Competition result data analysis method and system

Abstract

The invention provides a competition result data analysis method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining competition result data of road bicycle participants; based on the competition map and the position positioning information, obtaining a competition advancing route of the participants, and correcting the competition advancing route according to the video image information; comparing the corrected competition advancing route with a theoretical optimal route of the competition map; extracting physiological parameter information and speed information of corresponding time points for road sections with differences; and obtaining competition action optimization suggestions for the participants based on the extracted physiological parameter information and speed information. According to the method, the competition result data of the participants can be comprehensively analyzed, the playing conditions of the participants are analyzed from different angles, then problems can be found in a more targeted mode, and more accurate and effective suggestions are provided.

Description

Technical Field

[0001] The present invention relates to the technical field of automatic navigation, and more particularly, to a method and system for analyzing competition performance data. Background Art

[0002] The analysis of athletes' competition performance is of great significance. It not only helps to evaluate athletes' performance but also provides valuable guidance for future training and competition strategies. With the progress of technology, the evolution of these technologies has greatly improved the accuracy and depth of sports performance evaluation. Whether it is the dynamic monitoring of athletes' physiological parameters or the sensing technology based on sensors and cameras, it can improve the comprehensiveness and accuracy of monitoring the entire competition process.

[0003] Therefore, how to provide an analysis method that can deeply analyze the competition process of athletes based on the obtained competition performance data and provide more accurate and effective suggestions for athletes is an urgent problem to be solved at present. Summary of the Invention

[0004] To address the above problems, the present invention provides a method and system for analyzing competition performance data.

[0005] In a first aspect of an embodiment of the present invention, a method for analyzing competition performance data is provided. The method includes: Obtain competition performance data of road cycling participants, where the competition performance data includes physiological parameter information, position location information, speed information of the participants at various time points during the competition, and video image information collected by a camera; Based on the competition map and the position location information, obtain the competition route of the participants, and correct the competition route according to the video image information; Compare the corrected competition route with the theoretical optimal route of the competition map; For the different sections, extract the physiological parameter information and speed information at the corresponding time points; Based on the extracted physiological parameter information and speed information, obtain competition action optimization suggestions for the participants.

[0006] Optionally, the step of correcting the competition route according to the video image information specifically includes: Obtain the video image position of the participants on the track according to the video image information; Compare the video image position with the position location information according to the time points; If there is an inconsistent situation, correct the competition route according to the video image position.

[0007] Optionally, the step of comparing the corrected competition route with the theoretically optimal route of the competition map specifically includes: Obtain the theoretically optimal route based on the competition map, where the theoretically optimal route includes multiple optimal path positions sorted in chronological order; Compare the optimal path positions with the position location information constituting the competition route; Obtain a set of position location information with differences, which is the differential section.

[0008] Optionally, the speed information includes instantaneous speed and speed direction. The step of obtaining competition action optimization suggestions for the participants based on the extracted physiological parameter information and speed information specifically includes: Based on the specific differences between the optimal path positions and the position location information, obtain the optimization actions at each position in the differential section. The optimization actions include speed adjustment actions and direction adjustment actions; Obtain the quantified physical fitness information of the participants; Judge whether the participants can complete the optimization actions according to the physical fitness information; If yes, use the optimization actions as competition action optimization suggestions; If not, adjust the optimization actions to actions that can be completed based on the limitations of the physical fitness information, and use the adjusted optimization actions as competition action optimization suggestions.

[0009] Optionally, the physiological parameter information includes at least one of heart rate and human output power. The step of judging whether the participants can complete the optimization actions according to the physical fitness information specifically includes: Calculate the remaining disposable physical strength of the participants at the current position according to the physical fitness information and the physiological parameter information; Judge whether the remaining disposable physical strength supports the completion of the optimization actions.

[0010] Optionally, the step of obtaining competition action optimization suggestions for the participants based on the extracted physiological parameter information and speed information specifically further includes: After obtaining the quantified physical fitness information of the participants, calculate the personal competition optimal action plan based on the physical fitness information. The personal competition optimal action plan includes multiple personal competition optimal actions sorted in chronological order; Calculate the theoretical physiological parameters of the participants when performing each personal competition optimal action in turn; According to the video image information and the speed information, obtain the actual competition actions at the time points corresponding to each personal competition optimal action; Action optimization suggestions are obtained based on the specific differences between the optimal actions in individual competitions and the actual competition actions; Physiological parameter optimization suggestions are obtained based on the specific differences between the theoretical physiological parameters and the extracted physiological parameter information.

