Prediction Markets Across Sports, Media, and Finance: Institutional Entrenchment and the Risk of Path Dependence

In just a few years, prediction markets have gone from obscure tools concentrated in the niche corners of elite policy, academia, intelligence, and analytics communities to rapidly expanding fixtures throughout American economic, political, and cultural life. New partnerships between prediction market platforms and firms of every size and stage—from early-stage ventures to established industry leaders—are now announced on a near-daily basis.

At the same time, a parallel ecosystem of start-ups and incumbents is eagerly building out the products, infrastructure, and services that plug into, sit on top of, and extend prediction markets’ reach. The result is a rapidly growing network that’s embedding itself throughout our institutions in real time, spearheaded by firms eager to financialize everything in their endless quest to maximize profits—no matter how detrimental to individuals or society at large.

In the third installment of this Roosevelt Institute series, The Hidden House: Prediction Markets and How They’re Shaping Society, I home in on some of the biggest players across three institutions—professional sports leagues, our media ecosystem, and the finance industry¹—to highlight the scale at which the burgeoning prediction markets industry is entrenching itself in American society. I perform first-of-its-kind quantitative analysis of participation in prediction markets by some of the largest firms in professional sports, media, and finance. I then draw on path dependence theory to argue that as prediction markets continue expanding their reach and power, the window for meaningful intervention narrows, making policy action all the more pressing.

The explosive growth of prediction markets is part of a broader trend in the US economy toward “financialization”—the expansion of the financial sector and its mounting power over the real economy. With the rise of prediction markets, this trend is taken to its natural (and absurd) conclusion: the creation of a market for anything and everything, from the benign to the macabre. In the absence of reform that not only reins in the prediction markets industry but tackles financialization more broadly, our economy will continue to incentivize the short-term gains, extractive behavior, and speculation that has sowed so much misery and understandable cynicism among a public that struggles to get by, while the ultra-wealthy take evermore.

Section I: Path Dependence Theory and Regulatory Windows

Stemming from the social sciences, a range of disciplines has offered various definitions of path dependence, but at its core, the concept is simple: Early choices, conditions, or developments in a technology, institution, or broader system set the tone for its future trajectory. These early decisions or events, even seemingly small ones, have an outsized impact on future courses of action. The costs of switching to a different path—some alternative way of doing things—become greater the further down the path you go, as the increasing returns of that path begin to self-reinforce. A positive feedback loop emerges, gradually entrenching decisions that were made early on in the history of an institution or development. Large-scale changes, in turn, become harder to implement.

Scholars of historical institutionalism have used path dependence theory to better understand institutional legacies and the mechanisms that make institutions resistant to change. These scholars assess how “institutions and policies generate incentives for actors to stick with and not abandon existing institutions, adapting them only incrementally to changing political environments.” Of course, path dependence is not destiny. As political scientist Paul Pierson explains, path dependence theory simply holds that “previously viable options may be foreclosed in the aftermath of a sustained period of positive feedback, and cumulative commitments on the existing path will often make change difficult and will condition the form in which new branchings will occur.”

Institutions, therefore, can and do still change. But reversing policies or changing institutions after they have cemented, a state sometimes referred to as “lock-in”², becomes significantly harder and may only materialize during brief, intense periods—what historical institutionalists call “critical junctures.” In these moments, the right combination of economic, political, and social conditions converge in a relatively brief moment of rupture where there is a significantly increased likelihood that agents’ decisions can disrupt the current path and fundamentally alter the trajectory of an institution. But by the time such moments emerge, the path an institution has gone down may have caused considerable, cascading harms. Moreover, even when these critical junctures materialize, there is no guarantee that relevant actors will meet the moment and take advantage of them to implement the necessary institutional reforms or new policies. And even during these critical junctures, new developments and decision-makers alike are still bound by the institution’s history.

How decision-makers act early on in the trajectory of a new institution, then, before institutional arrangements calcify, becomes crucial. The more adoption and infrastructure accumulate, the more the question shifts from whether to regulate to how much damage regulation can still undo.

