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Post #16
So, here it is. As I said I call the old parameter "absolute predominance" (or alpha-predominance) and the new one "balanced predominance" (or beta-predominance).
The only difference is that instead of considering the number of games played in the last month / session, here I have considered the square root of that value. This is equivalent to a geometric mean where the "rating" parameter weighs twice compared to the "last month games" parameter. Well, these are the results (except for possible errors).
-- Top 36 beta-predominant players -- June 19th, 2020
...
The only difference is that instead of considering the number of games played in the last month / session, here I have considered the square root of that value. This is equivalent to a geometric mean where the "rating" parameter weighs twice compared to the "last month games" parameter. Well, these are the results (except for possible errors).
-- Top 36 beta-predominant players -- June 19th, 2020
| Position | --- Rank & username --- | Rating --- | Total games - | Last month games (sqrt) --- | α-Predominance --- | β-Predominance |
| ... | ||||||
| 34 | 2nd Lieutenant @PT | 2716 | 830 | 448 sqrt = (21.166) | 1216.768 | 57.487 |
| 5 | Lieutenant Colonel @Joeyseven | 4995 | 1321 | 110 sqrt = (10.488) | 549.450 | 52.388 |
| 90 | Serg Major @allthingsmustpass | 2043 | 29135 | 519 sqrt = (22.782) | 1060.317 | 46.544 |
| 33 | 2nd Lieutenant @Texx | 2728 | 16481 | 278 sqrt = (16.673) | 758.384 | 45.484 |
| 7 | Major General @Deepdaleduck | 4719 | 4539 | 79 = (8,888) | 372.801 | 41.942 |
| 31 | Private @1949midden | 2784 | 488 | 219 sqrt = (14.799) | 609.696 | 41.200 |
| ... | ||||||
| 98 | Sergeant Major @HalSucks | 2009 | 965 | 417 sqrt = (20.421) | 837.753 | 41.026 |
| 78 | Warrant Officer @ElectricBlue | 2144 | 25365 | 354 sqrt = (18.815) | 758.976 | 40.339 |
| 10 | Lieutenant Colonel @simomosi | 3987 | 4538 | 102 sqrt = (10.100) | 406.674 | 40.268 |
| 9 | Colonel @huskers01 | 4294 | 3400 | 81 sqrt = (9.000) | 347.814 | 38.646 |
| 151 | Command Serg @2BeeStings | 1722 | 634 | 501 sqrt = (22.383) | 862.722 | 38.544 |
| 8 | Brigadier Gen @ProblemChild96 | 4452 | 2605 | 67 sqrt = (8.185) | 298.284 | 36.440 |
| ... | ||||||
| 23 | Captain @Riskk | 3243 | 4870 | 116 sqrt = (10,770) | 376.188 | 34.927 |
| 11 | Lieutenant Colonel @maafi | 3880 | 4883 | 69 sqrt = (8.307) | 267.720 | 32.231 |
| 3 | Lieut General @hooboy11 | 5326 | 16732 | 36 sqrt = (6.000) | 191.736 | 31.956 |
| 47 | Chief War Officer @Hoodlum | 2407 | 35672 | 172 sqrt = (13.115) | 414.004 | 31.568 |
| 84 | Sergeant Major @superDENI | 2080 | 5572 | 221 sqrt = (14.866) | 459.680 | 30.921 |
| 2 | General @slackbatter | 5765 | 2540 | 27 sqrt = (5.196) | 155.655 | 29.955 |
| ... | ||||||
| 51 | Lance Corporal @McNulthy | 2366 | 285 | 159 sqrt = (12.610) | 376.194 | 29.835 |
| 64 | Warrant Officer @vodkamikebid | 2248 | 8155 | 170 sqrt = (13.038) | 382.160 | 29.309 |
| 42 | Private @abuzees | 2564 | 294 | 118 sqrt = (10.863) | 302.552 | 27.853 |
| 69 | Private @MrTrotsky | 2203 | 4553 | 148 sqrt = (12.166) | 326.044 | 26.802 |
| 28 | 2nd Lieutenant @roy12345 | 3036 | 1302 | 75 sqrt = (8.660) | 227.700 | 26.292 |
| 113 | Private @Andies | 1934 | 7404 | 184 sqrt = (13.565) | 355.856 | 26.235 |
| ... | ||||||
