A system for performance tracking

Abstract

A system for performance tracking, comprising: a plurality of user devices, each user device comprising a processor, a wireless communication module, a camera for capturing video footage, and a memory storing an application; a server communicatively coupled to the plurality of devices via a wireless network; and a plurality of user profiles associated with respective users of the plurality of user devices; wherein the application is configured to enable users to capture video footage, and wherein the server is configured to detect and analyse the location and / or movement of one or more objects within the video footage received from a respective user and return data derived from the analysis to that user through the application.

Description

[0001] A system for performance tracking

[0002] The present disclosure relates to a system for performance tracking. In particular, to such a system that allows users to track their performance in a chosen ball sport. The system preferably further allows for interaction / com petition between users of the system.

[0003] Technology has significantly transformed social interactions in many ways, with communication faster and more immediate. Individuals can readily communicate in real time, regardless of geographical location. Moreover, the rise of online platforms and forums has fostered the creation of niche communities. People can now find others who share very specific interests or experiences. Online gaming has further opened up new spaces for social interactions.

[0004] The present invention arose as a result of work looking to harness technology for the benefit of sports players seeking to develop their skills and engage with other like-minded players.

[0005] Representative features are set out in the following clauses, which stand alone or may be combined, in any combination, with one or more features disclosed in the text and / or drawings of the specification.

[0006] According to the present invention, in a first aspect, there is provided a system for performance tracking, comprising: a plurality of user devices, each user device comprising a processor, a wireless communication module, a camera for capturing video footage, and a memory storing an application; a server communicatively coupled to the plurality of devices via a wireless network; and a plurality of user profiles associated with respective users of the plurality of user devices; wherein the application is configured to enable users to capture video footage, and wherein the server is configured to detect and analyse the location and / or movement of one or more objects within the video footage received from arespective user and return data derived from the analysis to that user through the application.

[0007] According to the present invention in a further aspect, there is provided a method for performance tracking, comprising: establishing a wireless connection between a server and a plurality of user devices, each user device comprising a processor, a wireless communication module, a camera for capturing video footage, and a memory storing an application storing user profiles associated with respective users of the plurality of user devices; executing an application to enable users to capture video footage, and detecting and analysing the location and / or movement of one or more objects within the video footage received from a respective user and returning data derived from the analysis to that user through the application.

[0008] According to the present invention in a yet further aspect, there is provided a non-transitory computer-readable medium comprising instructions which, when executed by one or more processors, cause the one or more processors to perform the method as defined above.

[0009] According to the present invention in another aspect, there is provided a server communicatively coupled to a plurality of user devices via a wireless network, wherein the server is configured to: administer an application storing user profiles associated with respective users of the plurality of user devices; and detect and analyse the location and / or movement of one or more objects within video footage received from a respective user and return data derived from the analysis to that user through the application.

[0010] The one or more objects may comprise a sports ball, a movable piece of sports equipment and / or the user’s body, and / or a fixed piece of sports equipment.

[0011] When tracking a sports ball, in particular, the application may be configured to identify predefined data points along the path of the balls travel. The data points may comprise one or more of a ball release point, a bounce point, and a final impact point. The data points may be stored / used by the application / server for further analysis.Preferably, the application is configured to enable users to interact with one another via the server by exchanging data associated with the user profiles, wherein the exchanged data includes the data derived from the analysis of the video footage.

[0012] The application may be configured to rank the users against one another within the application on the basis of a comparison of the exchanged data.

[0013] The application may comprises a matchmaking algorithm for pairing users of similar skill level for competition against one another. The matchmaking algorithm preferably uses historical data derived from the analysis of the video footage as an input, for predicting the probable outcome of competitive pairings. The matchmaking algorithm may be based on an Elo rating system. The matchmaking algorithm may use the historical data, weighted rolling averages, and Bayesian inference for making predictions.

[0014] The application may be configured to allow for the exchange of cryptocurrency tokens between users via the server.

[0015] Each user profile may comprise biometric data for the respective user. The server may be configured to authorise the data derived from the captured video footage using the biometric data. Preferably, the biometric data comprises facial recognition, and the server is configured to authorise the data only when the respective user is identified in the respective video footage received by the server.

[0016] The server may be configured to authorise the data for a user (and allocate the data against the user profile of the user) only when the respective user is identified in the respective video footage before and / or after the movement of the object to be analysed. The server may be configured to authorise the captured footage only when the respective user is determined not to have left the field of view of the camera during capture.