Section II: The Prediction Markets Gold Rush in Three American Institutions

To assess the expansion of prediction markets across media and finance, I analyze the top 20 companies (by market capitalization) in the S&P 500’s Communications Services and Financials sectors, respectively. To assess their growth in professional sports, I focus on the five major US sports leagues. My analysis finds that of the three institutions at hand, prediction markets are the most embedded in professional sports, while fewer of the top players in media and finance have fully embraced this nascent industry. Nevertheless, across all three institutions prediction markets are rapidly extending their reach, risking becoming embedded fixtures absent meaningful policy intervention. For an industry dogged by scandal and demonstrated harms, securing the imprimatur of major players across these three sectors is critical to establishing its legitimacy.

Professional Sports

Given that 80 percent of the total trading volume (or gambling volume, depending on your perspective) on Kalshi is on sports-related event contracts,⁴ it could be argued that professional sports leagues have a vested interest in the success of prediction markets. Much of the sports industry is hopping on the prediction markets bandwagon with hopes of using the platforms to boost fan engagement and capture audience attention and profits.

Many of the prediction market partnerships in the domain of professional sports go well beyond conventional sponsorship deals. While logo placements and promotional appearances abound, deals also include official league data feeds, exclusive rights to use club intellectual property in connection with matches, standing integrity frameworks, and in some cases, plans to integrate live market activity into the fan experience, allowing viewers to trade as they watch a game. Product-level integration, data pipelines, and integrity apparatuses are different from typical, more passive sponsorship agreements because they build prediction markets into the operations of professional sports leagues and how fans experience the games.

Similarly, the rise of sports-focused exchanges further binds together professional sports and prediction markets. Just as the rise of sports betting in 2018 delivered massive gains to the leagues and drew them into embracing gambling, we can see similar dynamics playing out with prediction markets. The leagues have already begun to derive revenue, engagement, and data-licensing income from the markets, while prediction market companies, of course, depend on the leagues for a substantial share of their trading volume. As prediction markets become more normalized and increasingly adopted, the relationship between them and sports leagues is likely to keep hardening. The virtually identical pattern reflects the virtually identical functional purpose of betting and trading: Contracts on game outcomes are wagers on game outcomes, regardless of legal technicalities.

Of the five major professional sports leagues in the US, three of them—MLB, NHL, and MLS—have entered into an official partnership agreement with at least one prediction market platform.⁵ The NBA and especially the NFL have been more cautious than their counterparts in embracing prediction markets. But in recent months the NBA has more frequently been in talks with both Kalshi and Polymarket. The NFL has exhibited greater skepticism—for example, the league added prediction market commercials to its list of prohibited advertisements for the Super Bowl earlier this year (mirroring its season-long ban on such commercials during NFL broadcasts), and its executive vice president and chief revenue officer noted in August that prediction markets are “not a space that we’re considering right now commercially.” But the league hasn’t ruled out the possibility of doing business with the industry, provided that its regulatory concerns are meaningfully addressed.

Both the NBA and the NFL have asked the Commodity Futures Trading Commission (CFTC)—the regulatory agency that oversees prediction markets in the US—to address concerns that prediction markets run the risk of compromising game integrity by opening the door to insider trading.⁶ For example, they have asked the CFTC to more forcefully ban trades on events that could be susceptible to manipulation. In June, the CFTC released a rulemaking proposal that would address some of these and other leagues’ integrity concerns.⁷

Meanwhile, one year after the MLB formally petitioned the CFTC for integrity protections, MLB Commissioner Robert Manfred and CFTC Chairman Michael Selig signed an MOU in March that commits the league and the agency to ongoing information-sharing about baseball and its prediction markets. In May, the NHL followed suit, signing an MOU of its own with the CFTC. These moves illustrate how, together, the top US sports leagues and the CFTC are building guardrails that help legitimize institutional participation in the nascent prediction market industry.⁸ Moreover, because these are ongoing arrangements that include features like regular meetings and continuous information-sharing, rather than one-off deals, they establish durable relationships that will only become harder to unwind as more leagues follow.

