Full Time
Serie A · Stadio Giuseppe Meazza, Milan · 2026-05-24

AC MilanAC Milan
1 - 2
CagliariCagliari

+$636.90
Match Precision62%
Signal Hit Rate13/21
Model Lineup
🛡️
Oddsflow Core Strategy
+$325
★★★★★
3W-0L · 100%
Active Trader
+$125
★★☆☆☆
4W-4L · 50%
🎯
HDP Sniper
+$125
★★☆☆☆
4W-4L · 50%
PreMatch Edge
+$63
★★★★★
2W-0L · 100%
🧠 Key Question

Why did AI enter 6 times at 0', 21', 35', 43', 46', 58' — and still finish +$637?

Trade Story

Match Overview

AC Milan hosted Cagliari in the Serie A, finishing 1-2. Goals: A. Saelemaekers (2'), G. Borrelli (20'), J. Rodriguez (57'). OddsFlow deployed 21 trades across 6 waves, achieving 62% precision with a net result of +$636.90 (ROI: +32.8%).

Pre-Match Odds

The Asian Handicap held at -1.5 but home odds shifted from 1.9 to 1.98.

Trade Wave Analysis

### Wave 1 — Minute 0' (Score: 0-0) **Context:** Scoreless at 0'. 1 model (S5.1_Pre) entered Asian Handicap markets, targeting Cagliari -1.5. Average expected value was 38.0%, with a combined stake of $60. The sharpest edge was on Cagliari -1.5 (Asian Handicap): OddsFlow calculated 68.8% probability versus the market's implied 48.3% — a 20.5 percentage point gap at odds of 2.07. **Result:** All 2 trades won, netting +$62.90. ### Wave 2 — Minute 21' (Score: 1-1) **Context:** Level at 1-1 after G. Borrelli's equalizer at 20'. 1 model (oddsflow_core_v8.1) entered Asian Handicap markets, targeting Cagliari -1. Average expected value was 43.2%, with a combined stake of $214. The sharpest edge was on Cagliari -1 (Asian Handicap): OddsFlow calculated 78.0% probability versus the market's implied 49.3% — a 28.7 percentage point gap at odds of 2.03. **Result:** All 2 trades won, netting +$208.45. ### Wave 3 — Minute 35' (Score: 1-1) **Context:** Level at 1-1 after G. Borrelli's equalizer at 20'. 2 models (system4_BLEND_v10, system4_MC_v10) entered Over/Under and Asian Handicap markets, targeting Under 3.5 and Cagliari -1. Average expected value was 38.0%, with a combined stake of $678. The sharpest edge was on Cagliari -1 (Asian Handicap): OddsFlow calculated 83.1% probability versus the market's implied 49.3% — a 33.8 percentage point gap at odds of 2.03. **Result:** All 6 trades won, netting +$681.45. ### Wave 4 — Minute 43' (Score: 1-1) **Context:** Level at 1-1, 43'. 3 models (system4_BLEND_v10, oddsflow_core_v8.1, system4_MC_v10) entered Asian Handicap markets, targeting Cagliari -0.5. Average expected value was 18.4%, with a combined stake of $286. The sharpest edge was on Cagliari -0.5 (Asian Handicap): OddsFlow calculated 59.0% probability versus the market's implied 42.6% — a 16.4 percentage point gap at odds of 2.35. **Result:** All 3 trades won, netting +$386.10. ### Wave 5 — Minute 46' (Score: 1-1) **Context:** Level at 1-1, 46'. 2 models (system4_MC_v10, system4_BLEND_v10) entered Moneyline markets, targeting Draw. Average expected value was 18.7%, with a combined stake of $302. The sharpest edge was on Draw (Moneyline): OddsFlow calculated 43.7% probability versus the market's implied 31.7% — a 11.9 percentage point gap at odds of 3.15. **Result:** All 4 trades lost, netting $-302.00. ### Wave 6 — Minute 58' (Score: 1-2) **Context:** Cagliari leading 1-2 at 58'. J. Rodriguez scored moments ago. 2 models (system4_BLEND_v10, system4_MC_v10) entered Over/Under markets, targeting Over 4.25 and Over 3.5. Average expected value was 40.1%, with a combined stake of $400. The sharpest edge was on Over 3.5 (Over/Under): OddsFlow calculated 70.0% probability versus the market's implied 40.0% — a 30.0 percentage point gap at odds of 2.5. **Result:** All 4 trades lost, netting $-400.00.

