Cricket betting

Gambia v Zambia betting tips, prediction & odds

World T20 Qualifier · T20 · Saturday 24 October at 13:50

Odds updated Sat, 24 Oct, 11:00 (UK time) · full refresh every day at 08:00, then hourly

Every number below comes from 9,844 ball-by-ball simulations of this match (model cricket-sim-1.0.0), run on real historical delivery data. Selections are not published as tips until the model passes backtesting.

Team news & expected XI

Official team sheets are used the moment they are published. Until then each XI is the model's own selection read: who this side has picked in this format, where they batted and how many overs they bowled. Form figures are exponentially weighted over the last year, so recent matches count for more.

Gambia

Expected XI from selection history

Order	Player	Role	Plays	Form runs	Overs
1	Muhammed Manga	batter	87%	14.0@ 84.1	1.3
2	Asim Ashraf	all-rounder	41%	14.0@ 56.0	3.3
3	AM Rajpurohit	all-rounder	41%	8.7@ 76.6	3.6
4	Mustapha Suwareh	batter	85%	2.2@ 32.5	1.5
5	A Conteh	all-rounder	59%	5.8@ 63.6	3.6
6	Andre Jarju	all-rounder	88%	5.3@ 56.2	3.0
7	Abubacarr Kuyateh	all-rounder	92%	10.8@ 75.6	3.1
8	Ousman Bah	batter	86%	1.1@ 26.1	0.0
9	Ismaila Tanba	all-rounder	97%	10.4@ 130.1	2.0
10	F Campbell	batter	82%	5.6@ 75.0	0.0
11	ML Bojang	all-rounder	50%	6.4@ 100.4	3.2
12	M Jobarteh	all-rounder	97%	1.4@ 64.8	2.9
13	P Campbell	batter	40%	3.8@ 46.9	0.0

Last named squad (Gambia v Mozambique, 2024-10-24): AM Rajpurohit, Abubacarr Kuyateh, Andre Jarju, Asim Ashraf, B Jaye, F Campbell, Ismaila Tanba, M Jobarteh, Muhammed Manga, Ousman Bah, Shan Siddiqui

Zambia

Expected XI from selection history

Order	Player	Role	Plays	Form runs	Overs
1	Vasmiakram Chand	batter	46%	19.9@ 99.0	0.0
2	Muhammad Asim	all-rounder	72%	20.2@ 121.5	2.9
3	Ismail Kara	all-rounder	46%	35.3@ 166.0	3.8
4	Jakir Patel	batter	91%	15.9@ 112.7	0.0
5	JV Chand	all-rounder	92%	19.6@ 108.9	2.9
6	R Lungu	all-rounder	46%	9.4@ 63.4	3.8
7	Shahnawaz Patel	batter	42%	10.4@ 101.6	0.0
8	Javid Patel	all-rounder	97%	4.7@ 73.1	3.5
9	Ayaz Dadabhai	all-rounder	97%	9.3@ 108.6	3.3
10	Zakir Husain Patel	all-rounder	46%	15.6@ 147.9	2.6
11	Soyeb Pendi	all-rounder	74%	4.4@ 114.8	3.5
12	M Yambayamba	batter	55%	1.8@ 54.2	0.0
13	Aslam Bera	all-rounder	49%	0.5@ 22.3	3.1

Last named squad (Zambia v Malawi, 2026-08-15): Ayaz Dadabhai, Irfan Saleh, Ismail Kara, JV Chand, Jakir Patel, Javid Patel, R Lungu, Shadreck Malama, Soyeb Pendi, Vasmiakram Chand, Zakir Husain Patel

Pitch & ground

Nigeria Cricket Federation Oval 1, Abuja, Nigeria

Nigeria Cricket Federation Oval 1 · T20

Average 1st innings: 128.5
Average 2nd innings: 109.1
Runs per over: 6.54
Boundary balls: 1105%
Pace economy: 6.77
Spin economy: 6.29
Powerplay RPO: 6.17
Death RPO: 7.65
Chasing wins: 4170%
Batting first wins: 5830%
Matches counted: 24

Weather at the start

No forecast is available: a match needs a confirmed ground with coordinates and a start time inside the next two weeks.