The Ultimate Fighting Championship (UFC) sits outside the list of the top five US-based sports leagues. Its scale is financially comparable, though. According to its parent company, TKO Group Holdings, the UFC generated roughly $1.5 billion in revenue in 2025. Last year, TKO Group Holdings announced that it had entered into a multiyear partnership with Polymarket “to integrate prediction market technology into the live fan experience” for both UFC and its sister company Zuffa Boxing.

The prediction market entrenchment also extends down to individual teams, venues, and athletes. Just last week, five MLB teams entered into partnerships with Kalshi. The NHL’s Chicago Blackhawks have also partnered with Kalshi, while the New York Rangers have signed with Polymarket. (As prediction markets journalist Dustin Gouker has pointed out, many more teams across leagues are already under contract with companies now offering sports-related event contracts.) Kalshi has struck a deal with Madison Square Garden itself, securing naming rights for the entire sixth-floor concourse of the iconic venue. And individual athletes across sports are signing on as endorsers and investors alike: LIV Golf’s Bryson DeChambeau and NBA’s Giannis Antetokounmpo have both cut endorsement deals with Kalshi (with the latter also acting as a Kalshi shareholder), while MMA star Nate Diaz brandished the prediction market’s logo on his shorts in his first fight after a four-year hiatus. And a group of athlete-investors, including WNBA star Breanna Stewart and former NFL giants Marshawn Lynch and Richard Sherman, contributed $4.7 million to Kalshi’s billion-dollar Series E funding round.

There is also the influx of new prediction market platforms aimed specifically at sports (though most offer contracts on other topics as well), such as OG, ProphetX, and Novig (with the latter two beginning as state-regulated sports betting exchanges before launching nationwide this summer) as well as existing sports betting and daily fantasy sports companies that have expanded their offerings to include sports-related event contracts, like DraftKings, FanDuel, Fanatics, and Underdog. The expansion of these companies into the prediction markets space further blurs the lines prediction market companies insist exist between gambling and trading.

As sportsbooks and daily fantasy sports companies enter the prediction markets space, some of these companies are moving to vertically integrate and own the full prediction market stack, from the customer-facing app down to the exchange and clearing infrastructure. While both major US sportsbooks, FanDuel and DraftKings, initially partnered with CME Group to launch their respective prediction market platforms, the companies have signaled their interest in expanding their reach through other partnerships and potentially even bypassing third-party exchanges altogether by launching their own.

In the spring, FanDuel filed with the National Futures Association (NFA) to create a new futures commission merchant (FCM), New Ventures III, which would allow it to operate its own brokerage without CME Group involvement. Then, in June, FanDuel announced its partnership with Crypto.com’s OG Prediction Market while maintaining its partnership with CME Group. The move came as the FanDuel-CME partnership had not been as successful as FanDuel had hoped, prompting the company to announce in August that it would no longer route sports-related event contracts through CME’s venue (though it will continue to use CME for economic and financial contracts).

DraftKings has gone further, acquiring its own CFTC-licensed exchange, Railbird, in October 2025. That acquisition came with the technology and federal license it needed to launch DKeX in June, allowing the company to cut CME Group out of the loop entirely. Just a few weeks after DKeX’s launch, the NFA approved DraftKings as an FCM, bringing the company closer to its apparent goal of full vertical integration. Meanwhile, Underdog recently became the first sports prediction market company to own the entire prediction market license stack, after launching its own exchange in July. (Just a couple of weeks later, IG Group announced its acquisition of Underdog, a move that further integrates prediction markets into institutional trading.)

