It Figures

Extrapolating high scores in Tests

2008-07-06T13:29:51Z

Sanath Jayasuriya's 340 was the cornerstone of Sri Lanka's 952 for 6 declared, the highest total in Test cricket © Getty Images

When comparing the biggest team scores in Tests, the results can be a bit messy. This is because cricket often does not allow teams to carry their innings to completion, and big innings are often truncated by declaration or lack of time. We know for sure that the highest innings in a Test match is Sri Lanka’s 952 for 6 in 1997, but an interesting side question would ask if this is also the most ‘extraordinary’ score in Tests. For example, we know that the West Indies once made a score of 790 for 3. Where might such an innings have gone if it had continued? Can we compare it to Sri Lanka’s record? While we can never know for sure, it is possible to make a statistical estimate. The approach is to look at the way that innings naturally progress over a wide range of scores. Of course, there is plenty of variation between innings [part of cricket’s appeal], but there are statistical patterns. A team that is, say, five wickets down, will on average add a certain number of runs if the innings is played to completion.]]> is not very important, with only a limited effect on the future progress of the innings. This is shown in the following table, calculated from the outcomes of all relevant Test innings, which gives the average number of runs added by teams with five wickets down, at different starting points.

Average runs added when five down
Starting score	Runs added (average)	Projected all-out score
50 for 5	85	135
100 for 5	91	191
200 for 5	99	299
300 for 5	114	414
400 for 5	116	516
500 for 5	114	614
600 for 5	110	710

What we see here is that above a certain level, in this case about 300 runs, there is very little change in the potential scoring of a team. This is surprising, but it probably comes down to the fact that a batsman coming in at a score of 600 for 5 is likely to bat in a riskier manner, or with less intensity, than one who comes in at 300 for 5. This would appear to balance out any advantage from tired bowling or benign conditions. This pattern is also seen at 6, 7, 8 or 9 wickets down. It should be stressed that these runs added will often be theoretical in practice. For example, the projected all-out score for teams that reach 600 for 5 is 710, but in practice most such innings will not reach 700, often because of declarations. What the projected all-out score gives us is an estimate of where the innings was headed if the limits of time and tactics had been removed – its trajectory if you will. With modern computer power, the result of this process is an “Innings Projector” that can give a projected estimate for any score. (In practice, it only works for innings with two or more wickets down.) Estimates for extreme innings must remain provisional because of the rarity of the situations, but the fact that trends are so stable, as illustrated by the first table, adds confidence to the results. So what are the most extreme projected scores? Here is a list of the results:

Most extreme projected scores
Team	Opponent	Venue, year	Score	Projected score
Sri Lanka	India	Colombo (RPS) 1997	952-6	1028
West Indies	Pakistan	Kingston, Jamaica 1958	790-3	996
England	Australia	The Oval 1938	903-7	951
Sri Lanka	Zimbabwe	Bulawayo 2004	713-3	919
Sri Lanka	South Africa	Colombo (SSC) 2006	756-5	866
West Indies	England	St John’s, Antigua 2004	751-4	861
England	West Indies	Kingston, Jamaica 1930	849-10	849
New Zealand	Sri Lanka	Wellington 1991	671-4	821
India	Bangladesh	Dhaka (Mirpur) 2007	610-3	816
Australia	Zimbabwe	Perth (WACA) 2003	735-6	810
Pakistan	India	Lahore 1989	699-5	809
South Africa	Zimbabwe	Harare 2001	600-3	806
Australia	England	Lord’s 1930	729-6	804
England	India	Lord’s 1990	653-4	803
Australia	England	Leeds (Headingley) 1993	653-4	803
Australia	England	The Oval 2001	641-4	791
Australia	West Indies	Kingston, Jamaica 1955	758-8	788
Pakistan	India	Hyderabad (Pak) 1983	581-3	787
India	Pakistan	Multan 2004	675-5	785
Australia	England	Lord’s 1993	632-4	782
England	South Africa	Lord’s 1924	531-2	779
West Indies	New Zealand	Wellington 1995	660-5	770
England	South Africa	Durban 1939	654-5	764
Pakistan	Sri Lanka	Faisalabad 1985	555-3	761
South Africa	England	Lord’s 2003	682-6	757
Pakistan	Bangladesh	Multan 2001	546-3	752
India	Australia	Sydney 2004	705-7	752
India	Australia	Sydney 1986	600-4	750

So Sri Lanka retains the No. 1 position under this calculation. However, the West Indies 790 for 3 moves up to second place, while England’s 849 all out in the Timeless Test of 1930 moves down to seventh. Another aspect to these scores is that the distribution of the scores around these projections can be calculated, which means that the probability of a specific score can also be calculated. For example, the probability of a score of 790 for 3 actually exceeding the 1028 assigned to Sri Lanka’s record is about 24%. One other possible calculation here is a re-appraisal of the most one-sided innings victories in Tests. Using the projected score, the margin of victory can be re-calculated and compared more evenly. The most one-sided Tests in this analysis are:

Most one-sided Tests
Venue, year	Team	Opponent	Score	Projected score	Original margin	Projected margin
The Oval 1938	England	Australia	903-7	951	Inng and 579	Inng and 627
Multan 2001	Pakistan	Bangladesh	546-3	752	Inng and 264	Inng and 470
Bulawayo 2004	Sri Lanka	Zimbabwe	713-3	919	Inng and 254	Inng and 460
Kolkata 1958	West Indies	India	614-5	724	Inng and 336	Inng and 446
Dhaka (Mirpur) 2007	India	Bangladesh	610-3	816	Inng and 239	Inng and 445
Wellington 1995	West Indies	New Zealand	660-5	770	Inng and 322	Inng and 432
Johannesburg (New Wanderers) 2002	Australia	South Africa	652-7	699	Inng and 360	Inng and 407

(Please, no comments that the ‘highest’ does not mean the ‘greatest’. No one is claiming that it does. We are just looking at extremes here.) [Technical note: the trajectory at large scores must be calculated with care, because teams that continue with great success from a high starting point rarely complete their innings. This must be allowed for in the calculation. The way to do this is through an iterative process, where big innings that are declared closed are themselves calculated through to completion, firstly for innings that are nine wickets down, then eight, seven, and so forth, and these results are then fed back into the calculation for end points starting from fewer wickets down. For example, take a score of 500 for 3. This has occurred 37 times in Test matches. The projected score in this case is 705 all out. However, only three of the 37 teams have actually reached or exceeded a score of 705, while nine have been bowled out for less than 700. The reason that the projected score is above 700 is that many teams continue to do well but declare before reaching 700. Careful iterative analysis of these declared scores produces the average estimate of 205 runs added, or 705 all out for a projected score.]

The night-watchman story - Part II

2008-06-27T13:13:36Z

Matthew Hoggard has played some vital night-watchman innings © Getty Images

In the first part I looked at a methodology for determining night-watchman situations and looked at individual performances. In this concluding part, I have done a team analysis and come to a conclusion whether the night-watchman experiment is a success or not. I have also looked at readers' comments.

There was a suggestion to use the day-end player data which is available in text scorecards. While accepting that this is available in most scorecards, I have to express the inability to do so at the current stage because I have to download quite a few scorecards, do a text-based data mining to extract this data, do some complex parsing work and link this data to the player and fall-of-wicket data already available. This is certainly possible. However, this will take too much time and resources and it is not possible to do this at this instance. Possibly at a later date.]]> The question of setting up 25.0 as the cut-off batting average has already been raised in two forms. One, questioning the arbitrary nature of this cut-off value, and two, the applicability of lowering this for the pre-WW1 Tests in which the batting averages were consistently lower.

It is impossible for me to work out an algorithm to do a more objective determination of this cut-off value. Whatever I do is likely to be questioned and be subjected to unacceptable variations. I have done this summary of batting averages, over 1879 tests, to substantiate the 25.0 cut-off.

Total Bat Runs: 1719071
Innings:          66117
Not Outs:          8622
Bat Average:      29.90

This is the overall average. This is about 10% below the mid point of the highest average (68.8, excluding Bradman's freakish figure) and lowest average (0.0). As such a figure which is 25% below the mid point figure seems to be the ideal cut-off point for determining night-watchmen. This works out to 25.8, which is just above the current cut-off. Hence the cut-off of 25.0 is retained.

However there is a justification to have this cut-off at a lower figure of 20.0 for all Tests played before 1914. This has excluded some night-watchman instances. The number has now decreased from 563 to 552 since 11 instances which were earlier determined to be night-watchman instances are now outside the scope.

