Test top-score analysis: Bradman and Lara dominate
An analysis that identifies the most dominant innings by batsmen in Tests, in the context of contributions by other batsmen to the team score
The Tendulkar brace (on Tests and on ODIs), written during late 2013, was a tough pair for me. Not only did I have to put in a lot of effort but also had to face a barrage of (often unjustified) criticism from fans of the great cricketer, who did not want to recognise any analyses that did not sing unrestrained praise. However, one good measure came out of these two articles as a very valuable one for measuring player contributions. In those articles, I had presented a raw version of the HSI (High Score Index). This measure found support from many readers and I had promised that I would develop HSI as an independent measure after incorporating tweaks from many readers. In an earlier article, I have covered the ODI game: an easier one to start with because of the single-innings format. In this article I have covered Test matches. This is far more complicated with many nuances not found in the limited-overs format.
The tweaks suggested can be summarised as below.
- Extend the concept to all batsmen scores, not just the top two scores.
- Incorporate the team score into the computations.
- Avoid the very high range of numbers in the early version: the HSI for an innings went as high as 11.4.
- Look at how the players have performed in various classifications, with HSI as the key measure.
- Look at the possibility of using a GM (Geometric Mean) rather than AM (Arithmetic Mean) because of the significant variations.
A 100 as the top score does not provide enough information by itself. It could be out of a team score of 200 or 500. It could be supported by an innings close to 100, by a 50 or by a 10. It could be part of 300 for 1 or 400 for 5 or 200 all out.
The HSI is a measure of two components for the innings top score. The batsman stands alone at the top and his contribution gets enhanced depending on the support received. On the other hand the second-placed scorer has had the support of a higher-scoring batsman. So it is sufficient to take his and other lower-scoring batsmen's contributions based on the team score. With this background let me show you how it works.
Top batsman HSI = {Hs1/Team score} x {Hs1/Hs2}. This incorporates both components.
Other batsmen HSI = {Batsman score/Team score}.
I worked out that there is no need to multiply the lower scores by {Score/Hs1}. That would lower the values too much. An Hs1 of 100 and Hs2 of 90 (out of 200) would end up with the HSI value for Hs1 well over 25% higher than the HSI value for Hs2, which is incorrect.
Let me try to describe the HSI in a visual manner. If we represent the numbers on a linear scale, the team score is at the top. The batsman score is in the middle and the next highest score is below this. The HSI value increases as the distance between the batsman score and the team score decreases. Alternatively, the HSI value increases as the distance between the batsman score and the next highest score increases. Thus the HSI is dependent on how far away these two values are from the batsman score.
There was a suggestion that an average of the next two (or more) high scores be used to determine the HSI. There is some merit in this suggestion. However, whichever way I work this, I cannot see how a sequence of 100, 90, 80... would be significantly different from 100, 90, 25... For that matter we do not even know whether the 90 batsman has been in partnership with the top scorer or not. That would only complicate things. Now it is possible for readers to work out the HSI of an innings by just perusing the scorecards. I do not want to lose this simple application of the concept.
However one major problem, specifically related to Tests, has to be addressed and solved. It is best explained with an example. Let us say that Australia need 50 to win and they reach 50 for 1 with David Warner scoring 40, Chris Rogers scoring 5 and 5 are scored through extras. Warner's innings will get a HSI of 7.28 (8.0*0.88). Totally outrageous, incorrect and unrealistic. This is higher than the current highest HSI value. But there are also situations such as Len Hutton scoring 30 out of 52 all out or Virat Kohli scoring 105 out of 166 for 3 or Stan McCabe scoring 189 out of 274 for 3 and so on. These have to be taken care of. In the same example I have taken, what if Australia collapsed but still won the match by three wickets scoring 50 for 7 and Michael Clarke scoring 25, with the next-highest score being 5. He would have a correct HSI of 2.75 (5.0*0.55). All these situations have to be taken care of.
I analysed this problem in many ways and tried various options. I even did a customised exclusion of matches based on scores and wickets lost. But that meant that all innings played would not be included. Only when I did an analysis of all 2279 innings in which fewer than ten wickets were lost did I realise that loss of five wickets was the separation point. Loss of five wickets meant that the top order had their say and all support innings would be from the lower order. So I decided that all innings of five wickets or below would have their HSI values reduced by a factor. But what about 274 for 3 or 450 for 2 and so on? So I set a limit of 200 runs to apply this adjustment. It has worked very well.
In the previous examples, Warner's HSI would be multiplied by 0.167(1/6) and Kohli's by 0.5(3/6). Hutton, McCabe and Clarke would retain their values. This is exactly as it should be. It would be tempting for any reader, with a five-minute superficial study of this situation, to punch holes in this algorithm. Before doing that, please do not forget that I have spent well over ten hours solely to take care of this problem. I have analysed each wicket-fall group (0/1/2/3/4/5) of innings separately.
Now that the HSI for every innings has been determined, let us move to the many tables I have created. The first is the basic table of the HSI value itself. I have shown the top 30 HSI values. There is a downloadable Excel file which contains the innings which have HSI values greater than or equal to 0.1. Please download and peruse it before asking about specific innings or player.
Readers should remember that these calculations are scorecard-based, non-contextual and within a team. Hutton's 30, out of 52, will get a much higher HSI (2.795) than Ahmed Shehzad's 147 (HSI-1.039), which, in turn will get a much higher HSI value than Mahela Jayawardene's 374 (HSI-0.679). It does not mean that Hutton's innings was better or match-winning, like the other two. It only means that Hutton contributed more to his team in this specific innings than Shehzad or Jayawardene. The result is immaterial. The key word is "contribution". Please make sure that this point is clearly understood.
A note on the cut-off. I have selected 3000 Test runs as the cut-off for the main table and 168 batsmen qualify. Only three of these batsmen, Harbhajan Singh, Anil Kumble and Shane Warne, have an average below 20 and these three have been kept in. Once the cut-off is set, all players are considered equal. Afterwards, I am not going to say one batsman played in only so many matches and another played in many more matches and so on. The players have met the criterion set and that is it.
For the other 12 tables, there are varying cut-off points. In general 50 innings has been used as the minimum for qualification. However, readers should note that to qualify for the later tables only the appropriate cut-off is needed. A batsman who has scored fewer than 3000 Test runs could very well have played 50 innings at home or 30 third innings and so on.
After getting the HSI values I evaluated on the need to do an alternate mean-evaluation. I decided that it is not necessary to use GM and used AM itself since the distribution pattern revealed a few important facts. The top entry is at 6.4 and the next four entries are 4.7. See how steeply the values drop. Also only 13 innings have HSI values greater than 4.0. So there is really only a single outlier: Charles Bannerman's innings. I did not want to be influenced by this single performance.
A few important facts on HSI.