Media

In our media ecosystem, we see established news outlets, internet platforms, and social media companies cozying up with prediction market giants like Kalshi and Polymarket. My analysis of the top 20 companies in the S&P 500’s Communications Services sector reveals that 25 percent have integrated prediction market products or data into their content or offerings, embedding forecasting and probability data into programming, editorial coverage, or platform features. This includes established legacy news outlets like CNN, CNBC, and Fox, as well as internet platforms such as Google Finance, and posts on users’ accounts on social media platforms like Threads.¹²

As Table 2 indicates, the companies included in my analysis that produce informational content and are largely dependent on advertising and engagement have been the most likely to embrace prediction markets. This is perhaps because the format of prediction markets generates precisely the kind of attention their business models reward. In the face of changing technological and economic circumstances, prediction markets and prediction market–like features offer news outlets and platforms a potential pathway to further recapture audience attention and engagement—the lifeblood of businesses whose revenues, whether from advertising or carriage fees, ultimately depend on holding an audience. Social media and gaming companies, similarly, have found in these features a new revenue source—a way to supercharge the worst impulses of the attention economy by turning even more of the online experience into something to wager on. Meanwhile, infrastructure providers like Verizon, T-Mobile, AT&T, and Nebius are less involved with prediction markets, at least at this point in the industry’s development.

In the face of changing technological and economic circumstances, prediction markets and prediction market–like features offer news outlets and platforms a potential pathway to further recapture audience attention and engagement—the lifeblood of businesses whose revenues, whether from advertising or carriage fees, ultimately depend on holding an audience.

These trends reflect broader shifts in our media and information ecosystem. What is supposed to be a vital democratic institution that equips citizens with the information self-government requires is increasingly being converted into an extractive one, preying on our attention and our wallets. Prediction markets are the latest frontier in this transformation, with the civic justifications only growing thinner over time. Social media companies at least made their case on grounds that their platforms would connect us to one another. Prediction markets’ alibi—that betting odds amount to valuable public information—is thinner still.

Beyond the largest publicly traded communications companies outlined in Table 2, many more big names in the media space, public and private, independent and legacy alike, are embracing prediction markets. In many cases, these partnerships, like those in Table 2, involve prediction market data integration into existing outlets. Data from Polymarket, for example, is integrated across Dow Jones consumer platforms, including the Wall Street Journal, Barron’s, MarketWatch, and Investor’s Business Daily. Odds from the prediction market platform are displayed on Dow Jones outlets’ digital webpages, such as homepages and market-related pages, in addition to select print placements. Substack has also partnered with Polymarket to allow Substack users to incorporate the prediction market platform’s data directly into their content. According to Substack, after the partnership’s launch 20 percent of the top 250 highest-revenue publications on Substack began using Polymarket data to create content in their publications. Other outlets are going further. For instance, after applying for National Futures Association (NFA) membership as an introducing broker this past March, far-right news outlet Newsmax is on track to display regulated prediction market contracts and allow users to trade through its site.¹⁶

In the social media sphere, last year Elon Musk’s X (formerly Twitter) announced Polymarket as the social media giant’s official prediction market partner. As part of the deal, X’s AI agent, Grok, is integrated directly into Polymarket’s platform to provide real-time market context, explanations for shifts in market odds, and news annotations. In turn, Polymarket data is integrated directly on X. Meanwhile, in partnership with cryptocurrency exchange Crypto.com, Truth Social, the social media platform owned by the president (whose eldest son sits on the advisory boards of both Kalshi and Polymarket), announced plans last year to launch Truth Predict, a native, crypto-based prediction market that would allow Truth Social users to place crypto bets on event outcomes. While more recent public filings indicate a scaling down of the president’s personal ambitions in the prediction markets space, he and his administration have demonstrated a steadfast commitment to advancing industry interests.

