Original Title: The Game Behind The Game
Original Author: Vaidik Mandloi, TOKEN DISPATCH
Original Compilation: Luffy, Foresight News
Prediction markets have long been more than just a place for fans to trade: now, teams themselves have begun to use them.
Take a simple example: a basketball club promises the head coach that if the team makes it to the playoffs, a bonus of 20 million dollars will be awarded. This is a straightforward incentive; if the team wins enough games and makes it to the playoffs, the bonus will be paid.
However, from a financial perspective, this promise represents a massive liability. Once the team makes the playoffs, the 20 million dollars must be disbursed, regardless of how much the team earns that year or what its financial condition is.
To manage this risk, teams typically purchase insurance. Brokers design the policy and find insurance companies willing to underwrite it; those insurance companies might then transfer some of the risk to reinsurance companies to avoid bearing the entire exposure alone. The final price of this coverage is negotiated privately among institutions. The premium implicitly contains an assessment of the team's chances of advancing, but this number is never made public; it exists only in the quotes provided to the team.
Now, there is another solution for the same risk.
The team's chances of advancing have actually already been priced elsewhere. In prediction markets, this probability is traded daily, visible to everyone, and fluctuates in real-time with changing expectations.
The team does not have to rely solely on private insurance quotes; it can refer to public market probabilities to hedge part of the bonus risk.
How Sports Insurance Works
To understand how this system operates, let's first look at what has changed in the sports industry over the past 20 years.
Today, professional sports have annual revenues close to 560 billion dollars, with an annual growth rate of about 7%. Revenues come primarily from media rights, sponsorships, licensing, streaming platforms, and global business partnerships.
As revenue sources have expanded, the contracts tied to them have also soared.
Nowadays, team salaries are no longer just base salaries for the season; they also include a plethora of performance clauses linked to specific milestones. For example, if the team makes it to the conference finals, the head coach might receive an additional 5 million dollars; players can earn extra compensation if they reach 1,000 rushing yards, 25 touchdowns, or meet a minimum number of appearances; some contracts even stipulate that if the team goes further in the playoffs, bonuses will further increase. These clauses are automatically triggered once conditions are met, and the corresponding compensation must be paid.
Teams manage such exposures through insurance instead of passively bearing risks and hoping incentives do not cluster. They work with professional brokers, who then seek insurance companies willing to underwrite performance payouts; these insurance companies usually transfer part of the exposure to reinsurers, dispersing the risk into a larger capital pool. A simple bonus clause in a contract becomes an entire financial chain in the background.
Insurance companies measure the size of the exposure using a concept called "insurable value," which simply means: future income that depends on continued performance, including salary, incentives, endorsement income, etc., all of which are affected if a player cannot participate.
The explosive growth of such exposures is evident from the data. For instance, during the 2014 FIFA World Cup, the total insurable value of all participating teams was estimated at about 7.3 billion dollars. By the time of the 2022 World Cup, this figure skyrocketed to around 25 billion dollars. In less than ten years, the financial value directly tied to game performance has more than doubled.
When so much income is tied to performance, uncertainty cannot be left to chance; it must be managed. As a result, a complete industry has emerged, with the global sports insurance and reinsurance market currently estimated at about 9 billion dollars and expected to double by 2030. Its coverage ranges from event cancellations, athlete disabilities to sponsor guarantees and performance bonuses.
There are professional brokers like Game Point Capital that handle hundreds of millions of dollars in sports insurance each year; on the other side are underwriting institutions like Lloyd's of London, which annually write over 200 million dollars in sports-related accident and health premiums, along with large reinsurance companies that also underwrite hurricanes, aviation accidents, and other major disasters. This is because playoff bonuses are priced similarly to risks associated with storms and earthquakes.
Therefore, the pricing process is cautious and private. Brokers negotiate with insurance companies, insurance companies negotiate with reinsurance companies; each party uses its own models to estimate the probability of milestone achievement, which is factored into the premium. Teams only see the costs but not the probabilities behind them.
Why Private Reinsurance Prices Are Higher
The cost of sports insurance is not only dependent on the probability of a team achieving its goals but is also influenced by a variety of external risks.
In an ideal scenario, if a team has a 10% chance of reaching a milestone, the premium would roughly reflect a 10% risk plus a small profit. However, the reinsurance market is not an ideal world.