| 18 | Lieutenant @The_Bishop | 3437 | 1719 | 57 sqrt = (7.550) | 195.909 | 25.949 |
| 62 | Warrant Officer @wailuen84 | 2256 | 910 | 125 sqrt = (11.180) | 282.000 | 25.222 |
| 81 | Sergeant Major @bluewabbit | 2109 | 385 | 138 sqrt = (11.747) | 291.042 | 24.775 |
| 137 | Private @letitbe | 1802 | 1591 | 189 sqrt = (13.748) | 340.578 | 24.773 |
| 19 | Captain @KOE_KittyKat | 3434 | 5733 | 52 sqrt = (7.211) | 178.568 | 24.763 |
| 65 | Warrant Officer @DrJardi | 2241 | 1239 | 122 sqrt = (11.045) | 273.402 | 24.752 |
| ... | ||||||
| 239 | Corporal @options | 1350 | 822 | 333 sqrt = (18.248) | 449.550 | 24.635 |
| 108 | Sergeant Major @TomC | 1947 | 4358 | 159 sqrt = (12.610) | 309.573 | 24.552 |
| 15 | Major @Henris_1 | 3657 | 10612 | 45 sqrt = (6.708) | 164.565 | 24.531 |
| 24 | Captain @DurandalBlue | 3241 | 2671 | 57 sqrt = (7.550) | 184.737 | 24.470 |
| 40 | Chief War Officer @blackrabbit | 2594 | 742 | 88 sqrt = (9.381) | 228.272 | 24.334 |
| 128 | Sergeant Major @BigBrain94 | 1860 | 2274 | 171 sqrt = (13.077) | 318.060 | 24.323 |
beta-Predominance, 37th to 100th (click to show)
«God doesn't play dice with the World» ~ Albert Einstein
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Post #17
Clearly this ranking can change quite a lot from one month to the next depending on the number of games played. It can be considered a sort of "last month's performance". However, the data reported here are no longer updated since they refer to June 19th, but this was just an example.
What should this parameter represent? First of all it is a recognition towards users who play many games, they are those who make the site work and make it popular. If in addition to playing many games you are also good then easily you will be on this list. For a talented player, not much effort is required to appear in the list, just play 30 or 40 games a month. On the contrary, a player with a high rating who does not want to play much in order not to risk ruining his rating, will have difficulty entering this ranking. In short, those who dare to face the challenge every day are the most rewarded!
What should this parameter represent? First of all it is a recognition towards users who play many games, they are those who make the site work and make it popular. If in addition to playing many games you are also good then easily you will be on this list. For a talented player, not much effort is required to appear in the list, just play 30 or 40 games a month. On the contrary, a player with a high rating who does not want to play much in order not to risk ruining his rating, will have difficulty entering this ranking. In short, those who dare to face the challenge every day are the most rewarded!
«God doesn't play dice with the World» ~ Albert Einstein
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Post #18
Responded instantly on the message I got, then waited some before replying here. I'm still very intrigued by the list; I believe it shows exactly that what it's supposed to show; dominance, which could indeed be captured as a formula based on two variables; skill/rating and visibility/games played.
The higher your rating is and in the more games you've played (& thus got noticed by more people), the more you dominate.
I like that there's some more emphasis on rating rather than #of games and the new pre-fixes; alpha/absolute & beta/balanced - very clever.
