Matches (13)
IPL (2)
PSL (2)
Women's Tri-Series (SL) (1)
County DIV1 (3)
County DIV2 (4)
USA-W vs ZIM-W (1)
Anantha Narayanan

Test batting: location summary, by innings and vs country

An analysis of players' Test careers by innings number, opposition and host country

Jacques Kallis has a better average in the second innings than in the first innings © Getty Images

This is a continuation of the two ODI articles and analyses how Test batsmen and bowlers performed at home or away, against different teams and in the first or second innings. Normally I do analysis-centric articles which take on and expound a theme. Once in a while I do different types of articles in which I go deep in one area of the game and provide data tables around it. This is one such article. This has been a tough exercise on presentation and I must thank Milind for his invaluable suggestions.

This information is certainly available through StatsGuru of Cricinfo. However, what will not be available are the composite multidimensional tables which are provided here. You would have to put in multiple queries and saving the tables in an accessible format is another problem.

In order to avoid the usual questions and comments which relate to specific players, let me explain how these series of articles would be structured. I would cover the top/selected 10-12 players in a graph to visually present the variations. Then I would present data tables, in the body of the articles, which would normally cover the top 30 players or so. However the most important of the tables are the ones which have been uploaded and are available for downloading for permanent storage and perusal. Normally these cover the complete set of players, say 150 or so, who meet the cut-off criteria. So, before coming out with comments that "Miandad or Graham Gooch or Amarnath is not mentioned", please download the tables and check. Superficial reading of the articles is not enough.

The vs Country grouping is simple. I have 10 countries: Australia, Bangladesh, England, India, New Zealand, Pakistan, South Africa, Sri Lanka, West Indies & Zimbabwe. And the analysis is very extensive in that it is by country played against: at home, away and across career. These being Test matches, I have also analyzed the career averages by first and second innings.

1. The criteria is 3000 Test runs for the career analysis and 2000 runs for the other analyses. I know that Pollock and Headley will miss out. However I do not want to lower the target further since the vs Country numbers would be too low.
2. There is no problem with using the Batting Average since this is an analysis of Test matches. Not outs do not play that significant a part as happens in the ODI game.
3. There are problems with the single Australia-ICC Test match. It could be said that the ICC players played against Australia away. Fine. But what about Australia. Which country did they play against? And I am not certainly going to allocate part of the match runs/wickets only. So this match has been completely excluded from the analysis. So do not come out with a complaint if you see Muralitharan, in the next article, with 795 wickets and Hayden, in this analysis, short by over 100 runs.
4. There is no neutral location. Too few matches (probably a maximum of 20) have been played in the neutral locations for me to classify these. These are treated as "Away" for both, probably a very fair assignment.

There are some similarities between this and the previous article on Bradman. However that article had the individual innings as the basis while this analysis has, as basis, the runs scored in different locations, against other teams and different team innings. The objectives are quite different. There are different insights to be drawn. In these articles the unassailable fact is the superiority of Bradman, in figures. So all attempts have been made to highlight facts related to other batsmen. I request readers to try and maintain this. After all there are other Test batsmen than Bradman and Tendulkar.

First the graphs. I would only offer limited comments since I expect the readers to come out with their own comments. I might anyhow miss some obvious comment. Should not really matter. The ordering is different for different modes of presentation since we can get different insights. In general, the graphs are ordered by the concerned Batting Average values and the tables are ordered by the appropriate Runs scored values.

Batsmen analysis - Summary by location / innings

Summary of career performance
© Anantha Narayanan

This graph contains batsmen with the top 10 averages and Tendulkar and Lara. Kallis is the only modern batsman in the top-10. The visual presentations are quite clear and are also explained on the graphs. Bradman is Bradman. Let us stop there. Barrington's away batting average is significantly higher than his home figure. As is the case with Hammond. Walcott has been much better at home than away. Hutton is almost the same everywhere.

Understandably most batsmen have performed better in the first innings than the second innings. Only three batsmen, Bradman, Sutcliffe and Kallis have performed better in the second innings than the first. This should put Kallis in slightly different light.

Batsmen analysis - All matches - by opposing country

Summary of performance against each team
© Anantha Narayanan

This graph requires some explanation. These are ordered by the Batting Average values. The player's performance against the 10 team groups are plotted. Blue ovals indicate Batting Average values of over 50.0 and Red ovals indicate Batting Average values below 50.0. The number of innings and runs scored are displayed under each country. Both Tendulkar and Lara have a mixed bag of performances and have been sub-par against three teams each. Both have been just below par against New Zealand and South Africa.

