Trivia - bowling March 27, 2008

Bowlers with the most high-quality wickets - a follow-up

Many good suggestions were received to my previous post on quality of wickets taken by bowlers

I was in for a surprise with my previous post. I never expected it to receive so many comments (nearly 200) many of which were quite complimentary. My favourite post so far has been the one on the Revised Batting Average. Possibly the reason for the mixed reactions on that post might have been the fact that the traditional definition of batting average exists in the mind of many people who are not going to accept a change quickly. On the other hand this idea of "Batsman wicket quality" is totally new and many people have appreciated the originality of the theme.

Many good suggestions were received. It was difficult to decide what to take up and what to discard. However I have taken up three tweaks for implementation, in increasing order of difficulty.

Since I do not want to post a follow-up to a follow-up, I will respond individually to comments which I feel deserve a further response.

Quite a few complex computational alternatives have been suggested. I have gone through all these, and most have some merit. However, I have decided to retain the easy-to-understand methodology adopted by me since it would be possible for everyone to follow the computations easily - that axiom has always been the cornerstone of my analysis. I must acknowledge the originality of some of the suggestions, though.

1. Raising the bar to 200 wickets (now only 54 qualifying bowlers in lists)

Quite a few readers have suggested raising the qualifying bar to 200 wickets. This request is like a half-volley outside the off stump, bowled to a set batsman, which would be instantly driven for four. Only a few minutes work was needed here. The revised table is presented below. It should be noted that only the qualifying bar is raised and no other change has been done. Of course, this is only a temporary exercise for this blog and my database table cut-off stays at 100 wickets.

Table 1: Ordered by BQI

SNo Bowler            Bow Cty Mat Wkt  Sum of   BQI

1.Caddick A.R RFM Eng 62 234 7706.0 32.93 2.Hoggard M.J RFM Eng 67 248 8157.0 32.89 3.McKenzie G.D RF Aus 60 246 8018.0 32.59 4.Gough D RF Eng 58 229 7238.0 31.61 5.Bedser A.V RFM Eng 51 236 7456.0 31.59 6.Thomson J.R RF Aus 51 200 6291.0 31.45 7.Snow J.A RFM Eng 49 202 6313.0 31.25 8.Underwood D.L LSP Eng 86 297 9212.0 31.02 9.McDermott C.J RF Aus 71 291 8988.0 30.89 10.Lillee D.K RF Aus 70 355 10919.0 30.76 ... ... 50.Abdul Qadir RLB Pak 67 236 6516.0 27.61 51.Waqar Younis RFM Pak 87 373 10156.0 27.23 52.Garner J RF Win 58 259 6903.0 26.65 53.Wasim Akram LFM Pak 104 414 10754.0 25.98 54.MacGill S.C.G RLB Aus 42 203 5231.0 25.77

One reason for the low placement of Muttiah Muralitharan, Wasim Akram and Waqar Younis in this table might be their skill in taking lower-order wickets quickly and effectively. This is indeed a great attribute of these bowlers, and not to be scoffed at. It is true these great bowlers would have taken many top-order wickets and quite a few lower-order wickets also.

Table 2: Ordered by Difference between BQI and Bowling Average

SNo Bowler            Bow Cty BowAvge  BQI    Diff

1.Marshall M.D RF Win 20.95 30.06 9.11 2.Ambrose C.E.L RF Win 20.99 29.85 8.86 3.McGrath G.D RFM Aus 21.64 30.43 8.79 4.Donald A.A RF Saf 22.25 29.27 7.01 5.Trueman F.S RF Eng 21.58 28.44 6.86 6.Lillee D.K RF Aus 23.92 30.76 6.83 7.Hadlee R.J RFM Nzl 22.30 29.09 6.79 8.Bedser A.V RFM Eng 24.90 31.59 6.69 9.Imran Khan RF Pak 22.81 29.44 6.63 10.Pollock S.M RFM Saf 23.12 29.62 6.50 ... ... 50.Harbhajan Singh ROB Ind 31.40 28.71 -2.69 51.Sobers G.St.A LM Win 34.04 30.47 -3.57 52.Danish Kaneria RLB Pak 33.90 29.84 -4.06 53.Abdul Qadir RLB Pak 32.81 27.61 -5.19 54.Vettori D.L LSP Nzl 34.23 28.64 -5.59

A few suggested that instead of determining the measure of difference between BQI and Bowling Average, a measure of quotient, say BQI/Bowling Average can be determined. This has its own merits. However the differences are likely to be minimal: 40 minus 25 and 35 minus 20 both will work out to 15 while 40/25 will work out to 1.6 and 35/20 will work out to 1.75. It is difficult to select one method over the other. What I have done, however is to provide this information also in the Table. It can be seen that there is virtually no difference between Tables 2 and 2A.