At this point though, if I wanted to "dominate" this list, I could likely create a bunch of LT 2p games with people >X rating. It would keep my rating rather stable/safe, while adding extremely to my "visibility"-parameter. So as dough_boy pointed out, it'd be good if 2p games could be filtered out (I realise that's currently not possible in an easy way (you'd have to go check everyone's stats manually and deduct # of 2p games played between the updates)).
The assumed favouritism for live games is fine by me. I believe live games have a greater impact on visibility anyway.
PS: 36 is coooool
The higher your rating is and in the more games you've played (& thus got noticed by more people), the more you dominate.
I like that there's some more emphasis on rating rather than #of games and the new pre-fixes; alpha/absolute & beta/balanced - very clever.
At this point though, if I wanted to "dominate" this list, I could likely create a bunch of LT 2p games with people >X rating. It would keep my rating rather stable/safe, while adding extremely to my "visibility"-parameter. So as dough_boy pointed out, it'd be good if 2p games could be filtered out (I realise that's currently not possible in an easy way (you'd have to go check everyone's stats manually and deduct # of 2p games played between the updates)).
The assumed favouritism for live games is fine by me. I believe live games have a greater impact on visibility anyway.
PS: 36 is coooool
“Gravitation cannot be held responsible for people falling in love. How on earth can you explain in terms of chemistry and physics so important a biological phenomenon as first love? Put your hand on a stove for a minute and it seems like an hour. Sit with that special girl for an hour and it seems like a minute. That's relativity.”
― Albert Einstein
― Albert Einstein
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Post #19
I agree with Alex - if the list is designed to measure a combination of a player's ability and exposure/activity, then it works well.
I do have a couple of points of opinion on how the list could more accurately measure that combination of variables:
1. The way the list is measured inherently favours exposure over ability. The vast majority of players (97.4%) have a rating between 4000 and 500. So, the most skilled players have a predominance 8x higher than the least skilled players (ceteris paribus). And for 95% (within 2s.d. of mean) of players, the ratio quickly falls to only 6.38x.
By taking figures from the same percentiles we can see that being active is rewarded much more than being skilful. 97.4% of players played between 221 and 5 games. So, the most active players have a predominance 44.2x higher than the least active players (ceteris paribus). For 95% of players, the ratio is still highly overweighted at 34.2x.
Thus, being active has a far more significant impact on your predominance than being skilful. I think the intention was to have both variables influence the score equally, as implied by the formula predominance = rating x games played.
So-called beta-predominance attempted to rectify this by square-rooting the last month games variable:
97.4% of players played between 221 and 5 games, square rooted to 14.87 and 2.24, respectively. So, the most active players have a predominance 6.6x higher than the least active players (ceteris paribus). For 95% of players, the ratio is 5.8x.
So by taking a square root of the last month games, the difference between the relative weightings of the two variables has been reduced:
alpha predominance - 6.38:34.2
beta predominance - 6.38:5.8
So, even though choosing to use the square root was actually quite an arbitrary decision, it quite luckily turned out to be quite effective for equalising the weightings of the two variables
2. However, the two variables are still unequally weighted, now rating is actually over-represented in the beta predominance variable (6.38:5.8) by 10%. Also, since the time between D12 lists varies from month to month, so too will the disparity between rating and new games played. When the time between lists is longer, Playing more games will become more influencial on beta-predominance than rating, and vice versa. Thus, the measuring system is slightly inconsistent between lists.
Consider a ranking system where all players who qualify for the list are ranked in order of rating, and in order of last month games, then the two rankings are multiplied. If such a ranking system was used instead of absolute values, it would present two distinct advantages. Firstly, the weighting of the two variables (skill and exposure/activity) would always be weighted exactly equally, at 1:1, which is what we want if indeed we believe in the formula predominance = rating x last month games. Secondly, longer months would not distort the importance of the two variables.
3. I believe that, when talking about dominance, games last month is not as telling a variable as no. of players played with last month. If it were possible to collate the data where the number of players in each game was taken into account, then this measure would be more indicative of exposure. Clearly, someone who has played 10 9-player games has had more exposure than someone sho has played 10 2-player games. I realise however that collecting such data would be almost impossible.
