Score and competition data representation method and system based on K line and Boolean line

Abstract

The invention relates to a score and competition data representation method and system based on a K line and a Boolean line. The method comprises the steps of collecting score data related to a preset object competition; after the score data is sorted, corresponding indexes of a K line and a Boolean line are constructed; wherein the hollow K line represents progressive, and the solid K line represents backward; marking data exceeding the upper and lower rails of the Boolean line in the K line; and the marked K line and Boolean line realize visual display of scores and characteristics, and the progress situation is evaluated. The method mainly aims at textualized and static characteristics and defects of records of scores and the like in the fields of education, sports, competition and the like, the relative relation, statistical characteristics and historical information of data such as scores and the like are displayed through the graphical representation technology formed by combining the K line and the Boolean line, and existing visualization means and methods of the data such as the scores and the like are greatly enriched.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a method and system for representing performance and competition data based on K-line and Bollinger band. Background Art

[0002] Conventional forms of expressing learning results mostly use simple data or tables to show people the results of the test, and some use common graphics such as line graphs, scatter plots, and box plots. These forms of expression are either not intuitive enough or the information displayed is limited. As a mature market, the financial market needs to display, analyze, and manage a large amount of data, and develop a series of graphical means. This provides a reference for graphical technical means for education, sports, competition results and other data.

[0003] Bollinger Bands and K-lines are both commonly used graphic techniques in financial markets, especially in the stock market. K-lines show short-term price fluctuations and key price levels. Bollinger Bands show long-term market trends and provide rich and intuitive statistical information and patterns, which facilitates market participants to quickly conduct statistical analysis and decision-making. The graphic technique combined with Bollinger Bands and K-lines has the characteristics of visualization and dynamics of general graphics, and can display data features in more dimensions, including median, maximum value, minimum value, and especially the most important mean and standard deviation indicators in statistics, and make them visualized and dynamic.

[0004] Traditional performance recording methods lack dynamism and interactivity, and it is difficult to intuitively display the progress trajectory and fluctuation characteristics of the learning process. The disadvantages are as follows:

[0005] Existing chart methods (such as line charts and scatter plots) cannot simultaneously display multi-dimensional data of a single test;

[0006] 1. Statistical indicators (such as mean and standard deviation) are presented in digital form, which is not intuitive enough;

[0007] 2. Lack of automatic recognition and reminder mechanism for abnormal performance;

[0008] 3. It is difficult to show the relative relationship between individual performance and group level;

[0009] 4. The presentation of historical data is too static, making it difficult to analyze long-term trends. Summary of the invention

[0010] The purpose of the present invention is to propose a method and system for representing performance and competition data based on K-line and Bollinger Bands to solve the problems existing in the above-mentioned prior art, mainly targeting the textual and static characteristics and shortcomings of records of performance and the like in the field of education, and using a graphical technique combined with K-line and Bollinger Bands to display the relative relationship, statistical characteristics, and historical information of performance and other data, greatly enriching the existing visualization means and methods of performance and other data.

[0011] To achieve the above object, the present invention provides the following solutions:

[0012] A method for expressing performance and competition data based on K-line and Bollinger Bands, comprising:

[0013] Collect performance data related to the preset object competition;

[0014] After the performance data is sorted, the corresponding indicators of K-line and Bollinger Band are constructed; among them, the hollow K-line represents progress, and the solid K-line represents regression. The moving average of the performance data constitutes the middle track of the Bollinger Band, and the moving average plus or minus the weighted standard deviation constitutes the upper and lower tracks of the Bollinger Band.

[0015] The data of K-line exceeding the upper and lower tracks of Bollinger Bands will be marked;

[0016] The marked K-line and Bollinger Bands enable a visual display of performance and its characteristics, and evaluate progress.

[0017] Optionally, the collected performance data related to the preset object competition includes: individual performance and group performance;

[0018] The personal score includes: date, initial personal score within a preset window, final personal score within a preset window, highest personal score within a preset window, and lowest personal score within a preset window;

[0019] The group score includes: date, group score within a preset window, the highest group score within the preset window, and the lowest group score within the preset window.

[0020] A method for representing performance and competition data based on K-line and Bollinger Bands, which is applied to the scoring performance analysis of players and players of the same type; the method includes:

[0021] Collect performance data related to players and players of the same type; the performance data includes: game date, player's individual score, score of players of the same type, highest score of players of the same type, and lowest score of players of the same type;

[0022] After the performance data is sorted, the corresponding indicators of K-line and Bollinger Band are constructed;

[0023] The K-line exceeds the upper and lower tracks of the Bollinger Bands and is marked;

[0024] The marked K-line and Bollinger Bands enable a visual display of performance and its characteristics, and evaluate progress.

[0025] Optionally, the performance data is organized into K-line format including:

[0026] The average score of players of the same type is regarded as the starting data of the K-line, the individual score of the player is regarded as the ending data of the K-line, the highest score of players of the same type is regarded as the highest data of the K-line, and the lowest score of players of the same type is regarded as the lowest data of the K-line;

[0027] K-line start data, K-line end data, K-line highest data, and K-line lowest data construct the K-line; in addition, hollow K-line indicates progress, and solid K-line indicates regression;

[0028] The performance data is organized into the form of Bollinger Bands, including:

[0029] A number of preset matches are regarded as a moving window, and the window width of the moving window is larger than the window width of the K-line; the players' personal average scores in the matches within the window constitute the middle track, the players' personal average scores + the preset standard deviation constitute the upper track, and the players' personal average scores - the preset standard deviation constitute the lower track.