Table 2A: Ordered by Quotient between BQI and Bowling Average

SNo Bowler            Bow Cty  BowAvge   BQI     Quot

1.Marshall M.D RF Win 20.95 30.06 1.43 2.Ambrose C.E.L RF Win 20.99 29.85 1.42 3.McGrath G.D RFM Aus 21.64 30.43 1.41 4.Trueman F.S RF Eng 21.58 28.44 1.32 5.Donald A.A RF Saf 22.25 29.27 1.32 6.Hadlee R.J RFM Nzl 22.30 29.09 1.30 7.Lillee D.K RF Aus 23.92 30.76 1.29 8.Imran Khan RF Pak 22.81 29.44 1.29 9.Muralitharan M ROB Slk 21.77 27.78 1.28 10.Pollock S.M RFM Saf 23.12 29.62 1.28

2. Taking into account the batsman score at the time of dismissal

Quite a few readers have also suggested that the batsman's score, at the time of dismissal, should be considered. This is an excellent idea and strengthens the concept of quality of wickets taken by bringing in a "when" factor in addition to the "who" factor. This suggestion falls smack in between the previous and the next suggestions in terms of implementation difficulties. I have gone over my notes and come out with the following methodology.

Assign a weightage of 50% to the dismissed batsman's average [current or career, whatever it might be]. Assign the other 50% weightage to the batsman score at the time of dismissal, ranging from 100% credit for dismissal at 0 to 0% credit for any dismissal at or above the batsman average. A few examples are given below.

Batsman   Avge    Score  BQI-Fixed  BQI-Variable  BQI-Total

Bradman 99.94 0 49.97 49.97 99.94 Bradman 99.94 67 49.97 16.47 66.44 Bradman 99.94 304 49.97 0 49.97 (any score above 99)

Tendulkar 55.58 0 27.79 27.79 55.58 Tendulkar 55.58 25 27.79 15.29 43.08 Tendulkar 55.58 75 27.79 0 27.79 (any score above 55)

Vettori 27.12 0 13.56 13.56 27.12 Vettori 27.12 11 13.56 8.08 21.64 Vettori 27.12 28 13.56 0 13.56 (any score above 27)

Based on the modified calculation methodology, the revised tables are given below. This modification now reflects a significant improvement. It must, however, be noted the revised report is not comparable with the earlier reports since the basis has changed significantly. Previously the bowler got 100% of the Batting Average as credit. Now he gets 50% + x% as credit. As such the average BQI values have dropped and this report should be seen on its own.

The only comparison possible will be between this option and the next option, to be done in future.

Table 4: Ordered by BQI (Revised)

SNo Bowler            Bow Cty Mat Wkt  SumAvge BQI

1.Hoggard M.J RFM Eng 67 248 6412.0 25.85 2.Caddick A.R RFM Eng 62 234 6045.2 25.83 3.McKenzie G.D RF Aus 60 246 6146.3 24.98 4.Gough D RF Eng 58 229 5618.7 24.54 5.McGrath G.D RFM Aus 124 563 13766.6 24.45 6.Snow J.A RFM Eng 49 202 4910.8 24.31 7.Marshall M.D RF Win 81 376 8973.4 23.87 8.Ambrose C.E.L RF Win 98 405 9650.2 23.83 9.Bedser A.V RFM Eng 51 236 5581.4 23.65 10.Lillee D.K RF Aus 70 355 8314.5 23.42 ... ... 50.Muralitharan M ROB Slk 118 723 14511.2 20.07 51.Danish Kaneria RLB Pak 51 220 4410.2 20.05 52.Vettori D.L LSP Nzl 78 241 4810.6 19.96 53.Benaud R RLB Aus 63 248 4925.8 19.86 54.MacGill S.C.G RLB Aus 42 203 3807.4 18.76

For a full list, please click here.

No one can have complaints on the top ten bowlers. The only surprise is the presence of Matthew Hoggard, Andy Caddick and Darren Gough in the top four. The only reason, as already surmised, could be their playing against Australia and India quite frequently recently. Another reason could be the generally high current batting averages.

