January 27, 2012

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
57

Ian Botham scored majority of his runs against top-quality bowling attacks © Getty Images

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.

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

Comments have now been closed for this article

  • Gerry_the_Merry on February 4, 2012, 7:39 GMT

    Dear Ananth, So as I understand from this, the ha_wt is influencing BPI to get to run-weighted BPI, but is not influencing the BPI for the purpose of the tough group classification. BPI is nice to know, but the real deal is the tough group runs definition.

    I will not press this point further now. I have weighted for 8 months to see the tough group calculations. This edition has many many improvements over the May 2011 edition, but seems not to have team Ist / IInd. Perhaps your next edition will include this.

    If I am wrong, and your tough group definition already includes this, a thousand apologies, and I am very happy.

  • Gerry_the_Merry on February 4, 2012, 6:20 GMT

    Dear Ananth, You had mentioned that the run-weighted BPI incorporates Team Ist / Tem IInd delta. I wish to clarify from you if the BQI incorporates the team Ist / team IInd differentials, which as we found in one of your previous articles, was as high as 14% for top 7 batsmen. My apologies if i am raising it too often, but as of now I am unclear if this is incorporated in BQI, and hence if the tough group figures reflect this factor. Would be nice if you dropped a couple of lines explaining if you have done this, and if yes, how and if no, why not. [[ The code is given below. Pl make what you can of it.

    if (inns ==1 || inns==2) ha_wt=0.95;
    else                     ha_wt=1.05;
    bpi=mat[k]->m.bpi[bowinns];
    jj=mat[k]->pd[inns][j].player;
    psum[jj]->pb_wted_runs+=ha_wt*bpi*mat[k]->pd[inns][j].batruns;
    Ananth: ]]

  • Vikram on February 1, 2012, 12:43 GMT

    Hi Ananth, I have a couple of long flights coming up and wanted to see if I could get some data to play around with. While you have provided the BowlerPitchIndex, it doesn't have the names of the players who played in it. What I am asking for is cross table with players on Y axis and matchId on the X axis. That way I can do a more detailed analysis of each player against teams or on a time scale. For example, performance of batsmen against West Indies from 1976 to 1988, or Tendulkar across different time ranges. Let me know if that's possible. [[ Vikram I am sorry I copuld not reply earlier. I was caught up on my next article. I have something in the pipeline on what you asked for. Ananth: ]]

  • Ravi on February 1, 2012, 10:18 GMT

    Ananth, a very good article. Kim Hughes, Botham, G Vishwanath, May et al indeed deserve their high places. I have 2 questions. We saw in one of your recent articles how well MPVaughan has done against top attacks. Why does he suffer in this article? Where do Umrigar, Ranji, Duleepji, Trumper, Hobbs, sutcliffe stand? I think we should look at the batsman’s peer comparison (runs & avg compared to exact contemporaries). This will help rationalise batsmen with fewer aggregate but majority tough group runs (K Hughes etc- no disrespect for Hughes). This will also give credit to long careers (esp those straddling hard and easy bowling eras) and therefore high aggregate runs, Bradman, SRT, Sunny, Ponting, Waugh, Javed, Gooch etc. A big ask. What do you think? [[ Ravi, Vaughan's figures have not been as good, say, Atherton's, Buth then they belong to different generations. However his figures are better than KP and Strauss. The peer comparison has been done in an earlier article. http://blogs.espncricinfo.com/itfigures/archives/2009/08/test_batsmen_peer_players_comp.php http://blogs.espncricinfo.com/itfigures/archives/2009/08/following_up_on_the_test_batsm.php However these are over 2 years old and I may re-do these sometime now. Ananth: ]]

  • Ananth on January 31, 2012, 11:57 GMT

    I have completed some nice weighted batting averages. These have all been included in the PlayerGroup Excel sheet and the same has been uploaded. Please download and check these. The following two calculations have been done. 1. The first is a batting average weighted by (dismissed) innings for the three groups with the middle group as the base. All values are batting averages. The final value will be slightly lower than the career batting average since the first (tough) group is always be going to be less productive than the easy group. This is very indicative of the way the batsmen performed in difficult conditions. 2. This alternative is very interesting, since this takes away the concept of groups, not liked by some because of the seemingly arbitrary fixing of the same, altogether. I have used the Run-weighted BPI and the mean BPI to adjust the batting average. This adjustment is minimal and is probably the best adjustment of the lot. There are no abrupt changes nor is there any arbitrary work. My thanks to Anshu who has done bulk of the work on these.

  • Rahul Patidar on January 31, 2012, 9:49 GMT

    That would be great Anantha!!! Do you mind sharing any single source of match scorecards in text format?

  • AD on January 31, 2012, 9:38 GMT

    Anantha, As it stands: 1) If we change the goal-post (arbitrary marker) between the "Tough" and "middle" groups we can have any of 3 results: 1) No change in figures of the batsmen 2)Slight change 3)Considerable change. It should be relatively easy to move this goal-post 10/20/30% to either side and check which of the above 3 holds. [[ AD Pl see my recent comment and the uploaded file. First, the group split is not as arbitrary as you make it to be. I have looked for normal distribution. Anyhow the effect is minimized when the weighting takes place. Finally the alternate method completely ignores the group aplit. Ananth: ]] 2) Even at a casual glance at the above table there are over a dozen batsmen with better figures than the modern day Indian batsmen in the tough group. To pick any one particular West Indian batsman and compare to one particular Indian batsman to confirm some pre-existing hypothesis would strike most people as odd.This is also what I pointed out to Regi. [[ I repeat again, THERE IS NO PRE-EXISTING HYPOTHESIS. I do the analysis and post these results. That is all. Anyhow who is to say that the 1980s West indian batsmen are inferior to the current Indian batsmen. For that matter who is to say the the 1980s Indian batsmen were inferior to the current Indian batsmen. The top two places in the Career runs table are occupied by two current indian batsmen. However these two occupy the 14th and 22nd positions in the Batting average table. Finally let me say one more thing. I AM NOT DOING ANY COMPARING. I have done some useless work and posted the tables. The readers can and should interpret these in their own ways. Ananth: ]]

  • Aditya Nath Jha on January 31, 2012, 5:45 GMT

    i checked on the entire list of 261 batsmen - the weightages don't change!

  • Gerry_the_Merry on January 31, 2012, 5:29 GMT

    I think reasons why Richards and Lloyd feature in all tables under composite average is that 1) the WI '80s team was not a high scoring team, with usually 2-3 batsmen generally happy to play bailout / anchors rather than the whole team firing a la Aus in the 1999-2004 period and 2) the bowling was murderous.

    A simpler method would be to take the ratio of simple batting average / runs weighted BPI and sort on this index. Am not allowed to download files at work, must try at home.

  • Aditya Nath Jha on January 31, 2012, 4:40 GMT

    yes, anantha - i worked on table 1 (39 highest run getters plus flower). let me work it out for the entire 261 batsmen and see if the weightages change significantly (i don't think they will).

  • Gerry_the_Merry on February 4, 2012, 7:39 GMT

    Dear Ananth, So as I understand from this, the ha_wt is influencing BPI to get to run-weighted BPI, but is not influencing the BPI for the purpose of the tough group classification. BPI is nice to know, but the real deal is the tough group runs definition.

    I will not press this point further now. I have weighted for 8 months to see the tough group calculations. This edition has many many improvements over the May 2011 edition, but seems not to have team Ist / IInd. Perhaps your next edition will include this.

    If I am wrong, and your tough group definition already includes this, a thousand apologies, and I am very happy.

