{"product_id":"b0gymg158m","title":"Probabilistic Models for Sports Betting: Mathematical Foundations, Statistical Inference, and Applications Across Sports","description":"\u003cp\u003eSports betting is not primarily about predicting the future—it is about quantifying uncertainty.\u003c\/p\u003e\n\n\u003cp\u003eEvery football match, tennis tournament, horse race, or motorsport event can be viewed as a probabilistic system. The central challenge is to translate sporting performance, randomness, dependence, and incomplete information into meaningful probabilities.\u003c\/p\u003e\n\n\u003cp\u003eProbabilistic Models for Sports Betting  provides a systematic introduction to the mathematical and statistical models used to describe sports events and betting markets. Rather than presenting supposedly guaranteed strategies, the book explains how probabilistic models are constructed, what assumptions they require, how their parameters can be estimated, and when their predictions should—or should not—be trusted.\u003c\/p\u003e\n\n\u003cp\u003eEach method is developed step by step, with mathematical derivations, parameter interpretations, numerical examples, and practical applications across different sports.\u003c\/p\u003e\n\n\u003cp\u003eTopics covered include:\u003c\/p\u003e\n\n\u003cp\u003ePoisson, binomial, negative binomial, geometric, and related count models\u003c\/p\u003e\n\n\u003cp\u003eModels for goals, points, scores, and winning margins\u003c\/p\u003e\n\n\u003cp\u003eExponential, gamma, Weibull, and lognormal time-to-event models\u003c\/p\u003e\n\n\u003cp\u003eSkellam models for score differences\u003c\/p\u003e\n\n\u003cp\u003eDependence between teams, players, and competing events\u003c\/p\u003e\n\n\u003cp\u003eBradley–Terry and paired-comparison models\u003c\/p\u003e\n\n\u003cp\u003eModels for rankings, races, and multi-competitor events\u003c\/p\u003e\n\n\u003cp\u003eBest-of-(n) series and tournament probabilities\u003c\/p\u003e\n\n\u003cp\u003eBayesian modeling and parameter uncertainty\u003c\/p\u003e\n\n\u003cp\u003eParameter estimation, calibration, validation, and backtesting\u003c\/p\u003e\n\n\u003cp\u003eInterpretation of betting odds, expected value, and model risk\u003c\/p\u003e\n\n\u003cp\u003eThe book places particular emphasis on the connection between mathematical theory and real sporting situations. It shows, for example, how goal counts can be derived from scoring processes, how player strengths can be linked to opponent quality, how uncertainty in estimated parameters affects predicted probabilities, and how entire competitions can be simulated from individual event models.\u003c\/p\u003e\n\n\u003cp\u003eThis book is suitable for:\u003c\/p\u003e\n\n\u003cp\u003estudents of mathematics, statistics, data science, and economics\u003c\/p\u003e\n\n\u003cp\u003esports analysts and quantitative researchers\u003c\/p\u003e\n\n\u003cp\u003ePython and machine-learning practitioners\u003c\/p\u003e\n\n\u003cp\u003ebettors who want to understand the mathematics behind probability estimates\u003c\/p\u003e\n\n\u003cp\u003ereaders interested in stochastic modeling and statistical inference\u003c\/p\u003e\n\n\u003cp\u003eNo advanced betting experience is required. Familiarity with basic probability and statistics is helpful, while the detailed derivations allow readers to follow the development of the models step by step.\u003c\/p\u003e\n\n\u003cp\u003eProbabilistic Models for Sports Betting  is not a collection of quick betting tips. It is a rigorous guide to understanding the mathematical structures behind sports outcomes, probabilistic forecasts, and quantitative betting decisions.\u003c\/p\u003e","brand":"ANT","offers":[{"title":"Ebook","offer_id":67924168409333,"sku":"YSL51309","price":7.79,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/8774\/8597\/files\/61y9EfL0UkL._SY1500.jpg?v=1793672498","url":"https:\/\/www.newbooks.store\/products\/b0gymg158m","provider":"NewBooks","version":"1.0","type":"link"}