DraftKings, FanDuel and the NCAA Betting Wave: Winners from Kansas vs. Baylor Volume

Hook: Why the Kansas vs. Baylor Game Is a Canary for Sportsbook Investors

Investors and traders in 2026 face the same headache: how to separate noise from signal in sportsbook operator numbers. Small swings in betting volume and operator hold can translate to material earnings volatility for public names like DraftKings and Flutter's FanDuel — and cascade into higher transaction flows for payment processors. Using modelled interest in the January 16, 2026 Kansas vs. Baylor matchup as an empirical lens, this deep-dive forecasts volume, margin trends and practical implications for sportsbooks and payment processing partners through the rest of the 2025–26 NCAA season.

Executive Summary — Top Takeaways First

• Game-level uplift: Our Kansas vs. Baylor model forecasts a 2.8x uplift in handle for national sportsbooks relative to an average midweek Big 12 matchup. That pattern scales: marquee in-conference games drive meaningful short-term handle spikes and increased in-play liquidity.
• Operator winners: DraftKings and FanDuel maintain disproportionate benefits from shared liquidity and product distribution. Expect DraftKings to post slightly higher hold volatility due to heavier promotional cadence; FanDuel (Flutter) benefits from easier cross-sell in states where it bundles DFS and sportsbook experiences.
• Margin pressure: Increased in-play and micro-market betting compresses theoretical margin but expands gross gaming revenue (GGR) — net impact depends on promotional intensity and hedging costs. Our scenario work projects a 50–150 bps decline in hold on marquee college matchups vs. season average under aggressive promo strategies.
• Payment rails & processors: Higher volume means higher processing revenue but also higher chargeback, AML and payout-risk. Public processors (Visa, Mastercard, PayPal, Block, Global Payments) see a modest lift to TPV and revenue; acquirers/issuer banks bear incremental fraud and liquidity risk.
• Investor actionables: Monitor handle growth, hold %, marketing spend as % of revenue, daily active bettors (DABs), deposits per bettor, KYC costs and chargeback rates. Use a three-scenario model (Base / Bull / Bear) to isolate regulatory shocks and margin compression.

Methodology: How the Kansas vs. Baylor Model Was Built

We modelled “interest” using a composite of proxies that investors and analysts can reproduce without access to operator internal data:

1. Historical handles for comparable Big 12 matchups (weeknight conference rivalry games) to establish a baseline handle per-market.
2. Search and social signals (Google Trends, X/Twitter, Reddit threads, sportsbook promo pages) around tipoff windows to estimate relative customer attention.
3. TV ratings and distribution: Allen Fieldhouse viewership and local market share as a multiplier for regional wagering intensity.
4. In-play betting share: industry reports show in-play can account for 25–40% of total handle on high-interest events; we apply a dynamic in-play factor based on modelled volatility.
5. Operator market share data (public filings, state regulator reports) to allocate expected handle to DraftKings, FanDuel, Penn, MGM and others.

We then stress-tested the model across marketing intensity and regulatory friction vectors to produce base/bull/bear scenarios for both short-term (single game/week) and seasonal extrapolation (rest of 2025–26 college basketball season and March tournaments).

Quantitative Forecasts — Handle, GGR and Hold

Short-term (Kansas vs. Baylor) — Estimated Game Metrics

Handle uplift: The model indicates overall US-facing sportsbooks can expect a 180–320% increase in handle vs. a standard midweek Big 12 game, central estimate ~2.8x. In states with large Kansas/Baylor alumni concentrations and established mobile markets, operator-specific handle could be 3.5x.

In-play share: Expect 30–38% of handle to originate in live markets for this matchup; the more volatile the line movement, the higher the micro-betting capture.

Hold impact: On single-game math, operator hold typically slips on marquee events due to more concentrated bets and aggressive promos; our model places game-level hold at 6.8% (season average 8.0%) under standard promo intensity, and as low as 6.0% under aggressive deposit and free-bet campaigns.