  • Gerry_the_Merry on February 4, 2012, 6:20 GMT

    Dear Ananth, You had mentioned that the run-weighted BPI incorporates Team Ist / Tem IInd delta. I wish to clarify from you if the BQI incorporates the team Ist / team IInd differentials, which as we found in one of your previous articles, was as high as 14% for top 7 batsmen. My apologies if i am raising it too often, but as of now I am unclear if this is incorporated in BQI, and hence if the tough group figures reflect this factor. Would be nice if you dropped a couple of lines explaining if you have done this, and if yes, how and if no, why not. [[ The code is given below. Pl make what you can of it.

    if (inns ==1 || inns==2) ha_wt=0.95;
    else                     ha_wt=1.05;
    bpi=mat[k]->m.bpi[bowinns];
    jj=mat[k]->pd[inns][j].player;
    psum[jj]->pb_wted_runs+=ha_wt*bpi*mat[k]->pd[inns][j].batruns;
    Ananth: ]]

  • Vikram on February 1, 2012, 12:43 GMT

    Hi Ananth, I have a couple of long flights coming up and wanted to see if I could get some data to play around with. While you have provided the BowlerPitchIndex, it doesn't have the names of the players who played in it. What I am asking for is cross table with players on Y axis and matchId on the X axis. That way I can do a more detailed analysis of each player against teams or on a time scale. For example, performance of batsmen against West Indies from 1976 to 1988, or Tendulkar across different time ranges. Let me know if that's possible. [[ Vikram I am sorry I copuld not reply earlier. I was caught up on my next article. I have something in the pipeline on what you asked for. Ananth: ]]

  • Ravi on February 1, 2012, 10:18 GMT

    Ananth, a very good article. Kim Hughes, Botham, G Vishwanath, May et al indeed deserve their high places. I have 2 questions. We saw in one of your recent articles how well MPVaughan has done against top attacks. Why does he suffer in this article? Where do Umrigar, Ranji, Duleepji, Trumper, Hobbs, sutcliffe stand? I think we should look at the batsman’s peer comparison (runs & avg compared to exact contemporaries). This will help rationalise batsmen with fewer aggregate but majority tough group runs (K Hughes etc- no disrespect for Hughes). This will also give credit to long careers (esp those straddling hard and easy bowling eras) and therefore high aggregate runs, Bradman, SRT, Sunny, Ponting, Waugh, Javed, Gooch etc. A big ask. What do you think? [[ Ravi, Vaughan's figures have not been as good, say, Atherton's, Buth then they belong to different generations. However his figures are better than KP and Strauss. The peer comparison has been done in an earlier article. http://blogs.espncricinfo.com/itfigures/archives/2009/08/test_batsmen_peer_players_comp.php http://blogs.espncricinfo.com/itfigures/archives/2009/08/following_up_on_the_test_batsm.php However these are over 2 years old and I may re-do these sometime now. Ananth: ]]

  • Ananth on January 31, 2012, 11:57 GMT

    I have completed some nice weighted batting averages. These have all been included in the PlayerGroup Excel sheet and the same has been uploaded. Please download and check these. The following two calculations have been done. 1. The first is a batting average weighted by (dismissed) innings for the three groups with the middle group as the base. All values are batting averages. The final value will be slightly lower than the career batting average since the first (tough) group is always be going to be less productive than the easy group. This is very indicative of the way the batsmen performed in difficult conditions. 2. This alternative is very interesting, since this takes away the concept of groups, not liked by some because of the seemingly arbitrary fixing of the same, altogether. I have used the Run-weighted BPI and the mean BPI to adjust the batting average. This adjustment is minimal and is probably the best adjustment of the lot. There are no abrupt changes nor is there any arbitrary work. My thanks to Anshu who has done bulk of the work on these.

  • Rahul Patidar on January 31, 2012, 9:49 GMT

    That would be great Anantha!!! Do you mind sharing any single source of match scorecards in text format?

  • AD on January 31, 2012, 9:38 GMT

    Anantha, As it stands: 1) If we change the goal-post (arbitrary marker) between the "Tough" and "middle" groups we can have any of 3 results: 1) No change in figures of the batsmen 2)Slight change 3)Considerable change. It should be relatively easy to move this goal-post 10/20/30% to either side and check which of the above 3 holds. [[ AD Pl see my recent comment and the uploaded file. First, the group split is not as arbitrary as you make it to be. I have looked for normal distribution. Anyhow the effect is minimized when the weighting takes place. Finally the alternate method completely ignores the group aplit. Ananth: ]] 2) Even at a casual glance at the above table there are over a dozen batsmen with better figures than the modern day Indian batsmen in the tough group. To pick any one particular West Indian batsman and compare to one particular Indian batsman to confirm some pre-existing hypothesis would strike most people as odd.This is also what I pointed out to Regi. [[ I repeat again, THERE IS NO PRE-EXISTING HYPOTHESIS. I do the analysis and post these results. That is all. Anyhow who is to say that the 1980s West indian batsmen are inferior to the current Indian batsmen. For that matter who is to say the the 1980s Indian batsmen were inferior to the current Indian batsmen. The top two places in the Career runs table are occupied by two current indian batsmen. However these two occupy the 14th and 22nd positions in the Batting average table. Finally let me say one more thing. I AM NOT DOING ANY COMPARING. I have done some useless work and posted the tables. The readers can and should interpret these in their own ways. Ananth: ]]

  • Aditya Nath Jha on January 31, 2012, 5:45 GMT

    i checked on the entire list of 261 batsmen - the weightages don't change!

  • Gerry_the_Merry on January 31, 2012, 5:29 GMT

    I think reasons why Richards and Lloyd feature in all tables under composite average is that 1) the WI '80s team was not a high scoring team, with usually 2-3 batsmen generally happy to play bailout / anchors rather than the whole team firing a la Aus in the 1999-2004 period and 2) the bowling was murderous.

    A simpler method would be to take the ratio of simple batting average / runs weighted BPI and sort on this index. Am not allowed to download files at work, must try at home.

  • Aditya Nath Jha on January 31, 2012, 4:40 GMT

    yes, anantha - i worked on table 1 (39 highest run getters plus flower). let me work it out for the entire 261 batsmen and see if the weightages change significantly (i don't think they will).

  • Aditya Nath Jha on January 30, 2012, 13:37 GMT

    And these are the batsmen whose weighted ave drops to less than 90% of their career average.

    Hayden M.L (.88) Ganguly S.C (.88) Langer J.L (.88) Jayawardene M (.87) Smith G.C (.87) Mohammad Yousuf (.86) Laxman V.V.S (.86) Sangakkara K.C (.85) Dravid R (.84) Tendulkar S.R (.84) Ponting R.T (.83) Bradman D.G (.82) Sehwag V (.78) Hammond W.R (.7) [[ Aditya I understand the methodology. However I do not get the numbers. The mean of the average itself for the 261 players is 26.58 for the tough group. So the RpI mean would be still lower. How did you get 31.09. By any chance are you taking a subset of the players selected. Ananth: ]]

  • Aditya Nath Jha on January 30, 2012, 13:31 GMT

    these are the batsmen whose weighted average either exceeds their career average or comes terribly close. Batsman (ratio of weighted ave to career ave)

    Atherton M.A (1.03) Gower D.I (1.01) Gooch G.A (1.01) Flower A (1) Stewart A.J (1) Cowdrey M.C (.99) Waugh M.E (.99) Haynes D.L (.99) Richards I.V.A (.99) Chappell G.S (.99) Border A.R (.98) Lloyd C.H (.97)

  • Boll on January 30, 2012, 11:09 GMT

    @shrikanthk. thanks for the wonderful footage. Unfortunately I haven`t yet had time to sit down and give this analysis the attention it deserves - so much to consider. The Aussie resurgence, Pakistani heroics, and some good signs for the Kiwis have been keeping me rather busy. Cheers all [[ In the Ratings work I do for "Idea" I also do a past 12 months analysis of all players and teams. Three months back England had a massive lead at the top. Slowly it got whittled away by Pakistan and in the latest Ratings they have overtaken England at the top. For that matter Australia's wonderful run has moved them into second place. And India has had a freefall and are at no.8. Ananth: ]]

