Chapter 6 Further Reading: Box Score Fundamentals

Annotated Bibliography

This annotated bibliography provides resources for deeper exploration of box score statistics and their interpretation. Resources are organized by category and include academic papers, books, websites, and historical documents.


Foundational Texts

Basketball on Paper: Rules and Tools for Performance Analysis

Author: Dean Oliver Publisher: Potomac Books, 2004 ISBN: 978-1574886887

The seminal work in basketball analytics, Oliver's book established many concepts that remain central to the field. Chapter discussions of individual statistics, team efficiency, and the "Four Factors" provide essential theoretical grounding for understanding box scores in context.

Key Chapters: - Chapter 2: Individual Offensive Rating - Chapter 3: Individual Statistics in Context - Chapter 4: Evaluating Defense

Why Read This: Required reading for anyone serious about basketball analytics. Oliver's framework for understanding possession-based statistics builds directly on box score fundamentals.


Pro Basketball Forecast

Author: John Hollinger Publisher: Potomac Books, 2005 ISBN: 978-1574888904

Hollinger developed Player Efficiency Rating (PER) and Game Score, metrics that synthesize box score statistics into single-number evaluations. This book explains the methodology behind these calculations and their appropriate uses.

Key Contributions: - PER formula derivation and interpretation - Game Score for single-game evaluation - Historical player comparisons using composite metrics

Why Read This: Understanding PER's construction reveals both the power and limitations of box score-based composite metrics.


The Wages of Wins: Taking Measure of the Many Myths in Modern Sport

Authors: David J. Berri, Martin B. Schmidt, Stacey L. Brook Publisher: Stanford Business Books, 2006 ISBN: 978-0804758444

Berri and colleagues developed Wins Produced, an alternative to PER that weights box score statistics differently. The book challenges conventional wisdom about what statistics matter for winning.

Key Arguments: - Shooting efficiency is undervalued relative to scoring volume - Rebounds are highly predictive of team success - Traditional player evaluations often miss what actually matters

Why Read This: Provides alternative perspective on box score interpretation and challenges assumptions built into PER.


Academic Research

"A Starting Point for Analyzing Basketball Statistics"

Authors: Justin Kubatko, Dean Oliver, Kevin Pelton, Dan T. Rosenbaum Journal: Journal of Quantitative Analysis in Sports, Vol. 3, Issue 3, 2007

This foundational paper by four leading basketball analysts establishes terminology and methodology for basketball statistics. Provides rigorous definitions of rate statistics and proper calculation methods.

Topics Covered: - Possession estimation formulas - Individual rating calculations - Proper use of per-minute statistics

Why Read This: Establishes standardized definitions that subsequent research builds upon.


"Measuring Production and Predicting Results in the National Basketball Association"

Author: David J. Berri Journal: Journal of Productivity Analysis, 1999

Early academic treatment of basketball productivity measurement. Berri examines which box score statistics correlate with team wins, finding that shooting efficiency and rebounds matter more than commonly believed.

Key Findings: - Points per shot attempt strongly predicts winning - Rebounding correlates highly with team success - Assists are less predictive than commonly assumed

Why Read This: Academic rigor applied to common box score interpretation questions.


"Who is Most Valuable? Measuring the Player's Production of Wins in the National Basketball Association"

Author: David J. Berri Journal: Managerial and Decision Economics, 2008

Develops and validates Wins Produced metric using box score data. Compares different weighting schemes for combining individual statistics.

Methodological Contributions: - Regression-based weights for box score statistics - Adjustment for position-specific expectations - Validation against team-level outcomes

Why Read This: Demonstrates how to derive statistical weights from data rather than intuition.


Online Resources

Basketball-Reference.com

URL: https://www.basketball-reference.com Type: Statistical Database

The most comprehensive publicly available basketball statistics database. Contains complete box scores for every NBA game since 1946, along with advanced metrics, play indexes, and historical comparisons.