[0017] The server may be configured to restrict the exchange of data between users to authorised data.The application may comprise an anomaly detection algorithm for comparing the data derived from the analysis of the video footage with stored historical data derived from the analysis of the video footage for identifying unexpected performance improvements. The application may be configured to require reconfirmation of the user using the biometric data in the event unexpected performance improvements are detected, such as an unexpected spike in performance.

[0018] The application may be configured to continuously monitor for biometric data, and to associate data derived from the analysis of the video footage to the identified user in the video footage. This may allow for automatic switching between multiple users within the application running on a single user device.

[0019] The application may use data from an accelerometer and / or gyroscope within the user device to validate stability of the user device before permitting the recording of an activity.

[0020] The application may be configured to require the fixing of the camera of the user device at a predetermined height off the ground. The application may be configured to require the user device to be positioned with a target, which may comprise equipment (e.g. cricket stumps or a goal) or pitch markings, within a bounding box or other graphical guide shown on the display of the user device. The application may use computer vision techniques to accurately identify and position the equipment or markings. The computer vision techniques may comprise edge detection and / or perspective transformation.

[0021] The application may be configured to render equipment in augmented reality on the screen of the user device based on a marker provided by the user at an appropriate location in the real world.

[0022] The application may be configured to calculate the speed of the object (e.g. ball) by determining the distance travelled by the object over time. The application may use physics-based motion equations. The equation preferably accuratelymeasuring the object’s displacement using high frame rate video, which may be 60 frames per second or more, and may be 120 frames per second or more.

[0023] The application may be configured to optimise processing by automatically segmenting the video footage for removal of frames that are determined to be redundant.

[0024] Further, preferable, features will be evident from the dependent claims and also from the specific description that follows.

[0025] Non-limiting embodiments of the invention will now be discussed with reference to the following drawings:

[0026] Figure 1 shows a schematic representation of a system for performance tracking;

[0027] Figure 2A shows a frame from a video under analysis by the server, and Figure 2B shows a subsequent frame from the video under analysis in which the path of a ball has been tracked; and

[0028] Figure 3 shows an example screenshot of a user device running the application.

[0029] With reference to Figure 1 , there is shown, schematically, a system for performance tracking, which comprises a plurality of user devices 2 and a server 1 communicatively coupled to the plurality of user devices 1 via a wireless network 100, 110. Each user device 2 comprises a processor, a wireless communication module, a camera, and a memory storing an application. A plurality of user profiles are associated with respective users of the plurality of user devices. The application is configured to enable users to capture video footage and transfer the video footage to the server 1. The server 1 is configured to detect and analyse the location and / or movement of one or more objects within the video footage received from a respective user and return data derived from the analysis to that user through the application.The user devices 2 may comprise smartphones, tablet computers or similar mobile devices. The system may be delivered through mobile applications, supporting Android and IOS devices.

[0030] The wireless communication modules of the user devices 2 may comprise cellular transceivers and / or Wi-Fi transceivers for exchanging data with a corresponding base station 110. The base station 110 is connected for data communication with one or more data communication networks 100 via a suitable data link, such that the user devices 2 can exchange information with server 1.

[0031] As will be readily appreciated by those skilled in the art, numerous network configurations will be possible for implementation of a system according to the present disclosure. The present invention is not to be limited to any particular network configuration.

[0032] It is preferable that the one or more objects comprise a sports ball, the motion of which is tracked. The one or more objects may additionally or alternatively comprise a piece of sports equipment. Such sports equipment may be movable or fixed. For example, the sports equipment may comprise a bat, racket, glove, or similar that is used by a player during play, or stumps, a goal, or similar that form part of the equipment of play, and which may be fixed in place or may move also.

[0033] Whilst specific reference is made below to the sport of cricket. It should be appreciated that the present invention is not to be limited to any particular sport. The disclosed system may be adapted for use with numerous sports, including, but not limited to, baseball, tennis, football, American football, and basketball, as will be readily appreciated by those skilled in the art.

[0034] The application is preferably configured to enable users to interact with one another via the server by exchanging data associated with the user profiles, wherein the exchanged data includes the data derived from the analysis of the video footage.

[0035] The application may support both direct and server-mediated interaction between users. Direct interactions may allow users to send messages, photos, orother media directly to one another, without intermediation by the server 1.