  • Rahul Patidar on January 30, 2012, 10:57 GMT

    Hi Anantha,

    It was an absolute pleasure reading the article. In-fact, this being the first time I read your blog, I went back and read a couple more. I am thrilled to know that someone is already involved in doing these analytic pieces on cricket data. I have myself been trying to work on data I could get hold from the internet; and then try and do some predictive modelling. But I have had a lot of trouble getting/creating a query-able database. Internet data is difficult to import; or maybe I don't have the tolls and techniques to do the same. I would love to hear back from you regarding some easy ways to create a database for myself, which can be used to do more interesting work. Thanks, Rahul [[ Rahul, I use my own proprietary database created and maintained over the past 15 years with the base file being public domain scorecard text files. I have over 300 'C' programs to handle all this work. I am a single-person band doing everything. If I have to start again now, I would not even think of embarking on this. It would be virtually impossible for one person to do this. Best way is to extract data using Statsguru of Cricinfo. I was thinking of making my database and retreival programs available to users. However the updating process stumped me. I am still working on it. Currently I am thinking of making available an Excel file or CSV file containing the scorecards of all Tests. I have to work out all details of same, including updates. Ananth: ]]

  • Aditya Nath Jha on January 30, 2012, 10:50 GMT

    i have used the following method to determine the weighted average. First, the mean RpI for the 3 groups are 31.09, 41.68 and 58.16 (the median are 35.47, 44.45, 62.79). Taking the mean, 1 run against the tough group is equal to .75 runs against the middle group is equal to .53 runs against the weak group. With this, the weightage for the 3 groups become 43.85%, 32.71% and 23.44%. Then the average in each group is multiplied by its weight and summed up. I have not factored in not outs, which will have a minimal impact. The final "weighted" average - even for Don - has to be less than career average for the simple reason that everyone averages significantly less than career average against the tough group. I have not worked on %ge innings played or run scored individually as i have worked directly on averages. [[ Aditya I am going to publish this without any comments so that the others can send in their comments soon. I will look at it afterwards. Ananth: ]]

  • Aditya Nath Jha on January 30, 2012, 10:42 GMT

    here's my list of weighted average for the batsmen bradman 82.41 chappell gs 53.11 sobers 51.84 kallis 51.83 flower 51.62 lara 50.65 miandad 49.67 richards 49.57 border 49.42 gavaskar 48.02 sanga 47.58 waugh s 47.35 tendulkar 47.00 chanderpaul 46.44 boycott 45.84 lloyd 45.11 inzy 45.07 gower 44.83 yousuf 44.83 hayden 44.81 dravid 44.41

  • Sifter on January 30, 2012, 8:58 GMT

    Ah cool, I'm glad the boffins could expand on my idea with a bit more mathematical accuracy. And thanks for correcting me on those numbers Anshu N Jain - that makes a bit of difference! The weighted average makes more sense than dividing by 3, and helps to minimise those small sample problems, so is more mathematically sound. That said, I am a little disappointed that a guy like George Headley does better out of using the weighted method, he may be 'The Black Bradman' but he didn't play much in tough conditions and when he did he only averaged 25. Yet that is glossed over a bit by weighting the averages. But of course, he only had 8 tough innings - it's just as easy to argue he was unlucky in that he didn't get more chances or maybe he got some bad calls in those 8 innings. That's the joy of small samples I guess...Anyway, my 2 cents is that anyone who didn't average over 30 in the tough group doesn't deserve to be a top 10-20 all-time player. That's just my bias :)

  • Vikram on January 30, 2012, 8:42 GMT

    While some modifications are required to take care of the double counting, one analysis possible is to compare batsmen from one team from one age period - Say the Fab Four from India. So Dravid's poor performance (vis-a-vis the other 3) in the middle group is surprising. This analysis also confirms some hunches and shatters others. Azhar's performance in the tough group is an eye-opener for me. However, the sweetest stat is Robin Smith's performance - 34.1% runs at 34.4 in the hardest group. If he had the normal distribution of innings across the three categories, his stats would have matched his grace, style and strength of character. What a batsman, what a square cut. [[ For me the eye-opener was the much-maligned Ramprakash and Hick. They might not have moved the world but sure faced tough conditions more often than others. Ananth: ]]

  • Nitin Gautam on January 30, 2012, 6:56 GMT

    Anantha

    Thanks for giving a detailed comparison between the 2 disgraceful 4-0 drubbings. My opinion is that maybe Aus was little better than what they showed in Eng, but definitely this will have more impact in Indian cricket. I seriously wish some better sense prevails & IPL is cut short to once in 2 years, inclusion of sporting pitches, more under 19,22 tours to SF,ENG,AUS & robust infrastructure of FC cricket & most imp of all better handling of players. [[ Even though the England series was about 2% worse than the Australia one, the England disaster had mitigating circs: somewhat bowler-friendly pitches, injuries, lack of preparation et al. The Aussie fiasco had no such excuses. As such I think it was the greater disaster. But who cares. Even a qualification to the Tri-series Finals will be enough to paper over the chasm. And to hear Dravid say that he is nearer the end of his career than the beginning is an insult to our intelligence. And to hear Laxman's deafening silence is saddening. SRT maintains a Buddha-like stance. Should not the three come out with a joint statement talking about passing the baton to the youngsters and that they would work with the Board in effecting a smooth change-over. Ananth: ]]

    Regarding your analysis, with each passing days, these blogs are becoming richards, bradman types for which nothing new can be said. so i will settle with more modest "well done". Regarding SRT who happens to be my most fav player bt i realize the greatness of others in equal measure. cricket is such a tricky sport where statistical analysis can never show the complete picture though it brings a new dimension every time your blog comes across.

  • Anshu N Jain on January 29, 2012, 11:43 GMT

    {I will give an alternate interpretation of Group runs as (Group RpI * Group Completed innings)}

    Apologies to the other readers for going on about this!

    You said Group runs = Group RpI * Group completed innings

    This is okay only if, by Group RpI is mean "Group Runs per Completed innings", and not just "Group Runs per Innings". Hope this clarifies.

    As i had mentioned before, to derive the Group weights, either use All innings or use Completed innings, in both numerator and denominator. A mixed use will be biased towards/unfair to batsmen who have remained not out more often than the others (depending on how you effect the mix). [[ Anshu I use innings in only one manner. It was your use of "completed" innings which made me use the term. As far as I am concerned, an innings is one in which a batsman walks to the ground, that is all. Other than that I only use the term "not outs". Nothing else. From that point of view I have been consistent all along. F2/J2/N2 are sums of innings. G2/K2/O2 are sums of Runs. So the weighted RpIs in H2/L2/P2 are clearly RpI values. Now coming to the batsman calculations (take U2), It is Sum of (Group1runs-1 x RpI-3/RpI-1 + Group2Runs x RpI-3/RpI-2 + Group3Runs x RpI-3/RpI-3) / (Sum of innings). Where is the inconsistency in this. All innings refer only to "commenced" innings. And I do not want to ever use the term "completed" innings. It is a misnomer. Clarke's 329 is a completed innings. The impact of Not outs is always there. What is needed is consistency in computations. Another alternative computation will be to use Average right through and use (Inns - NotOuts) throughout. Really not necessary. Maybe players like Hussey, Dhoni will gain. Ananth: ]]

  • Anshu N Jain on January 29, 2012, 11:02 GMT

    Ananth,

    Your calculation of the RpI is perfectly all right.

    I have a problem with the calculation of the weights though.

    Group runs are nothing but (Group avg * Completed Group innings). [[ Anshu, let me split hairs with you a little bit. I will give an alternate interpretation of Group runs as (Group RpI * Group Completed innings). Then all numbers are RpI based. And I use completed innings in both numerator and denominator. Ananth: ]] So, your calculation implies Completed innings in the numerator and All innings in the denominator. What you end up with is not a weighted "average" but a weight nonetheless, which subsumes the number of N.O.s, which vary significantly across batsmen.

    Ultimately, when you weight the runs with the appropriate ratios, it punishes batsmen who have remained "not out" more often than the others, in the final calculation of the RpI measure.

  • shrikanthk on January 29, 2012, 7:15 GMT

    Some clips to interest the curious fans out here -

    This clip has some strokes from the two Bradman innings chosen by Ananth - 270 at Melbourne and 212 at Adeleide.

    http://aso.gov.au/titles/documentaries/bradman-era/clip2/

    A hook off Voce in the innings of 270 and a leg glance off Hammond during the 212 at Adeleide.