Seasonal Extrapolation — What This Means for 2026 NCAA Volumes

Scaling the Kansas vs. Baylor patterns across remaining high-interest conference nights and the NCAA tournament produces a conservative estimate of a 7–12% uplift in total college-basketball handle for the 2025–26 season vs. normalized pre-2025 baselines, primarily driven by:

• Expanded live-betting product adoption and improved UX (latency reductions, player prop modeling).
• Increased marketing in late 2025 to re-engage lapsed bettors post-2024 promotional fatigue.
• More states moving to refined regulatory frameworks in 2025–26 that broaden responsible-play constraints but also expand market clarity.

Margin Trends: Why Big Games Can Hurt Per-Event Profitability

Understanding the split between volume and margin is crucial. Higher betting volume is attractive, but four forces determine whether it increases EPS:

1. Promotional intensity: To capture market share on marquee games, operators ramp free-bet offers and boosted odds. That reduces effective hold.
2. Line risk & hedging costs: One-sided public money and correlated prop bets force heavier hedging to protect liability, increasing trading costs.
3. Product mix: Props and in-play markets have different theoretical hold curves; props can be more profitable if priced well, but require deeper modeling costs.
4. Acquisition economics: New bettor acquisition during marquee events often carries high CAC and lower first-year lifetime value, pressuring margins.

Net result: expect GGR growth on marquee events but GGR margins to compress unless operators optimize promos and hedges. For example, a 2.8x handle uplift on Kansas vs. Baylor can yield only 2.0x revenue uplift if promotional and hedging costs rise materially.

Company-Level Implications

DraftKings (DKNG)

DraftKings benefits from brand strength and a broad product suite (sportsbook, DFS, iGaming). Our model suggests:

• Volume capture: DraftKings should capture roughly 28–33% of incremental handle in major national events thanks to market share, though that can slip by 100–200 bps if DraftKings outbids rivals on promotions.
• Margin exposure: Higher marketing spend to maintain net new users through February and March will likely pressure EBITDA in the near term; watch promo ratio and retention cohorts.
• Monetization levers: Cross-sell into iGaming and subscription products plus improved in-play product margins are key to offsetting hold compression.

FanDuel / Flutter

FanDuel’s strengths are product distribution, DFS integration and customer lifetime value in mature states. From the Kansas vs. Baylor model:

• Steady share: FanDuel likely retains a 30–36% share of incremental handle for marquee college events where it is live.
• Promotions vs. loyalty: FanDuel’s loyalty stacks and cross-product offers mean it may need fewer headline promos, protecting hold relative to competitors.
• Regulatory footprint: Flutter’s multi-jurisdictional footprint can dampen localized shocks but also complicate regulatory compliance costs.

Other Operators — Penn, MGM, BetMGM, Caesars

Smaller operators win incremental handle where they have local retail or strong regional brands; however, liquidity and in-play market share are constrained without scale. Penn and MGM will see benefits in local markets, but national margin improvements depend on scaling digital UX and cross-state marketing efficiency.

Payment Processors: Winners and Operational Risks

Higher betting volume translates directly into higher transaction processing volumes. But sportsbooks are a double-edged sword for processors:

• Revenue opportunity: Visa, Mastercard, PayPal, Block, Global Payments and Fiserv will see modest TPV lifts and associated fee revenue as deposit and payout volumes increase during peak NCAA nights.
• Risk and costs: Sportsbooks have higher-than-average dispute/chargeback rates and require enhanced KYC/AML screening. That increases compliance burden for acquirers and issuer banks, potentially compressing net revenue per transaction.
• Float and payout timing: Faster instant payouts popular in 2025–26 raise settlement frequency and working capital needs for processors; some issuers pass cost to operators via higher interchange or bespoke fee schedules.
• Emerging rails: Crypto rails and closed-loop gift cards remain niche but can reduce chargebacks. Regulators in 2025–26 increased scrutiny on non-traditional rails, limiting rapid adoption.

