
스포츠
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.
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.
AI와 스포츠
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.
선수 성적
- 향후 성적 예측을 통한 드래프트 결정 지원
- 현재 가치와 위험을 파악하여 계약할 선수 결정
- 트레이드 옵션 평가
- 적합한 목표 제안
- 선수와 코치에게 피드백을 제공하여 선수 역량 개발
- 부상 예측 및 예방
티켓 구매
- 이탈 가능성이 높은 시즌 티켓 보유자 및 이유 예측
- 잠재적 시즌 티켓 구매자 식별
- 최적 가격 티켓
- 티켓 판매 / 참석 예측
- VIP 좌석 판매 최적화
경기 전략
- 팀의 초기 라인업 최적화
- 방어 포지셔닝을 포함한 최적의 경기 전략 결정
- 상대 선수에 대한 대응 전략 파악
- 실시간 경기를 기반으로 한 전략 실행 및 개선

분석 과제
With AI and machine learning 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.
DataRobot의 지원

DataRobot과 함께 AI 기업 이니셔티브를 시작하십시오.