Students will launch the ping pong analytics project by participating in a mini “Probability Playoff,” gathering real match data, and conducting firsthand interviews with players and spectators to understand what makes predictions trustworthy and exciting. They will create structured empathy maps grounded in direct quotes and observations to prepare for defining a focused design challenge in the next phase.

Students will synthesize their ping pong tournament user research into a clear, evidence-based problem definition that guides their prediction model design. They will identify patterns across interviews, craft a focused How Might We statement grounded in real quotes, and refine it through structured peer critique before moving into ideation.

Students will generate a wide range of user-centered solution ideas for their ping pong prediction models and analytics booth, then narrow their concepts using evidence from real user needs and statistical goals. By the end of the phase, teams will produce annotated concept sketches that serve as blueprints for prototyping.

Students will build, test, and refine prediction model prototypes for the ping pong tournament, using real user feedback and statistical reasoning to improve clarity, accuracy, and usability before final presentations.

Students will validate their refined ping pong tournament prediction models with new users, analyze additional match data to test long-run relative frequency, and present their full design journey—from user research to final bracket—during the Bracketology Bash.