ITF Women · Tennis · Aug 11, 2026 09:00 UTC · avg book margin 8.8%

Anastasia AbbagnatovsEdie Griffiths

Abbagnato–Griffiths 0–2: 15.1% moneyline edge at sugarhouse closed +29.7% tighter before the first serve

Offered at sugarhouse3.50Fair price3.04+15.1% above fair

Omenizer detected 10 bookmakers pricing this bet above the no-vig fair near close — this story covers one of them. Members see the full board, live.

The setup — the analysis as published at detection, written before the game and frozen for the record. The market it describes has since closed; the outcome is above.

At detection, sugarhouse quoted the moneyline for Anastasia Abbagnato vs Edie Griffiths (ITF Women) at decimal 3.50 — a 15.1% divergence from the sharp consensus. The mispricing sat executable on the board until the opening serve.

Griffiths took the match 2–0. The flagged position returned +2.50 units per 1-unit stake.

Between detection and kickoff, the market repriced toward the flagged side by +29.7%, closing substantially tighter than where we caught it. Closing-line value is how professionals measure detection: outcomes are noise, but repricing is signal.

This detection class — tennis moneyline at mid-range odds — has aggregated to +6.5% ROI across 2841 settled bets.

The engine that surfaces these edges runs before kickoff, not after. Each signal appears on the live board only while the execution window is open.

Historical, aggregate data on settled bets — not betting advice and not a guarantee. Markets adapt; edges fade; variance is real.

AN EXAMPLE OF THE MEMBER VIEW · what members see on a bet like this — shown for a different, already-settled match PRO
Ekaterina Alexandrova vs Kristina Liutova · WTA Tour · Tennis — flagged side Kristina Liutova @ 3.10
81 Omen Score

This is the complete breakdown members get for every live signal. The example below is a DIFFERENT match, already settled — its market is closed, so full disclosure costs nothing. Everything is real except values marked 🔒, which are members-only (decoy digits shown).

Why this bet
+12.0%
Entry edge
+7.2%
Edge near close
+0.8%
Risk-adjusted edge
2.89
Fair price (no-vig)
3.65
Entry odds
Quality
95/100
Confidence
3
Sharp books
Prime signal
Class
Market state: Strong sharp consensus (3+ books) · priced from: Sharp price
Sizing
4.5%
Recommended stake
3.4%
Full Kelly (theoretical max)
EV by devig methodthe same price run through every de-margining method
+9.7%
Shin
+8.4%
Power
+12.0%
Additive
-5.4%
Worst case
+12.0%
Multiplicative
Insights
High confidence + meaningful price gap — best risk-adjusted segment.
A sample of bookmakers on this betnear close — every price against the same no-vig fair
BookmakerOddsVs fair
Bwin3.10+7.2%
Sportingbet3.10+7.2%
Sportsinteraction3.10+7.2%
Superbet3.05+5.5%
Sx.Bet3.03+4.8%
Tailgate Exchange3.03+4.8%
Matchbook3.01+4.1%
Betway3.00+3.7%
Casumo3.00+3.7%
Unibet3.00+3.7%
Proline3.00+3.7%
Betjack3.00+3.7%
Risk & profitability profile
Heavy favoriteFavoriteCoin flipUnderdogLongshot
3.10 odds → 32% implied win probability
35%
Fair win probability
+4.1% 🔒
Expected ROI (model)
+7.4% 🔒
Cohort realized ROI
Proven Playbook matchesconditions are members-only
early value + short odds 🔒 (Any) — +7.9% settled ROI on 41% winners
consensus fade + late entry 🔒 (Any) — +6.3% settled ROI on 43% winners
steam entry + home side 🔒 (Any) — +4.3% settled ROI on 42% winners
Past performance

Based on 441 bets exactly like this one over the last 60 days

+7.0% 🔒
Closing line value
+7.7% 🔒
Average return
+6.3% 🔒
Beat the closing line
39%
Win rate
Likely ROI range: +3.2% to +8.3% 🔒
No reliable edge either way: too close to break-even to call
The endingthe part only a settled signal can show
Detected Jul 27, 12:51 UTC at 3.65 (+12.0% edge) → fair price at close 3.18 → closing-line value +2.4%
✅ Settled: WON · +2.65 units
A real, settled example — not a typical-results claim (read this signal's full story). The live breakdown for Anastasia Abbagnato vs Edie Griffiths is on the member board now · unlock with Pro
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Record settled · last updated Aug 12, 2026 07:42 UTC · How these numbers are made: methodology · the dataset — fair prices shown are margin-free. Spotted an error? Request a correction (include this page's URL).