Analyzing Baseball Data with R,(2/e)

Max Marchi (Author), Jim Albert Benjamin S. Baumer (Author)

  • 出版商: CRC
  • 出版日期: 2018-12-03
  • 售價: $2,200
  • 貴賓價: 9.5$2,090
  • 語言: 英文
  • 頁數: 360
  • ISBN: 0815353510
  • ISBN-13: 9780815353515
  • 相關分類: R 語言
  • 立即出貨 (庫存=1)

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商品描述

Analyzing Baseball Data with R Second Edition introduces R to sabermetricians, baseball enthusiasts, and students interested in exploring the richness of baseball data. It equips you with the necessary skills and software tools to perform all the analysis steps, from importing the data to transforming them into an appropriate format to visualizing the data via graphs to performing a statistical analysis.

 

The authors first present an overview of publicly available baseball datasets and a gentle introduction to the type of data structures and exploratory and data management capabilities of R. They also cover the ggplot2 graphics functions and employ a tidyverse-friendly workflow throughout. Much of the book illustrates the use of R through popular sabermetrics topics, including the Pythagorean formula, runs expectancy, catcher framing, career trajectories, simulation of games and seasons, patterns of streaky behavior of players, and launch angles and exit velocities. All the datasets and R code used in the text are available online.

 

New to the second edition are a systematic adoption of the tidyverse and incorporation of Statcast player tracking data (made available by Baseball Savant). All code from the first edition has been revised according to the principles of the tidyverse. Tidyverse packages, including dplyr, ggplot2, tidyr, purrr, and broom are emphasized throughout the book. Two entirely new chapters are made possible by the availability of Statcast data: one explores the notion of catcher framing ability, and the other uses launch angle and exit velocity to estimate the probability of a home run. Through the book's various examples, you will learn about modern sabermetrics and how to conduct your own baseball analyses.

 

Max Marchi is a Baseball Analytics Analyst for the Cleveland Indians. He was a regular contributor to The Hardball Times and Baseball Prospectus websites and previously consulted for other MLB clubs.

 

Jim Albert is a Distinguished University Professor of statistics at Bowling Green State University. He has authored or coauthored several books including Curve Ball and Visualizing Baseball and was the editor of the Journal of Quantitative Analysis of Sports.

 

Ben Baumer is an assistant professor of statistical & data sciences at Smith College. Previously a statistical analyst for the New York Mets, he is a co-author of The Sabermetric Revolution and Modern Data Science with R.

 

 

商品描述(中文翻譯)

《使用 R 分析棒球數據 第二版》向數據分析棒球的人、棒球愛好者和對探索棒球數據豐富性感興趣的學生介紹了 R。它為您提供了執行所有分析步驟所需的技能和軟件工具,從導入數據到將其轉換為適當格式,再通過圖形將數據可視化,最後進行統計分析。

作者首先概述了公開可用的棒球數據集,並對 R 的數據結構、探索性分析和數據管理能力進行了簡要介紹。他們還介紹了 ggplot2 圖形函數,並在整本書中使用了 tidyverse-friendly 的工作流程。本書的大部分內容都通過流行的 sabermetrics 主題來演示使用 R,包括 Pythagorean 公式、得分期望值、捕手接球、職業生涯軌跡、比賽和賽季模擬、球員連勝連敗行為模式以及發射角度和離場速度。書中使用的所有數據集和 R 代碼都可以在線上找到。

第二版新增了對 tidyverse 的系統採用,並納入了由 Baseball Savant 提供的 Statcast 球員追蹤數據。根據 tidyverse 的原則,第一版的所有代碼都經過了修訂。書中始終強調使用 tidyverse 套件,包括 dplyr、ggplot2、tidyr、purrr 和 broom。由於有了 Statcast 數據的可用性,新增了兩個全新的章節:一個探討捕手接球能力的概念,另一個使用發射角度和離場速度來估計擊出全壘打的概率。通過本書的各種示例,您將學習現代 sabermetrics 和如何進行自己的棒球分析。

Max Marchi 是克利夫蘭印地安人棒球分析師。他曾是《The Hardball Times》和《Baseball Prospectus》網站的常駐撰稿人,並曾為其他 MLB 俱樂部提供咨詢服務。

Jim Albert 是 Bowling Green State University 的統計學杰出教授。他是《Curve Ball》和《Visualizing Baseball》等多本書的作者或合著者,並擔任《Journal of Quantitative Analysis of Sports》的編輯。

Ben Baumer 是史密斯學院統計與數據科學助理教授。他曾是紐約大都會的統計分析師,是《The Sabermetric Revolution》和《Modern Data Science with R》的合著者。