1. There is one HSI value exceeding 6.0, 12 exceeding 4.0, 37 exceeding 3.0, 180 exceeding 2.0 and 1044 exceeding 1.0. So this is a rather exclusive club. Just to illustrate this: a 100 out of 200, with a next-highest score of 50 will have a HSI value of 1.0.
2. The highest HSI value is 6.382 for Bannerman in the very first innings ever played. More on this later. However, to overtake this value, a batsman would have to score 100 out of 150, with the next-highest score being around 10. As many as 74,856 innings have been essayed since Bannerman's 165 and no one has even come close to this HSI value. Not even within 24% of it.
3. The lowest HSI value for a significant Hs1 innings is in match #786. India scored 524 for 9 v New Zealand. The highest score was by Mohinder Amarnath, with 70. The next highest score was 68 and there were six 50s in the innings. Amarnath's 70 earned him a HSI of only 0.145.
4. The highest HSI value for a significant Hs2 innings is for Javed Miandad. In match #1000 - played in 1984. Pakistan scored 230 for 3. Mudassar Nazar top-scored with 106 and Miandad was close behind at 103. Mudassar's HSI was 0.507 and Miandad's HSI was 0.479. The highest HSI value for a HS2 innings in a completed innings was for Stuart Broad's 169. Only Jonathan Trott's 184 was ahead of him and Broad's innings had a HSI of 0.418.
5. The highest HSI value for a significant non-Hs1-Hs2 innings is for Alec Stewart's 79 in match #1411. England scored 321. The top scorer was Nasser Hussain who scored 106 (HSI-0.452). The next highest scorer was Graham Thorpe with 84 (HSI-0.284). Stewart's 79 fetched a HSI of 0.267.
6. 1044 HSI values are 1.0 and above. This represents 1.3% of the total.
7. 3337 HSI values are 0.5 and above. This represents 4.5% of the total.
8. 26300 HSI values are 0.10 and above. This represents 35.1% of the total.
9.The average Hs1 for 6736 team innings is 88.8. The average Hs2 for these innings is 56.4. The ratio is 1.57: remarkably the same as ODI.
10.The average HSI value for the 74857 innings is 0.125. This average also lets us take a stand on career averages of HSI. Maybe 0.2 would an excellent career average. Fifty-one batsmen have career HSI averages exceeding 0.2. A total of 148 batsmen have career HSI averages exceeding 0.125.
Now for the multiple HSI tables based on various selection criteria. This was one of the main objectives of this exercise. For most tables I have shown the top-30/20 players. It should be remembered that if a batsman qualifies on the specific criterion for the table, he would be included even though he may not qualify on the broad qualification of 3000 Test runs. Needless to say (or more appropriately, needs to be said) that the complete set of entries is available in the downloadable file with 14 tables. Please make an attempt to answer your question by downloading that file before asking me. Since this is by far the longest article I have ever penned (or more appropriately, keyed), I will only provide minimal comments.
I have only one overriding criterion for all tables. Irrespective of the number of innings played, Don Bradman is included in all tables. This is to see what he has achieved in all classifications.
| SNo | HSI | Test # | Year | Inns | BPos | For | TeamScore | Batsman | Runs | 1/2 | HS1 | HS2 | Vs |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 6.382 | 1 | 1877 | 1 | 1 | Aus | 245/10 | C Bannerman | 165 | Hs1 | 165 | 18 | Eng |
| 2 | 4.744 | 1033 | 1985 | 3 | 3 | Aus | 308/10 | AR Border | 163 | Hs1 | 163 | 20 | Ind |
| 3 | 4.741 | 846 | 1979 | 1 | 4 | Aus | 198/10 | GN Yallop | 121 | Hs1 | 121 | 16 | Eng |
| 4 | 4.729 | 1206 | 1992 | 3 | 7 | Ind | 215/10 | Kapil Dev | 129 | Hs1 | 129 | 17 | Saf |
| 5 | 4.692 | 1863 | 2008 | 3 | 1 | Ind | 269/ 7 | V Sehwag | 151 | Hs1 | 151 | 20 | Aus |
| 6 | 4.648 | 1481 | 2000 | 3 | 1 | Ind | 261/10 | VVS Laxman | 167 | Hs1 | 167 | 25 | Aus |
| 7 | 4.620 | 732 | 1974 | 3 | 2 | Eng | 432/ 9 | DL Amiss | 262 | Hs1 | 262 | 38 | Win |
| 8 | 4.559 | 1414 | 1998 | 2 | 4 | Saf | 200/10 | DJ Cullinan | 103 | Hs1 | 103 | 13 | Slk |
| 9 | 4.046 | 79 | 1904 | 3 | 3 | Eng | 103/10 | JT Tyldesley | 62 | Hs1 | 62 | 10 | Aus |
| 10 | 4.044 | 1694 | 2004 | 2 | 5 | Eng | 226/10 | GP Thorpe | 119 | Hs1 | 119 | 17 | Win |
| 11 | 4.034 | 1327 | 1996 | 3 | 4 | Ind | 219/10 | SR Tendulkar | 122 | Hs1 | 122 | 18 | Eng |
| 12 | 4.000 | 2038 | 2012 | 1 | 4 | Slk | 318/10 | DPMD Jayawardene | 180 | Hs1 | 180 | 27 | Eng |
| 13 | 3.872 | 1773 | 2005 | 1 | 4 | Win | 405/10 | BC Lara | 226 | Hs1 | 226 | 34 | Aus |
| 14 | 3.840 | 1541 | 2001 | 4 | 1 | Win | 88/ 7 | CH Gayle | 48 | Hs1 | 48 | 8 | Saf |
| 15 | 3.802 | 1171 | 1991 | 3 | 1 | Eng | 252/10 | GA Gooch | 154 | Hs1 | 154 | 27 | Win |
| 16 | 3.792 | 587 | 1965 | 2 | 3 | Pak | 307/ 8 | Saeed Ahmed | 172 | Hs1 | 172 | 29 | Nzl |
| 17 | 3.730 | 841 | 1979 | 3 | 3 | Win | 151/10 | HA Gomes | 91 | Hs1 | 91 | 15 | Ind |
| 18 | 3.671 | 58 | 1899 | 3 | 2 | Eng | 237/10 | PF Warner | 132 | Hs1 | 132 | 21 | Saf |
| 19 | 3.627 | 631 | 1968 | 4 | 3 | Nzl | 88/ 4 | BE Congdon | 61 | Hs1 | 61 | 9 | Ind |
