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IPL verdict list

Greatest IPL Batters of All Time

AB de Villiers rises above Chris Gayle by a breath. Chris Gayle keeps the better consistency in IPL batting, 43.26 to 38.82. AB de Villiers's longevity in IPL batting settles it, 13.4 yrs · 184 matches to 12.4 yrs · 142 matches.

#1

Royal Challengers Bengaluru · latest recorded team

Verdict88.2
Average
39.71
Strike rate
151.69
Consistency
38.82
Average in wins
76.08
Volume
5,162 runs
Longevity
13.4 yrs · 184 matches
#2

Punjab Kings · latest recorded team

Verdict87.4
Average
39.72
Strike rate
148.96
Consistency
43.26
Average in wins
59.92
Volume
4,965 runs
Longevity
12.4 yrs · 142 matches
#3

Delhi Capitals · latest recorded team

Verdict86.0
Average
40.52
Strike rate
139.77
Consistency
52.17
Average in wins
60.82
Volume
6,565 runs
Longevity
15.0 yrs · 184 matches
#4

Gujarat Titans · latest recorded team

Verdict84.5
Average
39.71
Strike rate
149.73
Consistency
42.65
Average in wins
51.91
Volume
4,646 runs
Longevity
10.1 yrs · 138 matches
#5

Sunrisers Hyderabad · latest recorded team

Verdict84.0
Average
42.08
Strike rate
166.72
Consistency
55.00
Average in wins
59.42
Volume
2,104 runs
Longevity
8.1 yrs · 64 matches
#6

Delhi Capitals · latest recorded team

Verdict83.4
Average
46.15
Strike rate
139.25
Consistency
49.66
Average in wins
57.98
Volume
5,815 runs
Longevity
13.1 yrs · 159 matches
#7

Mumbai Indians · latest recorded team

Verdict80.9
Average
33.68
Strike rate
148.59
Consistency
40.24
Average in wins
45.07
Volume
4,581 runs
Longevity
14.1 yrs · 179 matches
#8

Gujarat Titans · latest recorded team

Verdict79.8
Average
40.33
Strike rate
142.09
Consistency
51.91
Average in wins
55.03
Volume
4,598 runs
Longevity
8.1 yrs · 134 matches
#9

Royal Challengers Bengaluru · latest recorded team

Verdict78.4
Average
40.42
Strike rate
134.80
Consistency
49.09
Average in wins
52.14
Volume
9,336 runs
Longevity
18.1 yrs · 283 matches
#10

Lucknow Super Giants · latest recorded team

Verdict76.1
Average
31.59
Strike rate
164.09
Consistency
39.60
Average in wins
49.36
Volume
2,527 runs
Longevity
7.2 yrs · 104 matches
Where the verdict was won
AB de Villiers
88.2 — led by Strike rate (31.4 of it), then Average in wins (16.0)
Chris Gayle
87.4 — led by Strike rate (30.2 of it), then Average (15.6)
David Warner
86.0 — led by Strike rate (23.3 of it), then Average (16.6)
Jos Buttler
84.5 — led by Strike rate (31.0 of it), then Average (15.4)
Heinrich Klaasen
84.0 — led by Strike rate (34.2 of it), then Average (16.8)
KL Rahul
83.4 — led by Strike rate (22.5 of it), then Average (17.0)
Suryakumar Yadav
80.9 — led by Strike rate (29.8 of it), then Average (12.9)
Shubman Gill
79.8 — led by Strike rate (24.5 of it), then Average (16.2)
Virat Kohli
78.4 — led by Strike rate (16.5 of it), then Average (16.4)
Nicholas Pooran
76.1 — led by Strike rate (33.4 of it), then Average in wins (13.8)
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 88 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.

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
IPLGreatest IPL Batters of All TimeTop 10