Causal Hangover Effects
Andreas Santucci, Eric Lax

TL;DR
This study investigates whether playing in cities with active nightlife negatively impacts team performance in sports, using bookmaker odds and a causal model to identify hangover effects in NBA and MLB games.
Contribution
It introduces a causal framework to measure the impact of nightlife exposure on team performance, leveraging bookmaker data and focusing on back-to-back games in party cities.
Findings
Visiting party cities the day before reduces the likelihood of beating the spread.
The negative effect is statistically significant for NBA and MLB.
Market efficiency assumptions support causal interpretation.
Abstract
It's not unreasonable to think that in-game sporting performance can be affected partly by what takes place off the court. We can't observe what happens between games directly. Instead, we proxy for the possibility of athletes partying by looking at play following games in party cities. We are interested to see if teams exhibit a decline in performance the day following a game in a city with active nightlife; we call this a "hangover effect". Part of the question is determining a reasonable way to measure levels of nightlife, and correspondingly which cities are notorious for it; we colloquially refer to such cities as "party cities". To carry out this study, we exploit data on bookmaker spreads: the expected score differential between two teams after conditioning on observable performance in past games and expectations about the upcoming game. We expect a team to meet the spread half…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNuclear Engineering Thermal-Hydraulics · Risk and Safety Analysis
