Cricket has had a curious
relationship with numbers. The sport compiles the achievements of its players
in rich and detailed statistics. It celebrates a batting average in the 50s and
a bowling average in the 20s as some kind of an irrefutable stamp of greatness.
At other times, cricket and its patrons can be notorious in completely ignoring
it in favour of subjective narratives too. Looking at the numbers alone, to
argue for Gavaskar over Viswanath is a no brainer. But I strongly advise anyone
to stay away from it with Indian cricket fans of that generation.
To be fair, it's not necessarily contradictory.
In fact, for a sport which has undergone tremendous amount of change over the
years, some of its statistical measures have survived rather well. One such
measure is the batting average of 50: it is one of cricket's great constants.
Of course, it's not always unimpeachable. There are the 50ers who aren't quite
hall of famers, and there are hall of famers without achieving the 50
benchmark. But its value as a currency of greatness has largely stood the
test of time almost throughout Test cricket's life term. Even with
noticeable exceptions, that's quite an incredible feat.
While acknowledging the idea of
putting the 50 benchmark on a pedestal, cricket fans tend to get into the
nuances. How does the 50 spread out? Is it too skewed in favour of performances
at home? How is the record against the top ranked teams of that era? Didn't he
play in an era of mediocre bowlers and flat pitches? and so on. Some of the
questions are entirely subjective, others may not be. For instance, let me take
up the point about playing in an era of mediocre bowlers and flat pitches. Is
there a way to make it more objective for comparisons? I make an attempt.
A batsman can only play in an era
that he belongs to. If a particular era is more favourable to score runs than
others, it should have been the case for all players of that era and vice versa.
So, instead of looking at the absolute averages, we can perhaps look at the
incremental average of a batsman over the rest of his contemporaries. Now, how
do we define contemporaries? Gooch was Tendulkar's contemporary and so is
Murali Vijay.
I am going to take the first day
and last day of test cricket of a batsman and calculate the aggregate average
of all batsmen in that time period. For instance, for Kallis, the time period
is from December 14, 1995 to December 30, 2013. The average of a batsman (runs
scored by all batsmen/number of dismissals) in the period is 31.42, and the
career average of Kallis was 55.37. On an average he scored 23.94 runs more per
innings than the aggregate average. Let's call this incremental average the
alpha average. Now, batsmen can be compared across eras on the basis of the
alpha average.
I get it, the incremental
percentage of the runs scored over the aggregate average is a marginally more
sound indicator, but I like the idea of an absolute number of alpha average
because of my bias for the portability of a standalone metric but have given
both below.
For the purpose of this exercise,
I have taken all batsmen who average 50 and more and have played a minimum of
20 tests. Cut off date is Sep 18, 2014.
Player
|
Span
|
Mat
|
Ave
|
Average rank
|
1928-1948
|
52
|
99.94
|
1
|
|
1963-1970
|
23
|
60.97
|
2
|
|
1930-1954
|
22
|
60.83
|
3
|
|
1924-1935
|
54
|
60.73
|
4
|
|
1931-1939
|
20
|
59.23
|
5
|
|
2000-2014
|
128
|
58.76
|
6
|
|
1955-1968
|
82
|
58.67
|
7
|
|
1948-1958
|
48
|
58.61
|
8
|
|
1927-1947
|
85
|
58.45
|
9
|
|
1954-1974
|
93
|
57.78
|
10
|
|
1908-1930
|
61
|
56.94
|
11
|
|
1948-1960
|
44
|
56.68
|
12
|
|
1937-1955
|
79
|
56.67
|
13
|
|
1995-2013
|
166
|
55.37
|
14
|
|
1970-1984
|
87
|
53.86
|
15
|
|
1935-1951
|
34
|
53.81
|
16
|
|
1989-2013
|
200
|
53.78
|
17
|
|
1994-2014
|
158
|
53.1
|
18
|
|
1990-2006
|
131
|
52.88
|
19
|
|
2009-2014
|
44
|
52.65
|
20
|
|
1976-1993
|
124
|
52.57
|
21
|
|
1996-2012
|
164
|
52.31
|
22
|
|
1998-2010
|
90
|
52.29
|
23
|
|
1995-2012
|
168
|
51.85
|
24
|
|
1920-1929
|
20
|
51.62
|
25
|
|
1992-2002
|
63
|
51.54
|
26
|
|
2005-2013
|
79
|
51.52
|
27
|
|
2004-2014
|
105
|
51.5
|
28
|
|
2000-2014
|
91
|
51.41
|
29
|
|
2004-2014
|
79
|
51.32
|
30
|
|
1971-1987
|
125
|
51.12
|
31
|
|
1985-2004
|
168
|
51.06
|
32
|
|
2004-2014
|
95
|
51.02
|
33
|
|
2012-2014
|
22
|
50.94
|
34
|
|
1994-2009
|
103
|
50.73
|
35
|
|
1978-1994
|
156
|
50.56
|
36
|
|
1974-1991
|
121
|
50.23
|
37
|
|
1937-1957
|
78
|
50.06
|
38
|
.
