Purpose This study aims to examine the dual role of non-fungible tokens (NFTs) in elite European football by assessing their financial relevance for clubs and their governance-related implications for fan engagement and legitimacy. It explores how NFTs operate at the intersection of digital revenue innovation and contested issues of transparency, accountability and participation. Design/methodology/approach The study adopts a mixed-methods design. Quantitative financial data were drawn from the Deloitte Football Money League for the top 20 European clubs over the period 2021–2024 and analysed to assess the scale and distribution of NFT-related revenues. Qualitative data were collected from publicly accessible social media platforms and fan forums, focusing on discussions related to NFTs, fan tokens, governance practices and perceived risks. A thematic analysis was conducted, and findings from both data strands were integrated to enable triangulation and contextual interpretation. Findings The results indicate that NFT-related revenues remain economically marginal and uneven across elite European football clubs, with no clear evidence of a stabilising effect on financial sustainability. At the same time, qualitative analysis shows that NFTs carry social and governance significance that exceeds their direct financial contribution. Fan discourse consistently frames NFT initiatives in relation to transparency, cultural meaning and accountability, revealing tensions between club-led digital monetisation strategies and supporter expectations. Practical implications The findings suggest that NFT initiatives require careful strategic and governance consideration. While NFTs may offer limited supplementary revenue opportunities, their implementation has implications for fan trust and institutional legitimacy. Greater transparency and clearer governance arrangements may help align digital innovation with supporter expectations. Originality/value By integrating financial analysis with fan discourse, this study offers one of the first systematic examinations of NFTs in football that connects economic outcomes with governance and legitimacy concerns. The findings contribute to debates on digital innovation in sport by demonstrating that the significance of NFTs lies less in their financial scale than in their institutional and social implications.
Nick Riccardi, Rodney Paul, Andrew Weinbach, Hamid Ekbia
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.
Maria Christodimitropoulou, John Douvis, Panagiotis Alexopoulos, Panagiota Antonopoulou
This research examines the multifaceted digital transformation of tennis, analyzing the impact of new technologies on four key pillars: athlete training and performance, officiating and "smart" courts, fan experience and engagement, and emerging business models and governance. The integration of Artificial Intelligence, the Internet of Things through wearable sensors and "smart" equipment, and blockchain technology is radically reshaping how the sport is trained, played, watched, and managed. Technologies such as motion analysis systems, "smart" racquets, electronic officiating systems, personalized content platforms for fans, and Non-Fungible Tokens are analyzed. The research demonstrates that while these technologies offer unprecedented opportunities for performance optimization, objectivity in officiating, and deeper fan connection, they also present challenges related to adoption, regulation, commercial viability, and the need for unified governance. The research concludes that successfully navigating this new landscape requires a strategic approach that balances innovation with tradition, ensuring that technology acts as an enhancing factor for the sport rather than an end in itself.
Web3 prediction markets, exemplified by Polymarket, have gained prominence for leveraging collective intelligence to forecast a wide range of social, political, and sports events. However, among the thousands of prediction market events, consensus disputes still arise due to imperfections in market mechanisms. On Polymarket alone, the trading volume involving disputed events has reached $972,370,804.71, underscoring the critical need for objective and efficient dispute resolution. In this study, we introduce large language models (LLMs) to: (1) evaluate whether web-enabled LLMs can reproduce the decision quality of UMA's on-chain voting process once a dispute has been raised, and (2) predict, based on event rules, which market events are likely to face future disputes before they occur. Our findings show that LLMs are unable to reliably predict which events will become disputed in advance; however, once a dispute is initiated, web-enabled LLMs achieve 89.58% agreement with UMA's final resolutions and demonstrate strong stability.
