Sports Analytics and Data Science: Winning the Game with Methods and Models (FT Press Analytics)

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Sports activities Analytics and Data Technology may be the most available and practical guideline to sports activities analytics for everybody who cares about earning and everyone who’s interested in data technology. Miller, faculty director of Northwestern University’s pioneering Predictive Analytics program, displays how exactly to use advanced procedures of individual and group performance to guage the competitive placement of both individual sports athletes and teams, also to make even more accurate predictions on the subject of their future overall performance. You’ll get better at the discipline through reasonable sports activities vignettes and intuitive data visualizations—not complex mathematics.

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Thomas W. Miller illustrates them through reasonable case studies, with completely worked good examples in both R and Python.

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Every chapter targets one key sports activities analytics application. Miller manuals you through assessing players and groups, predicting ratings and making game-time decisions, crafting brands and advertising messages, increasing income and profitability, plus much more. Step-by-step, you’ll understand how analysts transform natural data and analytical versions into wins : both on the field and in virtually any sports activities business.

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Whether you’re a group executive, coach, lover, fantasy participant, or data scientist, this information is a powerful way to obtain competitive benefit… in virtually any sport, by any measure.ftpress.

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This exceptionally complete and practical guideline to sports data technology and modeling teaches through practical examples from sports activities industry economics, marketing, administration, performance measurement, and competitive evaluation.

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Thomas W.

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You’ll learn how successful sports activities analytics blends business and sports activities savvy, modern it, and sophisticated modeling methods.

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Miller’s modeling methods draw on strategies from economics, accounting, financing, classical and Bayesian figures, machine learning, simulation, and mathematical programming. Miller, head of Northwestern University’s pioneering system in predictive analytics, manuals you through defining complications, determining data, crafting and optimizing versions, composing effective R and Python code, interpreting your outcomes, and even more.

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Sports activities Analytics and Data Technology will be a great reference for everyone who would like to significantly investigate and even more accurately predict player, group, and sports business functionality, which includes students, teachers, sports activities analysts, sports supporters, trainers, coaches, and group and sports activities business managers. It will be beneficial to all learners of analytics and data technology who would like to build their abilities through familiar and available sports activities applications

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• Understanding sports marketplaces
• Assessing players
• Ranking groups
• Predicting ratings
• Making game day time decisions
• Crafting marketing text messages
• Promoting brands and items
• Developing revenues
• Managing budget
• Playing what-if video games
• Plus much more

See also

• Marketing Data Science: Modeling Techniques in Predictive Analytics with R and Python (FT Press Analytics)
• Business Analytics Principles, Concepts, and Applications with SAS: What, Why, and How (FT Press Analytics)
• Optimization in Operations Research (2nd Edition)