Cricket betting

Namibia v Ireland betting tips, prediction & odds

ODI · ODI · Friday 30 October at 07:30

Odds updated Fri, 30 Oct, 10:01 (UK time) · full refresh every day at 08:00, then hourly

Every number below comes from 9,941 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.

Namibia

Official team sheet

Order	Player	Role	Plays	Form runs	Overs
1	MB Kruger	batter	100%	18.2@ 72.5	—
2	L Steenkamp	batting allrounder	100%	—	—
3	JN Frylinck	batting allrounder	100%	15.2@ 56.7	—
4	MG Erasmus	batting allrounder	100%	28.3@ 68.6	—
5	JN Loftie-Eaton	wk-batter	100%	22.5@ 70.9	—
6	A Busing-Volschenk	batting allrounder	100%	—	—
7	ZE Green	wk-batter	100%	17.4@ 57.9	—
8	JJ Smit	bowling allrounder	100%	14.6@ 62.0	—
9	R Trumpelmann	bowler	100%	16.0@ 81.8	—
10	BM Scholtz	bowler	100%	7.0@ 65.4	—
11	JT Brassell	bowler	100%	0.3@ 7.6	—

No squad has been named for this side in this format in our records.

Ireland

Expected XI from selection history

Order	Player	Role	Plays	Form runs	Overs
1	PR Stirling	batter	97%	37.4@ 93.3	0.0
2	A Balbirnie	batter	97%	35.4@ 72.0	0.0
3	C Campher	all-rounder	72%	34.1@ 77.1	4.1
4	HT Tector	all-rounder	97%	32.1@ 79.5	3.0
5	AR McBrine	all-rounder	90%	15.6@ 97.1	7.4
6	L Tucker	batter	89%	32.2@ 100.0	0.0
7	GH Dockrell	all-rounder	97%	17.4@ 89.0	4.5
8	BJ McCarthy	all-rounder	45%	3.7@ 69.9	8.5
9	MR Adair	bowler	74%	14.0@ 90.5	8.2
10	CA Young	bowler	44%	15.0@ 119.5	7.7
11	GI Hume	bowler	53%	9.0@ 81.1	7.6
12	J Little	bowler	72%	5.3@ 87.1	7.9
13	MJ Humphreys	bowler	26%	0.9@ 55.2	7.5

Last named squad (West Indies v Ireland, 2025-05-25): A Balbirnie, AR McBrine, BJ McCarthy, C Carmichael, GH Dockrell, HT Tector, J Little, J Neill, L McCarthy, L Tucker, PR Stirling

Pitch & ground

High Performance Oval, Windhoek, Namibia

ODI average across all grounds

Average 1st innings: 237.8
Average 2nd innings: 198.3
Runs per over: 5.11
Boundary balls: 903%
Pace economy: 5.35
Spin economy: 4.95
Powerplay RPO: 4.69
Death RPO: 6.92
Chasing wins: 5144%
Batting first wins: 4856%
Matches counted: 867

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.
· Pitch numbers shown are the format-wide average because this ground has no stored record.

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 Fri, 30 Oct, 10:01 (UK time) · captured hourly from the live market

Batsman Fifty Ups (Individual Innings)


Curtis Campher 50 Ups	5	7	—	—	—
Lorcan Tucker 50 Ups	10	13	—	—	—

Batsman Ton Ups (Individual Innings)


Lorcan Tucker Ton Ups	0	2	—	—	—
Curtis Campher Ton Ups	0	0.5	—	—	—

Batsmans Runs (One Day)


Curtis Campher	38	42	23.5	sell	+14.5
Lorcan Tucker	53	57	13.7	sell	+39.3

Cricket Runs In Over


Ireland 37th Over Runs	6	6.5	192.1	buy	+185.6
Ireland 37th Over 100-50-0 Index - 6 Runs	41.6	49.5	192.1	buy	+142.6

Fall Of Next Wicket


5th Ireland Wkt	207	212	—	—	—

Innings Runs (1 Day Match)


