The best teams ever, take one

Having explained the ideas behind my system for rating test cricket teams, let’s now briefly discuss how I implemented it.  A database of all test cricket results can easily be downloaded from Cricinfo’s Statsguru service. And I wrote a program to parse and analyse these results in the programming language Perl, which is not a very fashionable language these days, but which is more than adequate for the task.  In fact, the core of the processing can be captured in a remarkably short program: iterative mathematical calculations are what computers do well.  And all 2000+ matches are easily analysed in around a second on a fairly old desktop computer. Most of the work of the program actually involves organising the results in a human-friendly way.

So, let’s first ask the question, who were the best (or, more accurately, most dominant) test teams of all time?  One issue here is that if team A had a high score at date X, that team almost certainly had almost as high a score shortly before and shortly after its peak; so the highest ratings ever could all belong to one team over a continuous period.  This might not be very interesting; so what I’ve done is divided test history into periods where one team was on top, and taken only the highest rating that each team held in one period.  And then top ten then comes out like this:

26 Dec 1999  24 Nov 2009  Australia      2 Jan 2008  283

18 Aug 1934  28 Jan 1955  Australia      5 Dec 1952  218

30 Nov 2012  25 Nov 2015  South Africa  22 Feb 2013  217

 6 Jul 2011   3 Feb 2012  England       18 Aug 2011  216

14 Sep 1983  26 Dec 1991  West Indies   11 Apr 1986  198

 5 Dec 1958  27 Jan 1961  Australia     21 Nov 1959  184

27 Jun 1930  23 Feb 1933  Australia      4 Mar 1932  169

23 Jan 1993  22 Jun 1995  West Indies   25 Mar 1994  168

 3 Aug 2010   6 Jul 2011  India          9 Oct 2010  166

 3 Feb 2012  30 Nov 2012  Australia      7 Apr 2012  163

Firstly, a few preliminaries.  In the table, the first column marks the start of a team’s period as world number one; the second date marks the end.  The team’s name is in the third column; the date of their highest rating during this period is in the third; and the rating itself is in the fifth.  In fact, there’s a complication with the dates.  Cricinfo makes the date a match starts available in an easy-to-download form.  So instead of recalculating the ratings after each match finishes, what I actually do is recalculate the ratings after all matches that started on a given day ended. It’s the date that those matches started which gets recorded as an attribute of the rating calculated after it ended – i.e. the Australians had a rating of 283 after the conclusion of the match that started on the 2nd January, 2008. This explains the apparent oddity that teams seem to have inevitably won the game that appears to have followed the date of their peak ranking. 

Secondly, some of the great teams have been rated the best in the world continuously for some very long periods.  Everyone knows the Australians were a great side in the early 21^st century:  we see they enjoyed almost 10 years on top of the rankings.  The Australians of Bradman (and shortly after) had over 20 dominant years (although World War Two counts for a few of those, and I didn’t adjust my system to account for the absence of test cricket during this period, a decision that could be questioned: perhaps I should have suspended the system and restarted with all teams at zero?).  Eight years of dominance were enjoyed by the West Indies from 1983 onwards. And all these sides duly had very high ratings at their peak.

But the Australians of recent vintage really were exceptionally strong. Indeed, the ICC agrees (although their ratings only cover the post-war years): no other team has ever been this dominant.  In fact, some of their best players of this era (Warne, McGrath, Langer) retired a year or so before the team’s peak rating in 2008.  But the ratings inevitably represent past, not future performance; and throughout 2007, a side without these greats actually added to the performances of their predecessors. Here’s another fun fact: between 1930 and 1955, Australia were just briefly off the number one slot in late 1933 and early 1934.  What weakened Bradman’s otherwise invincible team during this period?  The answer, of course, is the infamous bodyline series, where England used leg-theory to negate the Australian giant.

But there are also some apparent problems.  England had a good side in 2011, and South Africa thereafter.  But few would consider these teams amongst the best of all time.  Nonetheless, here they are, at 3^rd and 4^th place in the all-time list. The teams in 9^th and 10^th place are also of recent vintage, and might also be considered surprising inclusions.

One explanation for this is simply that we’ve ranked teams here by their highest rating, but what really makes us consider a team to be great is a long period in the number one slot – not the degree of dominance, but the length of time for which a team is dominant.  This value is, after all, the first thing I noticed when reviewing the list: maybe I should have sorted the teams by that criterion instead?  But there’s also another problem.  A team’s rating shows its average dominance against the other test playing sides.  And in recent years, Bangladesh and Zimbabwe have been persistently weak with respect to other teams (Zimbabwe’s current rating is -315; Bangladesh had a rating of -334 in 2008).  In other words, both these teams have been weaker than any team has ever been strong. For what it’s worth, when Australia had a rating of 283, Bangladesh had a rating of -321, and the net ratings difference of 604 is associated with an expected value for Australia in a match between the two sides of 0.985 – i.e. the ratings would have predicted something very close to a certain Australian win.

And the presence of two consistently weak teams weakens the average strength of all teams relative to the strongest ones (and it's that which the ratings measure). So even though we tried to make the ratings comparable (as a measure of dominance), the raw ratings still don’t necessarily tell us exactly what we might want to know.  So in the next post, we’re going to play with some different criteria for ordering teams, and see what sides come to the fore under each of them.