La Liga Team Bets $1 Million Against Themselves Before Match: Does Using Prediction Markets for Insurance Comply with Sports Regulations?

Foresight NewsPublicado a 2026-06-09Actualizado a 2026-06-09

Resumen

A Spanish La Liga club, reportedly Osasuna, purchased insurance against relegation and was linked to a transaction of over $1 million on the prediction market platform Kalshi, betting against its own victory in a crucial season-ending match. While Osasuna confirmed buying €1.2 million insurance for a potential €6 million payout in case of relegation through broker Howden, it did not confirm involvement with Kalshi. The reported trade involved intermediaries like Game Point Capital and Greenlight Commodities, with quant firm Susquehanna as the counterparty. This incident highlights the blurring line between financial hedging and gambling in prediction markets. Such markets allow trading on future event outcomes, like sports results. In the US, Kalshi operates as a regulated event contract market under the CFTC. However, Spanish authorities recently initiated penalties against Kalshi and Polymarket, considering their activities unlicensed gambling. The case raises core questions about prediction markets: who can trade, how insider information is handled, and whether participants can influence outcomes, especially in sports where results are human-driven. While leagues like La Liga and Serie A have partnered with Polymarket in North America, the regulatory clash and potential for conflicts of interest, as seen in this club's alleged transaction, present significant challenges as prediction markets evolve toward institutional risk management.


By: KarenZ, Foresight News


On May 23rd, Osasuna lost the match but avoided relegation from La Liga.


In the 38th and final round of the 2025-2026 Spanish Primera División season, Osasuna lost 0:1 to Getafe away. According to the club's own post-match announcement, they remained in La Liga because the draw between Elche and Girona meant the final standings ended in their favor. Osasuna will spend their eighth consecutive season in Spain's top-flight league.


Two weeks later, another financial page of this relegation battle was revealed: Osasuna officially admitted that the club had purchased relegation risk insurance through the insurance brokerage Howden, paying a premium of 1.2 million euros; if they were actually relegated, they would receive a payout of 6 million euros.


Another Ledger on Relegation Night


What truly propelled the incident into the center of the prediction market controversy was another link in the chain reported by the media.


On June 4th, according to an exclusive report by Semafor, a related party of an unnamed Spanish club placed a bet of over $1 million on the prediction market platform Kalshi, wagering that they themselves would *not* win a crucial match at the season's end. The transaction path involved intermediaries such as Game Point Capital and Greenlight Commodities. The counterparty was reportedly the quantitative trading firm Susquehanna, which profited over $1 million.


On June 8th, Osasuna issued an official statement confirming the purchase of relegation insurance but emphasized the club's involvement was "strictly limited" to purchasing coverage from Howden. The same day, Protos linked the anonymous club in Semafor's report to Osasuna, while also noting that Osasuna's official documents only mentioned Howden, with no mention of Kalshi, Susquehanna, Game Point Capital, or Greenlight.


A more precise summary is: Osasuna confirmed buying relegation insurance; Semafor first reported that an anonymous La Liga team hedged relegation risk via Kalshi; Protos later linked the two, suggesting that club was Osasuna, though the full details of the transaction chain have not been officially confirmed by the club.


A relegation battle on the pitch, an insurance policy in the club statement, and an event contract about relegation risk in media reports. It is the overlap of these three narratives that makes the story so glaring.


Relegation Can Also Be Financialized


The fear of relegation among football clubs is nothing new.


Relegation takes away broadcast revenue, matchday income, sponsorship leverage, and player valuations. For small and medium-sized clubs, it's not just a single loss, but a downward spiral for their entire business model.


Osasuna's official explanation is also quite measured: purchasing coverage through Howden, a premium of 1.2 million euros, with a payout of 6 million euros upon relegation; La Liga was informed, and the club's auditors and the chairman of the control committee were notified.


What makes the matter particularly sharp is the unconfirmed transaction chain reported in the media.


According to Semafor's report, the related transaction chain featured several roles familiar to Wall Street: the sports insurance broker Game Point Capital managing risk for the team, Greenlight Commodities (originally a firm focused on renewable energy credits) facilitating institutional access to prediction markets, and the quantitative trading firm Susquehanna willing to take on the counterparty risk.


