NFT Games: an Empirical Look into the Play-to-Earn Model
Yixiao Gao, Fei Li, Ruizhe Shi, Ruizhi Cheng, Jean Zhang, Bo Han, and Songqing Chen

TL;DR
This paper conducts an empirical analysis of NFT-based play-to-earn games, revealing concentration of NFTs among top wallets, limited profitability for players, and evaluating incentive mechanisms to enhance player earnings.
Contribution
It provides the first comprehensive measurement study of NFT games' transaction data and proposes game-theoretic incentive mechanisms to improve player profitability.
Findings
Few wallets control most NFTs, while most hold only a few and trade infrequently.
Promotion events temporarily increase trading activity and NFT prices.
Most players incur losses, with 9 out of 12 games showing negative profits on average.
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…
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Taxonomy
TopicsBlockchain Technology Applications and Security · FinTech, Crowdfunding, Digital Finance · Auction Theory and Applications