[0036] However, as will become apparent from the discussion below, server-mediated interactions between users are preferred, particularly in respect of any sporting competitions between users, wherein data to be shared may then be authorised by the server 1.

[0037] It is particularly preferred that each user profile comprises biometric data for the respective user. The server 1 may be configured to authorise the data derived from the captured video footage using the biometric data. The use of biometric data may be optional. However, restrictions may be applied on users who opt not to use biometric data. In a particularly preferred embodiment, the biometric data comprises facial recognition, and the server 1 is configured to authorise the data only when the respective user is identified in the respective video footage received by the server 1. The server 1 may be configured to authorise the data only when the respective user is identified in the respective video footage before and / or after the movement of the object to be analysed. The server may be configured to authorise the captured footage only when the respective user is determined not to have left the field of view of the camera during capture (or a relevant portion of the captured video).

[0038] Consideration will now be given, by way of example only, to the creation of a user profile and potential restrictions related to differing levels of authorisation.

[0039] Upon downloading the application to their device 2, a user is required to create a profile. Multiple levels of authorisation for the user profile will be possible, as will be appreciated by those skilled in the art. However, the user will be encouraged to complete their profile with the inclusion of facial recognition. This can then feed into ‘anti abuse’ measures that the application tests to validate gaming results between users. Principally, by use of facial recognition the situation can be avoided that a user has a third party perform recorded actions as part of a competition.

[0040] Where a user opts to include facial recognition, they are prompted during setup of facial recognition to take a plurality of photos of their face are taken using their device. The photos are taken from different angles using an alignment graphic, such as an oval. Three or more photos may be captured. These images areprocessed using facial landmark detection and stored in the application / on the server as biometric templates.

[0041] In a preferred arrangement, a deep learning-based dlib algorithm is implemented with a Histogram of Oriented Gradients (HOG) feature descriptor and a Support Vector Machine (SVM) classifier for face detection, followed by a deep metric learning model for recognition.

[0042] During the recording of an activity, as noted, the user may be required to stay in frame and look at the camera. Using a real-time face tracking pipeline, the application may continuously compare the user's face against the pre-stored biometric templates. The system preferably utilizes a Convolutional Neural Network (CNN)-based model. In a preferred arrangement, an accuracy of 99.38% on the "Labelled Faces in the Wild" benchmark has been achieved. As again noted, the use of facial recognition may ensure that only the registered user is performing the action, preventing fraudulent activity.

[0043] This feature further allows for automatic switching between users, such as in team practice sessions, or where two or more users are sharing a device during a session. By continuously identifying users, the system may dynamically adjust and assign statistics to the correct individual / user profile.

[0044] Once the verification of the user is complete, access to enter various competitions and tournaments between users of the system opens up to the user. However, prior to verification, the functionality of the app is still valuable in the sense that the user can monitor their own performance. The system may, however, be configured such that any statistics or other data, derived from the analysis of a video uploaded by the respective user, are not recorded in the system / shareable with other users until verified.

[0045] The outline architecture is that the video footage of the user taking part in any particular sporting activity, such as but not limited to bowling, pitching, batting, catching or kicking is uploaded from the user device to the server 1 , through any suitable network infrastructure (as discussed above), where the server analyses andvalidates the footage, using machine learning techniques, and then sends the data back to update the user profile.

[0046] As will be readily appreciated by those skilled in the art, the identification and tracking of objects using cameras is a prominent area within the field of computer vision. Typically, it involves modelling the scene background, detecting the foreground regions, and employing a known tracking algorithm to derive the instantaneous location of objects within the field of view of the

[0047] camera. Tracking systems are widely employed for applications such as defence and civil surveillance, traffic control, and game enhancement.

[0048] The present inventors have recognised the benefit of employing such object tracking techniques using existing user devices, for performance tracking during sports practice or play.

[0049] As will be appreciated, object detection and tracking in images using machine learning involves multiple techniques and algorithms. It typically consists of two main stages: (i) object detection; and (ii) object tracking.

[0050] In the present case, the system employs a multi-stage deep learning pipeline for object detection and motion tracking. Any suitable known object detection and tracking techniques may be implemented, as will be readily appreciated by those skilled in the art.

[0051] Object detection

[0052] A. Preprocessing

[0053] One or more preprocessing steps may be implemented, including, but not limited to:

[0054] Image Augmentation: Scaling, rotation, flipping, and / or colour adjustments to improve model generalization.