[0011] Optionally, the step of calculating the optimal action plan for individual competitions based on the physical fitness information specifically includes: Starting from the competition starting point, sequentially calculate the physical strength allocation amount for reaching each optimal path position based on the physical fitness information; Calculate the optimal actions for individual competitions that need to be executed for reaching each optimal path position according to the physical strength allocation amount; Collect all the optimal actions for individual competitions to obtain the optimal action plan for individual competitions.

[0012] Optionally, the step of obtaining the quantified physical fitness information of the participants specifically includes: Obtain the training data of the participants, where the training data includes the maximum heart rate, the duration of the maximum heart rate, the maximum human output power, and the duration of the maximum human output power; Quantify the training data according to the preset quantification rules to obtain the quantified physical fitness information of the participants.

[0013] Optionally, the step of adjusting the optimized action to an action that can be completed based on the limitations of the physical fitness information specifically includes: Obtain the action range that the participants can support according to the physical fitness information; Adjust the optimized action to the action that is closest to the optimized action within the action range.

[0014] In the second aspect of the embodiments of the present invention, a competition result data analysis system is provided, including: A data acquisition unit, configured to acquire the competition result data of the road bicycle participants, where the competition result data includes the physiological parameter information, position location information, speed information, and video image information collected by a camera at each time point during the competition; A route determination unit, configured to obtain the competition travel route of the participants based on the competition map and the position location information, and correct the competition travel route according to the video image information; A route comparison unit, configured to compare the corrected competition travel route with the theoretical optimal route of the competition map; An information extraction unit, configured to extract the physiological parameter information and speed information at the corresponding time points for the sections with differences; An analysis and optimization unit for obtaining competition action optimization suggestions for the participants based on the extracted physiological parameter information and speed information.

[0015] In summary, the present invention provides a competition result data analysis method and system, which can comprehensively analyze the competition result data of the participants, analyze the performance of the participants from different angles, and then can more pertinently discover problems and provide more accurate and effective suggestions. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the embodiments. It should be understood that the following drawings only show some embodiments of the present invention, and therefore should not be regarded as limiting the scope. For those of ordinary skill in the art, without creative efforts, other related drawings can also be obtained based on these drawings.

[0017] Figure 1 It is a method flowchart of the competition result data analysis method of the embodiment of the present invention; Figure 2 It is a functional module block diagram of the competition result data analysis system of the embodiment of the present invention.

[0018] Reference Signs: Data acquisition unit 110; Route determination unit 120; Area detection unit 130; Information extraction unit 140; Analysis and optimization unit 150. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] The analysis of athletes' competition results is of great significance. It not only helps to evaluate the performance of athletes, but also provides valuable guidance for future training and competition strategies. With the progress of technology, the evolution of these technologies has greatly improved the accuracy and depth of sports performance evaluation. Whether it is the dynamic monitoring of athletes' physiological parameters or the sensing technology based on sensors and cameras, it can improve the comprehensiveness and accuracy of the monitoring of the entire competition process.

[0020] Therefore, how to provide an analysis method that can deeply analyze the competition process of athletes based on the obtained competition result data and provide more accurate and effective suggestions for athletes is an urgent problem to be solved at present.

[0021] In view of this, the designer of the present invention designed a competition result data analysis method and system.

[0022] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Components of the embodiments of the present invention usually described and illustrated in the drawings here can be arranged and designed in a variety of different configurations.

[0023] Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0024] It should be noted that like reference numerals and letters denote like items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0025] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by terms such as "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product of the present invention is usually placed during use. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. In addition, terms such as "first" and "second" are only used for descriptive distinction and should not be construed as indicating or implying relative importance.

[0026] In the description of the present invention, it should also be noted that unless otherwise clearly specified and limited, the terms "set", "installed", "connected", and "connected" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the communication inside two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0027] It should be noted that, without conflict, the embodiments in the present invention and the features in the embodiments can be combined with each other.

[0028] A method for analyzing competition performance data provided in this embodiment will be specifically described below.

