DeepMidwicket
← All verdict lists

Test + ODI + T20I verdict list

Greatest Test, ODI & T20I Batters of All Time

Virat Kohli rises above David Warner, and the edge holds. David Warner keeps the better strike rate in T20I batting, 142.84 to 137.15. Virat Kohli's average in wins in T20I batting settles it, 60.96 to 39.25.

#1
Combined92.0
Test
91.3
ODI
97.6
T20I
87.2
#2
David Warner

Australia

Combined88.6
Test
88.2
ODI
93.9
T20I
83.8
#3
Combined84.8
Test
81.1
ODI
95.5
T20I
77.7
#4
Babar Azam

Pakistan

Combined84.7
Test
86.5
ODI
92.2
T20I
75.3
#5
Quinton de Kock

South Africa

Combined83.3
Test
78.9
ODI
93.9
T20I
77.2
#6
Combined81.8
Test
65.8
ODI
90.2
T20I
89.3
#7
Kane Williamson

New Zealand

Combined81.1
Test
94.3
ODI
90.9
T20I
58.1
#8
Combined80.7
Test
77.7
ODI
88.6
T20I
75.9
#9
Chris Gayle

West Indies

Combined79.0
Test
86.8
ODI
87.8
T20I
62.3
#10
AB de Villiers

South Africa

Combined78.8
Test
94.4
ODI
97.3
T20I
44.7
Where the verdict was won: Test
Virat Kohli
91.3 — led by Average (26.1 of it), then Volume (24.6)
David Warner
88.2 — led by Average (25.2 of it), then Volume (24.5)
Rohit Sharma
81.1 — led by Average (23.3 of it), then Volume (22.2)
Babar Azam
86.5 — led by Average (24.5 of it), then Volume (22.6)
Quinton de Kock
78.9 — led by Average (22.3 of it), then Volume (21.0)
Jos Buttler
65.8 — led by Volume (20.3 of it), then Average (18.1)
Kane Williamson
94.3 — led by Average (27.5 of it), then Volume (24.7)
KL Rahul
77.7 — led by Volume (22.1 of it), then Average (20.7)
Chris Gayle
86.8 — led by Volume (24.0 of it), then Average (23.9)
AB de Villiers
94.4 — led by Average (27.0 of it), then Volume (24.5)
Each bar is that player’s score out of 100, split into what produced it: segment length is the facet’s peer score times its weight. Darkest segment first. The segments add up to the score, so the bars are read against each other, not against a grid.
Where the verdict was won: ODI
Virat Kohli
97.6 — led by Average (20.0 of it), then Strike rate (16.0)
David Warner
93.9 — led by Average (19.3 of it), then Strike rate (16.5)
Rohit Sharma
95.5 — led by Average (19.7 of it), then Strike rate (15.7)
Babar Azam
92.2 — led by Average (19.9 of it), then Volume (14.0)
Quinton de Kock
93.9 — led by Average (19.4 of it), then Strike rate (16.5)
Jos Buttler
90.2 — led by Strike rate (17.9 of it), then Average (17.5)
Kane Williamson
90.9 — led by Average (19.6 of it), then Volume (14.3)
KL Rahul
88.6 — led by Average (19.7 of it), then Strike rate (15.3)
Chris Gayle
87.8 — led by Average (17.3 of it), then Volume (14.8)
AB de Villiers
97.3 — led by Average (19.9 of it), then Strike rate (17.0)
Each bar is that player’s score out of 100, split into what produced it: segment length is the facet’s peer score times its weight. Darkest segment first. The segments add up to the score, so the bars are read against each other, not against a grid.
Where the verdict was won: T20I
Virat Kohli
87.2 — led by Strike rate (19.0 of it), then Average (15.0)
David Warner
83.8 — led by Strike rate (25.1 of it), then Average (12.6)
Rohit Sharma
77.7 — led by Strike rate (22.3 of it), then Average (11.8)
Babar Azam
75.3 — led by Average (14.7 of it), then Average vs strong opposition (11.6)
Quinton de Kock
77.2 — led by Strike rate (23.9 of it), then Average (10.9)
Jos Buttler
89.3 — led by Strike rate (27.9 of it), then Average (13.0)
Kane Williamson
58.1 — led by Average (12.4 of it), then Average vs strong opposition (9.9)
KL Rahul
75.9 — led by Strike rate (21.7 of it), then Average (14.4)
Chris Gayle
62.3 — led by Strike rate (19.3 of it), then Average (8.7)
AB de Villiers
44.7 — led by Strike rate (16.8 of it), then Average (6.7)
Each bar is that player’s score out of 100, split into what produced it: segment length is the facet’s peer score times its weight. Darkest segment first. The segments add up to the score, so the bars are read against each other, not against a grid.

Transparent by design

How this ranking was calculated

The list is computed from scorecards, not selected by an AI model. Every player is measured against the same qualified peer population, and the rules below determine the order.

From scorecards to a verdict score
  1. Build the eligible peer population using the selected format, time window and qualification bars.
  2. Calculate every batting or bowling factor directly from the matching scorecards.
  3. Convert each factor to a score against qualified peers, respecting whether higher or lower is better.
  4. Apply the published weights. If a factor is unavailable, its weight is redistributed across that player's recorded factors.
  5. Add the weighted factors to produce the verdict score out of 100, then rank from highest to lowest.
Batting factors and weights

Compared with 1,218 batters who played at least 20 innings.

Batting factors and weights

Compared with 867 batters who played at least 20 innings.

Batting factors and weights

Compared with 99 batters who played at least 60 innings and scored at least 1,000 runs.

Important scoring choices

Longevity: uses the square root of career span in years multiplied by matches selected. Match counts and first/last dates come from playing-XI appearances, so a did-not-bat or did-not-bowl match still counts.

Contribution: total runs or wickets measure output within the selected period.

Test average magnitude: overall averages use 85% peer position and 15% raw distance from the best qualified average. For bowlers the ratio is reversed because a lower average is better. Contextual averages remain pure percentiles.

ODI eligibility: this curated list includes players representing current ICC full-member teams. All of their recorded opposition still counts.

Editorial scope: this is a transparent judgement model, not an official record table. It does not insert or promote named players, and it applies no blanket era multiplier.

Data and query audit
Test + ODI + T20IGreatest Test, ODI & T20I Batters of All TimeTop 10