A most interesting piece of stat: Calling Varun

[The Outsider]

A crude way would be to take some standard, like Tendulkar 35.44. So, on average India conceded 7 more runs per wicket than Australia during Tendulkar and Ponting's time. Ponting scored 11309 out of 151332 actual runs in 241 innings. Assuming the opposition batted same number of innings, if Ponting had Indian bowlers they would have conceded an extra 7 * 241 * 10 = 16870 runs. So he would have scored 11309 out of 168202(151332+16870) runs normalized to Tendulkar's bowling attack for a percentage of 6.7%

Given the batting averages of the team, similar method to above can be used to normalize for one's batting line up as well. That result would be more instructive.

[The Outsider]

patriot, your simple multiplication would be okay but not perfect because although the number of innings played by the batsmen is similar in most cases, but they are not exactly the same. I'll try to normalize using my way described above during the day when I get the time on statsguru for a while.

[patriot]

Further normalizing this by using batting avg of each batsman's team during their playing career will take away the unfair advantage that Lara has of playing in a team with weaker batting and be fair to Ponting and Hayden for representing a team with a stronger batting line up.

If we further normalize the below stat - by using each batsmans team's batting avg during their playing career - it will perfectly sort out any of the flaws and give us a near perfect picture. Is that correct Dhondy/Shwetabh ? Quote by patriot If we normalize by multiplying the player's respective sides bowling avg during their playing career to their contribution % of match total the rankings are as: Lara - 305.716 Sehwag - 283.106 Pietersen - 263.82 Tendulkar - 258.35 Dravid -252.86 Sangakarra - 241.22 Anwar - 228.72 Kallis- 226.57 Ponting- 212.44 Hayden - 206.82

[Guest BossBhai]

-- Removed on request of the user --

[Gunner_Mania]

The ugly union of SQL and cricket has semantics running for cover.

all the effects of IPL.. with no 'proper' kirkut to discuss SQL queries are seeing their few minutes posts of fame.

[teacup]

This analysis favors the flat-track bullies because of the sheer volume of runs they pile up on flat tracks. A 100 out of a team score of 200 all out has only 1/3rd the value of a 300 out of 600 for 5 declared. In other words, you have to play three 100/200 innings to match a 300/600 inning. No wonder then the biggest flat-track bully, Lara, tops the modern-day batsmen.

[Dhondy]

This analysis favors the flat-track bullies because of the sheer volume of runs they pile up on flat tracks. A 100 out of a team score of 200 all out has only 1/3rd the value of a 300 out of 600 for 5 declared. In other words' date=' you have to play three 100/200 innings to match a 300/600 inning. No wonder then the biggest flat-track bully, Lara, tops the modern-day batsmen.[/quote'] The Laureate returns!:hysterical: Patriot, adjusting would take away from the concept, IMO. As I have emphasised earlier in the thread, it's not necessary. Variables mostly cancel themselves out, and once you start "normalising" tables like these, they lose their import. Take them at face value or not at all.

[patriot]

Therefore the normalization would be as below: (% run contribution in match) * (your team's bowling avg during your playing time) * ( your teams batting avg during your playing time) Lara would be wrested of all the advantage that he was getting thus far. Can someone do the multiplication and rearrange descending wise, while I am back from lunch ? I think we will see a very very fair estimate. Lara - 305.716 * 29.94 = Sehwag - 283.106 * 39.45 = Pietersen - 263.82 * 35.82 = Tendulkar - 258.35 *37.4 = Dravid -252.86 * 37.56 = Sangakarra - 241.22 * 37.6 = Anwar - 228.72 * 31.45 = Kallis- 226.57 * 37.74 = Ponting- 212.44 *40.78 = Hayden - 206.82 * 39.77 =

[Sachinism]