  • Anshu N Jain on January 29, 2012, 5:06 GMT

    {I have used the completed innings and the three super-group weighted averages are 26.58, 36.13 and 49.61. These are about 10% lower, approximately the not outs component equivalent.}

    Ananth, this is because you have used the Completed innings in the numerator (sumproduct) and ALL innings in the denominator (pushing the denominator higher by the 10% you mention). This distorts the weighting in my view, because this will then be a queer mix of actual average and runs per innings. [[ I am not sure about this, Anshu. In fact you will see that instead of using inns*avge I have used the following formula. This refers only to determination of the three group values. sum(group runs) / sum (group inns). So this is in reality three RpI values. Hence the ratios are also in the same measure. That I agree. Now for the final formula for each batsman, Suppose I replace the current one with (grp1runs*grp1ratio+grp2runs*grp2ratio+grp3runs*grp3ratio)/(total inns). Everything will be in the same dimension and the final value will be a RpI measure. Tendulkar becomes 61.33 and Bradman, 103.88. I have added a colum and uploaded the same. Ananth: ]]

  • Gerry_the_Merry on January 29, 2012, 4:59 GMT

    Ananth, what I am proposing will magnify the difference.

    Take the MCG and SCG tests. The MCG test per my method will be (205+221+142+69)/20 = 31.8. SCG is 68.7 as you have computed.

    However, the T7 B3 yields 58 and 103, from your XL file. This is a less stark difference. It is a matter of what fits better. The two methods must ultimately yield similar results. [[ One thing I agree. The numbers are not comparable. So I get the feeling that both methods might come out with similar groups. If 103 is a very flat track 58.4 would be a middle one. Similarly if 68.7 is taken as a flat track 31.8 will be middle level one. My concern also is the exclusion of the sixth wicket partnership which is between a top batsman and no.7 batsman. In all the computations, Dhoni has remained out. Not that he contributed anything. Let me also say that I am comfortable with the top-10 partnerships, as suggested by Arjun. Only thing is that I have to do some scaling to achieve the correct weight before doing the GM. Finally let me say this. Because same numbers are used, all roads lead to the same destination. Rome or Mumbai or LondonWest/Nottingham/Birmingham/LondonSouth or MCG/SCG/WACA/AdelaideOval Ananth: ]]

  • Gerry_the_Merry on January 29, 2012, 4:43 GMT

    For the composite average, the correct method is to leave out using % innings in the three groups as weights.

    The simple reason is that if there are two batsmen, who have identical averages in each of the three groups, say 35, 45 and 65, they must have identical position in the composite average table. Of course, the raw averages should be multiplied by the factor of 49/26 and 49/36 and 1 respectively. [[ I will take two extreme examples of your pair of imaginary batsmen. Batsman 1: 1 inns at 35, 50 inns at 45 and 100 inns at 65. Batsman 2: 100 inns at 35, 50 inns at 45 and 1 inns at 65. Are you of the opinion that the two should have the same weighted average. Doesn't seem logical. This is where the number of innings comes in. That is the weighting factor. Ananth: ]]

    It should not matter if they have had different exposures to the different groups in terms of % innings. This variable is not in their control. The aim should be to strip the composite performance of the "opportunity effect".

    So if one batsman has had 20%, 50% and 30% innings exposure to the three groups, whereas the other has had 50%, 30% and 20%, they should both have the same placing in the composite average table.

  • Anshu N Jain on January 28, 2012, 19:06 GMT

    While batting: Windies have faced the best bowling attacks on average (lowest BQI, 34.60) and Lankans the poorest (Highest BQI, 36.35). India ranks 3rd from the top. While bowling: Aussies have delivered the best bowling attacks on average (lowest BQI, 32.46) and Kiwis the poorest (Highest BQI, 38.85). India ranks 3rd from the bottom. If we take the difference of the "Batting BQI" and "Bowling BQI", together with the overall Win:Loss ratio for each team as two distinct data sets, it is seen that there is extremely high correlation between the two (coeff 0.94). Doing the same for the difference of RSI, the coeff of correlation is just 0.11. Of course, RSI is a joint outcome of the two teams' in-match performance. Now, the sample size may be too small (just 8), but it does lend support to the assertion that the BQI is the pre-eminent determinant of team performance and result achievement. Ananth, your views? [[ Anshu, Leaving this off for the time being. You have used the number of innings played and average in determining the group weighted average. Hence your numbers are slightly higher. As you yourself have pointed out only the completed innings should be used. I have used the completed innings and the three super-group weighted averages are 26.58, 36.13 and 49.61. These are about 10% lower, approximately the not outs component equivalent. I have completed the batsman values as per this set of values and UPLOADED THE DOCUMENT. Now the final group-weighted averages are slightly nearer to the batting averages. Bradman is 117+ as against 120+. I have also compared this weighted average to the batting average. The range is from 110% for Hammond to 156% for Ramprakash. There is a strong correlation to the group distributions. Sifter/Ram: Your comments will be appreciated after perusing the new tables. Ananth: ]]

  • Gerry_the_Merry on January 28, 2012, 17:51 GMT

    Ananth, perhaps to improve objectivity on the PQI/RSI - May I propose the following please - Take the partnerships for first 5 wickets, i.e. until the 5th wicket falls, for the entire match, and average. Hence there will be a maximum of 20 such partnerships. I dont see any reason that we should only take top 7 partnerships (or 10 for that matter).

    If it is like Sydney test of Jan 2012, take 5+4+5 = 14 partnerships and average to get RSI.

    There will be stray cases of nightwatchman / exceptional #7 (Gilchrist) / exceptionally insipid batting boosting opposition batsmen's runs' value (e.g. 221 by Ponting in Adelaide) etc, but generally across 2100 tests, this should give a pretty good feel.

    Finally the aim is to get a good feel of what specialist batsmen scored in a test, by looking at the partnerships, and all innings in a test.

    Do you think this will work? [[ What you are prposing is very similar to the T7-RpI we started with except that it is closer to T6-RpI. Take SCG-2012. The T6-RpI is (101+637+271)/18=56.1. The T5-Ptships is (96+659+276)/15=68.7. The partnership values will always be higher since the divisors are 1 less.So I don't see any difference. Now let us take the T7-B3 values. Only 6 partnerships and 3 lower values are taken because the number of innings played is only 28. The T7-B3 avge is 103.1 and this falls to the lowest pitch group, one which is the easiest to bat on. Isn't it what it was. Even poor Indian batting scores 400 and Australia go on the rampage. The overall match RpW is 52.1 and match BpW is 83.3, all pointing to a very good wicket. Ananth: ]]

  • Gerry_the_Merry on January 28, 2012, 17:41 GMT

    Anshu, I dont see the logic of comparing across groups with a composite average, even if the component averages are scaled up according to the global group averages.

    See Charit's comment and Ananth's response. Look at the first table. Travelling down, till we reach Border, each batsman's easy group averages are comfortably higher than 2x the tough group averages. Why 2x? Because you have computed 28 and 56 as the global tough and easy group averages.

    I have ignored the mid group merely for illustrating the argument clearly - even in this composite index, there will be batsmen benefiting from the "mix effect".

    I for one am perfectly content looking at tough group averages. Perhaps some tweaking can be done to improve definition, but the tough group averages represent what we looked for in May 2011 - against the toughest attacks, who is the best...? [[ Gerry, this is only an alternative way of looking. What it does is to give weight to the % of runs scored against the tough groups, the average against the difficult of groups and negates the arbitrary cut-off problem. Maybe a revision of the formula will get the weighted averages to nearer the playar's career averages. Leave Richards, Lara, Tendulkar, Bradman, Ponting et al out of this. What this brings to light is to put in perspective the runs scored by lesser known batsmen in tough conditions. My own opinion of Ramprakash, Botham, Border, Boycott, Ranatunga, May, McGlew, Fleming et al has gone up. At least what this analysis should do is to take away the focus from the always-discussed batsmen. Ananth: ]]

  • Anshu N Jain on January 28, 2012, 15:49 GMT

    Ananth,

    This is what I did: Derived the weighted average "Average" of the 3 groups individually by the formula:

    Sumproduct(BatAvg for each batsman * No. of Innings for the batsman)/Sum(No. of Innings for each batsman)

    This gave the following weighted average Averages Tough: 28.5, Middle: 39.6, Easy: 56.7

    Then, for each batsman, weighted the average within each group by the ratio "Easy/Group Avg" to arrive at the modified average

    For Bradman, modified avg = ((53.7*56.7/28.5*11)+(98.91*56.7/39.6*23)+(113.08*56.7/56.7*46))/(11+23+46) = 120.5

    Ideally, should be using Completed innings only instead of all innings. Have done this as well. The difference is insignificant on the whole, but gives due to batsmen who have more N.O. innings against the Tough and Middle groups.

