SSAC22: Using Tracking and Charting Data to Better Evaluate NFL Players: A Review

(27:47)

SSAC22: Using Machine Learning to Describe how Players Impact the Game in the MLB

(24:4)

SSAC22: Using Machine Learning to Describe how Players Impact the Game in MLB - Open Source Workshop

(1:13)

SSAC22: Detection of Tactical Patterns Using Semi-Supervised Graph Neural Networks

(24:44)

SSAC22: Using Technology to Monitor Workload in Elite Figure Skating

(27:11)

SSAC22: Using Hex Maps to Classify \u0026 Cluster Dribble Hand-Off Variants in the NBA

(24:27)

SSAC22: In the Trenches of Football Analytics

(51:44)

SSAC22: Main Stage

(5:36:46)

SSAC22: Beyond Expected Goals: Analyzing and Implementing the Next Phase of Soccer Analytics

(1:1:34)

SSAC22: The Evolution of Sports Business: Keeping Up with the Shifting Landscape, Pres. by Wasserman

(1:1:33)

SSAC22 Research Papers Competition. Detection of tactical patterns using semi-supervised

(3:45)

SSAC22: A 1-on-1 with Calvin Johnson and Bomani Jones

(53:33)

SSAC22: NBA Strategy: Leveraging Analytics on In-Game Information Presented by Microsoft

(25:8)

SSAC22 Hackathon Final Presentations

(1:49)

SSAC22: Packing a Punch with Data: How Analytics Have Fueled the UFC

(56:12)

SSAC22: Sports Narrative Enhancement With Natural Language Generation

(26:59)

SSAC22: The Art \u0026 Science of Data Collection: Power Growth, While Delighting Your Fans (Adobe)

(26:38)

SSAC22: Chess Analytics: Winning Moves when the Clock Is Ticking

(26:56)

SSAC22: A Deep Reinforcement Learning Framework for Optimizing Player Decisions in Soccer

(25:9)