There was a suggestion that a situation where a No.7 batsman such as Vettori is substituted by a no.11 batsman such as Martin should be considered as a night-watchman instance. In this particular case, the average differential, 26+ against 2+, makes it a correct and valid suggestion. However, this cannot be generalised. If Kumble's place is taken by Sreesanth, the situation is murky. Kumble has an average of 18.25 and Sreesanth has an average of 15.50. By no stretch of imagination can we deem this to be a night-watchman situation. For that matter these numbers could even be reversed. Hence, while readily acknowledging the validity of the readers' suggestion, I have to, with reluctance, stick to my decision that only nos. 3-6 will be considered as night-watchman positions.

Then we come to the requirement that we have to consider the batting average of the batsman being replaced. This is something I am very loath to do because of the many inherent weaknesses. Until now I have determined a night-watchman situation solely by the measures of the specific batsman, what was his career-to-date batting average, what was his BPA and which position did he bat in. When I am not even sure who would have been the next batsman, such a move is fraught with problems.

Country summary (1879 tests)

Cty   NWI  Tests  Tests/NWI    # 3-6 inns  Inns/NWI

Aus:   96    696     7.25         4688       48.8
Bng:    5     53    10.60          417       83.4
Eng:  124    873     7.04         5880       47.4
Ind:   56    418     7.46         2797       49.9
Nzl:   50    342     6.84         2403       48.0
Pak:   62    335     5.40         2220       35.8
Saf:   55    332     6.03         2318       42.1
Slk:   22    177     8.04         1181       53.7
Win:   69    448     6.49         3023       43.8
Zim:   13     83     6.49          607       46.7
Icc:    0      1     0.00            8        0
      552   3758     6.80 (3.40)

Pakistan has used night-watchmen most often and Bangladesh the least. Sri Lanka have been quite reluctant to use the night-watchman option but South Africa haven't been averse to doing so. However, Bangladesh figures may not be accurate since only three of their batsmen have averages higher than 25.0 and a few night-watchman innings would have been lost. I did not want to lower the cut-off for them only to 20.0, which might have been the correct thing to do. It wasn't worth the effort since it might only add couple more instances.

The last column is a measure of night-watchman occurence based on the number of qualifying innings (nos. 3-6) for the concerned country. Here again Pakistan leads with one instance every 36 innings, followed by South Africa, once every 44 innings. Bangladesh, possibly for reasons already discussed, emplys this once every 83 innings. Just for information, Bangladesh have played 106 Test innings. Out of these, they have lost fewer than four wickets only three times - once the innings didn't start, once they lost three wickets and once they lost just two.

Overall the night-watchman instance occurs once in about three-and-a-half Tests.

Conclusion

Now for the difficlut task of determining whether the night-watchman experiment has been a success or not.

There was a very good suggestion to consider factors other than the night-watchman innings itself, such as how the innings progressed, how much the next batsman scored et al to determine whether a night-watchman stint was a success. I am not very comfortable with the idea of linking the actual performance of the night-watchman to what happened in the game itself. If Gillespie came in as night-watchman and lasted 100 balls, it was an uqualified success. Whether Michael Clarke, who Gillespie replaced, scored 0 or 100 the next day doesn't really matter. Whether Australia won or lost beacuse of this decision again does not matter. We are only looking at whether the night-watchman did his job or not. If he scored 1 in 50 balls he had succeeded. If he scored 9 in 15 balls, got out and the next batsman had to bat the same day, his stint was a failure.

Assuming that no captain would be dumb enough to send a night-watchman an hour before close of play, we are looking at a possible maximum of around 8-10 overs to be played during the evening. We must also assume that the night-watchman should last for some time the next day. A valid conclusion is that if a night-watchman bats for 30 balls, he has more than done his job, since he has probably been in the middle for around 45 minutes.

The balls faced will either be the actual number (available in most of the matches) or the one derived from the team scoring rate, as explained in Part 1. While accepting that there could be very good scores by night-watchman of 0s, 1s, 2s ..., there is no way to actually cull out this data. The only concession I will make is that any night-watchman who scores 15 or more has done his job. Outside edges and wild swings (unlikely) could get him around 10 runs but not 15. It is very likely that he has faced a fair number of deliveries, possibly 30+, to score 15 or more. This criteria can now be applied irrespective of the method of arriving at the "balls played" information. 221 out of the 552 night-watchmen innings fall under this either-or criteria (at least 30 balls faced or 15 runs scored).

Out of the total population of 552, it can be deduced that 221 have succeeded in their task, making the success rate of the night-watchmen exercise around 40%. This figure is certainly much more than what I expected. The success stories are very significant, as were the cases with Gillespie, Hoggard, Tudor and Larwood. One great factor in these night-watchmen decisions is that they are sent in with the expectation that he might fail more often than not, especially if his name does not start with 'G'. If they succeed, that is a bonus, and if not, other than the loss of one late-order wicket, no serious damage has occurred. Hence a success rate of 40% seems beyond all expectation.

We have to conclude that, over time, the night-watchman experiment has been a great success. Having said that, there is a lot to be said for top-order batsmen taking up the responsibility of batting in difficult conditions, a task for which they are eminently trained, both in skill and temparament.

I must acknowledge the contributions of Dr.Ashwin Mahesh, my co-founder at Thirdslip.Com who, long time back, mooted the idea of using the difference between the BPA and actual batting position to identify a night-watchman situation. Click here to see the complete list of night-watchman instances Click here to see the list of successful night-watchman instances Click here to see the list of unsuccessful night-watchman instances

The best night-watchman in Tests - Part I

2008-06-20T10:10:00Z

Jason Gillespie averages 116 balls per stint as night-watchman © AFP

After a light-weight ODI related post last time around (The "Unfulfilled team innings in ODIs"), I am now reverting to Test matches and a considerably more complex analysis.

The night-watchman concept in Test cricket is a paradox. A batsman of far lesser ability is sent to bat in place of a far more accomplished batsman, in possibly inferior batting conditions. The better batsman is preserved to bat when conditions are better. But this is as much part of Test cricket as white clothing, follow-on, new ball after 80 overs et al and deserves an in-depth look.

This time I have taken a conscious decision to do this post in two parts. The first part will deal with the individual batsmen performances while the second one will analyse the whole night-watchman canvas by team and by period. In addition, I will take a view on whether the night-watchman concept has been successful. I will also incorporate relevant readers' suggestions.]]> earlier study I have made on the Test batting positions. In that analysis, we looked at batting positions as a measure. To summarize that analysis, I had looked at the career Batting Position Average (BPA) of Test batsmen, keeping the two opening positions as 1. That index is used to have an analytical look at the night-watchmen.

Using night-watchmen as a tactic has existed down the ages. The night-watchmen regularly padded up an hour before close, and would walk in at the fall of a wicket. If he survived, great. Else, send another one hoping that at least he would survive. I have seen matches in which two such night-watchmen had failed and the regularly scheduled player was forced to bat, this time with his team having lost two more wickets. However, there have been many cases where the night-watchman survived that day and for quite some time the next day.

The Australians, led by Steve Waugh, changed things. A top-order batsman was expected to bat whatever be the time of the day, be it 10.47am or 16.53pm. There is no denying that this worked. Overall this seems to me to be the correct approach. Most other teams, for that matter even the Australians now, take the nigt-watchmen approach.

Our interest here is analytical. Let us first define a night-watchman. This is very difficult especially as there is very little data available on things like the time of the day when a batsman came to the wicket. So we can only take an algorithmic approach using the BPA and the batting position the batsman batted in. We may get it right 95% of the time, but that is enough.

A simple starting definition may be that a night-watchman is one who bats (somewhat) higher than his intended position. But we have to take care of situations such as an accomplished batsman like Gilchrist opening for Australia or Wasim Akram/Dhoni coming in earlier to speed up the scoring. Gilchrist's Batting Position Index in Tests is 6.68, indicating that he is a batsman who has batted at No.7 most of his career. Wasim Akram, scorer of three Test centuries and a BPA of 8.1, batting at number 3 or 4, would have to be taken care of. In order to do a correct job of selecting true night-watchmen for our analysis, it is necessary to define a number of related parameters other than batting position alone.

1. First our knowledge, research and intuition lets us decide who is not a night-watchman. Any batsman whose career-to-date batting average is higher than 25.00 cannot be classified as a night-watchman. No captain is going to risk a batsman of the calibre of Vettori (ave 26.65) to protect Styris (36.05). His wicket is too valuable to risk losing. In this regard, we also have to take care of genuine batsmen like Wasim Akram (22.64), Benaud (24.46) etc who have batting averages between 20 and 25. A slight tweak takes care of such batsmen.

Career-to-date average rather than career average is taken since by now I have realised the importance of taking this value as against career figure in certain situations. I have also realised the readers' preferences and have anticipated their inputs. It is also true that I have developed the Career-to-date figures and incorporated in my data base because of suggestions relating to earier postings making my task that much easier.
In this case there is perfect justification. A player's cumulative measures keep on changing. A captain who decides to use a player as a night-watchman at a certain point in his career may not do so at another point depending on changes. For instance, in match 1486 against India, Nicky Boje was used as a night-watchman when the first wicket fell late in the day. His career-to-date batting average at that time was only 14.00. Hence we have treated this correctly as a night-watchman innings even though his end-career average was 25.23. If the career figure was used, this match-winning innings of 85 would have been missed out. This is just an example.

