This study aims to provide foundational data for developing sports non-fungible token (NFT) marketing strategies and enhancing fan experiences by analyzing public sentiment and semantic structures of NBA NFTs. Social big data were collected between 2021 and 2025 from six global platforms (Google, YouTube, Twitter, Reddit, Yahoo, Quora) using the TextoM platform. The analyses conducted included text mining, sentiment analysis, semantic network analysis, and CONCOR analysis. Central keywords included NFT, NBA, TopShot, player, team, marketplace, and crypto. Sentiment analysis indicated 67.5% positive and 32.5% negative sentiment. Semantic network analysis revealed a structure centered around NFT, community, news, game, and blockchain. CONCOR analysis identified five clusters: NFT Infrastructure, NBA Branding, Market Economy, Community Engagement, and Temporal Context. Overall, NBA NFTs are perceived as technical assets and as emotionally driven, identity- and community-centered content. The findings of this study offer significant practical implications for practitioners and managers in the sports industry by guiding the development of marketing strategies that integrate emotional engagement and multidimensional consumer value. This study contributes to the emerging literature on sports NFTs by providing exploratory discourse-level insights into how NBA NFTs are discussed across online platforms and by identifying themes that may inform future theory-driven research at the consumer level.
Prediction markets such as Polymarket are increasingly cited as real-time probability estimates for financial outcomes, yet it remains unknown whether their prices are consistent with the risk-neutral probabilities implied by options markets pricing the same events. Using 2,671 daily observations across 24 Gold and Silver CME futures threshold contracts over a six-month period, this paper finds that Polymarket systematically overprices the upside relative to Black-76 implied probabilities by 8.9 percentage points for Gold and 5.3 percentage points for Silver, a finding robust to seven independent checks and consistent in direction with a contemporaneous independent study on Bitcoin threshold contracts. The divergence exhibits AR(1) half-lives under three days, narrows significantly as expiry approaches, and cannot be fully explained by transaction costs or the commodity risk premium. These results suggest systematic mispricing in prediction market binary threshold contracts, though the observed magnitudes should be interpreted as upper bounds on behavioural mispricing given the structural wedge between risk-neutral and real-world probability measures.
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 aggregate dispersed information into probabilistic forecasts that consistently outperform polls and expert panels, yet their adoption is constrained by a structural liquidity problem: providers of market depth bear adverse selection risk that deters retail participation. We present the Onix Protocol, a hybrid architecture that decouples the pricing function from the settlement function in prediction markets. By pairing automated market maker pricing-a Constant Product Market Maker (CPMM) for binary outcomes and a Logarithmic Market Scoring Rule (LMSR) for multi-outcome markets-with parimutuel (totalizator) settlement, we achieve a structural guarantee that liquidity-provider principal is never at risk from betting outcomes. We formalize the protocol's economic invariants, prove the LP principal guarantee for both market types, describe a "Lazy" liquidity pool enabling passive retail participation, analyze the dispute resolution mechanism under DAO governance, and discuss the experimental hypotheses this system is designed to test. The protocol is implemented as consensus-level operations on the VIZ distributed ledger.
<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.
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.
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.
Vitor Ayres Principe, Giullio César P. S. M. da Silva, Rodrigo Gomes de Souza Vale, Rodolfo de Alkmim Moreira Nunes
Background: Fan tokens emerge as a significant innovation that enables a new form of interaction between clubs and their followers and introduces an alternative economic model for sports entities. Purpose: The review discusses the technical characteristics of fan tokens and their role in enhancing fan participation in minor club decisions, reinforcing the sense of belonging and community. Methods: The research encompassed a systematic literature review, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and Evidence-Based Systematic Mapping in Software Engineering (EBSE). Thus, it presented a quantitative and qualitative analysis of the applications of fan tokens in the sports industry. Results: Despite engagement and monetization opportunities, the results highlight significant challenges, such as price volatility and appropriate regulation to ensure safe and effective adoption. The discussion also includes the ethical and social implications of using fan tokens, emphasizing the need for strategies that prioritize inclusion and fairness for fan engagement. Conclusion: Finally, the study proposes future research directions that consider continuous technological development and changes in fan expectations, aiming to optimize the use of fan tokens to benefit the stakeholders involved. Keywords: Sport Management; Blockchain; Fan Engagement; Fan Tokens; Digital Assets; Tokens
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.
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.
