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Anantha Narayanan

Consistency in Test bowlers: a new look

An improved way of analysing consistency across the career of Test bowlers statistically

This is based on an idea given by Prashanth. After giving the idea and participating in a discussion or two, he disappeared off the radar. However I thank him for providing the spark. Couple of years back Gabriel Rogers did a similar article. However that wonderful article was based on complex statistical methodology and would not have been out of place in an Annual Conference of Statisticians. Mine is simpler, more common-sense based and is aimed at everyone who comes into this blogspace, irrespective of his statistical knowledge.

The relevant points are explained below.

1. For this purpose five-Test slices are considered. This is a reasonable number and normally covers 2-3 months of Test cricket. Tests, rather than innings are used as the basis so that both bowling and batting can be covered in an equitable manner.
2. Five tests means that batsman can go through a Test or two of limited opportunities to bat or non-batting because of emphatic wins etc. There will be enough opportunities within the five-Test slice to catch up. Normally the bowlers do not have this problem since they do a higher share of a team's work and have to capture 20 wickets for a win.
3. There is enough time to get over short duration loss of form.
4. To measure consistency, only runs scored and wickets captured will be used. The fundamental cricket dictum that batsmen should score runs and bowlers should take wickets is followed. Averages are important mainly over a career and for comparisons across players.
5. Why not average? Let us take couple of examples to understand why not. McGrath and Trueman have career averages around 22.0 and WpT values of around 4.5. In a 5-Test period, match context being comparable, McGrath captures 25 wickets at 25.0 and Trueman, 15 wickets at 20.0. Who has performed closer to his career figures and for that matter, better. Certainly McGrath, despite the higher slice average. Similarly for batting.
6. Let us not forget that we remember numbers like 46 (Laker) and 41 (Alderman) rather than the specific averages. Similarly 774 (Gavaskar) and 688 (Lara) without being aware of the averages.
7. The career slices should be non-overlapping and equal, other than the last one. Gooch's 456 in one test should be part of one career slice only. Similarly Laker's 19 wickets. Hence the concept of rolling number of Tests is not valid.
8. Five Tests might seem arbitrary but represents a long enough career slice. It represents a long Test series.
9. The keyword is consistency with reference to the player's own career performance levels. It may happen that a bowler has a rather high WpT value: e-g, Barnes at 7.00, Muralitharan at 6.02 et al., and what is perfectly acceptable for another bowler might not be, for such bowlers. That is acceptable since they have set high benchmarks and we are interested in seeing how often they went off these benchmarks.
10. We are not looking about high and low values but only relative to the concerned player's career figures. Over a five-Test stretch Murali is expected to take 30 wickets and Kallis is expected to capture nine wickets. This will be the basis. If Murali captured 20 wickets in the Test slice, it is well below average and the same 20-wickets performance for Kallis, way above average.
11. I know that a bowler like Imran Khan who did not bowl at all in 3 slices at the end of his career would be slightly affected by this methodology. However there is no clear method of handling this. I do not want to exclude Tests where a bowler did not bowl. Then the number of slices would not be dependent on the number of Tests played. Also I don't want someone later on asking me to exclude batsman's Test where there has been an innings win for loss of few wickets. These are minor quirks and may only reduce the accuracy from 100% to 95%.
12. Adjustment is made for the last career slice if the same is fewer than five Tests.
13. The criteria for selection is 100 or more Test wickets. 160 bowlers qualify. The only bowlers of note who are missing are Shane Bond and Frank Tyson (Adrian, happy !!!).
14.The Standard Deviation (SD) of the slice ratios is used to determine consistency.

I had initially thought that I would combine the batsmen and bowlers together in a single article. However the introduction of six tall graphs meant that the article would have become very long and I have separated this into two articles. The graphs are also special purpose ones showing the slice plotting of up to 10 players per graph.

The following 5 groups are formed for purposes of determining consistency. For each career-slice of 5-tests, a ratio is formed between that concerned slice's runs/wickets and the career-average runs/wickets for 5 tests. This ratio is called SPF (Slice Performance Factor). Suppose the bowler has captured 17 wickets and his 5-Test career-WpT value is 24, the SPF value is 0.71. If he captured 30 wickets, the SPF is 1.25.

A. SPF  below 0.67:  Well below average - Falls into the inconsistent bracket.
B. SPF 0.67 - 0.90:  Below average
C. SPF 0.90 - 1.10:  Around average
D. SPF 1.10 - 1.33:  Above average
E. SPF  above 1.33:  Well above average - Falls into the inconsistent bracket.
Groups B, C and D are considered to be well within the average levels. Standard Deviation is also used to determine the consistency.

First some data tables. The first one is the core table of bowlers who have captured over 300 wickets in their Test career. The tables and graphs are presented with least comments. Let me allow the erudite readers to come out with their own comments.

BowlerTestsWktsAvgeWpTMeanStdDevMid3%C-SlicesGrp AGrp BGrp CGrp DGrp E
         
Muralitharan M13380022.736.01.000.27474.127451053
Warne S.K14570825.424.91.000.29569.02946955
Kumble A13261929.654.71.000.27574.12737584
McGrath G.D12456321.644.51.000.26672.02535854
Walsh C.A13251924.443.91.010.32870.42738745
Kapil Dev N13143429.653.30.990.39048.12777337
Hadlee R.J8643122.305.01.030.28383.318131022
Pollock S.M10842123.123.91.000.27472.72227544
Wasim Akram10441423.624.00.990.33766.72143653
Harbhajan Singh9840632.224.10.990.26185.02033680
Ambrose C.E.L9840520.994.11.000.28770.02028424
Ntini M10139028.833.91.000.35561.92128236
Botham I.T10238328.403.81.010.42952.42164254
Marshall M.D8137620.954.60.990.29270.61733452
Waqar Younis8737323.564.31.000.43055.61847124
Imran Khan8836222.814.10.980.46455.61851453
Vettori D.L11035833.873.31.000.41068.22246363
Lillee D.K7035523.925.11.000.24371.41422622
Vaas WPUJC11135529.583.21.000.37669.62346463
Donald A.A7233022.254.61.000.22686.71515441
Willis R.G.D9032525.203.61.000.17494.41814670
Lee B7631030.824.11.000.26687.51609232
Gibbs L.R7930929.093.90.990.27568.81633442
Trueman F.S6730721.584.60.990.30071.41424512

To clarify the table contents. WpT mean Wickets per test. Mean is the mean of the SPF values and is close to 1.0 for all bowlers. StdDev is the Standard Deviation for all the SPF values. Mid3% is the % of the Groups B, C and D over the total number of Career Slices, which is the next column: C-Slices. Grp A to Grp E are self-explanatory. The complete file is available for downloading. The link is provided at the end.

Amongst the top wicket-takers, only Hadlee and Harbhajan Singh have the Mid3% values exceeding 80, indicating a high level of consistency. Then comes Donald, with 86% and Willis, with a very high 94%.

Consistency is determined in two ways. The first is statistical. The Standard Deviation (SD) is determined for all the ratios. Low SD values indicate consistent players and high SD values indicate inconsistent players. The usual method of using the Coefficient of Variation is not required since the means for almost all players is around 1.00. Shown below are the SD tables with the low-20 SDs indicating very consistent bowlers.

Full post
The boundary crossers in Tests: an in-depth look

A comprehensive statistical analysis of fours and sixes hit by top batsmen in Tests

In one of my responses I had mentioned that I have to alternate some lighter articles with the heavier ones. This is one of the lighter ones. It still contains information which you cannot get otherwise but I expect that the topic will not elicit hundreds of comments and cross-comments. Quite a bit of this information is available in Cricinfo but not necessarily in this form and order.

Readers might remember that I had elicited help from readers and five of them, viz., Boll, Rameshkumar, Anshu, Ranga and Raghav chipped in magnificently and helped me add balls played data for about 500+ matches. Along with that I was able to derive the fours/sixes information also. This article is dedicated to these five readers. I have given below the summary of the balls played/fours/sixes information in my database.
Total balls data available: 1380 Tests (out of 2036 - 67.7&%)
Continuous information available: 1070-2036 (967 Tests)
1980 - 1987 period: 188 out of 221 Tests.
1877 - 1979 period: 225 out of 867 Tests.
At a pinch I can say that I have complete information available for all the modern greats including Tendulkar, Lara, Steve Waugh et al.

Since there are many tables, the tables are presented with appropriate headers and the comments are provided at the end of the tables. All the tables, barring one, are for batsmen for whom complete balls/fours/sixes information is available. The cut-off is 1500 Test runs since this is a sub-set of top batsmen.

Player career analysis - by % of runs in boundaries

BowlerTestsWktsAvgeWpTMeanStdDevMid3%C-SlicesGrp AGrp BGrp CGrp DGrp E
         
BatsmanLHTeamRuns4s6s46-Runs%
 
Shahid Afridi Pak171622052119269.5%
Flintoff A Eng384551382254466.2%
Gayle C.H~Win637393675419465.8%
Sehwag V Ind8178117488522463.9%
Gibbs H.H Saf616788747383062.1%
Yuvraj Singh~Ind177524719110262.1%
Trescothick M.E~Eng582083042357261.4%
Harbhajan Singh Ind216527140132461.2%
Kaluwitharana R.S Slk19332846117260.6%
Hinds W.W~Win260836816156860.1%
Cairns C.L Nzl332036587198259.7%
Imran Farhat~Pak23273404138459.5%
Kamran Akmal Pak264837214157259.4%
Tamim Iqbal~Bng174824112103659.3%
Gilchrist A.C~Aus5570676100330459.3%
...
...
Taylor M.A~Aus75257299297039.5%
Healy I.A Aus43564225171839.4%
Matthews G.R.J~Aus1849166569437.5%
McCosker R.B Aus1622143359036.4%
Jones A.H Nzl29222458102835.2%

As could be expected, the mercurial Shahid Afridi leads the table of boundary share with 69.5%. This could be partly discounted by the fact that Afridi has scored only 1716 runs. However Flintoff ups the ante with 66.2% out of the 3845 runs he scored. However the real impact is made by Chris Gayle who has scored 65.8% of his 6000+ runs in boundaries. Sehwag has scored over 63% of his 8000+ runs in boundaries. Then comes Gibbs. It is interesting that the three of the top-5 who have scored a lot of runs in boundaries are openers. Harbhajan Singh is a surprise occupant of this space and is the only bowler here. However considering that he has scored more Test runs than Afridi or Srikkanth or Sardesai, his place is well-deserved.

At the other end the usual culprits are there. Stodgy openers like Mark Taylor, McCosker are present here. Jones of New Zealand occupies the last place. Anticipating a question from interested readers, let me say that Chris Tavare just manages to beat Mark Taylor, with 39.9%.

Player career analysis - by number of runs in boundaries

BatsmanLHTeamRuns4s6s4/6-Runs%
        
Tendulkar S.R Ind15470199567838254.2%
Lara B.C~Win11953155988676456.6%
Dravid R Ind13288165521674650.8%
Ponting R.T Aus13196149073639848.5%
Kallis J.H Saf12379137590604048.8%
Sehwag V Ind8178117488522463.9%
Jayawardene M Slk10089119547506250.2%
Sangakkara K.C~Slk9347117829488652.3%
Waugh S.R Aus10927117520482044.1%
Inzamam-ul-Haq Pak8830110548470853.3%
Hayden M.L~Aus8626104682467654.2%
Laxman V.V.S Ind878111355457052.0%
Gooch G.A Eng8900107925446650.2%
Chanderpaul S~Win9709105731441445.5%
Smith G.C~Saf7997102023421852.7%
Gayle C.H~Win637393675419465.8%
Mohammad Yousuf Pak753095651413054.8%
Jayasuriya S.T~Slk697391059399457.3%
Gower D.I~Eng823197910397648.3%
Ganguly S.C~Ind721290057394254.7%

This is just to round off the article. The table lists the batsmen in order of the runs they scored off boundaries. As expected Tendulkar leads the table with 8382 runs in boundaries. Lara has leap-frogged over three batsmen who have scored more runs than him to be in second place with 6764 runs in boundaries. This shows his propensity to essay boundary shots. The next three places are taken by the next three top run-scoring batsmen.

Summary of fours and sixes hit by batsmen

Maximum fours: Tendulkar - 1995 (10.6 fours/Test)
Maximum sixes: Gilchrist -  100 (1.04 sixes/Test)
Average fours per Test (more than 11 fours per Test)
Full post
Batsman by bowler / pitch quality: The final grouping

A study to analyse the careers of Test batsmen by bowling quality and type of pitches

I was about three-fourths into this article when the news about Rahul Dravid's retirement came through. After wiping a tear or two (ok, a lot more), I was tempted to replace this article with a tribute to Dravid. It took me only a minute to dismiss that idea. That is not the way the incomparable Dravid would have planned his innings and I was going to take time, look at all nuances, derive additional facts and figures and build the article, brick by brick. That is the fitting tribute we can give to one of the greats. All these cliches found their true meaning when applied to Dravid. In many other cases, these are but hyperbole.