2. We should also ignore players whose BPA is less than 7.00. If a player normally bats in positions 1-6, and he moves up, he cannot be treated as a night-watchman. For instance a batsman with a batting average of 24 and BPA of 5.2 opens the batting, this is not an example of a night-watchman.

3. We have to look at it the other way as well: only innings in which tailenders have batted at positions 1-6 will qualify as night-watchmen innings. A no.10 batsman batting at no.8 is certainly not a night-watchman instance.

4. Finally, the key criterion. An innings will be considered as a night-watchmen innings if the difference between the batsman's BPA (rounded to nearest integer) and the one he actually bats in is greater than or equal to 3. Examples, a no.8 batsman batting at 5 or above, a no.10 batsman opening, a no.9 batsman sent at the fall of first wicket and so on.

A note on the need to round off BPA. A BPA value of 7.86 indicates a batsman who has batted at no.8 or below more often than at no.7 or above. Similarly a BPA value of 5.18 indicates a batsman who has batted at no.5 or above more often than at no.6 or below. It is necessary to round up 7.86 to 8.00 and round down 5.18 to 5.00. This is how the rounding off is effected.
The difference criteria of 3 was arrived at after many trials. If the difference was set up at 4, many a true night-watchman innings, such as a batsman with BPA of 9 batting at no.6, would be lost. A change to 2 would mean inclusion of many normal innings, such as a batsman with BPA of 7 batting at no.5.

5. There are situations when a batsmen such as Irfan Pathan or Derek Murray might genuinely have been asked to open a few times for strategic purposes. These are clearly non-night-watchman situations. However there is no way I can separate out these since their rounded BPA might be 7.0 and they have batted at no.1. The only way out seems to take a courageous decision that if a lower level batsman bats at the opening position, it is not a night-watchman situation. It is reasonable to expect that no captain would send his no.9 batsman to open, solely to protect his opening batsman, however late in the day the innings starts. This will also take out quite a few pre-WW1 batsmen such as Blackham who have opened at will. A total of 127 opening batsman innings have been handled by low order batsmen with BPA greater than or equal to 7.

It is true that many of the above criteria may seem arbitrary. However, before readers rush to comment after a 10-minute perusal of the article, I would like to remind them that I have been studying this fascinating aspect for over 2 years and have run programs with varying parameters many times before settling on the methodology. However, I am certain that by the time all readers' comments are received, the analysis would be improved considerably based on their feedback.

A. Analysis results

A total of 563 innings qualify under these criteria. It is possible that we might have missed a few genuine night-watchman innings and included a few non-night-watchman innings. I have aimed for 95% accuracy and am confident that I have achieved that. This works to slightly less than one in three tests. A perusal of the recent Test scorecards will indicate that this is a fairly accurate proportion.

These 563 innings are analysed in different ways below.

B. Runs scored

The top 10 individual scores are listed below.

Year MtNo Batsman            For Vs  Bat BPA Runs(BallsFaced) Batting Avge
                                                  Act  Calc   CTD*   Career
2006 1799 Gillespie J.N      Aus Bng  3  9.0 201*(425) (425) 15.69 [18.78]
1977 0811 Mann A.L           Aus Ind  3  7.0 105 (n/a) (214) 18.33 [23.62]
1999 1455 Tudor A.J          Eng Nzl  3  8.0  99*(119) (119) 22.33 [19.08]
1933 0224 Larwood H          Eng Aus  4  9.0  98 (n/a) (221) 16.12 [19.40]
1983 0944 Hemmings E.E       Eng Aus  3  9.0  95 (n/a) (174) 12.88 [22.53]
1978 0832 Wasim Bari         Pak Ind  3  9.0  85 (n/a) (125) 15.33 [15.88]
2000 1486 Boje N             Saf Ind  3  8.0  85 (198) (198) 14.00 [25.23]
1885 0018 Jarvis A.H         Aus Eng  5  8.0  82 (n/a) (322) 16.83 [16.83]
1948 0302 Bedser A.V         Eng Aus  4  9.0  79 (n/a) (183) 15.06 [12.75]
1959 0478 Nadkarni R.G       Ind Eng  4  7.0  76 (n/a) (223) 21.78 [25.71]

* Career-to-date average

The top innings has been the double-century scored by Gillespie. Coming in at 67 for 1, he lasted nearly 10 hours and remained unbeaten on 201 while 514 runs were scored, including a stand of 320 with Michael Clarke. This must be the leading contender for the most amazing innings in Test cricket history. But what about a few centuries which are being discussed as "Night-watchmen centuries". Let us look at all these.
Eknath Solkar scored his only century batting at no.3 against West Indies in 1975. However this innings gets ruled out since Solkar has scored over 1000 runs at an average of 25.43. It would be unfair to call him a night-watchman.
What about Nasim-ul-Ghani's 101. It is true that Nasim-ul-Ghani has come in as night-watchman in a few matches. However in the specific match against England he batted at No.6 and scored 101. His rounded BPA is 8. So this innings does not fall into the basket of night-watchman innings.
Consider the unbeaten 99 by A J Tudor playing for England against New Zealand. England, needing 210 to win, sent Tudor in as a night-watchman. He responded by remaining unbeaten on 99, just missing out on a unique achievement. A similarly stunning performance is that of Larwood, who, after going in at No.4 instead of his more customary No.9, scored 98 against Australia in the Bodyline series.
Kirmani scored a hundred batting at no.5. However, with a career batting average of 27.05 he surely does not qualify as a night-watchman by any standards. His career-todate batting average when he played the hundred was 26.44.

C. Balls faced

The top 10 innings, in terms of balls faced, are listed below.

Year MtNo Batsman            For Vs  Bat BPA Runs(BallsFaced) Batting Avge
                                                  Act  Calc   CTD   Career
2006 1799 Gillespie J.N      Aus Bng  3  9.0 201*(425) (425) 15.69 [18.78]
1885 0018 Jarvis A.H         Aus Eng  5  8.0  82 (n/a) (322) 16.83 [16.83]
1959 0478 Nadkarni R.G       Ind Eng  4  7.0  76 (n/a) (223) 21.78 [25.71]
1933 0224 Larwood H          Eng Aus  4  9.0  98 (n/a) (221) 16.12 [19.40]
1977 0811 Mann A.L           Aus Ind  3  7.0 105 (n/a) (214) 18.33 [23.62]
2000 1486 Boje N             Saf Ind  3  8.0  85 (198) (198) 14.00 [25.23]
2002 1597 Harris C.Z         Nzl Eng  4  7.0  71 (185) (185) 19.40 [20.45]
1948 0302 Bedser A.V         Eng Aus  4  9.0  79 (n/a) (183) 15.06 [12.75]
1983 0944 Hemmings E.E       Eng Aus  3  9.0  95 (n/a) (174) 12.88 [22.53]
1994 1246 de Villiers P.S    Saf Aus  5 10.0  30 (170) (170)  8.00 [18.89]

The "balls played" information is available only for 173 of the 563 innings. In order to a complete "balls played" analysis, I have done a pro-rata allocation of the "team balls" value to the 390 night-watchman who do not have the "balls played" information, based on batsman runs and team runs. It must be remembered that this calculation has been done for a limited purpose and I am ready to accept the possible variations. The zeros have a token 1 ball allocated. However this article is not to determine the best night-watchman zero, so I can live with that.
The maximum number of balls faced by a night-watchman, with no doubts whatsoever, is the 425 balls faced by Gillespie while scoring 201, against Bangladesh. It is safe to say that when the year 2100 dawns, Lara's record might have been broken, but not this record. It was a once-in-hundred-years innings.
The 201 by Gillespie is an extraordinary innings. Notwithstanding this innings, the most significant and arguably the best ever innings played by a night watchman in Test matches must be Gillespie's 4-hour vigil at Chennai last year when he played 165 balls while scoring 26. This was a vicious spinning track and the Indian bowlers included Harbhajan and Kumble. Gillespie played the way Gavaskar batted in his farewell innings against Pakistan at Bangalore during 1987, dropping the ball dead beyond the reach of the close cordon of fielders. The importance of the series, the significance of the result and what happened on the fifth day must surely make this the greatest night-watchman innings ever. I would go to the extent of placing this innings among the best 5 innings ever played on Indian soil. It was ironical that it is by an Australian batsman, and was also possible only because Gilchrist was the captain. A Steve Waugh might have sent Michael Clark or Lehmann the previous day.

