as the landing point and ball speed during serving practice. By comparing this data with the data range derived in reverse and providing feedback through feedback module 4, the trainers' areas for improvement can be identified, and targeted suggestions and modification plans can be provided for these areas.

[0081] Example 3:

[0082] This application discloses a set of regression equations for landing point skewness, landing point depth, and ball velocity obtained through the system of Example 1 and the method of Example 2, as follows:

[0083] The first set of measurement data obtained is as follows (units are SI units, not shown for ease of calculation):

[0084]

[0085]

[0086] The second set of data obtained is as follows (units are SI units, not shown for ease of calculation):

[0087]

[0088]

[0089]

[0090] The regression equations can be obtained from the two sets of data:

[0091] Landing point deviation X = 1.979 * swing speed Y – 0.093 * Z-axis internal spin velocity + 0.157 * X-axis internal spin velocity + 184.257;

[0092] Landing depth Y = -3.892 * swing velocity Y + 2310.618;

[0093] Ball speed V = -0.779 * swing speed Z – Y-axis internal spin angle * 1.015 – X-axis internal spin angle * 1.18 + hitting position Z * 52.642 + 28.939.

[0094] Using the regression equations described above, after setting the desired range of landing point deviation, landing point depth, and ball speed, various data can be obtained in reverse and fed back to the trainees, or compared with the data collected from the trainees' serves and fed back to the trainees, so that the trainees can optimize their serving actions and various physical abilities.

[0095] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A training method for tennis serve technique, characterized in that, Includes the following steps: S1: Obtain stadium data; S2: Obtain the serve data of the athletes, specifically including: S21: Obtain the three-dimensional coordinates of the point of contact when serving; S22: Obtain the rotation angle of the racket during the ball's impact when serving; S23: Obtain the racket's rotational angular velocity at the time of the serve; S24: Obtain the instantaneous swing speed of the racket at the moment of impact; The coordinates of the hitting point include the X-axis coordinate, Y-axis coordinate, and Z-axis coordinate; The rotation angles during a shot include the X-axis rotation angle, the Y-axis rotation angle, and the Z-axis rotation angle; The rotational angular velocity of a racket includes the X-axis angular velocity, Y-axis angular velocity, and Z-axis angular velocity; The swing speed of a racket includes the X-axis swing speed, Y-axis swing speed, and Z-axis swing speed; S3: Obtain the landing point and ball speed of each serve in step S2. The landing point includes the X coordinate of the landing point skewness (5) and the Y coordinate of the landing point depth (6). S4: Repeat steps S2 and S3 multiple times to obtain multiple sets of serve data; S5: Calculate and obtain the regression equations for the skewness of the landing point, the depth of the landing point, and the ball speed; S6: By setting the landing point and ball speed, and using regression equations for calculation and comparison, it makes suggestions for optimizing the serving action.

2. The tennis serve technique training method according to claim 1, characterized in that: In step S4, data is acquired by selecting multiple athletes for testing and recording the data, with each athlete being tested at least twice.

3. The tennis serve technique training method according to claim 1, characterized in that: S6 also includes: S61: The range of expected landing points and ball speeds; S62: By using regression equations, obtain the range of the required hitting point coordinates, the range of the racket's rotation angle during the hitting process, the range of the racket's instantaneous rotational angular velocity during the hitting process, and the range of the racket's instantaneous swing speed during the hitting process; S63: Based on the data from S62, provide reference suggestions and improvement plans for the trainees' movements.

4. The tennis serve technique training method according to claim 1, characterized in that: Step S2 also includes: The athletes' height, arm length, and swing speed were collected, and the data were grouped according to the above data. Regression equations were calculated separately for the serve data, serve landing point, and ball speed data in different groups.

5. A tennis serve training system, using the tennis serve technique training method as described in any one of claims 1-4, characterized in that, include: The data acquisition module (1) is used to collect the athlete's serve data, body data, and serve landing point and ball speed data; Data processing module (2), which is used to process the data collected by data acquisition module (1); The data calculation module (3) is used to calculate the data processed by the data processing module (2) to obtain the calculation results, and can compare the calculation results with the collected and processed data. The feedback module (4) can provide feedback on the results of the data calculation module (3) comparing the data.

6. A tennis serve training system according to claim 5, characterized in that: The data acquisition module (1) includes a high-speed camera acquisition module and a sensor acquisition module (12); The high-speed camera acquisition module includes multiple cameras capable of high-speed movement set on the court. The high-speed camera module (11) is used to acquire the three-dimensional position of the hitting point of each serve by the athlete, as well as the landing point and ball speed of the corresponding serve. The sensor acquisition module (12) is installed on the racket and / or the athlete to collect the racket's rotation angle during the serve, as well as the racket's rotational angular velocity and swing speed at the moment of impact.

7. A tennis serve training system according to claim 5, characterized in that: The data calculation module (3) calculates the landing point skewness regression equation, landing point depth regression equation and ball speed regression equation based on the acquired initial data. The data calculation module (3) also includes a data input module (31), which can be used to input data.

8. A tennis serve training system according to claim 5, characterized in that: The feedback module (4) includes an image display module (41) and / or a voice broadcast module (42).

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