    Shall I mail you the MS Excel file? [[ Anshu No, not really necessary. I will incorporate your formula and then upload the file so that I get familiarized with it and everyone can get that. Sifter Ram's spark was moved forward by you. However the division by 3 and the addition of averages would certainly have had problems because of the arbitrariness as pointed out by AD. However because Anshu has done the weighting, my preliminary view is that the arbitrariness disappeasr. The number of innings comes in. Ananth: ]]

  • Ananth on January 28, 2012, 13:17 GMT

    Anshu: I have uploaded the PitchBow Excel sheet with Home Team and Result. Sifter: I have done the Mean for the Batting average and uploaded the Player file.

  • Anshu N Jain on January 28, 2012, 10:48 GMT

    cont..

    6 Headley 76.1 7 Kallis 75.9 8 Hutton 75.4 9 Weekes 74.2 10 Lara 73.8

    Other notables:

    13 Richards 72.8 14 Miandad 72.6 17 Border 72.1 21 Tendulkar 70.6 24 Waugh 69.4 28 Chanderpaul 67.8 42 Dravid 66 43 Ponting 65.9

  • Anshu N Jain on January 28, 2012, 10:38 GMT

    cont.

    What I did, e.g., was using the weighted average of the 263 players (account for 60%+ of all test runs scored), together with your formula's elegant interplay of these averages (denominator being weighted average against the easy group), and then weighted them by the number of innings played against each group. Finally, dividing this by total number of innings played.

    The results are interesting: 1 Bradman - 120.5 2 Barrington - 78.8 3 Graeme Pollock - 77.9 4 Chappell Greg - 77.2 5 Sobers - 76.8 [[ Anshu I have replicated Sifter's formula as given and got the numbers. Can you explain yours, with Bradman's figures. I tried something and the numbers did not match. Ananth: ]]

  • Anshu N Jain on January 28, 2012, 10:31 GMT

    Thanks for posting the detailed tables Ananth!

    My first comment with the quick stat was to get the juices flowing. There's enough and more in the two tables to keep one occupied for hours on end :-), which is what I am doing at the moment, and will have some comments to share soon!

    I do have a request: if it is possible (probably readily available), could you, in the BowlerPitchIndex table (for each of the 7400+ innings), also include the following: 1. Home country 2. Match result

    @Sifter: Great idea to look at a composite average for comparison. The mean numbers that you use in your formula, though, are means of % of innings played against each group, and not batting averages.

    cont... [[ Yes. Those are the means of % of runs. Will post the revised tables within the hour. Ananth: ]]

  • AD on January 28, 2012, 9:51 GMT

    Regi Baptiste,Sifter , Anantha. Regi: Regret pricking your bubble. But several batsmen have done "better" than Tendulkar as per these tables.Picking any particular one and building a story around it doesn't really connote much. Infact , just about all modern day Indian batsmen have low figures in the first group. So,say Chanderpaul ,Jayawardene,Hayden ,Lara, Kallis, Inzy, Steve and Mark Waugh, Stewart, G.Smith are “ better” than them all? Me and Unni have suggested an alternative method in the previous blog. Also, the break up of these tables is entirely arbitrary. Change the goal-posts (table ranges) and you get different results. Re.the consistency, it depends on what time frames you chose to use. For eg.If you take till 2002/03 you will find Tendulkar ahead of Lara on practically every front. Lara's last 4 yrs included 3 great yrs and then a last year fade avg. in the low 40s inspite of a few big innings- pretty similar to what Tendulkar is now undergoing!

    Sifter: Am afraid your method wont work because of the reasons outlined to Regi. That is because it all depends on the arbitrary choosing of the goal-posts. Change the table categories- you change the avg. Per table etc.

    Anantha: You state “Arjun, I have always maintained that Lara had scored bigger and probably more significant innings but that Tendulkar was more consistent. This proves that. And there is a clear difference in averages which is reflected in the numbers.” If “This proves that” that means you too are using these tables to rationalise your stand-Then there are numerous other batsmen as mentioned above of whom the same would apply vis-a-vis Tendulkar. Why just Lara? Sometimes one feels that people base their judgements on a match highlights reels rather than looking at the entire match . Again, More tables would shed much more light. For eg. In a previous blog based on BQI alone had Richards with a very high average in the “Tough group”. But a closer look revealed most of his innings were clustered near the lower range of the table. Perhaps graphs for the top batsmen against BPI or BQI would be more revealing ! [[ Extremely disappointed to see your comment on my using the tables to prove a point or other. There is also an implication that the tables themselves have been prepared to support my ideas. This, despite, my accepting your and Unni's idea and my promise to come out with a later article. I would appreciate positive comments. Else please wait for the article based on your idea, as and when I do it. Ananth: ]]

  • Arjun on January 28, 2012, 8:47 GMT

    Ananth,

    this one is regarding methodology. It is incorrect to include low score just for the sake of normalizing. low scores by batsmen could be result of various factor; eg bad form, initial stages of career, opening the innings etc. Shaun marsh is a great example. All of his 6 innings during the series will be inculded according to your method. Pitch had nothing to do with it; just that he was in bad form.

    Thus i think top scores/partnership is the correct method. [[ Arjun For every single dismissal of Marsh I can point out to one caused by a great delivery or pitch. I will stop at one. Gambhir's first innings dismisaal off a steep rising delivery. The point is that whatever method we use we are likely to get similar figures. I am not going ton re-do excluding the low scores since that would throw the BPI calculation in a mess, Ananth: ]]

  • Regi Baptiste on January 28, 2012, 7:44 GMT

    Ananth, I am a bit disappointed that you did not comment on my earlier submission in which I suggested that arguably, the fairest comparison that could be made in cricket is a match up between Lara and Tendulkar; for the reason that they commenced their careers almost simultaneously - that is, 1989/90 and ended in the season of December 2007, the year when Lara retired. Hence they would have played against similar oppositions, on similar pitches, under the same rules, batting at the same position, etc. for a very long time. In other words, they were exposed for a long enough period to rather similar playing conditions and situations to justify a relatively sound match up, in terms of statistical fairness. Don't you think that if there should be any comparison of these two great gentlemen, that it should be done only using statistics from the period (1989/90 to 2006/07) when they competed against each other? Since Lara retired, there have been so many changes to the game, I think that cricket has entered into a new dispensation. So, while we are trying to do the impossible, that is, trying to find all sorts of fallible statistical scenarios to compare them with Bradman and others, why don't we just compare them on what they did in those 17 years? Isn't that the fairest way to go? [[ Because you yourself told me that I should not do any comparisons. So I did not comment. Any such discussions are out of place now. Ananth: ]]

  • WI FAN on January 28, 2012, 4:26 GMT

    Many fans of Brian Lara consider his 153* vs Australia, batting with the tail to win the game (while farming the strike) was the best innings he ever played and probably the best innings ever played by any batsman in the history of the game! .. [[ The Wisden-100 determined this to be the second best Test innings ever played, next to Bradma's 270. Ananth: ]]

    I mean he was batting with Walsh ! ! ! arguably the worst number 11 in the history of the game ! ! ! [[ No way. Martin, Maninder Singh, Chandrasekhar, Doshi, Reid and Valentine are there. Waslsh was a Bradman (okay, at least a Richards) comepred to some of these stalwarts. Ananth: ]]

  • shrikanthk on January 28, 2012, 3:16 GMT

    It's good to see Bradman's 212 getting a mention. It was played one the same ground where the 4-0 cremation concluded today - Adeleide Oval.

