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The Change Your Game | Cambia tu juego (formerly Game Changers) project has developed an Inventive Identity Toolkit for wide distribution across the informal science learning (ISL) community. The toolkit is aimed at exhibition designers and informal science educators; it provides practical tips to help visitors explore their inventive identities so they can see themselves as creative problem solvers. The toolkit first offers background on Joanna K. Garner and Avi Kaplan’s theoretical frameworks, the Dynamic Systems Model of Role Identity (DSMRI), and the Visitor Identification and Engagement in STEM (VINES) model. The toolkit then includes design tips for applying the DSMRI-VINES models and encouraging visitors’ inventive identity exploration in unstaffed exhibition galleries. Similarly, the toolkit offers specific facilitation techniques (and associated training exercises) to help educators encourage inventive creativity in informal learning spaces staffed by facilitators. The toolkit also provides a catalog of verbal and behavioral indicators that signify when a visitor has activated their inventive identities; this will help researchers and evaluators measure the efficacy of exhibitions, learning labs, and other informal learning environments that strive to foster these kinds of identity shifts. Finally, the toolkit provides a template for designing public programs and community events around inventiveness in sports. We have shared the Inventive Identity Toolkit with the informal science learning (ISL) community at informalscience.org. 

In this recent history, I describe how the embrace of computational analytics has transformed the management of professional sports in the 21st century. Sports analytics encompasses a set of data management technologies and mathematical techniques for interpreting observable statistical data about athletes and game play to help general managers, coaches, and players make better decisions and attain a competitive advantage. General managers use analytical information to evaluate players for drafting, trades, and contract-salary negotiations. Coaches and players use analytics to understand competitors’ tendencies, develop in-game strategies, and identify areas for training and improvement. Essentially, analytics is the application of “scientific management” (Taylor, 1911) to sports. Accordingly, the paper situates the twenty-first century Moneyball phenomenon (Lewis, 2004) in the context of a much longer history. Drawing on published primary sources and contemporary news coverage, I trace the evolution and gradual professionalization of the sports analytics community, which emerged from an eclectic group of postwar operations researchers, hobbyists, and fringe freelance journalists. I argue that the computational turn in professional sports has created competitive advantages for certain teams and directly influenced players’ in-game strategies. Moreover, this analytical turn has initiated a shift in epistemological authority in the front office. As professional teams have learned to “trust in numbers” (Porter, 1996), they have increasingly rejected the traditional expertise of former players and scouts and let the statisticians and “computer boys” take over (Ensmenger, 2012), albeit with predictable resistance. Advocates suggest that analytics have made the games fairer and leveled the playing field for teams with smaller payrolls. Meanwhile, critics suggest that analytics have turned players into automatons and robbed the games of individual creativity and spontaneity. Dear program committee: This individual paper could fit well in a panel on applied management, sports, computing, innovation, or STS.