| 20 | 3.615 | 130 | 1913 | 1 | 1 | Saf | 182/10 | HW Taylor | 109 | Hs1 | 109 | 19 | Eng |
| 21 | 3.557 | 226 | 1933 | 2 | 3 | Eng | 548/ 7 | WR Hammond | 336 | Hs1 | 336 | 60 | Nzl |
| 22 | 3.502 | 1439 | 1999 | 3 | 1 | Aus | 184/10 | MJ Slater | 123 | Hs1 | 123 | 24 | Eng |
| 23 | 3.470 | 164 | 1926 | 3 | 3 | Aus | 194/ 5 | CG Macartney | 133 | Hs1 | 133 | 24 | Eng |
| 24 | 3.398 | 1747 | 2005 | 1 | 4 | Win | 347/10 | BC Lara | 196 | Hs1 | 196 | 35 | Saf |
| 25 | 3.372 | 1939 | 2009 | 3 | 1 | Win | 317/10 | CH Gayle | 165 | Hs1 | 165 | 27 | Aus |
| 26 | 3.343 | 330 | 1951 | 2 | 1 | Eng | 272/10 | L Hutton | 156 | Hs1 | 156 | 29 | Aus |
| 27 | 3.307 | 1259 | 1994 | 1 | 3 | Win | 593/ 5 | BC Lara | 375 | Hs1 | 375 | 75 | Eng |
| 28 | 3.299 | 1271 | 1994 | 1 | 4 | Zim | 462/ 9 | DL Houghton | 266 | Hs1 | 266 | 50 | Slk |
| 29 | 3.290 | 91 | 1906 | 3 | 3 | Saf | 138/10 | GC White | 73 | Hs1 | 73 | 12 | Eng |
| 30 | 3.283 | 248 | 1935 | 4 | 3 | Aus | 274/ 2 | SJ McCabe | 189 | Hs1 | 189 | 40 | Saf |
On a cool spring day in 1877, Alfred Shaw bowled the first ball in Test cricket to Charles Bannerman. In all probability a dot ball. The next day Bannerman retired when he had scored 165. Australia scored 245 and went on to win the first-ever Test. Bannerman's dominant hundred has remained one of the best "Ashes" (not called so in 1877) innings ever. This innings has remained at the top of two factors for well over 137 years. This is the highest percentage of a completed innings. And the HSI is a fantastic 6.382 (0.696 * 9.1667). The next highest HSI value is 4.744 for Allan Border's epochal innings of 163 against India which has a HSI value of 4.744, 24% behind. Graham Yallop's 121 against England in 1979 has a HSI of 4.741.
However, the next entry is truly amazing. Kapil Dev walked in at 27 for 5 and sculpted a superlative innings of 129, supported by three scores of 17 by Nos. 8, 9 and 10. The HSI of this unforgettable innings is 4.729, the highest, by a mile, for any late-order innings.
This is followed by two modern classics. Virender Sehwag's 151 out of 269 for 7 and VVS Laxman's SCG blitz of 167 have HSI values either side of 4.65. Then comes the defensive classic of Denis Amiss. His nonpareil match-saving innings of 262 out of England's total of 432 for 9, fetched a HSI of 4.62.
Moin Khan's Sialkot classic of 117, like Kapil's, came batting at No. 7, has a very high HSI value of 2.848. Like Kapil, he entered at 15 for 5 and advanced the team score to 212.
There is another innings which is still more amazing. On a gluepot at the Gabba during the 1950-51 Ashes tour, Australia scored 228. England declared at 68 for 7. Australia countered by declaring at 32 for 7, setting England to score 193 for a sensational win. England were staring down the abyss at 30 for 6 when Hutton, by choice batting at No. 8, walked in. He scored 62 most memorable runs. Freddie Brown supported him a little but England fell 70 runs short. One of the most remarkable innings in Test history and the highest HSI value, for a No. 8 innings, Hutton's 62 gets a HSI of 1.966.
| SNo | HSI-1 Inns | HSI-2 Inns | Test # | Year | For | Vs | Batsman | TeamScore-1 Inns | BatScore-1 inns | TeamScore-2 Inns | BatScore-2 inns |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1.121 | 1.363 | 152 | 1923 | Eng | Saf | CAG Russell | 281/10 | 140 | 241/10 | 111 |
| 2 | 1.626 | 1.751 | 377 | 1953 | Nzl | Saf | GO Rabone | 230/10 | 107 | 149/10 | 68 |
| 3 | 1.010 | 1.804 | 523 | 1962 | Nzl | Saf | JR Reid | 164/10 | 60 | 249/10 | 142 |
| 4 | 1.334 | 1.613 | 569 | 1964 | Aus | Pak | RB Simpson | 352/10 | 153 | 227/ 2 | 115 |
| 5 | 1.832 | 1.271 | 735 | 1974 | Nzl | Aus | GM Turner | 255/10 | 101 | 230/ 5 | 110 |
| 6 | 1.333 | 1.016 | 736 | 1974 | Nzl | Aus | GM Turner | 112/10 | 41 | 158/10 | 72 |
| 7 | 1.025 | 1.325 | 873 | 1980 | Win | Nzl | DL Haynes | 140/10 | 55 | 212/10 | 105 |
| 8 | 1.076 | 1.125 | 1157 | 1990 | Pak | Win | Saleem Malik | 170/10 | 74 | 154/10 | 71 |
| 9 | 1.502 | 1.636 | 1301 | 1995 | Win | Eng | BC Lara | 216/10 | 87 | 314/10 | 145 |
| 10 | 1.307 | 1.188 | 1355 | 1997 | Eng | Nzl | MA Atherton | 228/10 | 94 | 307/ 6 | 118 |
| 11 | 2.192 | 1.094 | 1537 | 2001 | Eng | Slk | GP Thorpe | 249/10 | 113 | 74/ 6 | 32 |
| 12 | 1.014 | 1.287 | 1562 | 2001 | Zim | Saf | A Flower | 286/10 | 142 | 391/10 | 199 |
| 13 | 1.945 | 1.008 | 1572 | 2001 | Win | Slk | BC Lara | 390/10 | 221 | 262/10 | 130 |
| 14 | 1.583 | 1.055 | 1655 | 2003 | Pak | Bng | Yasir Hameed | 346/10 | 170 | 217/ 3 | 105 |
| 15 | 1.414 | 1.095 | 2086 | 2013 | Zim | Bng | BRM Taylor | 389/10 | 171 | 227/ 7 | 102 |
Since these are Test matches I added a new table here. These are the players who achieved a HSI double in a match. They secured HSI values of above 1.0 in both innings. This is a very tough ask as shown by the number of qualifying entries: a mere 15 in 2122 Tests. Only two players have done this twice in their career. Glenn Turner did the double in two consecutive Tests against Australia, in Christchurch and in Auckland with innings of 101, 110, 41 and 72. The first double helped New Zealand to a rare win over their trans-Tasman giants.