Key Mispricing Moments

- **Minute 35'** — Asian Handicap Cagliari -1: AI saw 83.1% vs market's 49.3% (33.8pp gap). correctly identified. - **Minute 35'** — Asian Handicap Cagliari -1: AI saw 82.8% vs market's 49.3% (33.5pp gap). correctly identified. - **Minute 58'** — Over/Under Over 3.5: AI saw 70.0% vs market's 40.0% (30.0pp gap). did not convert, but edge was real. - **Minute 21'** — Asian Handicap Cagliari -1: AI saw 78.0% vs market's 49.3% (28.7pp gap). correctly identified. - **Minute 58'** — Over/Under Over 3.5: AI saw 70.0% vs market's 42.1% (27.9pp gap). did not convert, but edge was real.

Model Performance

- **oddsflow_core_v8.1**: 3 trades, 3W/0L, +$324.55 (ROI: +108.2%) - **system4_BLEND_v10**: 8 trades, 4W/4L, +$124.95 (ROI: +15.9%) - **system4_MC_v10**: 8 trades, 4W/4L, +$124.50 (ROI: +15.7%) - **S5.1_Pre**: 2 trades, 2W/0L, +$62.90 (ROI: +104.8%)

Match Statistics

Possession was 48–52 in AC Milan's deficit. AC Milan had 16 shots (3 on target) versus Cagliari's 24 (10 on target). Expected goals: AC Milan 1.71 — Cagliari 2.6. Corners: 4-5.

🏆

Verdict

A highly profitable match for OddsFlow. The AI models identified significant mispricings and converted them efficiently, returning +32.8% ROI. Top performer: oddsflow_core_v8.1 at +$324.55.

Market Efficiency

What the closing market expected

The prices bookmakers settled on before kick-off, with the margin removed, next to what actually happened.

MarketLineImplied probability
1X2 (home / draw / away)Favourite: Home75.8% / 18.4% / 9.5%
Asian handicap-1.550.5%
Over / Under2.7551.3%

Probabilities are de-vigged, so they describe the market's view rather than the price you would have been offered.

Where the market was wrong

The significant undervaluation of Cagliari's outright win in the 1x2 market.

The Serie A clash between AC Milan and Cagliari concluded with a stunning 1-2 victory for Cagliari, a result that starkly contrasts with the pre-match market sentiment. The 1x2 market heavily favored AC Milan, assigning them a substantial 75.76% implied win probability, while Cagliari's chances were priced at a mere 9.5%. This represented a significant market inefficiency, as Cagliari delivered an upset. In the Handicap market, AC Milan was offered at -1.5, with a 50.51% probability of covering. Cagliari's outright win meant they comfortably covered the +1.5 line. The Totals market, set at 2.75 goals, showed a balanced expectation with both Over and Under priced at 51.28%. The match ultimately saw 3 goals, pushing the outcome to the Over. The most pronounced error was the severe misjudgment of Cagliari's ability to secure an outright win.

Trade Waves
Match Timeline
46'🔄
G
S. Gimenez(assist: C. Pulisic)AC Milan
61'🔄
T
F. Tomori(assist: Z. Athekame)AC Milan
61'🔄
N
C. Nkunku(assist: N. Fullkrug)AC Milan
62'🔄
J
A. Jashari(assist: L. Modric)AC Milan
62'🔄
R
J. Rodriguez(assist: A. Dossena)Cagliari
63'🔄
P
J. Pedro(assist: M. Palestra)Cagliari
68'🔄
F
Y. Fofana(assist: R. Leao)AC Milan
74'🔄
B
G. Borrelli(assist: P. Mendy)Cagliari
74'🔄
D
A. Deiola(assist: I. Sulemana)Cagliari
90'+5🔄
E
S. Esposito(assist: M. Felici)Cagliari
Odds Movement
Key Mispricing
Match Statistics
Pre-Match Odds
Verdict

A highly profitable match for OddsFlow. The AI models identified significant mispricings and converted them efficiently, returning +32.8% ROI on 21 trades. Top performer: Oddsflow Core Strategy at +$324.55.

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