Celta Vigo1 - 0Sevilla
Celta VigoWhy did AI enter 2 times at 15', 47' — and still finish +$925?
Match Overview
Celta Vigo hosted Sevilla in the La Liga, finishing 1-0. Goals: I. Moriba (51'). OddsFlow deployed 26 trades across 2 waves, achieving 88% precision with a net result of +$925.23 (ROI: +60.3%).
Pre-Match Odds
The Asian Handicap line moved from -0.75 to -0.5; the Over/Under stayed at 2.5 with Over odds moving from 1.91 to 2.08; the home moneyline drifted out from 1.75 to 1.93.
Trade Wave Analysis
### Wave 1 — Minute 15' (Score: 0-0) **Context:** Scoreless at 15'. 3 models (system4_BLEND_v10, system4_MC_v10, oddsflow_core_v8.1) entered Moneyline and Asian Handicap and Over/Under markets, targeting Celta Vigo and Celta Vigo -0.5 and Over 1.5. Average expected value was 17.9%, with a combined stake of $914. The sharpest edge was on Celta Vigo -0.5 (Asian Handicap): OddsFlow calculated 62.3% probability versus the market's implied 49.5% — a 12.8 percentage point gap at odds of 2.02. **Result:** 15 of 17 trades won, netting +$640.73. ### Wave 2 — Minute 47' (Score: 0-0) **Context:** Scoreless at 47'. 2 models (system4_MC_v10, system4_BLEND_v10) entered Over/Under and Moneyline markets, targeting Under 1.5 and Under 1.25 and Draw and Under 2.5. Average expected value was 30.1%, with a combined stake of $621. The sharpest edge was on Under 1.25 (Over/Under): OddsFlow calculated 83.7% probability versus the market's implied 55.9% — a 27.9 percentage point gap at odds of 1.79. **Result:** 8 of 9 trades won, netting +$284.50.
Key Mispricing Moments
- **Minute 47'** — Over/Under Under 1.25: AI saw 83.7% vs market's 55.9% (27.9pp gap). correctly identified. - **Minute 47'** — Over/Under Under 1.25: AI saw 83.7% vs market's 56.2% (27.6pp gap). correctly identified. - **Minute 47'** — Over/Under Under 1.25: AI saw 82.4% vs market's 55.9% (26.5pp gap). correctly identified. - **Minute 47'** — Over/Under Under 1.25: AI saw 82.4% vs market's 56.2% (26.2pp gap). correctly identified. - **Minute 47'** — Over/Under Under 2.5: AI saw 83.7% vs market's 66.7% (17.1pp gap). correctly identified.
Model Performance
- **system4_BLEND_v10**: 11 trades, 8W/1L/2V, +$401.22 (ROI: +62.3%) - **system4_MC_v10**: 12 trades, 8W/2L/2V, +$352.75 (ROI: +49.1%) - **oddsflow_core_v8.1**: 3 trades, 3W/0L, +$171.26 (ROI: +99.6%)
Match Statistics
Possession was 56–44 in Celta Vigo's favor. Celta Vigo had 11 shots (2 on target) versus Sevilla's 9 (2 on target). Expected goals: Celta Vigo 1.53 — Sevilla 0.79. Corners: 4-3.
Verdict
A highly profitable match for OddsFlow. The AI models identified significant mispricings and converted them efficiently, returning +60.3% ROI. Top performer: system4_BLEND_v10 at +$401.22.
What the closing market expected
The prices bookmakers settled on before kick-off, with the margin removed, next to what actually happened.
| Market | Line | Implied probability |
|---|---|---|
| 1X2 (home / draw / away) | Favourite: Home | 0.5% / 0.3% / 0.2% |
| Asian handicap | -0.5 | 0.5% |
| Over / Under | 2.5 | 0.5% |
Probabilities are de-vigged, so they describe the market's view rather than the price you would have been offered.
The market significantly undervalued the Under 2.5 Goals.
Celta Vigo secured a 1-0 victory over Sevilla. In the 1x2 market, Celta Vigo was the clear favorite with an implied win probability of 51.81%, accurately reflecting the outcome. For the Asian Handicap (-0.5), Celta Vigo also successfully covered, aligning with the market’s slight lean. However, the most notable inefficiency was found in the Totals (Over/Under 2.5) market. Despite the market leaning towards the Under 2.5 goals with a 54.35% implied probability, the actual match produced only 1 goal. This result indicates substantial Closing Line Value (CLV) on the Under, as the market, while directionally correct, still significantly undervalued the true probability of a very low-scoring affair. The OddsFlow model identified this discrepancy, highlighting a clear opportunity where bookmakers got it wrong.
A highly profitable match for OddsFlow. The AI models identified significant mispricings and converted them efficiently, returning +60.3% ROI on 26 trades. Top performer: Active Trader at +$401.22.
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