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Prediction Markets vs. Sportsbooks: A Deep Dive into Marketing, Measurement, and the New Competitive Landscape

By jili tutorial · September 13, 2026

Prediction Markets vs. Sportsbooks: A Deep Dive into Marketing, Measurement, and the New Competitive Landscape

Introduction: The Paradigm Shift No One Saw Coming

In a recent interview with European Gaming, Allan Stone, CEO of Intelitics—a performance marketing and analytics platform for the iGaming industry—delivered a sharp analysis of how prediction markets are reshaping the sportsbook landscape. The conversation centered on Kalshi’s explosive performance during the 2022 FIFA World Cup, the ripple effects on acquisition costs, measurement models, lifetime value assumptions, and the regulatory gap that operators have historically blamed for their shortcomings. Stone’s core thesis: most of the gap between traditional sportsbooks and prediction markets is self-inflicted, driven by marketing inertia rather than regulatory barriers.

This guide unpacks each of Stone’s key findings, adds context from the broader industry, and provides actionable takeaways for operators, affiliates, and marketers navigating this shifting terrain.

The Kalshi World Cup Run: What It Actually Proved

The Numbers That Changed the Narrative

Allan Stone opened the interview with a startling fact: “Fifteen people beat companies with a hundred times their headcount.” During the World Cup, Kalshi’s team of roughly 15 people generated trading volume higher than most sportsbooks’ entire handle, accompanied by nearly 6 million app downloads. The platform landed on a brand momentum list alongside household names—and ahead of the network that actually broadcast the tournament.

“Beating the broadcaster on brand recall during the broadcaster’s own tournament isn’t luck.”

This wasn’t a flash in the pan. It was a structural advantage in audience acquisition and engagement.

The Audience Distinction That Matters

Stone emphasized that sportsbooks have historically failed to attract a diverse user base. Women make up only about 20% of sportsbook depositors—a figure that has remained stagnant for years. During the World Cup, Kalshi’s female user base grew nearly twice as fast as its male user base, and by late June women represented close to one-third of all traders. Many of these were first-time bettors, people who had never placed a wager on anything before.

“The usage pattern backs it up. Sportsbook activity spiked early in the tournament and cooled off fast, the usual pattern. Kalshi kept building all the way through the knockout rounds.”

The traditional sportsbook engagement pattern is a sharp spike followed by a rapid decline. Kalshi’s curve was different—steady growth that peaked later, suggesting deeper engagement with the product, not just a single event.

The Caveat: Tourist Traffic or Real Retention?

Stone was careful not to overstate the permanence of this growth. Both Kalshi and Polymarket saw sports-related activity drop sharply the moment the World Cup ended, indicating that some of the volume was “tourist traffic chasing a moment.” However, the critical question remains:

“If Kalshi turns even a third of those new traders into people who show up for elections, weather, or whatever’s next, does the rest of the industry have an answer for that? I don’t think it does yet.”

The ability to repurpose a user base across multiple verticals (sports, politics, finance, entertainment) gives prediction markets a diversification advantage that sportsbooks, tied to seasonal sports calendars, lack.

The New Bidder in Every Auction: How Prediction Markets Are Inflating Acquisition Costs

The CEO’s Confession

Stone pointed directly to BetMGM’s CEO, who publicly acknowledged that prediction markets are “pulling marketing dollars out of the same channels sportsbooks live in, pushing acquisition costs higher and stretching out payback on new cohorts.” This is not speculation—it’s a public company telling investors why guidance moved.

“That’s not me reading tea leaves. That’s a public company telling investors why guidance moved.”

The Financial Fallout

The impact is already visible in earnings reports. DraftKings and FanDuel are projecting a combined loss of more than $500 million in EBITDA this year from building and marketing their own prediction products. PENN Entertainment’s CEO called the approaching football season an “arms race” and used the word “irrational” to describe the competitive spending.

Stone’s blunt assessment:

“If you’re not one of the three companies in that fight directly, your CPMs go up anyway. You’re bidding in the same auctions as multiple public companies plus a well-funded prediction market that just raised at a valuation higher than DraftKings, and none of them are optimizing for your payback window.”

The Capital Disconnect

In previous years, cheap capital masked poor unit economics. That safety net has vanished. Now, prediction markets—backed by venture capital and high valuations—can afford to spend without needing the same return on investment that sportsbooks require. This creates a structural imbalance:

“If your 2026 budget was built assuming last year’s competitive set, it’s already wrong.”

Every operator must now factor in a new competitor that doesn’t play by traditional sportsbook financial rules.

Where the Measurement Model Breaks: The Behavioral Mismatch

The Old Cage for a New Animal

Traditional sportsbooks built their measurement infrastructure around a predictable bettor rhythm:

  1. Deposit funds.
  2. Place a few wagers on Sunday’s NFL slate.
  3. Occasionally build a parlay.
  4. Wait for the next game cycle.