Other media outlets capitalizing on the growing popularity of prediction markets—and in doing so, helping to further normalize them—appear to be doing so at least in part as a response to the collapse of the traditional online search model that digital news outlets have relied on for years. The ubiquity of AI has led web traffic to news publishers to sharply dwindle, making reader loyalty more important than ever and leaving digital outlets to devise new strategies to boost engagement and monetize their customer base to capture profits—part of the “financialization of everything.” A few months ago, for example, Forbes partnered with tech startup Axiom to unveil ForbesPredict, a native prediction platform where readers make forecasts about the stories covered by Forbes and track results not for money, but for tokens. Those with more tokens flaunt a greater reputation for accurate predictions. Reader predictions are aggregated in real-time to reflect the collective view of Forbes readers.

Similarly, TIME Magazine’s recently launched digital games platform, TIME Games, includes “Market Movers,” a fantasy prediction market–style game powered by data from Kalshi and Polymarket, where players are presented with two real prediction market headlines and are tasked with picking the one markets say is more likely. While the game doesn’t involve real money or wagering, last fall TIME announced a partnership with the UK-based prediction market company, Galactic, that would introduce real-money prediction markets to its readers.¹⁷ TIME’s interest in the prediction markets gold rush comes as the magazine named Kalshi among the top 100 most influential companies of 2026.

Finance

Perhaps the most meaningful endorsement for the prediction market industry is that of institutional finance. For companies still routinely depicted as gambling operations, the imprimatur of major financial institutions and their development into a legitimate asset class would all but complete prediction markets’ legitimation, going considerable ways toward transforming a contested novelty into a settled fixture of American markets. This is doubly true for platforms like Kalshi that already hold a measure of legitimacy as federally regulated exchanges, and whose data are increasingly integrated into mainstream media outlets. Finance’s embrace would help cement their status by clearing the way for more cautious players waiting to see whether the space is safe to enter.

So far, just one of the top 20 companies in the S&P 500’s Financials Sector—Morgan Stanley—is currently materially involved with prediction markets.¹⁸ But several other firms have expressed interest, and one—Charles Schwab—is poised to make prediction market contracts available to customers in the coming months. Meanwhile, some significant players outside the top 20 are already heavily involved. Hesitation on the part of some of the very largest firms shows that some of the institutions with the most reputational capital at stake are still hedging, suggesting that the industry’s place in American finance is not yet as settled as its proponents claim. And yet significant parts of the global finance establishment are throwing their weight behind prediction markets. In the absence of policy action, this trend is likely to continue, and as more and more firms expand into the prediction markets space, it makes the largest companies’ entrance easier, lending the whole enterprise an air of unearned inevitability.

For companies still routinely depicted as gambling operations, the imprimatur of major financial institutions and their development into a legitimate asset class would all but complete prediction markets’ legitimation, going considerable ways toward transforming a contested novelty into a settled fixture of American markets.

In May, Morgan Stanley invested in Kalshi’s Series F funding round, which raised a total of $1 billion. In an earlier funding round, Charles R. Schwab—the founder and cochairman of the eponymous firm, acting in his individual capacity—invested $30 million.¹⁹ As for the financial institution itself, it appears to be a matter of time before it fully embraces prediction markets: In June, one of the world’s leading derivatives exchanges, Cboe, announced that its recently launched prediction markets suite Cboe Predicts (discussed below) is expected to become available through Schwab in the near future. This comes after Charles Schwab CEO Rick Wurster stated in April that the company is “taking a hard look” at prediction markets (but would refrain from offering event contracts related to sports, politics, or popular culture), and after Yahoo Finance reported in June that the company aims to introduce prediction market services that focus on financial and economic events before 2027.

Other finance industry giants listed in Table 3 have exhibited signs that they too are likely to enter the space soon. Goldman Sachs CEO David Solomon has referred to prediction markets as “super interesting” and has personally met with prediction market executives and dedicated a team of employees to study how the bank could enter the space. JPMorgan CEO Jamie Dimon has stated that “it’s possible” the company may “one day” offer prediction market services to customers.