Game Point Capital CEO Will Hall told Semafor they wanted to see how prediction markets handle such "large, binary outcome" risks.


This is both the most fascinating and the most dangerous aspect of prediction markets. They can turn the world's uncertainties into prices. Wars, elections, interest rates, sports matches, weather, policy votes—all can be placed into a "yes or no" box. Proponents say it's more honest than pundits and faster than polls; critics see a different picture: real-world anxieties sliced into chips, information advantages turned into profits.


The Osasuna case is especially sensitive because the underlying asset is not oil prices, exchange rates, or some distant macroeconomic indicator, but whether a team falls from La Liga.


Players strive on the pitch, fans pray in the stands, while another group calculates how much that relegation is worth.


It touches on the core issues of prediction markets: when real-world events are financialized, who can trade, who possesses information, and who has the capacity to influence outcomes?


More difficult questions also emerge: How should the compliance of team insiders betting against their own team or buying positions linked to adverse outcomes for themselves be assessed? Even if the trade is packaged as insurance or hedging, as long as the underlying asset directly ties to match results and relegation fate, the market is unlikely to view it as a purely financial instrument.


When Prediction Markets Collide with Regulation


On May 26th, just three days after Osasuna secured safety, Spain's Ministry of Social Rights, Consumer Affairs and 2030 Agenda initiated sanctioning procedures against Polymarket and Kalshi, ordering the temporary blocking of the two platforms' websites in Spain as a precautionary measure pending final rulings in the cases.


The explanation from Spain's General Directorate for the Regulation of Gambling (DGOJ) is straightforward: prediction markets allow users to buy and sell shares related to future event outcomes, with prices reflecting the probability of different outcomes; under Spanish regulatory interpretation, this type of trading on uncertain future outcomes is considered to have a gambling nature, thus requiring specific administrative authorization to operate locally. The announcement also mentioned the process is expected to take 3 to 4 months.


Kalshi's status in the US is entirely different. It emphasizes being regulated by the CFTC as a Designated Contract Market, trading event contracts.


Interestingly, professional football is not just passively involved with prediction markets. In April 2026, La Liga proudly announced a multi-year cooperation agreement with Polymarket, making Polymarket its "official predictions partner" in the US and Canada. In May, Serie A USA also announced a multi-year regional partnership with Polymarket, making Polymarket the official and exclusive prediction market partner of Serie A in the United States.


At the same table, it's called a financial market in the US, and seen as unlicensed gambling in Spain and many other places. This identity fracture is the central conflict in the expansion of prediction markets.


The Web3 circle is no stranger to such grey zones. Polymarket pushed prediction markets into the mainstream spotlight during the US elections. Many began to believe market prices could reveal the truth earlier than experts.


But the Osasuna incident pushes the issue a step further. Prediction markets are no longer just a way for retail users to observe the world; they are beginning to approach institutional risk management. When insurance brokers, sports advisors, intermediaries, and quantitative trading firms appear together, it's no longer just about "users placing bets."


This might be the moment prediction markets truly grow up, and also the moment they most need constraints.


If they are to become financial infrastructure, they must answer the oldest questions of financial markets: who can trade, who possesses insider information, who has the capacity to influence outcomes, and who is responsible for market integrity.


The sports field is especially tricky because match outcomes don't stem from natural laws, but from people. Players, coaches, management, referees, injuries, tactics, and psychological pressure can all alter the result.

Criptos en tendencia

Preguntas relacionadas

QWhat is the core controversy surrounding the Osasuna case according to the article?

AThe core controversy is that Osasuna reportedly purchased relegation insurance, and media reports suggest a related party placed a bet of over $1 million on a prediction market (Kalshi), effectively betting *against* the team winning a crucial match. This intertwines a sporting outcome with financial hedging, raising questions about market integrity, insider information, and the ethical and regulatory boundaries of using prediction markets for such purposes.

QHow did Spanish regulators view prediction markets like Kalshi and Polymarket in this context?

ASpanish regulators, specifically the General Directorate for Gambling Regulation (DGOJ), view such prediction markets as having a gambling nature. They initiated sanctioning procedures against Kalshi and Polymarket and ordered a temporary block on their websites in Spain, stating that trading on uncertain future events requires a specific license, which these platforms did not possess.

