Prediction Games Players compete by making predictions about upcoming event/observation in the real world Predictions are scored after event At TAMU, we are exploring their design for data-intensive domains Aim to improve data skills and mental models of domains First, let’s talk about the best known type of prediction game: Fantasy sports 57.4 million players in U.S. & Canada in 2016 Players explore data to play the game

What are Fantasy Sports Players of fantasy sports take on the role of coach Draft actual sport players for team Decide which players draft, trade, and start each week/game Get points based on player statistics History 1962: paper-based fantasy football game 1979: start of Rotisserie baseball Characteristics: Leagues among local friends and colleagues Significant effort of collecting statistics and computing winners Trophies and prizes for winners (and losers)

Fantasy Sport Move Online A natural fit Automatic collection and use of data Easy access for players Early effects Often no knowledge of other players Low consequences leads to low interest Players abandon teams early in season New interfaces aid sense of community League statistics / power ratings League polls / message boards Integrating virtual and real sport news News of injuries, anticipated changes to starting players, and weather forecasts Alongside articles about fantasy teams

Games as Derivative Forms Simple model Real world acts as data source for game engine Model maps data to game Collection of Data from Event Model Mapping Data to Game Context Real-World Event Virtual Event

Examples of Model Examples of prediction games Fantasy stock markets Fantasy SCOTUS Fantasy Congress Streaming or querying data Weather and traffic in racing or other simulation based on real-time conditions Action selection in game based on database of selections recorded in similar conditions

Fantasy Sports Practices Surveyed 160 self-reported fantasy sports players on Mechanical Turk Data source types? How many data features?

Data Analysis & General Activity Players vary regarding tool use Some use only tools in game web site Some use spreadsheets or statistical software Most players reported using a combination of in-game and out-of-game tools Rationale of tool choice Need range of features Convenience User Control Usability Number of interactions with game per week Length of average interaction

Motivations Some expected factors Sports engagement Entertainment Intellectual challenge But open-ended answers focused on social value “it is a way to connect with my father who loves sports and also plays” “to take part in an office activity with coworkers and not look like someone who doesn’t want to participate in social activities in the workplace”

Fantasy Climate: An Evolving Design From predicting weather to predicting change from historic norms

Designing Prediction Games Exploring a Design Space Effects of news and its visualization Effects of alternative modes of communication Alternative data visualizations

Access to Domain-Specific News GeoNews NewsBoard

Use and Effects of News Use during game shows effect on engagement Quality of predictions was better for those with GeoNews (1 = best, 7 = worst)

Alternative Modes of Communication

Use and Lessons of Communication Many more messages in IM But most content was in forum # of players agreed that communication tool increased engagement

Prediction Games Summary Fantasy games have 55 year history 50+ millions of players in US alone 18+ billion dollar industry Connecting the real and digital Using the real world as data for or part of game engine Community, context, and consequence result in engagement Potential for prediction games to encourage the development of data skills and domain understanding