Data | From Lara and Sachin to Smith and Labuschagne, who are the best batsmen in Tests across eras Premium

Labuschagne and Smith’s batting averages tower over their peers in a way that places them among the all­-time greats of the game

Best batsmen in Tests: Australia’s Steve Smith celebrates after scoring a century during play on the second day of the first cricket test between Australia and the West Indies in Perth, Australia, Thursday,

Test cricket in the T20 era has been increasingly decisive with most games finishing with a win/loss record instead of draws. Considering that Test victories require the winning team to get the opposition team all out at least once, this means that bowlers have rarely had it so good in Tests as they have in the current era. Which also suggests that batting in Tests has become more challenging than before.

Only 33 batsmen have historically scored at an average of more than 50 per innings and have played at least 30 Test matches. And in the current era, there exist just three such batsmen — Steve Smith, Marnus Labuschagne of Australia, and New Zealand’s Kane Williamson averaging 60.89, 59.43, 53.83 runs. Table 1 lists the currently active batsmen (who played at least one Test in 2022) with at least 30 Tests under the belt, ordered on batting average.

Chart appears incomplete? Click to remove AMP mode

Steve Smith is just one among three batsmen who have had an average of over 60 and have played at least 30 Tests. Fellow Aussie Donald Bradman with 99.94 and Englishman Herbert Sutcliffe with 60.73 are the other two.

Simply comparing batting averages is flawed — a batsman in an era could have faced better bowlers (or worse) than someone from another age. Then, there are the changes in rules, conditions, and technology (the covering of pitches; the limit on the bouncers per over; the introduction of helmets; DRS — just a few of these).

We need a method of normalisation that accounts for changes in eras and is able to compare batsmen. One way is to measure how a batsman has done in his time — the extent to which he has outperformed his peers. We can then compare this margin with the margins of other batsmen.

To do this, we find the difference between a player’s batting average and the average number of runs scored by all other batsmen during the period the player was active. For instance, Sachin Tendulkar averaged 53.78 between his debut in 1989 and retirement in 2013. All other players in this 24-year period averaged 33.34. The difference between Tendulkar and the rest in his time is 20.44. This difference is what we term as “Net Average”.

Click to subscribe to our Data newsletter

Table 2 shows the top batsmen ordered on “Net Average”. The Don tops the list by far — his 99.94 average was 67 runs (and change) more than the average runs for batters during his era — a “net average” that is more than twice the next best batsman in the list — Labuschagne with 29.55. Smith lags behind slightly. Tendulkar ranks 17th and Kohli ranks 38th.

While it is useful to limit this analysis to batsmen who have played at least 30 matches, we cannot rank batsmen merely on “net average”. That is because longevity in Test cricket matters and even elite batsmen undergo a regression in their ability to score in the later end of their careers.

Chart 1 plots the “Net Average” against the Total runs scored by batsmen who played at least 30 Tests. The chart is illuminating — it also marks out those batsmen (red dot) with a “net average” of just about 20 or more and also scored more than 7,000 runs and these are truly the elite in Test cricket.

This analysis is not complete, ideally, batsmen should be further classified on batting positions. But suffice to say, the Don once again stands out (literally) in his high net average, Tendulkar for the sheer volume of runs. Others like South Africa’s Jacques Kallis, Sri Lanka’s Kumar Sangakkara, Australia’s Smith and Chappell, West Indies’ Gary Sobers, Brian Lara, Pakistan’s Javed Miandad and England’s Wally Hammond round out this elite list. They indeed are the truly best ever.

srinivasan.vr@thehindu.co.in

Source: espncricinfo.com

Listen to our Data Point Podcast: How ‘The Hindu’ data team covers elections using night lights and census data

A week after the Gujarat elections, The Hindu’s data team breaks down the evolution of their election coverage.