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Artificial Intelligence in Athletics
- 1. Artificial Intelligence in Sports Cammy Case and Brian Ford
- 2. Overview of Artificial Intelligence ● Computers ● Analysis ● Data ● Man-made
- 3. Artificial Intelligence In Sports ● Used in data and statistics ○ Wearables ○ Safety ○ Identifying mentally tough ○ Broadcasting
- 4. Prior to Artificial Intelligence ● Statistics and data done by hand ○ Room for human error
- 5. Artificial Intelligence in Sports Now ● Tennis ● Baseball ● Football ● Volleyball
- 6. Tennis ● Babolat Tennis Racquet ● Computer version referee ○ in/out ○ speed & placement
- 7. Baseball ● Zepp ○ Swing analysis ● Automated Journalism
- 8. Football ● Cybersecurity software ● In-helmet sensors ● Broadcasting
- 9. Volleyball ● Hudl ○ Video analysis software
- 10. Potential for Future ● IBM automated highlight reels ○ Wimbledon ● Assistant coach
Editor's Notes
- Brian - the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.
- Primarily used in data and statistics Wearables - football or baseball Players put sensors in equipment Gyroscopes that track movements and record them Safety - NFL helmet sensors - identify concussions Identifying mentally tough - baseball & nfl Track reaction time and other things: Cognitive function Reactions to different situations - measure anger levels The most common use of AI in sports is in broadcasting Broadcasters are providing things for TV audiences to inform them of certain statistics Basketball - track players movements - runs, shots from a certain region Baseball - track launch angle of ball, how fast ball comes off bat
- Brian - data and stats recorded by hand that involved a team of people to accomplish Usually took hours even days to compute some of the stats Some of the data that we see today didn’t exist 20 years ago because there was no means of recording it ex. Launch angle in baseball This left plenty of room for human error that could have made a difference in what they were trying to accomplish at the time.
- AI is becoming more popular in sports today Examples that we will discuss: Tennis Baseball Football Volleyball
- In Digital to the Core we learned about the Babolat Tennis Racquet Digitally captures a players forehand, backhand, smash, serve Racquet contains accelerometer & gyroscope sensors, digital microprocessor, Bluetooth wireless communications and battery Gives players feedback of what they are doing correctly or incorrectly Babolat tennis racquet changed the rules of tennis by allowing sensors to be used in racquets during matches Sensors at net and around court that are able to judge whether a ball is in or out If referee missed call, can be challenged Sensors can determine the speed of serves
- Brian - Zepp is a motion sensor that is attached to the knob of a baseball bat and act very similar to what the babolat tennis sensors capture Wirelessly track launch angle, hand speed, time to impact, attack angle, bat speed impact and 3d swing analysis Used in practice however not legal in games YET Automated Journalism uses A.I to boost publicity for minor league baseball Uses a series of algorithms to produce and create content for minor league teams such as live stats, post and pre game analysis, and center focus on a specific player
- Casinos in Vegas use cybersecurity software to monitor who comes in, can track where eyes are looking, some can track heart rate Used to monitor if anyone is cheating or stealing from casino Can monitor potential threats Some football stadiums have implemented cybersecurity software to monitor the same things of fans in attendance Helmet sensors can monitor impact of hits Pounds of force that go into helmet to indicate a potential concussion to on-field trainers Monitor location of where the hit was on the helmet Monitor duration - how long impact was Monitor rotation and linear acceleration of the hit A threshold is determined and if an impact/sequence of impacts exceeds this threshold, then it is transferred to the alert monitor to the on-field trainers Broadcasting: Tracks passing yards Top left is weeks 1-5 Top right is weeks 1-17 (whole season) Bottom right is monitoring where receiver caught ball and then scored a touchdown Bottom left is rushing yards for entire season
- Brian - We use Hudl which is a video analysis software which track player movement on both teams. In this pic I want to look at my kills from the game so I am able to do so with the filter settings We also use this for film on other teams and track what they do in the games that we play them before games
- Brian - This coming summer IBM is going to implement automated highlight reels They are able to create templates and insert video clips in which exceed accelerometers that are positioned on the court that would then count as “highlight plays” or it can be manually entered from the broadcasting team Assistant coaches are something that the NFL and MLB are looking into. Able to store and track plays, players, on both your team and opposing team