Player
|
Average
|
Average
rank
|
Aggregate
Average
|
Alpha
average
|
Alpha
Avg Rank
|
Avg
rank - alpha avg rank
|
99.94
|
1
|
31.85
|
68.09
|
1
|
0
|
|
60.97
|
2
|
30.73
|
30.24
|
2
|
0
|
|
60.73
|
4
|
30.87
|
29.86
|
3
|
1
|
|
60.83
|
3
|
31.05
|
29.78
|
4
|
-1
|
|
58.61
|
8
|
29.19
|
29.42
|
5
|
3
|
|
58.67
|
7
|
29.87
|
28.80
|
6
|
1
|
|
59.23
|
5
|
30.57
|
28.66
|
7
|
-2
|
|
56.68
|
12
|
28.7
|
27.98
|
8
|
4
|
|
57.78
|
10
|
29.97
|
27.81
|
9
|
1
|
|
58.45
|
9
|
31.21
|
27.24
|
10
|
-1
|
|
56.94
|
11
|
29.82
|
27.12
|
11
|
0
|
|
58.76
|
6
|
32.33
|
26.43
|
12
|
-6
|
|
56.67
|
13
|
30.58
|
26.09
|
13
|
0
|
|
55.37
|
14
|
31.43
|
23.94
|
14
|
0
|
|
53.86
|
15
|
30.42
|
23.44
|
15
|
0
|
|
53.78
|
17
|
31.17
|
22.61
|
16
|
1
|
|
52.57
|
21
|
30.09
|
22.48
|
17
|
4
|
|
52.88
|
19
|
30.57
|
22.31
|
18
|
1
|
|
51.54
|
26
|
29.67
|
21.87
|
19
|
7
|
|
53.1
|
18
|
31.35
|
21.75
|
20
|
-2
|
|
53.81
|
16
|
32.49
|
21.32
|
21
|
-5
|
|
51.06
|
32
|
30.16
|
20.90
|
22
|
10
|
|
52.31
|
22
|
31.42
|
20.89
|
23
|
-1
|
|
51.12
|
31
|
30.43
|
20.69
|
24
|
7
|
|
52.29
|
23
|
31.62
|
20.67
|
25
|
-2
|
|
51.85
|
24
|
31.49
|
20.36
|
26
|
-2
|
|
50.56
|
36
|
30.22
|
20.34
|
27
|
9
|
|
50.06
|
38
|
29.77
|
20.29
|
28
|
10
|
|
52.65
|
20
|
32.36
|
20.29
|
29
|
-9
|
|
50.23
|
37
|
30.2
|
20.03
|
30
|
7
|
|
50.73
|
35
|
30.82
|
19.91
|
31
|
4
|
|
51.62
|
25
|
31.73
|
19.89
|
32
|
-7
|
|
51.41
|
29
|
32.11
|
19.30
|
33
|
-4
|
|
50.94
|
34
|
31.68
|
19.26
|
34
|
0
|
|
51.5
|
28
|
32.43
|
19.07
|
35
|
-7
|
|
51.32
|
30
|
32.51
|
18.81
|
36
|
-6
|
|
51.52
|
27
|
32.86
|
18.66
|
37
|
-10
|
|
51.02
|
33
|
32.54
|
18.48
|
38
|
-5
|
Out of the 38 players, 8 players jump down by 5 ranking
slots or more when the parameter is
changed from average to alpha average: Hussey(-10), Mathews(-9), Ryder(-7),
Clarke(-7), Sangakkara(-6), Amla(-6), Nourse (-5) and De Villiers (-5). Except
Nourse and Ryder, the other 6 players belong to the last decade and half. This
lends credibility to the notion that run scoring has become easier in recent
times partly because of dearth of quality bowlers, flatter tracks and perhaps
even better bats.