[0030] A performance and competition data representation method based on K-line and Bollinger Bands, applied to Rubik's Cube speed training analysis; the method includes:

[0031] Collect the performance data related to the players; the performance data includes: training date, each restoration time, daily data records; the daily data records include: first attempt time, last attempt time, fastest completion time, slowest completion time;

[0032] After the performance data is sorted, the corresponding indicators of K-line and Bollinger Band are constructed;

[0033] The K-line exceeds the upper and lower tracks of the Bollinger Bands and is marked;

[0034] The marked K-line and Bollinger Bands enable a visual display of performance and its characteristics, and evaluate progress.

[0035] Optionally, arranging the performance data into a K-line format includes:

[0036] The first restoration time is regarded as the K-line start data, the last restoration time is regarded as the K-line end data, the slowest restoration time is regarded as the K-line highest data, and the fastest restoration time is regarded as the K-line lowest data;

[0037] K-line start data, K-line end data, K-line highest data, and K-line lowest data are used to construct K-line. Among them, hollow K-line indicates progress, and solid K-line indicates regression.

[0038] The performance data is organized into the form of Bollinger Bands, including:

[0039] The preset number of training days is regarded as the window period. The average restoration time of the preset date is used to construct the middle Bollinger band. The average restoration time of the preset date + the preset standard deviation is used to construct the upper Bollinger band. The average restoration time of the preset date - the preset standard deviation is used to construct the lower Bollinger band.

[0040] A method for representing scores and competition data based on K-line and Bollinger Bands, which is applied to the analysis of test scores; the method includes:

[0041] Collect relevant test taker performance data, including test session number and test score;

[0042] After the performance data is sorted, the corresponding indicators of K-line and Bollinger Bands are constructed; the data where the K-line exceeds the upper and lower tracks of the Bollinger Bands are marked;

[0043] The marked K-line and Bollinger Bands enable a visual display of performance and its characteristics, and evaluate progress.

[0044] Optionally, arranging the performance data into a K-line format includes:

[0045] The preset sessions are regarded as K-line windows;

[0046] The median in the K-line window is regarded as the K-line start data, the current test score is regarded as the K-line end data, the average value of the test in the K-line window + the preset standard deviation is regarded as the K-line highest data, and the average value of the test in the K-line window - the preset standard deviation is regarded as the K-line lowest data;

[0047] In addition, hollow candlesticks indicate progress, while solid candlesticks indicate regression;

[0048] The performance data is organized into Bollinger Bands, including:

[0049] Several sessions are considered Bollinger Band windows;

[0050] The average value of the test within the Bollinger Band window constructs the middle track, the middle track + the preset standard deviation constructs the upper track, and the middle track - the preset standard deviation constructs the lower track.

[0051] A performance and competition data representation system based on K-line and Bollinger Bands, the system comprising: a data acquisition module, a data processing module, a marking module and a visualization module;

[0052] A data collection module is used to collect performance data related to the preset object competition;

[0053] The data processing module is used to organize the performance data into K-line and Bollinger band forms respectively; among which, the hollow K-line indicates progress, and the solid K-line indicates regression;

[0054] The marking module is used to mark the data when the K-line exceeds the upper and lower tracks of the Bollinger Bands;

[0055] The visualization module visualizes the marked K-line and Bollinger Bands to evaluate the progress.

[0056] Optionally, the data collection module collects performance data related to the preset object competition, including:

[0057] Collecting performance data related to the preset object competition includes: individual performance and group performance;

[0058] The personal score includes: date, initial personal score within a preset window, final personal score within a preset window, highest personal score within a preset window, and lowest personal score within a preset window;

[0059] The group score includes: date, group score within a preset window, the highest group score within the preset window, and the lowest group score within the preset window.

[0060] The beneficial effects of the present invention are:

[0061] The present invention first collects performance data related to the preset object competition; secondly, organizes the performance data into K-line and Bollinger band forms; then marks the data where the K-line exceeds the upper and lower tracks of the Bollinger band; finally, visualizes the marked K-line and Bollinger band to evaluate the progress. The present invention realizes real-time data viewing through mouse hovering, which enhances interactivity; automatically marks excellent (G) and attention-needed (S) performance, which is convenient for timely detection of problems; hollow and solid K-lines distinguish between progress and regression; changes in the width of the Bollinger band reflect changes in performance stability; the Excel table export function facilitates data storage and further analysis; and supports statistics and display of multiple groups of test data. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0063] Figure 1 The score K-line and Bollinger chart of a certain shooting guard of a team VS other shooting guards in an embodiment of the present invention;

[0064] Figure 2 This is an example of K-line and Bollinger Bands for the daily Rubik's Cube training performance data of the players in the embodiment of the present invention;

[0065] Figure 3 The K-line and Bollinger Bands examples of the academic performance of a certain student in an embodiment of the present invention;

[0066] Figure 4 The present invention is a flowchart of a method for representing performance and competition data based on K-line and Bollinger Bands according to an embodiment of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0068] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0069] Embodiment 1

[0070] This embodiment proposes a method for representing performance and competition data based on K-line and Bollinger Bands, including:

[0071] Collect performance data related to the preset object competition;

[0072] The performance data are organized into K-line and Bollinger Band indicators respectively; among them, the hollow K-line indicates progress, and the solid K-line indicates regression. The moving average (MA) of the performance data constitutes the middle track of the Bollinger Band, and the moving average plus or minus the weighted standard deviation (SD) constitutes the upper and lower tracks of the Bollinger Band.