D. The batsmen who have been the night-watchmen most often (Min 7 attempts):

Player           Inns    Runs     Balls       BpI

Saqlain     (Pak) 11      98       384       34.9
Hoggard     (Eng) 11      39       249       22.6
Gillespie   (Aus)  9     327      1040      116.0
Warne       (Aus)  7      34        92       12.9 
Headley     (Ind)  7      30       177       25.3
Prasanna    (Ind)  7      61
Morrison    (Nzl)  7       7
Venkat      (Ind)  7       4

Saqlain Mushtaq (very effectively) and Hoggard (less effectively) lead the field, followed by Gillespie, the night-watchman par excellence. However Gillespie is way ahead of the others in the key indicator, Balls per innings. Warne just makes to the list, having batted in positions 3,4 and 5 few times. He is, surprisingly, a failure as a night-watchman, scoring zero in three of his seven inngs. Maybe he resented being sent as a night-watchman. Venkataraghavan is still worse, scoring only 4 runs in his 7 innings, including 5 zeros. Maybe he also felt offended.

Morrison was the biggest failure, scoring 7 runs in one innings and not opening his account in the six other innings. It is a miracle why the captains continued to use Morrison as the night-watchman. One possibility is that he lasted quite a few balls without opening his account. I wait to be enlightened. Prasanna was better, scoring 61 runs in 7 attempts. Headley was also quite good, scoring 30 runs and lasting 177 balls.

E. Conclusion

Who has been the best night-watchman in history. Easy to guess. Jason Gillespie, in 9 innings has scored a total of 327 runs at an average (no doubt aided by the unbeaten 201) of 40.87. More relevantly, he has faced a total of 1040 balls in these 9 innings, an average of 116 balls per innings. His two great innings total 590 balls. However, note his sequence, in terms of balls played: 425, 165, 145, 79, 73, 71, 43, 35 and 5. Only one failure. He sold his wicket dearly. He wins the title hands down.

What has been the best night-watchman innings played. No need to look beyond Gillespie's two classics, his match-saving effort at Chennai and the mammoth 201 against Bangladesh. As far as I am (and most people are) concerned, the Chennai innings is the best, by a mile. It was a watershed innings and changed the course of one of the most important series of recent times. If India had won on that fourth day, they might very well be sitting at the top of the ICC Test Rankings now.

The second part will follow in a week's time.

'Unfulfilled' team innings in ODI matches

2008-06-11T15:30:38Z

Ramiz Raja scored an unbeaten 102 off 158 balls as Pakistan limped to 220 for 2 and lost to West Indies by ten wickets in 1992 © Getty Images

Continuing the ODI analysis work, here is another aspect. What do I mean by "unfulfilled" innings? An example, from an imaginary match will suffice. England: 250 for 2 in 50.0 overs lost to Australia: 251 for 7 in 49.3 overs A single line summary of a match. It conveys a lot. We do not need any further match or player information to sense that there was something wrong as far as the England innings was concerned. What were the England batsmen thinking? Whoever be the Australian bowlers, should they not have gone on to score, say, 270 for 6 or for that matter, 290 for 9. Especially as the Australian bowlers seemed to have taken very few wickets, indicating a batsmen-friendly pitch and/or lack of penetration. Let us ignore the current favourite broadcasters' jargon, "no bounce", "two-paced", "not coming on to bat", "ball stopping" et al. The bottom line, especially in view of the Australian reply, was that English batsmen messed up, and messed up big time.]]> Team batting first Odi# 717. Pakistan vs West Indies Played on 23 February 1992 at Melbourne Cricket Ground. West Indies won by 10 wickets. Pakistan: 220 for 2 wkt(s) in 50.0 overs. Unbeaten 3rd wkt ptshp: 123

Rameez Raja 102*(158), Javed Miandad 57*(61)

West Indies: 221 for 0 wkt(s) in 46.5 overs

Haynes D.L 93*(144), Lara B.C 88r(101)

This match does not fall into the data mining criteria already given and is provided only to show the type of matches left out. There is no doubt that Pakistan under-achieved to the tune of about 30 runs. Note how self-centred Ramiz Raja's innings was, taking 158 balls to score 102 runs. However West Indies' response indicated that they had the resources, both wickets and balls to score these 30 runs and more. Only one match in which the losing team lost just 2 wickets. 1. ODI # 2096. South Africa vs West Indies. Played on 4 February 2004 at New Wanderers Stadium, Johannesburg. South Africa won by 4 wickets. West Indies: 304 for 2 wkt(s) in 50.0 overs. Unbeaten 3rd wkt ptshp: 92

Gayle C.H 152*(153), Chanderpaul S 85 (114), Powell R.L 49*(24)

South Africa: 310 for 6 wkt(s) in 49.4 overs

Smith G.C 58 (60), Kallis J.H 139 (142)

The first match selected is painful for me because I watched this match and was furious at the way West Indies messed up their innings. In this case the blame must rest on their early batsman since the last 10 overs added over 100 runs. Look at the South African innings. They had very little to spare, especially balls. They had almost reached their limits. If West Indies had scored 20 more runs, which was there for the taking, they would have won the match. A classic example of a team which shoots itself in the foot. Now for the teams which lost 3 wickets. 2. ODI # 1391. England vs Sri Lanka. Played on 23 January 1999 at Adelaide Oval. Sri Lanka won by 1 wicket. England: 302 for 3 wkt(s) in 50.0 overs. Unbeaten 4th wkt ptshp: 154

Hick G.A 126*(118) Fairbrother N.H 78*(71)

Sri Lanka: 303 for 9 wkt(s) in 49.4 overs

Jayasuriya S.T 51 (36), Jayawardene D.P.M.D 120 (111)

This is as perfect as we are likely to get to this particular type of match. England with 7 wickets in hand probably fell 30 runs short. Sri Lanka just about managed it. Only one wicket and two balls at their disposal. 5 runs would have been their limit. It is probably unfair to throw the blame on the English batsmen when they finished with a 300+ score. However there is no denying the fact that they fell a few runs short. Either Hick or Fairbrother should have pressed the pedal. 3. ODI # 538. India vs New Zealand. Played on 17 December 1988 at Moti Bagh Stadium, Baroda. India won by 2 wickets. New Zealand: 278 for 3 wkt(s) in 50.0 overs. Unbeaten 4th wkt ptshp: 67

Wright J.G 70 (96), Jones A.H 57 (85), Greatbatch M.J 84*(67)

India: 282 for 8 wkt(s) in 47.1 overs

Manjrekar S.V 52 (69), Azharuddin M 108*(65), Sharma A.K 50 (36)

Somewhat similar to the previous match. New Zealand should have come closer to the 300 mark, considering the fact that India were well placed at the end so far as balls were concerned, but not in terms of wickets. Note Azharuddin's innings which has remained the fastest century by an Indian batsman for nearly 20 years. 4. ODI # 1572. India vs South Africa. Played on 9 March 2000 at Nehru Stadium, Kochi. India won by 3 wickets. South Africa: 301 for 3 wkt(s) in 50.0 overs. Unbeaten 4th wkt ptshp: 52

Kirsten G 115 (123), Gibbs H.H 111 (127)

India: 302 for 7 wkt(s) in 49.4 overs

Jadeja A 92 (109)

A peculiar match. Two good centuries from the losing team. Here the last 10 overs were the problem since South Africa were 238 for 1 in 40 and added only 63 in the last 10 overs. Kallis and Cronje just could not speed up enough. Like Sri Lanka against England, reported earlier, India had very little in the tank at the end. 5. ODI # 1824. South Africa vs Australia. Played on 6 April 2002 at St George's Park, Port Elizabeth. Australia won by 3 wickets. South Africa: 326 for 3 wkt(s) in 50.0 overs. Unbeaten 4th wkt ptshp: 132

Smith G.C 84 (103), Kallis J.H 80*( 59), Rhodes J.N 71*( 50)

Australia: 330 for 7 wkt(s) in 49.1 overs

Gilchrist A.C 52 (34), Ponting R.T 92 (107), Lehmann D.S 91 (94)

A very high score by South Africa chased with nonchalance by Australia. Difficult to blame a team which scored 326 runs and lost. The finish of the innings by Kallis and Rhodes was spectacular. This also brings us to the interesting point whether nothing more could be done beyond a certain stage. Maybe the accelarator pedal was already at the floor. 6. ODI # 301. Australia vs West Indies. Played on 10 February 1985 at Melbourne Cricket Ground. West Indies won by 4 wickets. Australia: 271 for 3 wkt(s) in 50.0 overs. Unbeaten 4th wkt ptshp: 68

Smith S.B 54 (90), Wood G.M 81 (119), Phillips W.B 56*(37)

West Indies: 273 for 6 wkt(s) in 49.2 overs

Richardson R.B 50 (90), Logie A.L 60 (56)