Only Bradman and Hobbs have performed above par across all countries. Tendulkar has been below par against Pakistan and South Africa while Lara has not been so successful against India and New Zealand. Looking down the graph, West Indies has been the toughest team to bat against and India the easiest to bat against.

Batsmen analysis - Home matches - by opposing country

Summary of performance in home Tests
© Anantha Narayanan

Other than Bradman, Weekes and Walcott have been outstanding at home against all opposition. Look at how well Australian bowlers have performed against all countries, away.

Batsmen analysis - Away matches - by opposing country

Summary of performance in away Tests
© Anantha Narayanan

Barring West Indies, Barrington has been above par while visiting the other countries. Same as with Hammond. Hobbs has also done well while on road. Surprisingly England has been a good country to visit and not so surprisingly New Zealand the toughest.

Now for the tables. Most of these are self-explanatory.

Test batsmen summary: by location, innings and average bowling quality

   Career Home Away 1st Ins 2nd Ins Avge31.79Adj Avge
BatsmanTeamInnsNosRunsAvgeRunsAvgeRunsAvgeRunsAvgeRunsAvgeBowQty/ABQ 
 
TendulkarInd311321547055.45676556.38870554.751092462.07454644.1434.460.9251.15
Ponting R.TAus282291334652.75744659.10579646.37936458.53398242.8234.820.9148.16
Dravid RInd286321328852.31559851.36766753.62910559.12418341.8334.150.9348.71
Kallis J.HSaf257391237956.78673858.59555854.49790555.28447459.6535.340.9051.08
Lara B.CWin23261195352.89621758.65569548.26824963.95370438.1932.020.9952.52
Border A.RAus265441117450.56574345.94543156.57680348.25437154.6432.790.9749.02
Waugh S.RAus260461092751.06571047.58521755.50855860.70236932.4534.190.9347.48
JayawardeneSlk217131044051.18664663.90379737.97769960.62274135.6036.400.8744.69
ChanderpaulWin243391029050.44544459.17484643.27674656.22354442.1933.980.9447.19
GavaskarInd214161012251.12506750.17505552.11615950.90396351.4734.170.9347.56
SangakkaraSlk18312938254.87518659.61419649.95578156.13360152.9636.390.8747.93
Gooch G.AEng2156890042.58591746.23298336.83500242.39389842.8430.541.0444.33
J MiandadPak18921883252.57448161.38435145.80650456.56232843.9234.590.9248.31
InzamamPak20022883049.61360452.23522548.83563651.24319446.9734.290.9345.99
LaxmanInd22534878145.97376751.60501442.49531044.25347148.8933.540.9543.57
Hayden M.LAus18414862650.74502357.08341542.69515350.03347351.8434.340.9346.97
RichardsWin18212854050.24313649.78540450.50604550.80249548.9232.660.9748.89
Stewart A.JEng23521846539.56465240.81381338.13500339.71346239.3430.451.0441.29
Gower D.IEng20418823144.25445442.83377746.06531146.59292040.5632.220.9943.66
Sehwag VInd1676817850.80424858.19384744.73617064.95200830.4234.490.9246.82
Boycott GEng19323811447.73435648.40375846.98479545.67331951.0633.570.9545.20
Smith G.CSaf17412804349.65357244.65445955.74487250.23317148.7836.470.8743.27
SobersWin16021803257.78407566.80395750.73510959.41292355.1532.070.9957.27
Waugh M.EAus20917802941.82401943.22401040.51556844.90246136.1933.120.9640.14
AthertonEng2127772837.70471638.98301235.86445839.45327035.5430.121.0639.79
Langer J.LAus18212769645.27440649.51326841.37517650.75252037.0634.020.9342.31
Cowdrey M.CEng18815762444.07353743.13408744.91525047.30237438.2933.230.9642.17
GreenidgeWin18516755844.72320948.62434942.22463543.32292347.1532.680.9743.50
Mohd YousufPak15612753052.29296563.09456547.06504360.04248741.4535.150.9047.30
Taylor M.AAus18613752543.50399343.40353243.60438443.41314143.6234.360.9340.25
Lloyd C.HWin17514751546.68288146.47463446.81519149.91232440.7732.230.9946.04
Haynes D.LWin20225748742.30386856.06361933.51445738.76303048.8733.530.9540.10
Boon D.CAus19020742243.66454146.34288140.01449143.60293143.7534.200.9340.59
Kirsten GSaf17615728945.27338442.30390548.21462047.14266942.3733.860.9442.50
Hammond W.REng14016724958.46300450.07424566.33507064.18217948.4243.860.7242.37
Ganguly S.CInd18817721242.18318042.97403241.57476943.75244339.4034.050.9339.37
Fleming S.PNzl18910717240.07294733.87422545.92486146.30231131.2332.760.9738.88
ChappellAus15119711053.86451554.40259552.96479158.43231946.3832.290.9853.04
Bradman D.GAus8010699699.94432298.232674102.85469797.852299104.5035.950.8888.38
The Home/Away and First/Second innings columns are self-explanatory. The last three columns are interesting. I have first posted the Average Bowling Quality, which is the Career-to-date bowling average faced by the batsman weighted by the runs scored. To counter the single bowler anomalies, the reciprocal method is used. An excellent bowling attack off which a 100 is scored will get a higher weight than the same attack off which 10 runs are scored. Thus this is a true depiction of the quality of bowling faced by the batsmen through their career and how they handled the attacks.

