The Outsider Posted March 30, 2010 Posted March 30, 2010 Awesome work there, Boss! Just a couple of caveats I would want to add : 1. The analysis assumes that the opposition batted for the same number of innings as the batsman in question, so the factor of 10. 2. It also assumes that all batsmen from the players' team batted in the innings. 3. Openers or number 3 batsmen will be at a slight advantage in case of uncompleted innings. But, looking at the batsmen from the modern era only the results do seem to reflect a lot of reality with the top performers with more than 100 innings being : Sehwag Lara Jayawardene Younis Khan Sangakkara Ponting Tendulkar Pietersen Yousuf Dravid Hayden Smith Kallis I suspect a break up between home and away will further bring out some more interesting results with probably Jayawardene and Younis Khan suffering, which in this sort of analysis seems to be a fun thing to do given a batsman's runs in enemy territory are worth their weight in gold.
Dhondy Posted March 30, 2010 Posted March 30, 2010 Fair estimation' date=' Dhondy jee?[/quote'] Nope. If you truly want to make a scientific analysis, stick to facts and don't make assumptions. In science, if one feels that the results might be affected by factors beyond control, you say that there could be some form of bias, and you leave it to the reader to draw his assumptions. You don't adjust your results for that bias. That's not allowed. It might look clever, but it's not scientific. An example of the folly of making assumptions is demonstrated in this thread where Boss looks at Lara's proportion of runs with and without Ambrose+Walsh in the side. You'd expect the proportion to be higher with those 2 great bowlers as they would drive down the opposition's runs, wouldn't you? His proportion actually falls from 9.56 to 9.40 when they play with him. The whole concept of adjustment therefore comes crashing down. That kind of test is called looking for construct validity and tells you what might have happened if your hypothesis was correct. It failed the test. But even if it didn't fail, you would not be correct in changing your actual figures. The original tables, with and without minnows, were well thought out and very informative. The rest is just...well, nice to read, but pure rubbish.
The Outsider Posted March 30, 2010 Posted March 30, 2010 Nope. If you truly want to make a scientific analysis, stick to facts and don't make assumptions. The original analysis rests on the assumption that all batsmen had the same support act in the line up and had the same bowling attack to bowl the opposition out. Both assumptions are plain wrong, so to construct a model in order to mimic the effect of the batsmen having played in similar set ups is completely scientific.
The Outsider Posted March 30, 2010 Posted March 30, 2010 I can account for all of these and then bifurcate them by home/away to make it more accurate .... So Pls modify the formula and post it and I will crunch later tonight ... :--D It'll become too convoluted without really adding much, IMO. We'll have to account for each batsmen the number of wickets which fell from his team and from the opposition in each test match. And once we get into a match by match break up we are going to enter murky territory about how accurate is it to use India's batting average over a 20 year period in a particular match in 1992 for example etc. etc. But just an away and home breakup of post # 101 would be nice.
