Cricket betting

Uganda v Zambia betting tips, prediction & odds

World T20 Qualifier · T20 · Tuesday 20 October at 10:00

Odds updated Tue, 20 Oct, 11:01 (UK time) · full refresh every day at 08:00, then hourly

Every number below comes from 9,707 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.

Uganda

Expected XI from selection history

Order	Player	Role	Plays	Form runs	Overs
1	R Lutaaya	batter	50%	9.3@ 129.6	0.0
2	SG Mangela	batter	49%	24.2@ 116.7	0.0
3	Raghav Dhawan	all-rounder	88%	32.2@ 111.6	2.0
4	R Obuya	batter	82%	23.1@ 133.5	0.0
5	Riazat Ali Shah	all-rounder	67%	28.0@ 186.9	1.8
6	CN Kakuru	batter	69%	9.5@ 96.3	0.0
7	DM Nakrani	all-rounder	87%	13.4@ 118.5	3.4
8	AR Ramjani	all-rounder	87%	16.4@ 132.4	3.8
9	C Kyewuta	all-rounder	70%	5.4@ 102.7	3.3
10	J Miyaji	all-rounder	76%	7.0@ 125.1	3.4
11	J Baguma	all-rounder	40%	1.1@ 52.3	3.0
12	H Ssenyondo	all-rounder	61%	1.8@ 84.7	3.9
13	F Nsubuga	all-rounder	67%	4.7@ 123.9	3.5

Last named squad (Uganda v Sierra Leone, 2026-09-09): Anas Baig, C Kyewuta, C Musemez, CN Kakuru, J Baguma, J Miyaji, K Waiswa, M Musinguzi, Olipa Gerald, R Obuya, Riazat Ali Shah

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 (Rwanda v Zambia, 2026-08-15): Ayaz Dadabhai, Irfan Saleh, Ismail Kara, JV Chand, Jakir Patel, Javid Patel, Joshep Zulu, M Yambayamba, R Lungu, 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 Tue, 20 Oct, 11:01 (UK time) · captured hourly from the live market

1st n Overs


Uganda Runs in First 10	89	92	—	—	—

Batsmans Runs (One Day)


Raghav Dhawan Runs	51	55	28.2	sell	+22.8
Riazat Ali Shah Runs	52	56	13.9	sell	+38.1
Gerald Olipa Runs	84	86	—	—	—
Alpesh Ramjani Runs	15	17	9.3	sell	+5.7

Cricket Runs In Over


Uganda Runs in Over 7	8.4	9.1	107.4	buy	+98.3

Fall Of Next Wicket


Fall of 3rd Uganda Wicket	87	92	—	—	—
Fall of 7th Uganda Wicket	182	184	—	—	—

Innings Runs (T20)


Uganda Innings Runs	192	193	107.4	sell	+84.6

Match Result


Uganda to win match	95.7	100	64.8	sell	+30.9
Zambia to win match	0	4.3	34.6	buy	+30.3

Supremacy


Uganda/Zambia	79	87	16.2	sell	+62.8

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. Team and player run projections are the better-tested part of the model.


Match winner	Zambia	34.6% (2.89)	23.00	back	+694.9% EVFlagged
Team runs	Uganda	107.4	192 – 193	sell	+84.6 runs
Supremacy	Uganda/Zambia	16.2	79 – 87	sell	+62.8 runs
Player runs	Riazat Ali Shah	13.9	52 – 56	sell	+38.1 runs
Match result index	Uganda to win match	64.8	95.7 – 100	sell	+30.9 pts
Match result index	Zambia to win match	34.6	0 – 4.3	buy	+30.3 pts
Player runs	Raghav Dhawan	28.2	51 – 55	sell	+22.8 runs
Player runs	AR Ramjani	9.3	15 – 17	sell	+5.7 runs
Match winner	Uganda	64.8% (1.54)	1.00	back	-35.2% EVFlagged

“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


Uganda	64.8%	1.54	1.00	95.8%	-35.2%	95.7 – 100	48/100
Zambia	34.6%	2.89	23.00	4.2%	+694.9%	0 – 4.3	38/100

Uganda to win

Why we like it

Head-to-head: 0-0 in 1 stored T20 meetingLOW sample
Uganda have won 0 of the 1 completed T20 matches we hold between these sides, the most recent on 20 Oct 2026.
Uganda full record
Projected runs: 107.4 vs 91.2
The simulation gives Uganda a +16.2 run expected margin over Zambia, from 9,707 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

Model and market disagree too far to trust
Model 64.8% against 95.8% implied by 1.00 with the bookmaker margin stripped out — -35.2% 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 0.6764 against a 0.6931 coin-flip baseline, so this chance is shown as a comparison, not a tip.
Confidence 48/100, data depth 39/100
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 20 Oct 2026.
Zambia 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: 91.2 vs 107.4
The simulation gives Zambia a -16.2 run expected margin over Uganda, from 9,707 simulated innings.
Model and market disagree too far to trust
Model 34.6% against 4.2% implied by 23.00 with the bookmaker margin stripped out — +694.9% 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 0.6764 against a 0.6931 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.