The other to achieve the HSI double is Brian Lara. The first was in England during 1995. Lara scored 87 and 145 in the Old Trafford Test. The two HSI values were 1.50 and 1.63. One of only two instances of the HSI values exceeding 1.5 in both innings. But, as often happened with Lara, in a losing cause. In the two innings the highest score by another batsman was 44. Six years later Lara repeated this during his historic tour of Sri Lanka. The 221 and 130 he scored at the SSC, Colombo, fetched him double HSIs exceeding 1.0. Needless to say, again in a losing cause, albeit with better support this time.
| SNo | HSI | Batsman | Runs | Avge | Inns | HSI-T | Gt-1.0 | % | GT-0.25 | % |
|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 0.392 | DG Bradman | 6996 | 99.94 | 80 | 31.3 | 8 | 10.0% | 34 | 42.5% |
| 2 | 0.340 | BC Lara | 11953 | 52.89 | 232 | 78.9 | 17 | 7.3% | 75 | 32.3% |
| 3 | 0.306 | L Hutton | 6971 | 56.67 | 138 | 42.2 | 8 | 5.8% | 41 | 29.7% |
| 4 | 0.289 | ED Weekes | 4455 | 58.62 | 81 | 23.4 | 5 | 6.2% | 23 | 28.4% |
| 5 | 0.289 | JB Hobbs | 5410 | 56.95 | 102 | 29.5 | 7 | 6.9% | 32 | 31.4% |
| 6 | 0.278 | WR Hammond | 7249 | 58.46 | 140 | 39.0 | 7 | 5.0% | 42 | 30.0% |
| 7 | 0.267 | GA Gooch | 8900 | 42.58 | 209 | 55.7 | 12 | 5.7% | 51 | 24.4% |
| 8 | 0.263 | SM Gavaskar | 10122 | 51.12 | 210 | 55.3 | 10 | 4.8% | 65 | 31.0% |
| 9 | 0.259 | Hanif Mohammad | 3915 | 43.99 | 93 | 24.1 | 7 | 7.5% | 24 | 25.8% |
| 10 | 0.259 | KC Sangakkara | 11151 | 58.08 | 207 | 53.6 | 14 | 6.8% | 57 | 27.5% |
| 11 | 0.251 | DL Amiss | 3612 | 46.31 | 88 | 22.1 | 5 | 5.7% | 18 | 20.5% |
| 12 | 0.248 | KF Barrington | 6806 | 58.67 | 130 | 32.2 | 4 | 3.1% | 40 | 30.8% |
| 13 | 0.244 | V Sehwag | 8586 | 49.34 | 178 | 43.5 | 10 | 5.6% | 35 | 19.7% |
| 14 | 0.239 | A Flower | 4794 | 51.55 | 110 | 26.3 | 7 | 6.4% | 32 | 29.1% |
| 15 | 0.238 | Mohammad Yousuf | 7530 | 52.29 | 154 | 36.7 | 8 | 5.2% | 39 | 25.3% |
| 16 | 0.238 | PA de Silva | 6361 | 42.98 | 159 | 37.9 | 8 | 5.0% | 40 | 25.2% |
| 17 | 0.238 | RN Harvey | 6149 | 48.42 | 137 | 32.6 | 5 | 3.6% | 37 | 27.0% |
| 18 | 0.237 | CL Walcott | 3798 | 56.69 | 74 | 17.6 | 3 | 4.1% | 20 | 27.0% |
| 19 | 0.236 | LRPL Taylor | 4178 | 46.94 | 98 | 23.1 | 4 | 4.1% | 26 | 26.5% |
| 20 | 0.233 | H Sutcliffe | 4555 | 60.73 | 84 | 19.5 | 3 | 3.6% | 24 | 28.6% |
| 21 | 0.233 | RA Smith | 4236 | 43.67 | 108 | 25.2 | 7 | 6.5% | 25 | 23.1% |
| 22 | 0.230 | G Boycott | 8114 | 47.73 | 192 | 44.1 | 13 | 6.8% | 41 | 21.4% |
| 23 | 0.230 | DM Jones | 3631 | 46.55 | 89 | 20.5 | 5 | 5.6% | 17 | 19.1% |
| 24 | 0.228 | CH Gayle | 6933 | 42.02 | 174 | 39.7 | 7 | 4.0% | 35 | 20.1% |
| 25 | 0.228 | Saeed Anwar | 4052 | 45.53 | 91 | 20.8 | 3 | 3.3% | 20 | 22.0% |
| 26 | 0.227 | IVA Richards | 8540 | 50.24 | 182 | 41.4 | 8 | 4.4% | 47 | 25.8% |
| 27 | 0.226 | AR Morris | 3533 | 46.49 | 79 | 17.8 | 4 | 5.1% | 16 | 20.3% |
| 28 | 0.226 | VT Trumper | 3163 | 39.05 | 89 | 20.1 | 5 | 5.6% | 14 | 15.7% |
| 29 | 0.225 | SR Tendulkar | 15921 | 53.79 | 326 | 73.2 | 12 | 3.7% | 88 | 27.0% |
| 30 | 0.224 | DJ Cullinan | 4554 | 44.21 | 114 | 25.5 | 4 | 3.5% | 22 | 19.3% |
The top ten in this table are a testament to the effectiveness and immense value of the HSI measure. Bradman, Lara, Hutton, Everton Weekes, Jack Hobbs, Wally Hammond and Sunil Gavaskar would be in anyone's top-ten table of batsmen. The others do not lag behind. We have already seen that 0.20 is the expected career average of a top-quality batsman. Bradman almost doubles this value and Lara is 70% over. There is no doubt about their value to their respective teams.
The top 11 batsmen have career HSI averages exceeding 0.250. Gavaskar is the leading Indian batsman, with an imposing HSI average of 0.263. Hanif Mohammad leads the field for Pakistan. This shows how valuable these two pint-sized giants were for their respective teams. Kumar Sangakkara's presence in the top ten is a clear indication of his stature in Sri Lankan cricket.
I can hear the phrase "in a weak team" being tossed about, especially for Lara. Of course he played in a weak team for the better part of his career. But what about Bradman, Hutton, Hobbs and Hammond? They were in strong teams. Even Graham Gooch and Sangakkara played for relatively strong teams. Only Lara, Gavaskar and Hanif could be said to have played for relatively weaker teams. Even then Gavaskar had above-average support. So this is not a table filled with players from weak teams. It is a table of quality batsmen.
Sehwag underlines his immense value to the Indian team by occupying a top-15 position. Viv Richards and Sachin Tendulkar played in strong batting teams and this fact is reflected in their top-30 positions. Maybe if we take Tendulkar's 1989-1995 period, he would be placed much higher.