patriot Posted March 30, 2010 Author Posted March 30, 2010 Alright brothers. Here is the final deal. I verified each stat a couple of times and corrected my past error where in I din't exclude minnows from the batting and bowling avg of each side during the players career. The formula is ( excluding the 2 minnows ): (% run contribution to match ) *( batting avg of side when player involved )*( bowling avg of side when player involved ) The final standing for 1990 - Date is: Rank 1) Sehwag: 8.02 * 38.68 * 37.49 = 11629.90 2 )Tendulkar: 7.29 * 36.81 * 36.44 = 9778.488 3) Dravid: 7.20 * 36.52 * 36.56 = 9613.23 4) Pietersen: 7.44* 35.44 * 36.03 = 9500.15 5) Lara: 9.2 * 29.4 * 34.32 = 9282.87 6) Ponting: 7.47 * 42.34 * 29.35 = 9282.812 7 ) Sangakarra: 8.03 * 34.5 * 32.81 = 9089.518 8) Hayden: 7.35* 41.62 * 28.99 = 8868.24 9) Kallis: 7.53 * 36.07* 31.09 = 8444.264 10 ) Inzamam: 7.16 * 33.4 * 33.5 = 8011.32 11) Saeed Anwar: 7.66 * 32.26 * 30.43 = 7519.60 As percentage of the No.1 the ratings are: Rank 1) Sehwag - 100 2) Tendulkar - 84 3) Dravid - 82.65 4) Pietersen - 81.68 5) Lara - 79.819 6) Ponting - 79.818 7) Sangakarra - 78.15 8) Hayden - 76.25 9) Kallis - 72.6 10)Inzamam - 68.88 11)Anwar - 64.65
patriot Posted March 30, 2010 Author Posted March 30, 2010 Nope. If you truly want to make a scientific analysis, stick to facts and don't make assumptions. In science, if one feels that the results might be affected by factors beyond control, you say that there could be some form of bias, and you leave it to the reader to draw his assumptions. You don't adjust your results for that bias. That's not allowed. It might look clever, but it's not scientific. An example of the folly of making assumptions is demonstrated in this thread where Boss looks at Lara's proportion of runs with and without Ambrose+Walsh in the side. You'd expect the proportion to be higher with those 2 great bowlers as they would drive down the opposition's runs, wouldn't you? His proportion actually falls from 9.56 to 9.40 when they play with him. The whole concept of adjustment therefore comes crashing down. That kind of test is called looking for construct validity and tells you what might have happened if your hypothesis was correct. It failed the test. But even if it didn't fail, you would not be correct in changing your actual figures. The original tables, with and without minnows, were well thought out and very informative. The rest is just...well, nice to read, but pure rubbish. >So you do not feel one has to normalize the % run contribution to account for each player's side's batting and bowling avg , to make a fair comparison ? > How would the list of your top 10 of the last 2 decades , look like?
bunny Posted March 30, 2010 Posted March 30, 2010 This is just regarding the % calculations: i) I think the % should be \Avg_i{individual runs_i/match_runs_i} and not \sum_i(individual runs_i)/\sum_i(match_runs_i). The second easily favors bigger scores, and defeats the entire purpose of calculating the %s. ii) As some have mentioned above, for unfinished innings we need to at least adjust the % calculations by including the batting averages of the players to come. For not-outs, we need to add the batsman's average to his score as well as the overall score. The above ii) will surely bring Sehwag down :)
patriot Posted March 31, 2010 Author Posted March 31, 2010 Super work, BB. What it keeps reiterating is that, Sehwag is an absolute legend among legends. What it does not tell us is the rate at which Sehwag plunders the runs, making him a phenomenon.
patriot Posted March 31, 2010 Author Posted March 31, 2010 What is interesting to see is that Hayden is highly overrated. We tend to rate him highly because he has done very well against us. But Sehwag is definately a more complete opener than Haydos.
observer1 Posted March 31, 2010 Posted March 31, 2010 Great point Daktre ... but Andy flower misses out due to him having played for Zim. Come on S - just for once, do me a favour - if you can come up with a score for individual batsmen, calculate the simplest of the scores for Andy Flower.... He has an average of 51, and surely deserves a place in this table, and will probably slot in above the likes of Ashoka Gurusinha, Nasser Hussain and Bob Simpson!
akshayxyz Posted March 31, 2010 Posted March 31, 2010 you exclude minnows to dis-account for 'free-runs'.. what about Andy flower (and other minnow heroes), who had to play against every non-minnow!! with worst team -bowling/batting support.. No senior to guide in the team.. tougher situations, etc..
sandeep Posted March 31, 2010 Posted March 31, 2010 The original tables, with and without minnows, were well thought out and very informative. The rest is just...well, nice to read, but pure rubbish. or I like the conclusion drawn by the 1st set of numbers more than then 2nd set, so the 2nd set is pure rubbish:winky: Interesting discussion btw, enjoyed it.
observer1 Posted March 31, 2010 Posted March 31, 2010 sorry daktre heres your stat : Batsman Inns Runs(A) T-Tot(B) T-Bowl(C) T-Bat(D) Wt(E) %(100*A/B) A*100/(B+E) A Flower 93 4794 58864 38.14 25.45 5840.40 8.14 7.41 that is far too intellectual for me to comprehend! where do the numbers stand in comparison to the others?
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