The Effect of Sport in Online Dating: Evidence from Causal Machine Learning
Daniel Boller, Michael Lechner, Gabriel Okasa

TL;DR
This study uses causal machine learning to analyze how sport activity influences online dating success, revealing that weekly sports significantly boost men's contact chances but not women's, with effects amplified by income.
Contribution
It introduces a novel causal analysis of sport's impact on online dating success, using advanced machine learning techniques on unique platform data.
Findings
Weekly sport increases men's message receipt probability by 50%.
No significant effect of sport on women's contact chances.
Higher income amplifies sport's positive effect for men.
Abstract
Online dating emerged as a key platform for human mating. Previous research focused on socio-demographic characteristics to explain human mating in online dating environments, neglecting the commonly recognized relevance of sport. This research investigates the effect of sport activity on human mating by exploiting a unique data set from an online dating platform. Thereby, we leverage recent advances in the causal machine learning literature to estimate the causal effect of sport frequency on the contact chances. We find that for male users, doing sport on a weekly basis increases the probability to receive a first message from a woman by 50%, relatively to not doing sport at all. For female users, we do not find evidence for such an effect. In addition, for male users the effect increases with higher income.
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.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