[0029] Please refer to Figure 1 , a method for analyzing competition performance data provided in this embodiment, the method includes: Step S101: Obtain the race result data of the road bicycle racers. The race result data includes the physiological parameter information, position location information, speed information of the racers at various time points during the race, and video image information collected by cameras.

[0030] During the road bicycle race, the position location information of the racers' vehicles can be obtained in real time through the positioning modules (such as GPS modules, Beidou modules, etc.) installed on the racers' vehicles, and the speed information can be obtained through the installed sensors (such as accelerometers, gyroscopes). The physiological parameter information such as the heart rate and breathing rate of the racers can be collected in real time through the devices carried by the racers. At the same time, the cameras installed above or on both sides of the track can collect the video image information of all the racers during the race throughout the process.

[0031] Through these above-mentioned data, the whole process and all-round recording of the racers' race results are realized. By fully and deeply analyzing these data, it not only helps to evaluate the performance of the racers, but also can provide valuable guiding suggestions for future training and race strategies.

[0032] Step S102: Obtain the race route of the racers based on the race map and the position location information, and correct the race route according to the video image information.

[0033] The race map includes information such as the detailed layout of the track, curves, slopes, altitude changes, etc. By combining the position location information, the position coordinates of the racers in the race map can be obtained.

[0034] In a road bicycle race, there is a fixed track arrangement, but the track has a certain width. How the specific race route of the racers on the track is can be obtained through the continuously acquired position location information. Adopting different race routes has an impact on the race results. For example, in a curve, riding closer to the inner side can shorten the driving distance, but at the same time increases the risk of falling, especially on a wet or uneven road surface. Choosing the appropriate route is particularly important. Therefore, it is very important for the racers to choose what kind of race route in different sections.

[0035] It should be noted that since the racers are always in a state of high-speed movement during the race, the positioning module may have a positioning deviation, resulting in inaccurate position location information obtained. The video image information recorded by the camera can capture the specific position of the racers on the track, so the race route obtained from the position location information can be corrected through the video image information.

[0036] Specifically, as a preferred mode of the embodiment of the present invention, step S102 specifically includes:

[0037] Obtain the video image position of the participants in the track according to the video image information; Compare the video image position with the position location information according to the time point; If there is an inconsistency, correct the race route according to the video image position.

[0038] When obtaining the position of the participants in the track according to the video image information, first extract the key frames from the video, and then use computer vision algorithms (such as YOLO, SSD, etc.) to detect the participants and other markers (such as road signs, dividing lines, etc.) in the video to confirm the exact position of the participants, that is, the video image position. Then align the time stamps of the key frames with the time stamps of the data collected by the positioning module to ensure that the two are compared within the same time frame.

[0039] When a significant deviation is found between the video image position and the position location information, the race route needs to be corrected. The specific correction method can be one of the following methods: 1. Interpolation method: Insert more points between two known position location information to make the race route smoother.

[0040] 2. Reprojection method: Recalculate the race route of the participants according to the actual position in the video and map it back to the map.

[0041] 3. Kalman filter: Use the Kalman filter to fuse multi-source data (such as GPS data and video data) to improve the accuracy of the race route calculation.

[0042] Through the above steps, the race map, position location information and video image information can be effectively utilized to obtain a more accurate race route.

[0043] Step S103, compare the corrected race route with the theoretical optimal route of the race map.

[0044] There are two common methods for obtaining the theoretically optimal route based on the competition map. One method is to obtain the optimal historical data on the competition map based on historical competition result data, then extract the travel routes in this historical data, and on this basis, appropriately correct the sections with obvious problems to obtain the theoretically optimal route. Another method is to calculate based on an optimized mathematical model, with the goal of minimizing the time to complete the entire competition while minimizing energy consumption as much as possible. Define the objective function, use the relevant information of the competition map as conditions, construct an optimization model, and then select a suitable algorithm (such as the shortest path algorithm, genetic algorithm, etc.) for calculation. After simulation, the optimal route can be obtained, and at the same time, the speed, power output, estimated time, etc. of each section can be obtained.