Table 5: Ordered by Quotient of BQI and Bowling Average (Revised)

SNo Bowler            Bow Cty BowAvge BQI     Diff  Quot

1.Ambrose C.E.L RF Win 20.99 23.83 2.84 1.14 2.Marshall M.D RF Win 20.95 23.87 2.92 1.14 3.McGrath G.D RFM Aus 21.64 24.45 2.81 1.13 4.Trueman F.S RF Eng 21.58 22.99 1.41 1.07 5.Donald A.A RF Saf 22.25 22.41 0.16 1.01 6.Hadlee R.J RFM Nzl 22.30 22.49 0.19 1.01 7.Pollock S.M RFM Saf 23.12 23.06 -0.06 1.00 8.Garner J RF Win 20.98 20.86 -0.12 0.99 9.Holding M.A RF Win 23.69 23.37 -0.31 0.99 10.Lillee D.K RF Aus 23.92 23.42 -0.50 0.98 ... ... 50.MacGill S.C.G RLB Aus 28.15 18.76 -9.39 0.67 51.Abdul Qadir RLB Pak 32.81 20.64 -12.17 0.63 52.Sobers G.St.A LM Win 34.04 21.11 -12.92 0.62 53.Danish Kaneria RLB Pak 33.90 20.05 -13.86 0.59 54.Vettori D.L LSP Nzl 34.23 19.96 -14.27 0.58

For a full list, please click here.

If one adds Wasim and Waqar to the top ten, this is almost a list of the top dozen pace bowlers of all time.

3. Applying the cumulative batsman average at the beginning of the Test (as against the career average)

Many people suggested applying "upto-current Test" batting average rather than the "career" batting average. This was the most voiced comment and deserves to be considered seriously. This has an impact at the early stages of a batsman's career. I had considered doing this earlier itself but ruled against it because of the complexity involved. Dynamic determination of the "upto-current Test" averages is very cumbersome. This method will slow down any analysis, even considering the high pentium speeds. The only alternative is to determine the "upto-current Test" averages as a one-off exercise for all 1866 Tests, store these static data within the match data for each player and use these any time required. Of course, the current averages will have to be created for each new Test as the data is appended. This exercise requires a redefinition of the database layout and considerable amount of programming since it is a systemic change. I will do this in the near future and make the results available to all the interested readers, even if not through a post in this blog.


It is amusing to see people complaining, even abusing the "Indian ***********" about the absence of their favourite bowlers from the list, most prominently Wasim Akram. Not having understood the analysis is a possible reason. The other reason is the difficulty in accepting any list which does not meet their perceived conclusions.

If I make a list of bowlers who have taken a hat-trick in Tests, Wasim Akram will appear twice. Dennis Lillee, Murali, Anil Kumble, Waqar and Richard Hadlee etc would not be on the list while Peter Petherick, Alok Kapali, Andy Blignaut, James Franklin and Irfan Pathan will appear in that list. Should one disown such a list because of the absence of the marquee names?

Just for the record, here is my own list, in alphabetical order, of the all-time great bowlers, taking all factors into consideration. This should satisfy the readers who should know that there is no narrow-minded chauvinism at work here.

Sydney Barnes, Bishan Bedi, Richard Hadlee, Michael Holding, Lillee, Malcolm Marshall, Glenn McGrath, Muttiah Muralitharan, Waqar Younis, Shane Warne, Wasim Akram.

A few have rightly commented on the dilution of the average because great bowlers tend to take lower-order wickets. Michael Clark and Onkar Walavalkar, among others, have given the example of someone taking all ten wickets would have the average batting average lowered significantly. My submission is that this list does not rate the bowlers at all. It is an alternative measure, hitherto untapped. The same Kumble whose ten-wicket haul in Delhi had an average batting average of 31 would have a higher average of batting average in the West Indies match in St Lucia - in which he took three wickets - of 41. It works both ways and over a long career, these variations even out. The points are well made, I concede.

Other interesting comments are by people complaining that the need is to enjoy the game and not reduce it to numbers or terming such analysis as useless or me as jobless (possibly I am !!!). Let me reply by saying that there are different types of cricket followers. There are those who only like to watch the game, they would not even bother about the batsman's strike-rate or some such simple measure. There are a few who are only number nerds. There are millions in between, the author included, who enjoy both watching the game and analysing it. If one does not want to see such analysis why get into this blog, which is purely an analyst's corner, at all? Entry to this blog is voluntary.

The comments for this post have been the most received so far for any post and have been very enjoyable, whether bouquets or brickbats. I have been made to think in a lateral manner and I thank all those who took the time to comment. It has been a great experience.

Anantha Narayanan has written for ESPNcricinfo and CastrolCricket and worked with a number of companies on their cricket performance ratings-related systems

Comments have now been closed for this article

  • testli5504537 on July 9, 2009, 23:10 GMT

    There are tons of information to be known about this. You made some great points that answered my questions.

