NFT Games: an Empirical Look into the Play-to-Earn Model

2026-02-14

AI Summary

This study addresses the lack of systematic empirical analysis on the real-world performance of Play-to-Earn (P2E) models in NFT-based games. Conducting the first large-scale empirical investigation across 12 prominent NFT games, we integrate on-chain Ethereum transaction data with off-chain website information to uncover critical issues in current P2E ecosystems, including extreme wealth concentration, low trading activity, and average player losses in 9 out of the 12 games examined. Grounded in game-theoretic principles, we design and simulate a novel incentive mechanism that substantially enhances players’ trading returns. Our findings provide both theoretical insights and practical guidance for designing economically sustainable P2E models.

Technology Category

• Game Theory and Economic Paradigms: Mechanism Design
• Multiagent Systems: Mechanism Design
• Humans and AI: Game Design — Procedural Content Generation & Storytelling

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Web Mining and Content Analysis: Models for Web evolution
• Security and Privacy: Large-scale security measurements

Abstract

The past decade has witnessed the burgeoning and continuous development of blockchain and its applications. Besides various cryptocurrencies, an industry that has quickly embraced this trend is gaming. Thanks to the support of blockchain, games have started to incorporate non-fungible tokens (NFTs) that can enable a new gaming model, play-to-earn (P2E), which incentivizes users to participate and play. While recent studies looked at several NFT games qualitatively and individually, an in-depth understanding is still missing, particularly on how the P2E model has transformed traditional games. In this work, we set to conduct a measurement study of NFT games, aiming to gain a comprehensive understanding of the effectiveness of P2E in practice. For this purpose, we collect and analyze relevant NFT transaction data from the underlying blockchain (e.g., Ethereum) of 12 games, supplemented with various data scraped from their websites. Our study shows that (1) a few top wallets control unproportionally high percentage of NFTs, and the majority of wallets own only one or two NFTs and do not actively trade; (2) promotion events do boost the trade amount and the NFT price for some games, but their effect does not sustain; and (3) few players actually earned a profit, and players in 9 out of 12 games who traded NFTs have a negative profit on average. Motivated by these findings, we further investigate effective incentive mechanisms based on game theory to improve the trading profits that players can earn from these NFT games. Both modeling and simulation results confirm the effectiveness of the proposed incentive mechanism.

Problem

• NFT games
• Play-to-Earn
• blockchain
• incentive mechanisms
• player profitability

Innovation

• Play-to-Earn
• NFT games
• blockchain measurement
• incentive mechanism
• game theory