[0045] By comparing the actual route with the theoretically optimal route, the competition performance of the participants can be quantitatively evaluated, and it can be clarified which sections perform excellently and which sections need improvement. By analyzing the sections with large deviations, the technical deficiencies of the participants under specific conditions can be found, such as corner handling, climbing skills, etc. If it is found that the actual performance of certain sections has a large deviation from the theoretically optimal route, the competition strategy can be adjusted to optimize the performance of these sections. Further, according to the comparison results, a personalized training plan can be formulated to focus on improving the capabilities of the participants in weak links, such as strength training, endurance training, etc.

[0046] Specifically, as a preferred embodiment of the present invention, step S103 specifically includes: Obtain the theoretically optimal route based on the competition map, and the theoretically optimal route includes multiple optimal path positions sorted in chronological order; Compare the optimal path positions with the position location information constituting the competition travel route; Obtain the set of position location information with differences, which is the difference section.

[0047] When making the comparison, the first thing to do is time synchronization, that is, the time stamps of the position location information of the competition travel route are consistent with the time frame of the optimal path positions, so as to make the comparison at the same time point. Then there is the alignment in spatial coordinates. Use GIS tools to spatially match the position location information with the optimal path positions of the theoretically optimal route on the map to ensure that the two are compared under the same geographic coordinate system.

[0048] In addition, the competition travel route and the theoretically optimal route can be visually overlaid on the map, which can more intuitively view the differences between the two.

[0049] The corresponding comparison threshold can be set as needed. Only when the difference between the two exceeds this threshold is it determined that there is a difference. By setting different thresholds, the different sections can be screened, and the key sections with larger differences (such as uphill sections, sharp turns, and sprint sections) can be determined for detailed analysis.

[0050] Based on the above solution, as a preferred implementation manner of the embodiment of the present invention, on the basis of route comparison, performance index comparison can be further performed, including time comparison, speed comparison, and energy consumption comparison, to screen out the different sections with different performance indexes. Specifically, the method of time comparison is to calculate the difference between the actual time used for each section and the theoretically optimal time used, and find out the sections with longer time consumption. The method of speed comparison is to compare the actual speed with the theoretically optimal speed to evaluate the speed control of the participants in different sections. The method of energy consumption comparison is to estimate the difference between the actual energy consumption and the theoretically optimal energy consumption according to the power output model to judge whether the participants allocate their physical strength reasonably.

[0051] Step S104: For the different sections, extract the physiological parameter information and speed information at the corresponding time points.

[0052] Through the above steps, the different sections where the participants perform poorly are confirmed. On this basis, according to the specific performance of the participants in the different sections, it is further determined how to make adjustments. Therefore, it is necessary to extract the physiological parameter information and speed information at the corresponding time points when the participants are driving on the different sections.

[0053] Step S105: Based on the extracted physiological parameter information and speed information, obtain the optimization suggestions for the participants' competition actions.

[0054] The way to obtain the optimization suggestions for the competition actions can be selected based on the optimization direction of the participants, mainly divided into two ways. One way is to provide optimization suggestions based on the best results of the current competition map. At this time, the physical fitness information of the participants themselves is not considered. The obtained optimization suggestions include both the optimization of the competition actions and the suggestions for improving the physical fitness.

[0055] Another way is to provide the optimization suggestions for the competition actions that the participants can currently support and complete on the basis of considering the physical fitness information of the participants themselves. The obtained optimization suggestions mainly include the optimization of the competition actions at each time node, the reasonable adjustment of the physiological parameters, and the reasonable allocation of physical strength, so that the participants can obtain the best competition results based on their current physical fitness.

[0056] Specifically, as a preferred manner of the embodiment of the present invention, step S105 specifically includes:

[0057] Based on the specific differences between the optimal path position and the position positioning information, obtain the optimization actions at each position on the differential section. The optimization actions include speed adjustment actions and direction adjustment actions; Obtain the quantified physical fitness information of the participants; Judge whether the participants can complete the optimization actions according to the physical fitness information; If yes, use the optimization actions as suggestions for optimizing the competition actions; If not, adjust the optimization actions to actions that can be completed based on the limitations of the physical fitness information, and use the adjusted optimization actions as suggestions for optimizing the competition actions.