Smith and Wood were probably too slow at the beginning; so was Richardson for West Indies. However they were clear about their target and just reached the same. 7. ODI # 794. India vs England. Played on 18 January 1993 at Sawai Mansingh Stadium, Jaipur. England won by 4 wickets. India: 223 for 3 wkt(s) in 48.0 overs. Unbeaten 4th wkt ptshp: 164

Kambli V.G 100*(149), Tendulkar S.R 82*( 81)

England: 224 for 6 wkt(s) in 48.0 overs

Stewart A.J 91 (126)

A low scoring match lost by India. Somewhat similar to Ramiz Raja's century mentioned earlier, Kambli's was probably quite slow. That India had slipped to 59 for 3 does not absolve the Mumbai pair of the tardiness of the partnership. It must be mentioned that Azharuddin, who essayed a 65-ball 108 in 1988, played a match-losing 6 in 28 balls here. 8. ODI # 615. West Indies vs England. Played on 3 April 1990 at Kensington Oval, Bridgetown, Barbados. West Indies won by 4 wickets. England: 214 for 3 wkt(s) in 38.0 overs. Unbeaten 4th wkt ptshp: 53

Smith R.A 69 (84) Lamb A.J 55*(39)

West Indies: 217 for 6 wkt(s) in 37.3 overs

Richardson R.B 80 (84), Best C.A 51 (43)

Somewhat similar to the previous match. David Smith of England took 31 balls for his score of 5 and Wayne Larkins, 73 balls for his 34. Together they had a strike rate of 2.4 runs per over. The matches in which the first batting team lost 4 wickets and the second batting team lost 7 wickets or more are shown in a summary form.

 9.2349 2006 Aus 434/4 in 50.0 Saf 438/9 in 49.5 won by 1 wicket
10.2499 2007 Ire 284/4 in 50.0 Ken 286/9 in 49.0 won by 1 wicket
11.1035 1996 Aus 242/4 in 50.0 Slk 246/7 in 49.4 won by 3 wickets
12.0716 1992 Zim 312/4 in 50.0 Slk 313/7 in 49.2 won by 3 wickets
13.2439 2006 Win 272/4 in 50.0 Eng 276/7 in 48.3 won by 3 wickets
14.2184 2004 Zim 252/4 in 50.0 Pak 258/7 in 48.1 won by 3 wickets

The first match needs a mention. I hope a reader does not come back and blast me for implying that Australia should have scored a few more runs. It was South Africa's relentless aggression and continuous attacking play that finally won them the match. Having said this I must mention that Lee could score only a single off the last two balls bowled by Telemachus. A four or two would have helped. In the second match, K.J.O'Brien scored 142 in 123 for Ireland. Kenya were 231 for 9 and a great Irish victory seemed certaiin. Then Odoyo, with a blistering 61 in 36 added 55 for the tenth wicket in 5 overs and won. A few more runsfor Ireland and who knows what might have happened. No particlular team has messed up their first innings, in this regard, more often than the others, although, for the record, Australia have been the culprit three times. Sri Lanka does not appear in this list even once. Team batting second Now for the team batting second. Here I have ignored all matches decided through D/L or equivalent methods. The reason has already been explained. In other matches, only reasonably close matches, where the margin of loss was less than 30 runs, are considered. That leaves us with only 3 competitive matches. 1. ODI # 56. Pakistan vs India. Played on 3 November 1978 at Zafar Ali Stadium, Sahiwal. Pakistan won (conceded by India). Pakistan: 205 for 7 wkt(s) in 40.0 overs

Asif Iqbal 62 (76)

India: 183 for 2 wkt(s) in 37.4 overs

Gaekwad A.D 78*(103), Amarnath S 62 (86)

This was the match conceded by India after Sarfraz bowled a series of bouncers in the 38th over. I do not want to get into an argument with anyone. It is clear that the short pitched balls were over-used. It is also clear that the rules were very vague and Pakistan were justified in using the rules to their advantage. Mushtaq Mohammad cannot be blamed for that. If Bedi was the fielding captain, surely he would also have done the same thing, although he could not very well have asked Ghavri and Mohinder Amarnath to bowl bouncers at 120 kmph. Anyhow why should a captain concede a match when so close to the target. Bedi should take responsibility for that. 2. ODI # 160. Pakistan vs Australia. Played on 8 October 1982 at Gaddafi Stadium, Lahore. Pakistan won by 28 runs. Pakistan: 234 for 3 wkt(s) in 40.0 overs

Zaheer Abbas 109 (117), Javed Miandad 61*(65)

Australia: 206 for 4 wkt(s) in 40.0 overs

Laird B.M 91*(114), Hughes K.J 64 (80)

Possibly defensive fields and defensive bowling prevented Australia from speeding towards the end. Alternately the lack of experience in handling chases could have been the reason. It must be conceded that a scoring rate of nearly 6 was quite difficult to achieve those days. 3. ODI # 333. Sri Lanka vs India. Played on 21 September 1985 at P.Saravanamuttu Stadium, Colombo. Sri Lanka won by 14 runs. Sri Lanka: 171 for 5 wkt(s) in 28.0 overs

Madugalle R.S 50*(39)

India: 157 for 4 wkt(s) in 28.0 overs

Vengsarkar D.B 50 (46)

The asking rate was quite high (6.10) and India, despite having Srikkanth and Kapil could not do much against the accurate Sri Lankan bowling, led by John. Finally I cannot close this without referring to this particular classic (mis)match. ODI # 19. England vs India. Played on 7 June 1975 at Lord's, London. England won by 202 runs. England: 334 for 4 wkt(s) in 60.0 overs

Amiss D.L 137 (147), Fletcher K.W.R 68 (107), Old C.M 51*(30)

India: 132 for 3 wkt(s) in 60.0 overs

Gavaskar S.M 36 (174), Viswanath G.R 37 (59)

This was the infamous Gavaskar crawl. Even though this was India's third ever ODI match, it is beyond anyone's, including his own, comprehension what Gavaskar was thinking. However, enough has been written on the subject. At least for this post let me hope that readers do not respond with messages such as "why was abc not considered", "xyz is superior to pqr", "efg was the best" et al. Consider these as the only matches to be looked into. Comments such as "This is a useless analysis" will not be published since there is no insight provided. On the other hand, a comment such as "The analysis is flawed since only the wickets lost are taken into account. The balls remaining should also be taken into consideration" will be published since that is a genuine comment on the article and adds value.

Why Australia's 2001 line-up is the best ODI side- A follow-up

2008-06-03T13:37:49Z

The original article received nearly 200 responses. Unfortunately not all could be posted, mainly because quite a few responses contained readers' own selection of their all-time best ODI teams. This was outside the theme of the article and I can assure the readers that they will have a chance later to come out with their views on this topic as well. Some posts were also rejected because they contained offensive language and/or referred to other responders in negative terms. I must thank the readers for the interest they have shown. I must confess that I keep learning new things because of the interaction. There are new perspectives which had escaped me the first time around. I have gone through all the responses. I have adopted the following three significant improvements. There were a few other valid suggestions which have not been implemented. These are summarised at the end, with my reasons for not implementing them.]]> 1. Decade-level adjustments To do this I have split the matches into four decades, the (swinging) 1970s, the (exciting) 1980s, the (nervous) 1990s and the (Twenty20-driven) 2000s. Please see the following table, first for batting and then for bowling. Incidentally this concept itself deserves of an independent post. In both tables I have used the base factor as the All match numbers, which is presented in the first column. I concede that this is heavily weighted towards the later years. However there is no other way. If I take the median match (no.1354) as a cut-off point, that match itself was played as recently as 1998. So whatever one does, this problem will remain.

ODI Matches - Analysis by Decade - BATTING
	All Matches	1970s	1980s	1990s	2000s
Matches played	2703	82	516	933	1172
Batsmen innings	46968	1418	8838	16266	20446
Balls bowled	1445956	46208	277516	505727	616505
Runs per match	414	369	393	414	426
Runs per innings	23.83	21.36	22.96	23.76	24.44
% of all-matches avge	100.0%	89.6%	96.3%	99.7%	102.5%
Runs per ball	0.774	0.656	0.731	0.764	0.811
% of all-matches avge	100.0%	84.7%	94.4%	98.7%	104.7%

a. There is a clear increase in the Runs per match, which has been done mainly to show the trend. b. Runs per innings, which is used to avoid the not outs impact, has clearly shown a move up, from 21.36 during the 1970s to 24.44 for the current decade matches. c. Similarly, the scoring rate (runs per ball) has shown a clear move upward, from 0.656 (Rpo of 3.94) during the 1970s to 0.811 (Rpo of 4.86) now. The adjustment is done in the following manner. The Batting Index figures are adjusted by the Decade adjustment values. In other words, the Batting Average Index is divided by 0.896 for the 1970s teams, by 0.963 for the 1980s teams, by 0.997 for the 1990s teams and by 1.025 for the current teams. Similarly the Batting Strike Rate Index is divided by 0.847 for the 1970s teams, by 0.944 for the 1980s teams, by 0.987 for the 1990s teams and by 1.047 for the current teams.