[0073] The data of the K-line exceeding the upper and lower tracks of the Bollinger Bands will be marked; W stands for slow and G stands for great.

[0074] The marked candlesticks and Bollinger Bands are displayed visually to evaluate progress.

[0075] Furthermore, the performance data collected for the preset competition includes two types: individual performance and group or class performance. One type is individual performance, which is generally a time (observation) window of several times in sequence to form a K-line for observation. The other type is to place individual performance in the group performance for observation. Individual performance, class performance and corresponding statistical indicators form a K-line, which is then examined together.

[0076] Among them, the personal score includes: date, initial personal score in the preset window, last personal score in the preset window, personal highest score in the preset window, and personal lowest score in the preset window; specifically, in this embodiment, four scores are set in one preset window, and the fourth score is observed, but the first three are put together to form a K-line for observation. It is generally better that this score is the score of the same course.

[0077] The group score includes: date, average score of the group within the preset window, highest score of the group within the preset window, and lowest score of the group within the preset window.

[0078] This embodiment realizes the dynamic visualization of performance data through the innovative application of K-line and Bollinger Bands, making the learning progress process more intuitive. Specifically, it is reflected in:

[0079] The K-line realizes the integrated display of multi-dimensional data (first, best, worst, and last scores) of a single test;

[0080] Bollinger Bands visually display learning trends and fluctuation ranges through moving averages and standard deviation channels.

[0081] Specific technical advantages:

[0082] 1. Real-time data viewing is achieved by hovering the mouse, which enhances interactivity;

[0083] 2. Automatically mark outstanding (G) and attention-needed (S) performance to facilitate timely detection of problems;

[0084] 3. Hollow and solid candlesticks distinguish between progress and regression;

[0085] 4. Changes in the width of the Bollinger Bands reflect changes in performance stability;

[0086] 5. Excel table import and export function facilitates data storage and further analysis;

[0087] 6.Support statistics and display of multiple groups of test data.

[0088] Embodiment 2

[0089] This embodiment proposes a performance and competition data representation method based on K-line and Bollinger Bands, which is applied to the scoring performance analysis of players and players of the same type; the method includes:

[0090] Collect performance data related to players and players of the same type; the performance data includes: game date, player's individual score, score of players of the same type, highest score of players of the same type, and lowest score of players of the same type;

[0091] After the performance data is sorted, the corresponding indicators of K-line and Bollinger Band are constructed;

[0092] The K-line exceeds the upper and lower tracks of the Bollinger Bands and is marked;

[0093] The marked K-line and Bollinger Bands enable a visual display of performance and its characteristics, and evaluate progress.

[0094] Furthermore, the performance data is organized into K-line format including:

[0095] The average score of players of the same type is regarded as the starting data of the K-line, the individual score of the player is regarded as the ending data of the K-line, the highest score of players of the same type is regarded as the highest data of the K-line, and the lowest score of players of the same type is regarded as the lowest data of the K-line;

[0096] K-line start data, K-line end data, K-line highest data, and K-line lowest data construct the K-line; in addition, hollow K-line indicates progress, and solid K-line indicates regression;

[0097] The performance data is organized into Bollinger Bands, including:

[0098] The preset number of games (for example, four games) are regarded as a moving window, and the window width of the moving window is larger than the window width of the K-line; the players' individual average scores in the games within the window are regarded as the middle track, the players' individual average scores + the preset standard deviation are regarded as the upper track, and the players' individual average scores - the preset standard deviation are regarded as the lower track.

[0099] Specifically, this embodiment is a K-line-Bollinger Bands-based player and similar player scoring performance analysis, and this example evaluates the performance of a person in group z. The steps include the following:

[0100] 1. Data collection stage

[0101] In this embodiment, the input data includes: game date (one game every 2-3 days); player's personal score (PlayerPPG); scores of players of the same type, such as scores of other shooting guards on the team (TeamGuardAvg); highest score of players of the same type, such as the highest score of shooting guards on the team (TeamGuardHigh); lowest score of players of the same type, such as the lowest score of shooting guards on the team (TeamGuardLow).

[0102] 2. K-line construction

[0103] In this embodiment, K-line data is constructed for each game; wherein the opening price is set as the average score of players of the same type; the closing price is set as the score of the player; the highest price is set as the highest score of players of the same type; and the lowest price is set as the lowest score of players of the same type.

[0104] Example:

[0105] The data of a certain game include: the average score of the team's defender: 15 points (opening price), the player's score: 18 points (closing price), the highest score of the team's defender: 22 points (highest price), the lowest score of the team's defender: 8 points (lowest price), etc.

[0106] 3. Trend analysis (this involves how simulation data is generated, which in turn can be regarded as a trend analysis model for data);

[0107] Baseline curve design: Starting point of rookie season: 8 points; Growth target: 18 points; Growth curve: exponential growth model; baseProgress = 8 + 10 (1exp (-linspace (0, 2, n) '));

[0108] Add random fluctuations: regular fluctuations: baseline value ± 4 points; explosive games (15% probability): baseline value + 10 points; sluggish games (10% probability): baseline value 8 points, etc.