[0055] Normalization: Adjust pixel values to a standard range (e.g., [0,1] or [-1,1]).B. Object Detection Models

[0056] One or more deep learning-based object detection models may be implemented, including, but not limited to:

[0057] i. Convolutional Neural Networks (CNNs)

[0058] ii. Region-Based CNN (R-CNN) Family

[0059] iii. Single Shot MultiBox Detector (SSD)

[0060] iv. You Only Look Once (YOLO)

[0061] v. Vision Transformers (ViTs) for Object Detection

[0062] C. Evaluation Metrics

[0063] Suitable evaluation metrics include, but are not limited to:

[0064] Intersection over Union (loU).

[0065] Mean Average Precision (mAP)

[0066] Object tracking

[0067] There are two main categories of tracking, which may be implemented:

[0068] i. Traditional Tracking Algorithms

[0069] Suitable traditional tracking algorithms include but are not limited to:

[0070] Kalman Filter.

[0071] Mean-Shift & CAMShift.

[0072] Optical Flow (e.g., Lucas-Kanade method).

[0073] ii. Deep Learning-Based Trackers

[0074] Suitable deep-learning based trackers include but are not limited to:DeepSORT

[0075] Siamese Networks.

[0076] ByteT rack.

[0077] In a preferred implementation, a YOLO model is used for object detection, such as detection of both the user and a ball in real-time. Following detection, the live video stream is automatically segmented, and redundant frames are removed for efficient processing.

[0078] An object trajectory-tracing algorithm is implemented using Optical Flow estimation and Kalman Filtering to create a smooth path representation. The system preferably identifies key data points on the object trajectory that are stored for later analysis.

[0079] In the example of a user bowling or pitching ball, the object trajectory tracing algorithm will trace the trajectory of the ball. Exemplary data points include the ball release point, bounce point, and final impact point (on the wicket line in the example of cricket). Data points may be varied in dependence on the sport being played, as will be readily appreciated.

[0080] Using physics-based motion equations, the model may, for example, calculate the speed of the object (e.g. ball) by determining the distance travelled over time. This is achieved by leveraging high-frame-rate video capture, which may, for example, be 60 frames per second (fps) or more, or 120 frames per second or more. The object’s displacement is accurately measured. The speed may be converted into various localized formats (km / h, mph) depending on the user's preferences.

[0081] The system may also calculate accuracy by monitoring movement of equipment to be impacted by another object, such as stumps to be impacted by a ball in the example of cricket. Such movement may be monitored using a CNNbased change detection model. Noting the discussion above, if such equipment, such as cricket stumps, is unavailable, virtual equipment may be generated usingaugmented reality, and impact points may be measured against such digital markers to determine accuracy scores.

[0082] By integrating these techniques, the system is able to offers a comprehensive analysis of sporting performance, providing valuable insights for skill improvement.

[0083] The system is preferably configured to ensure consistency in data collection.

[0084] The application may provide the user with instructions / visual cues for the setting up of their device for the recording of any desired activity.

[0085] The instructions may include guidance to fix the camera of their device at a specified height from the ground. Such height may, for example, be 1 metre above the ground. The appropriate positioning of the user device may be achieved, for example, by use of a tripod. The application may be configured to use accelerometer and / or gyroscope data, when available, to validate stability of the user device, and may prevent recording of an activity in absence of suitably detected stability.

[0086] The instructions may additionally / alternatively include guidance to set the user device in a specific orientation with respect to the area of the activity to be recorded. Relevant ground / pitch markings or items of equipment may require alignment with appropriate bounding boxes or alternative visual markers presented on the screen of the user device. In such case, computer vision techniques, such as but not limited to, edge detection and perspective transformation, may be used to identify and position the markings and / or equipment accurately.

[0087] Alternatively, in absence of available physical markings / equipment, the application may be configured to render these for display on the screen of the device using augmented reality. This allows alignment with any physical object to be used as an appropriately located marker, such as an item of clothing placed on the ground. In the example of cricket, a user may place an item, such as a jumper, on the ground in the appropriate location, with a “digital wicket” generated for the user.The path of the ball can then be tracked with respect to the digital wicket. Alternative equipment may, of course, be rendered in augmented reality for other sports.

[0088] Additionally, or alternatively, in dependence on the activity to be recorded, the user may select parameters to be mapped using a visual indicator on the screen, which may comprise a guideline or otherwise, enabling the user to adjust actions based on their training environment. In the example of cricket, the user could, by way of example only, select the length of their run up with this mapped using visual indicators.