I have finally arrived at the concluding article on this theme. I am going to classify runs scored by batsmen in the composite group comparing of the Bowling Quality and Pitch type, referred to in my last article. I believe that almost all problems present with the earlier Pitch Quality Index have been taken care of. I will do the classification with a brief introduction and will let the readers digest the same.

I have shown one major table and provided a number of tables for readers to unload and view. For a change let me keep one of my articles brief and to the point.

1. The major benefit is that I have avoided the wide variations which occurred when a single Test was considered and negated the impact of one's own bowlers had. Of course when I do the Innings Ratings analysis, I will re-visit the single Test theme and do what is required based on inputs given by Unni, Arjun, Ali, Gerry et al.

2. The problem of double counting has disappeared. When I look at a batsman's score I slot it into a group based on how easy or difficult run-scoring was, in the concerned location, during the specified period. The bowlers do not get into this at all.

3. A country might have started in one manner but completely changed its character over the years. Pakistan was one of the toughest countries to visit during the early years and over the past decade has completely changed. Compare England twenty and thirty years back. All these variations have been taken care of. Pakistan, during the 1946-1950 period had a PTI ratio value 1.23 while Pakistan's PTI ratio value during the period 2005-2012 is 0.74. England's figures for the two successive periods of 1980s and 1990s are 1.06 and 0.97 respectively.

4. There is no assumption that scoring at home is/was easy and scoring away is/was tough. This facet of the analysis is covered based on hard numbers. In New Zealand scoring was very difficult, often more so for the home team than the visiting teams. This is taken care of.

5. Within one country, there is a clear separation of home teams and visiting teams. So there is no adding of 80 (home) and 60 (visiting) in Australia during the 2000s to arrive at an unsatisfactory 70.

6. Within the same country group, batsmen runs are further classified based on the bowling quality. Example, Laxman's 167 in 2000 goes into the combined group 8 (Pitch-3 & BowQ-5) while Laxman's own 148, four years later goes into combined group of 7 (Pitch-3 & BowQ-4).

7. There is no grouping based on absolute values. Rather it is based on a true peer comparison basis and is only a dimension-less ratio. Changes over the various eras will be reflected correctly. This is peer comparison at its best. Same era and across countries.

8. One good point is that many teams starting in Test cricket have had a tough time, even while playing at home. The runs scored by the batsmen from these teams get recognition of the tougher conditions faced by them.

9. Readers can argue that I could have taken 15 time periods instead of 9. Possible. Readers can also argue that I could have taken the top-7 scores. Granted. However there is no end to these suggestions. These periods reflect distinct eras and have sufficient Tests played during each period to have a very sound basis.

10. Finally a quick perusal at the tables will indicate that the sharp differences which existed in the earlier analysis have now gone since the base has moved from a single Test to a period/country combination. There are some intriguing changes. It is now clear that the objections put forward by Unni, Ali and couple of other readers were quite valid. Some players, indeed, benefited by their bowlers' quality, very significantly. Look at the revised tables. The West Indian pitches during 1970-80 were good to bat on, at least for the home team. They were averaging 75.0 (all-teams 67.7) and 72.2 (all-teams 63.3) and batsmen like Richards scored a fair bit of runs at home. And they rarely faced a Group 5 bowling attack. Many thanks to all these readers.

First, the grouping methodology for the Pitch Type Index. The Pitch Type Index is the ratio between the Home/Visiting Top-7 Partnership average for the period/country and the Home/Visiting Top-7 Partnership average for the period/all-countries. A ratio of greater than 1.0 indicates tough situations and ratio below 1.00 indicates easier batting situations. I will not cover this in any greater detail. Details are available in the previous article, link provided here.

PTI-Home groupings: Total - 2022 innings (The 12 neutral Tests have no home teams)
PTI value of 1.15 - 1.50 : PTI Group 5    238 (11.7%)
PTI value of 1.04 - 1.15 : PTI Group 4    432 (21.2%)
PTI value of 0.93 - 1.04 : PTI Group 3    745 (36.6%)
PTI value of 0.88 - 0.93 : PTI Group 2    406 (20.0%)
PTI value of 0.70 - 0.88 : PTI Group 1    201 ( 9.9%)
PTI-Away groupings: Total - 2034 innings
PTI value of 1.09 - 1.50 : PTI Group 5    198 ( 9.7%)
PTI value of 1.06 - 1.09 : PTI Group 4    441 (21.7%)
PTI value of 0.94 - 1.06 : PTI Group 3    731 (35.9%)
PTI value of 0.89 - 0.94 : PTI Group 2    456 (22.4%)
PTI value of 0.70 - 0.89 : PTI Group 1    208 (10.2%)
Full post
Tests - Pitch type analysis: The final solution ???

A detailed statistical analysis of the quality and type of pitches in each host country

Finally I think I have found the solution to the vexed problem of how to handle the two very important factors faced by the batsmen. I am referring to the Bowler quality and Pitch type. These two are non-contextual in nature inasmuch as these are not influenced too much by the match conditions. I will briefly explain what has been done over the past 8 months in this blogspace. This will serve both as a recap and an introduction.

First the Bowling quality faced. I started with something simple and, with hundreds of wonderful responses from readers, I can confidently say that we have got almost close to what is ultimately needed. A brief summary of what is the final capsule is given below.

1. BQI to be done based on actual bowlers who bowled. This will take care of situations such as Imran playing as a batsman.
2. Use the reciprocal weighting method, as suggested by Arjun. This takes away the excess dilution of the bowling quality by weaker bowlers.
3. Use career-to-date bowling average at the beginning of the concerned Test, with special methods to handle the initial Tests.
4. Use the appropriate home or away c-t-d bowling average depending on where the Test is being played. There was a clear consensus on these two methods.
5. Incorporate recent form of bowlers.

These have made the BQI (Bowling Quality Index) a very powerful and effective method of valuing runs scored.

Now for the Pitch Type methodology.

I had done this earlier as a post-match determination. At that time I was not comfortable with using a Pitch type measure using previous Tests in the concerned location. I was swayed by the wide variations which happened in Tests in locations like Hamilton, Leeds, Kingston, Chennai et al. I was quite unsure of the whole methodology and this was reflected in the analysis. However at least I got the measure used correctly, after a number of trials. This was the top-7/10 partnerships in the match. This was suggested by Arjun. This worked very well since this encapsulated about 15 batsmen performances.

However this single-match post match methodology had some basic problems, as effectively pointed out by Unni and Ali. There was the double counting of bowler performances. Batsmen in strong-bowling teams benefited since their own bowlers kept the other team's runs and this, in turn, benefited the batsmen by making the match tilt towards a bowling one. I even have a complicated antidote to this problem sent by Unni.

So I set out to correct this. Using the single match lends itself to many varying situations, not all of which can be foreseen. So I have decided not to proceed on the single match basis. This article covers the revised work on Pitch type. I am sure the readers will find this more acceptable. In the next article I will look at the batsmen runs, adjusted by the BQI and revised Pitch type index.

I decided that I HAD to look at the history in detail. Couple of readers had also indicated that I must look at historic data and use the same to get an insight on the pitch type. So I put in some hard yards (or kilometres) in this area.

First I looked at the grounds. Easy to get discouraged. Over 100 grounds in which the 2000+ tests have been played. Only three grounds have had over 100 Tests played. This is less than a Test per year. Only 11 grounds have had over 50 Tests played there. And to top it all, there are 57 grounds in which fewer than ten Tests played. How do I get a handle on a pattern. I set myself a minimum target of ten Tests and in some important grounds like Bangalore, this required a period coverage of 17 years. Even five Tests in Bangalore took seven years. After a few fruitless days, I realized that proper ground analysis can only be done for about ten grounds and two countries, viz., Australia and England. They have settled patterns for playing Test cricket, playing regularly on core grounds. So the ground option was a non-starter.

I was getting nowhere. Suddenly I thought, "why grounds, why not countries". I first thought of the objections. Different types of grounds. Different levels of assistance. Flat tracks and dust bowls in the same country. But I realized that, these could all be handled if I followed my instinct and set time frames suitably. I briefly toyed with, and discarded, taking fixed numbers of Tests for each country. This evened the distribution very well. However it did not allow me to introduce the, almost mandatory, peer comparisons across grounds/countries. The similar numbers required varying number of non-overlapping years. So I went back to my tried and trusted period method which I had earlier used for the Test analysis - across ages.

This has worked very well. I have given the salient points below.

1. There are nine periods in all. As expected, the first two cover 50 years because of the sparse nature of Test series then. These periods reflect clear trends in Tests over the long period of 14 decades.

2. For each period, by Test, the top-7 partnership averages are determined, that too for the two teams independently.

3. A very important distinction is made between the Home team's top-7 averages and Visiting team's top-7 averages. This separation has completely changed and strengthened the methodology. In general, the home team's numbers are better than the visiting team's numbers (barring countries like Bangladesh and, surprisingly, New Zealand) and these varying numbers are not mixed up together.

4. These home and visiting numbers for each country are compared to the period values for home and visiting teams across all countries. This ratio, which ranges from 0.72 to 1.50, gives a clear indication as to the relative weight of the runs scored. This is the cornerstone of this analysis. I will decide later how this range can be implemented: as a continuous ratio or in the group methodology. Readers can now understand the importance of keeping the time periods across all countries same.

5. A special note is needed for a few situations. Bangladesh: The seven Tests played during 1950s-60s are treated as home Tests for Pakistan. The one Test played during 1999 between Sri Lanka and Pakistan is treated as neutral and visiting status is accorded for both. A similar treatment is done for the 12 Tests played in UAE and both teams in each of these Tests are accorded visiting team status. This is the case for some of the 1912 Triangular series matches. In these cases, instead of the top-7, the top-10 partnerships are taken since all four innings fall into the "visiting" group.

6. Readers would know how much of an importance peer comparisons are given in this blogspace. This method of working is peer comparisons at its best. Let us not forget that we are looking at the pitch characteristics, and nothing else. A player's x runs scored in a specific country, during s specific period of time, is adjusted by a ratio between the home or visiting batsmen average in that country and home or visiting batsmen for the whole cricket world.

7. It can be seen that the problem of double counting has disappeared. Let me take the example of Lara which was used often earlier. The problem was that Lara benefited from the quality of his bowlers dismissing the opponents for low scores. Now Lara's own bowlers do not get into the picture at all. He would be evaluated by how he and his fellow West Indian batsmen performed at home as against the peer batsmen playing at their respective homes. And similarly for away batting.

8. It must be clearly understood that bowling quality faced by batsmen still is a very important measure. When Clarke scored 151 against Australia in 2004, these runs would be treated almost at par as far as Pitch type are concerned since scoring runs for visiting batsmen in India was almost the same as the world figure (65.4 against period average of 65.8). However this was against a very potent Group-5 level Indian attack and he would get substantial credit for this. This would apply to many an innings against Australia in Australia.

9. Arguments will be raised in favour of incorporating the first/second innings separation. The problem is that if I go with both home/visiting and first/second innings separation, there would be four numbers per match and the whole process will be diluted. The lower partnerships would be very small. And I am loathe to take the first/second innings separation, without considering the home/visiting teams since that will add the stronger and weaker teams in a match and work out an average: a process I am not comfortable with.

Let me take the 1980-89 period. It will be obvious that run scoring in New Zealand, for the home team, which has a home-T7 average of 60.1, was more difficult than run scoring, for the home team, Pakistan, which has a home-T7 average of 71.4. This is taken care by the ratio between the respective home-T7 averages and across-countries home-T7 average of 66.3. So Wright's 130, scored at Eden Park during 1984 will have a weight upwards and Zaheer Abbas's 168 at Lahore during 1984 will be weighed downwards.

Now let me take the 2006-12 period. It will be obvious that run scoring, for the teams visiting Sri Lanka, which has a visiting-T7 average of 62.2, was more difficult than run scoring for the teams visiting India, which has a visiting-T7 average of 72.0. This is taken care by the ratio between the respective visiting-T7 averages and across-countries visiting-T7 average of 68.4. So North's 128 in Bangalore during 2010 will be valued at a lower level and Shaun Marsh's 141 in Colombo during 2011 will be valued at higher level.

In this analysis, it must always be remembered that, because the ratio is a run multiplying factor, sub-1.00 ratios indicate easier batting conditions and ratios above 1.00 indicate tougher batting conditions. I will later use these numbers to do a bowler analysis also. This will come out very well since the elements of playing at home or away are automatically incorporated.

I suggest readers read the above couple of times to understand the methodology fully before moving on to the tables. These are organized by period and country. In view of the number of tables there are only minimum of comments.