[0109] 4. Bollinger Bands Analysis:

[0110] Window period: recent 10 games; middle track: average score of 10 games; upper track: average score + 2 standard deviations; lower track: average score 2 standard deviations;

[0111] Example data:

[0112] Average of 10 games: 15 points; Standard deviation: 3 points; Upper limit: 21 points; Lower limit: 9 points;

[0113] 5. Performance Evaluation

[0114] Excellent performance (G mark, Great job): score > upper limit; example: the player scored 23 points > upper limit 21 points;

[0115] Need to pay attention (W mark, warning): score < lower track; example: player score 7 points < lower track 9 points;

[0116] 6. Data Visualization

[0117] In this embodiment, the graphic elements of data visualization include: X-axis: game date (mmdd format, only the year is displayed at the beginning of the year); Y-axis: score range (0-40 points); K-line: display single game performance; Bollinger band: reflect recent trends;

[0118] 7. Interaction Design

[0119] In this embodiment, the interactive design can be set to display the following information when the mouse is hovered: game date; individual score; average score of team defenders; highest / lowest score; average Bollinger Band data of 10 games; performance evaluation, etc.

[0120] 8. Data Storage

[0121] In this embodiment, data is stored in the form of an Excel table; the data includes: game date; individual scoring data; team data; statistical indicators; file name: player_scoring_data.xlsx;

[0122] This example uses a combination of K-line and Bollinger Bands to intuitively show: 1. The comparison between the player and other shooting guards on the team; 2. The stability of individual scoring; 3. Performance trends and growth curves; 4. Automatic identification of excellent and poor performance;

[0123] This example is suitable for: rookie player development tracking; scout data analysis; coaching staff technical and tactical adjustments; player self-assessment; this analysis method retains the rigor of traditional technical statistics, while increasing the readability and intuitiveness of the data, providing a new analysis tool for player development evaluation.

[0124] The score K-line and Bollinger chart (with mouse hover pop-up window) of a shooting guard of a team VS other shooting guards, such as Figure 1 Click the K-line marked with "G" to display the corresponding game data information.

[0125] Embodiment 3

[0126] This embodiment proposes a method for representing performance and competition data based on K-line and Bollinger Bands, which is applied to the analysis of Rubik's Cube speed training; the method includes:

[0127] Collect the performance data related to the players; the performance data includes: training date, each restoration time, daily data records; the daily data records include: first attempt time, last attempt time, fastest completion time, slowest completion time;

[0128] After the performance data is sorted, the corresponding indicators of K-line and Bollinger Band are constructed;

[0129] The K-line exceeds the upper and lower tracks of the Bollinger Bands and is marked;

[0130] Marked K-line and Bollinger Bands enable visualization of performance and characteristics, and evaluation of progress

[0131] Furthermore, the performance data is organized into K-line formats including:

[0132] The first restoration time is regarded as the K-line start data, the last restoration time is regarded as the K-line end data, the slowest restoration time is regarded as the K-line highest data, and the fastest restoration time is regarded as the K-line lowest data;

[0133] The performance data is organized into the form of Bollinger Bands, including:

[0134] The preset number of training days is regarded as the window period, and the average recovery time of the preset date is used to construct the middle track. The average recovery time of the preset date + the preset standard deviation is used to construct the upper track, and the average recovery time of the preset date - the preset standard deviation is used as the lower track.

[0135] Specifically, this embodiment is applied to the analysis of Rubik's Cube speed training, and realizes the representation of K-line and Bollinger Band for multiple groups of data in a time window (a training day):

[0136] 1. Data collection stage

[0137] The data collected in this embodiment include: training date (daily training); each restoration time (multiple attempts); daily data records: first attempt time; last attempt time; fastest completion time; slowest completion time, etc.

[0138] 2. K-line construction

[0139] In this embodiment, K-line data is constructed for daily training; wherein, the corresponding opening price in the K-line data is the first restoration time; the closing price is the last restoration time; the highest price is the slowest restoration time; and the lowest price is the fastest restoration time;

[0140] For example: training data for a certain day (4 attempts); first: 32.5 seconds (opening price); last: 30.1 seconds (closing price); slowest: 35.2 seconds (highest price); fastest: 29.8 seconds (lowest price).

[0141] 3. Progress curve analysis (this involves how the simulation data is generated, which can be regarded as data trend analysis);

[0142] In this embodiment, the baseline curve design includes: initial level: 35 seconds; target level: 25 seconds; progress curve: exponential decline model; base_times=35*exp(-0.02(1:n)')); adding random fluctuations: number of training times per day: 3-6 times; fluctuation amplitude: gradually decreases with increasing training; coefficient of variation: 0.2*exp(-0.02*i), i represents the number of windows.

[0143] 4. Bollinger Bands Analysis

[0144] In this embodiment, the Bollinger Bands are set up for analysis: Window period: the last 10 training days; Middle track: 10-day average time; Upper track: average time + 2 standard deviations; Lower track: average time 2 standard deviations;

[0145] For example: 10-day average: 28.5 seconds; standard deviation: 2 seconds; upper track: 32.5 seconds; lower track: 24.5 seconds.