Purpose - This study examines how Web3 technologies—including blockchain, non-fungible tokens (NFTs), and decentralized finance (DeFi)—affect the business models of sports organizations and the engagement behavior of fans. The research evaluates both the revenue and loyalty opportunities created by digital assets and the financial risks and regulatory challenges they introduce. Design/methodology/approach - A mixed-methods approach is employed, combining blockchain analytics, big data and social media monitoring, expert interviews, ethnographic observation of online fan communities, and systematic case analysis of NBA Top Shot, Chiliz/Socios.com, Sorare, and related platforms. Theoretical grounding draws on the Stimulus-Organism-Response (S-O-R) paradigm, the Fan Attitude Network (FAN) model, and Social Identity Theory (SIT). Findings - Fan tokens and NFTs create new revenue streams and deepen supporter loyalty through exclusive access, participatory governance, and gamified interactions. However, empirical evidence reveals high price volatility, speculative investor behavior, misleading marketing, and an unclear regulatory environment that expose fans to financial risk. Emerging markets such as Azerbaijan face additional structural barriers—limited fan culture depth, nascent regulation, and underdeveloped digital infrastructure—that preclude near-term viability of NFT-based fan engagement. Originality/value - This article is among the first to systematically integrate governance, financial risk, and regulatory dimensions of Web3 in sports within a single framework, moving beyond prior work focused narrowly on marketing and financial performance. It offers actionable implications for sports organizations, regulators, and platform developers. Research limitations/implications - The study is constrained by the rapidly evolving nature of Web3 technologies, jurisdictional variation in regulatory frameworks, and limited blockchain data accessibility for some platforms.
In this study, the authors developed a smart traceability framework for athletic equipment using distributed ledger technology. They conducted their research to address persistent gaps in authenticity, life cycle visibility, and fan-side provenance across the sports equipment ecosystem. The framework was designed through a design-science approach, integrating Internet of Things sensors, digital twins, Electronic Product Code Information Services logistics data, and retail/resale events into a unified distributed ledger technology architecture governed by smart contracts. Simulation results show high validation accuracy, strong life cycle coverage, stable ledger performance, and reliable ownership transfers across manufacturing, field use, and secondary markets. These findings indicate that end-to-end, tamper-resistant traceability can significantly improve trust, operational transparency, and fan engagement in real-world sports equipment environments.
Introduction: Blockchain-enabled products (e.g., cryptocurrencies and fan tokens) have rapidly expanded across professional sport, but the research landscape remains dispersed across finance, marketing, information systems, and sport management. Methods: This study conducted a thematic review of Web of Science Core Collection records supplemented by snowball searching, yielding 30 English-language peer-reviewed studies published between 2019 and 2025. Results: Based on the included titles, we mapped how the literature has developed and what it collectively implies for sport organizations, platforms, and consumers. Five recurring strands were identified: (1) fan tokens and sport cryptoassets as financial assets, emphasizing volatility, spillovers, and sensitivity to sport- and crypto-market events; (2) adoption, identity, and engagement research explaining why supporters buy/hold tokens, participate in voting, and engage in advocacy; (3) computational and platform-data approaches (e.g., sentiment/discourse analyses and poll/voting participation patterns) to quantify online engagement and market narratives; (4) blockchain applications and governance, including stakeholder-oriented discussions and ethical critiques regarding value creation, transparency, and power asymmetries; and (5) gambling-like risks and addiction-related correlates, highlighting the convergence of trading, betting-like dynamics, and potentially harmful consumption. Discussion: Limitations include dependence on WoS-indexed English-language publications, topic and context concentration (especially European football and major platforms), and heterogeneity in study designs and outcomes that precludes comprehensive data synthesis. Future research should broaden contexts beyond dominant sports/regions and use stronger longitudinal or quasi-experimental designs to test mechanisms and harms.