[0089] With reference to Figures 2A and 2B, an example of the analysis of video footage from a user is considered, by way of example only, in the context of cricket.

[0090] A user in the present example, is tracking their bowling. They have their smartphone setup on a tripod at the end of the wicket facing the batsman.

[0091] Figure 2A shows a video frame with the batsman ready to receive a ball. It can be seen that the stumps and crease have been identified, using a suitable object detection model, and are bounded with bounding boxes 3, 4, respectively.

[0092] Figure 2B shows a later video frame in which the ball has been bowled by the user, the ball having been detected in the frames of the video, again using a suitable object detection model, with its movement tracked using a suitable tracking algorithm. Analysis of the ball is shown in the top right of the image, wherein the accuracy reflects the determination that the ball would have impacted the stumps, and the determined ball speed is shown. The data points in this example, in line with the discussion above, comprise the ball release point (hidden from view by the analysis box), the bounce point, and the final impact point, as seen.

[0093] In line with the discussion above, the bowler may be required to look to the camera to be authenticated using facial recognition. There may be the requirement that the user looks to the camera before and / or after bowling.Figure 3 shows a sample screenshot of a user’s phone, which, by way of example only, shows the tracked recorded progress of the user’s bowling speed over time.

[0094] As must be appreciated, various metrics may be tracked, across numerous sports. Further consideration will be given below to the use of the system in the context of cricket. It should, however, be appreciated that this is purely exemplary, and should not be seen as limiting.

[0095] The system provides users with the ability to comprehensively track their performance in a sport.

[0096] • Metrics: Measure performance, such as bowling and batting metrics in the example of cricket, which may comprise speed, spin, accuracy, strike speed, or similar.

[0097] • Data-Driven Insights: Identify strengths and areas for improvement through detailed analytics.

[0098] Accessibility

[0099] • Play Anywhere: Use just a ball and smartphone or tablet to practice and play.

[0100] • Earn Rewards: Improve performance and earn tokens.

[0101] Global Competition

[0102] • Leaderboards: Compete on global leaderboards and participate in challenges.

[0103] • Engagement: Interact with current and former professional sportspeople.

[0104] Expert Coaching Insights

[0105] • Professional Tips: Receive training updates and tips from professional sportspeople.Community Engagement

[0106] Forums: Connect with other sports enthusiasts through forums.

[0107] Marketplace: Access eguipment offers and exclusive merchandise.

[0108] The system may further enhance the user experience by implementing additional features on top of the object detection and tracking features discussed above. The system preferably provides an interactive platform that combines gamification, and cryptocurrency rewards alongside the performance tracking to create a dynamic and engaging ecosystem for sports enthusiasts.

[0109] As has been discussed, users may compete against one another. The application preferably leverages Al-driven gamification to ensure a fair and engaging competitive experience. In such case, a reinforcement learning model may be implemented for continuously evaluating player performance across multiple performance parameters, which performance parameters will vary in dependence on the sport / activity in which players are competing. For example, in cricket, the performance parameters for competing bowlers may include one or more of bowling accuracy, speed, spin variation, and consistency. The performance parameters / metrics may be used to categorize users into dynamically adjusting skill tiers.

[0110] To maintain balanced gameplay, a matchmaking algorithm based on an Elo rating system may be implemented. The system uses historical performance data, weighted rolling averages, and Bayesian inference to predict the probable outcome of matchups. Players are paired with opponents of similar skill levels, ensuring competitive integrity while preventing unfair advantages.

[0111] Additionally, the Al may introduce controlled randomization through procedural content generation. This includes dynamically adjusting environmental factors, such as wind simulation and pitch conditions, to create varied playing experiences without disrupting fairness. The system may also adapt difficulty curvesbased on user performance trends, reinforcing a structured progression model that maintains engagement while minimizing skill gaps.

[0112] Furthermore, Al-based anomaly detection algorithms may be implemented to monitor gameplay patterns to identify irregularities, such as inconsistent performance spikes that may indicate unfair play or external assistance. If anomalies are detected, the system may trigger verification protocols, including facial recognition re-authentication or additional challenge-based assessments.

[0113] By integrating these Al methodologies, the application ensures a skill-based, engaging, and fair gaming ecosystem that adapts to player proficiency while promoting continuous improvement and competitiveness.

[0114] Gamification and rewards features may include the provision of in-application cryptocurrency tokens, which may be earned by practicing, improving skills, and participating in challenges, or may be purchased through the application. Such tokens may be used for in-application purchases, upgrades, and entering competitions.