Period : 1877-1914

PeriodCountryTestsHome TeamHomeVisiting TeamVisiting
T7-PS-AvgeIndexT7-PS-AvgeIndex
1877-1914Australia5756.90.9055.80.92
1877-1914England5150.21.0244.71.14
1877-1914South Africa2641.61.2352.80.97
  13451.41.0051.11.00

A somewhat lower scoring period. However that does not matter since we are using a ratio and a peer comparison. Scoring home runs against Australia was easier than doing so in England. A similar trend for the visiting batsmen.

Period : 1920-1939

PeriodCountryTestsHome TeamHomeVisiting TeamVisiting
T7-PS-AvgeIndexT7-PS-AvgeIndex
       
1920-1939Australia3578.90.9062.31.03
1920-1939England5875.70.9360.51.05
1920-1939India364.91.0965.80.97
1920-1939New Zealand852.81.3471.00.90
1920-1939South Africa2858.81.2069.20.92
1920-1939West Indies864.41.1069.10.92
  14070.71.0063.81.00

The averages increased dramatically with the arrival of the big scoring batsmen. England eased somewhat for the home batsmen. And the visiting batsmen did well.

Period : 1946-1959

PeriodCountryTestsHome TeamHomeVisiting TeamVisiting
T7-PS-AvgeIndexT7-PS-AvgeIndex
       
1946-1959Australia3566.10.9355.21.09
1946-1959England6464.30.9555.41.09
1946-1959India3063.00.9769.00.87
1946-1959New Zealand1637.11.50*61.30.98
1946-1959Pakistan1549.91.2342.91.41
1946-1959South Africa2552.01.1859.61.01
1946-1959West Indies2478.90.7882.70.73
  20961.31.0060.41.00

The post-war period saw a drop in averages. The new Zealanders found it very difficult to score in their backyard as did Pakistan and South African batsmen. Visitors to Pakistan had it really tough. West Indies was a feather-bed for all batsmen

Period : 1960-69

PeriodCountryTestsHome TeamHomeVisiting TeamVisiting
T7-PS-AvgeIndexT7-PS-AvgeIndex
       
1960-1969Australia3075.50.8668.50.91
1960-1969England5364.31.0157.01.09
1960-1969India3661.21.0665.60.95
1960-1969New Zealand1949.11.3259.51.05
1960-1969Pakistan1359.61.0959.91.04
1960-1969South Africa1568.30.9560.71.03
1960-1969West Indies2074.90.8766.70.93
  18665.01.0062.31.00

Australia eased considerably for all batsmen. The Indian batsmen found their home scoring touch.

Period : 1970-79

PeriodCountryTestsHome TeamHomeVisiting TeamVisiting
T7-PS-AvgeIndexT7-PS-AvgeIndex
       
1970-1979Australia4467.21.0162.81.02
1970-1979England4765.01.0461.21.05
1970-1979India3463.81.0659.41.08
1970-1979New Zealand2157.81.1770.30.91
1970-1979Pakistan1482.90.8267.40.95
1970-1979South Africa478.80.8647.41.35
1970-1979West Indies3475.00.9071.00.90
  19867.71.0064.01.00

Pakistan changed dramatically for their own batsmen. With the advent of quality spinners, batting in India was not that easy. Both Australia and England became slightly more easy for the batsmen.

Period : 1980-89

PeriodCountryTestsHome TeamHomeVisiting TeamVisiting
T7-PS-AvgeIndexT7-PS-AvgeIndex
       
1980-1989Australia5465.81.0166.00.94
1980-1989England5762.81.0667.00.92
1980-1989India4270.60.9461.41.01
1980-1989New Zealand2860.11.1057.81.07
1980-1989Pakistan4371.40.9356.51.10
1980-1989Sri Lanka1255.41.2057.11.08
1980-1989West Indies3072.20.9258.81.05
  26666.31.0061.91.00

Look at the change in West Indies for the visiting batsmen. To be expected with the advent of the great fast men. England struggled at home.

Period : 1990-1998

PeriodCountryTestsHome TeamHomeVisiting TeamVisiting
T7-PS-AvgeIndexT7-PS-AvgeIndex
       
1990-1998Australia5070.20.9555.71.09
1990-1998England5368.50.9769.10.88
1990-1998India2474.80.8956.71.07
1990-1998New Zealand3462.81.0668.40.89
1990-1998Pakistan3361.61.0856.61.07
1990-1998South Africa3062.21.0754.31.12
1990-1998Sri Lanka2667.50.9862.50.97
1990-1998West Indies3765.01.0258.51.03
1990-1998Zimbabwe1763.71.0459.81.01
  30466.41.0060.61.00

England became a much better country for all batsmen. Pakistan became tougher for all. Travelling to West Indies and Australia was becoming easier.

Period : 1999-2004

PeriodCountryTestsHome TeamHomeVisiting TeamVisiting
T7-PS-AvgeIndexT7-PS-AvgeIndex
       
1999-2004Australia3884.50.8162.91.04
1999-2004Bangladesh1642.21.50*80.70.81
1999-2004England3969.50.9970.40.93
1999-2004India2971.90.9665.41.00
1999-2004New Zealand2565.31.0568.50.96
1999-2004Pakistan1967.61.0268.00.96
1999-2004South Africa3176.90.8957.21.14
1999-2004Sri Lanka3671.60.9659.41.10
1999-2004West Indies3362.91.0964.91.01
1999-2004Zimbabwe2357.91.1971.90.91
1999-2004UAE40.00.0065.90.99
  29368.81.0065.61.00

Look at Australia's home average and visiting average. That is one of the biggest differences we have ever had.

Period : 2005-2012

PeriodCountryTestsHome TeamHomeVisiting TeamVisiting
T7-PS-AvgeIndexT7-PS-AvgeIndex
       
2005-2012Australia4180.00.9262.71.06
2005-2012Bangladesh2258.31.2780.40.83
2005-2012England5077.20.9662.61.07
2005-2012India3484.90.8771.70.93
2005-2012New Zealand2964.51.1566.51.01
2005-2012Pakistan13100.10.7485.10.78
2005-2012South Africa3970.21.0561.01.09
2005-2012Sri Lanka3177.90.9558.71.14
2005-2012West Indies3065.21.1372.70.93
2005-2012Zimbabwe754.91.3571.00.94
2005-2012UAE80.00.0077.10.87
  30473.91.0067.11.00

The last period sees a narrowing of the Australian figures. India and Pakistan became big scoring countries for all batsmen. The only Top-7 partnerships average exceeding 100 happened in Pakistan. Sri Lanka showed a wide variation between home batsmen and visiting batsmen.

Home Top-7 partnership averages: by country

Home T7-PsAvg187719201946196019701980199019992005All
Country191419391959196919791989199820042012Tests
           
Australia0.900.900.930.861.011.010.950.810.920.95
Bangladesh       1.631.271.29
England1.020.930.951.011.041.060.970.990.961.00
India 1.090.971.061.060.940.890.960.870.96
New Zealand 1.341.651.321.171.101.061.051.151.15
Pakistan  1.231.090.820.931.081.020.740.97
South Africa1.231.201.180.950.86 1.070.891.051.07
Sri Lanka     1.200.980.960.950.95
West Indies 1.100.780.870.900.921.021.091.130.96
Zimbabwe      1.041.191.351.12

Now for a graphical representation of how the numbers have stacked up, by country. Please remember that the lower part of the graph indicates that run scoring was on the easier side while the top half represents tougher run scoring conditions.

Top-seven partnership averages of home batsmen over the years © Anantha Narayanan

Most countries, barring Australia and England, have found it tough during their first period, even in their own countries. Pakistan seems to have wild swings. England seems to have the most stable of countries for the home batsmen. Barring a period or two, Australia have found their own backyard very comfortable.

Visiting Top-7 partnership averages: by country

Visiting T7-PsAvg187719201946196019701980199019992005All
Country191419391959196919791989199820042012Tests
           
Australia0.921.031.090.911.020.941.091.051.071.03
Bangladesh       0.820.840.78
England1.141.051.091.091.050.920.880.931.081.03
India 0.970.870.951.081.011.071.010.940.97
New Zealand 0.900.981.050.911.070.890.961.010.96
Pakistan  1.411.040.951.101.070.970.791.04
South Africa0.970.921.011.031.35 1.121.151.101.06
Sri Lanka     1.080.971.111.151.05
West Indies 0.920.730.930.901.051.031.010.930.93
Zimbabwe      1.010.920.950.93


Top-seven partnership averages of visiting teams over the years © Anantha Narayanan

It was indeed very tough for the visiting batsmen to travel to Pakistan during the initial periods. South Africa, during the 1970s was similar. England was somewhat tough during the early stages bot eased off somewhat recently.India has almost always been a reasonably easy place to visit. Look at Australia over the past 15 years: not too easy a place to tour.

I will have a follow-up article like my previous one, grouping batsman scores against a combination of the BQI and the new PTI (this article). I will use the same groups methodology. 5 for BQI, already explained. And 5 for PTI, suitably allocated depending on the distribution of 150+ values.

Full post
ODIs: a blue-print for the future

A list of ideas and suggestions to improve ODIs and their structure

In response to one of my recent articles there were quite a few comments on the ODI game and steps to be taken to improve and strengthen the same. This article is a summary encompassing the readers' suggestions and adding my own.

The article is in two parts. The first one deals with ways of strengthening the ODI matches through match-level changes. The second part concentrates on strengthening the game format.

Suggestions on ODI match-level changes


1. Two bowlers being allowed to bowl 12 overs each. This will tilt the scales a little bit in favour of the bowlers. Teams will be tempted to play four top bowlers since only six overs need to be bowled by the fifth bowler. It should be remembered that the 20% is not sacrosanct. Even now the bowlers might bowl above 20% in a few situations: rain affected matches and innings which do not go the full extent of 50 overs. It would be great to see Dale Steyn and Vernon Philander get the four extra overs since the batsmen have to plan for this eventuality.

This is needed because of recent rule changes like free-hits, marginal wides, one bouncer per over, Power Plays etc which are all in favour of the batsmen. There is a need to level the playing field a bit. Let me add that this suggestion has not been caused by the fact that batsmen can play a higher share of team balls. It is true only in single innings. However, over the entire career, there is no great difference in the % of balls bowed/faced by batsmen/bowlers. The following tables are interesting.

Batsman        TeamBalls BatBalls % faced
Marsh G.R 32370 7721 23.85 Greenidge C.G 34875 7908 22.68 Haynes 63324 13707 21.65 ... Tendulkar 120096 21073 17.55 Ponting 98998 17010 17.18
Full post
ODIs during 2011: an alternate look

A detailed analysis of team and individual performances in ODIs in 2011

This follows the review of the 2011 Tests. This will mostly be on Teams and important measures during the year, the 5-years before 2011 and the 40 years before. I will not do any individual innings listings since people immediately come out with objections and we lose the thread. All of us get side-tracked.

First a single paragraph each on the batting, bowling and team performances of 2011.


The historic innings of the year was Virender Sehwag's 219. After all, a world record score was overtaken. If Sehwag had played on till the end of innings, maybe 250 would have been crossed. The most powerful batting display was by Shane Watson during his 185 (in 96 balls) against Bangladesh. 150 runs in boundaries tells the story. If Bangladesh had scored another 30 runs he would have been the batsman to overtake Sachin Tendulkar. The most significant innings of the year was Gautam Gambhir's 97. Without that there was no win for India. MS Dhoni played an equally important innings but Gambhir's was more significant. 31 for 2 was a potentially losing situation while 114 for 3 was at least on an even keel. The poignant innings of the year were the two centuries by two great batsmen in their last World Cup matches. That they both lost the battle to India's fighting skills adds to the poignancy. I refer to Ricky Ponting and Mahela Jayawardene.

This was not a great year for bowling performances. Probably the most significant was Wahab Riaz's five wicket haul in the WC semi-final. Four of these were those of top order batsmen. He did his task admirably but his batsmen let him down. An equally good performance was that of Woakes who captured 6 wickets against Australia. The only Indian bowler to capture 5 wickets was Yuvraj Singh, remembering to say our prayers for his speedy recovery and to wear the blue jersey again, against Ireland: an important effort in a tight match. However the bowler of the year was Shahid Afridi who had four 5-wicket hauls, followed by Lasith Malinga, with three.

In my anxiety to do as little of individual performances as possible, I missed, inarguably, the individual performance of the year. It required Boll, an Australian, to point out this lapse. My apologies to Yuvraj and all his supporters. I had referred to him only in passing re the 5-wkt haul against Ireland. Yuvraj's 350+ runs and 15 wickets during the World Cup was the most outstabding individual performance of the year and couple of years before and possibly after. Thanks, Boll.

