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Test verdict list

Best Test Bowlers of the 1990s

Curtly Ambrose rises above Wasim Akram, and the edge holds. Wasim Akram keeps the better wicket-taking consistency in Test bowling, 52.25 to 39.84. Curtly Ambrose's bowling average vs strong opposition in Test bowling settles it, 21.14 to 24.06.

#1

West Indies

Verdict96.1
Bowling average
20.14
Bowling strike rate
52.26
Away bowling average
21.01
Bowling average vs strong opposition
21.14
Wicket-taking consistency
39.84
Bowling average in wins
15.16
Volume
309 wickets
#2

Pakistan

Verdict93.8
Bowling average
21.45
Bowling strike rate
48.91
Away bowling average
23.46
Bowling average vs strong opposition
24.06
Wicket-taking consistency
52.25
Bowling average in wins
17.19
Volume
289 wickets
#3

South Africa

Verdict93.5
Bowling average
21.83
Bowling strike rate
45.76
Away bowling average
21.77
Bowling average vs strong opposition
24.65
Wicket-taking consistency
51.43
Bowling average in wins
16.49
Volume
284 wickets
#4

Pakistan

Verdict92.6
Bowling average
21.71
Bowling strike rate
40.95
Away bowling average
24.49
Bowling average vs strong opposition
25.10
Wicket-taking consistency
50.50
Bowling average in wins
17.74
Volume
273 wickets
#5

South Africa

Verdict89.4
Bowling average
20.46
Bowling strike rate
52.61
Away bowling average
20.59
Bowling average vs strong opposition
23.45
Wicket-taking consistency
40.30
Bowling average in wins
15.57
Volume
161 wickets
#6

Australia

Verdict88.5
Bowling average
22.88
Bowling strike rate
52.47
Away bowling average
22.67
Bowling average vs strong opposition
27.27
Wicket-taking consistency
44.64
Bowling average in wins
20.85
Volume
266 wickets
#7

Australia

Verdict87.6
Bowling average
25.67
Bowling strike rate
64.32
Away bowling average
27.34
Bowling average vs strong opposition
21.97
Wicket-taking consistency
47.95
Bowling average in wins
21.35
Volume
351 wickets
#8

West Indies

Verdict86.4
Bowling average
25.97
Bowling strike rate
59.47
Away bowling average
26.54
Bowling average vs strong opposition
23.78
Wicket-taking consistency
37.76
Bowling average in wins
20.51
Volume
304 wickets
#9

West Indies

Verdict85.0
Bowling average
24.41
Bowling strike rate
52.31
Away bowling average
24.06
Bowling average vs strong opposition
22.66
Wicket-taking consistency
39.13
Bowling average in wins
16.54
Volume
145 wickets
#10

Zimbabwe

Verdict81.9
Bowling average
24.56
Bowling strike rate
55.54
Away bowling average
26.60
Bowling average vs strong opposition
22.84
Wicket-taking consistency
43.75
Bowling average in wins
16.40
Volume
111 wickets
Where the verdict was won
Curtly Ambrose
96.1 — led by Volume (34.1 of it), then Bowling average (29.4)
Wasim Akram
93.8 — led by Volume (33.3 of it), then Bowling average (28.5)
Allan Donald
93.5 — led by Volume (33.0 of it), then Bowling average (28.0)
Waqar Younis
92.6 — led by Volume (32.6 of it), then Bowling average (28.3)
Shaun Pollock
89.4 — led by Bowling average (28.9 of it), then Volume (28.9)
Glenn McGrath
88.5 — led by Volume (32.2 of it), then Bowling average (27.4)
Shane Warne
87.6 — led by Volume (35.0 of it), then Bowling average (25.1)
Courtney Walsh
86.4 — led by Volume (33.8 of it), then Bowling average (24.8)
Ian Bishop
85.0 — led by Volume (28.1 of it), then Bowling average (25.7)
Heath Streak
81.9 — led by Volume (25.8 of it), then Bowling average (25.4)
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.
Bowling factors and weights

Compared with 118 bowlers who played at least 10 innings and bowled at least 1,500 balls.

Important scoring choices

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

Fixed-era weighting: longevity is not scored because a player should not be penalised when only part of their career overlaps the era. Its allocation moves to runs or wickets.

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.

Wicket magnitude: career and long-era wicket volume uses 85% peer position and 15% raw distance from the leading qualified wicket total. This preserves the difference between exceptional totals that sit together at the top of a percentile table. Run volume stays a pure percentile, because career run totals vary far more widely and blending raw magnitude there would penalise a short career of outstanding quality.

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
TestBest Test Bowlers of the 1990sTop 10