  • testli5504537 on April 20, 2008, 19:35 GMT

    Regarding Wasim Akram, what you are ignoring is the fact that he hd to bowl a lot in the subcontinent. Even, say, if the average per wicket in the subcontinent is lesser than in Aus, it is still much, much easier for spinners to take wickets. Compare India's trio of Sree Shanth's, RP Singh's, and Pathan's bowling when they went to Aus and there form now at home. I think you'd agree it has substantially deteriorated. Pak's pitches like Multan where Sehwag got 300 are not the most refreshig site for bowlers. Whereas in India, most wickets are taken by spin bowlers. At least in the long-term, bowlers like Mcgrath and Ambrose-- very good bowlers in their right-- would find difficult to bowl out batsman in pitches like Multan with such Monotony. Of course, when Pak visisted India recently, again, spin took most the wickets. Conversely, the reason why Warne's average is quite high (compared to other greats) is again that Aus pitches are more conducive to pace bowling.

  • testli5504537 on April 14, 2008, 13:54 GMT

    Have you done any similar analysis on batting? Perhaps I missed it. I have always held that the "Not Out" factor must be eliminated in order to arrive at the "Real" average. Otherwise, people like Hussey (or Bevan in ODIs) have overstated averages.

  • testli5504537 on April 14, 2008, 13:51 GMT

    Terrific analysis. Just that, because of "rounding", the data in Table 5 is incorrectly ordered. For example, Marshall should head up the table and not Ambrose. And Lance Gibbs should follow Kumble

  • testli5504537 on April 14, 2008, 10:00 GMT

    Excellent analysis and some very interesting comments.

    There are a number of anomalies that come to light. For instance, the difference between top order and lower order batsman, playing top ranked teams and lesser teams and home and away performance. I think one of the most interesting careers to look at is Murali's and the comparison with Warne's. Murali's figures fluctuate dramatically between home and away and also top and lower ranked teams. I am not usre how you factor this into your table but no doubt others might add further comments.

    You comment on bowling partnerships but what difference do you think the strength of the whole bowling line up makes. Again, I look at Murali and Warne. Effectively Murali only had Vaas but Warne was part of a very strong bowling attack. The same could be said of the WI attack in the 1970's and 1980's and arguably the likes of Roberts, Garner and Croft suffer.

    Overall great work and a very interesting read.

    Thank you.

  • testli5504537 on March 31, 2008, 13:31 GMT

    Even though all of these comments and your post, Ananth, are very interesting, I cant but feel that if a person have to look at every aspect of a bowler's career, including conditions he bowled in, the amount of overs bowled prior to dismissing a batsmen, the quantity of Cola he had with dinner the previous night, the temperature they were playing in (dehydration)...etc...all useless info.

    The fact remains, as a club cricketer that bowls and bats in the top order, I know there is serious competition between team mates all the time! I dont believe that Nel sits in the dressing room after a match and have a gripe about Steyn's bagful of sticks he pouched. Who cares who bowled at who...the fact remains...:

    Over a period of 5 to ten years all averages flattens out, all bowlers had opportunities to pick up wickets against top, middle and lower order batsmen. If you trail a team mate by 100 wickets you have yourself to blame!

    Nice topic, but irrelevant. Its the roll of the dice!!

  • testli5504537 on March 31, 2008, 13:20 GMT

    Regarding Gough, Caddick and Hoggard all being in the top ten. Much as I like these guys they do seem to be an anomaly. Could it be caused by the fact they played on swinging English wickets more than the others. This would lead to high average sub continent cricketers being turned over more often. How would it distort the figures if you used the batting average figures for the country concerned? Alternatively I have lived through a golden age of English bowling without even realising it.

  • testli5504537 on March 31, 2008, 11:40 GMT

    Factoring in the batsman's score at the point of dismissal seems to me to be the wrong thing to do. One interpretation is that bowling Bradman out for a duck means that he must've been out of form and that bowling him for 300 means it must have been a truly amazing ball to stop the master in flight. The other interpretation says that bowling Bradman for a duck is an incredible feat, while bowling him for 300 indicates that it took an awful long time to get a decent ball in. The truth is, obviously, somewhere in the middle but you can't hope to quantify that just from knowing the batsman's score.

  • testli5504537 on March 31, 2008, 10:37 GMT

    Ignore those philistines who don't appreciate the stats of cricket! Two great articles that I will be mulling over again and again!!!!!!

  • testli5504537 on March 31, 2008, 3:26 GMT

    Have a simple suggestion? Instead of career averages, why don't you use averages against that country? Some averages are inflated by their performances against weak bowling attacks.

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