ODI Matches - Analysis by Decade - BOWLING
	All Matches	1970s	1980s	1990s	2000s
Matches played	2703	82	516	933	1172
Balls bowled	1445956	46208	277516	505727	616505
Team Runs conceded	1119374	30292	202884	386508	499690
Wickets captured	38120	1156	7097	13215	16652
Wkts per match	14.10	14.10	13.75	14.16	14.21
Bowling Average	29.36	26.20	28.59	29.25	30.01
% of all-matches avge	100.0%	89.2%	97.4%	99.6%	102.2%
Balls per wkt	37.9	40.0	39.1	38.3	37.0

a. It is surprising, maybe not so, that the average number of wickets captured per match has remained fairly constant over these 30-odd years. b. The bowling averages have shown a clear move upwards from 26.20 during the 1970s to 30.01 for the current decade. A minor concession, likely to have little impact on the final numbers, is made in that the bowling average for this purpose is calculated based on the team runs and team wickets. c. The balls per wkt figures show a slight reduction as time has gone by, with the difference being only around 7.5%. It's given here only for information. The adjustment is done in the following manner. The Bowling Index figures are adjusted by the Decade adjustment values. In other words, the Bowling Index is multiplied by 0.892 for the 1970s teams, by 0.974 for the 1980s teams, by 0.996 for the 1990s teams and by 1.022 for the current teams. Maybe it's not perfect, but this significant tweak has gone a long way in redressing the imbalance, as the results show. 2. Changing the weightings given to late order batsmen Jeff Grimshaw has demonstrated that the higher average batsmen would, most probably, be able to bat through their 50 (or whatever) overs without even approaching the late-order batsmen. On the other hand, the lower-average, quicker-scoring batsmen might need the late-order batsmen often. It is, however, essential that we recognize the quality of late-order batsmen. After all, Vettori and Martin are poles apart, when it comes to batting. Hence the weightage is changed, as follows. No. 8 Batsman: 0.40
No. 9 Batsman: 0.30
No.10 Batsman: 0.20
No.11 Batsman: 0.10
3. Home Advantage I have effected a 5% increase for all the Index values for home teams for reasons already explained. This value is not applied for the hundreds of matches played in neutral venues. The only question is, why 5%, why not 2.5% or why not 10%. I have no answer other than my gut feel that the additional weighting cannot exceed the value assigned for Fielding. The revised tables are summarized below. Batting 1. 2004 2196 1 AUS (vs Nzl) 19.95 20.68 40.63; Gilchrist A.C, Hayden M.L, Ponting R.T, Lehmann D.S, Martyn D.R, Symonds A, Clarke M.J. (after 21 other Australian teams (as compared to 107 Australian teams earlier)) 23. 1999 1390 2 SAF (vs Win) 18.80 20.63 39.43 Kirsten G, Gibbs H.H, Kallis J.H, Cullinan D.J, Cronje W.J, Rhodes J.N, Pollock S.M. (after 44 other teams) 68. 2005 2237 2 IND (vs Pak) 18.35 20.27 38.62 (Match lost) Sehwag V, Tendulkar S.R, Dhoni M.S, Ganguly S.C, Dravid R, Yuvraj Singh, Kaif M. Bowling 1. 1981 0116 2 WIN (vs Eng) 1.62 39.53 41.15 Roberts A.M.E, Holding M.A, Garner J, Croft C.E.H + Richards/Gomes. 2. 2001 1670 2 AUS (vs Win) 2.55 38.57 41.12 Warne S.K, Lee B, Bracken N.W, McGrath G.D, Symonds A. 3. 1981 0115 1 WIN (vs Eng) 1.37 39.53 40.90 Roberts A.M.E, Garner J, Holding M.A, Croft C.E.H + Lloyd/Gomes. 4. 2000 1552 2 AUS (vs Ind) 2.58 38.22 40.80 Warne S.K, Lee B, Fleming D.W, McGrath G.D, S.R.Waugh. 5. 2000 1622 2 AUS (vs Saf) 2.56 38.21 40.77 Warne S.K, Lee S, Gillespie J.N, Lee B, McGrath G.D. It is in Bowling that these changes are felt a lot. The top 5 teams are now composed of West Indian and Australian teams since the Australian bowlers have got their Indices adjusted accordingly. Team Strength 1. 2001 1670 2 AUS (vs Win) 39.47 38.57 2.55 80.59 Gilchrist A.C, Waugh M.E, Ponting R.T, Bevan M.G, Lehmann D.S, Martyn D.R, Symonds A, Warne S.K, Lee B, Bracken N.W, McGrath G.D. (after 24 other Australian teams (as compared to 144 Australian teams earlier)) 26. 1983 0189 1 WIN (vs Ind) 37.28 38.24 2.15 77.67 Greenidge C.G, Haynes D.L, Richards I.V.A, Logie A.L, Lloyd C.H, Gomes H.A, Dujon P.J.L, Marshall M.D, Roberts A.M.E, Holding M.A, Garner J. (after 19 other Australian/West Indian teams) 46. 2002 1918 1 SAF (vs Pak) 37.48 37.17 2.45 77.10 Smith G.C, Gibbs H.H, Dippenaar H.H, Kallis J.H, Rhodes J.N, Boucher M.V, Pollock S.M, Klusener L, Hall A.J, Donald A.A, Ntini M. You can note the significant change. The 1983 West Indian team moves up considerably. The top 100 now has teams from Australia, West Indies and South Africa. The best teams for all the 10 Test-playing countries can be viewed by clicking here.
Not considered 1. Career-to-date average or recent form adjusted values instead of career average I evaluated this option but decided not to do the change. The reasons are many. Richards is an outstanding 47.00(Avge) / .887(Strt) batsman. If his mid-career figures were lower or his recent form was not good, that does not make him any lesser, at any time in his career. Similarly for other great players such as Tendulkar, Lara, Wasim Akram, McGrath et al. The other reason is that between the 11 players these numbers would get evened out. The last reason is that this will involve too much work, for very little improvemet. 2. RPI instead of Batting Average This was also considered seriously. I did not do this because that meant I would be going away from the widely accepted Batting Average. It is true that a Hussey or Bevan might gain in view of the high number of Not outs. However this is more than compensated by the fact that they would have had very little time to settle down, they would have to throw the bat around and in general play for the team score. The early batsmen, on the other hand, may be hampered by the high number of dismissals. However they would have time to settle down, play themselves in and in general play longer innings. 3. Consider the two Bowling parameters separately This was also a good suggestion. However, I could not get away from the fact that the bowling average is a composite value of the two components (Bowling Average = Strike Rate x Accuracy). I also did some trial calculations. These showed that the impact of splitting the two components would be minimal. Hence I retained the Bowling Average. 4. Finally the Fielding Everyone knows that Jonty Rhodes was a great fielder. But then how great a fielder was he? Was he greater than Colin Bland, Roger Harper, Ricky Ponting et al or not? Is there a quantifiable and verifiable measure available? Even run-outs started getting attributed to specific fielders only recently. Possibly the greatest fielding display of all time was effected by Richards during the 1975 World Cup final against Australia. His three run-outs do not find a place on the scorecard. We do not have a measure for fielding. Until we get that (even then what about the earlier matches) it will be impossible to quantify fielding. I am not going to do a subjective error-prone Fielding Index. Instead I have done a low weighting of 5% for Fielding, done using the available Catches/Stumpings values. I have also resisted the temptation to come out with an all-time best world team. That is outside the scope of this team-oriented analysis and I want to avoid making the mistake I made in my previous post. Surely there will be another time when such an analysis will be done.