[0146] 5. Performance Evaluation

[0147] Excellent performances are marked with the character G: restoration time < lower track; example: completion time 23.5 seconds < lower track 24.5 seconds; those that need attention are marked with the character S: restoration time > upper track; example: completion time 33 seconds > upper track 32.5 seconds.

[0148] 6. Data Visualization

[0149] The graphic elements of data visualization include: X-axis: training date (mmdd format, only the year at the beginning of the year is displayed); Y-axis: time interval (10-55 seconds); K-line color: hollow (white fill): progress (last < first); solid (blue fill): regression (last > first).

[0150] 7. Interactive Features

[0151] Interactive functions are represented by hovering information, including: training date; number of training sessions; detailed time; first / last time; average time; Bollinger Bands data; status evaluation.

[0152] 8. Data Storage

[0153] This embodiment stores data in the form of an Excel spreadsheet; including: first problem-solving time; slowest / fastest time; last problem-solving time; moving average; Bollinger band upper and lower limits;

[0154] This embodiment is suitable for: 1. Rubik's Cube problem-solving introductory training; 2. Daily practice for sprint players; 3. Coaches tracking students' progress; 4. Competition preparation analysis.

[0155] The innovative contents of this embodiment include: 1. K-line reflects the quality of single-day training; 2. Bollinger Bands display stability is improved; 3. Unified display of multiple training data; 4. Intuitive distinction between progress / regression; 5. Automatic identification of abnormal performance; This analysis method combines: the integrity of traditional training records; the visualization advantages of financial technical analysis; the scientific nature of statistics; the convenience of interactive interface. It provides a professional data analysis tool for Rubik's Cube training, helping practitioners to better grasp the training effect and progress trend.

[0156] Examples of K-line and Bollinger Bands of players' daily Rubik's Cube training performance data (with a pop-up window on mouse hover, showing specific data and information corresponding to a single K-line) Figure 2 shown.

[0157] Embodiment 4

[0158] This embodiment proposes a method for representing scores and competition data based on K-line and Bollinger Bands, which is applied to the analysis of test scores. The method includes:

[0159] Collect relevant test taker performance data, including test session number and test score;

[0160] After the performance data is sorted, the corresponding indicators of K-line and Bollinger Band are constructed;

[0161] The K-line exceeds the upper and lower tracks of the Bollinger Bands and is marked;

[0162] The marked K-line and Bollinger Bands enable a visual display of performance and its characteristics, and evaluate progress.

[0163] Furthermore, the performance data is organized into K-line format including:

[0164] Preset a number of sessions as K-line windows;

[0165] The median in the K-line window is regarded as the K-line start data. The current test score is regarded as the K-line end data. The average value of the test in the K-line window + the preset standard deviation is regarded as the K-line highest data. The average value of the test in the K-line window - the preset standard deviation is regarded as the K-line lowest data.

[0166] In addition, hollow candlesticks indicate progress, while solid candlesticks indicate regression;

[0167] The performance data is organized into the form of Bollinger Bands, including:

[0168] A number of exams are preset as Bollinger Band windows;

[0169] The average value of the test within the Bollinger Band window constructs the middle track, the middle track + the preset standard deviation constructs the upper track, and the middle track - the preset standard deviation constructs the lower track.

[0170] Specifically, this embodiment is for test score evaluation. This embodiment takes full advantage of the time complementarity of the K-line and the Bollinger Bands for one time window and one data case, and redefines the data features corresponding to the data port of the K-line.

[0171] The data feature definition in this embodiment includes: the sample size is set to 60 exams; the score range is set to 50-100 points; the observation window, i.e., the K-line window, is set to 5 exams; and the Bollinger Band window is set to 10 exams;

[0172] For example: the benchmark score for a certain exam is 75 points; the normal score is 69-81 points; the difference is 55-90 points.

[0173] 2. K-line calculation method

[0174] The K-line window in this embodiment corresponds to five consecutive exams; the data to be calculated include: the opening value is set as the median in the time window; the highest value is set as the mean + 1.5 standard deviation; the lowest value is set as the mean + 1.5 standard deviation; the closing value is set as the score of the exam; the mean is set as the average of the exams;

[0175] Numerical range control: the upper limit of the highest value is set to 100 points; the lower limit of the lowest value is set to 50 points.

[0176] 3. Bollinger Bands Analysis

[0177] The calculation parameters include: the middle track is the 10-time moving average; the upper track is the middle track + 2 standard deviations; the lower track is the middle track 2 standard deviations;

[0178] Initial value processing: if the number of exam sessions is less than 3: the standard deviation is the standard deviation of all current exams; else: the standard deviation is the standard deviation of the most recent exam.

[0179] 5. Performance assessment mechanism;

[0180] In this embodiment, the excellent performance is marked with the character G; wherein the trigger condition is: the score is greater than or equal to the upper track; its meaning is that it can represent a significant excess of the stable level;

[0181] The attention performance is marked with the character W; the trigger condition is: the current score <= lower track; its meaning is that it needs special attention.

[0182] 6. Visual design

[0183] Visualization design includes: graphic configuration, drawing elements, and Bollinger band color design; among them, graphic configuration includes: window size is set to 1200x600; coordinate range is set to X-axis: test number (-2 to n+2), Y-axis: score (45-115); drawing elements include: K-line chart is set to blue; Bollinger band includes: middle rail is set to red solid line; upper and lower rails are set to red dotted lines;

[0184] 7. Interactive Features

[0185] The interactive function of this embodiment displays information by hovering the mouse; the displayed information includes: test date; actual score; median score; moving average; Bollinger band upper and lower limits; and status evaluation.

