What criteria would you use in rating the best?

[Uppercut]

Top 30 century averages: Qualification: 5 centuries or more

1 KC Sangakkara 121.64
2 DG Bradman 108.39
3 FMM Worrell 105.00
4 SJ McCabe 101.50 (no wonder he jumps right up the latest ratings)
5 A Flower 100.00
6 WR Hammond 99.00
7 SP Fleming 97.86
8 V Sehwag 92.14
9 Javed Miandad 85.60
10 VT Trumper 77.80
11 BC Lara 77.78
12 GS Sobers 77.53
13 SR Tendulkar 71.67
14 L Hutton 71.07
15 GA Headley 69.14
16 ST Jayasuriya 68.29
17 GC Smith 68.21
18 SR Waugh 67.18
19 R Dravid 66.15
20 DPMD Jayawardene 64.10
21 RG Pollock 63.86
22 IVA Richards 59.79
23 Mohammad Yousuf 56.47
24 JH Kallis 56.11
25 GS Chappell 55.74
26 RT Ponting 55.39
27 WH Ponsford 55.29
28 Younis Khan 55.15
29 AR Border 55.00
30 S Chanderpaul 53.11
Frustrates me actually to see Fleming so high up. If he had got past his mental block with centuries, he could have averaged 50.

Very interesting. Which players are at the bottom, when a minimum of 10 or so centuries is set?

I do think the merits of this system for comparing batsmen are questionable, one who scores a century in both innings is of at the very least equal merit to one who scores a double hundred and a duck. Indeed, for openers, it means seeing off the new ball twice. Nevertheless, very interesting ranking- and a lot of modern-era players there.

 

[Days of Grace]

I do think the merits of this system for comparing batsmen are questionable, one who scores a century in both innings is of at the very least equal merit to one who scores a double hundred and a duck. .

The average only counts once you score a century. So, if you score 214 and then a duck, you still have a century average of 114.00

 

[Uppercut]

The average only counts once you score a century. So, if you score 214 and then a duck, you still have a century average of 114.00

But if you score 100 in both innings of a match you have a century average of... 0? Am i understanding this right?

 

[Days of Grace]

Yes, that's right.

When you think about it, openers have a better chance to score big hundreds as they have the whole innings to bat if they don't get out.

 

[Uppercut]

Yes, that's right.

When you think about it, openers have a better chance to score big hundreds as they have the whole innings to bat if they don't get out.

Yeah but you're counting runs scored after passing 100 as double, because they count for a player's overall average and also his post-century average. In a test match, all runs count the same, and scoring 100 twice is of no less value than scoring 200 then 0. 'Tis what i was trying to get at

 

[Days of Grace]

Yeah but you're counting runs scored after passing 100 as double, because they count for a player's overall average and also his post-century average. In a test match, all runs count the same, and scoring 100 twice is of no less value than scoring 200 then 0. 'Tis what i was trying to get at

The post century average as a weighting is only worth 20% of the overall average in a batsmen's rating. Think of it as a supplement.

 

[Days of Grace]

I will now try to explain the formula.

Formula for Test Batsmen:

Basically there are 10 criteria for ranking test batsmen. Each has a certain percentage of the weighting, i.e. how important is each criteria in assessing a batsmen. The percentage of each criteria is worked out by getting the average for each criteria for the top 30 ranked batsmen.

1. Average - of course, the most important. 100% worth. x4.5
2. Runs scored - longivity. worth 15%. Divide by 200
3. Peak average - best average over a 15 match period for batsmen before 1914, 25 matches for batsmen between 1919 and 1969 and 30 matches for batsmen after 1970. 35% of rating. x1.275
4. Away Ave - self-explanatory. worth 30% of rating. x1.45
5. 2nd team innings average - when conditions get tougher. worth 25% of rating. x1.2
6. Strike rate for major innings (i.e. scores of 80+) - how dominant was a batsmen when he was set? worth 20% of rating. divide by 1.1
7. Century average - average runs scored after scoring a century. For powers of concentration and ruthlessness. worth 20% of rating. divide by 1.25
8. Consistency - percentage of 50+ scores per innings. worth 35% of rating. x2.4
9. Career Centuries - longevity. worth 20% of rating. x2.25
10. Centuries per match. percentage of centuries scored per match. worth 25% of rating. x2.4

Finally, penalties are given for lack of matches played, starting from less then 30 matches. These penalties are naturally lighter for batsmen before 1914.

