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Opinion

Comparing the Waughs against Zimbabwe

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Roar Rookie
30th November, 2021
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The Waugh lads’ performances against Zimbabwe provide an ideal opportunity to showcase Enhanced Statistical Interrogation (ESI) techniques.

The Waughs played only one innings each against Zimbabwe in the one-off Harare Test played in October 1999.

Some might think that no meaningful analysis is possible with such a small sample size. Enter Enhanced Statistical Interrogation – it deals with these sorts of issues with ease.

Zimbabwe batted first and were bundled out for 194, with Neil Johnson top scoring with 75.

The Australians responded with 422. Mark scored 90 batting at four and Steve scored 151 not out batting at five, with Damien Fleming chiming in with a brisk 65 from number nine.

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Zimbabwe managed to produce 232 in their second innings, which the Australians passed at 0-5 in their second innings (Greg Blewett four not out, Michael Slater zero not out, extras one).

Is Steve Waugh an infinitely better bat than Mark? After all, Mark averages 90 against Zimbabwe and Steve averages infinity. Everybody thinks that 151 divided by zero equals infinity, the Riemann Sphere notwithstanding.

How does Enhanced Statistical Interrogation deal with this seemingly tricky situation? There are three techniques or procedures: capping, debloating and boosting.

Capping deals with it thus: the Australians needed to score no more than 300 in the first innings to win the Harare Test, therefore the last 122 runs were meaningless, of which around 65 were scored by Steve.

Steve Waugh

(Credit: Ben Radford/Allsport/Getty Images)

This proves beyond doubt that Steve’s capped score is 86. Mark is plus four using this technique (i.e. 90 minus 86).

Mark came out to bat with Australia struggling at 2-7. The match was in the balance.

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He righted the ship with a partnership of 89 with Justin Langer followed by 78 with Steve.

Mark departed the scene at 5-174. The fact that he got out proves that he knew the job was done and that batting would be simple from that point.

This is where debloating comes in. Steve was 30 at the time, therefore the 121 runs that followed are bloated.

This is tackled by dividing Fleming’s 65 by his career average of 19.06, which produces a bloat quotient (or BQ) of 3.41, i.e. every 3.41 runs were actually only worth one.

The BQ is then applied to Steve’s 121 to produce a debloated score of 35.48, which is added to his 30 pure runs. Steve’s debloated score is thus 65.48. Mark is up 25.42.

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Boosting is a related technique: hard runs are adjusted to reflect their true value.

The boost monomial (or BM) in this case is 1.75, which when applied to Mark’s 90 produces a score of 157.5. Mark is ahead of Steve by 6.5 runs.

Note that the appropriate BM must be selected from the boost monomial log-log plot in consultation with yourself.

The third law of Enhanced Statistical Interrogation is that if all three techniques produce results that are in the same direction then the result is valid.

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