Oof, I might need to edit this to make it more readable. What do you think of these points? Agree/disagree?
I do have a couple of points of opinion on how the list could more accurately measure that combination of variables:
1. The way the list is measured inherently favours exposure over ability. The vast majority of players (97.4%) have a rating between 4000 and 500. So, the most skilled players have a predominance 8x higher than the least skilled players (ceteris paribus). And for 95% (within 2s.d. of mean) of players, the ratio quickly falls to only 6.38x.
By taking figures from the same percentiles we can see that being active is rewarded much more than being skilful. 97.4% of players played between 221 and 5 games. So, the most active players have a predominance 44.2x higher than the least active players (ceteris paribus). For 95% of players, the ratio is still highly overweighted at 34.2x.
Thus, being active has a far more significant impact on your predominance than being skilful. I think the intention was to have both variables influence the score equally, as implied by the formula predominance = rating x games played.
So-called beta-predominance attempted to rectify this by square-rooting the last month games variable:
97.4% of players played between 221 and 5 games, square rooted to 14.87 and 2.24, respectively. So, the most active players have a predominance 6.6x higher than the least active players (ceteris paribus). For 95% of players, the ratio is 5.8x.
So by taking a square root of the last month games, the difference between the relative weightings of the two variables has been reduced:
alpha predominance - 6.38:34.2
beta predominance - 6.38:5.8
So, even though choosing to use the square root was actually quite an arbitrary decision, it quite luckily turned out to be quite effective for equalising the weightings of the two variables
2. However, the two variables are still unequally weighted, now rating is actually over-represented in the beta predominance variable (6.38:5.8) by 10%. Also, since the time between D12 lists varies from month to month, so too will the disparity between rating and new games played. When the time between lists is longer, Playing more games will become more influencial on beta-predominance than rating, and vice versa. Thus, the measuring system is slightly inconsistent between lists.
Consider a ranking system where all players who qualify for the list are ranked in order of rating, and in order of last month games, then the two rankings are multiplied. If such a ranking system was used instead of absolute values, it would present two distinct advantages. Firstly, the weighting of the two variables (skill and exposure/activity) would always be weighted exactly equally, at 1:1, which is what we want if indeed we believe in the formula predominance = rating x last month games. Secondly, longer months would not distort the importance of the two variables.
3. I believe that, when talking about dominance, games last month is not as telling a variable as no. of players played with last month. If it were possible to collate the data where the number of players in each game was taken into account, then this measure would be more indicative of exposure. Clearly, someone who has played 10 9-player games has had more exposure than someone sho has played 10 2-player games. I realise however that collecting such data would be almost impossible.
Oof, I might need to edit this to make it more readable. What do you think of these points? Agree/disagree?
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Post #20
@AlexCheckMate, I am glad for your interest and appreciation!
@Virtuosity98 same, adding this: when things are simple let's make them more complex!
kidding
@All
Head-to-head lovers are certainly advantaged in this list, while capped cards players are disadvantaged. In fact, Dima had something to complain about, he expressed it his own way but basically he is right. Nothing I can do though. As I said I would have liked better to use the turns taken instead of the games played, but I do not have a record of that data.
In my opinion the perfect parameter for measuring a player's activity fairly would be the sum of all alive opponents for each turn he took in the last session. However, it doesn't seem any feasible, so I play with the data that I have.
Plus, the rating too is not an effective measure of a player's skills because it has too strong fluctuations. For example, on the list of May 16th I had 2800 points, in that of June 19th I had 3400 .. Wow, have I improved so much in a month?! No, I haven't. Using a metaphor I can say that in the first case Maafi took a picture while I was sitting, in the second case he took a picture while I was jumping, but in reality I am always the same "tall".