And batsmen playing before 1900 get 35% boost to their rating. Batsmen playing between 1900 and 1914 get a 20% boost to their rating. Batsmen having their careers interrupted by WWI or WWII get a 7.5% boost to their rating.


Example: Ricky Ponting vs. Viv Richards

1. Average: Ponting 58.37x4.5 = 262.67. Richards 50.23x4.5 = 226.04
2. Runs scored: Ponting 10099/200 = 50.50. Richards 8540/200 = 42.7
3. Peak average: Richards 75.19x1.275 = 95.87. Ponting 74.08x1.275 = 94.45
4. Away average: Ponting 51.54 x1.45 = 74.73. Richards 50.50 = 73.23
5. 2nd innings average: Richards 48.92 x1.2 = 58.70. Ponting 48.65 x1.2 = 58.38
6. Strike rate for 80+ scores: Richards 70.22/1.1 = 63.84. Ponting 62.43/1.1 = 56.75
7. Century average: Richards 59.79/1.25 = 47.83. Ponting 55.39/1.25 = 44.31
8. Consistency: Richards 37.9 x2.4 =90.96. Ponting 37.7 x2.4 = 90.45
9. Career Centuries: Ponting 35 x2.25 = 78.8. Richards 24 x2.25 = 54.0
10. Centuries per match: Ponting 29% x2.4 = 70.59. Richards 20% x2.4 = 47.60.

There you have it.

 

[Days of Grace]

Top 50 Test Bowlers

1 M Muralitharan 1247
2 SF Barnes 1001
3 Sir RJ Hadlee 998
4 GD McGrath 957
5 SK Warne 947
6 MD Marshall 938
7 CEL Ambrose 917
8 Imran Khan 897
9 WJ O'Reilly 886
10 AA Donald 867
11 AK Davidson 858
12 DK Lillee 842
13 CV Grimmett 839
14 J Garner 836
15 Waqar Younis 836
16 Wasim Akram 827
17 FS Trueman 821
18 CA Walsh 808
19 GA Lohmann 804
20 SM Pollock 794
21 JC Laker 793
22 A Kumble 784
23 JH Wardle 773
24 NAT Adcock 752
25 AV Bedser 740
26 MA Holding 730
27 DW Steyn 725
28 C Blythe 722
29 RR Lindwall 716
30 IT Botham 713
31 FH Tyson 708
32 CTB Turner 707
33 HJ Tayfield 702
34 DL Underwood 698
35 Fazal Mahmood 696
36 RGD Willis 681
37 WA Johnston 672
38 W Barnes 667
39 R Benaud 664
40 KR Miller 664
41 R Peel 664
42 IR Bishop 664
43 AME Roberts 663
44 Shoaib Akhtar 658
45 JB Statham 657
46 JA Snow 655
47 FR Spofforth 651
48 CEH Croft 640
49 W Bates 638
50 H Verity 631

 

[Days of Grace]

Formula for Test Bowlers:

Basically there are 9 criteria for ranking test bowlers. Each has a certain percentage of the weighting, i.e. how important is each criteria in assessing a bowler. The percentage of each criteria is worked out by getting the average for each criteria for the top 30 ranked bowlers.

1. Average - of course, the most important. 100% worth. complex microsoft formula that gives more points the lower your average is =2109.1*(EXP(average*-0.0953))
2. Wickets taken - longivity. worth 35% of rating. x0.3
3. Peak average - best average over a 15 match period for bowlers before 1914, 25 matches for bowlers between 1919 and 1969 and 30 matches for bowlers after 1970. 35% of rating. average formula x0.27
4. Away Ave - self-explanatory. worth 30% of rating. average formula x0.34
5. Wickets per innings - worth 65% of rating. x67.5
6. Consistency - percentage of 3wkts+ per innings. worth 25% of rating. x1.45
7. % of top order (batsmen 1-7) wickets - worth 20% of rating. divide by 1.35
8. Career 5 wickets in an innings - worth 12% of rating. x1.5
9. Career 10 wickets in a match - worth 8% of rating. x5

Finally, penalties are given for lack of matches played, starting from less then 30 matches. These penalties are naturally lighter for bowlers before 1914.

And bowlers playing before 1900 get 35% penalty to their rating. Bowlers playing between 1900 and 1914 get a 20% penalty to their rating. Bowlers having their careers interrupted by WWI or WWII get a 7.5% boost to their rating.