QWhat was Osasuna's official statement regarding their financial arrangements for relegation risk?

AOsasuna's official statement confirmed that the club purchased relegation risk insurance through the insurance broker Howden, paying a premium of 1.2 million euros for a potential payout of 6 million euros if relegated. The club emphasized its involvement was 'strictly limited' to this insurance purchase and stated that La Liga and its internal auditors were informed.

QAccording to the article, what is the key difference in how prediction markets are treated in the US versus Spain?

AIn the United States, platforms like Kalshi operate under the oversight of the Commodity Futures Trading Commission (CFTC) as a designated contract market, framing their products as 'event contracts' within a financial regulatory framework. In Spain and similar jurisdictions, the same activities are classified as gambling, requiring a different set of licenses and facing potential blocks if unauthorized.

QWhat broader implication does the Osasuna case highlight for the future of prediction markets?

AThe case highlights that prediction markets are evolving from platforms for retail speculation to tools for institutional risk management. This growth necessitates confronting fundamental financial market questions: defining who can trade, managing insider information, preventing outcome manipulation, and ensuring overall market integrity, especially in sensitive areas like sports where human agency determines results.

Lecturas Relacionadas

On the First Day of Listing, Changxin Technology's Market Value Exceeds 3 Trillion Yuan, Which Securities Firm Has the Largest Floating Profit?

On July 27th, Changxin Technology, the largest-ever IPO on China's STAR Market, debuted with its share price soaring 465.82% to close at 49 yuan. Its market capitalization reached 3.28 trillion yuan, instantly making it the most valuable A-share company. The stellar performance delivered substantial gains for involved securities firms, primarily through equity investments rather than underwriting fees. China Merchants Securities emerged as the biggest winner. Its direct investment subsidiary, Zhaozheng Investment, alone holds a 0.54% pre-issue stake, translating to a paper profit exceeding 155 billion yuan based on the first-day closing price—surpassing the firm's entire 2025 net profit of 123.5 billion yuan. Other major beneficiaries include Huaan Securities, with an estimated profit of around 123 billion yuan from its 0.44% stake, and the lead underwriters, CICC and CITIC Securities, which each gained approximately 46 billion yuan from mandatory follow-on investments. Firms like Founder Securities, Haitong Securities, and GF Securities also reported significant holdings valued in the billions. Despite these paper gains, shares of some brokerages like Huaan and China Merchants fell on the listing day, reflecting broader market pressures. Analysts remain bullish on Changxin's long-term prospects, citing the AI-driven demand surge for DRAM (Dynamic Random-Access Memory) and a supportive supply-demand dynamic with projected shortages through 2028. As China's largest and most advanced integrated DRAM designer and manufacturer, Changxin is poised to capture growth from domestic substitution and global market shifts, potentially challenging the current "big three" oligopoly (Samsung, SK Hynix, Micron). The IPO proceeds, focused on capacity upgrades and R&D, are expected to accelerate China's semiconductor self-sufficiency.

marsbitHace 21 min(s)

On the First Day of Listing, Changxin Technology's Market Value Exceeds 3 Trillion Yuan, Which Securities Firm Has the Largest Floating Profit?

marsbitHace 21 min(s)

Will Changxin Technology Continue to Rise Today?

Changxin Technology made a historic debut on the stock market, with its share price soaring 465.82% to close at 49 yuan. Its market capitalization reached 3.28 trillion yuan, surpassing Industrial and Commercial Bank of China to become the largest company by market cap on the A-share market. Daily trading volume exceeded 140 billion yuan, a first in A-share history. This created a moment of realization for 7.7 million investors who won the lottery for its shares. On the first day, investor strategies varied: some sold immediately and later regretted missing intraday highs, others secured profits to avoid future volatility, while a third group held or even bought more shares, betting on long-term growth. The staggering IPO, massive public enthusiasm, and debut during a peak industry cycle led some to compare Changxin to PetroChina's 2007 listing, which was followed by a long decline. Key similarities noted include comparable fundraising scales (approx. 666 billion yuan for Changxin vs. 668 billion for PetroChina) and both companies listing at a perceived high point in their respective commodity cycles (oil then, memory chips now). However, analysts caution against over-simplifying the comparison. They highlight core differences: Changxin operates in the high-growth semiconductor sector with strong "domestic substitution" tailwinds. Brokerages like Huaxi Securities project significant revenue and profit growth from 2026 to 2028, driven by DDR5 adoption, product mix optimization, and economies of scale. Nomura Securities issued a "buy" rating with a 116 yuan target price, citing AI-driven demand for DRAM, tight supply as major players shift to HBM production, and Changxin's vast room for market share growth. Some analysts position the current memory cycle, fueled by AI, as just beginning, contrasting with the mature energy cycle PetroChina entered. The article concludes that for investors, monitoring the memory cycle's progression and Changxin's breakthroughs in high-end technologies like HBM will be crucial, rather than relying on superficial historical parallels.