This work is an off-shoot of a comment for the previous article. Basically I have adjusted the batsman average by a factor which is 31.79 / ABQ. What is 31.79. That is the single bowling average value across 135+ years and 2000+ Tests. Bradman's ABQ being a below-par 35.95, his average gets reduced from 99.94 to 88.38. Gooch, having faced an above-par bowling attack of 30.54, has his average increased from 42.58 to 44.32. This seems to be an excellent adjustment tool.

Test summary: All matches vs other teams

BatsmanTeamRunsAvgeInsAus Bng Eng Ind Nzl Pak Saf Slk Win Zim 
All matches    AvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeIns
 
TendulkarInd1547055.4531157.367137956.347  49.43642.32742.54560.53655.23076.514
Dravid RInd1326552.6428439.760701060.937  63.82853.72633.84048.63263.83897.913
Ponting R.TAus1324252.76280  65544.25854.45153.62666.82652.54346.42353.44496.74
Kallis J.HSaf1229656.6625538.14779.2742.746722864.12666.926  38.92573.6431707
Lara B.CWin1191253.1823052.15686.5262.15134.62941.41753.322493586.514  55.54
Border A.RAus1117450.56265    56.38252.23551.73259.53633.11054.31139.559  
Waugh S.RAus1092751.06260    58.27341.93138.53434.63049.92587.61149.8511453
JayawardeneSlk1044351.1921734.92366.41459.93767.52851.619324059.428  44186010
ChanderpaulWin1029050.44243503854.6852.45465.74042.92042.92650.6364212  28.89
GavaskarInd1012251.1221451.731  38.267  43.41656.541  66.71165.548  
SangakkaraSlk938254.8718342.7177314353657.12459.21479.62548.628  541989.36
Gooch G.AEng890042.5821533.379    55.63352.22442.71623.2662.7644.851  
J MiandadPak883252.5718947.340  51.13267.5398029    41.61629.82828.65
InzamamPak882950.1619834.12580.8854.63252.11766.219  32.323603153.52442.919
LaxmanInd878145.9722549.75439430.628  58.41743.12537.53147.42257.236408
RichardsWin854050.2418244.454  62.45050.74143104227        
Stewart A.JEng846539.5623530.765    40.61545.92652.32239.23941.21636.943699
Hayden M.LAus843850.23182  33.6545.735593536.61846.81043.73651.11351.5272503
Gower D.IEng823144.2520444.877    44.937502249.427  93332.838  
Boycott GEng811447.7319347.571    57.12238.22584.41037.312  45.953  
Sehwag VInd809550.9116543.94035.262722  44.41891.11450.22672.91852.21758.74
SobersWin803257.7816043.138  60.66183.53023.81889.513        
Smith G.CSaf803150.1917238.62782.6957.43434.923442044.720  351269.325812
Waugh M.EAus802941.82209    50.15133.22442.62042.422422924.61441.348901
AthertonEng772837.7021229.766    57.413681741.41943.83218831.750377
Langer J.LAus767445.68180  36250.23840.32662.923572042.72035.91437.933204
Cowdrey M.CEng762444.0718834.375    72.61159.62445.21539.327  51.536  
GreenidgeWin755844.7218540.452  50.44847.93955.11931.927        
Mohd YousufPak753052.2915629.621252662.52449.92753.415  29.81329261011468.410
Taylor M.AAus752543.50186    42.36142.21847.61679.22041.41943.61528.137  
Lloyd C.HWin751546.6817550.248  45.15158.64416.71437.918        
Haynes D.LWin748742.3020242.159  47.85934.13249.62037.12940.52201    
Boon D.CAus742243.66190    45.75770.82047.52723.92043.31132.91539.940  
Kirsten GSaf728945.2717634.434155248.735401950.12355.918  42.61634.52482.55
Hammond W.REng724958.4614051.958    79.3911311  62.542  35.520  
Ganguly S.CInd721242.1818835.14461.8657.819  46.91547.52033.83146.32432.11644.213
Fleming S.PNzl717240.0718925.22766.2635.13732.620  47.51641.22758.32346.91637.617
ChappellAus711053.86151    45.96573.6556.62263.227  6615631  
Bradman D.GAus699699.9480    89.8631796    2025  74.56 

