Al-Ahli Jeddah vs Al Kholood Statistics & Analysis

Al-Ahli Jeddah

May 16, 2026 - 18:00

3 2.25

0 0.62

xG Accuracy: 69%

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 3-0 ✖ Incorrect

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 18, 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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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	33	16	7	10	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 Shabab	33	8	11	14	35
14	Al Kholood	33	9	5	19	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-Ittihad FC	33	54	43	+11	55
7	Al Khaleej Saihat	33	53	58	-5	37
8	Al-Ettifaq	33	50	54	-4	49
9	Al Shabab	33	44	56	-12	35
10	NEOM	33	42	47	-5	44
11	Al-Fayha	33	41	53	-12	38
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	66.0	25.1	+40.9	81
3	Al-Ahli Jeddah	33	55.6	24.3	+31.3	78
4	Al-Qadisiyah FC	33	58.8	33.4	+25.4	74
5	Al-Ittihad FC	33	47.6	37.0	+10.6	55
6	NEOM	33	44.2	38.9	+5.3	44
7	Al Shabab	33	43.1	43.3	-0.2	35
8	Al Taawon	33	41.1	42.2	-1.1	53
9	Al Khaleej Saihat	33	40.9	42.6	-1.7	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-Ettifaq	33	38.4	54.9	-16.5	49
16	Al Kholood	33	31.6	48.5	-16.9	32
17	Al Najma	33	26.8	60.1	-33.3	13
18	Al Okhdood	33	26.3	61.8	-35.5	20