The above are partly subjective and the readers are welcome to come out with their significant performances.

India were the deserving WC winners. They were the most resilient and balanced of all teams. In all three knock-out matches there were many moments when they looked like slipping but the hour cometh and the men cometh. Almost all the players contributed. That week in spring, India was the team and held their nerve to win a deserved WC. The rest of the year was not so great but the WC win was very well-earned. India had done this on-the-brink performances three times during 2011, chronicled elsewhere. As readers are aware of, I am the last person to blindly support India, but deserved credit must be given whole-heartedly where it is due, for the very significant performances during those six weeks in 2011.

As single matches go, the Sri Lankan demolition of England by 10 wickets in the WC quarter-final and Australia's blitz, led by Watson, at 8-plus runs per over against Bangladesh were the most devastating of the year. As far as the match of the year is concerned there were a few 300s chased comfortably, 200s chased with difficulty, sub-200 totals defended and so on. However the match of the year has to be Ireland's brave and successful chase of England's 300-plus total. Thinking of this match, looks like the collective brains of the IPL franchisees were left behind outside the hotel. How else can anyone explain no one picking up Kevin O'Brien for 50000 dollars?

1. A look at performance of teams during 2011 (with and without weight for WC)

TeamODIsWonNRLostMaxPtsTeam PtsPerformance %WCPtsPerf % (incl WC)
 
Pakistan3224176452.081.3%284.4%
India34213106843.263.5%1078.2%
Australia2518165037.474.8%176.8%
South Africa159063017.658.7%162.0%
New Zealand179173419.055.9%261.8%
Sri Lanka28142125628.851.4%560.4%
England30113166024.240.3%142.0%
West Indies28101175621.037.5%139.3%
Zimbabwe1760113411.232.9%032.9%
Ireland12408247.631.7%031.7%
Scotland4301205.829.0%029.0%
Bangladesh2060144011.629.0%029.0%
Afghanistan2200204.422.0%022.0%
Netherlands10208203.618.0%018.0%
Canada10109202.010.0%010.0%
Kenya8008200.00.0%00.0%

This is the traditional 2-1-0 method of evaluating team performance. I have done this to provide a complete analysis. There is no weight for WC matches in the first analysis segment. I have used the 2-1-0 values for the neutral matches and weighed the home matches down by 10% and the away matches upwards by 10%. The relative strengths of the teams is not taken into account since the complexity is not worth it. If I were to do a complete Team Ratings work then the team strengths will come into the equation.

Pakistan were the best team by a mile, with a performance measure of 81.3%. They had a great year despite playing ALL their matches away from home. They compiled an excellent record of 75% wins. Australia were nearly as good, winning 18 of their 25 matches. Their performance measure was a very creditable 74.8%. India were just about average, clocking in at 63.5%. A quixotic scheduling meant that India played their last 20 matches against West Indies and England compiling a not-so-great 12-2-6 record. South Africa was below average with 58.7%. New Zealand and Sri Lanka got a 50-plus value. England and West Indies were below-par, clocking at below 50%.

The additional evaluation is the more relevant table in that the World Cup results are incorporated. After all the World Cup is a quadrennial event and is the most important event in cricketing calendar. World Cup wins have to be recognized. I have used a simple methodology. I have added 10/5/2/1 points respectively to the winner/runner-up/losing semi-finalists/losing quarter-finalists. This seems very fair and recognizes the importance of World Cup performances. May be subjective, but no one should have any complaints. Anyhow if a reader wants, he can put in his own weight for the World Cup and re-do the tables. India's win, and the 10 points they secured, pushed them into the second place, ahead of Australia. Pakistan's overall performance was so good that they managed to retain their top place. On balance, I would place Pakistan and India as the teams of the year. Pakistan had a great year and India won the World Cup. How I wish these two teams revive their wonderful rivalry: if required, on the desert grounds, hopefully with an aura of brotherhood than acrimony (Sriram's words).

Now for a series of tables analysing key figures for the teams. This would give us a good insight into why certain teams performed very well. Remember that Pakistan, India and Australia are the top three teams. Sri Lanka, despite their WC Final, had a very indifferent year. First a composite table looking at RpO (Runs per Over), RpW (Runs per Wicket) and BpW (Balls per Wicket) values.

2. Comparisons of own and other teams' RpO, RpW and BpW

TeamRpO  RpW  BpW  
 ForVsDiffForVsDiffForVsDiff
 
Australia5.474.910.5637.728.19.634.341.47.0
New Zealand5.464.990.4738.127.111.032.641.89.3
Pakistan4.874.500.3731.624.27.332.338.96.6
India5.515.170.3435.929.66.334.339.04.7
Sri Lanka5.044.830.2131.427.34.233.837.43.6
Ireland5.325.110.2128.031.3-3.336.731.5-5.2
England5.415.52-0.1130.336.0-5.739.133.6-5.5
West Indies4.844.98-0.1428.730.9-2.237.235.5-1.7
Zimbabwe4.785.02-0.2428.538.7-10.246.235.8-10.4
Bangladesh4.395.06-0.6624.331.9-7.637.833.1-4.7
Netherlands4.465.29-0.8322.342.2-19.947.930.0-17.9
Canada4.275.76-1.5019.433.2-13.834.527.3-7.2
Below 10 ODIs         
Afghanistan6.085.600.4820.219.11.120.519.9-0.6
Scotland4.945.15-0.2131.130.11.035.137.92.7
Kenya3.935.66-1.7318.444.9-26.547.628.1-19.5

First the RpO values. I have considered this as more important than the RpW and BpW figures since this is what ultimately leads to an ODI win. The table is ordered on the RpO differential. Australia leads the table with a healthy RpO differential of 0.56. This has led to their excellent 75% performance. New Zealand were next with 0.47. Their overall numbers are quite good and it is surprising that they do not have better results. Pakistan has a slightly lower RpO differential of 0.37. However it must be noted that this figure is on somewhat lower RpO values, they having played many matches with lower average scores. Their differential is 7.6% as against New Zealand's 8.6%. India has a RpO differential of 0.34. Sri Lanka and Ireland have the same RpO differential of 0.21, indicating the great year Ireland had. As expected England and West Indies have negative RpO differentials.

The other comparison I have made is between own RpW and RpW. The RpW differentials show similar weights as the RpO differentials. New Zealand leads with a differential of 11.6 and Australia and Pakistan follow with 9.6 and 7.3 respectively. This is repeated in the BpW figures. New Zealand again leads with 9.3 and Australia and Pakistan follow with 7.0 and 6.6.

3. Analysis of boundaries hit

TeamODIsTeam Runs4s hit4s/match6s hit6s/match4s6s %
 
Ireland12274125321.1494.147.60%
Zimbabwe17379235020.6533.145.30%
West Indies28601744115.81475.244.00%
New Zealand17369129817.5724.244.00%
Canada10180515515.5282.843.70%
Australia25577448419.4913.643.00%
India34846273721.71133.342.90%
Netherlands10198715715.7323.241.30%
Pakistan32653355217.2752.340.70%
Sri Lanka28609653819.2521.940.40%
England30697756718.9692.338.40%
Bangladesh20376030615.3291.437.20%
South Africa15363428018.7372.536.90%
Below 10 ODIs       
Afghanistan23632914.5136.553.40%
Scotland48416015143.538.50%
Kenya8132410312.9151.937.90%

This is an analysis of the boundaries hit by teams during 2011. At the end I have compared all these key measures for the year 2011, the previous decade and the 40-year period. Those values can be compare to these. This table is ordered by boundaries as % of team runs.

We are again in for a surprise. Ireland leads the table having hit 47.6% of their team runs in boundaries. The second is another surprise. Zimbabwe clocks with 45.3%. The surprises continue with West Indies and New Zealand at 44.0% and Canada with 43.7%. Then come the big guns. Australia has cored 43.7% and India and Pakistan have both got above 40%. What is South Africa doing at the lower reaches of the table at 36.9%.

There are two other minor measures. The fours per match and sixes per match. India leads the fours measure with 21.7 and Ireland closely follows with 21.1 and Zimbabwe with 20.6. These are the only teams clocking above 20. West Indies lead the sixes column with 5.7 per match. They, led by Gayle, Pollard and Russell crossed the ropes a huge 147 times. New Zealand and Ireland follow next with 4.2 and 4.1. Sri Lanka's lack of heavy hitters is shown by the relatively low 1.9 per match.

4. Analysis of Extras conceded and Maidens bowled

TeamODIsVsRunsExtrasExtras/300ballsOversMaidensMaidens %
 
India3479532258.51537.4674.36%
Canada102522738.7437.3163.66%
Netherlands102450738.9463.2204.32%
Bangladesh2042371309.2838.0465.49%
Ireland122846909.5557.1193.41%
Zimbabwe17382813410.5762.0334.33%
New Zealand17360112710.6721.5324.43%
South Africa15282510411.0619.0315.01%
West Indies28571321211.11148.2443.83%
England30752227911.11361.4543.97%
Sri Lanka28553221711.81145.1585.06%
Australia25559925613.71139.1363.16%
Pakistan32603131315.61340.1886.57%
Below 10 ODIs       
Afghanistan2363119.164.523.08%
Scotland41024236.7199.084.02%
Kenya8175111820.2309.1165.18%

This is an analysis of the teams' performances on field. Two measures have been analyzed. The first is a look at the extras conceded by the team. To be consistent with the overall summary analysis, I have determined the number of Extras conceded by the team per 300 balls, the expected innings size. India has shown that they are the most disciplined bowling attack and wicket-keeping competency with a low Extras per 300 balls of 8.5. Then come a series of lower-tiered teams with Extras per 300 balls values of 10 or less. The lower half of the teams has the more fancied teams. The last two places are occupied by Australia and Pakistan, with 13.7 and 15.6 extras per 300 balls. Pakistan's lack of discipline might very well be intentional. Readers would remember the instructions Imran gave to Wasim Akram in 1992. Go for the wickets: don't bother about the extras.

On the right hand side of the table I have the maidens bowled and what % these comprise out of the overs bowled by the team. Pakistan is the leader with 6.57% of their overs as maidens: worked out an average of more than 3 maidens per match. Bangladesh, with their accurate spinners, come in next with 5.5%. Sri Lanka, with a similar bowling combination, is next with around 5.1%. South Africa has a maidens % above 5. Amongst the top teams, Australia has the lowest maidens % of 3.16%. Maybe their attacking field placements or the pace-dominant attacks.

5. An analysis of wins achieved by Teams during 2011

TeamWins in 2011VeryCloseClose winsEasy winsHuge wins Batting firstChasing
 
Pakistan2425141 1113
India2132142 813
Australia1812140 810
Sri Lanka140174 86
England111531 65
West Indies101142 55
South Africa90144 72
New Zealand90131 45
Zimbabwe62112 33
Bangladesh62040 24
Ireland40121 22
Netherlands21100 02
Canada10010 01
Below 10 ODIs        
Kenya00000 00
Scotland20120 12
Afghanistan21100 11

This table analyses the wins achieved by the teams. The table is ordered by the number of wins. First the split between wins batting first and chasing. Both Pakistan and India have chased 13 times successfully, although this is higher proportion of India's 21 wins, as against Pakistan's 24. South Africa, probably with their excellent bowling attack, have successfully defended nearly 80% of the times. Australia have been equally successful whether they were defending or chasing.

The last section is an analysis of the wins by the type of wins. There are four classifications: Very Close, Close, Easy and Thumping. India has had 3 very close wins. The one-run win over South Africa, two-wicket win over South Africa and one-wicket win over West Indies. Sri Lanka and South Africa have won four of their matches by a mile.

6. A few important measures compared

Measure20112006-10All-ODIs
 
Matches1467693234
Runs per over4.754.654.37
Runs per wicket28.227.927.4
Balls per wicket35.636.037.6
4s per match36.437.335.4
6s per match6.095.864.95
Boundary runs as %43.045.643.0
% Inns >= 3005.410.26.7
% Inns <= 1002.83.43.8
Opening Ptshp Avge35.036.935.0
% OP >= 1008.77.07.2
% OP <= 10 31.131.628.8
Extras/300 balls14.916.516.9

Now for a look at various measures for 2011, the preceding five years and the 41 year period.

The Runs per Over values for 2011 are almost the same as the previous five years and slightly above the historic levels. With the way the laws are formed against the bowlers it is a miracle that the average RpO has reached 5.0.

The three Runs per Wicket numbers are almost comparable. The differences are very minimal.

The Balls per Wicket are the same as for the previous five years and are slightly lower than the historic figure.

The 4s per match and 6s per match both showed a marginal decrease/increase from the previous half-decade. Similarly the Boundary % of runs showed a slight decline. It looks as if the trend set during the later half of the 2000s decade will be maintained.