Prediction markets have grown from niche research focused platforms into a multi-billion-dollar industry, yet the academic literature on the properties of these new platforms has not caught up. Prediction markets on the touch probability of traded assets are a new form of contract, in which traders bet on whether an asset will reach a specified price level within a given window. They represent a structurally distinct and largely unexamined category. Because these contracts reference a continuously traded underlying with a deep options market, the probability they quote may already be embedded in existing market data. This thesis asks if Polymarket Bitcoin price-target contracts contribute to price discovery, or whether they merely repackage the touch probability already implied by the Bitcoin spot and options markets. The analysis uses 258 monthly barrier contracts traded between October 2024 and March 2026 and proceeds in three stages: a Mincer-Zarnowitz calibration regression, per-contract Granger causality tests at the hourly frequency, and a cross-sectional comparison of Polymarket prices against a closed-form one-touch barrier probability evaluated under both implied and realised volatility. The calibration test cannot reject Polymarket prices are unbiased probability forecasts of their resolution outcomes. The Granger causality tests reveal that Polymarket no detectable predictive content for next-hour Bitcoin returns. A closed-form barrier probability computed from the spot price, strike, time to maturity, and a volatility estimate explains over 95% of the cross-sectional variation in Polymarket prices under both implied and realised volatility, though the joint null of exact equality is rejected. The price tracks the realised-volatility benchmark and sits below the implied-volatility one, so the level departure is consistent the variance risk premium embedded in options rather than independent information about Bitcoin. The three results replicate out of sample on 252 Ethereum contracts. Taken together, the findings suggest that financial-asset prediction markets contribute little information beyond what is already priced in the underlying spot and options markets.
<p>Resumo <br>Este artigo investiga a viabilidade econômica e comportamental da criação de criptomoedas <br>personalizadas (Fan Coins) atreladas à performance de jogadores de futebol, utilizando métodos <br>quantitativos em Econometria, com foco em arrecadação por bilheteria, patrocínios e apostas esportivas. A <br>análise inclui os casos de Diego Ribas (Flamengo), Neymar (Santos), e artilheiros do São Paulo e Palmeiras. <br>A proposta é analisar como a reputação e a performance esportiva podem ser transformadas em ativos <br>digitais de valor mensurável. Ainda, propõe-se a utilização de sistemas de inteligência artificial para gestão <br>de carteiras de patrocinadores e um aplicativo de fan clube com sistema de assinaturas para fomentar um <br>novo modelo de negócios esportivos baseado em dados e personalização. <br>Palavras-chave: Fan Coin; Criptomoeda; Econometria; Economia do Esporte; Teoria dos <br>Jogos; Finanças Comportamentais; Apostas Esportivas; Inteligência Artificial; Modelagem <br>Financeira; Patrocínio Digital.</p>
AbstractThis article investigates the economic and behavioral feasibility of creating personalizedcryptocurrencies (Fan Coins) linked to the performance of soccer players, using quantitative methods inEconometrics, focusing on box office revenue, sponsorships and sports betting. The analysis includes theThe cases of Diego Ribas (Flamengo), Neymar (Santos), and top scorers from São Paulo and Palmeiras.proposal is to analyze how reputation and sports performance can be transformed into digital assets withmeasurable value. Furthermore, it is proposed to use artificial intelligence systems to manage sponsorportfolios and a fan club application with a subscription system to foster a new sports business model basedon data and personalization.Keywords: Fan Coin; Cryptocurrency; Econometrics; Sports Economics; Game Theory;Behavioral Finance; Sports Betting; Artificial Intelligence; Financial Modeling; Digital Sponsorship
Introduction This study explores the feasibility of embedding futarchy, specifically policy-binding conditional prediction markets anchored to democratically chosen key performance indicators (KPIs) in Decentralized Science (DeSci) governance. By externalizing belief formation to speculative markets while anchoring values democratically, futarchy offers a structurally distinct alternative to existing Decentralized Autonomous Organization (DAO) governance models. Methods Through an empirical analysis of governance data from 13 DeSci DAOs, this study examines governance, participation, and cadence patterns that condition futarchic adoption. A retrospective simulation using proposals from VitaDAO assessed the degree to which historical decisions align with futarchy-preferred outcomes. Results The results indicate full directional alignment under deterministic modeling, suggesting latent compatibility between futarchy and existing DeSci governance. Discussion The analysis further outlines the design principles for implementation, emphasizing measurable KPIs and epistemic diversity. Futarchy, if carefully instantiated, may serve as a governance alternative for funding truth-tracking science through probabilistic decision making and market-based information aggregation.
