Project
| # | Title | Team Members | TA | Documents | Sponsor |
|---|---|---|---|---|---|
| 54 | Soccer Team Gameplay Metrics |
Regis Lato Shixing Ma Yi Rui Zhao |
Dongwei Shi | design_document1.pdf final_paper1.pdf other1.pdf proposal1.pdf |
Micron |
| # Problem Current smart soccer balls only measure ball speed and spin after a stationary shot. There are also gps chips that measure player location during the duration of a match. Also there are apps that allow coaches to manually enter player data as completed passes, shots on goal, completed dribbles etc. All of this data is not readily available from an automatic system. There has to be a human recording each touch of the ball to calculate completed passes. We aim to combine all these features into one system. # Solution Overview We want to build a system that is able to measure metrics for individual players over the duration of a soccer game. The metrics that we aim to gather include data like: Passes between player A and B (by knowing when two players of the same team touch the ball consecutively). Bad passes (in the next ball touch is by an opposing player). Longest string of dribbles(the most consecutive touches of the ball by one player), time of possession (continuous time until an opposing player touch is recorded) Because we don’t want players to be carrying heavy electronics around during the game, we will be integrating all the electronics inside the ball. The only additional thing players will have is a lightweight, paper-thin RFID tag sticker in their cleats. Instead of messing around with an actual soccer ball, we will be using a high density foam ball that can be easily manipulated to fit the necessary sensors inside. # Solution Components ## Sensor Subsystems To achieve this, we will use a accelerometer, gyroscope and an RFID reader to be able to measure the necessary data. The accelerometer and gyroscope will be able to tell us if the ball is in motion or not and what is the spin and speed of the ball. We can achieve this by using an IMU (inertial measurement unit) which combines the two sensors into one chip and provides 2 to 9 degrees of freedom based on the selected chip. The accelerometer should be in the rage of ±4g(higher value would increase accuracy), the MPU 6050 could be a good option. The RFID reader paired with RFID tags on the player will be used to tell us the specific player that is or has been in contact with the ball. The RFID reader selection will be determined based on the power draw, read range, and the read time (<8.3ms, based on the foot to ball contact time). ## Processing Subsystem We will use a SoC microcontroller with wifi and bluetooth capabilities (such as the ESP32) to process data received by the sensors and to send it to a cloud database or a computer nearby. The microcontroller only needs enough processing power to read and send out sensor data. The actual data parsing will be done by an external computer. ## Power Subsystem The ball cannot be wired during a game, so we will use a rechargeable lithium ion battery to power the system. We aim to have the ball last at least a quarter of a soccer match (~22.5 minutes). We will try to use the smallest battery required to meet this goal to minimize the weight of the ball. Since wireless charging is likely too complicated for this project, our charging system will be wired. ## Backend Data Processing We will build a mobile app or web app to parse and display desired metrics for players or the team. # Criterion for Success Our baseline goal will be to have somewhat kickable ball that can detect and differentiate players that have been in contact with it. With that data we should be able to compute and display individual metrics as described above. |
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