Why Australia's 2001 line-up is the best ODI side

2008-05-23T12:25:46Z

Post-Note: "I urge readers to read and understand the reasoning behind the analysis. It is NOT to determine the best ODI team across years or teams. Rather it is to determine the best team that walked on to the field, as 11 players. Many comments have been made ignoring this fact. So much so, no comment which lists the readers' favourite team will be published. Let me add that over 50 comments have gone unpublished because of this." For my next post, I wanted to stay away from Test cricket, on which most of the recent It Figures posts have been. At the other extreme we have Twenty20, which has had an all-pervading presence on almost all the channels on television, and the web and print media as well. That leaves the often-ridiculed form of cricket, one-day internationals. I never thought I would say this, but I have already started longing for ODI cricket. This time I have taken for analysis a topic which I had looked at for Tests, and am now adapting to ODIs: how strong is an ODI team and how do the teams compare over the 37 years of ODI cricket? Where does the 2007 Australian team stand when compared to the West Indian teams of early 1980s, or for that matter the Australian teams of the late 1990s? It has turned out to be a fascinating study. ]]> Batting
ODI batting consists of two distinctly measurable and independent factors: how many runs are scored and how fast they are scored. In other words, the batting average and the strike-rate. No one can question the decision to treat these two parameters equally. The average is taken rather than the lesser known and acceptable runs per innings or my own development, the extended batting average. The average is a widely accepted measure and presents the best method of measuring runs scored. Only two batsmen in ODI history, Michael Bevan and Michael Hussey, have averages higher than 50 (among those with a minimum of 20 innings), mainly because of their number of not-outs. However this is partly rectified by limiting the average to 50.0 for these two batsmen. There is no problem with strike-rate. That is available as a straight computation of runs scored / balls faced. The averages and strike-rates of the top seven batsmen in the team's batting order are summed. The averages and strike-rates for batsmen nos. 8 to 11 are given a 25% weightage each. The arrived total is divided by eight and the Team Batting Average and Team Strike-Rate are arrived at. The batting average index points are determined by dividing the team batting average by two. The maximum value for this is 25.0. The strike-rate index points are determined by multiplying the team strike-rate (runs per ball) by 25.0. The maximum value for this is just over 25.0. Only one batsman in ODI history, Shahid Afridi, has a career strike rate of over 1.00. Care is taken that these full values are applied only for career aggregates of 1000 runs and above. Otherwise Arvind Kandappah of Canada and Alex Obanda of Kenya will single-handedly make their team's batting averages huge. These two have Bradmanesque career batting averages of 97.0, although scoring only 97 and 194 runs respectively.

 SNo. Year MtNo I Team   vs     AvIdx  SRIdx  Bat

   1. 2005 2257 2 AUS (vs Bng) 19.89 20.99 40.87
      (Gilchrist, Hayden, Ponting, Martyn, Clarke M, 
       
Symonds, Hussey).   
   2. 2005 2261 2 AUS (vs Eng) 19.91 20.90 40.81
   3. 2005 2259 1 AUS (vs Eng) 19.67 20.78 40.45
   
Next 105 teams are Australian, followed by

 109. 2005 2282 2 ICC (vs Aus) 18.15 20.47 38.62
        (Sangakkara, Sehwag, Kallis, Lara, Dravid, 
         Pietersen, Flintoff, Afridi)

Next 16 teams are Australian, then

 126. 2004 2202 1 IND (vs Bng) 18.06 20.43 38.49
        (Sehwag, Tendulkar, Ganguly, Dravid, Kaif, 
         Yuvraj Singh, Dhoni). 

Then another 5273 teams

5400. 2004 2172 1 USA (vs Aus)  3.27  9.73 13.00
5401. 1979 0067 1 CAN (vs Eng)  5.05  7.85 12.91
5402. 1979 0070 1 CAN (vs Aus)  4.76  6.98 11.74

Note: Out of the 2703 matches considered, two matches were abandoned without even the team information being available. The first 108 teams in the batting list are Australian. These 108 matches have come over a nine-year period, from 1999 to 2008, a period of total Australian domination, punctuated by three World Cup wins. The three batsmen who have been part of almost all these matches are Adam Gilchrist, Ricky Ponting and Andrew Symonds. Bowling
Like batting, bowling also has two components, the bowling strike-rate and accuracy. However, unlike batting, the bowling average is a fantastic measure since it encompasses both these key measures in a single value. Consider the following.

                  Runs Conceded
Bowling Average = -------------
                  Wickets Taken

Rewriting this as

                  Runs Conceded     Balls Bowled
Bowling Average = -------------  x  -------------
                  Balls Bowled      Wickets Taken

This can be written as

Bowling Average = Bowling Accuracy x Bowling Strike-Rate.

There is no need to measure these two factors independently. It is sufficient to take the single composite measure, bowling average and work on it. Unlike the batting computation, the bowling averages of the best five bowlers is taken and divided by five. This is because it is expected the team would use their best five bowlers. Even if Jacques Kallis bats at No. 3, he is likely to be used as a bowler if he is one of the best five. Whether he bowls in the concerned match or not is outside the scope of this analysis since this study only measures how strong a team potentially is, not how strong the team actually was. Here also care is taken that bowlers with less than 50 wickets have their figures scaled down suiitably. Otherwise Gary Gilmour, with 16 career wickets at 10.31, will completely tilt the figures of the late-1970s Australian teams. The bowling index is determined by subtracting the Team Bowling Average from 60.0. Since the best bowling average for qualifying bowlers [minimum 50 wickets] is 18.85 by Garner, the highest value will not exceed the maximum weightage given to bowlers, of 45. For both batting and bowling, I have also taken the full career figures rather than the career-to-date figures in view of the complexity of calculation and the fact that we are averaging and the minor differences tend to get ironed out. Fielding
Only catches and stumpings are considered. The values for all 11 players are added, divided by 11, and multiplied by two to get a team fielding average. The highest value is 1.95 and the maximum index value is 3.90. It is obvious that this figure will be strongly influenced by the wicketkeeper's figures. A per match average rather than catches/stumpings aggregate is taken to be fair to weaker teams.

 SNo. Year MtNo I Team   vs    Fld   Bow   Tot

   1. 1981 0116 2 WIN (vs Eng) 1.55 38.65 40.20
      (Roberts, Holding, Croft, Garner)
   2. 1982 0134 2 WIN (vs Pak) 2.25 37.79 40.03
   3. 1982 0135 2 WIN (vs Aus) 2.25 37.79 40.03

Next 21 teams are West Indian, then

  25. 2001 1670 2 AUS (vs Win) 2.44 35.95 38.38

Then another 5374 teams

5400. 1979 0070 1 CAN (vs Aus) 0.17 10.00 10.17
5401. 1979 0067 1 CAN (vs Eng) 0.17 10.00 10.17
5402. 1979 0064 1 CAN (vs Pak) 0.17 10.00 10.17

The first 24 teams in the batting list are West Indian teams. These 24 matches have come over a six-year period, from 1981 to 1987. The two bowlers who have been part of almost all these matches are Holding and Garner. Final Team Strength
This arrived by adding the batting, bowling and fielding indices. The maximum is 100, making it easier to see things in perspective.

 SNo. Year MtNo I Team   vs     Bat   Bow  Fld  Team

   1. 2001 1670 2 AUS (vs Win) 38.95 35.95 2.44 77.34
      (Gilchrist, Waugh M, Ponting, Bevan, Lehmann, Symonds,
       Martyn, Warne, Lee, Bracken, McGrath).   
   2. 2004 2180 1 AUS (vs Eng) 39.28 35.39 2.56 77.23
      (Gilchrist, Hayden, Ponting, Martyn, Lehmann, Clarke M, 
       Symonds, Lee, Gillespie, Kasprowicz, McGrath).   
   3. 2004 2172 2 AUS (vs Usa) 39.28 35.39 2.56 77.23
       (Same as previous team)      
   4. 2004 2131 2 AUS (vs Zim) 39.10 35.30 2.69 77.09
   5. 2003 1951 2 AUS (vs Ind) 39.47 35.02 2.43 76.91

Next 140 teams are Australian, then

 146. 1982 0139 2 WIN (vs Aus) 33.82 37.79 2.25 73.86
      (Greenidge, Haynes, Richards, Gomes, Lloyd, 
       Bachhus, Dujon, Roberts, Holding, Clarke ST, Garner).

Next 19 teams are Australian/West Indian, then

 166. 2005 2282 2 ICC (vs Aus) 38.62 32.75 2.28 73.65
      (Sangakkara, Sehwag, Kallis, Lara, Dravid, 
       Pietersen, Flintoff, Shahid Afridi, Pollock S, 
       Vettori, Shoaib Akhtar, Muralitharan).

Then another 5233 teams

5400. 1975 0024 1 EAF (vs Ind) 13.06 10.00 0.52 23.58
5401. 1979 0067 1 CAN (vs Eng) 12.91 10.00 0.17 23.07
5402. 1979 0070 1 CAN (vs Aus) 11.74 10.00 0.17 21.91

The first 145 teams in the list are Australian. These 145 matches have come over a nine-year period, from 1999 to 2008, a period of total Australian domination, punctuated by three World Cup wins. The five players who have been part of almost all these matches are Gilchrist, Ponting, Symonds, Brett Lee and Glenn McGrath. Finally I have done another "fourth dimension" formation. Australia have had the best batting teams ever and West Indies, the best bowling teams ever. Let us combine the two into one all-time great ODI team. Take the first seven players from the Australian 2005 team [Match no. 2257] and add to it the best four bowlers from the 1981 West Indies side [Match no. 116]. Given below is the final squad. Just to round up the analysis, this all-time great team has an index value of 77.05, which is lower than the Australia 2005 figure. This has been caused no doubt by the loss of batting and fielding points of the Australian team (Watson/Lee/Gillespie/Kasprowicz are much better batsmen and fielders than the West Indian bowling quartet). However, the team listed below is an outstanding one with a superb bowling attack.