On
other hand, 6 players jump up the ranking by 5 ranking slots or more when you change
the parameter: Hayden, Flower, Gavaskar, Richards, Border, Waugh and Compton . Curiously, all
these players average over 50, none average more than 51.54.
Ranking based on alpha
percentage:
Player
|
Average
|
Average
rank
|
Aggregate
Average
|
Alpha
average
|
Alpha
percentage
|
Alpha
% Rank
|
Avg
rank - alpha % rank
|
99.94
|
1
|
31.85
|
68.09
|
214%
|
1
|
0
|
|
58.61
|
8
|
29.19
|
29.42
|
101%
|
2
|
6
|
|
60.97
|
2
|
30.73
|
30.24
|
98%
|
3
|
-1
|
|
56.68
|
12
|
28.7
|
27.98
|
97%
|
4
|
8
|
|
60.73
|
4
|
30.87
|
29.86
|
97%
|
5
|
-1
|
|
58.67
|
7
|
29.87
|
28.80
|
96%
|
6
|
1
|
|
60.83
|
3
|
31.05
|
29.78
|
96%
|
7
|
-4
|
|
59.23
|
5
|
30.57
|
28.66
|
94%
|
8
|
-3
|
|
57.78
|
10
|
29.97
|
27.81
|
93%
|
9
|
1
|
|
56.94
|
11
|
29.82
|
27.12
|
91%
|
10
|
1
|
|
58.45
|
9
|
31.21
|
27.24
|
87%
|
11
|
-2
|
|
56.67
|
13
|
30.58
|
26.09
|
85%
|
12
|
1
|
|
58.76
|
6
|
32.33
|
26.43
|
82%
|
13
|
-7
|
|
53.86
|
15
|
30.42
|
23.44
|
77%
|
14
|
1
|
|
55.37
|
14
|
31.43
|
23.94
|
76%
|
15
|
-1
|
|
52.57
|
21
|
30.09
|
22.48
|
75%
|
16
|
5
|
|
51.54
|
26
|
29.67
|
21.87
|
74%
|
17
|
9
|
|
52.88
|
19
|
30.57
|
22.31
|
73%
|
18
|
1
|
|
53.78
|
17
|
31.17
|
22.61
|
73%
|
19
|
-2
|
|
53.1
|
18
|
31.35
|
21.75
|
69%
|
20
|
-2
|
|
51.06
|
32
|
30.16
|
20.90
|
69%
|
21
|
11
|
|
50.06
|
38
|
29.77
|
20.29
|
68%
|
22
|
16
|
|
51.12
|
31
|
30.43
|
20.69
|
68%
|
23
|
8
|
|
50.56
|
36
|
30.22
|
20.34
|
67%
|
24
|
12
|
|
52.31
|
22
|
31.42
|
20.89
|
66%
|
25
|
-3
|
|
50.23
|
37
|
30.2
|
20.03
|
66%
|
26
|
11
|
|
53.81
|
16
|
32.49
|
21.32
|
66%
|
27
|
-11
|
|
52.29
|
23
|
31.62
|
20.67
|
65%
|
28
|
-5
|
|
51.85
|
24
|
31.49
|
20.36
|
65%
|
29
|
-5
|
|
50.73
|
35
|
30.82
|
19.91
|
65%
|
30
|
5
|
|
52.65
|
20
|
32.36
|
20.29
|
63%
|
31
|
-11
|
|
51.62
|
25
|
31.73
|
19.89
|
63%
|
32
|
-7
|
|
50.94
|
34
|
31.68
|
19.26
|
61%
|
33
|
1
|
|
51.41
|
29
|
32.11
|
19.30
|
60%
|
34
|
-5
|
|
51.5
|
28
|
32.43
|
19.07
|
59%
|
35
|
-7
|
|
51.32
|
30
|
32.51
|
18.81
|
58%
|
36
|
-6
|
|
51.02
|
33
|
32.54
|
18.48
|
57%
|
37
|
-4
|
|
51.52
|
27
|
32.86
|
18.66
|
57%
|
38
|
-11
|
While the change in ranks gives a sense of who has
been relatively better off or worse off in playing in the era that they did,
just sorting the alpha average from high to low presents an interesting picture
too. Down the bottom, we see the players of the last 15 years crowd out others