What we could not source

· No forecast is available for this ground yet.

Every live spread market

The full set of Spreadex spread lines currently priced on this match, exactly as captured. Sell below the lower figure, buy above the higher one. Where the simulation covers a market we show its expected makeup beside the price, the side that implies and the edge in points per £1 a point — comparisons, not tips, until the format clears backtesting.

Odds updated Sat, 24 Oct, 11:00 (UK time) · captured hourly from the live market

Match Result


Zambia to win match	86.6	93.4	67.2	sell	+19.4
Gambia to win match	6.6	13.4	32.1	buy	+18.7

More T20 spread markets across every priced match.

Model vs market

The simulation output next to the live bookmaker price on every market we hold a price for. Fixed-odds edges are expected value per £1 staked; spread edges are the expected points gained per £1 a point. Positive numbers are where the model disagrees with the price — they are comparisons, not published tips.

Honest health warning: across 146 replayed T20 matches the model’s match-winner probabilities have not yet beaten a simple coin-flip benchmark, so treat the match-winner comparisons below as work in progress rather than value. Run projections need separate validation; this does not establish a profitable team or player runs strategy.

What does “coin flip” mean?

It is a deliberately simple test: give each team a 50% chance in every decided, two-team match, without looking at players, form or the pitch. It does not mean every real match is evenly matched, or that our model literally tosses a coin.

We score the probability given to the actual winner, not just count correct picks. Lower is better. Always saying 50/50 scores about 0.69. A model saying 80% when that team loses gets a bigger penalty than one saying 55%. “Not better than chance” means its tested winner probabilities have not improved on that simple starting point — they are not a proven betting edge.

This test excludes draws and ties; it is not a three-outcome Test-match benchmark. Beating it still does not prove profit: the offered odds, bookmaker margin and settled returns matter too. A confidence score of 80/100 is not an 80% chance of winning.


Match winner	Gambia	32.1% (3.12)	7.50	back	+140.7% EVFlagged
Match result index	Zambia to win match	67.2	86.6 – 93.4	sell	+19.4 pts
Match result index	Gambia to win match	32.1	6.6 – 13.4	buy	+18.7 pts
Match winner	Zambia	67.2% (1.49)	1.07	back	-28.0% EV

“Flagged” means the gap between the model and the price is too big to be a real edge — we read it as a sign the model is missing something about this match, and it is one of the checks that keeps tips switched off.

Match winner projection


Gambia	32.1%	3.12	7.50	12.5%	+140.7%	6.6 – 13.4	37/100
Zambia	67.2%	1.49	1.07	87.5%	-28.0%	86.6 – 93.4	38/100

Gambia to win

Why we like it

Head-to-head: 0-0 in 1 stored T20 meetingLOW sample
Gambia have won 0 of the 1 completed T20 matches we hold between these sides, the most recent on 24 Oct 2026.
Gambia full record
Nigeria Cricket Federation Oval 1 · T20: 58.3% of matches won batting firstMEDIUM sample
Chasing sides have won 41.7% at this ground across 24 recorded matches, which is built into the simulated result.

Risks

Projected runs: 95.3 vs 113.5
The simulation gives Gambia a -18.2 run expected margin over Zambia, from 9,844 simulated innings.
Model and market disagree too far to trust
Model 32.1% against 12.5% implied by 7.50 with the bookmaker margin stripped out — +140.7% per £1 staked. A gap this size is more likely a data problem than an edge, so it is flagged rather than tipped.
Winner probabilities have not passed backtesting
Across 146 replayed T20 matches the model's log loss is 0.68 against a 0.69 coin-flip baseline, so this chance is shown as a comparison, not a tip.
Confidence 37/100, data depth 16/100
Confidence is scored from the ball-by-ball history behind these teams, how settled the XI is and how many simulations agreed.