Lifetime value (LTV) cohorts, predicted-value windows, CRM triggers—all of it assumes this shape. A prediction market trader behaves completely differently:

“Attribution breaks first. Your CRM was built to say this person is a sports bettor or a casino player. It has no clean bucket for someone who found you through a market on the World Cup and checks in daily without ever placing what your system recognises as a wager.”

The CRM Blind Spot

If the data model cannot describe the behavior, it cannot value it. Sportsbooks are effectively trying to fit a new animal into an old cage. For example, a user who trades on a Federal Reserve interest rate decision may never place a sports bet, yet they interact with the platform daily. Current sportsbook CRM systems would likely classify such a user as low-value or inactive, when in reality they could be a high-frequency trader with significant lifetime value.

Stone’s recommendation: rebuild behavioral models from scratch rather than retrofitting prediction market activity onto existing sportsbook frameworks.

The Lifetime Value Problem: Nobody Has a 12-Month Number Yet

Belief vs. Measured Cohort

Despite bold projections from industry leaders, Stone argues that no one genuinely knows what a prediction market user is worth over 12 months.

“Anyone telling you different is guessing with confidence, which is worse than just guessing.”

He references Jason Robins, CEO of DraftKings, who stated publicly that DraftKings “believes” it can eventually get prediction customers to the same LTV as sportsbook customers. The key word: believes.

“That’s a projection, not a measured cohort.”

The Platinum Tier as a Clue

Kalshi’s introduction of a Platinum VIP tier earlier this year is telling. As Stone notes:

“You don’t build a white-glove retention program for users you’ve already sized up. You build it because you’re trying to find out who your whales actually are.”

The existence of such a program signals that even Kalshi is still discovering its high-value user profiles.

The One Data Point Problem

A meaningful 12-month LTV number requires a cohort that has lived through:

Prediction markets at this scale have had exactly one World Cup.

“That’s one data point pretending to be a trend line.”

Stone’s advice for 2027 budgeting:

“Treat any LTV figure you hear from this category as a hypothesis, not a benchmark, until someone’s watched a cohort for a full year without a tentpole event propping it up.”

Affiliates Repricing the Shelf Space: A New Cost Structure

How Prediction Markets Pay Affiliates

Affiliates are already moving into prediction market traffic. The compensation models differ:

Neither model resembles a mature sportsbook rate card. Instead, affiliates are stitching together CPA, revshare, and hybrid deals in real time, because no one has years of cohort data to properly price the partnership.

“That’s the exact mistake I’ve been warning operators about for years, just showing up in a new category. You can’t price a partner deal off volume when you don’t know what the volume is worth yet.”

The Simple Impact on Sportsbook CPAs

Affiliates have finite inventory—best placements, trusted lists, highest-intent audiences. If a prediction market offers less friction, a newer story, and higher willingness to pay for that inventory, sportsbooks must pay more to retain the shelf space they once had by default.

“You’re not losing affiliates. You’re bidding against a category that doesn’t need the deal to make sense yet.”

This dynamic will continue to push sportsbook customer acquisition costs upward until the market reaches a new equilibrium—or until prediction markets themselves mature enough to demand rational returns.

Europe vs. the US: What Transfers and What Stays Home

Coordinated Regulatory Action

Nine European regulators—from Belgium, France, Germany, Italy, the Netherlands, Poland, Portugal, Spain, and Switzerland—have already coordinated against unlicensed prediction market platforms. The UK Gambling Commission treats them as betting intermediaries, subject to existing gambling laws.

Stone suggests that if Europe licenses prediction products rather than blocking them, the US marketing playbook will only partially transfer. The part that doesn’t transfer is the important part: the context of regulation and consumer behavior.

In the US, prediction markets operate in a relatively permissive environment (especially for event contracts on non-sports topics), which has allowed them to grow rapidly. European markets, with stricter licensing and advertising controls, may force a different marketing approach—one that relies less on broad brand awareness campaigns and more on organic, community-driven acquisition.

The Regulatory Gap Underneath

Stone’s overarching point returns to the regulatory argument: “Fix the regulatory gap, and there’s still a marketing problem sitting underneath it.” Even if regulation were equalized, sportsbooks would still face the behavioral, measurement, and retention challenges outlined above.

“Most of the gap is marketing, not regulation.”

Key Takeaways for Operators

AreaTraditional Sportsbook MindsetNeeded Shift
AcquisitionCompete on same channels, same mathAccept new bidders with different payback horizons
MeasurementModel based on game-week rhythmBuild models that capture probability-trading behavior
LTVAssume 12-month cohort stabilityTreat as hypothesis; watch for non-tentpole cycles
AffiliatesFixed-rate CPA/revshare dealsDynamic pricing; accept uncertainty in volume value
RegulationBlame regulatory gapAddress marketing and product gap first

Conclusion: The Window of Opportunity

Prediction markets have proven they can attract audiences sportsbooks have long coveted, at a fraction of the headcount and with a fundamentally different engagement pattern. The industry is still in the early stages of understanding this new competitor. The operators that survive—and thrive—will be those that:

The gap between sportsbooks and prediction markets is real, but it’s not primarily regulatory. It’s a gap in marketing sophistication, behavioral understanding, and willingness to adapt.