Predictions / Football / Saudi-Arabia. Pro League / Al-Ittihad FC vs Damac

Al-Ittihad FC vs Damac Prediction, Odds & AI Betting Tips

Al-Ittihad FC Al-Ittihad FC
May 10, 2026 - 18:00
2 1.46
1 0.83
xG Accuracy: 82%
Damac Damac
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Tracked markets vs full-time result

Each row compares the model’s highlighted side (or lean) to what happened at full time.

  • Market Prediction Result Outcome
  • Over / Under 2.5 Under 2.5 Over 2.5 (3 goals) ✖ Incorrect
  • Both Teams To Score BTTS No Yes ✖ Incorrect
  • 1X2 Al-Ittihad FC Al-Ittihad FC ✔ Correct
  • Correct Score Insights 1-0, 1-1, 2-0, 0-0, 2-1 2-1 ✔ Correct

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AI match briefing

AI Match Summary

Quick read on how the model reads this matchup.

  • League: Pro League
  • Fixture: Al-Ittihad FC vs Damac
  • Kickoff: 2026-05-07 17:00:00
  • 1X2 (model): Home 50.4% · Draw 29.8% · Away 19.7%
  • xG (showing): Al-Ittihad FC 1.46 — Damac 0.83 (total xG ≈ 2.29)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 59.9% · Implied: 41.9% · Probability edge: +18.0 pts · Est. EV: +37.8%
  • BTTS (model): Yes 44.9% · No 55.1%
  • Correct score (top bin): 1-0 (14.8%)

Totals and BTTS are evaluated against current market prices where available.

1X2 can look balanced even when side markets show clearer structure.

Best Bet + Reason

Primary pick from the decision engine: Under 2.5 goals.

If 1X2 looks tight, the engine may still find clearer structure in totals or BTTS — that is intentional.

When several markets sit near +EV, keep stakes small — correlation means edges do not add cleanly.

FAQ

How should I read EV versus a probability gap?

Probability edge = model probability minus implied probability (reported here in percentage points). EV ≈ model probability × best tracked decimal odds − 1, shown as return per unit stake. They are related but not interchangeable labels.

Why might 1X2 look unattractive while totals do not?

Tight 1X2 prices often embed a fair three-way split, so EV on match-winner can sit negative even when Over/Under or BTTS still diverges from the model — compare the 1X2 row on the market cards to O/U and BTTS.

Who has the edge in the match-winner market?

Use the 1X2 model percentages in the summary and the 1X2 market card: the side with the highest model % is the model lean, but check EV — a lean can still be -EV after prices.

Is the most likely correct score a good bet?

Usually no as a standalone bet: the “most likely” scoreline is still a low absolute probability tail event (often single digits, sometimes low teens). Use it as context; keep any correct-score stake in the “fun / small” bucket.

Risk Factors

  • Price movement: implied probabilities and EV move with odds.
  • Sample / data gaps: low-information leagues widen forecast bands.
  • In-play state: goals and red cards are not modelled here.
  • Scoreline variance: the most likely scoreline is still usually a low absolute probability outcome (often well below 20%).

Methodology

  • Inputs: Same structured facts bundle as the public prediction page (xG / Poisson snapshot, market EV where available, decision engine v2).
  • Compliance: Educational framing only; not personalised advice.

Last Updated

May 22, 2026 (UTC)

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Pro League Pro League — Standings
# TEAM MP W D L PTS
1 Al-Nassr 34 28 2 4 86
2 Al-Hilal Saudi FC 34 25 9 0 84
3 Al-Ahli Jeddah 34 25 6 3 81
4 Al-Qadisiyah FC 34 23 8 3 77
5 Al-Ittihad FC 34 16 7 11 55
6 Al Taawon 34 15 8 11 53
7 Al-Ettifaq 34 14 8 12 50
8 NEOM 34 12 9 13 45
9 Al-Hazm 34 11 9 14 42
10 Al-Fayha 34 10 8 16 38
11 Al-Fateh 34 9 10 15 37
12 Al Khaleej Saihat 34 10 7 17 37
13 Al Shabab 34 8 11 15 35
14 Al Kholood 34 9 6 19 33
15 Al Riyadh 34 7 9 18 30
16 Damac 34 6 11 17 29
17 Al Okhdood 34 5 5 24 20
18 Al Najma 34 3 7 24 16
# TEAM MP GS GC +/- PTS
1 Al-Nassr 34 91 28 +63 86
2 Al-Hilal Saudi FC 34 85 27 +58 84
3 Al-Qadisiyah FC 34 83 34 +49 77
4 Al-Ahli Jeddah 34 71 25 +46 81
5 Al Taawon 34 59 46 +13 53
6 Al-Ittihad FC 34 55 48 +7 55
7 Al Khaleej Saihat 34 54 62 -8 37
8 Al-Ettifaq 34 51 55 -4 50
9 Al Shabab 34 44 57 -13 35
10 NEOM 34 43 48 -5 45
11 Al-Fayha 34 41 54 -13 38
12 Al-Fateh 34 41 55 -14 37
13 Al Kholood 34 39 61 -22 33
14 Al-Hazm 34 38 57 -19 42
15 Al Riyadh 34 35 63 -28 30
16 Damac 34 32 55 -23 29
17 Al Najma 34 32 76 -44 16
18 Al Okhdood 34 27 70 -43 20
# TEAM MP xG xGC +/- PTS
1 Al-Nassr 34 65.9 24.9 +41.0 86
2 Al-Hilal Saudi FC 34 66.0 25.1 +40.9 84
3 Al-Ahli Jeddah 34 55.6 24.3 +31.3 81
4 Al-Qadisiyah FC 34 58.8 33.4 +25.4 77
5 Al-Ittihad FC 34 47.6 37.0 +10.6 55
6 NEOM 34 44.2 38.9 +5.3 45
7 Al Shabab 34 43.1 43.3 -0.2 35
8 Al Taawon 34 41.1 42.2 -1.1 53
9 Al Khaleej Saihat 34 40.9 42.6 -1.7 37
10 Al-Fateh 34 40.9 43.5 -2.6 37
11 Al-Fayha 34 33.1 42.3 -9.2 38
12 Al Riyadh 34 40.3 50.0 -9.7 30
13 Damac 34 24.2 37.4 -13.2 29
14 Al-Hazm 34 31.7 46.5 -14.8 42
15 Al-Ettifaq 34 38.4 54.9 -16.5 50
16 Al Kholood 34 31.6 48.5 -16.9 33
17 Al Najma 34 26.8 60.1 -33.3 16
18 Al Okhdood 34 26.3 61.8 -35.5 20
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