[0058] During specific implementation, first, in the first way, directly compare the differences between the optimal path position and the position positioning information, and then obtain the corresponding optimization actions. Here, the optimization actions include both adjustments to speed and adjustments to direction. Through speed adjustment, the competition terrain can be more reasonably utilized and physical strength can be distributed. Through direction adjustment, the traveling route can be made more matching with the optimal path. On this basis, as a preferred implementation manner, the optimization actions can also include adjustments to heart rate, breathing rate, and power output.

[0059] After obtaining the optimization actions, further consider the physical fitness of the participants to judge whether the participants have the ability to complete the optimization actions. For example, at this time, the optimization action requires the participants to increase their speed. However, based on the physical fitness of the participants, it may no longer be possible to increase the speed. At this time, it is necessary to adjust the optimization actions to actions that the participants can complete.

[0060] When judging whether the participants can complete the optimization actions according to the physical fitness information, it is necessary to be based on the quantified physical fitness information of the participants and the specific position of the current differential section on the competition map.

[0061] Specifically, as a preferred manner of the embodiment of the present invention, the step of obtaining the quantified physical fitness information of the participants specifically includes: Obtain the training data of the participants, where the training data includes maximum heart rate, maximum heart rate duration, maximum human output power, and maximum human output power duration; Quantify the training data according to the preset quantification rules to obtain the quantified physical fitness information of the participants.

[0062] The acquisition of physical fitness information mainly relies on the training data recorded during past training. As other implementation methods, the historical competition performance data of the participants can also be used. Among them, the maximum heart rate, the duration of the maximum heart rate, the maximum human output power, and the duration of the maximum human output power are the most convenient and accurate parameters in actual competitions. They can not only be directly obtained from common smart wearable devices on the market, but also have good applicability for most types of sports. As other implementation methods, the physical fitness information can also include parameters such as heart rate variability, blood lactate concentration, oxygen saturation, muscle activation pattern, breathing frequency and depth, and core temperature.

[0063] After obtaining the training data or historical performance data, these data are quantitatively analyzed according to appropriate quantization rules to facilitate subsequent calculations. The selection of the quantization rules is related to the calculation steps of the subsequent required parameters. Commonly used quantization rules include: Heart Rate Reserve Percentage (HRR): The calculation formula is (Current Heart Rate - Resting Heart Rate) / (Maximum Heart Rate - Resting Heart Rate) × 100. It is used to evaluate the exercise intensity.

[0064] Duration of Maximum Heart Rate (D-MHR): Records the time that a player can maintain when approaching or reaching the maximum heart rate, usually in seconds or minutes.

[0065] Average Heart Rate (AHR): The average heart rate during the entire training or competition, which reflects the overall exercise intensity.

[0066] Normalized Power (NP): Used to measure the average power output during cycling, considering the impact of power fluctuations.

[0067] Functional Threshold Power (FTP): Refers to the maximum average power that a player can continuously output within one hour and is an important indicator for measuring endurance.

[0068] Duration of Maximum Power Output (D-MPO): Records the time that a player can maintain when approaching or reaching the maximum power output, usually in seconds or minutes.

[0069] Based on the quantitatively analyzed physical fitness information, at any time node or section during the progress of the competition, based on the partial competition performance completed by the participants, it is possible to estimate the actions that can currently be supported to complete.

[0070] Specifically, as a preferred embodiment of the present invention, the physiological parameter information includes at least one of heart rate and human output power. The step of determining whether the participant can complete the optimization action according to the physical fitness information specifically includes: Calculating the remaining disposable physical strength of the participant at the current position according to the physical fitness information and the physiological parameter information; Determining whether the remaining disposable physical strength supports the completion of the optimization action.

[0071] According to the current position of the participant, it can be determined how much of the race part they have completed. Then, based on their specific performance in the completed part (including the traveling speed, traveling route, and power output in each section), the remaining disposable physical strength or remaining energy reserve of the participant can be calculated. When the requirements of the optimization action are higher than what the current remaining disposable physical strength can support, it means that the participant cannot complete the optimization action at the current position. At this time, the optimization action needs to be adjusted.

[0072] Specific adjustment methods include: Obtaining the action range that the participant can support according to the physical fitness information; Adjusting the optimization action to the action that is closest to the optimization action within the action range.