Zambia to win

Why we like it

Head-to-head: 0-0 in 1 stored T20 meetingLOW sample
Zambia have won 0 of the 1 completed T20 matches we hold between these sides, the most recent on 24 Oct 2026.
Zambia full record
Projected runs: 113.5 vs 95.3
The simulation gives Zambia a +18.2 run expected margin over Gambia, from 9,844 simulated innings.
Nigeria Cricket Federation Oval 1 · T20: 58.3% of matches won batting firstMEDIUM sample
Chasing sides have won 41.7% at this ground across 24 recorded matches, which is built into the simulated result.

Risks

Price comparison
Model 67.2% against 87.5% implied by 1.07 with the bookmaker margin stripped out — -28.0% per £1 staked.
Winner probabilities have not passed backtesting
Across 146 replayed T20 matches the model's log loss is 0.68 against a 0.69 coin-flip baseline, so this chance is shown as a comparison, not a tip.
Confidence 38/100, data depth 19/100
Confidence is scored from the ball-by-ball history behind these teams, how settled the XI is and how many simulations agreed.

Team runs projection

Gambia

Projected 20-over innings total

median 92 · 10th–90th percentile 48–148

Wickets lost 6.0

Powerplay runs 33


120+	24.6%
140+	13.2%
160+	6.4%
180+	2.7%
200+	0.9%

confidence 37/100 · data 16/100

Zambia

Projected 20-over innings total

113

median 108 · 10th–90th percentile 56–179

Wickets lost 4.0

Powerplay runs 50


120+	40.1%
140+	26.9%
160+	16.7%
180+	9.8%
200+	5.4%

confidence 38/100 · data 19/100

Gambia runs

Why we like it

95.3 projected vs 128.5 parMEDIUM sample
Nigeria Cricket Federation Oval 1 · T20 averages 128.5 in the first innings over 24 matches; the model has Gambia below that by 33.2 runs.
Middle of the range 92.0, 10th–90th 48–148
Eight innings in ten finish inside that band, with 6.0 wickets lost on average and 32.9 powerplay runs.

Risks

Model has run 16.4 runs low in testing
Measured over 146 replayed T20 matches, average error 33.3 runs.

Zambia runs

Why we like it

113.5 projected vs 128.5 parMEDIUM sample
Nigeria Cricket Federation Oval 1 · T20 averages 128.5 in the first innings over 24 matches; the model has Zambia below that by 15.0 runs.
Middle of the range 108.0, 10th–90th 56–179
Eight innings in ten finish inside that band, with 4.0 wickets lost on average and 50.1 powerplay runs.

Risks

Model has run 16.4 runs low in testing
Measured over 146 replayed T20 matches, average error 33.3 runs.

Player runs projection

Expected runs today, not a career average: each player's chance of batting, expected balls faced and the opposition attack are simulated together.


Muhammad Asim Zambia	26.6	19	67	72.0%	24	49.5%	19.7%	—	—
Jakir Patel Zambia	17.6	11	46	91.0%	16	35.0%	8.1%	—	—
Muhammed Manga Gambia	17.2	12	43	87.0%	23	35.0%	6.5%	—	—
JV Chand Zambia	16.7	11	43	92.0%	18	34.1%	6.7%	—	—
Ismail Kara Zambia	16.2	0	56	46.0%	18	28.3%	12.4%	—	—
Ismaila Tanba Gambia	11.3	6	31	97.0%	12	22.5%	2.5%	—	—
Vasmiakram Chand Zambia	10.7	0	38	46.0%	18	21.0%	5.7%	—	—
Andre Jarju Gambia	10.7	6	29	88.0%	15	19.8%	1.7%	—	—
Asim Ashraf Gambia	9.2	0	33	41.0%	24	18.8%	4.3%	—	—
Mustapha Suwareh Gambia	8.7	4	24	85.0%	11	14.4%	1.3%	—	—
Abubacarr Kuyateh Gambia	8.1	4	23	92.0%	11	13.2%	0.9%	—	—
AM Rajpurohit Gambia	7.3	0	27	41.0%	16	13.9%	3.1%	—	—
A Conteh Gambia	7.3	0	23	59.0%	12	12.6%	1.6%	—	—
Ousman Bah Gambia	6.8	2	20	86.0%	11	10.7%	0.6%	—	—
F Campbell Gambia	5.4	0	17	82.0%	11	8.1%	0.3%	—	—
Ayaz Dadabhai Zambia	5.3	0	18	97.0%	9	8.6%	0.5%	—	—
Javid Patel Zambia	5.1	0	16	97.0%	10	7.3%	0.4%	—	—
R Lungu Zambia	4.9	0	19	46.0%	14	9.4%	1.1%	—	—
Shahnawaz Patel Zambia	3.9	0	15	42.0%	12	7.3%	0.8%	—	—
Soyeb Pendi Zambia	3.6	0	14	74.0%	10	6.4%	0.4%	—	—
ML Bojang Gambia	3.2	0	12	50.0%	10	5.1%	0.2%	—	—
Zakir Husain Patel Zambia	2.9	0	11	46.0%	11	5.7%	0.7%	—	—