marsbitHace 46 min(s)

Will Changxin Technology Continue to Rise Today?

marsbitHace 46 min(s)

Claude Designer Lags Behind Engineers, Fires Back by Creating a Million-User Tool

The article tells the story of Nate Parrott, a designer at Anthropic who created Claude Design as a side project to keep pace with his engineering teammates. When Anthropic released Opus 4.5 in November 2025, the two engineers on Parrott's Claude Code team significantly increased their output using the new AI capabilities. Parrott, the sole designer, found himself struggling to match their speed, becoming a bottleneck in the workflow. To catch up, he began experimenting in his spare time. He initially tried prompting Claude to generate designs from text descriptions and screenshots, with limited success. His breakthrough came when he shifted focus from asking Claude to "design" to asking it to generate HTML. He realized HTML could be a rich visual canvas for creating everything from slides and interactive prototypes to full web pages. He built a simple interface with a chat panel on the left and a live HTML preview on the right. The key to making the output useful was incorporating Anthropic's brand system—fonts, colors, assets, and design principles—into the prompts. This ensured generated designs were immediately on-brand. He shared an internal prototype with his team, and other product designers quickly adopted it for creating clickable prototypes, a task traditionally requiring manually drawing every state. The project's "official" turning point came during an Anthropic Labs offsite, where Parrott noticed many attendees were using his tool to build presentation slides on the fly, sometimes right before their turn to speak. This organic adoption convinced the Labs team to formally staff the project, turning the side project into a real product. Claude Design is positioned as a "pre-production" tool for visual communication and exploration—handling slides, landing pages, PDFs, emails, and social media graphics. It integrates with tools like Canva, Adobe, and Vercel. Its core value is accelerating the early stages of design: exploring directions, building consensus, and establishing systems. For actual production code, Anthropic still recommends Claude Code. The story highlights how AI disrupts workflows unevenly and how individuals can respond by building new tools to create their own advantages. Parrott's tool, born from necessity, eventually gained over a million users in its first week.

marsbitHace 56 min(s)

Claude Designer Lags Behind Engineers, Fires Back by Creating a Million-User Tool

marsbitHace 56 min(s)

Fields Medalist Warns: AI Could Kill Mathematics

The 2026 Fields Medal award was followed by a startling announcement: laureate Jacob Tsimerman joined OpenAI to pursue AI safety research, predicting AI would surpass humans in all mathematical proof areas within two years. Soon after, Fields Medalists Terence Tao and Timothy Gowers expressed deep concern at ICM 2026. Gorges warned that AI might "kill" mathematics not through stagnation, but through an overwhelming surplus of proofs, likening it to a lake dying from eutrophication. This concern is echoed in the "Leiden Declaration," signed by over 3,000 mathematicians including Tao, Peter Scholze, and Kevin Buzzard, advocating for mathematics as a profoundly human endeavor. However, Gowers, who did not sign, fears a future where AI-generated mathematics proliferates while human expertise and the shared intuition vital to the field vanish, turning math into an unvisited "cemetery of thought." Gowers' perspective shifted dramatically after testing ChatGPT 5.5 Pro. The AI solved a doctoral-level number theory problem and later produced a counterexample for the "unit distance problem," achievements Gorges considered publishable in top journals. He now concedes that large language models can handle advanced research, a realization that left him feeling the "rug pulled out from under" him when AI solved problems he personally contemplated. The debate extends to the nature of mathematical discovery. As noted by Peter Woit, AI agents have no interest in the "credit game" of academia. If theorems cease to be attributed to individual mathematicians, truth may simply return to its impersonal state in the universe. The central question remains: in an age of potentially limitless AI-generated discovery, what is the role and purpose of the human mind in mathematics?