The last two columns are interesting. If we take 1.0 as the hallmark of a world class innings (only 1.3% - once in two Tests), Bradman has achieved this in 10% of the innings he has played. Lara comes next with a creditable 7.3%. Hobbs is at 6.9%. Robin Smith is a surprise at 6.5%. Similarly, taking 0.25 as an above-average level contribution, Bradman clocks in at 42.5% and Lara at 32.3%.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.420 | WR Hammond | 57 | 3755 | 65.88 | 24.0 |
| 2 | 0.415 | DG Bradman | 56 | 5078 | 90.68 | 23.2 |
| 3 | 0.347 | BC Lara | 68 | 3860 | 56.76 | 23.6 |
| 4 | 0.316 | GM Turner | 69 | 2887 | 41.84 | 21.8 |
| 5 | 0.313 | IVA Richards | 63 | 3787 | 60.11 | 19.7 |
| 6 | 0.299 | DL Amiss | 70 | 3305 | 47.21 | 20.9 |
| 7 | 0.298 | L Hutton | 131 | 6721 | 51.31 | 39.0 |
| 8 | 0.285 | JB Hobbs | 98 | 5153 | 52.58 | 27.9 |
| 9 | 0.283 | Saeed Ahmed | 59 | 2498 | 42.34 | 16.7 |
| 10 | 0.281 | GA Gooch | 189 | 7990 | 42.28 | 53.2 |
| 11 | 0.267 | KC Sangakkara | 193 | 10468 | 54.24 | 51.5 |
| 12 | 0.267 | DA Warner | 55 | 2462 | 44.76 | 14.7 |
| 13 | 0.266 | AJ Stewart | 112 | 4655 | 41.56 | 29.8 |
| 14 | 0.263 | SM Gavaskar | 199 | 9442 | 47.45 | 52.3 |
| 15 | 0.258 | Hanif Mohammad | 62 | 2585 | 41.69 | 16.0 |
| 16 | 0.254 | VT Trumper | 56 | 1909 | 34.09 | 14.2 |
| 17 | 0.253 | KC Wessels | 55 | 2333 | 42.42 | 13.9 |
| 18 | 0.252 | DI Gower | 59 | 2692 | 45.63 | 14.9 |
| 19 | 0.249 | V Sehwag | 169 | 8166 | 48.32 | 42.2 |
| 20 | 0.249 | SP Fleming | 79 | 3309 | 41.89 | 19.7 |
It is not a surprise that Bradman leads in most of these tables. However in the 1-3 batting position table, Hammond just about edges ahead of him with a very high career HSI average of 0.42. Bradman's average is 0.415. Lara is in third place with 0.347. Turner is a surprise fourth with 0.316. It is clear that Richards out-performed his compatriots quite significantly with 0.313. Readers can see that the 20th entry in this table has a relatively high average HSI of 0.249.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.339 | BC Lara | 163 | 8079 | 49.56 | 55.3 |
| 2 | 0.337 | DG Bradman | 24 | 1918 | 79.92 | 8.1 |
| 3 | 0.303 | ED Weekes | 70 | 3858 | 55.11 | 21.2 |
| 4 | 0.301 | AD Nourse | 60 | 2940 | 49.00 | 18.1 |
| 5 | 0.250 | A Flower | 104 | 4364 | 41.96 | 26.0 |
| 6 | 0.247 | RN Harvey | 57 | 2693 | 47.25 | 14.1 |
| 7 | 0.239 | LRPL Taylor | 96 | 4142 | 43.15 | 22.9 |
| 8 | 0.238 | Mohammad Yousuf | 151 | 7378 | 48.86 | 36.0 |
| 9 | 0.230 | DJ Cullinan | 110 | 4229 | 38.45 | 25.3 |
| 10 | 0.230 | DCS Compton | 116 | 5422 | 46.74 | 26.7 |
| 11 | 0.230 | JR Reid | 99 | 3201 | 32.33 | 22.8 |
| 12 | 0.225 | S Chanderpaul | 228 | 10215 | 44.80 | 51.2 |
| 13 | 0.225 | SR Tendulkar | 325 | 15809 | 48.64 | 73.1 |
| 14 | 0.225 | PA de Silva | 148 | 5896 | 39.84 | 33.4 |
| 15 | 0.219 | Javed Miandad | 183 | 8678 | 47.42 | 40.1 |
| 16 | 0.219 | PBH May | 59 | 2634 | 44.64 | 12.9 |
| 17 | 0.219 | GR Viswanath | 148 | 5605 | 37.87 | 32.4 |
| 18 | 0.218 | RA Smith | 93 | 3566 | 38.34 | 20.3 |
| 19 | 0.216 | MD Crowe | 121 | 5209 | 43.05 | 26.2 |
| 20 | 0.214 | JH Kallis | 201 | 9896 | 49.23 | 42.9 |
In positions 4-7, Lara edges out Bradman by the third decimal. Then come the middle-order giants: Weekes, Dudley Nourse, Andy Flower and Neil Harvey. Tendulkar has an average HSI of 0.225 in these positions. Barring one innings, this is Tendulkar's entire career.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.516 | BC Lara | 58 | 4000 | 68.97 | 29.9 |
| 2 | 0.454 | DG Bradman | 22 | 2387 | 108.50 | 10.0 |
| 3 | 0.295 | IVA Richards | 48 | 2531 | 52.73 | 14.2 |
| 4 | 0.295 | RB Kanhai | 44 | 2869 | 65.20 | 13.0 |
| 5 | 0.288 | Javed Miandad | 60 | 3730 | 62.17 | 17.3 |
| 6 | 0.279 | KC Sangakkara | 63 | 3477 | 55.19 | 17.6 |
| 7 | 0.260 | WR Hammond | 46 | 2691 | 58.50 | 12.0 |
| 8 | 0.258 | S Chanderpaul | 62 | 3396 | 54.77 | 16.0 |
| 9 | 0.258 | CL Hooper | 42 | 1791 | 42.64 | 10.8 |
| 10 | 0.256 | CG Greenidge | 49 | 2455 | 50.10 | 12.6 |
| 11 | 0.251 | Mohammad Yousuf | 42 | 2060 | 49.05 | 10.5 |
| 12 | 0.250 | GR Viswanath | 45 | 1688 | 37.51 | 11.2 |
| 13 | 0.248 | DPMD Jayawardene | 71 | 3695 | 52.04 | 17.6 |
| 14 | 0.244 | V Sehwag | 45 | 2586 | 57.47 | 11.0 |
| 15 | 0.235 | KF Barrington | 41 | 2726 | 66.49 | 9.7 |
| 16 | 0.234 | IT Botham | 57 | 2261 | 39.67 | 13.3 |
| 17 | 0.230 | SP Fleming | 58 | 2980 | 51.38 | 13.3 |
| 18 | 0.228 | SR Tendulkar | 89 | 5518 | 62.00 | 20.3 |
| 19 | 0.227 | GA Gooch | 68 | 3101 | 45.60 | 15.4 |
| 20 | 0.223 | TT Samaraweera | 42 | 2472 | 58.86 | 9.4 |
In Tests, the first innings is the marker-setting innings. The second innings is more often a reactive taking-stock innings. The third innings is a target-setting one. The fourth innings always has a target. It could be one run to win, 731 runs to win, batting out 200 overs et al. Lara leads the first innings HSI table with a remarkable average of 0.516, one of only two times a batsman has exceeded 0.5 in these tables. Bradman follows with 0.454. And then daylight and Richards and Rohan Kanhai follow with 0.295. Lara's RpI for first innings is a high 68.97.