It wouldn't be very useful to make one parameter perfectly representative of reality if we do not do the same with the other. We can say that both are approximations, but they are easily available data. Overall, it seems to me that the "beta-predominance" comes close to representing what I wanted, so I'm personally satisfied.
Anyway, I will draw up the list also in the coming months, so maybe we will have a broader view.
@Virtuosity98 same, adding this: when things are simple let's make them more complex!
kiddingSome answers in short (click to show)
@All
Head-to-head lovers are certainly advantaged in this list, while capped cards players are disadvantaged. In fact, Dima had something to complain about, he expressed it his own way but basically he is right. Nothing I can do though. As I said I would have liked better to use the turns taken instead of the games played, but I do not have a record of that data.
In my opinion the perfect parameter for measuring a player's activity fairly would be the sum of all alive opponents for each turn he took in the last session. However, it doesn't seem any feasible, so I play with the data that I have.
Plus, the rating too is not an effective measure of a player's skills because it has too strong fluctuations. For example, on the list of May 16th I had 2800 points, in that of June 19th I had 3400 .. Wow, have I improved so much in a month?! No, I haven't. Using a metaphor I can say that in the first case Maafi took a picture while I was sitting, in the second case he took a picture while I was jumping, but in reality I am always the same "tall".
It wouldn't be very useful to make one parameter perfectly representative of reality if we do not do the same with the other. We can say that both are approximations, but they are easily available data. Overall, it seems to me that the "beta-predominance" comes close to representing what I wanted, so I'm personally satisfied.
Anyway, I will draw up the list also in the coming months, so maybe we will have a broader view.
«God doesn't play dice with the World» ~ Albert Einstein
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Post #21
-- Top 36 beta-predominant players -- July 24th, 2020
...
| Placement | . . . --- Rank & username --- . . . | Rating --- | Total games - | Last session games (sqrt) --- | β-Predominance | -count- |
| ... | ||||||
| 51 | Warrant Officer @2BeeStings | 2318 | 1136 | 502 sqrt = (22.405356) | 51,936 | -1- |
| 4 | Lieutenant General @Joeyseven | 5080 | 1426 | 95 sqrt = (9.746794) | 49,514 | -2- |
| 43 | Chief Warrant Officer @Hoodlum | 2467 | 36072 | 400 sqrt = (20.000000) | 49,340 | -3- |
| 69 | Unranked @clydesdale444 | 2101 | 31097 | 448 sqrt = (21.166010) | 44,470 | -4- |
| 2 | General @slackbatter | 6078 | 2590 | 50 sqrt = (7.071067) | 42,978 | -5- |
| 11 | Dominator @ProblemChild96 | 3917 | 2720 | 115 sqrt = (10.723805) | 42,005 | -6- |
| ... | ||||||
| 94 | Sergeant Major @abutia | 1970 | 3475 | 407 sqrt = (20.174241) | 39,743 | |
| 36 | Chief Warrant Officer @Texx | 2597 | 16699 | 218 sqrt = (14.764823) | 38,344 | -8- |
| 99 | Sergeant Major @allthingsmustpass | 1927 | 29488 | 353 sqrt = (18.788294) | 36,205 | |
| 41 | Chief Warrant Officer @PT | 2508 | 1023 | 193 sqrt = (13.892443) | 34,842 | -10- |
| 20 | Lieutenant @TP_knighty | 3164 | 3782 | 104 sqrt = (10.198039) | 32,267 | |
| 1 | General @AlexCheckMate | 6293 | 665 | 26 sqrt = (5.099019) | 32,088 | -12- |
| ... | ||||||
| 12 | Major @KOE_KittyKat | 3658 | 5809 | 76 sqrt = (8.717797) | 31,890 | |