[0073] When adjusting the action, it is necessary to classify and process the specific content of the optimization action. One category is directly related to the limitations of physical fitness, such as increasing speed, increasing output power, etc., which cannot be completed under the limitations of physical fitness and need to be adjusted to the supportable range. Another category is not directly related to the limitations of physical fitness, such as adjusting the direction, maintaining or reducing speed, reducing output power, etc., and no adjustment is required.

[0074] After adjustment, the optimization action that the participant can complete is obtained. Combining all the adjusted optimization actions and the optimization actions that do not require adjustment, the race action optimization suggestions for the entire race are obtained.

[0075] As a preferred embodiment of the present invention, for the second method of obtaining race action optimization suggestions described above, there is another implementation method. Specifically, step S105 further specifically includes: After obtaining the quantified physical fitness information of the participant, calculating the personal race optimal action plan based on the physical fitness information, where the personal race optimal action plan includes multiple personal race optimal actions sorted in chronological order; Calculating the theoretical physiological parameters of the participant for each personal race optimal action in turn; Obtain the actual competition actions corresponding to the optimal action time points of each individual competition according to the video image information and the speed information; Obtain action optimization suggestions based on the specific differences between the optimal actions of individual competitions and the actual competition actions; Obtain physiological parameter optimization suggestions based on the specific differences between the theoretical physiological parameters and the extracted physiological parameter information.

[0076] When obtaining the optimal actions, first refer to the quantified physical fitness information of the participants, and then obtain the optimal action plan for individual competitions based on the physical fitness information according to the competition map. Since the optimal action plan for individual competitions is generated based on the physical fitness information of the participants, each optimal action in it can be completed by the physical fitness of the participants. Therefore, there is no need to consider whether the participants can complete the action optimization suggestions, and directly obtain the action optimization suggestions based on the specific differences between the optimal actions of individual competitions and the actual competition actions. At the same time, to complete all the optimal actions of individual competitions in the optimal action plan for individual competitions, the participants need to adjust the state of physiological parameters accordingly to be as consistent as possible with the theoretical physiological parameters when implementing each optimal action of individual competitions. Therefore, it is necessary to compare the theoretical physiological parameters with the extracted physiological parameter information, find the differences between the two, and then put forward optimization suggestions for the adjustment of physiological parameters.

[0077] The calculation of the optimal action plan for individual competitions can adopt the same idea as obtaining the theoretical optimal route, that is, establishing a mathematical model for calculation. The difference is that in addition to taking minimizing the time to complete the entire competition as the goal, the physical fitness information of the participants also needs to be used as a constraint condition for simulation. Specifically, the steps of calculating the optimal action plan for individual competitions based on the physical fitness information include: Starting from the competition starting point, calculate the physical strength distribution amount to reach each optimal path position based on the physical fitness information in turn; Calculate the optimal actions for individual competitions that need to be executed to reach each optimal path position according to the physical strength distribution amount; Collect all the optimal actions for individual competitions to obtain the optimal action plan for individual competitions.

[0078] In the same competition map, the theoretical optimal route and the optimal path positions that make up the theoretical optimal route are the same. However, considering that the physical fitness information of different participants is different, the physical strength distribution amounts for different participants to reach each optimal path position are also different. Correspondingly, the optimal actions for individual competitions that need to be executed to reach each optimal path position will also be different, which need to be obtained through detailed simulation and calculation based on the specific quantified values of the physical fitness information.

[0079] After obtaining the optimal action plan for the individual competition, the performance of the contestants in this competition is compared with it to obtain action optimization suggestions and physiological parameter optimization suggestions on different sections of the road.

[0080] The following is a specific case to illustrate: There is one participant, and his physical fitness data is as follows: Maximum heart rate (MHR): 190 bpm Resting heart rate (RHR): 50 bpm Functional Threshold Power (FTP): 350 W Maximum human power output (MPO): 1000 W Duration of maximum heart rate (D-MHR): 60 seconds Maximum human power output duration (D-MPO): 10 seconds The race route is as follows: Total distance: 100 km Flat road: 60 km Climbing: 20 km Downhill: 15 km Sharp turn: 5 km The real-time competition data of the participants are as follows: Current heart rate (CHR): 170 bpm Current Power Output (CPO): 280 W Current speed (CS): 35 km / h Current position (CP): 30 km completed Real-time analysis and action suggestions are as follows: (1) Flat road sections: The current speed is 35 km / h, slightly lower than the theoretical optimal speed (38 km / h).

