Price in the Player? Testing Performance-Based Mispricing in NFT Fantasy Sports Markets

Session Title

Sports Betting: Strategy & Investment

Presentation Type

Paper Presentation

Start Date

28-5-2026 12:00 AM

Abstract

This study examines behavioral pricing patterns in blockchain-based fantasy sports markets by analyzing non-fungible token (NFT) sales on Sorare.com, a decentralized platform where users buy, sell, and compete with digital player cards. Each NFT corresponds to a licensed professional soccer player and is traded in a secondary market on Ethereum-based infrastructure. We construct a unique dataset by linking player performance data with transaction-level NFT sales across multiple seasons, focusing on the Rare and Super Rare card tiers. To isolate the effects of recent performance on secondary market prices, we develop a matching algorithm that connects NFT transaction records to individual card IDs based on sale timestamps and card-specific metadata. This structure allows us to test whether player NFTs are priced efficiently, or whether recent on-field success leads to temporary price inflation consistent with hot hand bias. Our results align with the presence of performance-chasing or hot hand pricing, where recent form leads to a temporary inflation of perceived value. Our framework builds on prior work examining the hot hand hypothesis in traditional sports betting markets—including studies by Camerer (1989), Brown and Sauer (1993), and Paul and Weinbach (2005, 2011, 2014)—and extends this behavioral lens to tokenized digital assets.

Author Bios

Ph.D. Candidate in Information Science and Technology at Syracuse University with a focus oncomputational social science and sport analytics. Experienced researcher and educator with expertisein econometric and machine learning modeling, natural language processing, and data managementand visualization. Published researcher across sport economics, sport analytics, and computationalmethods, with experience presenting at domestic and international conferences.

Share

COinS
 
May 28th, 12:00 AM

Price in the Player? Testing Performance-Based Mispricing in NFT Fantasy Sports Markets

This study examines behavioral pricing patterns in blockchain-based fantasy sports markets by analyzing non-fungible token (NFT) sales on Sorare.com, a decentralized platform where users buy, sell, and compete with digital player cards. Each NFT corresponds to a licensed professional soccer player and is traded in a secondary market on Ethereum-based infrastructure. We construct a unique dataset by linking player performance data with transaction-level NFT sales across multiple seasons, focusing on the Rare and Super Rare card tiers. To isolate the effects of recent performance on secondary market prices, we develop a matching algorithm that connects NFT transaction records to individual card IDs based on sale timestamps and card-specific metadata. This structure allows us to test whether player NFTs are priced efficiently, or whether recent on-field success leads to temporary price inflation consistent with hot hand bias. Our results align with the presence of performance-chasing or hot hand pricing, where recent form leads to a temporary inflation of perceived value. Our framework builds on prior work examining the hot hand hypothesis in traditional sports betting markets—including studies by Camerer (1989), Brown and Sauer (1993), and Paul and Weinbach (2005, 2011, 2014)—and extends this behavioral lens to tokenized digital assets.