- Sangakkara is the stand out exception. But at the same time, players whose
careers stretched from the 1990s till the 2000s and even the 2010s, like
Tendulkar, Kallis, Dravid, Lara, Ponting, and Chanderpaul are still somewhere
in the middle. This could mean two things: 1) Run scoring in the 90s was
difficult and these guys were a class above the rest or 2) They made up for
their relative drought of the 90s by feasting in the 2000s and boosting their
overall alpha average. Let's see:
Individual Average
|
Aggregate Average
|
Alpha Average
|
Matches
|
|||||||||
1990s
|
2000s
|
2010s
|
1990s
|
2000s
|
2010s
|
1990s
|
2000s
|
2010s
|
1990s
|
2000s
|
2010s
|
|
Tendulkar
|
56.70
|
54.35
|
50.01
|
29.63
|
32.02
|
32.03
|
27.07
|
22.33
|
17.98
|
73
|
89
|
38
|
Kallis
|
41.08
|
58.70
|
53.68
|
29.13
|
32.02
|
32.04
|
11.95
|
26.68
|
21.64
|
32
|
101
|
33
|
Dravid
|
49.96
|
54.85
|
46.18
|
28.99
|
32.02
|
32.51
|
20.97
|
22.83
|
13.67
|
34
|
103
|
27
|
Lara
|
51.60
|
54.06
|
N.A
|
29.41
|
31.66
|
N.A
|
22.19
|
22.40
|
N.A
|
65
|
66
|
0
|
Ponting
|
44.51
|
58.38
|
37.30
|
29.19
|
32.02
|
32.57
|
15.32
|
26.36
|
4.73
|
33
|
107
|
28
|
Chanderpaul
|
40.61
|
52.31
|
71.78
|
29.23
|
32.02
|
32.22
|
11.38
|
20.29
|
39.56
|
37
|
86
|
35
|
Tendulkar's
alpha average was way higher in the 1990s than in the 2000s. It's both a
testimony to the fact that he was a notch above the rest in the 90s when run
scoring was harder, and also a reflection of his somewhat relatively more
mortal self in the 2000s that he doesn't quite tower above the rest.
In the
case of Kallis, Ponting and Chanderpaul, the lower alpha averages is more an
indication of their early phase of batting career and trying to establish
themselves rather than their struggle in a harder decade for batting. But they
were clearly helped by the fact that their batting peak reached in a relatively
easier time for batting. Chanderpaul seems to be peaking where most careers
will be on the wane.
For a
player establishing himself in the 1990s, Dravid was considerably better than
Kallis, Ponting and Chanderpaul. But he didn't capitalize in the next decade as
much as Kallis and Ponting did, though his alpha average in the 2000s is very
healthy too.
The
decade of play doesn't make a difference to Lara as he was equally consistent
in both, though he didn't particularly tower over the rest in either decades.