Gavaskar is conspicuous by failing to make the cut. His HSI average is only 0.194. Milind's father is a big fan of Gavaskar. So he had the right to criticise on the lines "Yeh pyar hai, gila nahin [It is my love, not a complaint]", when he once said that India as a team would have fared better if Gavaskar eked out his second-innings performance in the first innings since the chances of a win were slim at the start of second innings. Well said, Mr Pandit.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.402 | L Hutton | 44 | 2673 | 60.75 | 17.7 |
| 2 | 0.323 | BC Lara | 72 | 4249 | 59.01 | 23.3 |
| 3 | 0.312 | DG Bradman | 28 | 2310 | 82.50 | 8.7 |
| 4 | 0.302 | GP Thorpe | 56 | 2873 | 51.30 | 16.9 |
| 5 | 0.286 | V Sehwag | 58 | 3823 | 65.91 | 16.6 |
| 6 | 0.286 | PA de Silva | 43 | 2264 | 52.65 | 12.3 |
| 7 | 0.283 | KP Pietersen | 46 | 2521 | 54.80 | 13.0 |
| 8 | 0.273 | SM Gavaskar | 62 | 3552 | 57.29 | 17.0 |
| 9 | 0.266 | Mohammad Yousuf | 46 | 2977 | 64.72 | 12.3 |
| 10 | 0.261 | MC Cowdrey | 51 | 2537 | 49.75 | 13.3 |
| 11 | 0.254 | RN Harvey | 42 | 2266 | 53.95 | 10.6 |
| 12 | 0.254 | DPMD Jayawardene | 69 | 4598 | 66.64 | 17.5 |
| 13 | 0.250 | AB de Villiers | 48 | 2638 | 54.96 | 12.0 |
| 14 | 0.242 | ME Trescothick | 40 | 2192 | 54.80 | 9.7 |
| 15 | 0.238 | R Dravid | 89 | 4984 | 56.00 | 21.2 |
| 16 | 0.228 | DI Gower | 52 | 2572 | 49.46 | 11.8 |
| 17 | 0.227 | KF Barrington | 40 | 2334 | 58.35 | 9.1 |
| 18 | 0.223 | KC Sangakkara | 57 | 3474 | 60.95 | 12.7 |
| 19 | 0.222 | SR Tendulkar | 106 | 5692 | 53.70 | 23.5 |
| 20 | 0.220 | AC Gilchrist | 47 | 2501 | 53.21 | 10.3 |
These are the reactive performances. Hutton leads with a career HSI average of 0.402. Lara follows next with 0.323 and then Bradman, with 0.312. Thorpe is in fourth place with 0.302. Then comes the marauder, Sehwag, with 0.286. Aravinda de Silva, Kevin Pietersen and Gavaskar are also up there.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.546 | DG Bradman | 15 | 1565 | 104.33 | 8.2 |
| 2 | 0.361 | AR Border | 76 | 3511 | 46.20 | 27.4 |
| 3 | 0.325 | DL Haynes | 41 | 1938 | 47.27 | 13.3 |
| 4 | 0.324 | GA Gooch | 66 | 2722 | 41.24 | 21.4 |
| 5 | 0.322 | KC Sangakkara | 59 | 3161 | 53.58 | 19.0 |
| 6 | 0.297 | JH Kallis | 67 | 3394 | 50.66 | 19.9 |
| 7 | 0.280 | VVS Laxman | 52 | 2332 | 44.85 | 14.5 |
| 8 | 0.274 | DI Gower | 62 | 2287 | 36.89 | 17.0 |
| 9 | 0.272 | AN Cook | 46 | 2212 | 48.09 | 12.5 |
| 10 | 0.270 | DC Boon | 55 | 2186 | 39.75 | 14.8 |
| 11 | 0.270 | BC Lara | 56 | 2264 | 40.43 | 15.1 |
| 12 | 0.263 | SR Tendulkar | 71 | 2989 | 42.10 | 18.7 |
| 13 | 0.260 | ML Hayden | 41 | 2152 | 52.49 | 10.7 |
| 14 | 0.259 | PA de Silva | 47 | 1692 | 36.00 | 12.2 |
| 15 | 0.254 | BB McCullum | 40 | 1696 | 42.40 | 10.2 |
| 16 | 0.249 | Habibul Bashar | 44 | 1416 | 32.18 | 11.0 |
| 17 | 0.243 | Inzamam-ul-Haq | 51 | 2327 | 45.63 | 12.4 |
| 18 | 0.242 | SM Gavaskar | 55 | 2486 | 45.20 | 13.3 |
| 19 | 0.242 | G Boycott | 51 | 2085 | 40.88 | 12.3 |
| 20 | 0.239 | S Chanderpaul | 65 | 2194 | 33.75 | 15.5 |
The third innings sees Bradman with 0.546, although he played only 15 innings. The 270 would have certainly helped. We now have some other names indicating that the requirements are different. Border, Desmond Haynes, Gooch come in. For the first time, Lara moves past the top-ten positions.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.406 | SM Gavaskar | 33 | 1398 | 42.36 | 13.4 |
| 2 | 0.378 | GA Gooch | 29 | 1121 | 38.66 | 11.0 |
| 3 | 0.294 | DG Bradman | 15 | 734 | 48.93 | 4.4 |
| 4 | 0.277 | MA Atherton | 39 | 1375 | 35.26 | 10.8 |
| 5 | 0.274 | MA Butcher | 25 | 787 | 31.48 | 6.8 |
| 6 | 0.263 | G Boycott | 34 | 1234 | 36.29 | 8.9 |
| 7 | 0.263 | CH Gayle | 39 | 1280 | 32.82 | 10.3 |
| 8 | 0.243 | RN Harvey | 30 | 857 | 28.57 | 7.3 |
| 9 | 0.238 | Inzamam-ul-Haq | 31 | 867 | 27.97 | 7.4 |
| 10 | 0.232 | L Hutton | 31 | 953 | 30.74 | 7.2 |
| 11 | 0.231 | BC Lara | 46 | 1440 | 31.30 | 10.6 |
| 12 | 0.229 | AJ Stewart | 39 | 1136 | 29.13 | 8.9 |
| 13 | 0.227 | GC Smith | 41 | 1611 | 39.29 | 9.3 |
| 14 | 0.223 | IR Bell | 29 | 803 | 27.69 | 6.5 |
| 15 | 0.219 | ME Waugh | 27 | 820 | 30.37 | 5.9 |
| 16 | 0.212 | CG Greenidge | 38 | 1383 | 36.39 | 8.1 |
| 17 | 0.208 | Younis Khan | 29 | 1003 | 34.59 | 6.0 |
| 18 | 0.208 | JG Wright | 27 | 734 | 27.19 | 5.6 |
| 19 | 0.205 | G Kirsten | 29 | 780 | 26.90 | 5.9 |
| 20 | 0.196 | V Sehwag | 34 | 901 | 26.50 | 6.7 |
Gavaskar leads in the fourth-innings table with 0.406. Gooch follows closely. Bradman, with only 15 innings is next. Graeme Smith is in the top 20, with a HSI average of 0.227, but with a very high aggregate of 1611 runs. I wonder whether there was a case for combining the first and second innings as "first" and third and fourth as "second". However, what dissuaded me from doing that was my take that the third and fourth innings are quite different in the challenges faced.