The capital of reinsurance companies is limited. For every 1 dollar invested in playoff bonus insurance, there is 1 dollar less available for business related to hurricanes, aviation, catastrophic bonds, and more. They must continuously balance their portfolios among different regions and types of risks. Thus, when evaluating sports risks, they consider a combination of: probability, own capital, outcome volatility, and correlation with existing risks.
Another constraint is that the sports reinsurance market is highly concentrated. A few global institutions hold most of the underwriting capacity. Whether a team receives coverage and how much they get often depends on the reinsurance company's own portfolio composition.
All these factors combined ultimately result in the premiums charged to teams that not only include the pure milestone probabilities but also a lot of unseen costs.
When Probabilities Are No Longer Hidden in a Black Box
Until now, outcome probabilities have permeated every aspect: reinsurance modeling, broker negotiations, premium determinations. But this number has never been made public.
Now imagine: what happens when this probability is priced in the public market? Prediction markets have achieved this in a very interesting way.
Platforms like Kalshi have launched contracts for discrete real-world events, one category of which pertains to sports outcomes. The contracts pose a simple question: Can Team X make it to the playoffs?
Each contract ultimately settles at 1 dollar or 0 dollars. For example, if a price trades at 0.06 dollars, it implies a market-implied probability of 6%.
This number is not established by underwriting committees but is derived from real buyers and sellers trading with real money, and it is corrected in real time according to individual assessments of probabilities and prices.
This mechanism is now being put to practical use. Game Point Capital uses the Kalshi market to hedge performance bonuses related to basketball. In one case, a contract related to the playoffs traded at around a 6% price on the exchange, while the over-the-counter offer implied a price of about 12-13%. In another case, a second-round advancement contract traded at nearly 2% on the exchange, while the private reinsurance market price was at 7-8%.
This is not an insignificant difference. Based on a 20 million dollar exposure, the difference between 6% and 12% implied probabilities translates to millions of dollars in premium costs.
You might ask: aren't these just numbers pointed out by traders? Why take them seriously? Why are they more trustworthy than the models of insurance companies?
Numerous studies show that market-based odds are powerful predictors of actual outcomes. Academic research over decades on the sports betting market has shown that bookmaker odds are highly efficient in predicting game results. More recently, direct comparisons between prediction markets and traditional sports betting have shown nearly identical success rates in predicting outcomes for about 1,000 NBA games during the 2024-25 season.
In games with market-implied probabilities exceeding 95%, both accurately predict over 90% of results.
The conclusions from election markets are even clearer. During the 2024 U.S. presidential election, a study comparing Polymarket with traditional polls indicated that Polymarket offered a more accurate prediction of final outcomes, particularly in swing states.
When tens of thousands of people continuously update expectations in real-time markets, collective probabilities often astonishingly align with reality.
Prediction markets achieve continuous price discovery. Any new information entering the system gets continuously updated and priced, without waiting for the next review by underwriters.
However, to truly have practical value, the market must be able to handle scale. In recent major events like the Super Bowl, Kalshi managed about 22 million dollars in trades without significant price fluctuations. This indicates that both long and short positions have real depth, sufficient to support large-scale hedging without impacting prices.
As these markets grow, a new set of unlicensed financial tools has emerged around prediction markets.
For example, Kalshinomics analyzes event contracts like analysts assess stocks and bonds, tracking how probabilities change over time, liquidity performance before and after significant events, and whether prices deviate from fundamentals.
There are also platforms like PredictionIndex that focus on tracking and ranking various prediction markets, allowing you to see total trading volume, contract types, public chains, and trading mechanisms, consolidating the whole space into one place, providing a visual representation of market size.
When the probability of an outcome can be priced in real-time and can effectively absorb funding, it becomes a true tool that institutions can use. Teams can now hedge performance bonuses directly with publicly traded probabilities, sponsors can hedge against risk exposure related to viewership targets, and production studios can hedge box office milestones. In principle, any earnings dependent on clear and verifiable outcomes can be converted into tradable contracts.
Institutions no longer need to negotiate customized insurance contracts; the outcomes themselves can be traded publicly.
What makes this structure truly usable for institutions is the final piece of the puzzle: identity. Traditional insurance functions effectively because counter-parties are verified, contracts enforceable, and exposures auditable, while the public market has always lacked this layer.
Companies like Dflow are binding real-world identities to trading behavior. This means market participants can be identified, screened, and associated with real entities instead of remaining completely anonymous. This also makes contract settlement, exposure management, and incorporating positions into existing compliance frameworks possible.
From a practical perspective, it increasingly resembles not a typical trading venue but rather a functional insurance layer operating directly on public probabilities.
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