Matches (12)
IPL (2)
Women's Tri-Series (SL) (1)
County DIV1 (3)
County DIV2 (4)
QUAD T20 Series (MAL) (2)
Anantha Narayanan

An in-depth look at Twenty20 results

A detailed study of Twenty20 results indicates the matches haven't been as close as you'd expect

When one views T20 matches, there seems to be a feeling of continuous activity, not because there is a contest between bat and ball but because of the boundaries being hit, the stadium noise and the IPL hangover. At the end of the match Ravi Shastri, irrespective of how the match finished, would say that it was a "humdinger of a match". Alternately some other anchor would mouth similar "words of wisdom". But I have always felt that the matches are not as close as they are made out to be. The excitement seems to be a "manufactured" one. How does one prove or disprove this seemingly subjective observation? I propose to do that by delving into the scorecards and coming out with a suitable analysis.

First let us eliminate some of the matches. Needless to say that only T20 internationals will be considered. IPL matches are not true international matches. Also if the IPL is to be included, then all other club leagues should be included. All matches which finished through the D/L route are discarded. It is clear to most people that, Queen's honours notwithstanding, the learned duo, M/s Duckworth and Lewis, have made a pig's breakfast of the D/L calculations when it comes to T20 matches. More about it in a later article. Finally matches which finished in a tie and decided through the single-over-eliminator will be discarded. After all when the 40 overs were bowled, the teams have finished dead level.

That leaves us with 168 matches (out of the 185 we started with). Now we will separate the wins defending totals (first batting team wins) from the wins chasing the target totals since the two wins are as different as chalk and cheese. One is a bowler-driven defensive win and the other is a batsman-driven attacking win.

First let us take the matches won by teams batting first and defending their totals. There are 83 such matches, just below the 50% mark. There is only one objective in front of the defending team: restrict the opposite team to a total below their own total. Whether this is done by dismissing the other team or restricting them to a total below the total is immaterial. The win is stated as "by x runs" and this is the only measure necessary to measure the type of win. The only factor to be taken into consideration is that a match score of 200/190 is a less emphatic win than a match score of 100/90. This is achieved by dividing the run differential by the first innings total and the Win Index arrived at.

It is a fact that T20 wickets are cheaper to get than ODI wickets (a Balls-per-wicket value of 18.2 against 42.6). This makes the wickets valuation somewhat difficult. I tried adding the wickets captured component to the Win Index. It did not work out, especially for very close matches. Take a match such as 150/148 a.o. By all criteria this is a very close match and should have a very low Win Index value. However once I give credit to the winning team for capturing wickets, the Win Index moves way up and goes into a comfortable win zone (because of the 10 wickets), which is wrong.

A few statistical highlights of this group of matches.

1. The average Win Index is 20.5. This can be compared to the average for the other group later.
2. The average first innings score is 169 for 6.5 wickets.
3. The average second innings score is 133 for 8.5 wickets.
4. The average winning margin is 36 runs, which makes the wins quite comfortable.
5. Out of the 83 matches, the losing team has lost 8 or more wickets in 59 matches (71%).

Before we look at the tables, let me emphasise that absolute values cannot be used in these exercises. An over represents 5% of a team's balls-resource unlike ODIs in which an over represents 2% of the resource. There is less of a difference in terms of runs since T20 scoring rates are higher. Even then, 10 runs in T20 represents around 6% of the average T20 total while the same 10 runs represents around 4% in ODIs. What is normal in T20s is difficult in ODIs. Hence all comparisons are only in relative % values.

Now for the tables.

Matches won by teams defending totals

No  Win  MtId Cty  First Inns  Vs Second Inns  Vs Team Result
Index          <--Score-->     <--Score-->
1. 66.2 0027 Slk 260 6 20.0 Ken 88 10 19.3 lost by 172 runs 2. 61.6 0094 Saf 211 5 20.0 Sco 81 10 15.4 lost by 130 runs 3. 59.2 0075 Zim 184 5 20.0 Can 75 10 19.2 lost by 109 runs 4. 55.9 0002 Eng 179 8 20.0 Aus 79 10 14.3 lost by 100 runs 5. 50.7 0152 Win 138 9 20.0 Ire 68 10 16.4 lost by 70 runs 6. 50.2 0055 Pak 203 5 20.0 Bng 101 10 16.0 lost by 102 runs ... ... ... 70. 4.7 0114 Pak 149 4 20.0 Saf 142 5 20.0 lost by 7 runs 71. 4.6 0123 Pak 153 5 20.0 Nzl 146 5 20.0 lost by 7 runs 72. 3.2 0046 Ind 157 5 20.0 Pak 152 10 19.3 lost by 5 runs 73. 3.0 0036 Nzl 164 9 20.0 Eng 159 8 20.0 lost by 5 runs 74. 2.3 0130 Can 176 3 20.0 Ire 172 8 20.0 lost by 4 runs 75. 2.1 0120 Nzl 141 8 20.0 Slk 138 9 20.0 lost by 3 runs 76. 2.0 0109 Eng 153 7 20.0 Ind 150 5 20.0 lost by 3 runs 77. 1.6 0134 Aus 127 10 18.4 Pak 125 9 20.0 lost by 2 runs 78. 1.2 0007 Slk 163 10 20.0 Eng 161 5 20.0 lost by 2 runs 79. 1.0 0006 Saf 201 4 20.0 Aus 199 7 20.0 lost by 2 runs 80. 0.8 0179 Saf 120 7 20.0 Win 119 7 20.0 lost by 1 run 81. 0.8 0167 Nzl 133 7 20.0 Pak 132 7 20.0 lost by 1 run 82. 0.8 0099 Saf 128 7 20.0 Nzl 127 5 20.0 lost by 1 run 83. 0.7 0083 Aus 150 7 20.0 Nzl 149 5 20.0 lost by 1 run