There is a slight increase in 300-plus innings, just above 11%, to previous half-decade and significant increase to the overall figure. I get the feeling we have now settled into a once in 9/10 innings situation. Also 6 of these 300-plus innings were chased down and one equalled (India-England). Surprisingly there is a significant increase in the sub-100 innings. And let me also say that not all these have been the so called minnows. Experienced teams are caught in situations, out of the blue and get dismissed for below 100.

The Opening partnerships in Tests showed a 20% drop from the previous decade and overall figures. Surprisingly the opening partnerships in ODIs seems to have maintained an upward trend: 36.9 against 34.3 for 2006-2010. I guess the runs keep coming because of the attacking fields. The sub-10 opening partnerships are almost at static levels. There has also been a steady increase in the 100-plus opening partnerships. A strong reason could be the Powerplay rule changes.

There was a continuing drop in the Extras per 300 balls from 16.9 to 14.9. As I have already mentioned this must be due to the severe handling of No balls. The No-balls incidence has gone down from 1.9 to 0.9. The other three forms of extras are very slightly down.

Over the next month or so I intend to compile all the reader ideas submitted and come out with a blueprint for the ODI game. Let me see if I can persuade ESPNcricinfo to forward the same to ICC. Surely the ODI game cannot survive in this bloated format.

Anand has pointed to a gem. India were at the receiving end of four 5-wkt hauls during the World Cup 2011. I have checked this out, but this could very well be a record in a WC. The bowlers were Wahab Riaz, Rampaul, Steyn and Bresnan. He has also suggested Steyn's 5-wkt haul as a memorable bowling performance.

Full post
Tests during 2011: an alternate look

An analytical look at individual and team performances in Test cricket played in 2011

This review of the year should have come out a few weeks earlier. However I was caught up in completing the series of articles on Bowling and Pitch quality and hence this slight delay. Anyhow the year is still fresh in our memory and here we go. I also do not want to hear the words Bowling/Pitch quality for a month or so.

1. A look at performance of teams during 2011

TeamTestsHomeNeutralAwayHomeNeutralAwayHomeNeutralAwayPerformance
  WinsWinsWinsDrawsDrawsDrawsLossesLossesLosses%
England850120000081.2
Pakistan1001502100180.5
Australia920200220156.7
New Zealand500210010153.0
South Africa520010020045.0
India1220110300541.7
West Indies1010120220240.0
Sri Lanka1100122211237.3
Zimbabwe310000020018.0
Bangladesh50001003019.0


This is the traditional 2-1-0 method of evaluating team performance. I have analyzed the matches from home-neutral-away points of view. I have used the 2-1-0 values for the neutral matches and weighed the home matches down by 10% and the away matches upwards by 10%. For another website ratings work I do an additional measure of the team rating points (my famous 100 point split between the two teams). However for this I am going limit myself to the traditional 2-1-0 valuation only.

If one forgets the January disaster for England in the desert, they fully deserve the top position. Their overall record of 6-2-0 is outstanding and the best by any team. Pakistan has only a slightly inferior record of 6-3-1 indicating a welcome resurgence, continuing on to 2012. Just for information, the UAE matches are treated as neutral. Australia left the Ashes trauma of 2010 behind and compiled a 4-2-3 record. New Zealand and South Africa played the minimum of five Tests and compiled identical 2-1-2 records. Then comes India, somewhat fortuitously placed at no.6. They had a 3-4-5 record. They are indeed still lower down if one takes the defeat margins. And let us not forget that the next 3 Tests in 2012 have been thumping losses.

2. An alternate look at performance of teams during 2011

TeamOwn RpWOth RpWDifferenceOwn WpTOth WpTDifference
 
England59.228.530.718.510.97.6
Pakistan41.626.415.219.612.47.2
South Africa3026.53.518.216.41.8
Australia29.428.31.116.417.3-0.9
Zimbabwe33.834.6-0.81718.3-1.3
India30.935.6-4.717.017.00.0
West Indies27.733-5.315.818.4-2.6
New Zealand25.832.2-6.415.219.6-4.4
Sri Lanka29.740.8-1112.617.3-4.6
Bangladesh27.148.6-21.51218.4-6.4


I can hear that strident caller saying "Cut the crap. This is what my ten-year old son/nephew/sister/cousin/.. does in 15 minutes flat on a Sunday afternoon. Where is this "alternate look"? Ah! that is coming now. Why were the teams successful? Good bowling and batting and fielding is fine. But what are the numbers? In this table I look at two sets of numbers to throw light on the success of certain teams and failures of the others.

First the RpW (Runs per wicket) values. I have compiled the "own RpW" and "other RpW" values and got the difference. This difference will indicate the success or lack of of the teams. England's own figure is 59.2 (amazing number - indicating an average innings of nearly 600) and 28.5. The "other RpW" is less than half of the "own RpW". The difference is a mind-boggling 30.7. Pakistan has a very respectable 41.6 and a tight 26.7, giving them a difference of 15.2. No wonder these two teams are so far up on the top. Then after a lot of daylight comes South Africa with a difference of 3.5. Australia is the only other team with a positive difference, viz., 1.1. Those who are surprised to see Zimbabwe placed above India, please be reminded that, leaving the Napier disaster aside, they have made a determined return to Test cricket. Their scores since their return are 370, 291, 412, 141, 313 and 331. Very creditable indeed. Compare this with India's sequence in England, viz., 286, 261, 288, 158, 224, 244, 300 and 283. No wonder Zimbabwe, have a difference of 0.8 are placed above India, with a difference of -4.7. One could also say India were lucky enough to play six Tests against West Indies.

The other comparison I have made is between "own WpM (wickets per match)" and "other WpM". After all a team has to take 20 wickets to win. Once again England and Pakistan are way up with a differential of 7.6 (18.5 vs 10.9) and 7.2 (19.6 vs 12.4) wickets respectively. South Africa has 1.8. India has a flat 0.0. Surprisingly Australia have a negative value of 0.9. This is no doubt due to their heavy defeat against England, narrow win over Sri Lanka, the 47 and the loss of 20 wickets in Hobart and Melbourne. Sri Lanka have done poorly in both measures. However let us not forget that they won a Test and two ODIs in South Africa.

3. The top team performances

2003 2011 Eng 87.45 vs Ind 12.55 England won by an innings and 242 runs
2022 2011 Pak 85.66 vs Bng 14.34 Pakistan won by an innings and 184 runs
1989 2011 Eng 82.55 vs Aus 17.45 England won by an innings and 83 runs
2023 2011 Saf 82.49 vs Slk 17.51 South Africa won by an innings and 81 runs
2001 2011 Eng 82.18 vs Ind 17.82 England won by 319 runs
2017 2011 Ind 80.46 vs Win 19.54 India won by an innings and 15 runs
1994 2011 Eng 80.43 vs Slk 19.57 England won by an innings and 14 runs
2004 2011 Eng 80.25 vs Ind 19.75 England won by an innings and 8 runs

These are the eight imposing wins during 2011. The criteria for selection is match rating points of 80 and above for the winning team. This is secured by any innings win or huge run-margin wins. Only one such win qualifies. This methodology has been explained in my September 2010 article. India has been at the receiving end quite often during 2011. The heaviest win was recorded by England over India (innings and 242 runs). Two other wins by England also fall in this category. Thus India has lost three matches heavily. India's home win over West Indies was achieved comfortably. In terms of winners, this was, without any question, England's year. 5 of these 8 wins have been achieved by them.

It may be of interest to note that India has started 2012 disastrously. All three of their losses have been worse than 80-20. New Zealand's thumping of Zimbabwe comes out with a 89.2-10.8 rating.

4. The year of the debutant bowler

2016 2011 Philander V.D        Saf Aus  7.0  3  15 5 151.2 Debut
2018 2011 Cummins P.J          Aus Saf 29.0  5  79 6 140.3 Debut
2020 2011 Pattinson J.L        Aus Nzl 11.0  5  27 5 131.4 Debut
2015 2011 Ashwin R             Ind Win 21.3  5  47 6 129.4 Debut
2005 2011 Lyon N.M             Aus Slk 15.0  3  34 5 117.7 Debut
2026 2011 de Lange M           Saf Slk 23.2  3  81 7 116.3 Debut
2010 2011 Elias Sunny          Bng Win 23.0  0  94 6 112.4 Debut
2013 2011 Bracewell D.A.J      Nzl Zim 25.0  2  85 5  99.2 Debut


The selectors only had to select a bowler and he would deliver a five-wicket performance. I have not checked this out but can confidently say that at no time in history would eight bowlers, on debut, have captured five wickets or more within a calendar year. And all these happened during the last four months. The stand-out performance was Philander's match-winning effort, discussed later.

5. The debut centurions

1999 2011 Debut Edwards K.A          Win Ind 110  139.6 Debut
2007 2011 Debut Marsh S.E            Aus Slk 141   94.2 Debut


Two centuries were scored on debut during 2011, Edwards did this during their home series against India. He did reasonably well when West Indies came over to India. Marsh scored a wonderful century against Sri Lanka and then dropped like a brick against India.

6. The top batting performances

2003 2011 Cook A.N             Eng Ind 294  193.0
2004 2011 Dravid R             Ind Eng 146* 186.9
2016 2011 Amla H.M             Saf Aus 112  185.0
1997 2011 Dravid R             Ind Win 112  183.0
2016 2011 Clarke M.J           Aus Saf 151  177.3
...
2021 2011 Warner D.A           Aus Nzl 123* 162.9


These are the top 5 rated batting performances. Dravid essayed two of these, both away. The Oval masterpiece of 146 was the innings people would talk of for years to come. To see him losing his stumps almost every innings over the past month has been painful, to say the least. However for me the two stand-out performances have been by two Australians, both in losing causes. Clarks's 151 was a masterpiece and deserved a win. However their own meltdown prevented that. Warner showed everyone that he is not just an attacking batsman. His unbeaten century would have become Lara/Inzamam/Greenidge-esque if only they had scored seven more runs. This innings was almost similar to Tendulkar's epic of 136 except that Warner remained unconquered.

In deference to the wishes of my Sri Lankan readers, I must make a mention of Sangakkara's three top quality innings: 211 against Pakistan, 119 against England and 108 against South Africa. All against top class bowling attacks and away. The first two were match-saving efforts and the third won a rare away match.

7. The top bowling performances

1988 2011 Harbhajan Singh      Ind Saf 38.0  1 120 7 180.4
1988 2011 Steyn D.W            Saf Ind 31.0 11  75 5 164.0
2021 2011 Bracewell D.A.J      Nzl Aus 16.4  4  40 6 154.0
2016 2011 Philander V.D        Saf Aus  7.0  3  15 5 151.2
2004 2011 Swann G.P            Eng Ind 38.0  6 106 6 148.1


These were the top rated bowling performances. For me the stand-out performance was that of Philander on his debut. The match was dead and gone with Australia taking a near-200 run lead. Philander, on his debut, bowled the perfect spell, bowling 42 deliveries on the spot. He could probably have taken all 10 wickets, the perfect way he bowled. His spell paved the way for a tough but reasonable task which was achieved quite comfortably. However without Philander, there would have been no Amla/Smith. Only slightly below is Bracewell's match-winning spell at Hobart. He gave the Australians a taste of the medicine they themselves were going to administer the Indian batsmen a few weeks later.

8. A few important measures compared

Measure20112000-10All-Tests
 
Runs per wicket32.534.331.9
Runs per over3.153.222.82
Wickets per match32.630.930.7
Result %69.275.365.2
Home wins %33.34538.6
Away wins %35.930.426.6
Overs per match336329348
Balls per wicket61.863.967.9
% Inns >= 5005.410.26.7
% Inns <= 1002.83.43.8
Opening Ptshp Avge30.939.636.9
% OP >= 1006.19.29.2
% OP <= 10 36.128.228.7
2-5 Ptshp Avge157.8160.5149.6


Now for a look at various measures for 2011, the preceding decade and the 135 year period.

The Runs per wicket values showed a distinct downward trend from the previous decade of over 5%. It is slightly above the all-Tests figure. There were many below-par performances by fancied teams which accounted for this. The Runs per over figure was only marginally lower. The wickets were taken in about 2 balls fewer keeping with the trend of lowering Runs per wicket.

The Wickets per match numbers showed a distinct increase of about 5% from the 2000-10 decade. However the surprising fact is that this did not show a corresponding increase in Result %. On the contrary there was a drop of 6% from the 2000s. Difficult to explain this.

The Home win % showed a huge drop of 25% from the 2000s decade figure. The away wins showed an increase of about 15%. Maybe the sample size of 39 Tests for 2011 is not big enough. It is possible that the slight drop in home performance of Australia and South Africa contributed to this. It is possible that teams, sand India during 2011, also travel better.