While
it is fair to compare the incremental average over the aggregate average, it
still leaves room for ambiguity because of the inclusion of tail enders and
keepers in the mix. There are the often repeated assertions in cricket that the
ability of tail enders with the bat has improved considerably in modern times,
and wicket keeper batsmen aren’t the same since Gilchrist happened. It’ll be a
worthwhile exercise to test these notions separately, but for the sake of this
theme, let’s just remove them from the equation and compare the just the top
order aggregate averages and work the batsman’s alpha average based on that.
Player
|
Average
|
Average rank
|
Top 6
|
Alpha Top 6 Avg
|
Alpha Avg (Top 6) Rank
|
Alpha avg rank - Alpha top 6 avg
rank
|
Alpha Avg Rank
|
99.94
|
1
|
39.99
|
59.95
|
1
|
0
|
1
|
|
60.97
|
2
|
38.07
|
22.90
|
2
|
0
|
2
|
|
60.73
|
4
|
38.20
|
22.53
|
3
|
0
|
3
|
|
58.61
|
8
|
36.17
|
22.44
|
4
|
1
|
5
|
|
60.83
|
3
|
38.94
|
21.89
|
5
|
-1
|
4
|
|
58.67
|
7
|
36.98
|
21.69
|
6
|
0
|
6
|
|
56.68
|
12
|
35.63
|
21.05
|
7
|
1
|
8
|
|
59.23
|
5
|
38.27
|
20.96
|
8
|
-1
|
7
|
|
57.78
|
10
|
36.88
|
20.90
|
9
|
0
|
9
|
|
56.94
|
11
|
36.49
|
20.45
|
10
|
1
|
11
|
|
58.45
|
9
|
38.92
|
19.53
|
11
|
-1
|
10
|
|
58.76
|
6
|
39.82
|
18.94
|
12
|
0
|
12
|
|
56.67
|
13
|
38.13
|
18.54
|
13
|
0
|
13
|
|
53.86
|
15
|
37.23
|
16.63
|
14
|
1
|
15
|
|
55.37
|
14
|
38.80
|
16.57
|
15
|
-1
|
14
|
|
52.57
|
21
|
36.86
|
15.71
|
16
|
1
|
17
|
|
53.78
|
17
|
38.50
|
15.28
|
17
|
-1
|
16
|
|
52.88
|
19
|
37.92
|
14.96
|
18
|
0
|
18
|
|
51.54
|
26
|
36.80
|
14.74
|
19
|
0
|
19
|
|
53.1
|
18
|
38.63
|
14.47
|
20
|
0
|
20
|
|
51.12
|
31
|
37.13
|
13.99
|
21
|
3
|
24
|
|
51.06
|
32
|
37.30
|
13.76
|
22
|
0
|
22
|
|
52.31
|
22
|
38.84
|
13.47
|
23
|
0
|
23
|
|
50.56
|
36
|
37.09
|
13.47
|
24
|
3
|
27
|
|
50.23
|
37
|
36.94
|
13.29
|
25
|
5
|
30
|
|
50.06
|
38
|
36.80
|
13.26
|
26
|
2
|
28
|
|
51.62
|
25
|
38.43
|
13.19
|
27
|
5
|
32
|
|
52.29
|
23
|
39.14
|
13.15
|
28
|
-3
|
25
|
|
52.65
|
20
|
39.50
|
13.15
|
29
|
0
|
29
|
|
51.85
|
24
|
38.86
|
12.99
|
30
|
-4
|
26
|
|
53.81
|
16
|
41.11
|
12.70
|
31
|
-10
|
21
|
|
50.73
|
35
|
38.11
|
12.62
|
32
|
-1
|
31
|
|
50.94
|
34
|
38.68
|
12.26
|
33
|
1
|
34
|
|
51.41
|
29
|
39.53
|
11.88
|
34
|
-1
|
33
|
|
51.5
|
28
|
39.69
|
11.81
|
35
|
0
|
35
|
|
51.32
|
30
|
39.80
|
11.52
|
36
|
0
|
36
|
|
51.52
|
27
|
40.23
|
11.29
|
37
|
0
|
37
|
|
51.02
|
33
|
39.83
|
11.19
|
38
|
0
|
38
|
As convincing as the argument to
separate the keepers and tail enders was, the result isn’t particularly
telling. Richards and Ryder move up 5 ranks, possibly indicating the relatively
better batting abilities of tail enders and/or the keepers of their time. They
did much better when compared against their contemporary top 6 than when
compared against their contemporary aggregate of all 11. Rest are all marginal
differences in ranks except Nourse, who quite amazingly moves down by 10 ranks.