Key Features: - Complete historical statistics - Advanced metric calculations - Play finder and game finder tools - Detailed glossary of terms

Why Use This: Essential resource for accessing box score data and understanding metric calculations.


NBA.com/Stats

URL: https://www.nba.com/stats Type: Official League Statistics

The NBA's official statistics portal provides current season data with tracking metrics not available elsewhere. Includes shot charts, matchup data, and possession statistics.

Key Features: - Official league statistics - Player tracking data - Lineup statistics - Shot chart visualization

Why Use This: Authoritative source for current data; tracking metrics supplement traditional box scores.


Cleaning the Glass

URL: https://cleaningtheglass.com Type: Advanced Statistics Site

Subscription-based site providing cleaned statistical data with garbage time filtered out. Emphasizes proper interpretation and context for statistics.

Key Features: - Garbage time filtering - Lineup and on/off statistics - Historical percentile rankings - Thoughtful context for all numbers

Why Use This: Demonstrates how filtering and context improve box score interpretation.


82games.com

URL: http://www.82games.com Type: Basketball Analysis Site

Long-running basketball analytics site with historical lineup data and unique statistical breakdowns. Archives contain early influential analysis pieces.

Key Features: - Lineup statistics - Player vs. position analysis - Historical articles

Why Use This: Archive of influential early analytics work; unique lineup data.


Historical Resources

"A History of Basketball Statistics"

Publication: Sports Illustrated Archives, Various Years Type: Historical Documentation

Sports Illustrated's archives contain contemporary reporting on statistics evolution, including coverage of when new statistics were introduced and how they were received.

Topics Covered: - Introduction of three-point line - Debates over early composite metrics - Historical perception of statistics

Why Read This: Provides historical context for how basketball statistics were understood in different eras.


NBA Official Records

Publisher: NBA Properties Type: League Documentation

The NBA's official record books document when various statistics were first tracked and provide official league records. Essential for historical research.

Available Information: - First year each statistic was tracked - Official league records by category - Rule changes affecting statistics

Why Consult This: Authoritative source for historical accuracy about statistical tracking.


Advanced Topics

SprawlBall: A Visual Tour of the New Era of the NBA

Author: Kirk Goldsberry Publisher: Houghton Mifflin Harcourt, 2019 ISBN: 978-1328767516

Goldsberry revolutionized basketball visualization through shot charts and spatial analysis. This book explains how shot location data supplements traditional box scores.

Key Contributions: - Shot chart visualization methodology - Analysis of shooting efficiency by location - Historical trends in shot selection

Why Read This: Bridges gap between traditional box scores and spatial data.


"Predicting NBA Player Performance"

Authors: Multiple (MIT Sloan Sports Analytics Conference papers) Source: MIT SSAC Paper Archive URL: http://www.sloansportsconference.com/

The MIT Sloan Sports Analytics Conference publishes papers annually on basketball analytics. Many papers explore limitations of box score metrics and propose improvements.

Sample Relevant Papers: - "Improved NBA Adjusted +/- Using Regularization" (Sill, 2010) - "Possession-Based Player Performance Analysis" (Engelmann, 2017) - "Characterizing the Spatial Structure of Defensive Skill" (2014)

Why Read These: Represents cutting edge of basketball analytics research.


Textbooks and Educational Materials

Statistics in Sports

Editors: Jim Albert, Jay Bennett, James J. Cochran Publisher: CRC Press, 2005 ISBN: 978-1584883883

Academic textbook covering statistical methods across multiple sports. Basketball sections address regression analysis applied to player evaluation.

Relevant Chapters: - Statistical modeling of player performance - Regression approaches to talent evaluation - Proper use of statistical inference

Why Read This: Provides rigorous statistical foundation for sports analytics work.


Mathletics: How Gamblers, Managers, and Sports Enthusiasts Use Mathematics in Baseball, Basketball, and Football

Author: Wayne Winston Publisher: Princeton University Press, 2009 ISBN: 978-0691139135

Winston's textbook approach to sports analytics includes substantial basketball content. Worked examples demonstrate analytical techniques using box score data.

