How prediction markets work in sports betting

Traditional sports betting runs on fixed odds. The operator sets a line, takes the opposite side of the bet, and manages the margin. The player bets against the house. This is where the fixed odds vs prediction markets comparison usually starts: the two run on different business models, not just different products.

In prediction markets, participants trade contracts with each other. Prices move based on supply and demand, like a financial exchange, and the operator earns a fee on volume rather than a margin on outcomes. Kalshi and Polymarket are the most visible examples. Both are platforms where users buy and sell positions on whether an event will happen.

For operators dealing with tighter margins and higher costs to acquire players, this model makes sense on paper. Peer-to-peer betting means the operator doesn’t lose money when players win. Engaged users bring more trading activity, which keeps the market liquid. Players also tend to stick around longer on exchange platforms than on traditional sportsbooks, at least in markets where the model has had time to prove itself.

Europe has had Betfair running a licensed exchange model since 2000. The US is in the middle of an argument about federal versus state jurisdiction: Kalshi now handles sports contracts while fighting cease-and-desist letters from seven states at once. Asia-Pacific has a mix of licensed operators and platforms running in legal grey zones.

None of this maps cleanly onto prediction markets in iGaming as they’d need to function in Latin America.

Three regulatory environments, three different issues

Latin America is not one market, and prediction markets regulation in Argentina, Brazil, and Mexico proves it. Operators who treat the region as a single block tend to find out the hard way that sports betting regulation LatAm-wide runs across three incompatible frameworks, and prediction markets fit none of them cleanly.

Brazil is the most structured story. Law No. 14,790/2023 went live on January 1, 2025, creating a federal licensing regime under the Secretariat of Prizes and Bets (SPA). The license costs BRL 30 million and covers fixed-odds betting. Brazil’s rules do include a licensed betting-exchange category for peer-to-peer sports betting, separate from the event-derivative products the country banned outright in April 2026. For an iGaming operator platform entering Brazil, the compliance stack alone takes 12 to 18 months to build correctly, and a product category with no clear legal footing isn’t worth adding on top of that.

Argentina runs on a provincial system. Each province controls its own gambling regulation, and Buenos Aires Province, CABA, and Córdoba each set their own licensing requirements. There is no federal iGaming law equivalent to Brazil’s. In the iGaming Argentina market, a prediction market product would need approval from each jurisdiction separately, on top of the court order that already blocked Polymarket nationwide in March 2026. The iGaming platform Argentina operators build on has to clear that provincial patchwork one region at a time, not one federal regulator.

Mexico operates under a federal concession model, managed by Segob. The concession framework was built for traditional sports betting and casino gaming. Regulatory appetite for new product structures is low, and enforcement of existing rules is uneven. For most operators, Mexico is a volume market where managing compliance cost matters more than product innovation.

In all three markets, prediction markets sit outside the frameworks built for fixed-odds betting. Argentina and Brazil have already shown what happens when a platform treats that gap as a loophole: both blocked the platforms that tried.

Why the agent model matters for prediction markets in iGaming

Most commentary on this misses one key detail. The agent model iGaming distribution in Latin America runs on, especially in Argentina, puts a person between the platform and the player at every step. Agents bring in players, handle deposits and withdrawals, extend credit, and stay in touch with players over time. They function as the trust layer that makes a platform usable, in a region where players trust a person before they trust an app.

That trust is exactly what a prediction-market-style product would need, and agents already have it. Prediction markets run on live prices and constantly shifting positions, which is a lot of new information to hand a player with no context. An agent who already manages that player’s money and answers their questions is the natural person to translate that information, not someone to route around.

The gap is tooling: nobody has built the systems that would let an agent handle exchange-style products the way they already handle fixed-odds bets. There’s no dashboard showing player positions. No credit and settlement tools built for prices that move instead of a fixed line. That gap is exactly why prediction markets in iGaming can’t just be dropped into the region as-is: they need an agent-facing layer built first, and that’s a product problem a vendor can solve without touching licensing or rebuilding distribution from scratch.

Liquidity is the other wall

Prediction markets need depth on both sides of every contract, or spreads widen and prices stop meaning anything. Betfair took years to build that depth in the UK. Kalshi got there faster because the US already had tens of millions of active bettors and a culture of financial trading built into its target audience from day one. Latin America doesn’t start from either position, and that’s the real design question behind prediction markets in iGaming here: how do you concentrate trading activity that’s currently split across country, currency, and payment rail?

Argentina’s currency volatility, losing over half its value against the dollar in 2023, already pushes players toward stablecoins and dollar-pegged assets. A platform can build directly on that existing behavior instead of treating it as friction. A product that settles and holds positions in stablecoins by default removes one of the biggest frictions to keeping capital in the system long enough to trade. Brazil’s Pix rail is fast and cheap for a single fixed-odds bet, but it wasn’t built for capital that needs to move in and out of open positions repeatedly, and that’s a real integration problem for anyone building settlement into an exchange-style product here.

Exchange betting in Latin America, if it gets built at all, will need settlement and position-holding designed around the payment behavior that already exists in the region: stablecoin-first, not dollar-first or real-first.

What can operators learn from prediction markets in LatAm?

Prediction markets don’t work here as a standalone product yet, but the underlying logic still has real value for iGaming LatAm operators. This is where operators and the iGaming operator platform providers building for them have room to move right now.

Player engagement data can feed dynamic odds on low-volatility markets, a feature several European platforms already run in production. Letting engagement data shape pricing, instead of relying only on mathematical models, can improve margins and player satisfaction at the same time, particularly in niche markets where the risk from professional bettors is low.

Group-position and social prediction features, where players interact around shared bets, have shown better retention in early tests elsewhere. This isn’t peer-to-peer betting in the full sense prediction markets use, no matching engine, no order book. It runs as an add-on inside a normal fixed-odds platform, with social features layered on top.

Position-transparency dashboards, showing players what others are betting on, are something prediction markets do well and traditional sportsbooks rarely attempt. Players who can see what the market expects tend to make better-informed bets and stay longer.

None of these changes need a new gambling license for the operator, and none require a vendor to build exchange-matching infrastructure either. What they need is engineering investment in engagement data and social features, the same direction platform providers are already moving in Europe. That’s the practical shape prediction markets in iGaming can take in Latin America right now, without waiting for Argentina or Brazil to change their current rules.

Conclusion

Prediction markets in iGaming aren’t coming to Latin America the way Kalshi and Polymarket built them, and the last few months made that official rather than theoretical: Argentina’s courts and Brazil’s regulators have both blocked the standalone model outright.

The agent model, currency volatility, and fragmented payment rails are the specific conditions any real product here has to be built for: agent-facing tools instead of a direct-to-player exchange, stablecoin-first settlement instead of copying a US or European payment stack, and engagement-driven features layered onto fixed-odds platforms instead of a separate exchange license nobody can get yet.

For teams building iGaming platforms in the region, that’s a narrower brief than “launch a prediction market,” but it’s a buildable one. The operators and platform providers who move first on agent tooling, transparency features, and stablecoin settlement will be the ones ready when, or if, the regulatory door in Brazil or Argentina opens wider than it is today.