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

Foresight NewsPublished on 2026-06-09Last updated on 2026-06-09

Abstract

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.

Related Questions

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.

Related Reads

OpenAI's 'Blueprint for the Future': Making AI Beneficial for Every Person on the Planet

A new transformative technology emerges every few generations. OpenAI draws a parallel with the advent of electricity in the 1920s, which initially brought convenience but ultimately enabled unprecedented progress in medicine, engineering, and living standards by empowering people to create new possibilities. AI is poised to recreate this phenomenon. Its true significance lies not in the technology itself, but in what people can achieve with it—from understanding a medical bill or starting a business to aiding scientific discovery. OpenAI believes AI should be universally accessible, allowing everyone to use it according to their own needs. This future, however, is not guaranteed. While transformative tech can centralize power, OpenAI's philosophy is that AI must serve humanity, augmenting human capabilities and broadly distributing its benefits. The company's first commitment is to build AI for human service, aiming to empower the many rather than concentrate power in a few. Safety, alignment with human intent, and oversight are paramount. OpenAI is optimistic about AI's potential to expand human welfare but remains clear-eyed about risks. The goal is to help people achieve more, not to replace them. Full automation is not the desired future; human judgment, values, and direction will become even more critical. OpenAI outlines three core goals: 1. Build automated AI researchers to accelerate and increasingly automate the research process itself, maintaining close human collaboration. The internal projection is that by March 2028, a significant portion of their research will be conducted by AI systems working alongside human researchers. 2. Accelerate economic development by advancing science, boosting productivity, and fostering growth, while ensuring the fruits are widely shared. 3. Provide a personal AGI for everyone on Earth, allowing individuals to benefit from this transformative technology in their own way. The company is entering its third phase, moving from foundational AGI research (Phase 1) to product deployment and learning from real-world use (Phase 2). The current challenge is making advanced AI abundant, affordable, safe, practical, and usable for all individuals and organizations. OpenAI concludes that a widely distributed power structure leads to a more resilient, adaptable, and free society. A positive AI future should not be controlled by a handful of entities but built, benefited from, and owned by many. If realized correctly, AI can become a cornerstone for enhancing global productivity, creativity, scientific advancement, and economic opportunity, fulfilling the mission to ensure AGI benefits all of humanity.

marsbit12m ago

OpenAI's 'Blueprint for the Future': Making AI Beneficial for Every Person on the Planet

marsbit12m ago

Arthur Hayes' New Article: AI Bubble Nears Bursting, Crypto Market Faces Short-Term Pressure

In a new essay, Arthur Hayes argues that the AI market bubble is approaching a rupture, which will place significant short-term pressure on crypto assets. He identifies rising oil prices, a trio of massive tech IPOs (SpaceX, Anthropic, OpenAI), and potential anti-AI political rhetoric from Trump as the three key catalysts for a correction. Hayes posits that the prolonged blockage of the Strait of Hormuz will drive energy prices higher, increasing operational costs for data centers and squeezing AI company profits. Simultaneously, the market may struggle to absorb the upcoming wave of multi-trillion dollar tech IPOs. Furthermore, with high inflation hurting his election chances, Trump could pivot to attacking the AI sector with proposals for heavy taxation and regulation to win over voters, spooking the market. Hayes notes that nearly all new dollar liquidity since 2022 has flowed into the AI sector, leaving little for Bitcoin, explaining its recent underperformance. He believes an AI stock crash would trigger a broad risk-off sentiment and credit contraction, dragging down crypto in the near term. Consequently, his fund, Maelstrom, has sold all AI-related stocks and non-core cryptocurrencies, retaining only Bitcoin and Ethereum while building positions in traditional energy stocks. He anticipates Bitcoin will bottom and resume its bull run only after the AI bubble pops and a new monetary easing cycle begins.

marsbit15m ago

Arthur Hayes' New Article: AI Bubble Nears Bursting, Crypto Market Faces Short-Term Pressure

marsbit15m ago

Trading

Spot
Futures

Hot Articles

How to Buy LA

Welcome to HTX.com! We've made purchasing Lagrange (LA) simple and convenient. Follow our step-by-step guide to embark on your crypto journey.Step 1: Create Your HTX AccountUse your email or phone number to sign up for a free account on HTX. Experience a hassle-free registration journey and unlock all features.Get My AccountStep 2: Go to Buy Crypto and Choose Your Payment MethodCredit/Debit Card: Use your Visa or Mastercard to buy Lagrange (LA) instantly.Balance: Use funds from your HTX account balance to trade seamlessly.Third Parties: We've added popular payment methods such as Google Pay and Apple Pay to enhance convenience.P2P: Trade directly with other users on HTX.Over-the-Counter (OTC): We offer tailor-made services and competitive exchange rates for traders.Step 3: Store Your Lagrange (LA)After purchasing your Lagrange (LA), store it in your HTX account. Alternatively, you can send it elsewhere via blockchain transfer or use it to trade other cryptocurrencies.Step 4: Trade Lagrange (LA)Easily trade Lagrange (LA) on HTX's spot market. Simply access your account, select your trading pair, execute your trades, and monitor in real-time. We offer a user-friendly experience for both beginners and seasoned traders.

5.3k Total ViewsPublished 2025.06.04Updated 2026.06.02

How to Buy LA

Discussions

Welcome to the HTX Community. Here, you can stay informed about the latest platform developments and gain access to professional market insights. Users' opinions on the price of LA (LA) are presented below.

活动图片