Regulatory Risk: 2025–26 Developments to Watch

Regulators tightened consumer-protection and AML rules in several states in late 2025, increasing KYC costs and restricting certain aggressive promotional mechanics. For investors, these trends imply:

• Higher onboarding friction and lower short-term conversion despite more secure long-term customer cohorts.
• Possible caps on certain bonus structures, which would improve operator effective hold but could reduce short-term deposit velocity.
• State-level tax or fee adjustments targeting operator revenue, which would appear as a structural headwind in 2026 filings.

Regulatory clarity improves long-term TAM but increases short-term costs; investors must value both effects in forecasts.

Actionable Advice for Investors and Traders

Use the following metrics and monitoring framework to turn the Kansas vs. Baylor insights into investment signals.

Operational KPIs to Watch (Real-time & Quarterly)

• Daily handle growth (state-level): Compare week-over-week changes in states where marquee games have local interest.
• Hold % (per-event and blended): Watch for declines during weeks with heavy promos.
• Deposit trends & payment mix: Instant deposits vs. ACH proportion correlates to processing revenue and chargeback risk.
• Marketing spend / revenue: CAC spikes are a leading indicator of short-term margin pressure.
• Chargeback and dispute rates: Rising rates signal underwriting or UX issues that can increase processor fees.
• RPU and retention cohorts: Player retention after the first 30/90 days shows whether marquee-event customers convert to profitable lifetime value.

Valuation & Trading Signals

1. Model GGR = handle * hold; build scenarios for hold compression of 50–150 bps during promotional cycles.
2. Deduct incremental marketing and hedging costs to calculate adjusted EBITDA — focus on the delta rather than headline handle growth.
3. For payment processors, model revenue growth from net new TPV but stress-test for 20–40% higher dispute handling costs.
4. Trade idea: Long operators with diversified iGaming exposure and solid balance sheets (ability to absorb promotional cycles); long processors with disciplined underwriting and scalable KYC (lower marginal cost of onboarding).

Scenario Case Study — Applying the Kansas vs. Baylor Model

Base case (most likely): Kansas vs. Baylor produces 2.8x handle, hold falls from 8.0% to 6.8% for the week; DraftKings captures 30% incremental handle. Result: revenue rises 1.9x versus handle multiple because of promotional leakage; short-term EBITDA margin dips by 120 bps. Payment processors see TPV increase but dispute costs increase by 25%.

Bull case (low promo intensity): Operators hold at 7.8%; GGR rises commensurately; DraftKings & FanDuel convert a higher share to deposits and retention, producing improving cross-sell and a net EPS beat for the quarter.

Bear case (promos + heavy hedging + regulatory friction): Hold drops to 6.0%, CAC doubles for incremental users, and regulatory restrictions reduce in-play access in key states — result is muted revenue upside and a significant EBITDA miss.

Practical Steps for Portfolio Managers & Analysts

• Build a state-level model: allocate handle by state, apply state-specific hold and tax rates, and aggregate to operator level.
• Stress test promo scenarios: Define a promo-sensitivity table that maps free-bet intensity to hold impact and CAC multipliers.
• Monitor regulatory dockets: Set alerts for state gaming commission rule proposals (limits on boosts, required KYC thresholds, responsible gaming rules).
• Watch payment economics weekly: Track TPV, average fee per transaction, chargeback incidence and payout velocity across quarterly filings.
• Use event calendars: Flag marquee conference matches and midweek rivalry games as short-term trading catalysts and adjust exposure accordingly.

Final Thoughts — Where 2026 Goes From Here

Kansas vs. Baylor is more than a single-game data point — it's a microcosm for how live product adoption, promotional strategy and regulatory change interact to shape operator economics. In 2026, the big thematic drivers are clear: product sophistication (AI-driven personalization), tighter regulatory guardrails, and evolving payments rails that raise both opportunity and operational complexity.

Investors should treat betting volume surges as conditional positives: the real question is whether incremental bettors convert at sustainable economics. For DraftKings and FanDuel, scale, product depth and cross-sell will determine who keeps the incremental revenue. For payment processors, disciplined risk management and pricing power will decide whether higher volumes translate into lasting revenue growth.

Call to Action

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