AI Being Used in Sports Analytics Today
AI can track much more than just basic stats like goals, assists, and rebounds. Advanced metrics from AI provide a depth insight into how AI is being used in sports analytics today. For example, in soccer, AI might track not only how often a player touches the ball but also the quality of their touches, distance covered at high speed, and contribution to team defense.
Game Outcome Prediction
Some of the most thrilling usages of our AI data analysis in sports include the predictive capability. By considering many factors, like past performance, weather, and even mental state, we can predict the outcome of a game with impressive accuracy. This isn’t just useful for fans or sports betting companies; teams also use these predictions to know how to prepare better for their opponents.
AI in Player Performance Forecasting
Our AI can also become an important predictor of the future performances of a player, using his or her past performance data and development trajectory to chart how he or she is more likely to perform in the future. This enables teams to make better decisions about which players to invest in and how much to offer in contract or transfer fees. For example, AI can predict that a young soccer player, based on his rapid improvement in dribbling and goal-scoring skills, will be a star in a couple of years. That prediction could be made to inform a team’s decision to sign early before its market value goes up astronomically.
