ELI: Prediction market traders are mainly DeFi tech workers

A report from Emotional Logic Interfaces (ELI) estimates roughly 17 million people in the U.S. will use prediction markets this year. The firm describes the typical user as a tech worker active in decentralized finance, about 90% male, with a 40–50% overlap with sports bettors.

ELI analyzed 100 million online signals tied to an estimated 220 million online accounts. The firm used anonymized data licensed from providers including GlobalWebIndex and YouGov and applied artificial intelligence to map retail, media and social behaviors. ELI reports a claimed 91% accuracy and says its segments are built from observed actions rather than predictive modeling.

The report finds these users are more likely than the general public to engage with high-risk investments and cryptocurrency. It reports the group is 2.8 times more likely to choose high-risk investments, 3 times more likely than the national average to use crypto and DeFi products, and 13 times more likely to show interest in politics. The analysis also finds participants are four times more likely than average to have played fantasy sports and 43% less likely than the average American to identify as gamblers.

The study notes sports-event contracts make up an estimated 85–90% of trading volume on one platform it examined. The report also states a large majority of users still lose money on exchanges.

Geographic concentrations differ from a Wall Street profile. ELI finds higher densities of prediction-market users in tech-focused secondary cities such as Nashville, Austin, Fort Collins and Louisville. The group includes many coders, software developers and other tech workers who tend to favor crypto and alternative financial services over traditional banks.

Ian Baer, lead author of the report, described prediction-market players as more closely aligned with cryptocurrency enthusiasts and as a distinct group from typical sports gamblers, calling them “a separate profession” and “very different from gambling.”

The report was produced to provide operators and regulators with a data-driven profile of prediction-market users and their online behaviors. Its methodology emphasizes observed individual actions and anonymized data sources to build audience segments and behavioral patterns.