Overs per match was only marginally higher at 336 overs. This comprised of 12 draws at an average of 367 overs (quite a few rain-affected draws) and 17 results at an average of 322 overs. Let us convert this at about 14 overs per hour (especially since dawdling India played over 35% of the Tests), this comes to 23 hours. Add to this an hour of wickets falling and innings changes, we come to around 24 hours. This is around 4 days of play. Remember this is on an average. Let me add that the 2012 has started with only 290 overs per match for the 7 conclusive Tests. That is well below 4 days play. Only one Test, the Adelaide one, reached the fifth day: That too, courtesy, Mr. M.J.Clarke.

There is a sharp drop in 500+ innings, just above 50%, the respective figures standing at 5.4 and 10.2% respectively. For that matter the year 2011 was below the all-Tests average. Quite surprisingly, the sub-100 innings also showed a drop from 2000-10 and all-Tests values. Quite inexplicable.

The Opening partnerships failed miserably during 2011. The average runs scored dropped from nearly 40 to just over 30. It was way below the all-Tests figure. Maybe the Indian openers and Strauss and Hughes contributed to this. Similarly there was a significant drop in the 100+ opening partnerships (once in 16 innings as against once in 11 innings) and the sub-10 partnerships showed a sharp increase. Maybe the new crop of exciting pace bowlers contributed to this. Pattinson, Cummins, Philander, Bracewell, Yadav, Broad et al are going to continue in this vein. Ably supported by the resurgence of Siddle, Hilfenhaus, Andersen, et al. Of course Steyn, Morkel, Zaheer are always there. The other significant reason could be the continuing Twenty-20 approach of the openers.

However the middle-order partnerships for the second, third, fourth and fifth wickets have held firm. This value of 158 is quite close to the 2000-10 value of 160.

9. My own abiding memories of 2011


These are strictly my personal selections.

The match of the year was New Zealand's sevn-run win over Australia. Warner batted as he would never have been expected to. Bracewell bowled as Hadlee did 26 years back. Until the last ball bowled by Bracewell to Lyon, the result was in doubt. As Djokovic told a few weeks later at Melbourne, there should have been two winners. Both teams fought hard to the last ball. A close contender was Australia's redeeming series-equalling win over South Africa at Wanderer's.

The innings of the year was Warner's unbeaten 123, referred to quite a few times already. Warner would go through bad patches in his career. He should only rewind the clock back to 13 December 2011 and Hobart, when he almost climbed Everest through the North face. Amazing thing is that Warner's 180 at Perth might very well be the innings of 2012 and it is going to take some beating.

The bowling performance of the year was Philander's 5 for 15 against Australia. The match was dead and gone, but for Philander. I have never seen 42 balls delivered on a coin. That was McGrath-like.

The most forgettable performance of the year was Sehwag's golden pair at Birmingham. He lasted a round 190 overs less than the 7 English batsmen. That symbolized the Indian English debacle as Dravid's loss of his stumps symbolized six months later.

The bravest performance of 2011 was by Zimbabwe on their comeback. They fought hard and four of their six innings exceeded 300. And this was against Pakistan, New Zealand and Bangladesh.

The non-stories of the year were Tendulkar's ton of tons, the various retirement stories circulated, the complete irrelevance of Champions' League (even though, as a contest, it was far superior to IPL) and the millions of words written on India's free fall (all destined to have no effect).

The Indian Test debacles have been chronicled ad nauseam. However the meltdown of the year was Sri Lanka's 24-over capitulation on the last day at Cardiff.

MS Dhoni comes in two situations next. The sporting gesture of the year was Dhoni's recall of Bell. The cop-out of the year was Dhoni's refusal to go for the win at Roseau, against West Indies.

Full post
Batsman analysis by bowler-pitch quality - part 2

Part two of the study to analyse the careers of Test batsmen by bowling quality and type of pitches

This is the follow-up article to the one analysing the batsmen performance in conditions related to bowler quality and pitch types. There were a number of very useful suggestions and after a careful study some of these have been implemented. There have been very sound arguments also that there is an element of double-counting and this method, in general, favours batsmen with very good bowling attacks backing them. This point is accepted. However it would be impossible for me to implement these radical suggestions without a lot of work, including quite a bit of validation. Hence I have gone ahead with the current method, modified suitably. The elimination of the double-counting and the development of a single evaluation factor will be done later.

Meanwhile let us look at the current method, which, double-counting notwithstanding, offers many insights. The modifications are summarized below.

1. Take the top-7(or fewer) partnerships rather than individual scores. This was suggested by Arjun again. The partnerships basis might very well end with similar numbers. However it seems to smoothen the outlier/out performer situation. If 320 for 2 was reached through 200, 50, 40 and 30, the 200 seems clearly to be a way-out performance and brings some attendant concerns. However in whichever way the partnerships have been formed, 100/100/120 or 150/20/150, the partnerships clearly convey the comfort feelings for distinct PAIRS of batsmen, rather than single batsman. This will obviate, to a great extent, the need to take off outliers.

3. However I do not want to miss out the low-3 scores, suggested by Anshu, since that normalizes the values. However this time I will take the individual scores since these represent clear failures. But I will be tougher and limit these failures to top-6 rather than top-7 since the top-6, barring stray no.7 guys like Gilchrist, (pre-WC-Win) Dhoni, Vettori et al, represent the real batsmen.

4. I will consider varying numbers for both these measures. Otherwise the impact will go out of proportion. The table is given below.

- Upto 5 innings in match: 3 + 2.
-  6 to 10 innings:        4 + 2.
- 11 to 20 innings:        5 + 3.
- 21 to 29 innings:        6 + 3.
- 30 to 44 innings:        7 + 3.

5. The final Bowler-Pitch index will be derived as a Geometric Mean (GM) of the BQI and RSI values. Both are basically runs. The GM has many benefits. It is ALWAYS a number between the smaller and arithmetic mean values. As the difference between the two numbers increases, it moves closer to the smaller number. And we never get out-of-the-range values.

6. Probably one mistake I made was to combine the first three groups as tough super groups. This set the cat amongst the pigeons. Richards' 82% was way out and readers spent quite some time on that. The first two groups are fine: they are really tough conditions. However the third one is the middle group in which many many runs are scored and should not have been combined with the first two groups. Hence I now have three super groups. The first one is the really tough one (5-4), the second one, the middle group (3) and the third one the easiest to bat against (2-1).

7. I have compiled the values for innings played and the batting averages for each group and have shown these important values, as asked for by many readers.

8. I am not going to give the individual group values. There is too much data. I will give only the summaries by the three super groups.

9. I have done the run-weighted BPI value for each batsman. However I will only show two tables of extreme values of this measure. The similarity of the numbers will warrant some obvious comments.

10. Look at the tough groups numbers carefully. The % of career score only indicates that the batsman faced tough conditions and made some runs on these more often in his career than a more fortunate peer. However an average of above 40 in the revised tough groups is something to sit up and take notice.

11.I have also given a table of selected innings for the top-3 groups. These are not presented as the best innings ever played. However these were made in very tough conditions, bowler-pitch wise. Some of these might be in this table because the bowlers behind the concerned batsmen were outstanding. But they certainly were special innings.

12.Finally I am going to present these tables with minimal comments. My hands are protesting.

1. Player wise distribution table by super groups

BatsmanCtyCareerCareerBatting ToughGrps(5-4) MiddleGrp(3) EasyGrps(2-1)
  InnsRunsAvge InnsRunsAvge% InnsRunsAvge% InnsRunsAvge%
                    
Tendulkar S.R Ind3091543255.71 58168429.5410.9%117552254.1435.8%1348226 69.7153.3%
Dravid R Ind2841326252.63 52155431.7111.7%106392439.6429.6%1267784 74.8558.7%
Ponting R.T Aus2741291552.50 47126628.13 9.8%104461947.1335.8%1237030 68.2554.4%
Kallis J.H Saf2541226057.02 70233737.1019.1% 94391048.8831.9% 906013 83.5149.0%
Lara B.C Win2321195352.89 91346238.9029.0% 76305241.8125.5% 655439 84.9845.5%
Border A.R Aus2651117450.56 90285838.6225.6%107438647.1639.3% 683930 72.7835.2%
Waugh S.R Aus2601092751.06 74220334.9720.2% 94407150.2637.3% 924653 66.4742.6%
Gavaskar S.M Ind2141012251.12 61217738.1921.5% 81345943.7834.2% 724486 72.3544.3%
Jayawardene M Slk2131008950.44 52170734.1416.9% 68262641.0326.0% 935756 66.9357.1%
Chanderpaul S Win234 970949.28 69214735.2022.1% 91350145.4736.1% 744061 68.8341.8%
Sangakkara K.C Slk179 934755.97 36110732.5611.8% 62300551.8132.1% 815235 69.8056.0%
Gooch G.A Eng215 890042.58 97325034.5736.5% 71297143.0633.4% 472679 58.2430.1%
Javed Miandad Pak189 883252.57 63217636.2724.6% 67277848.7431.5% 593878 76.0443.9%
Inzamam-ul-Haq Pak200 883049.61 48141232.0916.0% 82364247.3041.2% 703776 66.2542.8%
Laxman V.V.S Ind223 872846.18 40105827.8412.1% 82289440.1933.2%1014776 60.4654.7%
Hayden M.L Aus184 862650.74 30106435.4712.3% 72297844.4534.5% 824584 62.7953.1%
Richards I.V.A Win182 854050.24 57237043.0927.8% 78354747.9341.5% 472623 63.9830.7%
Stewart A.J Eng235 846539.56 97271630.5232.1% 86326241.2938.5% 522487 54.0729.4%
Gower D.I Eng204 823144.25 85272034.0033.0% 75313245.3938.1% 442379 64.3028.9%
Boycott G Eng193 811447.73 62192533.7723.7% 84402352.9349.6% 472166 58.5426.7%
Sehwag V Ind165 809850.93 30 74024.67 9.1% 49185940.4123.0% 865499 66.2567.9%
Sobers G.St.A Win160 803257.78 43136232.4317.0% 58275754.0634.3% 593913 85.0748.7%
Waugh M.E Aus209 802941.82 62226140.3828.2% 84287936.9135.9% 632889 49.8136.0%
Smith G.C Saf168 776149.43 32101532.7413.1% 60238741.8830.8% 764359 63.1756.2%
Atherton M.A Eng212 772837.70 96255526.8933.1% 79320242.6941.4% 371971 56.3125.5%
Langer J.L Aus182 769645.27 44 95321.6612.4% 63317254.6941.2% 753571 52.5146.4%
Cowdrey M.C Eng188 762444.07 73230633.4230.2% 79339248.4644.5% 361926 56.6525.3%
Greenidge C.G Win185 755844.72 58182432.0024.1% 77323946.2742.9% 502495 59.4033.0%
Mohammad Yousuf Pak156 753052.29 42117530.1315.6% 52194138.0625.8% 624414 81.7458.6%
Taylor M.A Aus186 752543.50 53150930.8020.1% 73294143.2539.1% 603075 54.9140.9%
Lloyd C.H Win175 751546.68 53196339.2626.1% 68277246.9836.9% 542780 53.4637.0%
Haynes D.L Win202 748742.30 66224235.5929.9% 85286039.7238.2% 512385 56.7931.9%
Boon D.C Aus190 742243.66 54174734.9423.5% 69222235.8429.9% 673453 59.5346.5%
Kirsten G Saf176 728945.27 62151226.0720.7% 65280246.7038.4% 492975 69.1940.8%
Hammond W.R Eng140 724958.46 14 31926.58 4.4% 33121439.1616.7% 935716 70.5778.9%
Ganguly S.C Ind188 721242.18 39 93727.5613.0% 73258538.0135.8% 763690 53.4851.2%
Fleming S.P Nzl189 717240.07 64147123.7320.5% 83375748.1752.4% 421944 49.8527.1%
Chappell G.S Aus151 711053.86 59203738.4328.6% 54246152.3634.6% 382612 81.6236.7%
Bradman D.G Aus 80 699699.94 11 53753.70 7.7% 23227598.9132.5% 464184113.0859.8%
Flower A Zim112 479451.55 47126330.0726.3% 35131345.2827.4% 302218100.8246.3%


I am not going to do too much elaboration but will allow the readers to do their own interpretations. Now that the innings and batting averages are shown some points will be obvious.

1. It can be seen that batsmen like Botham, Wood, May et al have the tough super group % as 40+. However it can also be seen that they have all played around 50% of their innings in these groups.
2. There was a comment that batsmen from same teams had similar numbers. This is effectively disproved now. Ponting is 9.8%, Mark Waugh is 28.2%, Martyn 23.4%, Clarke 16.5% and Gilchrist 16.9%. Haynes 29.9%, Greenidge 24.1% and Lloyd 26.1%. Jayawardene is 16.9% and Sangakkara is 11.8%, with similar averages. And so on.
3. Clarke and Gilchrist have tough group averages exceeding 40. The best is McDonald/Bradman with 53+ and R.Mclean with 50+.
4. Kumble's tough group % is 22+ and Dravid's 11.7%. This does not mean anything. However the averages are 13.4 and 31.7. So read and interpret these numbers with care.
5. Slice and dice in whichever way you want to, Hammond props up the tables.

