Tests - Pitch type analysis: The final solution ???

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

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

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

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

Now for the Pitch Type methodology.

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

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

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

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

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

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

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

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

2. For each period, by Test, thetop-7 partnershipaverages are determined, that toofor the two teams independently.

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

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

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

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

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

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

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

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

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

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

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

Period : 1877-1914

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

Period : 1920-1939

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

Period : 1946-1959

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

Period : 1960-69

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

Period : 1970-79

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

Period : 1980-89

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

Period : 1990-1998

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

Period : 1999-2004

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

Period : 2005-2012

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

Home Top-7 partnership averages: by country

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

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

Visiting Top-7 partnership averages: by country

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

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