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Sports
Score Big with AI and Machine Learning
Professional sports organizations once viewed data and analytics as having the potential to deliver an informational edge over the competition. Today, sports analytics data science is table stakes. These organizations need to go beyond simply using data to make decisions and execute on new ideas faster than the competition, enabling their people to take the best action at the right time.
Learn how Enterprise AI is changing the game.
AI in Sports
Sporting organizations have mountains of raw data, with more becoming available all the time. This information can now be used to drive value across all aspects of their organization from selling more tickets to preventing injuries in players. DataRobot enables these organizations to combine AI, machine learning, and sports to power insights and decisions both on and off the field.
Player Performance
- Support draft decisions with future performance predictions
- Decide which players to sign by understanding their present value and risk
- Evaluate trade options
- Precisely target offers
- Enhance player development by providing feedback to players and coaches
- Predict and prevent injuries
Ticketing
- Predict which season ticket holders are likely to churn and why
- Identify potential season ticket holders
- Optimally price tickets
- Forecast ticket sales/attendance
- Optimize suite sales
In-Game Strategy
- Optimize a team’s starting lineup
- Determine optimal game strategy, including defensive positioning
- Understand how to counteract your opponent
- Execute and refine your strategy based on real-time events
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AI Use Cases in Sports
With machine learning and AI in sports applications, organizations can use their data to improve every area of their operations. From player recruitment and performance to ticket sales, predictive analytics can help make targeted decisions and strategic changes that impact every area of a sports organization.
Check out more AI use cases in SportsDataRobot Can Help You With:
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