But the most significant movement among major financial institutions is happening beyond the top 20 included in this analysis. In August 2024, Interactive Brokers announced the launch of its wholly-owned subsidiary, ForecastEx, a CFTC-regulated exchange where clients can trade “Forecast Contracts” on certain economic and climate-related events. The global electronic brokerage giant has since expanded its prediction market offerings by launching a first-of-its-kind unified and searchable interface that allows investors to trade on prediction market contracts across ForecastEx, Kalshi, and CME Group. In addition to economic and climate-related events, clients using the unified platform can also trade contracts related to elections, and the company has said it plans to eventually expand the platform to include other exchanges as well. Kalshi CEO Tarek Mansour declared the integration “a testament to the growing importance of prediction markets for sophisticated investors and financial institutions. We’re just in the early innings of deep institutional adoption.”

Robinhood first connected to Interactive Broker’s ForecastEx, and then last year partnered with Kalshi to offer a “prediction markets hub” in its app. But more recently Robinhood has exhibited greater ambitions by launching Rothera, its own CFTC-licensed exchange and clearinghouse in a joint venture with Susquehanna International Group. While so far just a collection of certain sports-related event contracts are routed to Rothera, Robinhood plans to scale over time. The financial services company’s decision to vertically integrate by purchasing its own exchange is significant, as it indicates that yet another major institutional player in finance is actively working to expand event contracts to be not just retail products, but institutional ones. Its foray into the space is proving to pay off, with prediction market revenue accounting for 20 percent of the company’s trading revenue in Q2 2026, surpassing both stock and crypto revenue.

Two of the largest traditional derivatives exchanges, CME Group and Cboe Global Markets, have also entered the fray. As discussed in the previous section, CME moved to provide the exchange infrastructure for retail event contracts, initially serving as the sole exchange provider for both major sportsbooks’ prediction products. That the incumbent core of global derivatives entered this market at all is telling; even as FanDuel and DraftKings build out their own exchanges, CME’s willingness to serve as the rails signals that at least part of the global finance establishment sees prediction markets as belonging to its own institutional future.

Meanwhile, Cboe recently introduced Cboe Predicts, a prediction markets suite that launched its first offering in June—binary options contracts based on the Mini-S&P 500 Index. With these contracts, customers can place bets on whether the S&P 500 reaches a certain threshold. The contracts are available on Interactive Brokers, and are expected to be available at Charles Schwab soon as well. With this rollout, Cboe also introduced a new prediction markets resource hub and courses on trading.

The Intercontinental Exchange (ICE), the parent company of the New York Stock Exchange, not only unveiled a data distribution agreement with Polymarket in the fall of 2025, but announced it would be investing some $2 billion into the prediction market company. The move was heralded by Polymarket CEO Shayne Coplan as “a major step in bringing prediction markets into the financial mainstream.”

A few months later, ICE announced the launch of a new tool for delivering prediction market data and analytics. With ICE’s Polymarket Signals and Sentiment tool, Polymarket data has become incorporated into ICE’s global data feeds, allowing professional and institutional traders to consider crowdsourced probability assessments as structured market signals. With the launch of the tool, prediction market data has seemingly established a place for itself in professional investment workflows.

More recently, ICE launched cash-settled economic indicator futures contracts based on global monetary policy decisions and US natural gas storage reports. Nasdaq also recently obtained Securities and Exchange Commission (SEC) approval²⁰ to list “Outcome Related Options” tied to the Nasdaq 100 Index and the Nasdaq 100 Micro Index.

Section III: Where Are We Now? Prediction Markets and the Narrowing Window

As prediction markets embed themselves deeper in sports, media, finance and other sectors of our economy and society, and as a broader ecosystem of products, services, and infrastructure develops around them, it will become harder to enact adequate and meaningful action to restrict the industry. Each new partnership, product launch, and institutional adoption makes prediction markets more familiar to institutional players and the public alike, more relied upon, and ultimately more normalized, as businesses build around them, institutions incorporate their data, and the public becomes accustomed to them. And with each of these steps, the disruption that serious regulatory intervention would cause grows larger, while the political will to risk that disruption grows smaller.