This systematic review examines how elite athletes are leveraging digital platforms, generative artificial intelligence (AI), and blockchain to build autonomous brands, bypass traditional sport gatekeepers, and develop athlete-owned business models. Drawing on 47 peer-reviewed studies (2016-2025), we synthesise evidence across five domains: athlete branding and self-production, disintermediation, platform-enabled empowerment, AI-driven content innovation, and emerging commercial structures. The findings reveal a decisive shift in sport's power balance, with athletes acting as media producers, cultural influencers, and entrepreneurial actors. Digital platforms enable direct-to-fan engagement, while AI tools lower content production costs whilst personalising interactions and extend global reach. Blockchain facilitates decentralised monetisation and data sovereignty, supporting ventures such as athlete-owned leagues and non-fungible tokens. However, these developments embed new dependencies on platform algorithms and volatile digital markets. From a platform capitalism perspective, athlete autonomy is constrained by corporate-controlled infrastructures; from a value co-creation lens, fan relationships become participatory spaces for shared cultural and commercial value creation. The review highlights governance challenges, including ethical implications of synthetic media, data ownership, and the regulation of AI-enabled branding ecosystems. We argue that sport governance must evolve from a control-oriented model to one that positions athletes as co-creators of value and strategic partners in decision-making. Future research should address equity in digital visibility and sustainable athlete-led business ecosystems. Governance mechanisms that reconcile technological opportunity with autonomy protection should be explored as well. Athletes are no longer peripheral actors in sport's commercial order, they are emerging as its architects, with significant implications for the future of sport governance.
Quentin Botha, Laurent Bindschaedler, Christoph Siebenbrunner
Decentralized mathematics prediction markets promise new forms of collaboration and incentive alignment, but traditional requirements engineering methods fail to address the unique governance, incentive, and security challenges of such Web3 systems. This paper demonstrates how they can be addressed through a requirements-driven design of a decentralized prediction market for mathematical conjectures, and proposes concrete enhancements to existing frameworks. Our work delivers actionable guidelines for engineering secure, incentive-aligned decentralized platforms, and sets a new standard for early-stage RE in the Web3 era.
Philip Kang, Yong Jae Ko, Sangpil Youm, Yoonki Chun · 6 authors
Purpose The current study attempted to unravel the complexities of sport Non-Fungible Token (NFT) consumption by exploring consumers' perceived values and risks of sport NFTs. Design/methodology/approach To achieve this goal, the authors conducted an exploratory study by collecting 23,445 tweets from Twitter and adopted artificial intelligence tools (i.e. latent Dirichlet allocation topic modeling and visualization, Word2Vec and uniform manifold approximation and projection) to analyze the data. Findings The results revealed that sport NFT platforms (i.e. NBA Top Shot, NFL All Day and UFC Strike) engage users through a blend of intrinsic and extrinsic motivations, including personal enjoyment, financial rewards and social recognition. Originality/value The current research not only illuminates the newly emerged NFT market but also provides exploratory evidence to understand sport NFT consumers’ value perception by using machine and deep learning approaches. Practically, the current study provides valuable insights to sport NFT brand managers by identifying significant values that trigger sport NFT consumers' engagement with sport NFT consumption behavior.