    It was one of his more defensive innings. England employed leg theory to contain him with Verity and company attacking his legs with a defensive field. He wore them down and still managed to score at a fair clip. A crucial innings in a rather close game.

    I remember one shot from that innings whose newsreels I watched in a documentary. Bradman leg-glancing Hammond to the fine-leg fence. If I'm not mistaken Hammond was bowling with his cap on! [[ I am singularly happy at that list. There are many wonderful innings, not all of them known. Ananth: ]]

  • Sifter on January 28, 2012, 3:10 GMT

    Hi Ananth, great number crunching! Just a follow up to Ram's post about combining all 3 averages. I used a method from the dataset which said the mean average of the 230-odd players in the tough group was 22.7, the middle group was 35.5 and the easiest was 41.8. So the formula I made aimed to weight each groups accordingly was: (Tough avg x 41.8/22.7) + (Middle avg x 41.8/35.5) + Easiest avg

    Top 10 then becomes: Bradman 109.46, Barrington 73.45, Hutton 71.48, G.Chappell 71.33, G.Pollock 71.31, A.Flower 69.82, Kallis 69.77, D.Nourse 69.53, Sobers 69.47, Harvey 68.98. Other notables were Lara in 11th spot with 68.59, V.Richards 17th 66.56, Tendulkar 28th 62.61, Clarke 36th 60.98, Gilchrist 37th 60.79, Ponting 61st 58.50, Hammond 86th 55.20 and Sehwag 106th 53.08.

    Small sample sizes for each group makes this analysis a little weaker though eg. Graeme Pollock only played 3 tough innings, Bradman only 11 tough, Nourse only 14 Medium innings. So some error would creep in there. [[ New and welcome look. Let me look at it in detail. Ananth: ]]

  • shrikanthk on January 28, 2012, 3:04 GMT

    Nice analysis!

    What i am saying is that if someone average 50 agianst Australia it should mean that he is a very gifted player so therefore he should always average more against bangladesh

    Charith: Cricket isn't such a simple game. If that were the case all players ought to do MUCH MUCH better in first-class cricket than in test cricket. That's not necessarily the case. Be it the Victorian era or the Williams-Middleton era, nearly all batsmen have found it near-impossible to average over 60 in ANY form of the game over an entire career - be it Test cricket, First Class, one-dayers or even high-class club/league cricket.

    Cricket is a one-ball game. It takes one ball to get out. It doesn't matter how "poor" the attacks are or how favourable the pitch is. Consistency in cricket is an impossible pipedream

    Only one man has managed to defy this natural law of cricket to a remarkable extent - that man was DG Bradman.

  • Ananth on January 28, 2012, 1:20 GMT

    Nitin, You had asked for comparisons between the two 4-0 results. Here we go. I am doing this a few minutes after Siddle was announced since I have to wait for the MOM announcement.

    Lord's      73.8 - 26.2
    Nottingham  81.9 - 18.1
    Birmingham  87.5 - 12.5
    Oval        80.3 - 19.7
         Avge   80.9 - 19.1
    Now for the Australian tour.
    MCG         71.8 - 28.2
    SCG         82.1 - 17.9
    Perth       81.1 - 18.9
    Adelaide    80.2 - 19.8
         Avge   78.8 - 21.2
    India just about managed to avoid this series becoming worse than the England series, which itself was the worse performance ever in Test history by a team. MCG helped a lot for this dubious achievement. However there is no doubting that this sequence of 8 Tests, with an overall score of 79.9 - 20.1 in favour of the opposition team is the WORST EVER OVERSEAS SEQUENCE, MINNOWS INCLUDED. This sequence is equivalent to (nearly) 8 "innings + 1 run" victories.

  • Ram on January 27, 2012, 22:09 GMT

    Great Analysis Anantha!

    So we have three averages for each player, the tough average, middle average and easy average. Is there a reasonable method to integrate the three averages and come up with an "effective career average", which can be compared to their career average, and can be used as one of the parameters to compare the players? A crude example of an effective average: E = (tough runs X 2 + middle runs + easy runs/2)/ Innings Played

    For Tendulkar, the above works out to E = (1684 X 2 + 5522 + 8226/2)/309 = 42.08

    For Lara, it is 54.73

    I am sure there will be a better method for computing E. [[ Very good idea. However the 2 and 0.5 are too drastic. You must appreciate that the grouping itself is rather arbirtrary and has ben dictated by the need to have similar numbers in Groups 5 & 4, between 4 & 2 and 3 having a third or so. We have to look at a better method. The Run-weighted BPI offers a good alternative. Ananth: ]]

  • milpand on January 27, 2012, 20:37 GMT

    * private * 'In the meantime' or simply 'Meanwhile' preferred over 'In the meanwhile'. * private * [[ Why "private". "Meanwhile let us look at the current method" looks and feels correct and has been corrected. Ananth: ]]

    I find this measure to be a major building block towards a higher purpose and thus agree wholeheartedly to 'read and interpret these numbers with care.'

    A filter for career runs > 6995, sorted by decreasing 'Tough Super groups as a % of Career average' reveals a familiar set of batsmen clustered right next to each other, at the very bottom, with only Langer and Hammond below them.

    Sobers G.St.A 0.56 0.94 1.47 Bradman D.G 0.54 0.99 1.13 Ponting R.T 0.54 0.90 1.30 Tendulkar S.R 0.53 0.97 1.25 Sehwag V 0.48 0.79 1.30

    As you have already mentioned, Mark Waugh leads this table:

    Waugh M.E 0.97 0.88 1.19 Richards I.V.A 0.86 0.95 1.27 Haynes D.L 0.84 0.94 1.34 Lloyd C.H 0.84 1.01 1.15 Gooch G.A 0.81 1.01 1.37 [[ Two unsung heroes, (the other) Waugh and Gooch straddle the three West Indian trio. Ananth: ]]

  • charith on January 27, 2012, 18:42 GMT

    dear ananth i love your work but please don't take this the wrong way. What i am saying is that if someone average 50 agianst Australia it should mean that he is a very gifted player so therefore he should always average more against bangladesh. (unless he doesn't apply himself well when batting against weak sides and costing his team the match) [[ Charith My sincere apologies for the aggressive tone of my response. The sarcasm was unwarranted. Ananth: ]]

  • Anshu N Jain on January 27, 2012, 18:12 GMT

    Quick stat:

    Of the players in this list of 263 with more than 50 innings against the Tough Super groups (there are 60 of them), Tendulkar's average against the Tough Super groups as a % of his Career average is the lowest (53%). [[ Another view, without assigning any minimum number of innings, is that Sehwag's tough-super-groups average is 24.67, 48.4% of his career average. Let us also salute the highest. Mark Waugh has an incredible 96.5% of his career average in the tough-super-groups category. What is amazing that Mark Waugh in fact averages only 36.9 in the middle group category. This from one who is said to have a care-free attitude. There was a lot of steel within. Ananth: ]]

  • charith on January 27, 2012, 14:40 GMT

    I think its really wrong to glorify batsmen who have higher percentages or higher averages against difficult opposition than others.It only proves that they were careless when facing easier opponents and therefore their respective team could have lost the match.Which in the end is all that matters. [[ I I have seen one crazy logic this is it. So we should not talk about someone's average of, say, 50 against Australia/West indies since the concerned batsman might have averaged only 40 against Bangladesh and might have cost his team the match. Then what is really required is an average of 30 against Aus/WI so that the concerned batsman could have averaged 80 against Bangladesh and ensured his team's win. My head spins. Ananth: ]]

  • Masud Vorajee on January 27, 2012, 13:35 GMT

    Jacques Kallis is such a gun...

