Al Okhdood vs Al Khaleej Saihat Statistics & Analysis

Al Okhdood

May 16, 2026 - 16:05

3 1.03

1 1.99

xG Accuracy: 44%

Al Khaleej Saihat

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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 (4 goals) ✖ Incorrect
Both Teams To Score BTTS No Yes ✖ Incorrect
1X2 Al Khaleej Saihat Al Okhdood ✖ Incorrect
Correct Score Insights 1-1 3-1 ✖ Incorrect

AI match briefing

AI Match Summary

Pre-match snapshot for this fixture.

League: Pro League
Fixture: Al Okhdood vs Al Khaleej Saihat
Kickoff: 2026-05-16 16:05:00
1X2 (model): Home 17.7% · Draw 23.9% · Away 58.4%
xG (showing): Al Okhdood 1.03 — Al Khaleej Saihat 1.99 (total xG ≈ 3.02)
Best +EV line (same label as hero card when Primary thresholds are not met): BTTS No
Model: 43.2% · Implied: 41.5% · Probability edge: +1.7 pts · Est. EV: +2.8%
BTTS (model): Yes 56.8% · No 43.2%
Correct score (top bin): 1-1 (10.0%)

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

Best current value angle on the board — same leg as the “Best +EV” hero when Primary rules are not met: BTTS No.

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.

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.

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.

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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Back to Statistics

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