marsbitHace 1 hora(s)

Fields Medalist Warns: AI Could Kill Mathematics

marsbitHace 1 hora(s)

NVIDIA's 20-Year CUDA Moat Collapsed Over a Weekend, Claude Single-Handedly Got AMD's New GPU Running

In a single weekend, Claude, an AI agent from Anthropic, successfully ported and optimized its cutting-edge model to run on a brand-new AMD MI355X server rack without any manual code intervention. This feat demonstrates a potential breakthrough in overcoming NVIDIA's long-established CUDA software ecosystem dominance, built over two decades. Anthropic's team simply instructed Claude to get the AMD machine running. By Monday, it not only worked but was showing a continuously improving performance curve. The achievement impressed AMD CEO Lisa Su and accelerated a major deployment partnership: Anthropic plans to deploy up to 2GW of AMD Instinct GPUs starting in 2027. The key enabler is AMD's new ROCm.AI platform, a toolbox designed specifically for AI agents like Claude. It provides AI-readable documentation, including chip instruction sets (ISA), and tools like the Hyperloom service that allows agents to autonomously profile performance, identify bottlenecks, test configurations, and generate optimized kernels. In a demo, Hyperloom boosted the output speed of a model by 38%. This represents a fundamental shift. While CUDA's strength lies in its vast, human-expert-driven ecosystem of tools and tacit knowledge, AMD's strategy is to make its hardware and software stack directly accessible and optimizable by AI agents. An agent can parallelize tasks—debugging, profiling, coding—that would take human engineers years to master, compressing the traditional software adaptation timeline from years to tasks. The competition is no longer just about peak hardware specs but also about how well AI can read, utilize, and tune a platform.

marsbitHace 1 hora(s)

NVIDIA's 20-Year CUDA Moat Collapsed Over a Weekend, Claude Single-Handedly Got AMD's New GPU Running

marsbitHace 1 hora(s)

Trading

Spot

Artículos destacados

Cómo comprar LA

¡Bienvenido a HTX.com! Hemos hecho que comprar Lagrange (LA) sea simple y conveniente. Sigue nuestra guía paso a paso para iniciar tu viaje de criptos.Paso 1: crea tu cuenta HTXUtiliza tu correo electrónico o número de teléfono para registrarte y obtener una cuenta gratuita en HTX. Experimenta un proceso de registro sin complicaciones y desbloquea todas las funciones.Obtener mi cuentaPaso 2: ve a Comprar cripto y elige tu método de pagoTarjeta de crédito/débito: usa tu Visa o Mastercard para comprar Lagrange (LA) al instante.Saldo: utiliza fondos del saldo de tu cuenta HTX para tradear sin problemas.Terceros: hemos agregado métodos de pago populares como Google Pay y Apple Pay para mejorar la comodidad.P2P: tradear directamente con otros usuarios en HTX.Over-the-Counter (OTC): ofrecemos servicios personalizados y tipos de cambio competitivos para los traders.Paso 3: guarda tu Lagrange (LA)Después de comprar tu Lagrange (LA), guárdalo en tu cuenta HTX. Alternativamente, puedes enviarlo a otro lugar mediante transferencia blockchain o utilizarlo para tradear otras criptomonedas.Paso 4: tradear Lagrange (LA)Tradear fácilmente con Lagrange (LA) en HTX's mercado spot. Simplemente accede a tu cuenta, selecciona tu par de trading, ejecuta tus trades y monitorea en tiempo real. Ofrecemos una experiencia fácil de usar tanto para principiantes como para traders experimentados.

268 Vistas totalesPublicado en 2025.06.04Actualizado en 2026.06.02

Cómo comprar LA

Discusiones

Bienvenido a la comunidad de HTX. Aquí puedes mantenerte informado sobre los últimos desarrollos de la plataforma y acceder a análisis profesionales del mercado. A continuación se presentan las opiniones de los usuarios sobre el precio de LA (LA).

活动图片