  • Regi Baptiste on January 27, 2012, 13:20 GMT

    Ananth, Good work once again. However, please don't let onayone trap you into this Lara vs Tendulkar debate; or other players comparison debate with data that is taken from such wide and general domains like this. As one of the world's top statistical analysts, you know that for one to execute a genuine comparison of any two performers, one needs to narrow as much as possible, the data to those taken from performances carried out in the most 'like conditions' to which both subjects were exposed. Hence, as far as batsmanship in cricket is concerned, there is no better comparison that can be made (in terms of relative accuracy) than a comparison between Lara and Tendulkar; because they both began their careers around the same time. So, if you want the most genuine comparison, why don't you look at their figures between 1989 and the end of the season in December 2006 when Lara played his last test? Those were the 16 years when they played against similar oppositions, on similar pitches, with the same rules, etc. If you do so, then you would find out that it is a 'MYTH' for anyone to say that Tendulkar 'WAS' ever more consistent than Lara! If you do this analysis, you would also find out that no element of batting data showed that Tendulkar performed better than Lara when both competed during those 16 years. And I think this should bring closure to this Tendulkar-Lara better batsman debate.

  • Ranga on January 27, 2012, 12:24 GMT

    Another silent killer is Kepler Wessels, who made more runs against top bowling and lesser against others. An unheralded batsman, he has faced tougher bowling all through. Also my respect for Tony Greig grows, because he has done well against tough bowling, while facing sub-44 attacks throughout his career.

    One thing about these articles is that there is no superstar in these. This article gives credit to those who deserve in the right areas. In this article, Mark Ramprakash is the superstar. I dont think any other article would give these perspectives. It was so informative and has given different points of view and different paradigms to batting. Despite playing for the same team, literally, M Waugh has faced tougher bowling than his twin and of course, a funny Indian view is Kumble has faced tougher bowling than SRT, though their common tests coincide almost 100%. These perspectives are refreshing and pleasurable. So the theory of same team similar attack is not really true. [[ Even in the top-25 innings, there are well-known wonderful innings but also the innings from lesser-known-talked-about batsmen such as Amiss, Endean, Fleming, Bacchus, Gregory et al. Ananth: ]]

  • Ranga on January 27, 2012, 11:56 GMT

    Some interesting outcomes though. To average 35+ in the tough group needs some skills and application, Mark Waugh has perhaps, the most consistent streak among modern batsmen. Unlike many who feel moody guys like him, Lara, etc revel only when there is challenge and do not get motivated enough to perform when the challenge is not great, Mark Waugh shows remarkable consistency across the groups. Ditto with Lara (as Arjun has rightly put). To my knowledge, Lara has not really shown any difference in approach or attitude. It is just that some lesser bowlers have had him. But Lara has faced far more difficult bowlers than others on more occasions, not necessarily an outcome of his weak team.

    Finally, abt the fab 3, all 3 have been products of tough 1st class structures. VVS, since 1992-95 had been a regular U-19 and A team player who toured Aus, Eng, etc. RD was also a product of tough 1st class structures. No substitute for preparation. Talent notwithstanding. [[ Ranga Unfortunately we have multiple forms of cricket running parallel. The Test/ODI cricket stream. The IPL stream and the Ranji/FC stream. Almost no established Test player plays FC. The Bists of the world can only hope for the crumbs and with some the support and luck go to IPL. The first group are, of course, the stars of IPL. How can they play FC when that time can be used to participate in IPL. So where are we heading for. Today the talk is that Rohit Sharma is the saviour of all problems of mankind. Is he ??? Ananth: ]]

  • arjun on January 27, 2012, 11:10 GMT

    If we leave aside easy runs, only Richards and Tendulkar average above 45.00.(qualification 8000 test runs)

    Through your blog time and again we have known that lara has scored most of his runs against tough attacks/conditions; but this anaylsis reveals he has also flourised against easy attacks averaging 84.0. This reduces his average to 40.20 in Super + Middle group.

    Below is performance of India's Famous 6 in Top 2 groups.

    Tendulkar 7206 runs @ 45.32 Dravid 5478 @ 37.02 Laxman 3952 @ 35.59 Sehwag 2599 @ 34.20 Ganguly 3522 @ 34.53 Ghambhir 1118 @ 31.06

    Tendulkar has performed 20 % better than 2nd best Dravid. [[ Arjun, I have always maintained that Lara had scored bigger and probably more significant innings but that Tendulkar was more consistent. This proves that. And there is a clear difference in averages which is reflected in the numbers. Let us also look at the % of career runs. Lara's is just below 50. But look at Border. That is where Richards who had a career average of 50.xx and could easily gone below 50, if he had scored 41 fewer, really comes through. Ananth: ]]

  • AD on January 27, 2012, 10:28 GMT

    Anantha,

    We do indeed have some divergence now among players.However, still several similar groupings. I guess we will just have to wait till you attempt a discounting of batting and bowling quality one day.

    A couple of requests: 1) Would it be possible to have the BPIs per group?

    2) Also, too few groups result in distortions quite often.If I recall these results are rather similar to a previous blog when you analysed performance against only Bowling quality. In that analysis too a lot of performances were clustered around the end of a particular group- and the sharp cut-offs result in slightly misleading interpretations.

    As, such for a deeper perspective- It may be better to divide your groupings into 2 equal tables each. For eg the "Tough super group" may be divided into two equal groups (without naming them- though we may then make out the difference between Super-super tough groups and tough super groups). [[ AD, too much work. Last time I had 5 groups and 2 super-groups. THis time I have 5 groups and 3 super-groups. The only thing is that I have not shown all 5 groups. I can probably do a table with just the 5 groups, as I had done in the previous article in addition to what I have already uploaded. Ananth: ]]

  • b.c.g on January 27, 2012, 10:28 GMT

    great article b.t.w. Thanks

  • b.c.g on January 27, 2012, 10:27 GMT

    Both of fleming's innings were on flat pitches.Gooch & Jayasuriya too played theirs on pretty dead pitches.The bowling attacks they faced were exceptional however!!!!!!!!!!!!

    Also Lara & to some extent Kallis seem to be the best modern day batsmen averaging 37-38 in the tough group.

  • Gerry_the_Merry on January 27, 2012, 10:26 GMT

    Ananth, good work, but i am afraid that readers who are seeing this article only, will miss the methodology as most of it has come through reader comments in the earlier pieces. I would recommend strengthening the description in this article itself, and your follow up can then be easily interpreted.

    Surprised to find Laxman so low in the tough group averages. I thought building in team Ist and team IInd differences into the BQI would raise his average in the tough group (not that this is my ulterior motive), but it does not seem to have made any difference (27 is a miserable average)

    Would there be a way to portray 1) base numbers for the top 20 batsmen in tough group 2) what this changes to when incorporating pitch quality, which should then match your current results, so that the impact of pitch quality can be understood in isolation.

  • nastle on January 27, 2012, 10:24 GMT

    this seems much more informative than the first part. thanks. Can you explain how "run-weighted BPI" (or BQI, you seem to mix them) is calculated? Was also suprised not to find bradman in the top weighted table. Too few career runs? [[ This is somewhat like the weighted bowling average faced by batsmen in their careers. It is simply Sum of (Innings Runs x Innings BPI) ------------------------------------------------ Career Runs. It is of the order of 40 to 60. The BPI range itself is 8.89 to 91.80 (the GM) with a mean of 46.59. No Bradman faced too many ordinary attacks and the pitches were slightly more benign. Ananth: ]]

  • Vikram on January 27, 2012, 7:34 GMT

    Hi Ananth, again a great analysis, and those 25 innings are real gems. What this analysis proves is that 1970s and 80s were the worst time for batsmen as the bowling quality on average was very high. The bastmen in 1990s and 2000s had to face occasional high standard bowling units and in some cases excelled. It also shows that Lara's highs are unmatched in the present generation. Finally, let me have a look at the final table to see where Robin Smith is. For some reason, I always loved him. As for the Indian batsmen, it is difficult to think about them at the moment, given the disastrous performances. It will need a little time before I can get myself worried about Tendulkar, Dravid or Laxman again. Anyways, thanks again for the wonderful effort. [[ Vikram, my selection was pyrely a programmed one and had no personal tweaks. Si I am all the more happy to see that there so may outstanding efforts. Ananth: ]]

  • No featured comments at the moment.