Adam Gilchrist
Matthew Hayden
Ricky Ponting
Damien Martyn
Michael Clarke
Andrew Symonds
Michael Hussey
Andy Roberts
Michael Holding
Colin Croft
Joel Garner.

Readers should not forget that this not necessarily the best ODI Team of all time, It has been formed by merely taking the first 7 players from the best ever Batting line-up and adding the 4 bowlers from the best ever Bowling line-up. Theoretically this team can be further improved by taking in Tendulkar, Richards, Dhoni, Wasim Akram, Shane Warne et al. That is a different day and different motivation. For the present let us enjoy the combination of two different eras. If we tamper with this team, the charm would be lost. The Australia-West Indies combination would be missing. After all, these two countries have dominated the ODI scene during these 37 years, West Indies during the first ten years and Australia, the last 20.

ODI Analysis - by decade
Batting	AllMats	1970s	1980s	1990s	2000s
Matches played	2703	82	516	933	1172
Runs scored	1119374	30292	202284	386508	499690
balls bowled	1445956	46208	277516	505727	616505
Batsmen innings	46968	1418	8838	16266	20446

So near yet so far

2008-05-09T13:24:58Z

When Virender Sehwag strode out on the fourth day of the recent Test against South Africa in Chennai, he already had 309 runs to his name. There would have been a great many fans wondering how far he could go: could he top Brian Lara’s 400? Statistics, however, indicate the fans were very likely to be disappointed [as they were]. The truth is that while 309 and 400 sound like reasonably similar scores, they are not. In fact, it is harder for a batsman to add another 100 runs if he has already made 300, than it is at almost any other score.]]> Conversion rates in 100-run increments Score range No. of dismissals No. of successes Conversion rate 0-99* 33,822 2942 8% 100-199 2334 279 10.7% 200-299 192 22 10.3% 300-399 17 1 5.6% *0-99 data involves only recognised batsmen (#1-6 in batting order). “Number of successes” refers to the number of innings that have passed through the specified range without dismissal, e.g., for 0-99 it refers to the number of centuries. While interesting, this data is not very robust for the 300-399 range. If the next batsman to make a triple-century happens to go on to 400, the conversion rate will almost double [to a rate similar to the 300-400 conversion rate in first-class cricket of 11%]. However, the difficulty batsmen encounter above 300 can also be seen when we look more closely, at 20-run increments.

Conversion rates in 20-run increments
Score range	No. of dismissals	No. of successes	Conversion rate
100-119	1105	1791	62%
120-139	581	1087	65%
140-159	329	667	67%
160-179	209	414	66%
180-199	110	279	72%
200-219	96	142	60%
220-239	50	84	63%
240-259	22	55	71%
260-279	19	30	61%
280-299	5	22	81%
300-319	7	14	67%
320-339	5	7	58%

Note the similarity of the pattern at the 200-run mark and the 300-run mark. As batsmen approach 200, their conversion rate rises, only to fall suddenly after reaching the milestone; the same thing happens at 300. A dismissal between 280 and 299 is a rare thing. It is also striking that a batsman’s ability to add runs once he has reached 300 [67% and 58% for 300-319 and 320-339] is, in effect, no better than for those who have just reached 100 [62% and 65%]. Further perspective can be gained by looking at the one batsman who did make it to 400, Brian Lara at St John’s in 2004. In that innings, Lara played with caution and great focus after reaching 300, taking 178 balls to go from 300 to 400 [56 runs per 100 balls]. This is probably the slowest progression from 300 to 400 in first-class cricket: in doing this under very benign conditions when quick runs were called for, Lara also sacrificed any chance his team had of winning the match. Few triple-centurions take this approach. The surprisingly high rate of failures after reaching 300, when scoring should be easiest, is probably a combination of mental exhaustion and the need for quick runs in those circumstances. The typical scoring-rate for triple-centurions in their first 300 runs is about 63 runs per 100 balls, but for runs beyond 300 [apart from Lara], the rate is over 80 runs per 100 balls, in time-limited Tests.

Sensational sessions

2008-04-12T13:38:29Z

Jack Hobbs made his highest Test score of 211 as England hammered 503 runs on a single day at Lord's in 1924 © The Cricketer International

Test cricket has changed in many ways over the decades; to the statistician, one of the most striking is the speed at which it is played. By that, I don’t mean the speed of bowling or scoring, though these are important, but simply the sheer amount of cricket that gets played in any given hour or day. Today, it is rare to see even 90 overs bowled in six hours, but in days gone by, 140 or even 150 overs in a day was commonplace. On the second day of the Lord’s Test of 1946, India and England wheeled through no fewer than 161 six-ball overs. For spectators, it must have been rich entertainment when batsmen were on the attack. One of the most productive innings came at Lord’s in 1924, when England put South Africa’s bowlers to the sword, scoring 503 runs on the second day, for just two wickets, in less than five-and-a-half hours. England scored 200 runs before lunch and another 223 between lunch and tea. While 200 or more in one session is rare enough, keeping it up for two sessions in a row appears to be unique. ]]> Times commented that towards the end he batted as though he “seemed to think someone else might as well have a turn at batting”. One of those others was Frank Woolley, one of the most aggressive batsmen of his generation, who scored 134 not out off 123 balls, fine hitting in any era. A tally of 223 runs in one session raises the question of records. Where does it stand? No one seems to have assembled a list before, so here is my attempt. This is one record that favours old-time Tests, but there are a few modern entries [all involving “minnows”]. Pre-War Tests in England predominate, mainly because sessions and days in other countries in the days of high over-rates tended to be shorter than in England. (a pre-War Test day in England was often six-and-a-half hours, but in Australia only five hours.) I have examined only those Tests that had specified tea breaks; tea breaks were not always taken in Tests before 1910. In fact, there are quite a few extreme cases from sessions that were extended beyond the normal two hours, for various reasons. These have been put into a separate list. Note that all of the two-hour cases were the lunch-tea session, whereas all of the extended-session cases are in the opening or closing sessions. Most runs in a two-hour (maximum) session
236 (43 overs) Aus v SA, Lunch-Tea, Joburg 1921 (119 off 85 balls by Jack Gregory)
233 (41 overs) Eng v Pak, Lunch-Tea, Nottingham 1954 (Denis Compton 173)
231 (45 overs) Eng v NZ, Lunch-tea 3rd day, Leeds 1949 (both teams batted)
223 (43 overs) Eng v SA, Lunch-Tea, Lord’s 1924
220 (47 overs) Eng v NZ, Lunch-Tea, Wellington 1933 (Wally Hammond 151)
208 (32 overs, 100 minutes) Aus v SA, lunch-tea, Sydney 1910/11
207 (29 overs) Aus v Zimbabwe Lunch-Tea Perth 2003 (both Matt Hayden and Adam Gilchrist scored centuries in the session) Most runs in a longer session
249 (33 overs) SA v Zim, post-tea 1st day, Cape Town 2005
244 (58 overs, 165 minutes), Eng v Aus, post-tea, Oval 1921
239 (45 overs, 140 minutes), Eng v NZ, pre-lunch, Lord’s 1937 (two teams)
223 (35 overs, 150 minutes) Eng v Ban, post-tea, Chester-le-Street 2005 (Marcus Trescothick 127)
221 (150 minutes) Eng v SA, pre-Lunch, Oval 1935 (Les Ames 123)
219 (35 overs, 150 minutes) NZ v Zimbabwe, post-Tea, Harare 2005 (Daniel Vettori 127)
~210 (150 minutes) Eng v India, pre-Lunch, Oval 1936
208 (47 overs, 154 minutes) Aus v SA, post-tea, Melbourne 1910/11 (Victor Trumper 133)
200 (57 overs, 150 minutes) Eng v SA, pre-Lunch, Lord’s 1924 Readers are invited to submit others that I may have overlooked. ******** Speaking of remarkable sessions, I was asked if India, all out for 76 against South Africa in Ahmedabad, had become the first team to be bowled out before lunch on the first day of a Test match. Not quite, as it happens, but there appears to be only one precedent, and that was 112 years ago. In the Lord’s Test of 1896, Australia was bowled out for 53 in 85 minutes, allowing England to reach 37/0 before lunch. India also became the first team to be bowled for less than 100 after scoring over 600 in their previous innings in the same series. Sri Lanka once went from 713/3 to all out 97 in consecutive innings in 2004, but as their opponents were Zimbabwe and Australia respectively, it’s not quite the same thing.

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

2008-03-27T10:34:41Z

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.]]> 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
                                      BatAvge

  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. Conclusion 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.