Statistics / Football / Saudi-Arabia. Pro League / NEOM vs Al Shabab

NEOM vs Al Shabab Statistics & Analysis

NEOM NEOM
May 11, 2026 - 16:50
2 2.20
1 1.69
xG Accuracy: 78%
Al Shabab Al Shabab
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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 Over 2.5 Over 2.5 (3 goals) ✔ Correct
  • Both Teams To Score BTTS Yes Yes ✔ Correct
  • 1X2 NEOM NEOM ✔ Correct
  • Correct Score Insights 2-1 2-1 ✔ Correct

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Pro League
  • Fixture: NEOM vs Al Shabab
  • Kickoff: 2026-05-11 16:50:00
  • 1X2 (model): Home 48.7% · Draw 22.4% · Away 28.9%
  • xG (showing): NEOM 2.2 — Al Shabab 1.69 (total xG ≈ 3.89)
  • Primary / headline line (Betting Primary Pick when shown): Over 2.5 goals
  • Model: 74.5% · Implied: 56.8% · Probability edge: +17.7 pts · Est. EV: +28.1%
  • BTTS (model): Yes 73.5% · No 26.5%
  • Correct score (top bin): 2-1 (8.4%)

Use the cards for tiering; this text only restates the same inputs in narrative form.

Early match state can move realised goals away from pre-kick projections.

Best Bet + Reason

Primary angle highlighted on the page: Over 2.5 goals.

Model probability is compared to implied probability from odds to highlight a probability edge; EV uses the same model probability with the best decimal price tracked.

Edges shrink quickly if prices move; always re-check the number on your book.

FAQ

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.

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.

What is the best-supported line in this snapshot?

Match the hero card above: if it says “Betting Primary Pick”, that leg cleared primary rules; if it says “Best +EV (tracked markets)”, it is the strongest +EV line that did not meet stricter Primary thresholds. The bullets below repeat the same model %, implied %, edge (pts), and EV % as that card.

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.

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 17, 2026 (UTC)

How to use this
  • Focus on the Primary line when you want one actionable idea.
  • Do not parlay many thin-edge picks together; edges do not add reliably.
  • Treat longshots as optional, high-stake-sizing plays only.

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Back to Statistics
Pro League Pro League — Standings
# TEAM MP W D L PTS
1 Al-Nassr 33 27 2 4 83
2 Al-Hilal Saudi FC 33 24 9 0 81
3 Al-Ahli Jeddah 33 24 6 3 78
4 Al-Qadisiyah FC 33 22 8 3 74
5 Al-Ittihad FC 32 16 7 9 55
6 Al Taawon 33 15 8 10 53
7 Al-Ettifaq 33 14 7 12 49
8 NEOM 33 12 8 13 44
9 Al-Hazm 33 10 9 14 39
10 Al-Fayha 33 10 8 15 38
11 Al Khaleej Saihat 33 10 7 16 37
12 Al-Fateh 33 9 9 15 36
13 Al Kholood 33 9 5 19 32
14 Al Shabab 32 7 11 14 32
15 Damac 33 6 11 16 29
16 Al Riyadh 33 6 9 18 27
17 Al Okhdood 33 5 5 23 20
18 Al Najma 33 2 7 24 13
# TEAM MP GS GC +/- PTS
1 Al-Nassr 33 87 27 +60 83
2 Al-Hilal Saudi FC 33 84 27 +57 81
3 Al-Qadisiyah FC 33 78 33 +45 74
4 Al-Ahli Jeddah 33 67 24 +43 78
5 Al Taawon 33 59 44 +15 53
6 Al Khaleej Saihat 33 53 58 -5 37
7 Al-Ittihad FC 32 52 40 +12 55
8 Al-Ettifaq 33 50 54 -4 49
9 NEOM 33 42 47 -5 44
10 Al-Fayha 33 41 53 -12 38
11 Al Shabab 32 41 54 -13 32
12 Al-Fateh 33 41 55 -14 36
13 Al Kholood 33 39 61 -22 32
14 Al-Hazm 33 36 57 -21 39
15 Al Riyadh 33 34 63 -29 27
16 Damac 33 31 51 -20 29
17 Al Najma 33 31 76 -45 13
18 Al Okhdood 33 27 69 -42 20
# TEAM MP xG xGC +/- PTS
1 Al-Nassr 33 65.9 24.9 +41.0 83
2 Al-Hilal Saudi FC 33 63.9 24.5 +39.4 81
3 Al-Ahli Jeddah 33 54.1 23.6 +30.5 78
4 Al-Qadisiyah FC 33 58.8 33.4 +25.4 74
5 Al-Ittihad FC 32 47.6 37.0 +10.6 55
6 NEOM 33 43.5 36.8 +6.7 44
7 Al Shabab 32 43.1 43.3 -0.2 32
8 Al Taawon 33 41.1 42.2 -1.1 53
9 Al Khaleej Saihat 33 39.8 41.3 -1.5 37
10 Al-Fateh 33 40.9 43.5 -2.6 36
11 Al-Fayha 33 33.1 42.3 -9.2 38
12 Al Riyadh 33 40.3 50.0 -9.7 27
13 Damac 33 24.2 37.4 -13.2 29
14 Al-Hazm 33 31.7 46.5 -14.8 39
15 Al Kholood 33 30.9 47.0 -16.1 32
16 Al-Ettifaq 33 38.4 54.9 -16.5 49
17 Al Najma 33 26.8 60.1 -33.3 13
18 Al Okhdood 33 25.0 60.7 -35.7 20
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