The top 6 of his time averaged a whopping 41.11! Does the fact that his career
coincided with that of Bradman's have anything to do with this handsome top
order average?
The aggregate record during
Bradman's time:
overall
|
409
|
1928-1948
|
128
|
4376
|
584
|
120798
|
364
|
31.85
|
254
|
Bradman's record:
Mat |
Inns
|
NO
|
Runs
|
HS
|
Ave
|
100
|
|
Tests
|
52
|
80
|
10
|
6996
|
334
|
99.94
|
29
|
Removing Bradman alone from the
409 players over those two decades:
Runs
|
||||||||||
Aggregate
|
408
|
1928-1948
|
128
|
4296
|
574
|
113802
|
364
|
30.58
|
225
|
The top 6 record of his time:
Players
|
Span
|
Mat
|
Inns
|
NO
|
Runs
|
HS
|
Ave
|
100
|
259
|
1928-1948
|
128
|
2612
|
196
|
96631
|
364
|
39.99
|
238
|
Removing Bradman from the list:
258
|
1928-1948
|
128
|
2532
|
186
|
89635
|
364
|
38.21
|
209
|
Bradman as an individual makes a
difference of 1.27 runs per batsman for the 408 players of his era and an even
more impressive 1.78 runs per top 6 batsman. A big part of the reason is, well,
he's Bradman. But a part of it is also because he played in 41% of the total
matches played in his time. Contrast that with someone like George Headley who
only played 11% of the matches of his time.
To get some perspective on that, I
compared the Bradman's influence on his era with another batsman from a
different era whose average was in the healthy 50s and who featured in 60% of
the matches of his time: Jack Hobbs. He improved the average of the batsmen of
his era by 0.83 runs for all and by 1.04 for the top 6 of his time.
Modern batsmen play a lot less
proportion of the overall matches in addition to the fact that the number of
matches have shot up by 4 to 5 times from the earlier eras and are at a
disadvantage to make such significant impact individually. Sangakkara, who
averages the most among modern batsmen and has played 20% of the matches in his
time, improves the average of his era by 0.27 for all and by 0.31 for the top 6
of his time.
Getting back to the point made
earlier in computing the alpha average by considering only the top 6 batsmen, there
are two widely floated around theories in modern cricket: Wicketkeepers bat way
better since Gilchrist and tail enders aren't mugs with the bat in modern day
cricket.
Let's consider wicket keepers
first.
This is the total aggregate of
wicket keeper batsmen record in Test cricket:
Wicket keeper batting record decade wise:
Note: The decisive shift in a trend could have happened at any time, but I have just chosen to compare them on the parameters of decades solely on discretion rather than any compelling rationale. Also the comfort that even if something decisive happened midway, it would still show up in these filters.