[0081] The current power output ratio is 280 / 350=0.8280 / 350=0.8, and there is still room for improvement.

[0082] It is recommended to increase the cadence appropriately and increase the power output to around 300 W to increase the speed to close to 38 km / h.

[0083] Take advantage of the following effect in a large group to reduce wind resistance and save energy.

[0084] (2) Climbing section: We are about to enter a climbing section, which is expected to be 10 kilometers long.

[0085] The current heart rate is 170 bpm, which is close to 89% of the maximum heart rate ((170−50)(190−50)×100(190−50)(170−50)×100).

[0086] It is recommended to adjust the gear ratio, use a lower gear to maintain a stable cadence, and avoid premature fatigue.

[0087] Appropriately increase the power output to about 320 W, but avoid excessive physical exertion.

[0088] (3) Downhill section: If there is a downhill section ahead, it is recommended to relax the brakes, make full use of the downhill inertia, and increase the speed to about 45 km / h.

[0089] Maintain a low center of gravity and a stable posture, reduce air resistance, and improve downhill efficiency.

[0090] (4) Sharp turn section: Try to ride as close to the inner side as possible to shorten the driving distance, but ensure sufficient grip to avoid falling.

[0091] Adjust the speed in advance according to the road conditions and the radius of the curve to ensure a smooth passage through the curve.

[0092] Finally, organize the above analysis results and action suggestions into a detailed report for coaches and athletes to reference.

[0093] In summary, the race result data analysis method provided by the implementation of the present invention can comprehensively analyze the race result data of the participants, analyze the performance of the participants from different angles, and thus can more specifically identify problems and provide more accurate and effective suggestions.

[0094] As Figure 2 shown, the race result data analysis system provided by the implementation of the present invention, the system includes: A data acquisition unit 110 for acquiring the race result data of the road bicycle participants, where the race result data includes the physiological parameter information, position location information, speed information, and video image information collected by the camera of the participants at each time point during the race; A route determination unit 120 for obtaining the race route of the participants based on the race map and the position location information, and correcting the race route according to the video image information; A route comparison unit 130 for comparing the corrected race route with the theoretical optimal route of the race map; An information extraction unit 140 for extracting the physiological parameter information and speed information at the corresponding time points for the sections with differences; An analysis and optimization unit 150 is configured to obtain optimization suggestions for the competition actions of the participants based on the extracted physiological parameter information and speed information.

[0095] The competition result data analysis system provided by the embodiments of the present invention is used to implement the above-mentioned competition result data analysis method. Therefore, the specific implementation manners are the same as those of the above method and will not be elaborated herein.

[0096] In summary, the present invention provides a competition result data analysis method and system, which can comprehensively analyze the competition result data of the participants, analyze the performance of the participants from different perspectives, and thus can more specifically identify problems and provide more accurate and effective suggestions.

[0097] In several embodiments disclosed in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions, and operations of devices, methods, and computer program products according to multiple embodiments of the present application. In this regard, each block in the flowchart or block diagram may represent a module, a program segment, or a part of code, and the module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as the combination of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0098] In addition, in each embodiment of the present application, the various functional modules may be integrated together to form an independent part, or each module may exist alone, or two or more modules may be integrated to form an independent part.

[0099] If the above-described functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application. The foregoing storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROMs, Read-Only Memories), random access memories (RAMs, Random Access Memories), magnetic disks, or optical discs.

Claims

1. A method for analyzing competition performance data, characterized in that: The method comprises: Obtaining competition performance data of road cycling participants, wherein the competition performance data includes physiological parameter information, position information, speed information, and video image information collected by a camera at each time point of the competition; Obtaining a competition route of the contestant based on the competition map and the position positioning information, and correcting the competition route according to the video image information; Compare the corrected race route with the theoretical optimal route of the race map; For road sections with differences, extract the physiological parameter information and speed information at the corresponding time points; Based on the extracted physiological parameter information and speed information, optimization suggestions for the contestants' competition movements are obtained.

2. The competition performance data analysis method according to claim 1, characterized in that: The step of correcting the race route according to the video image information specifically includes: Acquire the video image position of the contestant on the track according to the video image information; Comparing the video image position with the position location information according to the time point; If there is any inconsistency, the race route is corrected according to the video image position.