2. Top batsmen by run-weighted BQI values

BatsmanCtyCareerBattingWeighted
  RunsAvgeBPI
McLean R.A Saf 212030.2941.2
Ramprakash M.R Eng 235027.3341.5
Howarth G.P Nzl 253132.4542.0
McDonald C.C Aus 310739.3343.0
Wood G.M Aus 337431.8343.0
Waite J.H.B Saf 240530.4443.2
Botham I.T Eng 520033.5543.4
Bailey T.E Eng 229029.7443.5
Hughes K.J Aus 441537.4243.6
Greig A.W Eng 359940.4443.6
Hudson A.C Saf 200733.4543.6
Benaud R Aus 220124.4643.7
Goddard T.L Saf 251634.4743.8
Wasim Raja Pak 282136.1743.8
Coney J.V Nzl 266837.5843.8
Gregory S.E Aus 228224.5443.9
Randall D.W Eng 247033.3844.0
May P.B.H Eng 453746.7744.1
Cronje W.J Saf 371436.4144.1
Rhodes J.N Saf 253235.6644.1


These are the top batsmen based on the run-weighted BPI values. McLean and Ramprakash lead the field. Most batsmen are in the 1950s-80s period.No modern batsman figures in the top-20. No sub-continental batsman is in the top-20. They all have 45+ values. A few unfancied batsmen like Ramprakash, Wood, Hughes, Howarth have made into this list.

3. Bottom batsmen by run-weighted BQI values

BatsmanCtyCareerBattingWeighted
  RunsAvgeBPI
     
Cook A.N Eng 587648.9752.9
Trott I.J.L Eng 203156.4253.4
Ponsford W.H Aus 212248.2353.6
Jones A.H Nzl 292244.2753.8
Washbrook C Eng 256942.8254.1
Headley G.A Win 219060.8354.2
Hendren E.H Eng 352547.6454.2
Edrich W.J Eng 244040.0055.2
Hammond W.R Eng 724958.4655.4
Ames L.E.G Eng 243440.5757.2

This is the other end. Many modern batsmen and batsmen from the 1920s figure here. Somehow Ames has managed to push Hammond off the last place. Cook and Trott are the leading batsmen of today who have found their place here. Most of today's top batsmen are around the 50 mark.

4. Selected innings which crossed the BPI zone of excellence

MtNoYearBatsmanForVsBatPosRunsBPI GrpBPIResult
          
7881976Amiss D.L EngIndOP179 534.9Won
231886Shrewsbury A EngAus3164 535.0Won
3611952Endean W.R SafAus3162 535.0Won
3311951Simpson R.T EngAus3156 533.6Won
11711991Gooch G.A EngWinOP154 532.4Won
451895Graham H AusEng5105 529.1Won
9151981Hughes K.J AusWin5100 528.9Won
8271978Sadiq Mohammad PakEng2 97 526.6Drawn
451895Trott A.E AusEng9 85 529.1Won
8901980Wasim Raja PakWin6 77 529.1Drawn
10561986Greenidge C.G WinPak1 75 526.1Won
17732005Lara B.C WinAus4226 440.6Lost
14511999Lara B.C WinAus4213 441.4Won
10701987Greenidge C.G WinNzlOP213 440.8Won
2581937Bradman D.G AusEng3212 441.6Won
421894Gregory S.E AusEng6201 438.8Lost
5931965Edrich J.H EngNzlOP310 349.2Won
2361934Bradman D.G AusEng5304 348.2Drawn
16412003Fleming S.P NzlSlk3274 347.3Drawn
6711970Pollock R.G SafAus4274 347.5Won
16972004Dravid R IndPak3270 348.7Won
2571937Bradman D.G AusEng7270 344.2Won
17432005Younis Khan PakInd3267 348.3Won
13581997Young B.A NzlSlkOP267 349.2Won
12711994Houghton D.LZimSlk4266 347.8Drawn
18002006Fleming S.P NzlSaf3262 349.0Drawn
17162004Jayasuriya S.T SlkPakOP253 343.8Won
8451979Bacchus S.F.A.FWinInd2250 349.6Drawn


I am sure there would be adverse comments on this table. Individual innings will be commented upon saying they do not belong here. Possibly they do not. However these were very good innings played, whose inclusion here is based on the parameters set. Any list which includes Gooch's 154, Lara's 223/213, Hughes' 100, Bradman's 212/270/304, Greenidge's 213, Graeme Pollock's 274, Dravid's 270, Jayasuriya's 253 et al cannot really be a bad table. These innings would fill almost anyone's list of top-25 or so innings. The selection criteria is a composite one involving Runs, BPI group and BPI value.

To download/view the document containing the Bowler-Pitch-Index values for 7340 innings, please click/right-click here.

To download/view the document containing the Player tables for selected 261 batsmen tables please click/right-click here.

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Batsman analysis by bowler-pitch quality - part one

Part one of a study to analyse the careers of Test batsmen by bowling quality and type of pitches

Finally the time has come for me to complete the analysis of batsmen by two important factors, Bowler quality and Pitch quality. This exercise was started about 7 months back and has moved on wonderfully well with meaningful insights from many readers. In my earlier two articles I had covered the BQI and RSI ("Runs scored index": revised name for Pitch quality) methodologies. As has happened quite frequently lately, the article, with over 10 tables and 4 graphs, has become very long and I necessarily have to split it into two articles.

The tables are current up to and including match # 2029. This was totally unexpected and was made possible since the Perth non-contest finished within 45% of the allotted time. One could say India lost by an innings, 37 runs and 250 overs.

BQI is a pre-match estimate of the bowling quality expected, based on the career-to-date home/away averages, he location of the Test and the recent form of players. There is a provision to handle the early Tests of top bowlers. The final grouping is given below.


15.0 - 27.0: Group 5 - 998 (13.7%) Amongst the best of all time 27.0 - 32.0: Group 4 - 1675 (22.6%) A very good attack 32.0 - 38.0: Group 3 - 2111 (28.5%) Good attack 38.0 - 45.0: Group 2 - 1596 (21.5%) Below average 45.0 - 60.0: Group 1 - 953 (13.7%) A poor attack

RSI is a post-match determination of the ease of scoring in the Test. This is done by considering the top-10 scores and determining the Runs per innings. The final grouping is given below. This has been slightly modified from the previous article. The lower limit was raised and the upper limit was lowered since otherwise there were too few matches in these end categories.


Below 45.0: Group 5 - 224 (11.0%) A nightmare for the batsmen 45.0 - 55.0: Group 4 - 330 (16.3%) Quite difficult to bat on 55.0 - 67.5: Group 3 - 516 (25.4%) Good pitch - favouring bowlers 67.5 - 80.0: Group 2 - 499 (24.1%) Good pitch - favouring batsmen 80.0 - 90.0: Group 1 - 269 (13.3%) A high-scoring pitch. Above 90.0 : Group 0 - 200 ( 9.9%) Where the bowlers are cannon-fodder.

To determine the impact of the bowling quality and the pitch quality, my first idea was to add the two values and determine groups based on that. Both measures are indicative of runs. However that was a non-starter since the range of RSI values was much wider and it was not a normal distribution unlike the BQI values which were normally distributed. BQI is a traditional average (Runs per wicket) while RSI consists of the average of the top-10 values. Adding these two resulted in a lopsided distribution and proper grouping was impossible.

Hence I finalized on adding the two group values. Here there were no such problems. The ranges were similar and there was no lopsided distribution. This method takes care of close matches between well-matched teams as also lop-sided matches such as between Australia and Zimbabwe or currently Australia and India. The extreme groups are exactly what they are portrayed as: impossible to bat on or impossible to bowl on. Let us briefly look at the numbers derived by adding the same.


10 / 9 : At least one 5. Nothing below 4. A batsman's nightmare. 8 / 7 : At least one 4. Nothing below 2. A bowler dominated pitch. 6 / 5 : 1 or 0 means a 5 comes in. 3 is a key number either way.
Fair to batsmen and bowlers. 4 / 3 : Max BQI is 4 and max RSI is 3. Possibly formed with 1s/2s.
Strongly batsman-dominant pitch. 2 / 1 : Either 2 & 0 or 1 & 1 or 1 and 0. A bowler's graveyard.
The final BPI groups are outlined below.

10 - 156 9 - 404 Group total: 560 ( 7.6%) PLATINUM group. Scoring runs is extremely tough. 8 - 702 7 - 1115 Group total: 1817 (24.8%) GOLD group. Scoring runs is very difficult. 6 - 1416 5 - 1345 Group total: 2761 (37.6%) SILVER group. Possible to score runs, but lot of application called for. 4 - 1090 3 - 707 Group total: 1797 (24.5%) BRONZE group. Scoring runs is very easy. 2 - 315 1 - 86 Group total: 401 ( 5.5%) TIN group. Free runs served on the buffet table.

It should be understood that this analysis has some inherent features, outlined below.

1. This analysis takes into account Bowling and Pitch qualities, which form one cornerstone of an Innings Ratings analysis. As such the match-specific factors such as match status, innings status, position at entry, result, support received, management of late-order batsmen et al are not considered.

2. It will favour batsmen coming from bowler-dominated countries like New Zealand, England.

3. The sub-continent batsmen will lose some of their sheen.

4. High individual scores will almost always be associated with high RSI values. Hence these scores are likely to be valued less. It is possible that this could be compensated partly by the bowling quality. For instance Laxman's classic of 281 has a RSI of 0 but a BQI of 4. Similar numbers for Sehwag's 319. Jayasuriya's 340 has 0 and 1. Clarke's 329 has 0 and 2. On the other hand, Hammond's 336 has 3 and 1. And so on. Warner's 180 gets a 4 and 2 (the Indian attack quite average).

5. The purpose of the analysis is to look a new dimension of batting (i-e) from the Bowling and Pitch points of view. There is no intention to put down certain players. Please do not come out with such comments. These will not be recognized.

Incidentally I consider these three groups, viz., Platinum, Gold and Silver as the tough and challenging conditions. These comprise of 6 BPI groups and represent 61.3% of the total runs. There might be fluctuations within these groups. However runs scored in these conditions should be accorded the tough-runs category. Later in this article I will do an analysis based on the runs scored in these three challenging conditions.

Now for a different summary. This table summarizes the group runs for the subset of 266 batsmen selected for this analysis. The cut-off is 2000 Test runs. This sample size is very significant and represents about 60% of the total runs scored.


PLATINUM group: 45228 runs ( 3.9%) GOLD group: 220331 runs (19.2%) SILVER group: 438904 runs (38.2%) Tough groups: 704463 runs (61.3%) BRONZE group: 350118 runs (30.5%) TIN group: 93731 runs ( 8.6%) Easier groups: 443849 runs (38.7%) Total: 1148312 runs (100.0%)

Player Group wise distribution table

BatsmanCtyCareerPlatinum(10-9)Gold(8-7)Silver(6-5)ToughGrpsBronze(4-3)Tin(2-1)EasyGrps
  RunsRuns%Runs%Runs%Runs%Runs%Runs%Runs%
                 
TendulkarInd15432 408 2.6175011.3488031.6703845.6654242.4185212.0839454.4
DravidInd13262 322 2.4179713.5413331.2625247.1572043.11290 9.7701052.9
PontingAus12915 254 2.0 989 7.7550942.7675252.3475336.8141010.9616347.7
KallisSaf12260 99 0.8217917.8460237.5688056.1339427.7198616.2538043.9
LaraWin11953 563 4.7282923.7398533.3737761.7422435.3 352 2.9457638.3
BorderAus11174 470 4.2228620.5462441.4738066.0324229.0 552 4.9379434.0
Waugh S.RAus10927 373 3.4167715.3460542.1665560.9347231.8 800 7.3427239.1
GavaskarInd10122 395 3.9203120.1399439.5642063.4277927.5 923 9.1370236.6
JayawardeneSlk10089 213 2.1130112.9352634.9504050.0378037.5126912.6504950.0
ChanderpaulWin 9709 478 4.9195920.2366337.7610062.8273628.2 873 9.0360937.2
SangakkaraSlk 9347 36 0.4125513.4372939.9502053.7301432.2131314.0432746.3
GoochEng 8900 676 7.6279531.4307734.6654873.6181120.3 541 6.1235226.4
J MiandadPak 8832 270 3.1228225.8286032.4541261.3253828.7 88210.0342038.7
InzamamPak 8830 169 1.9132215.0358440.6507557.5358040.5 175 2.0375542.5
LaxmanInd 8728 384 4.4107012.3254129.1399545.8353340.5120013.7473354.2
HaydenAus 8626 253 2.9 803 9.3328138.0433750.3297734.5131215.2428949.7
RichardsWin 8540 425 5.0214525.1446052.2703082.3137116.1 139 1.6151017.7
StewartEng 8465 729 8.6257330.4326438.6656677.6161119.0 288 3.4189922.4
GowerEng 8231 313 3.8220826.8336440.9588571.5221126.9 135 1.6234628.5
BoycottEng 8114 272 3.4151518.7403249.7581971.7211726.1 178 2.2229528.3
SehwagInd 8098 148 1.8 761 9.4181022.4271933.6382447.2155519.2537966.4
SobersWin 8032 114 1.4111513.9399549.7522465.0235829.4 450 5.6280835.0
Waugh M.EAus 8029 220 2.7172021.4347843.3541867.5235629.3 255 3.2261132.5
Smith G.CSaf 7761 0 0.0 96612.4270234.8366847.3320441.3 88911.5409352.7
AthertonEng 7728 527 6.8271035.1309840.1633582.0114614.8 247 3.2139318.0
                 