[0186] Information box settings: Position: Dynamic adjustment; Size: 0.3x 0.25; Background: White; Border: Black.

[0187] 8. Data Storage

[0188] The data in this embodiment is stored via Excel files;

[0189] For example, Table 1: Daily_Data is set with test number, actual score, median score, highest score, lowest score, moving average, and upper and lower limits of Bollinger Bands;

[0190] For example, Table 2: Statistics settings include average score; standard deviation, median, highest score, lowest score, number of times exceeding the upper track, number of times breaking the lower track, and system characteristics.

[0191] The effects of this embodiment are as follows:

[0192] The evaluation dimensions of this embodiment include: single test performance, periodic stability, long-term improvement trend, and abnormal performance identification;

[0193] The application value of this embodiment includes: learning effect evaluation, grade fluctuation warning, study plan adjustment, and test performance analysis;

[0194] The innovations of this embodiment include: multi-dimensional performance display, dynamic evaluation criteria, instant interactive feedback, and automatic abnormality identification;

[0195] The usage scenarios of this embodiment include: daily test evaluation, learning effect tracking, teaching quality monitoring, and student growth files;

[0196] This embodiment provides an intuitive and scientific analysis tool for educational assessment, which can help teachers and students better understand and improve the learning process.

[0197] Example of K-line and Bollinger Bands of a student's academic performance (with a pop-up window on mouse hover to display specific data and information corresponding to a single K-line) Figure 3 shown.

[0198] Embodiment 5

[0199] This embodiment proposes a performance and competition data representation system based on K-line and Bollinger Bands, the system comprising: a data collection module, a data processing module, a marking module and a visualization module;

[0200] A data collection module is used to collect performance data related to the preset object competition;

[0201] The data processing module is used to organize the performance data into K-line and Bollinger band forms;

[0202] The marking module is used to mark the data when the K-line exceeds the upper and lower tracks of the Bollinger Bands;

[0203] The visualization module visualizes the marked K-line and Bollinger Bands to evaluate the progress.

[0204] Furthermore, the data collection module collects performance data related to the preset object competition, including:

[0205] Collecting performance data related to the preset object competition includes: individual performance and group or class performance;

[0206] Among them, personal scores include: date, initial personal score within the preset time, final personal score within the preset time, personal highest score within the preset time, and personal lowest score within the preset time;

[0207] The group or class score includes: date, the scores of other members of the group or class within the preset time, the highest score of other members of the group or class within the preset time, and the lowest score of other members of the group or class within the preset time.

[0208] Specifically, in this embodiment, the data collection module is responsible for collecting original performance data from external sources (such as user input, file import, etc.).

[0209] The input of the data collection module is: the score data of a single test. The score data can be entered manually or imported from external files (such as Excel, CSV). The data is sorted and stored in chronological order for subsequent processing.

[0210] The output of the data acquisition module is: time series arrangement and storage of raw data.

[0211] Data processing module, used to calculate the candlestick and Bollinger Bands indicators.

[0212] The input of the data processing module is: normalized time series data (score data).

[0213] The output of the data processing module is: K-line data and Bollinger Bands data (including moving average, upper and lower rails).

[0214] Among them, K-line calculation: calculate the opening price, closing price, highest price and lowest price according to the order of performance, and determine the progress / regression status, and decide whether to use solid or hollow K-line. Bollinger Band calculation: by setting the moving window size, calculate the moving average (MA), standard deviation (SD) and the upper and lower tracks of the Bollinger Band, and mark whether the performance exceeds the Bollinger Band (needs attention or excellent performance).

[0215] The visualization module is used to generate graphical interfaces and handle interactions with users;

[0216] The input of the visualization module is: the calculated K-line and Bollinger Bands data;

[0217] The output of the visualization module is: dynamically generate a graphical interface to display the K-line chart and Bollinger Bands;

[0218] Among them, K-line drawing: based on the calculation results of the K-line, draw solid and hollow K-lines to indicate the state of progress or regression. Bollinger Band drawing: draw moving averages, upper and lower rails, and marked abnormal points. Interactive function: listen to mouse hover events, display relevant information boxes (such as date, grades, statistical indicators, etc.), and support dynamic adjustment of the position of the information box.

[0219] Data storage module, used to save and export analysis results;

[0220] Input of the data storage module: data processing results and visualization results;

[0221] Output of the data storage module: exported analysis result file (such as Excel file);

[0222] The results of each analysis are saved, and multiple tables are supported, such as daily summary tables and detailed data tables. They can be exported to Excel format for subsequent viewing or archiving.

[0223] The core algorithm flow and control logic of this embodiment are as follows:

[0224] 1. Data initialization phase

[0225] Input: single test result data;

[0226] Processing: Organize and store data in chronological order, ensuring that the data format and order meet the requirements of subsequent analysis;

[0227] Output: Normalized time series data (sorted by date, including each grade).

[0228] 2. K-line calculation stage

[0229] Input: All scores of a single test;

[0230] Processing: Calculate the opening price, closing price, highest price and lowest price;

[0231] Determine the progress or regression of performance:

[0232] If the closing price ≤ the opening price, it indicates progress and a hollow candlestick is drawn;

[0233] If the closing price > opening price, it means retreat and a solid candlestick is drawn;

[0234] Output: calculated K-line data.