Ireland Runs	273	279	192.1	sell	+80.9

Innings Runs Bands


175 Runs	96.5	100	—	—	—
200 Runs	96.5	100	—	—	—
225 Runs	94.5	99.5	—	—	—
250 Runs	78.9	86.4	—	—	—
275 Runs	47.8	55.8	—	—	—
300 Runs	17.4	24.3	—	—	—
325 Runs	1.5	8.7	—	—	—
350 Runs	0	3.5	—	—	—
375 Runs	0	3.5	—	—	—
400 Runs	0	3.5	—	—	—

Innings Runs Bands


170 Runs	96.5	100	—	—	—
180 Runs	96.5	100	—	—	—
190 Runs	96.5	100	—	—	—
200 Runs	96.5	100	—	—	—
210 Runs	96.5	100	—	—	—
220 Runs	96.1	100	—	—	—
230 Runs	92.1	98.9	—	—	—
240 Runs	87.2	93.9	—	—	—
250 Runs	78.9	86.4	—	—	—
260 Runs	68.7	75	—	—	—
270 Runs	54.7	62.9	—	—	—
280 Runs	41	48.9	—	—	—
290 Runs	27.9	35.8	—	—	—
300 Runs	17.4	24.3	—	—	—
310 Runs	9.2	15.9	—	—	—
320 Runs	3.3	10.7	—	—	—
330 Runs	0.5	6.6	—	—	—
340 Runs	0	3.9	—	—	—
350 Runs	0	3.5	—	—	—
360 Runs	0	3.5	—	—	—
370 Runs	0	3.5	—	—	—
380 Runs	0	3.5	—	—	—
390 Runs	0	3.5	—	—	—
400 Runs	0	3.5	—	—	—
410 Runs	0	3.5	—	—	—

Match Result


Namibia to win match	59.5	64.8	37.9	sell	+21.6
Ireland to win match	35.2	40.5	61.3	buy	+20.8

Multi Overs


Ireland Multi-Overs 37x38	37	42	—	—	—

Supremacy


Ireland/Namibia	7	17	21.7	buy	+4.7
Namibia/Ireland	9	19	-21.7	sell	+30.7

More ODI 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 29 replayed ODI 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.


Team runs line	Ireland under 200	56.5% (1.77)	29.00	back	+1537.1% EVFlagged
Team runs line	Ireland under 200	56.5% (1.77)	29.00	back	+1537.1% EVFlagged
Team runs	Ireland	192.1	273 – 279	sell	+80.9 runs
Match winner	Ireland	61.3% (1.63)	2.50	back	+53.2% EVFlagged
Player runs	L Tucker	13.7	53 – 57	sell	+39.3 runs
Match result index	Namibia to win match	37.9	59.5 – 64.8	sell	+21.6 pts
Match result index	Ireland to win match	61.3	35.2 – 40.5	buy	+20.8 pts
Player runs	C Campher	23.5	38 – 42	sell	+14.5 runs
Supremacy	Ireland/Namibia	21.7	7 – 17	buy	+4.7 runs
Match winner	Namibia	37.9% (2.64)	1.53	back	-41.9% 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


Namibia	37.9%	2.64	1.53	62.0%	-41.9%	59.5 – 64.8	61/100
Ireland	61.3%	1.63	2.50	38.0%	+53.2%	35.2 – 40.5	60/100

Namibia to win

Why we like it

Head-to-head: 0-0 in 4 stored ODI meetingsLOW sample
Namibia have won 0 of the 4 completed ODI matches we hold between these sides, the most recent on 30 Oct 2026.
Namibia full record

Risks

Projected runs: 170.4 vs 192.1
The simulation gives Namibia a -21.7 run expected margin over Ireland, from 9,941 simulated innings.
Model and market disagree too far to trust
Model 37.9% against 62.0% implied by 1.53 with the bookmaker margin stripped out — -41.9% 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 29 replayed ODI matches the model's log loss is 0.75 against a 0.69 coin-flip baseline, so this chance is shown as a comparison, not a tip.