[0115] Gamification

[0116] • Tokens: Earn and use tokens for rewards, upgrades, and competitions. • Avatars: Create personalized avatars and track progress on local and global rankings.

[0117] Example games, in the exemplary context of cricket, may comprise one or more of the following:

[0118] 1. Wide Ball - “Missed it!”

[0119] • Graphic / Effect: When a wide ball is bowled, an animated graphic appears showing the ball veering off course, perhaps with a comical “miss” effect, like a cricket bat wildly swiping at thin air.

[0120] • Sound: A humorous “whoops!” or buzzer sound effect to signify the mistake.• Message: “Whoops! Wide! Try to keep it in the lines!” or “You went wide — let’s reel it in next time!”

[0121] 2. Middle Stump Wicket - “Stump Celebration!”

[0122] • Graphic / Effect: When the middle stump is bowled out, fireworks explode around the stumps, and a sparkling crown is placed on top of the stump.

[0123] • Sound: A cheering crowd sound followed by a loud “Kaboom!” sound of fireworks.

[0124] • Message: “Middle stump down! The king of the crease!” or “Wicket! You’ve knocked the crown off the king!”

[0125] 3. Perfect Yorker - “Bowling Master!”

[0126] • Graphic / Effect: A glowing golden ball swoops in with a trail of light to hit the target perfectly.

[0127] • Sound: A deep, powerful “whoosh” sound followed by an epic “Perfect Yorker!” voiceover.

[0128] • Message: “That’s a brilliant Yorker! Precision at its finest!” or “A perfect Yorker — bowling genius!”

[0129] 4. Dot Ball - “Steady Bowler!”

[0130] • Graphic / Effect: After a dot ball, the screen could briefly show a calm, zen-like figure, possibly a bowler meditating or calmly adjusting their cap to signify focus.

[0131] • Sound: A peaceful “ding” or wind chime sound to suggest calm concentration.

[0132] • Message: “Dot ball! Solid bowling, keep up the pressure!” or “Nice and tight — let’s keep it going!”

[0133] 5. No Ball - “Foot Fault!”

[0134] • Graphic / Effect: When a no-ball is bowled, an animated referee with a red card or a cricket umpire shakes their head disapprovingly.

[0135] • Sound: A referee’s whistle followed by the voice “No Ball!” with a lighthearted tone.

[0136] • Message: “Oops! Foot fault — try again!” or “No ball! Keep that front foot in check!”6. Fast Ball - “Speedster!”

[0137] • Graphic / Effect: For particularly fast deliveries, speed lines appear behind the ball, with a flash effect to emphasize the pace.

[0138] • Sound: A high-speed “whoosh” as the ball is released, followed by a voiceover: “Fast ball!” or “You’re a speedster!”

[0139] • Message: “Blazing fast! That one had pace!” or “Lightning speed on that delivery!”

[0140] 7. Spin Ball - “Twist and Turn!”

[0141] • Graphic / Effect: The ball could spin with a vibrant swirl effect, showing the movement of the ball in the air.

[0142] • Sound: A whooshing sound, followed by a “spin” sound effect, like a rapid twirl.

[0143] • Message: “Spin sensation! That ball’s got some serious turn!” or “That’s a wicked spin!”

[0144] 8. Bowler’s Streak - “Consistency King!”

[0145] • Graphic / Effect: When the bowler delivers a series of successful balls (e.g., no wides, no no-balls), a special trophy or streak icon appears at the top of the screen.

[0146] • Sound: A cheerful, upbeat melody plays as the streak continues.

[0147] • Message: “You’re on fire! Keep the streak going!” or “Streak intact! Consistency is key!”

[0148] 9. Batsman Duck - “Close Call!”

[0149] • Graphic / Effect: When the bowler narrowly misses hitting the stumps, the batsman could perform a dramatic ducking motion, with a cartoon-like “whoosh” sound.

[0150] • Sound: A high-pitched “woosh” as the ball narrowly misses.

[0151] • Message: “That was close! Almost had you there!” or “Lucky escape, try again!”

[0152] 10. Hat Trick- “Bowler’s Legend!”• Graphic / Effect: After a hat-trick, a special celebration screen would pop up with confetti, flashing lights, and a cricket bat spinning.

[0153] • Sound: Roaring crowd noise followed by “Hat trick! Bowling legend!” or “Three wickets in a row — legendary stuff!”

