Podcast Summary — Business of Betting (Host: Jason Tro; Guest: Thomas McGrath, CRO, TXTS) 🎙️

Episode Snapshot

• Guest: Thomas McGrath, Chief Revenue Officer, TXTS (TX Odds)
• Host: Jason Tro
• Topic: TXTS history, product evolution (odds aggregation → live/historical odds → event data origination), scouting/stadium data, market landscape, and future plans 🏟️📊

Key Takeaways ✅

TXTS origin & evolution

• Founded ~25 years ago from odds-collection tech originally built by founders with exchange/betting backgrounds.
• Early product: generation‑1 feed — pre-match odds (40 sports, ~300 bookmakers).
• Generation‑2: in‑play feed (collected Asian bookmakers prices) used by big European books to automate pricing.
• Latest: Fusion feed — expanded coverage, player props, richer metadata, push (server‑to‑server) feed for sub‑second in‑play viability.

Product offering

• Core: live odds + historical odds (every price since system inception saved) — valuable for modelers (opening/closing lines, full historical database).
• Delivery: API‑first philosophy (“API or die”), with an improving UI for traders and clients.
• No bootleg/paywalled scraping: TXTS follows an ethical collection policy; they avoid extracting behind login/paywalls and won’t sell single-bookmaker‑only feeds as primary business.

New direction: Event data origination (US college sports)

• Since Aug 2024 TXTS launched a stadium scouting operation for:
  • College football (FBS) — play‑by‑play (every drive: snaps, pass/rush, outcomes)
  • College basketball (including tournaments)
• Human scouts: large recruitment — 13,000 applicants → ~350 trained live scouts; supported by QA, supervisors, analysts based in Chicago (100–120 staff).
• Goal: provide a dataset that didn’t exist for college sports micro‑betting, player props, and fast/accurate in‑play markets — enabling innovators (e.g., micro‑betting firms) to build products.

Coverage strategy & product design

• Focus on primary markets that power models and derivative markets; emphasis on markets that “move the dials” rather than extremely niche one‑offs.
• Technical approach: legacy schema sometimes dropped nonconforming markets; new fusion/server‑to‑server mapping enables far more market types.
• UI: previously Java client only; now a productized UI exists (still iterating).

Market landscape & competition

• Many live‑odds vendors globally; some repackagers/resellers exist — hard to precisely count.
• TXTS differentiators:
  • Longevity and stable independent ownership (not PE‑backed or for sale).
  • Deep historical archive and reliable API service used by large operators for decades.
  • Willingness to adapt feeds and add richer event data for emerging US market needs.
• TXTS open to cooperation with major data providers rather than antagonism.

Business & ethics

• TXTS avoids selling single-bookmaker‑only datasets; sells sport‑oriented market feeds.
• Pricing aim: fair and not exploitative (especially for new event data verticals).

Vision & near‑term plans

• Continue maturing in‑play capabilities and expand/stabilize scouting/event data for college sports.
• Possibility to extend to more sports later after solidifying processes.
• Interested in evolution of regulatory/market structure (e.g., CFTC developments, European exchanges entering US) — could alter opportunities/costs.

Miscellaneous views from Thomas

• Horse racing: acknowledged as culturally important but declining in attendance; personal interest in breeding/rehoming horses.
• Desire for sports betting to become more efficient (lower margins) over time via better tech/data.

Practical/Instructional Points (for companies wanting similar data/origination)

• Building reliable event data requires:
  • Robust recruitment & training pipeline for scouts (large applicant pool → rigorous vetting).
  • QA, supervisors, analyst teams for around‑the‑clock coverage.
  • Purpose-built ingestion tools/UI for scouts and downstream APIs for clients.
  • Clear ethical collection policy regarding paywalled sources.
  • Focus on data elements that enable productization (e.g., play‑by‑play, drives, player actions) rather than trying to capture every obscure market.
• Technical migration: moving from schema‑driven DB to flexible server‑to‑server mapping enables delivering arbitrary market types.

Quotes & Soundbites 🗣️

• “We give you the ingredients for you to bake the cake.” — TXTS approach (API/product philosophy)
• “We’re not scraping scoreboards … we do things ethically.” — collection stance
• “Every opening and closing Premier League price from 99–00 to now is saved.” — historical depth

Who should care?

• Sportsbooks, syndicates, market‑makers, modelers, micro‑betting vendors, data integrators, and anyone building in‑play or player‑prop products — especially those targeting US college sports.

If you want, I can:

• Extract timestamps and map topics to episode minutes, or
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