Predictions / Football / Saudi-Arabia. Pro League / Al-Ahli Jeddah vs Al Kholood

Al-Ahli Jeddah vs Al Kholood Prediction, Odds & AI Betting Tips

Al-Ahli Jeddah Al-Ahli Jeddah
May 16, 2026 - 18:00
3 2.25
0 0.62
xG Accuracy: 69%
Al Kholood Al Kholood
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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 No ✔ Correct
  • 1X2 Al-Ahli Jeddah Al-Ahli Jeddah ✔ Correct
  • Correct Score Insights 2-0, 1-0, 3-0, 2-1, 1-1 3-0 ✔ Correct

Next AI Predictions Available Today

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AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

  • League: Pro League
  • Fixture: Al-Ahli Jeddah vs Al Kholood
  • Kickoff: 2026-05-16 18:00:00
  • 1X2 (model): Home 73.5% · Draw 18.9% · Away 7.6%
  • xG (showing): Al-Ahli Jeddah 2.25 — Al Kholood 0.62 (total xG ≈ 2.87)
  • Primary / headline line (Betting Primary Pick when shown): Under 2.5 goals
  • Model: 45.3% · Implied: 37.3% · Probability edge: +8.0 pts · Est. EV: +26.8%
  • BTTS (model): Yes 42.4% · No 57.6%
  • Correct score (top bin): 2-0 (14.4%)

Where EV is shown, it is estimated return per unit stake at the best tracked decimal price — not the same thing as a raw probability gap.

Correct score remains high-variance even when a line is most likely on paper.

Best Bet + Reason

Primary angle highlighted on the page: Under 2.5 goals.

We separate probability edge (model minus implied, in points of probability) from estimated EV (economic edge at the best price shown on the page).

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

FAQ

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.

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.

Safer market than correct score?

Markets with more liquidity and smoother prices (often 1X2 or O/U 2.5 from many books) are usually easier to reason about than long-tail correct-score prices; still read EV on each leg.

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 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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