Sydney Sweeney is helping sell sports predictions, which is a pretty good indication that prediction markets have moved beyond the people who enjoy arguing about probability on the internet.
Novig’s Sept. 9 campaign announcement introduced the actress as a partner and equity holder in its sports-focused exchange. The campaign, called “Just Sports,” runs across digital, social, video, and outdoor advertising through football season. It’s designed to get people to notice an app, recognize the brand, and give it a try, which is exactly what hiring someone as famous and popular as Sweeney is supposed to do.
Without giving in to the controversy that surrounded the campaign, the next most interesting thing is what actually happens when users open the Novig app.
Prediction markets offer a place to turn something you already enjoy, whether that’s football, politics, or arguing about who’ll win an award, into something you can trade. Your attention becomes a potential edge, and your opinion gets a price.
That’s a powerful pitch in a culture where everyone already spends hours keeping up with things. Maybe, just maybe, all that watching, scrolling, and arguing could finally pay?
The industry also sells a much bigger idea: bringing together people willing to risk money can produce better forecasts. That promise and the business of keeping people entertained can coexist, but they reward different behavior. Understanding that difference tells you more about prediction markets than any celebrity ad does.
Finally, a price on your group chat
The basic product is easy to understand. You buy a contract tied to an outcome, and in a standard yes-or-no market the winning contract pays $1. Pay 60 cents and hold it until the result, and you either make 40 cents or lose your 60 cents, before fees. CryptoSlate’s guide to prediction markets and sports betting walks through the way they work.
The cultural appeal is just as simple. Most of us already have opinions we’d like some credit for having. We knew that team was overrated, that candidate couldn’t win, that film would do well. Prediction markets essentially let you buy a small financial receipt for your judgment before the result is known.
They can also give ordinary leisure a second purpose. Watching a match becomes research, knowing the players becomes expertise, and checking an app becomes keeping up with your positions. That kind of vocabulary is flattering because it recognizes something fans already believe about themselves: they know more than the casual observer.
Sometimes they do. Someone who follows a sport closely can know things a casual viewer has missed. But knowing a lot about the subject and making money at the available price are separate skills.
Imagine buying ten contracts at 90 cents each. Eight win and pay $1 apiece. You’ve been right eight times out of ten, a result that would make you insufferable in a group chat, and you’ve still turned $9 into $8 before fees.
That difference is easy to lose when the product is introduced through familiar faces and familiar entertainment. The endorsement can make a platform feel approachable; it can’t tell you whether the trade you’re considering is worth its price.
The distribution now reaches well beyond individual celebrities. Kalshi’s partnership with the NHL includes official data, league branding, and visibility during national broadcasts. Its CNN agreement brings market data into news programming and gives newsroom teams access to political and cultural probabilities.
Taken together, these arrangements place prediction markets on both sides of the viewing experience. They can be something you’re invited to participate in during a game and something you’re shown as evidence while watching the news.
The crowd has to come from somewhere
There’s a serious intellectual case for prediction markets. Economists Justin Wolfers and Eric Zitzewitz have studied how markets combine dispersed information into forecasts. Someone who thinks a contract is mispriced has a reason to put money behind that view, and the resulting trades can make the price much more telling.
But “the crowd” is a convenient phrase for a group of people who found a particular platform, could access it, had money to spare, and chose to trade a particular event. It’s worth thinking about how that group gets assembled.
Celebrity marketing recruits people because they recognize or like them, and sports partnerships recruit people where they’re already emotionally invested. However, neither is a test of forecasting ability. Those customers can bring knowledge, entertainment spending, or a mixture of both, and the outcome depends on how they trade and who trades against them.
Having more participants can help. Someone with good information needs another person willing to take the other side, and a busier market can make entering or leaving a position easier. Casual money can create opportunities that draw informed traders in.
Still, popularity alone can’t establish accuracy. Ten thousand people repeating the same view don’t necessarily bring ten thousand independent pieces of information. Nor does attracting money to a championship final automatically tell us more about a less popular economic or political event.
The distinction becomes especially relevant when a price leaves the trading app and appears in a news segment. Viewers see a percentage that looks precise, without necessarily seeing the amount available to trade, the concentration of money behind it, or the contract’s exact settlement terms.
There are ways to judge whether those percentages deserve confidence. Over enough comparable events, outcomes priced around 70% should happen roughly seven times in ten if the forecasts are well calibrated. You can also compare them with other forecasts made at the same point. That kind of assessment takes patience and includes the dull misses alongside the spectacular wins.
It measures something different from how many people downloaded an app because they liked the ad.
The prediction market always wants another trade
The business incentives are easier to see in the less glamorous parts of a platform’s website. Kalshi’s explanation of its fees says it earns money through transaction charges. The exact cost varies by market and order, but the basic commercial relationship is straightforward: trading activity produces revenue.
Novig’s optional points program turns participation into a progression system. Executed trades earn points toward monthly tiers, from Starter to Obsidian, with rewards including trading credits and access to a monthly cash pool.
This is familiar consumer-app design. You earn status, move toward a reward, and get another reason to come back. Applied to a trading product, it creates an extra consideration alongside whether an individual position is worth taking: the trade may help you reach a tier.
Someone can enjoy those features and understand exactly what they’re doing. Entertainment is a legitimate reason to spend money. The difficult part is keeping track of the full cost when the activity also offers the satisfaction of feeling informed and financially capable.
Here the platform’s interests and the customer’s can pull apart without anyone breaking a rule. Someone trying to make accurate forecasts might be best served by watching, waiting, or deciding they have no edge. Someone selling transactions benefits when more of those opinions become trades. Sweeney’s equity stake is the perfect example of that difference: owning part of the company means participating in the platform’s fortunes, a different proposition from buying contracts inside it.
CryptoSlate has already examined the blurred boundary between speculation and gambling. The cultural question goes beyond which label wins. Prediction markets give daily attention a financial outlet, making the things people follow for pleasure feel like opportunities they might be wasting by staying on the sidelines.
That invitation can become exhausting. There’ll always be another game, announcement, or award, and being interested in something doesn’t create an obligation to put money on it. Nor does reading a market’s forecast require becoming its customer.
The most valuable thing prediction markets produce is a probability anyone can look at for free. The most profitable thing for the company is getting that person to place another trade. Keeping those two uses separate leaves more room to enjoy the match.
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