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

Yixiao Gao, Fei Li, Ruizhe Shi, Ruizhi Cheng, Jean Zhang, Bo Han, Songqing Chen

TL;DR

This work measures the real-world efficacy of Play-to-Earn in NFT games by analyzing on-chain data from 12 Ethereum-based titles (with Axie Infinity on Ronin), supplemented by game-site data. It reveals pronounced NFT ownership concentration, variable but short-lived promotional effects, and a majority of players experiencing negative profits, suggesting that the current $P2E$ design fails to sustain ordinary participants. The authors develop a simple, game-theoretic incentive mechanism and validate it through simulations, showing that properly calibrated incentives can significantly improve trader profits and NFT circulation. The findings highlight the need for carefully engineered incentives to realize the promised $P2E$ economics and offer a quantitative framework for evaluating future NFT-game incentive schemes.

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.

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

TL;DR

This work measures the real-world efficacy of Play-to-Earn in NFT games by analyzing on-chain data from 12 Ethereum-based titles (with Axie Infinity on Ronin), supplemented by game-site data. It reveals pronounced NFT ownership concentration, variable but short-lived promotional effects, and a majority of players experiencing negative profits, suggesting that the current design fails to sustain ordinary participants. The authors develop a simple, game-theoretic incentive mechanism and validate it through simulations, showing that properly calibrated incentives can significantly improve trader profits and NFT circulation. The findings highlight the need for carefully engineered incentives to realize the promised economics and offer a quantitative framework for evaluating future NFT-game incentive schemes.

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.
Paper Structure (25 sections, 3 theorems, 9 equations, 12 figures, 8 tables, 1 algorithm)

This paper contains 25 sections, 3 theorems, 9 equations, 12 figures, 8 tables, 1 algorithm.

Key Result

Theorem 1

Assume there is only one player and he/she has the basic profile for all the assets $j$ in the interval $[1, T]$, where $j = 1, \ldots, K$. Then a plan exists for a game player to maximize his/her total payoff in this interval.

Figures (12)

  • Figure 1: The largest percentage of NFTs owned by a single wallet (as of 06/30/23)
  • Figure 2: The largest percentage of NFTs owned by a single wallet (change over time)
  • Figure 3: The ODI in the games (as of 06/30/23)
  • Figure 4: The ODI in the games (change over time)
  • Figure 5: Wallets that owns one or more NFTs
  • ...and 7 more figures

Theorems & Definitions (5)

  • Theorem 1
  • proof
  • Theorem 2
  • Theorem 3
  • proof