Tendulkar is placed at 28th with an average HSI value of 0.179. Laxman is below average in the first innings but far better in the third and fourth innings while Tendulkar is vice versa. Dravid is better placed in innings two and three. The bottom line is that these three gentlemen worked beautifully as a team.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.402 | DG Bradman | 50 | 4322 | 86.44 | 20.1 |
| 2 | 0.368 | BC Lara | 111 | 6217 | 56.01 | 40.8 |
| 3 | 0.300 | GA Gooch | 126 | 5708 | 45.30 | 37.8 |
| 4 | 0.289 | RA Smith | 62 | 2631 | 42.44 | 17.9 |
| 5 | 0.276 | DCS Compton | 76 | 3963 | 52.14 | 21.0 |
| 6 | 0.267 | Mohammad Yousuf | 52 | 3067 | 58.98 | 13.9 |
| 7 | 0.266 | DPMD Jayawardene | 121 | 6846 | 56.58 | 32.1 |
| 8 | 0.264 | PA de Silva | 72 | 3290 | 45.69 | 19.0 |
| 9 | 0.262 | L Hutton | 77 | 3930 | 51.04 | 20.2 |
| 10 | 0.257 | RN Harvey | 66 | 2806 | 42.52 | 17.0 |
| 11 | 0.250 | KP Pietersen | 89 | 4537 | 50.98 | 22.3 |
| 12 | 0.248 | MJ Slater | 57 | 2842 | 49.86 | 14.2 |
| 13 | 0.244 | M Azharuddin | 66 | 3412 | 51.70 | 16.1 |
| 14 | 0.240 | JH Edrich | 77 | 3155 | 40.97 | 18.5 |
| 15 | 0.239 | DJ Cullinan | 59 | 2363 | 40.05 | 14.1 |
| 16 | 0.239 | SM Gavaskar | 106 | 5031 | 47.46 | 25.4 |
| 17 | 0.237 | GR Viswanath | 80 | 3280 | 41.00 | 19.0 |
| 18 | 0.236 | KC Sangakkara | 108 | 6138 | 56.83 | 25.5 |
| 19 | 0.236 | PBH May | 57 | 2865 | 50.26 | 13.4 |
| 20 | 0.225 | S Chanderpaul | 119 | 5630 | 47.31 | 26.8 |
Bradman was king at home. Lara follows closely. And then Gooch and, quite surprisingly, Robin Smith.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.375 | DG Bradman | 30 | 2674 | 89.13 | 11.2 |
| 2 | 0.364 | WR Hammond | 72 | 4245 | 58.96 | 26.2 |
| 3 | 0.361 | L Hutton | 61 | 3041 | 49.85 | 22.0 |
| 4 | 0.330 | JB Hobbs | 62 | 3475 | 56.05 | 20.4 |
| 5 | 0.315 | BC Lara | 121 | 5736 | 47.40 | 38.1 |
| 6 | 0.290 | KC Sangakkara | 87 | 4082 | 46.92 | 25.2 |
| 7 | 0.288 | SM Gavaskar | 104 | 4926 | 47.37 | 29.9 |
| 8 | 0.288 | KF Barrington | 57 | 3375 | 59.21 | 16.4 |
| 9 | 0.272 | V Sehwag | 91 | 3930 | 43.19 | 24.8 |
| 10 | 0.267 | A Flower | 56 | 2307 | 41.20 | 15.0 |
| 11 | 0.263 | AR Border | 118 | 5154 | 43.68 | 31.0 |
| 12 | 0.258 | M Amarnath | 61 | 2967 | 48.64 | 15.7 |
| 13 | 0.250 | SR Tendulkar | 176 | 8705 | 49.46 | 44.1 |
| 14 | 0.248 | CH Gayle | 87 | 3633 | 41.76 | 21.6 |
| 15 | 0.248 | R Dravid | 166 | 7690 | 46.33 | 41.1 |
| 16 | 0.236 | SP Fleming | 98 | 4216 | 43.02 | 23.1 |
| 17 | 0.236 | G Boycott | 93 | 3758 | 40.41 | 21.9 |
| 18 | 0.234 | IVA Richards | 115 | 5404 | 46.99 | 26.9 |
| 19 | 0.234 | Hanif Mohammad | 53 | 2221 | 41.91 | 12.4 |
| 20 | 0.232 | DI Gower | 90 | 3713 | 41.26 | 20.9 |
This definition of away included neutral locations. Look at the top five positions. Bradman, Hammond (no doubt helped by the 336 not out), Hutton, Hobbs and Lara: five of the greatest batsmen who ever lived. Gavaskar is also there. Of the modern batsmen, Sangakkara (with considerable help from runs against Bangladesh) and Sehwag (with very little against Bangladesh) are in the top ten.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.480 | DG Bradman | 43 | 4813 | 111.93 | 20.7 |
| 2 | 0.373 | GR Viswanath | 37 | 1637 | 44.24 | 13.8 |
| 3 | 0.345 | GA Gooch | 55 | 2867 | 52.13 | 19.0 |
| 4 | 0.317 | Saeed Anwar | 36 | 2254 | 62.61 | 11.4 |
| 5 | 0.312 | WR Hammond | 44 | 2584 | 58.73 | 13.7 |
| 6 | 0.302 | JB Hobbs | 45 | 2720 | 60.44 | 13.6 |
| 7 | 0.290 | GP Thorpe | 63 | 3006 | 47.71 | 18.3 |
| 8 | 0.284 | KC Sangakkara | 74 | 4913 | 66.39 | 21.0 |
| 9 | 0.280 | GS Chappell | 62 | 3595 | 57.98 | 17.4 |
| 10 | 0.274 | BC Lara | 52 | 2929 | 56.33 | 14.2 |
| 11 | 0.269 | Inzamam-ul-Haq | 76 | 4690 | 61.71 | 20.5 |
| 12 | 0.266 | L Hutton | 48 | 2678 | 55.79 | 12.8 |
| 13 | 0.264 | M Azharuddin | 32 | 1609 | 50.28 | 8.5 |
| 14 | 0.264 | DA Warner | 31 | 1608 | 51.87 | 8.2 |
| 15 | 0.247 | JH Edrich | 35 | 1771 | 50.60 | 8.6 |
| 16 | 0.241 | KP Pietersen | 67 | 3655 | 54.55 | 16.1 |
| 17 | 0.241 | RN Harvey | 66 | 3253 | 49.29 | 15.9 |
| 18 | 0.240 | GS Sobers | 46 | 3097 | 67.33 | 11.1 |
| 19 | 0.238 | IT Botham | 47 | 1918 | 40.81 | 11.2 |
| 20 | 0.238 | C Hill | 44 | 2223 | 50.52 | 10.5 |
In the wins table, Bradman's name is expected. But Gundappa Viswanath's presence is wholly unexpected. That means he played many valuable innings in the 37 India wins. Saeed Anwar's contribution to Pakistan wins is highlighted. Lara is in tenth position, albeit with a good HSI average of 0.274.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.461 | L Hutton | 39 | 1700 | 43.59 | 18.0 |