It can be seen that 5 of the 83 matches have been won with a very high Win Index of 50+. However more importantly, only 14 matches (around one in six matches) could be classified as close matches. The winning margin in the other matches has been 10 runs or more which is quite comfortably a full-over score. This puts paid, at least for these types of wins, to the general feeling that the T20 matches are close matches. Five out of 6 are not.

Now for wins by the second batting teams. There are 85 such matches, which is just over 50%. These are batsmen-driven chasing wins. The chasing team works with two clearly identified resources. The first, and the more important one, explained later, is the number of balls, normally 120. The other one is the number of wickets, 10. The win is normally stated in the lesser of the two resources, wickets. This is less of a resource restriction since the overall balls-per-wicket figure for all 185 matches is 18.2, meaning that the average number of wickets lost would be 6.4 in a 120-ball innings.

The balls left and the wickets left form the basis for determining the Win Index. The proportion of balls left to the maximum balls carries a 66.7% weight. The wickets remaining carries a 33.3% weight. This is not a linear scale since the top order wickets are more valuable. The wicket values are 0.12, 0.12, 0.12, 0.12, 0.12, 0.10, 0.10, 0.08, 0.06 and 0.06 for wickets 1-10. For instance if a team has lost only 1 wicket, their valuation for this component is 0.293 (0.333*0.88). On the other hand if they have lost 7 wickets the valuation for this components 0.067 (0.333*0.20) and so on.

A few statistical highlights of this group of matches.

1. The average Win Index is 27.5. This is a 25% increase over the first group of matches indicating that the chasing wins are a little more easy and the index values are higher.
2. The average first innings score is 129 for 8.0 wickets.
3. The average second innings score is 131.6 for 3.8 wickets. This confirms the view that the wins are relatively easier.
4. The average winning margin is 6.2 wickets and 18 balls. which makes the wins very comfortable.
5. Out of the 83 matches, the losing team has lost 5 or fewer wickets in 68 matches (80%).

Matches won by teams chasing totals

No  Win  MtId Cty  First Inns  Vs Second Inns  Vs Team Result
Index          <--Score-->     <--Score-->
1. 72.2 0131 Bng 78 10 17.3 Nzl 79 0 8.2 won by 10 wickets 2. 70.4 0021 Ken 73 10 16.5 Nzl 74 1 7.4 won by 9 wickets 3. 65.5 0041 Slk 101 10 19.3 Aus 102 0 10.2 won by 10 wickets 4. 61.6 0014 Pak 129 8 20.0 Saf 132 0 11.3 won by 10 wickets 5. 58.3 0129 Sco 109 9 20.0 Ken 110 0 12.3 won by 10 wickets 6. 58.2 0052 Ind 74 10 17.3 Aus 75 1 11.2 won by 9 wickets 7. 57.0 0067 Ber 70 10 20.0 Can 71 2 10.3 won by 8 wickets ... ... ... 80. 9.4 0172 Nzl 149 6 20.0 Eng 153 7 19.1 won by 3 wickets 81. 8.9 0082 Slk 171 4 20.0 Ind 174 7 19.2 won by 3 wickets 82. 7.2 0176 Pak 191 6 20.0 Aus 197 7 19.5 won by 3 wickets 83. 7.2 0072 Slk 137 9 20.0 Pak 141 7 19.5 won by 3 wickets 84. 7.2 0048 Nzl 129 7 20.0 Saf 131 7 19.5 won by 3 wickets 85. 4.6 0151 Slk 135 6 20.0 Nzl 139 8 19.5 won by 2 wickets

In line with our findings, the top 7 wins have a Win Index value exceeding 55. Also only 6 of the matches could be termed close. The cut-off for determining close matches varies between the two types of wins.

Adding the five tied matches to the 168, only 25 of the 173 matches (14%) can be termed as quite close. The other 86% of the matches are relatively easier wins. This confirms my feeling that the excitement is mostly artificially created.

Those of you who would like to raise a point on the relative strengths of the teams, let me point out that in T20s there are fewer contests between the top teams and the minnows. This normally happens only in the World Cups.

Also furthermore, the lesser number of overs actually reduces the relative strength-differential between teams because there is lesser room for error. Hence, it is quite intriguing that there have been such wide margins of victory.

To view/down-load the table of defending wins, please click/right-click here.

To view/down-load the table of chasing wins, 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