Somerset vs Sussex Scorecard & Result

CCH ·Match 27

Finished

Somerset

NLNLW

338 & 150/5

(39.2 ov)

Sussex

NWNLW

152 & 335

(97.3 ov)

Somerset won by 5 wickets

·22·····

4 runs

1·41·1

7 runs

·W··W1

1 runs

1·211·

5 runs

31b1··

5 runs

··241W

7 runs

·4···1

5 runs

··1···

1 runs

·41···

5 runs

····1·

1 runs

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0 runs

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0 runs

····42

6 runs

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0 runs

·1····

1 runs

1·411·

7 runs

b·4·1·

5 runs

·1·11·

3 runs

·1···1

2 runs

·2·411

8 runs

·111··

3 runs

···2·1

3 runs

111··1

4 runs

···2··

2 runs

·1··41

6 runs

211··W

4 runs

·441·1

10 runs

··1···

1 runs

2····1

3 runs

···1··

1 runs

··1·12

4 runs

······

0 runs

1·4···

5 runs

4·····

4 runs

··11·2

4 runs

···W··

0 runs

·4·441

13 runs

1·····

1 runs

·1··4·

5 runs

·1

1 runs

Batting

RB4s6sSR

LLewis GregoryL. Gregory

93 118 12 0 78.8

JJosh DaveyJ. Davey

2 5 0 0 40

Bowling

OMRWEcon

JJames ColesJ. Coles

11.2 2 28 2 2.5

OOllie Edward RobinsonO. Robinson

8.2 1 27 2 3.2

MATCH STATS SOM SUS

PP 49/4 (4) 48/0 (3.9)

Middle 43/0 (2.1) 94/2 (4.5)

Death 370/11 (3.3) 324/18 (2.9)

4s 61 58

6s 0 2

Dots 71% 70%

Extras 1 4

Best P'ship 75(6) 96(11)

Date and time 16/05/2025 · 13:00

Competition County Championship · Match 27

Toss Sussex won the toss, elected to bowling

Playing XI

Lewis Gregory —

Josh Davey —

Tom Lammonby —

James Rew —

Tom Abell —

Tom Banton —

AM Vaughan —

Craig Overton —

Migael Pretorius —

Matt Henry —

Jack Leach —

Playing XI

Daniel Hughes —

Thomas Haines —

Tom Clark —

Tom Alsop —

James Coles —

John Simpson —

Fynn Hudson-Prentice —

Jack Carson —

Nathan McAndrew —

Ollie Edward Robinson —

James Hayes —

Form — last 10 matches

3W4L43%

WOWorcestershire 154/10

WAWarwickshire 337/10

SOSomerset 239/10

22-08-2024 · CCH

Head-to-head — last 5

SO2–1

Form — last 10 matches

5W2L71%

WOWorcestershire 180/10

09-05-2025 · CCH

SUSussex 169/10

NONottinghamshire 300/10

WAWarwickshire 454/10

GLGloucestershire 109/10

Predictions Stat

0%20%40%60%80%100%7 Sept2 Oct21 Oct

Method	Accuracy	Record	ROI
ML	61.5%	32 – 20	-13.8%
AI 1	64.2%	34 – 19	-8.8%
AI 2	64.2%	34 – 19	-9.3%
Math	57.7%	30 – 22	-17%
Books	73.6%	39 – 14	+5%

How we measure thisUpdated 21 Oct 2026