Statistics are great and can be a very powerful tool for analysis of sporting matches. Over the years, sport has evolved into a “big business” providing a source of entertainment, revenue and employment. This places pressure on sports people and their teams to become not only successful, but the best.
These days, every professional sports team keeps statistics and records of their own players to measure their performance and value. As with anything good in life however, for every good statistic there are a hundred bad ones waiting in the wings to trip and mislead you.
For example, James Faulkner was averaging over 100 with the bat for most of the 2017-18 Big Bash League season. Any casual observer could be lead to believe that Faulkner was punching well above his weight. In a match against the Sydney Sixers however, he came in just before the death and took 12 balls to score more than a single.
Of the 17 deliveries Faulkner faced during that innings, he hit just one boundary. This is a far more valuable piece of knowledge than Faulkner’s batting average, especially considering the game scenario. At the death with less than five overs remaining, being able to find the boundary is a critical component of maximising the team’s total.
We are not trying to single out Faulkner’s case in particular. It is crystal clear that he’s had more pressure placed on his shoulders ever since he, almost single-handedly, saved Australia’s bacon in a 2014 one-day international against England in Brisbane. We are simply trying to show that the misleading information provided by Faulkner the Finisher’s batting average is just one example of the kind of misleading statistics we are trying to eradicate.
It seems more and more that Twenty20 cricket is making a batsman’s average redundant. It should no longer be the preferred statistic for displaying a batsman’s proficiency in the shortest format of the game. This is largely thanks to the fact that the definition of the batting average and the equation used to calculate it do not match.
The actual batting average equation offers a “reward” for batsmen who survive their innings and remain not out by only using the number of innings in which the batsman is dismissed in the denominator without any runs from those innings being removed from the numerator. If the calculation of batting average is flawed, then how it is applied in cricket is definitely flawed.
Under the current system, it is possible for two batsmen with significantly different performance records to record the same batting average. This leads to both players being assessed as having a similar level of performance and ability. A batsman that scores 19, 20, 25, 15 and 21 from five innings will have the same batting average as a batsman that scores 95, 2, 3, 0 and 0 in five innings.
Batting average is used as the primary assessor of a batsman’s ability. That’s why it is astounding that it remains such a crude predictor of the expected run output of a batsman during a game.
A batsman’s strike rate is also a crude indicator of how efficiently and quickly batsmen score their runs. The traditional batting strike rate provides a total of the expected number of runs a batsman will score after 100 balls. Being able to score runs quickly is an invaluable skill in Twenty20 cricket and therefore, a strike rate of 170 is more desirable than one of 100 because it means more runs will have been scored in the same amount of time.
Like the batting average however, this statistic is not without its flaws. For starters, the batting strike rate spits out the expected number of runs a batsman will score after 100 balls. A game of Twenty20 cricket lasts for 120 balls (20 overs * 6 balls). When was the last time ONE batsman faced 100 balls in a T20 match?
Let’s look at another example. Suppose a batsman came out to bat after the fall of a wicket, hit the first ball he faced for six and then got out with the very next delivery. A quick glance at the strike rate will tell you he was striking at an impressive 300, but a closer analysis of the game scenario will tell you that his team lost 2 wickets for 6 runs off just 3 balls. Therefore, this batsman was actually a detriment to his team for giving up his wicket so easily.
This is the purpose of this website. If you look under the surface, every statistic will have some sort of flaw spreading its lies about player performances. However, the aim of this website is to weed out some of the more misleading statistics in order to guide you towards more in-depth assessments of cricket statistics.