Key Sections: - Linear weights for player evaluation - Regression analysis in basketball - Simulation methods for decision-making

Why Read This: Accessible introduction to quantitative methods in basketball.


Video and Multimedia

Thinking Basketball (YouTube Channel)

Creator: Ben Taylor URL: https://www.youtube.com/c/ThinkingBasketball Type: Video Analysis

Ben Taylor's video analysis demonstrates how to interpret statistics in context. Episodes combine box score analysis with film study.

Key Series: - "Thinking Basketball" series on greatest players - Contextual analysis of statistics - Integration of film and numbers

Why Watch This: Demonstrates proper integration of statistics and video analysis.


The Basketball Analytics Podcast

Type: Audio Content Various Platforms

Multiple podcasts cover basketball analytics topics, featuring interviews with analysts and discussion of statistical methods.

Recommended Episodes: - Interviews with Dean Oliver - Discussions of metric development - Team analytics department features

Why Listen: Provides perspective on how statistics are used professionally.


Specialized Topics

"Home Court Advantage and Referee Bias"

Various Academic Studies

Multiple academic papers document home court advantage in assists credited and other statistics. Relevant for understanding "scorer bias" discussed in Chapter 6.

Key Findings: - Home teams receive approximately 0.5 more assists per game - Foul calls favor home teams - The effect is consistent across decades

Why Read This: Quantifies limitations of assist statistics.


"Rebounds and Player Evaluation"

Author: David Berri Various Publications

Berri has written extensively on why rebounds are undervalued in traditional analysis. His work demonstrates the predictive power of rebounding for team success.

Key Arguments: - Rebounds have higher correlation with winning than commonly believed - Individual rebounding skill is partially separable from team effects - Per-minute rebounding rates are relatively stable

Why Read This: Challenges assumptions about rebounding interpretation.


Practical Application

FiveThirtyEight Basketball Coverage

URL: https://fivethirtyeight.com/tag/nba/ Type: Applied Analytics Journalism

FiveThirtyEight provides accessible applied analytics coverage, including explanation of their RAPTOR metric and regular statistical analysis.

Key Features: - RAPTOR metric explanation - Regular statistical features - Accessible presentation of complex concepts

Why Read This: Demonstrates how analytics concepts apply to current events.


The Athletic (Basketball Coverage)

URL: https://theathletic.com Type: Sports Journalism

The Athletic employs several analytically-minded basketball writers who integrate statistics into their reporting. Subscription required.

Notable Writers: - Seth Partnow (former Bucks analyst) - John Hollinger (PER creator) - Kevin Pelton (ESPN analytics expert)

Why Read This: High-quality integration of statistics and basketball writing.


Reading Path Recommendations

For Beginners

  1. Start with Basketball-Reference glossary
  2. Read Oliver's "Basketball on Paper" Chapters 1-4
  3. Explore FiveThirtyEight explainer articles
  4. Watch Thinking Basketball introduction videos

For Intermediate Analysts

  1. Complete Oliver's "Basketball on Paper"
  2. Read Kubatko et al. academic paper
  3. Explore Berri's alternative perspective
  4. Work through Winston's "Mathletics" examples

For Advanced Researchers

  1. Review MIT Sloan Conference paper archives
  2. Study regression-based methods in Statistics in Sports
  3. Examine original RAPM and APM papers (covered in later chapters)
  4. Follow current research in JQAS

Updates and Living Resources

Basketball analytics evolves rapidly. Stay current through:

  • Twitter/X: Follow analysts like @kpelton, @NateSilver538, @baborta
  • Reddit: r/nbadiscussion for analytical basketball discussion
  • Newsletters: Various analyst newsletters provide regular updates
  • Conferences: MIT Sloan Sports Analytics Conference (annual)

This bibliography represents resources available as of the textbook publication date. URLs and availability may change over time.