Example: Waqar Younis vs. Wasim Akram

1. Average: Waqar 23.56 = 223.35. Wasim 23.62 = 222.08
2. Wickets taken: Wasim 414 x0.3 = 124.2. Waqar 373 x0.3 = 111.9
3. Peak average: Waqar 17.98 = 102.64. Wasim 19.85 = 85.88
4. Away average: Wasim 24.44 = 69.83. Wasim 26.06 = 59.84
5. Wickets per innings: Waqar 2.42 x67.5 = 163.49. Wasim 2.29 x67.5 = 154.39
6. Percentage of 3+ wkts per innings: Waqar 44.2% x1.5 = 66.23. Wasim 41.4% x1.5 = 62.15
7. % of top order wickets: Waqar 70.78/1.35 = 52.43. Wasim 64.98/1.35 = 48.13
8. Career 5 wickets in an innings: Wasim 25 x1.5 = 37.5. Wasim 22 x1.5 = 33
9. Career 10 wickets in a match: Wasim/Waqar 5 x5 = 25

Total: Waqar Younis 836 Wasim Akram 827

So, the statistics show that while Wasim may have looked the better bowler (his action is my favourite) and adapted to overseas conditions better, overall Waqar was the more proficient wicket taker.

 

[Uppercut]

I'm interested, why do you use two calculations, typically a multiplication then a division, for every measure? Rather than, say, multiplying by 4.5 before finding the score as a percentage of the overall ranking, couldn't you just save time by finding one constant for each statistical measure and multiplying by it every time, before adding the resulting figures up to achieve the score?

Equally, why did you use a complex excel formula for bowling averages when you could have simply used its inverse multiplied by a constant? Is the listed formula a more accurate indication of the measure's worth, and if so, why?

Just enquiring

 

[Days of Grace]

I'm interested, why do you use two calculations, typically a multiplication then a division, for every measure? Rather than, say, multiplying by 4.5 before finding the score as a percentage of the overall ranking, couldn't you just save time by finding one constant for each statistical measure and multiplying by it every time, before adding the resulting figures up to achieve the score?

Equally, why did you use a complex excel formula for bowling averages when you could have simply used its inverse multiplied by a constant? Is the listed formula a more accurate indication of the measure's worth, and if so, why?

Just enquiring

The first part, not sure what you mean, really. Anyway, it works the way it is, so I don't think I'll change it.

The second part, hmmm, I followed what Migara gave me. Not sure how to do the thing (i.e. inverse) on excel that you are suggesting.

 

[Uppercut]

The first part, not sure what you mean, really. Anyway, it works the way it is, so I don't think I'll change it.

The second part, hmmm, I followed what Migara gave me. Not sure how to do the thing (i.e. inverse) on excel that you are suggesting.

All i meant for the first part was that you first multiply by a constant for each measure (e.g. 4.5) then by a percentage (e.g. 100%). All you really need to do there is multiply by 450%, it gives the same result but means you have to do half as many calculations - although if the formulae are already set up there is indeed no point in changing it.

As for the averages suggestion, Migara's knows more on statistics than I, so his suggestion probably is a better method. Using the inverse simply means that instead of using someone's bowling average to be, say, 30, you take it to be 1/30, and work from there- the effect is the same; as bowling average decreases the overall ranking value will increase.

 

[Goughy]

I will now try to explain the formula.

Example: Ricky Ponting vs. Viv Richards

1. Average: Ponting 58.37x4.5 = 262.67. Richards 50.23x4.5 = 226.04
2. Runs scored: Ponting 10099/200 = 50.50. Richards 8540/200 = 42.7
3. Peak average: Richards 75.19x1.275 = 95.87. Ponting 74.08x1.275 = 94.45
4. Away average: Ponting 51.54 x1.45 = 74.73. Richards 50.50 = 73.23
5. 2nd innings average: Richards 48.92 x1.2 = 58.70. Ponting 48.65 x1.2 = 58.38
6. Strike rate for 80+ scores: Richards 70.22/1.1 = 63.84. Ponting 62.43/1.1 = 56.75
7. Century average: Richards 59.79/1.25 = 47.83. Ponting 55.39/1.25 = 44.31
8. Consistency: Richards 37.9 x2.4 =90.96. Ponting 37.7 x2.4 = 90.45
9. Career Centuries: Ponting 35 x2.25 = 78.8. Richards 24 x2.25 = 54.0
10. Centuries per match: Ponting 29% x2.4 = 70.59. Richards 20% x2.4 = 47.60.

There you have it.

Ok, my thoughts. Tell me if I misunderstand.