Jiaxin Wang, Qian’ang Mao, Hongliang Sun, Jiaqi Yan
With the development of blockchain technology, crypto gambling has gained popularity due to its high level of anonymity. However, similar to traditional casinos, crypto casinos are controlled by a few internal Delegatees, making it impossible for them to achieve complete transparency and fairness. These delegatees are hidden among gamblers and are difficult to identify and distinguish in anonymous and large-scale blockchain transaction networks. This paper proposes an unsupervised dual-stage role identification method to adaptively identify key roles and hidden delegatees in label-sparse crypto casinos. Specifically, inspired by voting-style transaction patterns, we propose a novel voting influence metric for key node identification. This metric is based on one-dimensional structural entropy to capture global dissemination capability. Subsequently, we develop a multi-view graph neural network framework enhanced with two-dimensional global structural entropy minimization and self-supervised contrastive learning to improve the robustness and interpretability of hidden role partitioning. Experiments on real-world cases of the most mainstream blockchains-Ethereum, TRON, and Arbitrum-demonstrate that our proposed method effectively reveals distinct role compositions and collusion patterns, distinguishing between gamblers and delegatees. Our results achieve a higher match with identities confirmed by judicial authorities than existing methods, indicating the effectiveness and generalizability of our approach in enhancing security and regulation oversight.
Vitor Ayres Principe, Tiago Ribeiro, Wecisley Ribeiro do EspÃrito Santo, Rodrigo Gomes de Souza Vale · 5 authors
This study examines the innovative application of Decentralized Autonomous Organizations (DAOs) within the sports management sector, leveraging blockchain technology to enable more transparent and inclusive governance. This paper explores how DAOs can disrupt traditional governance structures through the democratic participation of fans and stakeholders. It emphasizes the potential of DAOs to facilitate collaborative governance in line with the four modes of governance framework: chief, clan, custodian, and consortium. By dissecting decentralized governance models, the paper discusses how DAOs can transform traditional structures, enabling more democratic fan participation in sport club decisions. The research highlights such innovations’ economic, social, and environmental benefits with real-world examples of DAO implementations in sports organizations. Additionally, the study proposes a conceptual model for integrating DAOs into sports clubs, optimizing resource management, enhancing fan engagement, and aligning club operations with the Environmental, Social, and Governance (ESG) criteria. This conceptual model is a foundation for future research and practical applications in the sports management field.
This article presents a conventional asset penalizing game model in green finance. We use a Mean Field Game (MFG) approach to investigate how a large population of small interacting conventional asset holders influences green asset prices, resulting in a green asset premium. Firstly, we formulate the green premium for green assets in a decentralized exchange pool setting. Using a virtual curve to model how collective behavior affects green asset prices, we analyze green premium cost implications for agents. Then, we develop our MFG model for the transition of green assets. To address the MFG problem, we use the Pontryagin maximum principle to find the fix-point solution in a deterministic conventional asset price setting. In the numerical experiment, we expand it to the stochastic price case and use Monte Carlo simulations to obtain the equilibrium collective asset transfer rate under certain market conditions. For empirical analysis, we examine the explanatory power of our model concerning the real market's green premium.
In an era where two-fifths of the global population is engaged in gaming, this industry’s technological and economic evolution is of paramount importance, promising continued growth. Beyond mere entertainment, gaming has become a primary medium for social interaction, enriched by technologies like virtual, augmented, and extended reality. Gaming has increasingly become intertwined with the financial market as game developers shift their focus from gameplay enjoyment to monetization of in-game assets and some players prioritize the potential for livelihood in gaming. This transformation has been accelerated by the integration of blockchain, decentralized finance (DeFi) protocols, and non-fungible tokens (NFTs), which provide users with more control over their in-game assets and enable external trading of such assets in the secondary market. This chapter delves into this integration, examines its impact on the gaming industry, and provides a high-level overview of key related legal and ethical issues that warrant further exploration.