Lennart Ante, Aman Saggu, Benjamin Schellinger, Friedrich-Philipp Wazinski
This paper investigates the potential of blockchain-based fan tokens, a class of crypto asset that grants holders access to voting on club decisions and other perks, as a mechanism for stimulating democratized decision-making and fan engagement in the sports and esports sectors. By utilizing an extensive dataset of 3,576 fan token polls, we reveal that fan tokens engage an average of 4,003 participants per poll, representing around 50% of token holders, underscoring their relative effectiveness in boosting fan engagement. The analyses identify significant determinants of fan token poll participation, including levels of voter (dis-)agreement, poll type, sports sectors, demographics, and club-level factors. This study provides valuable stakeholder insights into the current state of adoption and voting trends for fan token polls. It also suggests strategies for increasing fan engagement, thereby optimizing the utility of fan tokens in sports. Moreover, we highlight the broader applicability of fan token principles to any community, brand, or organization focused on customer engagement, suggesting a wider potential for this digital innovation.
Mathew Fukuzawa, Brandon M. McConnell, Michael G. Kay, Kristin Thoney-Barletta · 5 authors
Purpose Demonstrate proof-of-concept for conducting NFL Draft trades on a blockchain network using smart contracts. Design/methodology/approach Using Ethereum smart contracts, the authors model several types of draft trades between teams. An example scenario is used to demonstrate contract interaction and draft results. Findings The authors show the feasibility of conducting draft-day trades using smart contracts. The entire negotiation process, including side deals, can be conducted digitally. Research limitations/implications Further work is required to incorporate the full-scale depth required to integrate the draft trading process into a decentralized user platform and experience. Practical implications Cutting time for the trade negotiation process buys decision time for team decision-makers. Gains are also made with accuracy and cost. Social implications Full-scale adoption may find resistance due to the level of fan involvement; the draft has evolved into an interactive experience for both fans and teams. Originality/value This research demonstrates the new application of smart contracts in the inter-section of sports management and blockchain technology.
Decentralized exchanges are becoming a competitive necessity for Web3 users. However, they cannot beat centralized exchanges in terms of user experience. Due to expensive gas fees, the blockchain cannot implement the classic order book model which is the pillar for traditional finance exchanges. Instead, most decentralized exchanges operate on the Automated Market Maker (AMM) model using a pre-defined mathematical pricing rule. AMM is more efficient to run on the blockchain but the biggest tradeoff is impermanent loss for liquidity providers and price slippage for traders. This remains the most noticeable drawback of today’s AMM. In this paper, we make the following contributions. First, we observe that if AMM is virtualized as an order book, its “order-book" shape is awkwardly different from that of a real-world order book. We argue that this is conceptually connected to the above weakness. We are thus motivated to design an AMM, the first of its kind, that mimics the price impact behaviors of real-world order books. Second, the proposed AMM, thanks to this property, significantly outperforms the state-of-the-art AMM in impermanent loss. Interestingly, our AMM can even result in impermanent gain. We are also better for large orders where price slippage is a concern. Third, another feature is that, while today’s AMM typically requires a fixed inventory ratio for the liquidity pool, the new AMM allows this ratio to vary, giving liquidity providers flexible options for joining or exiting the pool. All these advantages are offered without losing desirable properties of an AMM regarding split-order exploitation, arbitrage risks, and liquidity continuity. Our findings are validated by theoretical analysis with mathematical proofs and, also, experimental evaluation which was comprehensively conducted using two real-world datasets and a synthetic dataset representing different market scenarios. Our research is the first in the literature on AMM design that factors in statistical properties from the order book model.
Krzysztof Gogol, Robin Fritsch, Malte Schlosser, Johnnatan Messias · 6 authors
This paper studies liquid staking tokens (LSTs) on automated market makers (AMMs), both theoretically and empirically. LSTs are tokenized representations of staked assets on proof-of-stake blockchains. First, we model LST-liquidity on AMMs theoretically, categorizing suitable AMM types for LST liquidity and deriving formulas for the necessary returns from trading fees to adequately compensate liquidity providers under the particular price trajectories of LSTs. For the latter, two relevant metrics are considered: (1) losses compared to holding the liquidity outside the AMM (loss-versus-holding, or "impermanent loss"), and (2) the relative profitability compared to fully staking the capital (loss-versus-staking) which is specifically tailored to the case of LST-liquidity. Next, we empirically measure these metrics for Ethereum LSTs across the most relevant AMM pools. We find that, while trading fees often compensate for impermanent loss, fully staking is more profitable for many pools, raising questions about the sustainability of the current LST liquidity allocation to AMMs.