Players
|
Span
|
Mat
|
Inns
|
NO
|
Runs
|
HS
|
Ave
|
100
|
|
Aggregate
|
258
|
1877-2014
|
2139
|
6706
|
902
|
155553
|
232*
|
26.8
|
191
|
Wicket keeper batting record decade wise:
Players
|
Mat
|
Inns
|
NO
|
Runs
|
HS
|
Ave
|
100
|
|
2000s
|
47
|
464
|
1490
|
179
|
41705
|
232*
|
31.81
|
65
|
2010s
|
62
|
195
|
641
|
71
|
19597
|
224
|
34.38
|
35
|
1970s
|
24
|
198
|
624
|
83
|
14764
|
152
|
27.29
|
11
|
1990s
|
37
|
347
|
1086
|
135
|
25950
|
173
|
27.28
|
30
|
1930s
|
26
|
89
|
272
|
45
|
5829
|
149
|
25.67
|
9
|
1940s
|
15
|
45
|
130
|
18
|
2648
|
152
|
23.64
|
3
|
1980s
|
39
|
266
|
773
|
109
|
15696
|
210*
|
23.63
|
14
|
1960s
|
35
|
186
|
588
|
73
|
12150
|
192
|
23.59
|
12
|
1950s
|
38
|
164
|
505
|
68
|
9005
|
209
|
20.6
|
10
|
1890s
|
13
|
32
|
106
|
23
|
1637
|
134*
|
19.72
|
1
|
1920s
|
16
|
51
|
157
|
36
|
2373
|
84
|
19.61
|
0
|
1900s
|
9
|
41
|
133
|
26
|
1825
|
115
|
17.05
|
1
|
1880s
|
11
|
29
|
97
|
16
|
1293
|
82
|
15.96
|
0
|
1910s
|
9
|
29
|
93
|
20
|
954
|
72
|
13.06
|
0
|
1870s
|
3
|
3
|
11
|
0
|
127
|
38
|
11.54
|
0
|
Note: The decisive shift in a trend could have happened at any time, but I have just chosen to compare them on the parameters of decades solely on discretion rather than any compelling rationale. Also the comfort that even if something decisive happened midway, it would still show up in these filters.
Prima facie, the idea of wicket keeper batsmen seems to have been a serious thing since the 1930s. And from there till almost 1990s, there has been spikes and troughs in different time periods. The average jumped up by 3.70 runs from the 1960s to the 1970s. But somehow the significance was lesser because of the lack of follow up in the next decade. That is where the jump of 4.53 runs from the 1990s to the 2000s achieves greater significance. More than the normal volatility, this seemed like a big leap for the discipline.
That Gilchrist made his debut
towards the end of 1999 makes it appealing to think of him as the single
biggest factor but it's a bit too
simplistic. Even excluding him from the records, the average in 2000s is a very
impressive 30.26.
List of wicket keepers with at
least 1000 runs and average above 30 in the 2000s:
20
|
34
|
1972
|
232*
|
73.03
|
6
|
|
91
|
129
|
5130
|
204*
|
46.63
|
16
|
|
25
|
40
|
1390
|
131*
|
42.12
|
2
|
|
23
|
38
|
1404
|
169
|
41.29
|
2
|
|
48
|
81
|
3117
|
230
|
40.48
|
7
|
|
40
|
62
|
2176
|
148
|
40.29
|
3
|
|
40
|
66
|
2056
|
124*
|
36.07
|
3
|
|
47
|
80
|
2525
|
158*
|
34.12
|
6
|
|
48
|
79
|
2394
|
143
|
31.92
|
3
|
|
30
|
40
|
1044
|
154*
|
30.7
|
2
|
|
104
|
152
|
4024
|
122*
|
30.02
|
2
|
Somewhere between the end of 1990s and into the 2000s cricket either seems to have moved towards placing greater emphasis on batting credentials of keepers or just fortunate to be flooded with a rich vein of talent clustered around the same time. That is the key difference in the 2000s. Gilchrist is no doubt a phenomenon, but so was Les Ames in his time. That Gilchrist played in an era of great keeper batsmen is what made his era so special.
List of keeper batsmen with more
than 1000 runs in 2010s
Runs
|
||||||
19
|
31
|
1726
|
169
|
59.51
|
6
|
|
17
|
27
|
1041
|
124
|
45.26
|
3
|
|
24
|
44
|
1673
|
200
|
40.8
|
3
|
|
54
|
83
|
2709
|
126
|
39.26
|
5
|
|
48
|
78
|
2632
|
224
|
37.07
|
3
|
|
34
|
58
|
1629
|
136
|
31.32
|
2
|
|
26
|
39
|
1031
|
120
|
30.32
|
2
|
All of them average more than 30 with De Villiers setting a
whole new benchmark for wicket keeper batsmen.
Stats or anecdotes, there is no disputing the notion that
wicket keeper batsmen have had a huge leap in terms of ability and achievement with
the bat since the 2000s.