3. The competition performance data analysis method according to claim 2, characterized in that: The step of comparing the corrected race route with the theoretical optimal route of the race map specifically includes: Obtaining a theoretical optimal route based on the game map, wherein the theoretical optimal route includes a plurality of optimal path positions sorted in chronological order; comparing the optimal path position with the position location information constituting the race route; The set of position positioning information with differences is obtained, which is the difference road section.

4. The competition performance data analysis method according to claim 3, characterized in that: The speed information includes instantaneous speed and speed direction. The step of obtaining competition action optimization suggestions for the contestants based on the extracted physiological parameter information and speed information specifically includes: Based on the specific differences between the optimal path position and the position positioning information, an optimization action at each position of the difference section is obtained, wherein the optimization action includes a speed adjustment action and a direction adjustment action; Obtain quantified physical fitness information of participants; Judging whether the contestant can complete the optimized action according to the physical fitness information; If possible, the optimized action will be used as a match action optimization suggestion; If not, the optimized action is adjusted to an action that can be completed based on the limitation of the physical fitness information, and the adjusted optimized action is used as a game action optimization suggestion.

5. The competition performance data analysis method according to claim 4, characterized in that: The physiological parameter information includes at least one of heart rate and human output power. The step of judging whether the contestant can complete the optimization action according to the physical fitness information specifically includes: Calculate the remaining disposable physical strength of the contestant at the current position according to the physical fitness information and the physiological parameter information; Determine whether the remaining available physical strength supports completion of the optimization action.

6. The method for analyzing competition results data according to claim 4, characterized in that: The step of obtaining competition action optimization suggestions for the contestants based on the extracted physiological parameter information and speed information specifically includes: After obtaining the quantified physical fitness information of the contestants, the optimal action plan for the individual competition based on the physical fitness information is calculated, wherein the optimal action plan for the individual competition includes a plurality of optimal actions for the individual competition sorted in chronological order; Calculate the theoretical physiological parameters of the contestants in each individual competition's optimal action in turn; According to the video image information and the speed information, obtaining the actual competition action corresponding to the optimal action time point of each individual competition; Get action optimization suggestions based on the specific differences between the best individual competition actions and actual competition actions; Physiological parameter optimization suggestions are obtained based on the specific differences between theoretical physiological parameters and the extracted physiological parameter information.

7. The method for analyzing competition results data according to claim 6, characterized in that: The step of calculating the optimal action plan for an individual competition based on the physical fitness information specifically includes: Starting from the starting point of the competition, the amount of physical strength distribution required to reach each optimal path position is calculated in sequence based on the physical fitness information; Calculate the optimal individual competition action required to reach each optimal path position according to the physical strength distribution; Collect all the best actions of individual competitions to get the best action plan for individual competitions.

8. The method for analyzing competition performance data according to any one of claims 4 to 7, characterized in that: The step of obtaining the quantified physical fitness information of the contestants specifically includes: Acquiring training data of the contestants, the training data including maximum heart rate, maximum heart rate duration, maximum human body power output, and maximum human body power output duration; The training data is quantified according to preset quantification rules to obtain quantified physical fitness information of the contestants.

9. The method for analyzing competition results data according to claim 8, characterized in that: The step of adjusting the optimized action to an action that can be completed based on the limitation of the physical fitness information specifically includes: Obtaining a range of movements that the contestant can support based on the physical fitness information; The optimization action is adjusted to an action whose action range is closest to the optimization action.

10. A competition performance data analysis system, characterized in that: include: A data acquisition unit, used to acquire competition performance data of road cycling participants, wherein the competition performance data includes physiological parameter information, position positioning information, speed information of the participants at various time points during the competition, and video image information collected by a camera; A route determination unit, configured to obtain a competition route of a contestant based on a competition map and the position positioning information, and to modify the competition route according to the video image information; A route comparison unit, used to compare the corrected race route with the theoretical optimal route of the race map; An information extraction unit, used for extracting physiological parameter information and speed information at corresponding time points for road sections with differences; The analysis and optimization unit is used to obtain competition action optimization suggestions for the contestants based on the extracted physiological parameter information and speed information.

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