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• catalog abstract ""To real baseball fans, statistics are indispensable, and inextricably tied to understanding and enjoying the game. But how useful are ordinary baseball stats as tools for evaluating a player, choosing a strategy, or predicting a winner?" "In this look at the numbers and the game, Jim Albert and Jay Bennett examine just what we learn, and just what we think we learn, from baseball statistics. The authors consider the key questions every serious fan obsesses about: What is the best way to rate a great hitter? Is there really a fair way to name an MVP? Does anyone have a reasonably accurate way to predict the outcome of a game? How likely is it that some of the game's milestone achievements (e.g., Mark McGuire's single-season home run record) will be broken?" "By incorporating the seldom-used statistical techniques of probability, the authors come to some original and surprising conclusions: It turns out, for example, that the phenomenon of "streakiness" (a hot hand, a hot bat) is measurable and can serve as a very useful predictor of performance. Conversely, they find that a lot of situational statistics (home versus away games, play on artificial turf versus grass) are, statistically speaking, little more than "noise." And, in news that will bring consolation to Cubs and Red Sox fans, they declare that it's not always the best team that wins the World Series." "Keeping the mathematics at an accessible level, Albert and Bennett show that statistics is not just a powerful tool of analysis and prediction, but a pleasurable and informative pastime in its own right."--Jacket.".
• catalog contributor b12170130.
• catalog contributor b12170131.
• catalog created "2001.".
• catalog date "2001".
• catalog date "2001.".
• catalog dateCopyrighted "2001.".
• catalog description ""By incorporating the seldom-used statistical techniques of probability, the authors come to some original and surprising conclusions: It turns out, for example, that the phenomenon of "streakiness" (a hot hand, a hot bat) is measurable and can serve as a very useful predictor of performance. Conversely, they find that a lot of situational statistics (home versus away games, play on artificial turf versus grass) are, statistically speaking, little more than "noise." And, in news that will bring consolation to Cubs and Red Sox fans, they declare that it's not always the best team that wins the World Series."".
• catalog description ""Keeping the mathematics at an accessible level, Albert and Bennett show that statistics is not just a powerful tool of analysis and prediction, but a pleasurable and informative pastime in its own right."--Jacket.".
• catalog description ""To real baseball fans, statistics are indispensable, and inextricably tied to understanding and enjoying the game. But how useful are ordinary baseball stats as tools for evaluating a player, choosing a strategy, or predicting a winner?" "In this look at the numbers and the game, Jim Albert and Jay Bennett examine just what we learn, and just what we think we learn, from baseball statistics. The authors consider the key questions every serious fan obsesses about: What is the best way to rate a great hitter? Is there really a fair way to name an MVP? Does anyone have a reasonably accurate way to predict the outcome of a game? How likely is it that some of the game's milestone achievements (e.g., Mark McGuire's single-season home run record) will be broken?"".
• catalog description "Includes bibliographical references (pages 347-150).".
• catalog description "Simple Models from Tabletop Baseball Games -- All-Star Baseball (ASB) -- Model Assumptions of All-Star Baseball -- The APBA Model: Introducing the Pitcher -- Strat-O-Matic Baseball: The Independent Model -- Sports Illustrated Baseball: The Interactive Model -- Which Model Is Best? -- Exploring Baseball Data -- Exploring Hitting Data -- A Batch of On-Base Percentages -- Simple Graphs -- Typical Values--the Mean and the Median -- Measures of Spread--Quartiles and the Standard Deviation -- Interesting Values -- Comparing Groups -- A Five-Number Summary -- A Boxplot -- Boxplots to Compare Groups -- OBPs of Offensive and Defensive Players -- Relationships Between Batting Measures -- Relating OBP and SLG -- Relating OBP and Isolated Power -- What about Pitching Data? -- Strikeouts and Walks -- Looking at Strikeout Totals -- Defining a Strikeout Rate -- Comparing Strikeout Rates of Starters and Relievers -- Association Between Strikeouts and Walks? -- Exploring Walk Rates -- Comparing Walk Rates of Starters and Relievers -- Introducing Probability -- Beyond Data Analysis -- Looking for Real Effects -- Predicting OBPs -- Probability Models -- A Coin-Toss Model -- Observed and True OBPs -- Learning about Batting Ability -- Estimating Batting Ability Using a Confidence Interval -- Comparing Hitters -- Situational Effects -- Surveying the Situation -- Looking for Real Effects -- Observed and True Batting Averages -- Batting Averages of the 1998 Regulars -- Two Models for Batting Averages -- A .276 Spinner Model.".
• catalog extent "xviii, 350 p. :".
• catalog identifier "0387988165 (alk. paper)".
• catalog issued "2001".
• catalog issued "2001.".
• catalog language "eng".
• catalog publisher "New York : Copernicus,".
• catalog subject "796.357/01/5195 21".
• catalog subject "Baseball Statistics.".
• catalog subject "GV877 .A46 2001".
• catalog tableOfContents "Simple Models from Tabletop Baseball Games -- All-Star Baseball (ASB) -- Model Assumptions of All-Star Baseball -- The APBA Model: Introducing the Pitcher -- Strat-O-Matic Baseball: The Independent Model -- Sports Illustrated Baseball: The Interactive Model -- Which Model Is Best? -- Exploring Baseball Data -- Exploring Hitting Data -- A Batch of On-Base Percentages -- Simple Graphs -- Typical Values--the Mean and the Median -- Measures of Spread--Quartiles and the Standard Deviation -- Interesting Values -- Comparing Groups -- A Five-Number Summary -- A Boxplot -- Boxplots to Compare Groups -- OBPs of Offensive and Defensive Players -- Relationships Between Batting Measures -- Relating OBP and SLG -- Relating OBP and Isolated Power -- What about Pitching Data? -- Strikeouts and Walks -- Looking at Strikeout Totals -- Defining a Strikeout Rate -- Comparing Strikeout Rates of Starters and Relievers -- Association Between Strikeouts and Walks? -- Exploring Walk Rates -- Comparing Walk Rates of Starters and Relievers -- Introducing Probability -- Beyond Data Analysis -- Looking for Real Effects -- Predicting OBPs -- Probability Models -- A Coin-Toss Model -- Observed and True OBPs -- Learning about Batting Ability -- Estimating Batting Ability Using a Confidence Interval -- Comparing Hitters -- Situational Effects -- Surveying the Situation -- Looking for Real Effects -- Observed and True Batting Averages -- Batting Averages of the 1998 Regulars -- Two Models for Batting Averages -- A .276 Spinner Model.".
• catalog title "Curve ball : baseball, statistics, and the role of chance in the game / Jim Albert, Jay M. Bennett.".
• catalog type "Statistics. fast".
• catalog type "text".