As Section II showed, institutional adoption of prediction markets is well on its way, with new partnerships and deeper integration taking hold. As the ecosystem broadens, the mechanisms of lock-in will intensify, making the industry powerful enough to resist regulation under less-friendly future administrations and weaving prediction markets so deeply into our institutions that dislodging the web of actors and arrangements built around them grows ever harder.

As prediction markets embed themselves deeper in media, sports, finance and other sectors of our economy and society, and as a broader ecosystem of products, services, and infrastructure develops around them, it will become harder to enact adequate and meaningful action to restrict the industry. 

We can see path-dependent dynamics beginning to play out both among the firms discussed in this brief and in the wider ecosystem forming around them. Sports betting companies, for example, have spent considerable capital building prediction market infrastructure. DraftKings’s acquisition of Railbird, which paved the way for the company to launch its own exchange, DKeX, cost as much as $250 million. Such a price tag may have been harder to justify when DraftKings’s trading volume was on the lower end, but as it sharply climbed, the per-transaction fees flowing to CME grew large enough that operating its own exchange became the more economical choice. With DKeX, DraftKings can now pocket the margin itself, an advantage that only compounds as volume grows, and with it, the company’s incentive to see the industry flourish. Together with its market-making operation, growing customer base, and expanding slate of contracts, more and more of DraftKings’s business becomes tied up with the broader success of the prediction markets industry.

Or consider the development of a secondary ecosystem comprised of companies that are not prediction markets themselves, but have acquired their own stake in the industry’s survival. Evidence of this exists both in major institutions that are devising new prediction market products and in startups whose entire premise depends on these markets’ existence. ICE’s Polymarket Signals and Sentiment tool, for example, packages Polymarket data into a product ICE sells to its own customers. Others are whole businesses built around prediction markets. Last month, for example, Axios reported the launch of Eventual, what it called a first-of-its-kind prediction market media company, founded by former Politico journalist Alex Keeney. Modeled on FiveThirtyEight but substituting trading odds for conventional polling, Eventual produces analysis for traders, investors, forecasters, and policymakers, and launched with a data partnership with Polymarket. An industry becomes harder to dislodge when an ancillary network forms around it.

But the industry’s continued expansion and influence throughout our society need not be inevitable. While adoption is racing ahead at a troubling pace, lock-in at this point remains incomplete.²¹ As the Roosevelt Institute will describe further in our next piece on this topic, the legal question surrounding prediction markets remains open, with states vying to exert their authority over event contracts, and lower courts split on whether these contracts fall under exclusive federal jurisdiction or whether they are subject to state gambling laws.²²

Similarly, the battle of ideas is still being fought. Although prediction markets are really just gambling by another name, whether courts will accept industry’s argument that they qualify as a financial asset class worthy of exclusive federal regulation remains unsettled. Contrast this with healthcare policy in the US, where even favorable reform moments failed to dislodge the status quo because the private insurance system had become the common sense. Unlike employer-based health insurance, where ideological entrenchment protected the incumbent system, here the unsettled framing and bipartisan pushback against the ascent of these markets may well cut against industry. And regardless of the ensuing legal battles, ideological debate, and current regulatory position, the window for legislative action certainly remains open. There is a mounting bipartisan coalition rallying against varying aspects of the prediction markets creep, with a number of bills introduced at both the federal and state levels that seek to rein in the industry.

But this will require a strong commitment on the part of policymakers, who, with every step prediction market companies take toward greater institutional adoption, face a narrowing window for enacting serious regulation. Leaving things to industry and a captured regulatory apparatus will allow prediction markets to continue down their current path of full-scale entrenchment.

Once path dependence meaningfully takes hold, course correction will hinge on the rare moments when circumstances and political will converge. By then, how many more millions of dollars will retail traders have lost to sophisticated market makers? How many more insiders will benefit from trading on apparent insider information? How much more will our collective faith in institutions atrophy, as the corrupting effects of these markets continue to shape our society? And who benefits if we simply wait and see?