Ireland to win

Why we like it

Head-to-head: 0-0 in 4 stored ODI meetingsLOW sample
Ireland have won 0 of the 4 completed ODI matches we hold between these sides, the most recent on 30 Oct 2026.
Ireland full record
Projected runs: 192.1 vs 170.4
The simulation gives Ireland a +21.7 run expected margin over Namibia, from 9,941 simulated innings.

Risks

Model and market disagree too far to trust
Model 61.3% against 38.0% implied by 2.50 with the bookmaker margin stripped out — +53.2% 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 29 replayed ODI matches the model's log loss is 0.75 against a 0.69 coin-flip baseline, so this chance is shown as a comparison, not a tip.

Supremacy spread

Ireland/Namibia

Market 7 – 17 · model expected margin 21.7 runs

Model edge: buy +4.7 runs per £1 a point

Team runs projection

Namibia

Projected 50-over innings total

170

median 160 · 10th–90th percentile 83–274

Wickets lost 4.7

Powerplay runs 46


120+	73.4%
140+	62.2%
160+	50.4%
180+	40.0%
200+	31.0%

confidence 61/100 · data 61/100

Ireland

Projected 50-over innings total

192

median 186 · 10th–90th percentile 99–296

Spreadex spread: 273 – 279model edge: sell +80.9 runs

Wickets lost 6.0

Powerplay runs 36


120+	82.3%
140+	73.7%
160+	63.4%
180+	53.1%
200+	43.5%

Live bookmaker prices


Under 200	56.5%	1.77	29.00	+1537.1%
Under 200	56.5%	1.77	29.00	+1537.1%
Under 190	51.7%	1.93	29.00	+1398.7%
Under 180	46.9%	2.13	29.00	+1260.3%
Under 175	44.3%	2.26	29.00	+1185.5%
Under 170	41.8%	2.40	29.00	+1110.8%

confidence 60/100 · data 61/100

Namibia runs

Why we like it

170.4 projected vs 237.8 parLOW sample
ODI average across all grounds averages 237.8 in the first innings over 867 matches; the model has Namibia below that by 67.5 runs.
Middle of the range 160.0, 10th–90th 83–274
Eight innings in ten finish inside that band, with 4.7 wickets lost on average and 45.8 powerplay runs.

Risks

Model has run 3.8 runs high in testing
Measured over 29 replayed ODI matches, average error 62.5 runs.

Ireland runs

Why we like it

192.1 projected vs 237.8 parLOW sample
ODI average across all grounds averages 237.8 in the first innings over 867 matches; the model has Ireland below that by 45.7 runs.
Middle of the range 186.0, 10th–90th 99–296
Eight innings in ten finish inside that band, with 6.0 wickets lost on average and 35.8 powerplay runs.
Model 192.1 against a 273–279 spread
Mid price 276.0. Expected 80.9 runs per £1 a point selling.
Under 200 priced 29.00, model fair odds 1.77
The simulation makes it 56.5% against 3.4% implied by the captured price — +1537.1% per £1 staked.

Risks

Model has run 3.8 runs high in testing
Measured over 29 replayed ODI matches, average error 62.5 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.