Krzysztof Gogol, Manvir Schneider, Tessone, Claudio, Livshits, Benjamin
Layer-2 (L2) blockchains inherit Ethereums security guarantees while reducing gas fees. As a result, they are gaining traction among traders at Automated Market Makers (AMMs), sparking debate over whether they contribute to liquidity fragmentation of Ethereum. Our research suggests that such fragmentation is not currently occurring. However, it could emerge in the future, particularly if Liquidity Providers (LPs) recognize the higher returns available on L2s. Using Lagrangian optimization, we develop a model for optimal liquidity allocation across AMMs on Ethereum and its L2s, using staking as a benchmark. We show that, in equilibrium, AMM liquidity provision returns converge to this reference rate. Additionally, we measure the elasticity of trading volume with respect to Total Value Locked (TVL) in AMMs and find that, on well-established blockchains, an increase in TVL does not necessarily lead to higher trading volume. Finally, our empirical findings reveal that Ethereums liquidity pools are oversubscribed compared to those on L2s and often yield lower returns than staking Ether. LPs could maximize their rewards by reallocating more than two-thirds of their liquidity to L2s and staking.
Hongzhou Chen, Xiaolin Duan, Abdulmotaleb El Saddik, Wei Cai
Harnessing the transparent blockchain user behavior data, we construct the Political Betting Leaning Score (PBLS) to measure political leanings based on betting within Web3 prediction markets. Focusing on Polymarket and starting from the 2024 U.S. Presidential Election, we synthesize behaviors over 15,000 addresses across 4,500 events and 8,500 markets, capturing the intensity and direction of their political leanings by the PBLS. We validate the PBLS through internal consistency checks and external comparisons. We uncover relationships between our PBLS and betting behaviors through over 800 features capturing various behavioral aspects. A case study of the 2022 U.S. Senate election further demonstrates the ability of our measurement while decoding the dynamic interaction between political and profitable motives. Our findings contribute to understanding decision-making in decentralized markets, enhancing the analysis of behaviors within Web3 prediction environments. The insights of this study reveal the potential of blockchain in enabling innovative, multidisciplinary studies and could inform the development of more effective online prediction markets, improve the accuracy of forecast, and help the design and optimization of platform mechanisms. The data and code for the paper are accessible at the following link: https://github.com/anonymous.
Digital assets and the traditional financial sectors are increasingly interacting. In the field of cryptocurrency, the combination with the sports industry has received attention from fans and clubs, media, and academic circles. Based on the LASSO-VAR model which is suitable for large samples, this article investigates the connectivity between sports cryptocurrency Chiliz (CHZ) and listed European football club stocks. The results show that there is a certain interrelatedness among the selected assets, and it becomes closer with the outbreak of major emergencies. In addition, CHZ is a net recipient of spillovers, while club stocks show diversification. Our results are helpful for club fans, individual and institutional investors, market regulators, and policymakers to make correct decisions.
Automated Market Makers (AMMs) are a cornerstone of decentralized finance. They are smart contracts (stateful programs) running on blockchains. They enable virtual token exchange: traders swap tokens with the AMM for a fee, while liquidity providers supply liquidity and receive these fees. Demand for AMMs is growing rapidly, but our experiment-based estimates show that current architectures cannot meet the projected demand by 2029. This is because the execution of existing AMMs is non-parallelizable. We present SAMM, an AMM comprising multiple shards. All shards are AMMs running on the same chain, but their independence enables parallel execution. The security of SAMM, unlike in classical sharding solutions, relies on incentive compatibility. Therefore, SAMM introduces a novel fee design. Through analysis of Subgame-Perfect Nash Equilibria (SPNE), we show that SAMM incentivizes the desired behavior: liquidity providers balance liquidity among all shards, overcoming destabilization attacks, and trades are evenly distributed. We validate our game-theoretic analysis with a simulation using real-world data. We evaluate SAMM by implementing and deploying it on local testnets of the Sui and Solana blockchains. To our knowledge, this is the first quantification of high-demand-contract performance. SAMM improves throughput by 5x and 16x, respectively, potentially more with better parallelization of the underlying blockchains. It is directly deployable, mitigating the upcoming scaling bottleneck.