[0154] Numerous variations and alternatives will be readily conceived, both within the context of cricket and more widely, particularly with respect to other sports.

[0155] Additional, possible features include, but are not limited to:

[0156] • Personalized Celebration Animations: Users can unlock and select their favourite celebration animations, such as fireworks, gold coins, or a “bowler’s dance move” after a perfect ball.

[0157] • Skill Milestones: Achievements like bowling a first perfect Yorker or hitting a target area with a certain number of balls may unlock new celebratory animations, avatars, or bowling gear.

[0158] • Challenge Mode: Time-limited challenges where players need to bowl a series of specific deliveries (e.g., three Yorkers in a row) to unlock rewards like new animations or sounds.

[0159] • Trophy Room: A virtual “trophy room” where players can view their achievements, such as “Perfect Yorker King,” “Spin Master,” or “Fast Baller.”

[0160] Benefits

[0161] • Increased Engagement: Gamified elements make the experience more interactive and rewarding, encouraging users to return for more practice.

[0162] • Fun and Motivation: Humorous animations and sounds make learning more enjoyable, turning mistakes into opportunities for fun.

[0163] • Higher Retention Rates: New challenges and rewards tied to progression keep users engaged and motivated to improve their bowling skills.

[0164] Demographics and User BaseThe application is designed to cater to a diverse and global user base, encompassing a wide range of demographics.

[0165] The application appeals to various age groups, each with unique needs and interests. Professional athletes, typically aged 20-35, seek advanced analytics and professional coaching tools to enhance their performance. Club players, ranging from 18-40 years old, are passionate about sport and look for ways to refine their techniques and receive feedback. Hobby players, who enjoy sport as a recreational activity, appreciate the application's easy-to-use features, gamified experiences, and social connectivity. Young aspiring players, aged 10-18, benefit from the application’s educational tools, motivational rewards, and opportunities to learn from professionals.

[0166] Token

[0167] The cryptocurrency token is preferably an Ethereum Virtual Machine (EVM) compatible ERC-20 token natively issued on the Vanar Blockchain (https: / / vanarchain.com). However, as will be readily appreciated by those skilled in the art, the token need not be limited as such.

[0168] Token Utility Overview

[0169] The use of the cryptocurreny token within the application, enhances the user experience by providing various utilities within the application.

[0170] Some non-limiting potential utilities of the token, include but are not limited to:

[0171] 1. Leaderboard Competitions (Pay to Play)

[0172] Players can pay using tokens to enter leaderboard competitions where they compete against other players. The top performers will be rewarded with additional tokens, fostering a competitive environment and encouraging skill improvement.2. Performance Rewards

[0173] Tokens will be awarded to players for outstanding performances. This incentivizes players to improve their skills and track their progress using the app.

[0174] 3. Competitions and Tournaments

[0175] Players can use tokens to enter special competitions and tournaments. These events will offer significant rewards and recognition, providing an additional layer of excitement and engagement.

[0176] 4. Merchandise Purchases and Discounts

[0177] Tokens can be used to enter a gamified marketplace where players compete to win exclusive merchandise and in application power ups. Players are guaranteed products by entering, with further exclusive prizes being awarded to entrants using algorithm-based competitions based on player performance. Access to further high-quality equipment is available through engagement and player statistics.

[0178] 5. Access to VIP Events

[0179] Tokens will grant players access to VIP events, such as meet-and-greets with professional sportsmen, exclusive training sessions, and other special events. This utility adds a unique value proposition, enhancing the overall user experience.

[0180] 6. In-App Purchases

[0181] Players can use tokens for various in-application purchases, such as unlocking advanced features, accessing premium content, and customizing their profiles. This provides a seamless and integrated way to enhance the application experience.

[0182] 7. Staking and Earning

[0183] Players can stake their tokens to earn additional rewards over time. This encourages long-term engagement and loyalty, as players benefit from holding and using their tokens within the application ecosystem.8. Community Voting

[0184] Token holders will have the ability to participate in community voting on application features, updates, and new content. This ensures that the development of the app is aligned with the preferences and needs of its users.

[0185] Numerous alternative arrangements and modifications to the embodiments as described herein will be readily appreciated by those skilled in the art within the scope of the appended claims. In particular, features of the described embodiments may be readily combined.

[0186] When used in this specification and claims, the terms "comprises" and "comprising" and variations thereof mean that the specified features, steps or integers are included. The terms are not to be interpreted to exclude the presence of other features, steps or components.