Muhammad Asim runs

Why we like it

Expected to face 24 balls at number 2
Opportunity drives the projection: 26.6 runs on average, 67 in the top 10% of simulations.
Recent form 20.2 runs an inningsMEDIUM sample
Weighted over the last 12 innings at a strike rate of 121.5.
Against paceMEDIUM sample
214 runs off 163 balls in 11 T20 matches — strike rate 131.3 vs 122.8 overall, average 35.7 vs 24.3 overall.

Risks

Only 72% likely to play
Taken from how often the player has been selected in this team's recent XIs; the projection is already scaled down for it.
Thin data (31/100)
Not enough recorded balls behind this player in this format for a firm number.

Jakir Patel runs

Why we like it

Expected to face 16 balls at number 6
Opportunity drives the projection: 17.6 runs on average, 46 in the top 10% of simulations.
Recent form 15.9 runs an inningsMEDIUM sample
Weighted over the last 14 innings at a strike rate of 112.7.

Risks

Against paceLOW sample
121 runs off 113 balls in 12 T20 matches — strike rate 107.1 vs 113.0 overall, average 20.2 vs 18.1 overall.
Thin data (31/100)
Not enough recorded balls behind this player in this format for a firm number.

Muhammed Manga runs

Why we like it

Expected to face 23 balls at number 1
Opportunity drives the projection: 17.2 runs on average, 43 in the top 10% of simulations.
Recent form 14.0 runs an inningsLOW sample
Weighted over the last 0 innings at a strike rate of 84.1.
Against paceLOW sample
105 runs off 118 balls in 6 T20 matches — strike rate 89.0 vs 79.7 overall, too few dismissals for a meaningful average.

Risks

Thin data (29/100)
Not enough recorded balls behind this player in this format for a firm number.

JV Chand runs

Why we like it

Expected to face 18 balls at number 8
Opportunity drives the projection: 16.7 runs on average, 43 in the top 10% of simulations.
Recent form 19.6 runs an inningsMEDIUM sample
Weighted over the last 14 innings at a strike rate of 108.9.

Risks

Thin data (38/100)
Not enough recorded balls behind this player in this format for a firm number.

Ismail Kara runs

Why we like it

Expected to face 18 balls at number 3
Opportunity drives the projection: 16.2 runs on average, 56 in the top 10% of simulations.
Recent form 35.3 runs an inningsLOW sample
Weighted over the last 5 innings at a strike rate of 166.0.

Risks

Only 46% likely to play
Taken from how often the player has been selected in this team's recent XIs; the projection is already scaled down for it.
Thin data (16/100)
Not enough recorded balls behind this player in this format for a firm number.

Ismaila Tanba runs

Why we like it

Expected to face 12 balls at number 10
Opportunity drives the projection: 11.3 runs on average, 31 in the top 10% of simulations.
Recent form 10.4 runs an inningsLOW sample
Weighted over the last 0 innings at a strike rate of 130.1.

Risks

Thin data (23/100)
Not enough recorded balls behind this player in this format for a firm number.

How these projections are built

The model simulates the match ball by ball from historical delivery data: expected line-ups and batting positions, opposition bowling attack, venue scoring and format baselines. Each figure is the output of those simulations, never an estimate written by hand. Track its settled record on the cricket model performance page, and see the live prices on the cricket betting hub.