Therefore the normalization would be as below: (% run contribution in match) * (your team's bowling avg during your playing time) * ( your teams batting avg during your playing time) Lara would be wrested of all the advantage that he was getting thus far. Can someone do the multiplication and rearrange descending wise, while I am back from lunch ? I think we will see a very very fair estimate. Lara - 305.716 * 29.94 = Sehwag - 283.106 * 39.45 = Pietersen - 263.82 * 35.82 = Tendulkar - 258.35 *37.4 = Dravid -252.86 * 37.56 = Sangakarra - 241.22 * 37.6 = Anwar - 228.72 * 31.45 = Kallis- 226.57 * 37.74 = Ponting- 212.44 *40.78 = Hayden - 206.82 * 39.77 =

Sehwag = 11168.53 Tendulkar = 9662.29 Dravid = 9497.42 Pietersen = 9450.03 Lara = 9153.14 Sangakarra = 9069.87 Ponting = 8663.30 Kallis = 8550.75 Hayden = 8225.23 Anwar = 7193.24 3 Indians at the top :aha:

[patriot]

^ Rightfully pushing Anwar at the very bottom of that list - This method IMO is about right, think. We can test it's veracity by using the same for batters for the decade 1970- 1990 ( the likes of Sunny, Greg C., IVA, Border, Miandad )

[The Outsider]

Here are the final numbers normalized to take into account the side's bowling and batting averages :

Sehwag	8.28
Lara	7.84
Sangakkara	7.34
Tendulkar	7.28
Pietersen	7.22
Dravid	7.18
Ponting	7.06
Kallis	6.85
Hayden	6.80
Anwar	6.24

Lara back to the pack after removing the spurious effects of a strong bowling and weak batting.

[patriot]

(% run contribution in match during career) * (your team's bowling avg during your playing time) * ( your teams batting avg during your playing time) > Sunny = 8.29 * 35.15 * 33.72 = 9825.78 > Greg C. = 7.97 * 30.10 * 32.95 = 7904.6 > Viv RIchards = 7.32 * 28.04 * 34.37 = 7054.53 > Miandad = 7.82 * 30.75 * 34.31 = 8250.35 Rearranged : 1) Sunny - 9825.78 2)Miandad - 8250.35 3) Greg C - 7904.6 4) Viv Richards - 7054.53 Fair call above ?

[Guest BossBhai]

-- Removed on request of the user --

[Guest BossBhai]

-- Removed on request of the user --

[patriot]

Boss, I think Shwetabh's list is 100 % accurate ,as I forgot to discount minnows for each player's team's bowling and batting avg in my calculation. So the top 10 are: Sehwag 8.28 Lara 7.84 Sangakkara 7.34 Tendulkar 7.28 Pietersen 7.22 Dravid 7.18 Ponting 7.06 Kallis 6.85 Hayden 6.80 Anwar 6.24 Apart from that, Shwetabh and I have done the same thing. I think it is a good way of estimation but can only be applied across the same era.

[patriot]

Fair estimation, Dhondy jee?

[Guest BossBhai]

-- Removed on request of the user --

[The Outsider]

Proff , whats the formula you used here ?

Weighted Percentage = Runs scored*100/(Unweighted runs + Weight) Unweighted runs are the total runs you had calculated earlier, Runs scored is the runs for a batsman from your earlier calculation. Weight = 10*Number of innings*((35.44 - Bowling Average) + (35.03 - Batting Average)) I normalized with respect to Tendulkar's numbers - of course that is arbitrary - you can choose any batsman. 35.44 and 35.03 are India's bowling and batting averages during the time Tendulkar played. Above can be refined by : 1. Excluding minnows in overall team average calculations. 2. Instead of doing it for the duration of a player's career, you can choose to do it only for the matches he featured in.

[observer1]

in most studies involving animals and some variables, you can always find a statistical test that will prove your hunch. and you simply then publish your paper. much as i like reading the scientific dissection behind these analyses, i suspect we are getting close to that level now. and, what happened to andy flower?

[Guest BossBhai]

-- Removed on request of the user --