Batsman analysis by bowler-pitch quality - part one

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Player Group wise distribution table

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

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

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

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

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

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

Platinum Group (Groups 9 and 10) tables

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

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

Gold Group (Groups 7 and 8) tables

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

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

Silver Group (Groups 6 and 5) tables

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

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

Bronze Group (Groups 4 and 3) tables

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

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

Tin Group (Groups 2 and 1) tables

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

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

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

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

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

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

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

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