PR Stirling Ireland	38.8	26	95	97.0%	51	57.7%	29.9%	—	—
MG Erasmus Namibia	37.6	30	84	97.0%	55	63.3%	30.9%	—	—
HT Tector Ireland	36.9	27	89	97.0%	53	58.1%	30.7%	—	—
A Balbirnie Ireland	29.1	11	85	97.0%	49	40.7%	24.3%	—	—
M van Lingen Namibia	25.4	0	87	42.0%	59	35.0%	21.8%	—	—
C Campher Ireland	23.5	13	64	72.0%	45	41.0%	16.3%	38 – 42	sell +14.5
JN Frylinck Namibia	18.9	10	52	81.0%	37	34.9%	11.0%	—	—
ZE Green Namibia	16.9	8	48	82.0%	33	32.6%	9.2%	—	—
GH Dockrell Ireland	16.6	9	46	97.0%	27	32.3%	8.6%	—	—
JP Kotze Namibia	16.1	7	46	78.0%	27	28.2%	8.7%	—	—
L Tucker Ireland	13.7	6	39	89.0%	24	26.5%	5.5%	53 – 57	sell +39.3
AR McBrine Ireland	13.5	7	36	90.0%	26	25.5%	4.9%	—	—
JN Loftie-Eaton Namibia	13.3	2	41	86.0%	31	26.6%	6.8%	—	—
MB Kruger Namibia	12.7	4	37	87.0%	26	24.9%	5.4%	—	—
N Davin Namibia	12.6	0	43	43.0%	30	22.6%	8.2%	—	—
JJ Smit Namibia	10.1	0	33	97.0%	25	19.8%	4.2%	—	—
MR Adair Ireland	7.5	0	26	74.0%	14	14.5%	2.1%	—	—
R Trumpelmann Namibia	5.1	0	20	68.0%	20	10.4%	1.8%	—	—
CA Young Ireland	4.5	0	17	44.0%	19	8.9%	1.2%	—	—
GI Hume Ireland	4.1	0	16	53.0%	20	7.3%	0.6%	—	—
BJ McCarthy Ireland	3.9	0	15	45.0%	16	6.9%	0.7%	—	—
JI de Villiers Namibia	1.7	0	3	37.0%	19	3.2%	0.2%	—	—

PR Stirling runs

Why we like it

Expected to face 51 balls at number 1
Opportunity drives the projection: 38.8 runs on average, 95 in the top 10% of simulations.
Recent form 37.4 runs an inningsLOW sample
Weighted over the last 0 innings at a strike rate of 93.3.
Against spinHIGH sample
376 runs off 398 balls in 16 ODI matches — strike rate 94.5 vs 86.7 overall, average 41.8 vs 35.6 overall.

Risks

Against paceHIGH sample
833 runs off 1028 balls in 39 ODI matches — strike rate 81.0 vs 86.7 overall, average 34.7 vs 35.6 overall.

MG Erasmus runs

Why we like it

Expected to face 55 balls at number 6
Opportunity drives the projection: 37.6 runs on average, 84 in the top 10% of simulations.
Recent form 28.3 runs an inningsLOW sample
Weighted over the last 0 innings at a strike rate of 68.6.

HT Tector runs

Why we like it

Expected to face 53 balls at number 6
Opportunity drives the projection: 36.9 runs on average, 89 in the top 10% of simulations.
Recent form 32.1 runs an inningsLOW sample
Weighted over the last 0 innings at a strike rate of 79.5.
Against paceHIGH sample
839 runs off 923 balls in 40 ODI matches — strike rate 90.9 vs 85.2 overall, average 46.6 vs 47.7 overall.

Risks

Against spinHIGH sample
677 runs off 834 balls in 35 ODI matches — strike rate 81.2 vs 85.2 overall, average 37.6 vs 47.7 overall.

A Balbirnie runs

Why we like it

Expected to face 49 balls at number 2
Opportunity drives the projection: 29.1 runs on average, 85 in the top 10% of simulations.
Recent form 35.4 runs an inningsLOW sample
Weighted over the last 0 innings at a strike rate of 72.0.
Against spinHIGH sample
510 runs off 636 balls in 21 ODI matches — strike rate 80.2 vs 72.4 overall, average 102.0 vs 34.1 overall.

Risks

Against paceHIGH sample
551 runs off 838 balls in 38 ODI matches — strike rate 65.8 vs 72.4 overall, average 22.0 vs 34.1 overall.

M van Lingen runs

Why we like it

Expected to face 59 balls at number 2
Opportunity drives the projection: 25.4 runs on average, 87 in the top 10% of simulations.

Risks

Against spinHIGH sample
519 runs off 551 balls in 28 ODI matches — strike rate 94.2 vs 92.8 overall, average 34.6 vs 40.6 overall.
Only 42% 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.

C Campher runs

Why we like it

Expected to face 45 balls at number 3
Opportunity drives the projection: 23.5 runs on average, 64 in the top 10% of simulations.
Recent form 34.1 runs an inningsLOW sample
Weighted over the last 0 innings at a strike rate of 77.1.

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.

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.