[0235] 3. Bollinger Bands calculation stage

[0236] Input: Closing price data;

[0237] Processing: Set the moving window size (N) and calculate the moving average (MA) and standard deviation (SD) of each window;

[0238] Calculate the upper and lower Bollinger Bands based on MA and SD:

[0239] Upper rail = MA + 2SD; Lower rail = MA - 2SD;

[0240] Output: Bollinger Bands upper and lower rail data.

[0241] 4. Abnormal performance markers

[0242] Input: Closing price, upper and lower Bollinger Bands;

[0243] Processing: If the closing price > upper track, mark as "S" (need attention);

[0244] If the closing price is less than the lower track, it is marked as "G" (excellent performance);

[0245] Output: Abnormal performance mark (S, G).

[0246] 5. Interactive function implementation

[0247] Input: data points in the graphical interface;

[0248] Processing: Listen to mouse movement events, obtain mouse coordinates, and determine whether it is hovering near a data point; dynamically display an information box to display relevant data (such as date, score, statistical indicators, etc.); adjust the position of the information box so that it is always displayed within the user's visible range;

[0249] Output: A dynamically updated interface showing detailed performance information and statistical indicators.

[0250] The key design and technical aspects used in this embodiment are as follows:

[0251] 1. Data structure design

[0252] Data Structure

[0253]

[0254]

[0255] 2. Visualization Implementation

[0256] Coordinate system drawing:

[0257] X-axis: represents the test date;

[0258] Y-axis: represents the score range (usually 0 to 100);

[0259] K-line drawing:

[0260] Solid K-line: indicates regression;

[0261] Hollow candlestick: indicates progress;

[0262] Bollinger Bands drawing:

[0263] Moving average: solid line;

[0264] Bollinger Bands upper and lower rails: dotted lines;

[0265] 3. Interaction Implementation

[0266] Event Listener:

[0267] Mouse movement event: monitor the coordinates of the mouse to determine whether it is near a data point; dynamic update:

[0268] Contents of the information box: display relevant dates, scores, and statistical information;

[0269] Dynamically adjust the position of the information box: ensure that the information box does not block other content in the view;

[0270] 4. Data Export

[0271] Export Excel file:

[0272] Supports exporting summary tables and detailed data tables, including dates, scores, statistical indicators, etc.

[0273] The system usage process (based on modules);

[0274] 1. Data input:

[0275] Enter manually or import from file;

[0276] 2. Parameter settings:

[0277] Set the Bollinger Bands period (10 days by default) and display range (e.g. set a certain date range);

[0278] 3. Visualization Analysis:

[0279] Users view performance trends, identify unusual performance, and assess progress;

[0280] 4. Data export:

[0281] Export the analysis results to Excel format and save the report;

[0282] Control logic and connection relationship between system modules:

[0283] The data collection module inputs the original score data into the data processing module for analysis;

[0284] The data processing module calculates the K-line and Bollinger Band indicators based on the time series data, and passes the calculation results to the visualization module for graphical display;

[0285] The visualization module plots the processed data into K-line charts and Bollinger Bands charts, and supports hovering the mouse to view detailed data;

[0286] The data storage module saves the processing and visualization results to files for subsequent query and analysis. Figure 4 shown.

[0287] The advantages of this embodiment are: through the innovative application of K-line and Bollinger Bands, dynamic visualization of performance data is achieved, making the learning progress process more intuitive. Specifically, it is reflected in:

[0288] K-line realizes the integrated display of multi-dimensional data of a single test (first, best, worst, and last scores)

[0289] Bollinger Bands visually display learning trends and fluctuation ranges through moving averages and standard deviation channels.

[0290] Specific technical advantages:

[0291] 1. Real-time data viewing is achieved by hovering the mouse, which enhances interactivity;

[0292] 2. Automatically mark outstanding (G) and attention-needed (S) performance to facilitate timely detection of problems;

[0293] 3. Hollow and solid candlesticks distinguish between progress and regression;

[0294] 4. Changes in the width of the Bollinger Bands reflect changes in performance stability;

[0295] 5. Excel table export function facilitates data storage and further analysis;

[0296] 6.Support statistics and display of multiple groups of test data.

[0297] The above embodiments are only descriptions of the preferred embodiments of the present invention, and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should fall within the protection scope determined by the claims of the present invention.

Claims

1. A method for expressing performance and competition data based on K-line and Bollinger Bands, characterized in that: include: Collect performance data related to the preset object competition; After the performance data is sorted, the corresponding indicators of K-line and Bollinger Band are constructed; among them, the hollow K-line represents progress, and the solid K-line represents regression. The moving average of the performance data constitutes the middle track of the Bollinger Band, and the moving average plus or minus the weighted standard deviation constitutes the upper and lower tracks of the Bollinger Band. The data of K-line exceeding the upper and lower tracks of Bollinger Bands will be marked; The marked K-line and Bollinger Bands enable a visual display of performance and its characteristics, and evaluate progress.

2. The performance and competition data representation method based on K-line and Bollinger Bands according to claim 1, characterized in that: Collecting performance data related to the preset object competition includes: individual performance and group performance; The personal score includes: date, initial personal score within a preset window, final personal score within a preset window, highest personal score within a preset window, and lowest personal score within a preset window; The group score includes: date, group score within a preset window, the highest group score within the preset window, and the lowest group score within the preset window.