HammondEng 7249 31 0.4 322 4.4159522.0194826.9312243.1217930.1530173.1
FlemingNzl 7172 328 4.6113815.9362350.5508971.0198627.7 97 1.4208329.0
BradmanAus 6996 0 0.0 71610.2220731.5292341.8299842.9107515.4407358.2
HuttonEng 6971 533 7.6 86212.4194827.9334348.0193427.7169424.3362852.0
MayEng 4537 54412.0180639.8129328.5364380.3 60513.3 289 6.4 89419.7
Flower AZim 4794 354 7.4 78116.3150331.4263855.0161633.7 54011.3215645.0
H BasharBng 3026 207 6.8 58019.2113937.6192663.6110036.4 0 0.0110036.4

The table is self-explanatory. The table consists of the top-25 batsman, by aggregate of runs and five special selections. Bradman and Hammond represent the pre-WW2 era, Hutton and May, the 1950s-60s and Fleming, New Zealand. There is a case for Martin Crowe's inclusion but 1700 runs was too much to ignore. Andy Flower and Habibul Basher represent Zimbabwe and Bangladesh.The complete Excel sheet containing the group-wise breakdown for the qualifying 266 batsmen can be downloaded and perused.

Graph of career runs ordered by runs scored against tough and easy groups © Anantha Narayanan

This graph splits the batsman career runs by the tougher groups (10-5) and easier groups (4-1). Since the overall average for the tough groups runs is around 60%, it is fair to assume that a tough group runs % of above 50 should be acceptable. The Indian quartet of Tendulkar, Dravid, Laxman and Sehwag are all below 50%. As does Graeme Smith. However it can be seen that both the pre-WW2 stalwarts, Bradman and Hammond are also below 50%. In fact Hammond's 26.9% is the lowest, by a wide margin, amongst all established players. Let us spare a moment for Peter May whose tough-runs % is in excess of 80, amongst the highest in this group.

Graph of percentage of career runs scored against tough groups © Anantha Narayanan

In this graph, I have shown the batsmen, at the top and bottom of the ladder of tough-groups run %. The very much under-rated Australian batsman, Kim Hughes, leads the table having scored an amazing 88% of his runs in these tough conditions. Spare a moment to recognize this achievement. Ian Botham, again under-rated as a batsmen, has also scored 88% of his runs in tough conditions. Warne might have got his measure, but Cullinan was no bunny, coming in third with 82.8%. Richards is a surprise placement at fourth ad Atherton in the fifth position. The top 20 positions has no current player. The nearest we get to a modern player is Graham Thorpe (and Nasser Hussain). The best India batsman is Viswanath, with 77.7%. For these graphs I have considered only batsmen who have scored 4000 or more runs.

At the other end, we have the Indian stalwarts, Laxman, Tendulkar and Sehwag. Bradman and Sutcliffe are also in the bottom 10. Hammond props up the table with 26.9%.

Platinum Group (Groups 9 and 10) tables

BatsmanTeamCareer RunsRuns%
     
Harvey R.N Aus 6149 91314.8
May P.B.H Eng 4537 54412.0
Lamb A.J Eng 4656 47110.1
Smith R.A Eng 4236 399 9.4
Hughes K.J Aus 4415 397 9.0
Stewart A.J Eng 8465 729 8.6
Richardson R.B Win 5949 472 7.9
Knott A.P.E Eng 4389 339 7.7
Botham I.T Eng 5200 402 7.7
Hooper C.L Win 5762 443 7.7
BatsmanTeamCareer RunsRuns%
     
Harvey R.N Aus 6149 91314.8
Stewart A.J Eng 8465 729 8.6
Gooch G.A Eng 8900 676 7.6
Lara B.C Win11953 563 4.7
May P.B.H Eng 4537 54412.0
Hutton L Eng 6971 533 7.6
Atherton M.A Eng 7728 527 6.8
Cowdrey M.C Eng 7624 519 6.8
Thorpe G.P Eng 6744 510 7.6
Chanderpaul S Win 9709 478 4.9

The presence of Harvey and May in the top two positions in the % of career runs indicates that run scoring during the 1950s-60s was tough and these runs should mean more. The list then moves to the 80s-90s. Almost all the later players are from this period. I am almost certain that no one from this list of top-10 would get into any list of top-10 batsmen. But the lowest placed batsman on this has scored more than 7% of his runs in the toughest of conditions. Hats off to them.

The second table contains the Platinum group batsmen ordered on the runs scored. Harvey is again on top. What a great batsman he was? Then the English stalwarts, Stewart and Gooch, who spent half their careers facing the West Indian quicks. Lara represents the modern era. Not many runs, and less than 5%, but more than anyone else of this period. May, Hutton and Cowdrey of the 50s-60s come in. Surprising inclusions are Thorpe and Chanderpaul.

Gold Group (Groups 7 and 8) tables

BatsmanTeamCareer RunsRuns%
     
May P.B.H Eng 4537180639.8
Atherton M.A Eng 7728271035.1
Botham I.T Eng 5200175033.7
Hughes K.J Aus 4415145633.0
Gooch G.A Eng 8900279531.4
Thorpe G.P Eng 6744208730.9
Stewart A.J Eng 8465257330.4
Hussain N Eng 5764174630.3
Graveney T.W Eng 4882147330.2
Redpath I.R Aus 4737142830.1
BatsmanTeamCareer RunsRuns%
     
Lara B.C Win11953282923.7
Gooch G.A Eng 8900279531.4
Atherton M.A Eng 7728271035.1
Stewart A.J Eng 8465257330.4
Border A.R Aus11174228620.5
Javed Miandad Pak 8832228225.8
Gower D.I Eng 8231220826.8
Kallis J.H Saf12260217917.8
Haynes D.L Win 7487217829.1
Richards I.V.A Win 8540214525.1

The Gold Group tables, representing the batsmen who have performed very well against very tough conditions also follows a similar path. This table is almost totally dominated by the English batsmen from 1950-2000. This clearly indicates that the conditions in England were such and the English batsmen also travelled reasonably well. It is of interest to note that May has scored over 50% of his runs in the toughest of conditions. And Gooch, nearly 40%. Atherton deserves a separate mention,. And what about Botham as a batsman, a third of his runs on these conditions. Spare a thought for the much maligned Kim Hughes, one of only two Australians.

In the table ordered on runs scored, Lara leads by a few runs from Gooch and Atherton. This confirms that Lara scored many of his runs in tough situations. Javed Miandad's presence in the later table is a welcome introduction of an Asian batsman and speaks of his class.

Silver Group (Groups 6 and 5) tables

BatsmanTeamCareer RunsRuns%
     
Cullinan D.J Saf 4554299965.9
Kallicharran A.I Win 4399248856.6
Viswanath G.R Ind 6080320352.7
Richards I.V.A Win 8540446052.2
Lloyd C.H Win 7515383851.1
Fleming S.P Nzl 7172362350.5
Greenidge C.G Win 7558379250.2
Boycott G Eng 8114403249.7
Sobers G.St.A Win 8032399549.7
Boucher M.V Saf 5407258347.8

This is the middle group and should and does see a lot of runs scored. Cullinan might have been a Warne-bunny but he sure scored over 65% of his runs in this middle not-so-easy conditions. Viswanath is the leading Indian here having scored over 50% of his runs. Some famous batsmen, viz., Richards, Lloyd, Sobers, Greenidge have scored around 50%. Boucher is a surprising addition here. He seems to have scored quite a bit of his tally in this group. It is possible that he has scored more at home than away.

I have not got a separate table ordered on runs. Suffice to say that the most runs have been scored by Ponting, with 5509 runs, Tendulkar, with 4880 runs and Border, with 4624 runs.

Bronze Group (Groups 4 and 3) tables

BatsmanTeamCareer RunsRuns%
     
Younis Khan Pak 6205371759.9
Zaheer Abbas Pak 5062252749.9
Mohammad Yousuf Pak 7530369849.1
Sehwag V Ind 8088382447.3
Dilshan T.M Slk 4662216446.4
Sutcliffe H Eng 4555199243.7
Dravid R Ind13206572043.3
Hammond W.R Eng 7249312243.1
Bradman D.G Aus 6996299842.9
Hussey M.E.K Aus 5435232342.7

The Bronze table represents the runs scored in conditions which are strongly in favour of the batsmen. Now you can see the entry of almost all top batsmen, including Bradman and Hammond coming in. Younis Khan is the only batsman to get well over the 50% mark of his career runs. Zaheer Abbas and Mohd Yousuf are around 50%. Then Sehwag, with 47.3%. It is of interest to note that the table is headed by modern batsmen and batsmen of the pre-WW2 vintage. There is not one batsman from the 1950s to 1980s.

Again I have not got a separate table ordered on runs. Suffice to say that the most runs have been scored by Tendulkar, with 6542 runs, Dravid, with 5720 runs and Ponting, with 4753 runs. These are the top three run-getters in Tests.

Tin Group (Groups 2 and 1) tables

BatsmanTeamCareer RunsRuns%
     
Hammond W.R Eng 7249217930.1
Hutton L Eng 6971169424.3
Compton D.C.S Eng 5807133923.1
Cook A.N Eng 5868115119.6
EdeC Weekes Win 4455 87019.5
Sehwag V Ind 8088155519.2
Gayle C.H Win 6373117218.4
Samaraweera T.T Slk 5022 91618.2
de Villiers A.B Saf 5239 90917.4
Kallis J.H Saf12260198616.2

These are the easiest of runs. The pitches are flattest of flat and the bowling extremely benign. This is a surprising mix of the 1930s, 1950s, 1960s and 200s period batsmen. However more than half are from the current lot of batsmen.

Again no separate table ordered on runs. Suffice to say that the most runs have been scored by Hammond, with 2179 runs, Kallis, with 1986 runs and Tendulkar, with 1852 runs. Incidentally Lara, amongst modern batsman has a very low tally of these easy runs, with 352. Inzamam- ul-haq has only 175 runs and Richards, only 139 runs.

Some preliminary conclusions can be drawn. The conditions for batsmen were favourable to the batsmen during the pre-WW2 period. Then during the next 50 years or so, the conditions became more favourable for bowlers. This was also partly due to the rather low scoring rates of 1950s-60s. Then over the past 15 years, the conditions have become more favourable to the batsmen. Partly also because of the faster scoring and the consequent benefits. And the English batsmen of the post-WW2 period have had the toughest of conditions to make runs.

This is a fascinating set of tables. The significant positions are filled by lesser batsmen. This is a natural outcome when players score well over 10000 runs. There are significant questions to be answered. Lara is the only top scorer to have found a place in a Platinum or Gold table. And the nearest to him is Chanderpaul. Why? Also the volume of runs and the averages are used freely when talking about batsmen. This analysis shows the importance of looking at the match conditions in which these runs were scored. Forgotten batsmen like Hughes and Cullinan stand out. The value of runs scored by Richards, Atherton, Viswanath, Gooch et al stands enhanced. Readers' comments on these important points will be most welcome. Again, let me remind everyone. Please make objective comments and avoid accusations. This analysis is about 266 batsmen and not one or two.

To download/view the document containing the Player tables for selected 261 batsmen tables please click/right-click here.

In the next part of the article I will cover the following.

1. The Batsman tables based on the run-weighted BPI values.
2. Graphs for above, both top-30 batsmen and high and low values.
3. Career details of runs and relevant BPI group for 5 selected players, total, home and away.
4. A selection of top innings played in the Platinum and Gold groups.

Incidentally I have written another article, not an analytical one, for another site. I thought it would be good for the interested readers to peruse the same. I have uploaded the MSWord file and provided the link below. Please click/right-click here.

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