| 2 | 0.382 | DL Haynes | 30 | 1065 | 35.50 | 11.5 |
| 3 | 0.361 | BC Lara | 126 | 5316 | 42.19 | 45.5 |
| 4 | 0.334 | HW Taylor | 46 | 1569 | 34.11 | 15.4 |
| 5 | 0.326 | GN Yallop | 32 | 1035 | 32.34 | 10.4 |
| 6 | 0.304 | RN Harvey | 30 | 962 | 32.07 | 9.1 |
| 7 | 0.288 | Saeed Ahmed | 30 | 1135 | 37.83 | 8.6 |
| 8 | 0.283 | SR Tendulkar | 112 | 4088 | 36.50 | 31.7 |
| 9 | 0.281 | GM Turner | 35 | 874 | 24.97 | 9.8 |
| 10 | 0.273 | RA Smith | 52 | 1734 | 33.35 | 14.2 |
| 11 | 0.271 | PBH May | 30 | 1215 | 40.50 | 8.1 |
| 12 | 0.270 | AD Nourse | 34 | 1331 | 39.15 | 9.2 |
| 13 | 0.263 | B Sutcliffe | 46 | 1222 | 26.57 | 12.1 |
| 14 | 0.261 | JB Hobbs | 42 | 1889 | 44.98 | 11.0 |
| 15 | 0.261 | A Flower | 66 | 2372 | 35.94 | 17.3 |
| 16 | 0.254 | ME Trescothick | 40 | 1467 | 36.67 | 10.1 |
| 17 | 0.248 | RB Kanhai | 40 | 1340 | 33.50 | 9.9 |
| 18 | 0.247 | Mohammad Yousuf | 65 | 2393 | 36.82 | 16.1 |
| 19 | 0.241 | AI Kallicharran | 30 | 937 | 31.23 | 7.2 |
| 20 | 0.240 | JG Wright | 46 | 1365 | 29.67 | 11.0 |
Note the low RpI values of batsmen in this table covering losses. Hutton has performed valiantly in the losses. Haynes and Lara are also there. Many of Tendulkar's losses would have occurred during the early years. Incidentally, this is the only featured table in which Bradman is not present. That is because, in the 22 Australia losses, Bradman averaged only 0.20 in the HSI value measure. His RpI fell to a mortal value of 43.2.
| SNo | Avge HSI | Batsman | Innings | Runs | RpI | Total HSI |
|---|---|---|---|---|---|---|
| 1 | 0.462 | CH Gayle | 45 | 2990 | 66.44 | 20.8 |
| 2 | 0.418 | DG Bradman | 15 | 1231 | 82.07 | 6.3 |
| 3 | 0.356 | BC Lara | 54 | 3708 | 68.67 | 19.2 |
| 4 | 0.341 | Hanif Mohammad | 52 | 2771 | 53.29 | 17.7 |
| 5 | 0.340 | DL Amiss | 34 | 1643 | 48.32 | 11.6 |
| 6 | 0.327 | PA de Silva | 56 | 3154 | 56.32 | 18.3 |
| 7 | 0.316 | SM Gavaskar | 103 | 6101 | 59.23 | 32.5 |
| 8 | 0.307 | G Kirsten | 46 | 2370 | 51.52 | 14.1 |
| 9 | 0.301 | V Sehwag | 54 | 3118 | 57.74 | 16.2 |
| 10 | 0.299 | WR Hammond | 60 | 3614 | 60.23 | 17.9 |
| 11 | 0.298 | AR Border | 99 | 5217 | 52.70 | 29.5 |
| 12 | 0.291 | CL Hooper | 44 | 2257 | 51.30 | 12.8 |
| 13 | 0.290 | IVA Richards | 54 | 3043 | 56.35 | 15.7 |
| 14 | 0.283 | KC Sangakkara | 59 | 3733 | 63.27 | 16.7 |
| 15 | 0.283 | Mohammad Yousuf | 34 | 2298 | 67.59 | 9.6 |
| 16 | 0.279 | KF Barrington | 65 | 3755 | 57.77 | 18.2 |
| 17 | 0.272 | MP Vaughan | 41 | 2102 | 51.27 | 11.2 |
| 18 | 0.271 | JH Kallis | 72 | 4337 | 60.24 | 19.5 |
| 19 | 0.269 | GA Gooch | 74 | 3400 | 45.95 | 19.9 |
| 20 | 0.261 | KP Pietersen | 52 | 2831 | 54.44 | 13.6 |
What do we have here? Chris Gayle leads the table. I get the feeling the two 300s, totaling 650 runs, have helped push this value up. Maybe for Lara also, and for Hanif.
The HSI is an excellent measure to capture two important aspects of a batsman score: the support he received (or lack of) and his contribution to the team score. The fact that 30 out of 52 would be rated much higher than 374 out of 756 indicates that the measure is size-independent. As such it has a tremendous value across years and Tests. The other inherent characteristic is the true peer-comparison aspects built in. And the fact that Clem Hill's 188 will be treated in identical manner to Jayawardene's 180, played 122 years later.
To download/view the file containing all qualifying entries of the 14 tables, please CLICK HERE. My take is that many of the questions can be answered if you download this file, and view the contents.
To download/view the huge Excel file (size-10 Mb) containing details of the 26000+ innings with HSI values 0.100 and above, please CLICK HERE. Instead of asking me obvious questions for which the answers are already there in the tables, you could download the file and view the tables.
This article has already raised very justified demands for similar articles, listed below. Some suggestions for performances to be included are already in. I will try and do these after a few days.
: Sub-100 innings, not just forgotten ones.
: Late-order innings.
However my next article will be a similar performance-measuring analysis for the forgotten lot: the Test bowlers.
Anantha Narayanan has written for ESPNcricinfo and CastrolCricket and worked with a number of companies on their cricket performance ratings-related systems
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