  • Vikram on January 27, 2012, 7:34 GMT

    Hi Ananth, again a great analysis, and those 25 innings are real gems. What this analysis proves is that 1970s and 80s were the worst time for batsmen as the bowling quality on average was very high. The bastmen in 1990s and 2000s had to face occasional high standard bowling units and in some cases excelled. It also shows that Lara's highs are unmatched in the present generation. Finally, let me have a look at the final table to see where Robin Smith is. For some reason, I always loved him. As for the Indian batsmen, it is difficult to think about them at the moment, given the disastrous performances. It will need a little time before I can get myself worried about Tendulkar, Dravid or Laxman again. Anyways, thanks again for the wonderful effort. [[ Vikram, my selection was pyrely a programmed one and had no personal tweaks. Si I am all the more happy to see that there so may outstanding efforts. Ananth: ]]

  • nastle on January 27, 2012, 10:24 GMT

    this seems much more informative than the first part. thanks. Can you explain how "run-weighted BPI" (or BQI, you seem to mix them) is calculated? Was also suprised not to find bradman in the top weighted table. Too few career runs? [[ This is somewhat like the weighted bowling average faced by batsmen in their careers. It is simply Sum of (Innings Runs x Innings BPI) ------------------------------------------------ Career Runs. It is of the order of 40 to 60. The BPI range itself is 8.89 to 91.80 (the GM) with a mean of 46.59. No Bradman faced too many ordinary attacks and the pitches were slightly more benign. Ananth: ]]

  • Gerry_the_Merry on January 27, 2012, 10:26 GMT

    Ananth, good work, but i am afraid that readers who are seeing this article only, will miss the methodology as most of it has come through reader comments in the earlier pieces. I would recommend strengthening the description in this article itself, and your follow up can then be easily interpreted.

    Surprised to find Laxman so low in the tough group averages. I thought building in team Ist and team IInd differences into the BQI would raise his average in the tough group (not that this is my ulterior motive), but it does not seem to have made any difference (27 is a miserable average)

    Would there be a way to portray 1) base numbers for the top 20 batsmen in tough group 2) what this changes to when incorporating pitch quality, which should then match your current results, so that the impact of pitch quality can be understood in isolation.

  • b.c.g on January 27, 2012, 10:27 GMT

    Both of fleming's innings were on flat pitches.Gooch & Jayasuriya too played theirs on pretty dead pitches.The bowling attacks they faced were exceptional however!!!!!!!!!!!!

    Also Lara & to some extent Kallis seem to be the best modern day batsmen averaging 37-38 in the tough group.

  • b.c.g on January 27, 2012, 10:28 GMT

    great article b.t.w. Thanks

  • AD on January 27, 2012, 10:28 GMT

    Anantha,

    We do indeed have some divergence now among players.However, still several similar groupings. I guess we will just have to wait till you attempt a discounting of batting and bowling quality one day.

    A couple of requests: 1) Would it be possible to have the BPIs per group?

    2) Also, too few groups result in distortions quite often.If I recall these results are rather similar to a previous blog when you analysed performance against only Bowling quality. In that analysis too a lot of performances were clustered around the end of a particular group- and the sharp cut-offs result in slightly misleading interpretations.

    As, such for a deeper perspective- It may be better to divide your groupings into 2 equal tables each. For eg the "Tough super group" may be divided into two equal groups (without naming them- though we may then make out the difference between Super-super tough groups and tough super groups). [[ AD, too much work. Last time I had 5 groups and 2 super-groups. THis time I have 5 groups and 3 super-groups. The only thing is that I have not shown all 5 groups. I can probably do a table with just the 5 groups, as I had done in the previous article in addition to what I have already uploaded. Ananth: ]]

  • arjun on January 27, 2012, 11:10 GMT

    If we leave aside easy runs, only Richards and Tendulkar average above 45.00.(qualification 8000 test runs)

    Through your blog time and again we have known that lara has scored most of his runs against tough attacks/conditions; but this anaylsis reveals he has also flourised against easy attacks averaging 84.0. This reduces his average to 40.20 in Super + Middle group.

    Below is performance of India's Famous 6 in Top 2 groups.

    Tendulkar 7206 runs @ 45.32 Dravid 5478 @ 37.02 Laxman 3952 @ 35.59 Sehwag 2599 @ 34.20 Ganguly 3522 @ 34.53 Ghambhir 1118 @ 31.06

    Tendulkar has performed 20 % better than 2nd best Dravid. [[ Arjun, I have always maintained that Lara had scored bigger and probably more significant innings but that Tendulkar was more consistent. This proves that. And there is a clear difference in averages which is reflected in the numbers. Let us also look at the % of career runs. Lara's is just below 50. But look at Border. That is where Richards who had a career average of 50.xx and could easily gone below 50, if he had scored 41 fewer, really comes through. Ananth: ]]

  • Ranga on January 27, 2012, 11:56 GMT

    Some interesting outcomes though. To average 35+ in the tough group needs some skills and application, Mark Waugh has perhaps, the most consistent streak among modern batsmen. Unlike many who feel moody guys like him, Lara, etc revel only when there is challenge and do not get motivated enough to perform when the challenge is not great, Mark Waugh shows remarkable consistency across the groups. Ditto with Lara (as Arjun has rightly put). To my knowledge, Lara has not really shown any difference in approach or attitude. It is just that some lesser bowlers have had him. But Lara has faced far more difficult bowlers than others on more occasions, not necessarily an outcome of his weak team.

    Finally, abt the fab 3, all 3 have been products of tough 1st class structures. VVS, since 1992-95 had been a regular U-19 and A team player who toured Aus, Eng, etc. RD was also a product of tough 1st class structures. No substitute for preparation. Talent notwithstanding. [[ Ranga Unfortunately we have multiple forms of cricket running parallel. The Test/ODI cricket stream. The IPL stream and the Ranji/FC stream. Almost no established Test player plays FC. The Bists of the world can only hope for the crumbs and with some the support and luck go to IPL. The first group are, of course, the stars of IPL. How can they play FC when that time can be used to participate in IPL. So where are we heading for. Today the talk is that Rohit Sharma is the saviour of all problems of mankind. Is he ??? Ananth: ]]

  • Ranga on January 27, 2012, 12:24 GMT

    Another silent killer is Kepler Wessels, who made more runs against top bowling and lesser against others. An unheralded batsman, he has faced tougher bowling all through. Also my respect for Tony Greig grows, because he has done well against tough bowling, while facing sub-44 attacks throughout his career.

    One thing about these articles is that there is no superstar in these. This article gives credit to those who deserve in the right areas. In this article, Mark Ramprakash is the superstar. I dont think any other article would give these perspectives. It was so informative and has given different points of view and different paradigms to batting. Despite playing for the same team, literally, M Waugh has faced tougher bowling than his twin and of course, a funny Indian view is Kumble has faced tougher bowling than SRT, though their common tests coincide almost 100%. These perspectives are refreshing and pleasurable. So the theory of same team similar attack is not really true. [[ Even in the top-25 innings, there are well-known wonderful innings but also the innings from lesser-known-talked-about batsmen such as Amiss, Endean, Fleming, Bacchus, Gregory et al. Ananth: ]]

  • Regi Baptiste on January 27, 2012, 13:20 GMT

    Ananth, Good work once again. However, please don't let onayone trap you into this Lara vs Tendulkar debate; or other players comparison debate with data that is taken from such wide and general domains like this. As one of the world's top statistical analysts, you know that for one to execute a genuine comparison of any two performers, one needs to narrow as much as possible, the data to those taken from performances carried out in the most 'like conditions' to which both subjects were exposed. Hence, as far as batsmanship in cricket is concerned, there is no better comparison that can be made (in terms of relative accuracy) than a comparison between Lara and Tendulkar; because they both began their careers around the same time. So, if you want the most genuine comparison, why don't you look at their figures between 1989 and the end of the season in December 2006 when Lara played his last test? Those were the 16 years when they played against similar oppositions, on similar pitches, with the same rules, etc. If you do so, then you would find out that it is a 'MYTH' for anyone to say that Tendulkar 'WAS' ever more consistent than Lara! If you do this analysis, you would also find out that no element of batting data showed that Tendulkar performed better than Lara when both competed during those 16 years. And I think this should bring closure to this Tendulkar-Lara better batsman debate.