On to the lower order:
This is the record of batsmen from no.8 to no.11 in the
history of cricket:
Players
|
Mat
|
Inns
|
Runs
|
HS
|
Ave
|
100
|
|
Aggregate
|
1928
|
2136
|
24067
|
277051
|
257*
|
15.25
|
96
|
Quite obviously, there'll be exceptions here of top order
batsmen batting lower down the order for various reasons. But spread over such
a large population, it's insignificant.
Decade
|
Matches
|
Average of Nos. 8 to 11
|
1920s
|
51
|
17.72
|
2010s
|
195
|
16.54
|
1980s
|
266
|
16.05
|
1960s
|
186
|
15.78
|
1890s
|
32
|
15.75
|
1940s
|
45
|
15.57
|
2000s
|
464
|
15.51
|
1870s
|
3
|
15.3
|
1900s
|
41
|
15.12
|
1970s
|
198
|
14.79
|
1990s
|
347
|
14.34
|
1930s
|
89
|
14.22
|
1950s
|
164
|
14.05
|
1910s
|
29
|
14.01
|
1880s
|
29
|
12.57
|
The total range of averages across all decades is 5.15 runs
between 1880s and 1920s. The best decade for run making, 2000s, has a tail
ender average of 15.51 which puts it in the 7th place, way behind the 1980s -
the glory era of fast bowling.
There is no real improving or worsening pattern over time
here.
List of batsmen (8 to 11) who have scored at least 1000 runs
and average >= 20:
Span
|
Mat
|
Runs
|
HS
|
Ave
|
100
|
|
1997-2012
|
53
|
1577
|
122*
|
35.04
|
2
|
|
1995-2008
|
75
|
2330
|
111
|
32.81
|
2
|
|
1978-1993
|
61
|
1967
|
116
|
32.78
|
2
|
|
1997-2012
|
100
|
3502
|
140
|
30.71
|
5
|
|
1981-1992
|
55
|
1667
|
173
|
27.78
|
2
|
|
1976-1986
|
63
|
1598
|
102
|
27.55
|
1
|
|
1986-1993
|
47
|
1180
|
73
|
26.81
|
0
|
|
2000-2006
|
40
|
1125
|
82
|
26.78
|
0
|
|
1994-2009
|
105
|
2785
|
100*
|
25.55
|
1
|
|
1920-1937
|
40
|
1003
|
65*
|
25.07
|
0
|
|
1973-1990
|
56
|
1641
|
103
|
24.49
|
1
|
|
2007-2014
|
73
|
2120
|
169
|
24.09
|
1
|
|
2007-2014
|
57
|
1559
|
123*
|
23.26
|
1
|
|
2007-2013
|
33
|
1185
|
106
|
22.78
|
1
|
|
1946-1959
|
41
|
1062
|
104
|
22.59
|
1
|
|
1985-2002
|
87
|
2160
|
257*
|
22.26
|
2
|
|
2008-2013
|
60
|
1370
|
85
|
22.09
|
0
|
|
1993-2005
|
48
|
1187
|
127*
|
21.98
|
1
|
|
1978-1995
|
53
|
1212
|
75
|
21.26
|
0
|
|
1998-2006
|
54
|
1421
|
59
|
20.89
|
0
|
|
1999-2008
|
75
|
1415
|
64
|
20.8
|
0
|
|
1946-1960
|
51
|
1103
|
118
|
20.42
|
2
|
Most of the solid record belongs
to all rounders who were batting out of position and wicket keepers. Even here,
the numbers are heavily skewed in favour of 1980s and beyond. But that hardly
seems to impact the aggregate numbers of the recent decades.
Anecdotally, the theory that tail
enders have become better batsmen in recent times is so sound. Cricket fans can
recollect a sizeable number of matches where tail enders have played out spells
and spells of incisive bowling to bat out for a draw. The ugly blindfold like
slog is history. Cricket is a lot more professional with an ever expanding
support staff assisting cricketers to hone their secondary skill. Bats are
better and so are protection equipments. It all adds up to make perfect sense.
But at a macro level, stats just
don't add up to make a convincing case.