I have resolved not to mention the dreaded B word once in this paragraph. Coming down to earth, the averages which stand out, after ensuring that sufficient innings are played are: Sutcliffe 46 @ 66.9 and Barrington 39 @ 64.0 against Australia. Richards 50 @ 62.4 and Lara 51 @ 62.1 against England. Zaheer Abbas 25 @ 87.0 and Sobers 30 @ 83.5 against India. Javed Miandad 29 @ 80.0 against New Zealand. Sangakkara 25 @ 79.6 and Taylor 20 @ 79.2 against Pakistan. Harvey 23 @ 89.2 against South Africa. Tendulkar 36 @ 60.5 against Sri Lanka. Kallis 43 @ 73.6 and Gavaskar 48 @ 65.5 against West Indies. I am certain I have missed out some gems.

Test summary: Home matches vs other teams

BatsmanTeamRunsAvgeInsAus Bng Eng Ind Nzl Pak Saf Slk Win Zim 
Home matches    AvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeIns
 
Ponting R.TAus744659.10147  34.5244.3288626511869.91658.22250945.4231303
TendulkarInd676556.3813562.729  60.617  49.31844.21436.21752.51761.7161137
Kallis J.HSaf673858.5913433.626127453.92691.71368.81347.213  41.11594.32158.73
JayawardeneSlk664663.9011235.31579.47891870.21866.71230.71510512  45.41155.74
Lara B.CWin621758.65111662386.527824352349.7660.8951.41769.87    
Gooch G.AEng591746.2313133.546    66.71758.11945.81023.2680.8447.629  
Border A.RAus574345.94145    47.33953.41952.81857.72029.2563.2433.940  
Waugh S.RAus571047.58140    47.54137.916421725.21349.511130839.13069.52
Dravid RInd559851.3612035.730  47.814  63.81442.91739.21876.91158.4101266
ChanderpaulWin544459.1711480.4171082402770.32946.8665.91163.11543.34  24.33
SangakkaraSlk518659.619530.511118739.21874.31452.8768.81065.812  681263.84
GavaskarInd506750.1710852.512  3639  43.2654.422  104561.124  
Hayden M.LAus502357.0896  30.5256.81771.81341.91132653.91854.4747.7192503
AthertonEng471638.9812429.838    64.11158.71331.21346.716  29.330753
Stewart A.JEng465240.811263033    52.99351763.91641.62358.8826.91560.55
Boon D.CAus454146.34108    42.92973.21558.31618.3931.2536.9946.325  
ChappellAus451554.4096    503773.6536.296022    58.823  
J MiandadPak448161.388669.912  70891.41882.615    51.91226.81628.65
Gower D.IEng445442.8311345.232    52.12057.81836.822  55122.420  
Langer J.LAus440649.5194  36248.42750.61387.9872.11054.91052.5425.817123
Boycott GEng435648.401005034    64.31246.11787.3518.84  4128  
Bradman D.GAus432298.2350    78.5331796    2025  74.56  
Sehwag VInd424858.197640.220  26.412  71.9990.76841178.1753.110741
JayasuriyaSlk411443.7710231.11475.6530.61494.81031.5842.6144515  27.91143.311
SobersWin407566.807538.918  73.42472.91736.181378        
Waugh M.EAus401943.2299    50.823221145.91245940.31463.844226 

I will let the readers come out with real gems from this table.

