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What would a modern player need to beat Bradman?

R

RossTaylorsBox

Cricket Web: All-Time Legend
They're not being compared and their method of comparison means little in the context of this paper. Now you can answer my question.
 
R

RossTaylorsBox

Cricket Web: All-Time Legend
Migara said:
Now if you do the same for bowling averages, it will actually show that it has a different distribution. Most likely averaging 19 with ball would be very much closer to averaging 90 with bat due to the extreme long tail in bowling averages. (zero inflation of batting averages vs infinity deflation in bowling averages)
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This also tells me you don't understand/didn't read the paper methodology. "Zero inflation" is a modelling technique for the large number of ducks, and so "infinity deflation" doesn't really make any sense in this context.
 
Spark

Spark

Global Moderator
Migara said:
Actually 14.8, 12.8 and 11.7 standard deviations are not that different from each other. all are extreme values, unlike 2.0 and 4.4. (Variances are compared as ratios via a F distribution). So this explains that GA Headly was not that different from Bradman. Actually he was black Bradman.

Now if you do the same for bowling averages, it will actually show that it has a different distribution. Most likely averaging 19 with ball would be very much closer to averaging 90 with bat due to the extreme long tail in bowling averages. (zero inflation of batting averages vs infinity deflation in bowling averages)
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?? I'm very confused. How does Headley, who has a distribution mean of 63, become the same as Bradman, distribution mean of 93?
 
Coronis

Coronis

International Coach
Going beyond basic averages is just too hard.

This may have reinvigorated my interest in maths though.
 
capt_Luffy

capt_Luffy

Cricketer Of The Year
Migara said:
Barnes and Tyson played in an era batting average was much lower than the present. Infact Barnes' adjusted average was around 20-21. Still a legend, but with the pack, rather than away from it.

If there is time I would model the averages with number of opposition players played against to see whether variability reduces when facing greater number of opponents.
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True for Barnes, but not Tyson. In the period he played, the mean batting average was hardly different than today's. Also, by that logic; how would you compare Lohman's adjusted bowling average? Is it equal to averaging 200 with the bat?
 
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S

subshakerz

Hall of Fame Member
Migara said:
Now this is the claim we have trouble with. Is he twice better as a 50 averaging batsman, say Tendulkar or Lara. Very difficult to say because there is no particular way to compare the quality of cricket they played, or the effect of increasing number of oppositions and conditions to play in. At best this is a subjective analysis.

May be some one use AI to model for all these variables and can come up with an answer.
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Tendulkar and Lara are ATG bats so he isn't twice as good as them.

Twice as good as regular worldclass bats so like twice as good as Mohd Yousuf or Jayawardena.
 
Migara

Migara

International Coach
capt_Luffy said:
True for Barnes, but not Tyson. In the period he played, the mean batting average was hardly different than today's. Also, by that logic; how would you compare Lohman's adjusted bowling average? Is it equal to averaging 200 with the bat?
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Lohmann also comes very close to 20 IIRC. You can check DoG's threads on the matter.
 
Migara

Migara

International Coach
RossTaylorsBox said:
This also tells me you don't understand/didn't read the paper methodology. "Zero inflation" is a modelling technique for the large number of ducks, and so "infinity deflation" doesn't really make any sense in this context.
Click to expand...
Exact opposite with happens with bowling to batting. As there are batsmen who has not scored, there a lot more bowlers who have not taken a wicket.

Now in log transformation 0 s are excluded because ln(0) is undefined. This inflates the expected values compared to universal batting average. Exact opposite happens with bowling where ln(infinity) is undefined and removed from transformation. This makes bowling averages to be less than universal average, hence deflation.
 
R

RossTaylorsBox

Cricket Web: All-Time Legend
Migara said:
Exact opposite with happens with bowling to batting. As there are batsmen who has not scored, there a lot more bowlers who have not taken a wicket.

Now in log transformation 0 s are excluded because ln(0) is undefined. This inflates the expected values compared to universal batting average. Exact opposite happens with bowling where ln(infinity) is undefined and removed from transformation. This makes bowling averages to be less than universal average, hence deflation.
Click to expand...
I do not care about your undergrad textbook, I just want you to try to read the paper.
 
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