Supremacy spread

Uganda/Zambia

Market 79 – 87 · model expected margin 16.2 runs

Model edge: sell +62.8 runs per £1 a point

Team runs projection

Uganda

Projected 20-over innings total

107

median 103 · 10th–90th percentile 52–170

Spreadex spread: 192 – 193model edge: sell +84.6 runs

Wickets lost 4.3

Powerplay runs 43


120+	36.9%
140+	23.4%
160+	13.7%
180+	7.1%
200+	3.4%

confidence 48/100 · data 39/100

Zambia

Projected 20-over innings total

median 87 · 10th–90th percentile 43–146

Wickets lost 5.8

Powerplay runs 38


120+	22.7%
140+	12.0%
160+	5.9%
180+	2.6%
200+	0.9%

confidence 38/100 · data 19/100

Uganda runs

Why we like it

107.4 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 Uganda below that by 21.1 runs.
Middle of the range 103.0, 10th–90th 52–170
Eight innings in ten finish inside that band, with 4.3 wickets lost on average and 42.9 powerplay runs.
Model 107.4 against a 192–193 spread
Mid price 192.5. Expected 84.6 runs per £1 a point selling.

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

91.2 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 37.3 runs.
Middle of the range 87.0, 10th–90th 43–146
Eight innings in ten finish inside that band, with 5.8 wickets lost on average and 38.2 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.


Raghav Dhawan Uganda	28.2	24	63	88.0%	29	56.8%	19.5%	51 – 55	sell +22.8
Muhammad Asim Zambia	17.1	11	45	72.0%	22	36.2%	7.3%	—	—
Riazat Ali Shah Uganda	13.9	3	44	67.0%	19	26.9%	7.7%	52 – 56	sell +38.1
R Obuya Uganda	13.6	6	39	82.0%	14	24.7%	6.2%	—	—
JV Chand Zambia	13.3	9	33	92.0%	17	26.1%	2.6%	—	—
Jakir Patel Zambia	13.0	8	34	91.0%	14	24.7%	3.5%	—	—
SG Mangela Uganda	12.0	0	41	49.0%	20	24.6%	6.2%	—	—
Ismail Kara Zambia	11.1	0	39	46.0%	17	21.9%	6.3%	—	—
DM Nakrani Uganda	9.4	2	29	87.0%	13	17.9%	2.2%	—	—
AR Ramjani Uganda	9.3	0	30	87.0%	13	18.6%	2.8%	15 – 17	sell +5.7
Vasmiakram Chand Zambia	7.9	0	28	46.0%	18	15.7%	2.6%	—	—
R Lutaaya Uganda	6.8	0	23	50.0%	9	12.1%	2.2%	—	—
Ayaz Dadabhai Zambia	6.4	3	18	97.0%	9	8.3%	0.3%	—	—
Javid Patel Zambia	5.6	2	16	97.0%	9	6.4%	0.2%	—	—
CN Kakuru Uganda	5.6	0	18	69.0%	10	9.2%	0.8%	—	—
Soyeb Pendi Zambia	4.8	0	16	74.0%	9	6.7%	0.1%	—	—
R Lungu Zambia	4.3	0	15	46.0%	13	6.8%	0.4%	—	—
C Kyewuta Uganda	4.0	0	15	70.0%	10	6.8%	0.5%	—	—
Shahnawaz Patel Zambia	3.9	0	15	42.0%	11	6.5%	0.3%	—	—
Zakir Husain Patel Zambia	3.8	0	15	46.0%	10	6.5%	0.3%	—	—
J Miyaji Uganda	3.3	0	12	76.0%	11	5.0%	0.2%	—	—
J Baguma Uganda	1.2	0	3	40.0%	10	1.6%	0.0%	—	—

Raghav Dhawan runs

Why we like it

Expected to face 29 balls at number 6
Opportunity drives the projection: 28.2 runs on average, 63 in the top 10% of simulations.
Recent form 32.2 runs an inningsLOW sample
Weighted over the last 5 innings at a strike rate of 111.6.
Against paceMEDIUM sample
318 runs off 261 balls in 19 T20 matches — strike rate 121.8 vs 110.0 overall, average 45.4 vs 31.7 overall.
Against spinMEDIUM sample
166 runs off 163 balls in 14 T20 matches — strike rate 101.8 vs 110.0 overall, average 41.5 vs 31.7 overall.

Muhammad Asim runs

Why we like it

Expected to face 22 balls at number 2
Opportunity drives the projection: 17.1 runs on average, 45 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.

Riazat Ali Shah runs

Why we like it

Expected to face 19 balls at number 11
Opportunity drives the projection: 13.9 runs on average, 44 in the top 10% of simulations.
Recent form 28.0 runs an inningsLOW sample
Weighted over the last 5 innings at a strike rate of 186.9.
Against paceMEDIUM sample
411 runs off 295 balls in 32 T20 matches — strike rate 139.3 vs 125.5 overall, average 34.3 vs 38.7 overall.

Risks

Against spinHIGH sample
456 runs off 423 balls in 36 T20 matches — strike rate 107.8 vs 125.5 overall, average 35.1 vs 38.7 overall.
Only 67% 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.

R Obuya runs

Why we like it

Expected to face 14 balls at number 7
Opportunity drives the projection: 13.6 runs on average, 39 in the top 10% of simulations.
Recent form 23.1 runs an inningsLOW sample
Weighted over the last 4 innings at a strike rate of 133.5.
Against spinMEDIUM sample
226 runs off 182 balls in 18 T20 matches — strike rate 124.2 vs 122.0 overall, average 32.3 vs 20.7 overall.

Risks

Against paceHIGH sample
338 runs off 302 balls in 31 T20 matches — strike rate 111.9 vs 122.0 overall, average 16.1 vs 20.7 overall.
Only 82% 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.

JV Chand runs

Why we like it

Expected to face 17 balls at number 8
Opportunity drives the projection: 13.3 runs on average, 33 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.

Jakir Patel runs

Why we like it

Expected to face 14 balls at number 6
Opportunity drives the projection: 13.0 runs on average, 34 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.

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.