3. A method for expressing performance and competition data based on K-line and Bollinger Bands, characterized in that: Applied to the analysis of scoring performance of players and peers; methods include: Collect performance data related to players and players of the same type; the performance data includes: game date, player's individual score, score of players of the same type, highest score of players of the same type, and lowest score of players of the same type; After the performance data is sorted, the corresponding indicators of K-line and Bollinger Band are constructed; The K-line exceeds the upper and lower tracks of the Bollinger Bands and is marked; The marked K-line and Bollinger Bands enable a visual display of performance and its characteristics, and evaluate progress.

4. The performance and competition data representation method based on K-line and Bollinger Bands according to claim 3, characterized in that: The performance data is organized into K-line format including: The average score of players of the same type is regarded as the starting data of the K-line, the individual score of the player is regarded as the ending data of the K-line, the highest score of players of the same type is regarded as the highest data of the K-line, and the lowest score of players of the same type is regarded as the lowest data of the K-line; K-line start data, K-line end data, K-line highest data, and K-line lowest data construct the K-line; in addition, hollow K-line indicates progress, and solid K-line indicates regression; The performance data is organized into the form of Bollinger Bands, including: A number of preset matches are regarded as a moving window, and the window width of the moving window is larger than the window width of the K-line; the players' personal average scores in the matches within the window constitute the middle track, the players' personal average scores + the preset standard deviation constitute the upper track, and the players' personal average scores - the preset standard deviation constitute the lower track.

5. A method for expressing performance and competition data based on K-line and Bollinger Bands, characterized in that: Applied to the analysis of Rubik's Cube speed training; the methods include: Collect the performance data related to the players; the performance data includes: training date, each restoration time, daily data records; the daily data records include: first attempt time, last attempt time, fastest completion time, slowest completion time; After the performance data is sorted, the corresponding indicators of K-line and Bollinger Band are constructed; The K-line exceeds the upper and lower tracks of the Bollinger Bands and is marked; The marked K-line and Bollinger Bands enable a visual display of performance and its characteristics, and evaluate progress.

6. The performance and competition data representation method based on K-line and Bollinger Bands according to claim 5, characterized in that: The results data is organized into K-line format including: The first restoration time is regarded as the K-line start data, the last restoration time is regarded as the K-line end data, the slowest restoration time is regarded as the K-line highest data, and the fastest restoration time is regarded as the K-line lowest data; K-line start data, K-line end data, K-line highest data, and K-line lowest data are used to construct K-line; among them, hollow K-line indicates progress, and solid K-line indicates regression; The performance data is organized into the form of Bollinger Bands, including: A preset number of training days is regarded as the window period. The average recovery time of the preset date constructs the middle Bollinger band, the average recovery time of the preset date + the preset standard deviation constructs the upper Bollinger band, and the average recovery time of the preset date - the preset standard deviation constructs the lower Bollinger band.

7. A method for expressing performance and competition data based on K-line and Bollinger Bands, characterized in that: Applied to the analysis of test scores; methods include: Collect the relevant performance data of candidates, including test sessions and test scores; After the performance data is sorted, the corresponding indicators of K-line and Bollinger Band are constructed; The K-line exceeds the upper and lower tracks of the Bollinger Bands and is marked; The marked K-line and Bollinger Bands enable a visual display of performance and its characteristics, and evaluate progress.

8. The performance and competition data representation method based on K-line and Bollinger Bands according to claim 7, characterized in that: The results data is organized into K-line format including: Preset a number of sessions as K-line windows; The median in the K-line window is regarded as the K-line start data, the current test score is regarded as the K-line end data, the average value of the test in the K-line window + the preset standard deviation is regarded as the K-line highest data, and the average value of the test in the K-line window - the preset standard deviation is regarded as the K-line lowest data; In addition, hollow candlesticks indicate progress, while solid candlesticks indicate regression; The performance data is organized into Bollinger Bands, including: Several sessions are considered Bollinger Band windows; The average value of the test within the Bollinger Band window constructs the middle track, the middle track + the preset standard deviation constructs the upper track, and the middle track - the preset standard deviation constructs the lower track.

9. A performance and competition data presentation system based on K-line and Bollinger Bands, characterized in that: For implementing any of the methods of claims 1-8, the system comprises: a data acquisition module, a data processing module, a marking module and a visualization module; A data collection module is used to collect performance data related to the preset object competition; The data processing module is used to organize the performance data into K-line and Bollinger band forms respectively; among which, the hollow K-line indicates progress, and the solid K-line indicates regression; The marking module is used to mark the data when the K-line exceeds the upper and lower tracks of the Bollinger Bands; The visualization module visualizes the marked K-line and Bollinger Bands to evaluate the progress.

10. The performance and competition data presentation system based on K-line and Bollinger Bands according to claim 9, characterized in that: The data collection module collects the performance data related to the preset object competition, including: Collecting performance data related to the preset object competition includes: individual performance and group performance; The personal score includes: date, initial personal score within a preset window, final personal score within a preset window, highest personal score within a preset window, and lowest personal score within a preset window; The group score includes: date, group score within a preset window, the highest group score within the preset window, and the lowest group score within the preset window.

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