2nd innings average doesnt need to be there IMO, especially for batsmen. Firstly it is already counted heavily in overall average. A good 2nd innings average will be reflected in the overall average. Secondly, in batting a good first innings total is what a game is based on. Hence, win the toss and bat. Being able to score big first time around is the crux of the game.

My other issue, is that draws on flat tracks are overly represented. Who cares if a player socres runs by the boatload when bowlers toil and a result is never a possibility. it is pressure free gimmi runs that are unimportant.

I have a few more ideas but they are the 2 main ones.

I like the process, and I dont mind the subjective weightings at all. Its a worthy and impressive undertaking.

 

[Uppercut]

Ok, my thoughts. Tell me if I misunderstand.

2nd innings average doesnt need to be there IMO, especially for batsmen. Firstly it is already counted heavily in overall average. A good 2nd innings average will be reflected in the overall average. Secondly, in batting a good first innings total is what a game is based on. Hence, win the toss and bat. Being able to score big first time around is the crux of the game.

My other issue, is that draws on flat tracks are overly represented. Who cares if a player socres runs by the boatload when bowlers toil and a result is never a possibility. it is pressure free gimmi runs that are unimportant.

I have a few more ideas but they are the 2 main ones.

I like the process, and I dont mind the subjective weightings at all. Its a worthy and impressive undertaking.

Rather than using 2nd innings average, perhaps try using 4th innings average? Still not perfect, but i understand you want some form of statistical weighting towards runs scored under pressure, and that would be a better method than 2nd innings average.

 

[Debris]

The value of a player depends so much on the situation that I am going to suggest that there is no good way to rate players.

 

[Days of Grace]

Rather than using 2nd innings average, perhaps try using 4th innings average? Still not perfect, but i understand you want some form of statistical weighting towards runs scored under pressure, and that would be a better method than 2nd innings average.

Or, rather, the last innings of a match, because sometimes, following on in the 3rd innings of a match, a batsmen is fighting to save the draw.

But, I don't think statsguru has a function for 'last innings'

 

[Days of Grace]

Ok, my thoughts. Tell me if I misunderstand.


My other issue, is that draws on flat tracks are overly represented. Who cares if a player socres runs by the boatload when bowlers toil and a result is never a possibility. it is pressure free gimmi runs that are unimportant.

So, you are suggesting an average for matches that have results?

I suspect a few subcontinent batsmen would tumble down the ratings

 

[Goughy]

So, you are suggesting an average for matches that have results?

I suspect a few subcontinent batsmen would tumble down the ratings

so you rig the process to provide the results you want? Kind of makes the rating worthless.

I dont care if Indian, English or Zimbabweans fall. I think its easier and far more rewarding to compare apples to apples not easy runs on flat tracks in meaningless games compared to result games on balanced tracks.

Your system rewards players that pad their stats in easy conditions when there is nothing to play for. I am saying that that is a bad system that is prejudiced against those that make tough and valuable runs.

 

[Days of Grace]

so you rig the process to provide the results you want? Kind of makes the rating worthless.

I dont care if Indian, English or Zimbabweans fall. I think its easier and far more rewarding to compare apples to apples not easy runs on flat tracks in meaningless games compared to result games on balanced tracks.

Your system rewards players that pad their stats in easy conditions when there is nothing to play for. I am saying that that is a bad system that is prejudiced against those that make tough and valuable runs.

No, I don't rig the process. The laugh symbol meant that I know and you know that subcontient batsmen thrive on flat tracks.

When I have time, I will incorporate averages in result matches, rather then 2nd inns.

 

[Migara]

All i meant for the first part was that you first multiply by a constant for each measure (e.g. 4.5) then by a percentage (e.g. 100%). All you really need to do there is multiply by 450%, it gives the same result but means you have to do half as many calculations - although if the formulae are already set up there is indeed no point in changing it.

As for the averages suggestion, Migara's knows more on statistics than I, so his suggestion probably is a better method. Using the inverse simply means that instead of using someone's bowling average to be, say, 30, you take it to be 1/30, and work from there- the effect is the same; as bowling average decreases the overall ranking value will increase.

What Days of Grace has done is referred to as exxponential formula. With each unit of x gets away from zero or a set number, y increases more and more. 1, 2, 4, 8, 16, 32, 64 is an example. Like wise 1, 3, 6, 10, 15, 21.... also can be set in to a function that is exponetial. That's easy maths I would think. We all learnt exponential series in our maths classes