Test summary: Away matches vs other teams

BatsmanTeamRunsAvgeInsAus Bng Eng Ind Nzl Pak Saf Slk Win Zim 
Away matches    AvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeInsAvgeIns
 
TendulkarInd870554.7517653.238137954.330  49.51840.21346.42867.91947.714407
Dravid RInd766753.621644430701068.823  63.81478.6929.72233.12165.72879.27
Ponting R.TAus579646.37133  95.5344.13026.52559.7862.11046.82144.21461.121311
Lara B.CWin569548.2611943.333  48.82733636.91148.21346.7181017  55.54
Kallis J.HSaf555854.4912143.82131.5329.32058.515591390.513  35.31055.4225034
Border A.RAus543156.57120    65.14351.11650.21461.91638548.3753.119  
RichardsWin540450.5011547.639  64.33445.42419.2442.814        
InzamamPak522548.8312035.21489342.52254.91059.615  31.81580.91348.9164912
Waugh S.RAus521755.50120    74.23247.41535.31742.11750.21417.3368.521  
GavaskarInd505552.1110651.119  41.128  43.61058.919  37.2670.224  
LaxmanInd501442.4913444.12939434.519  40.2937.4940.41848.21347.82741.56
ChanderpaulWin484643.2712930.22141.2666.62754.61141.21430.61542.12141.38  316
Lloyd C.HWin463446.811084936  42.13075.52215.31133.89        
Mohd YouPak456547.0610531.918378354.31533.71755.214  26.11032.51278.4958.17
Younis KhanPak450050.0010031.812128547.41476.81265.38  40.41442.617401350.55
Smith G.CSaf445955.748643.71267572.21735.91257.21245.611  44.847313  
J MiandadPak435145.8010338.128  46.62449.92177.314    15.8433.812  
GreenidgeWin434942.221103132  56.13045.32556.21217.311        
Hammond W.REng424566.337261.935      3213  62.926  258  
Fleming S.PNzl422545.9210029.315116237.91935.711  50646.3201051041.98399
SangakkaraSlk419649.958865.2640.6730.61836.51066.8786.51535.816  3471402
Cowdrey M.CEng408744.911003648    103455.91633.2433.110  60.318  
Ganguly S.CInd403241.5710434.82061.8665.415  27.7849.3336.11636.817401230.67
Waugh M.EAus401040.51110    49.52843.51335.8840.61343.61591040.522901

Let us set aside Hammond's average of 321.0 against New Zealand and Mohd Yousuf's 378.0 against Bangladesh (albeit in 3 innings each). The stand-out averages are: Hammond 35 @ 61.9 and Tendulkar 38 @ 53.2 against Australia. Steve Waugh 32 @ 74.2 and Dravid 23 @ 68.8 against England. Lloyd 22 @ 75.5 and Sobers 13 @ 99.9 against India. Kallis 13 @ 90.5 and Sangakkara 15 @ 86.5 against Pakistan. Inzamam 13 @ 80.9 and Fleming 10 @ 104.7 against Sri Lanka. Finally Gavaskar 24 @ 70.2 and Steve Waugh 21 @ 68.5 against West Indies. Again this is probably not a final list.

But for me the most inexplicable and impossible-to-understand performance is Sobers' 10 innings in New Zealand at 15.1. His scores during 3 tours are 27, 25, 27, 1, 1, 11, 0, 20, 39 and 0. What really happened ???

To download/view the Excel sheet containing the following tables, please click/right-click here. The serious students of the game are going to have a link to this Excel file on their desktop and refer to it a few times a day.

Batsman location summary and innings summaries.
Batsmen run analysis vs Team - for all matches
Batsmen run analysis vs Team - for home matches
Batsmen run analysis vs Team - for away matches
No specific conclusions. I thought for long and decided against coming out with any selection of batsmen. It will be a red herring.

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

Terms of Use  •  Privacy Policy  •  Your US State Privacy Rights  •  Children's Online Privacy Policy  •  Interest - Based Ads  •  Do Not Sell or Share My Personal Information  •  Feedback