[0187] The features disclosed in the foregoing description, or the following claims, or the accompanying drawings, expressed in their specific forms or in terms of a means for performing the disclosed function, or a method or process for attaining the disclosed result, as appropriate, may, separately, or in any combination of such features, be utilised for realising the invention in diverse forms thereof.

[0188] Although certain example embodiments of the invention have been described, the scope of the appended claims is not intended to be limited solely to these embodiments. The claims are to be construed literally, purposively, and / or to encompass equivalents.

Claims

Claims1. A system for performance tracking, comprising:a plurality of user devices, each user device comprising a processor, a wireless communication module, a camera for capturing video footage, and a memory storing an application;a server communicatively coupled to the plurality of devices via a wireless network; anda plurality of user profiles associated with respective users of the plurality of user devices;wherein the application is configured to enable users to capture video footage, andwherein the server is configured to detect and analyse the location and / or movement of one or more objects within the video footage received from a respective user and return data derived from the analysis to that user through the application.

2. A system as claimed in Claim 1 , wherein the one or more objects comprise a sports ball.

3. A system as claimed in Claim 1 or 2, wherein the one or more objects comprise a movable piece of sports equipment and / or the user’s body.

4. A system as claimed in any preceding claim, wherein the one or more objects comprise a fixed piece of sports equipment.

5. A system as claimed in any preceding claim, wherein the application is configured to enable users to interact with one another via the server by exchanging data associated with the user profiles, wherein the exchanged data includes the data derived from the analysis of the video footage.

6. A system as claimed in Claim 5, wherein the application is configured to rank the users against one another within the application on the basis of a comparison of the exchanged data.

7. A system as claimed in any preceding claim, wherein the application comprises a matchmaking algorithm for pairing users of similar skill level for competition against one another.

8. A system as claimed in Claim 7, wherein the matchmaking algorithm uses historical data derived from the analysis of the video footage as an input, for predicting the probable outcome of competitive pairings.

9. A system as claimed in any preceding claim, wherein the application is configured to allow for the exchange of cryptocurrency tokens between users via the server.

10. A system as claimed in any preceding claim, wherein each user profile comprises biometric data for the respective user.

11. A system as claimed in Claim 10, wherein the server is configured to authorise the data derived from the captured video footage using the biometric data.

12. A system as claimed in Claim 11 , wherein the biometric data comprises facial recognition, and the server is configured to authorise the data only when the respective user is identified in the respective video footage received by the server.

13. A system as claimed in Claim 12, wherein the server is configured to authorise the data only when the respective user is identified in the respective video footage before and / or after the movement of the object to be analysed.

14. A system as claimed in Claim 12 or 13, wherein the server is configured to authorise the captured footage only when the respective user is determined not to have left the field of view of the camera during capture.

15. A system as claimed in any preceding claim, wherein the application comprises an anomaly detection algorithm for comparing the data derived from theanalysis of the video footage with stored historical data derived from the analysis of the video footage for identifying unexpected performance improvements.

16. A system as claimed in Claim 15, when dependent on any of Claims 11 to 14, wherein the application is configured to require re-confirmation of the user using the biometric data in the event unexpected performance improvements are detected.

17. A system as claimed in any of Claims 11 to 16, when dependent on Claim 5 or 6, wherein the server is configured to restrict the exchange of data to authorised data.

18. A system as claimed Claim 10 or any claim dependent thereon, wherein the application is configured to continuously monitor for biometric data, and to associate data derived from the analysis of the video footage to the identified user in the video footage.

19. A method for performance tracking, comprising:establishing a wireless connection between a server and a plurality of user devices, each user device comprising a processor, a wireless communication module, a camera for capturing video footage, and a memory storing an application storing user profiles associated with respective users of the plurality of user devices;executing an application to enable users to capture video footage, and detecting and analysing the location and / or movement of one or more objects within the video footage received from a respective user and returning data derived from the analysis to that user through the application.

20. A non-transitory computer-readable medium comprising instructions which, when executed by one or more processors, cause the one or more processors to perform the method according to Claim 19.

21. A server communicatively coupled to a plurality of user devices via a wireless network, wherein the server is configured to: administer an application storing userprofiles associated with respective users of the plurality of user devices; and detect and analyse the location and / or movement of one or more objects within video footage received from a respective user and return data derived from the analysis to that user through the application.

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