Lies, Damned Lies & Statistics – The Moneyball Effect

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BEN ROBERTS ponders whether cricket coaches could gain inspiration from the 2011 movie Moneyball which tracks the story of Oakland A’s Billy Beane crafting a baseball club on a budget by employing computer-generated analysis and statistics.

I might as well throw my voice into the vortex of latter opinion and desire that has been borne out of 2011’s release of the film Moneyball. I only recently got around to watching this film, and enjoyed it immensely. The film’s release has awoken the rest of the sporting world to a concept that was not even new in the period portrayed in the movie, but has been around for over 30 years. Suddenly everyone wants a piece of the action, and to find the killer measurable statistic for their sport of choice that separates the wheat from the chaff.

Baseball is a sport that is made for such a concept. Without going into much detail, in my opinion baseball lends itself so easily to this analysis due to: 1) being very static in game play with players not moving around the field randomly but in a definite order; 2) having direct cause and effect relationships in the game play, for example an out always equals a run saved; 3) Major League Baseball being a market based sport (also replicated in many others but not cricket) meaning that value is something more easily determined as it comes in dollars and cents.

Cricket by contrast does not have such a static nature nor cause and effect relationships. While commentators always say that the best way to restrict scoring is to take wickets this is not an absolute (like baseball) until you are talking about the 10th wicket to fall. Neither does the sport have a market based nature, although players are more today shifting first-class teams the game remains a sport played at the highest level as a regional representative.

The key premise of the theory is stated early in the movie when Jonah Hill’s character tells Brad Pitt’s character that for years they have been asking the wrong question. They should be trying to buy wins (a direct result of runs scored and restricted) not players. The improvement in statistics themselves had been around for many years, the trouble was the ignorance of the users.

Cricket has a multitude of data already at its disposal. Former Australian coach John Buchanan was known for the recording of extensive data and this has now become the norm for most first-class teams. The difficulty is that unlike baseball where you can name what you want, cricket you cannot be as sure. Yes more runs are important, but in test matches you need to take wickets also.

Okay, then lets just use such analysis for limited over matches where it’s all about runs. Good idea, except last night I saw a rain interrupted T20 match get decided by the Duckworth-Lewis method which gets used a lot and relies on wickets in a calculation of a par score. As well, we still seem to value bowling in limited over games, if we are truly only after more runs why not simply stock your team with 11 batsman who can nominally roll their arm over and field well?

The difficulty is that we do not know what the question to ask is, what constitutes total value in a game of cricket? This is the entire premise of using such statistics and until you restrict the questions that you want the statistics answer you can have them tell you all manner of things. Let me give you an extreme example: You have two batsmen, 1 and 2. In traditional statistics both average 36 and  have a strike rate of 72 runs per 100 balls. A normal innings therefore for either is to score 36 runs off 50 deliveries.

So we have a dilemma: If we need to choose, both look equal based on traditional measures. Turning to a more  detailed statistical analysis we find that batsman 1 gets them in 36 singles whereas batsman 2 usually hits 6 sixes (I told you the example was extreme). Which batsman is the more valuable?

My initial reaction is to say batsman 1 is more valuable in that they turn the strike over to the other batsman giving greater chance for team scoring while they are at the crease whereas batsman 2 faces a stack of dot balls. But what is the effect on the bowlers? Does the potentially greater runs scored per single ball by player 2 make them more valuable? Unless you know what you really want statistics can tell you anything.

Do not read me wrong, such analysis has every place in the game but requires a liberal amount of common sense to be applied. You can easily measure the worth of two identically skilled players as above. You may use the above analysis in comparison to what the team needs, but you cannot make the clear cut decisions that they can in baseball as there is no single measure of value.

How would you statistically make the decision (as for the recent Melbourne test) whether to play an opening batsman Ed Cowan or all-rounder Daniel Christian? You are comparing apples with oranges. In baseball you can use a standard measure of total value to the team and cut through inconsistencies, in cricket understanding and intuition must still be applied.

I have only a rudimentary understanding of statistic usage, and someone more esteemed than I may be able to prove that there is a methodology escalating statistical analysis beyond being a support category in cricket decision making. But until that time remain wary of the limitations when trying to apply to cricket. Mark Twain believed it was Benjamin Disraeli who said “There are three kinds of lies: lies, damned lies, and statistics.” Though it remains historically an un-sourced statement, there is still much truth to it.

Ben contributes regularly to the following two Blogs:

Balanced Sports – The thinking fans sport opinion and analysis site.

Books with Balls – Reviewing the literature of a number of genres but definitely no Danielle Steele.

Recent World Cricket Stories:
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