Data and Code for: Rational Inattention in the Infield

Principal Investigator(s): View help for Principal Investigator(s) Vivek Bhattacharya, Northwestern University; Greg Howard, University of Illinois at Urbana-Champaign

Version: View help for Version V1

Name	File Type	Size	Last Modified
codebooks			12/21/2020 04:14:PM
data			12/21/2020 04:17:PM
exhibits			12/21/2020 04:16:PM
output			12/21/2020 04:14:PM
raw			12/21/2020 06:19:PM
temp			12/21/2020 04:18:PM
LICENSE.txt	text/plain	8.5 KB	02/25/2021 09:50:AM
README.txt	text/plain	17.8 KB	02/25/2021 11:06:AM
all_data.dta	application/x-stata	2.3 GB	12/21/2020 07:02:AM
batter_robustness.do	text/x-stata-syntax	2.6 KB	12/21/2020 06:57:AM

Project Citation:

Bhattacharya, Vivek, and Howard, Greg. Data and Code for: Rational Inattention in the Infield. Nashville, TN: American Economic Association [publisher], 2022. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2022-10-21. https://doi.org/10.3886/E129501V1

Project Description

Summary: This paper provides evidence of rational inattention by experienced professionals in strategic interactions. We add rational inattention to a game of matching pennies with state-dependent payoffs. Unlike the full-information mixed-strategy Nash equilibrium, payoffs of different actions need not be equated state-by-state. Moreover, players respond partially to payoff differences, this responsiveness is stronger when attention costs are lower, strategies converge to full-information Nash as stakes increase, and average payoffs across all states are approximately equal across actions. We test these predictions using data on millions of pitches from Major League Baseball, where we observe strategies, payoffs, and proxies for attention costs.

Scope of Project

Subject Terms: behavioral economics; rational inattention; cognitive costs

JEL Classification:
      C72 Noncooperative Games
      D83 Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
      D91 Micro-Based Behavioral Economics: Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making

Geographic Coverage: United States

Time Period(s): 2008 – 2017

Collection Date(s): 2/6/2020 – 2/6/2020 (Date MLB GameDay data was scraped)

Universe: Major League Baseball players

Data Type(s): event/transaction data

Collection Notes: The data is collected from the following sources:

MLB's Pitchf/x and Gameday systems
Bill Petti's Baseball Tools website (https://billpetti.github.io/baseball_tools/)
Fangraphs (www.fangraphs.com)
ESPN analysis (http://www.espn.com/espn/feature/story/_/id/12331388/the-great-analytics-rankings)
Baseball Reference (www.baseball-reference.com)
Greg Stoll's analysis, via Retrosheet (www.retrosheet.org)
Tom Tango's analysis (www.insidethebook.com)

Further details and licensing information can be found in README.txt and LICENSE.txt.

Methodology

Unit(s) of Observation: Actions (usually pitches) in a baseball game

Related Publications

Download this project

Published Versions

V1 [2022-10-21]

Export Metadata

Dublin Core

DDI 2.5

Report a Problem

Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.

This material is distributed exactly as received from the data depositor. As of April 2026, depositors are required to submit study materials in accessible formats. ICPSR has not reviewed, checked, or processed this material. For additional information about the study, please contact the investigator(s) directly. If you have questions about the accessibility of materials distributed by ICPSR or require further assistance, please visit ICPSR's Accessibility Center.