| 103 | Sergeant Major @SmokinHog | 1897 | 404 | 282 sqrt = (16.792855) | 31,856 | |
| 44 | Private @1949midden | 2431 | 653 | 165 sqrt = (12.845232) | 31,227 | -15- |
| 38 | Chief Warrant Officer @Riskk | 2560 | 5011 | 141 sqrt = (11.874342) | 30,398 | |
| 64 | Private @letitbe | 2182 | 1763 | 172 sqrt = (13.114877) | 28,617 | |
| 139 | Command Sergeant @SN007 | 1722 | 1055 | 271 sqrt = (16.462077) | 28,348 | |
| ... | ||||||
| 77 | Private @Andies | 2060 | 7592 | 188 sqrt = (13.711309) | 28,245 | |
| 26 | 2nd Lieutenant @Blagoje_Jovovic | 3008 | 135 | 87 sqrt = (9.327379) | 28,057 | -20- |
| 39 | Chief Warrant Officer @phillberto | 2559 | 2283 | 117 sqrt = (10.816653) | 27,680 | |
| 167 | Master Sergeant @HalSucks | 1556 | 1277 | 312 sqrt = (17.663521) | 27,484 | |
| 19 | Lieutenant @simomosi | 3170 | 4613 | 75 sqrt = (8.660254) | 27,453 | |
| 90 | Sergeant Major @God_of_War | 2001 | 295 | 188 sqrt = (13.711309) | 27,436 | |
| ... | ||||||
| 111 | Private @Dominator3 | 1866 | 569 | 203 sqrt = (14.247806) | 26,586 | -25- |
| 158 | Private @MrTrotsky | 1627 | 4813 | 260 sqrt = (16.124515) | 26,235 | |
| 30 | Chief Warrant Officer @TimTheGreat | 2786 | 268 | 87 sqrt = (9.327379) | 25,986 | |
| 10 | Lieutenant Colonel @maafi | 3967 | 4922 | 39 sqrt = (6.244997) | 24,774 | |
| 61 | Private @cdravis | 2222 | 241 | 117 sqrt = (10.816653) | 24,035 | |
| 52 | Private @HannibalTunsi | 2315 | 2746 | 101 sqrt = (10.049875) | 23,265 | -30- |
| ... | ||||||
| 219 | Sergeant @GeneralHalsey | 1357 | 3273 | 279 sqrt = (16.703293) | 22,666 | |
| 7 | Brigadier General @Deepdaleduck | 4665 | 4562 | 23 sqrt = (4.795831) | 22,373 | |
| 151 | Command Sergeant @Mdhaglund | 1655 | 328 | 178 sqrt = (13.341664) | 22,080 | |
| 128 | Command Sergeant @genghis_burke | 1799 | 181 | 147 sqrt = (12.124355) | 21,812 | |
| 157 | Master Sergeant @IsolatedBadger | 1628 | 524 | 179 sqrt = (13.379088) | 21,781 | -35- |
| 32 | 2nd Lieutenant @roy12345 | 2683 | 1365 | 63 sqrt = (7.937253) | 21,296 |
beta-Predominance, 37th to 100th (click to show)
«God doesn't play dice with the World» ~ Albert Einstein
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Post #22
what i dont like about the stat, is that it doesnt take into account the player amount of the finished games. having 7 finished 1vs1 games is like one finished 7p game. in both cases you have fought against 7 players, but in one case its one single game and in another its 7 games. therefore the predominance is in the second case much higher. it seems that these stats are supporting people who play many short + live games.
it would be much more interesting to have a statistics, that shows how many and how often you beat other players. something like "amount of defeated players"
it would be much more interesting to have a statistics, that shows how many and how often you beat other players. something like "amount of defeated players"
"vorple: the real strategy comes when you cant just win cuz you got lucky and got the big card stack"
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Post #23
Any update to this kind of information? Always fun to see things like this.
Hi there!
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Post #24
I think The_Bishop updates it whenever a new d12 list is made. If he has time, that is!
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Post #25
Yep, probably... Do we got a new D12 list?
«God doesn't play dice with the World» ~ Albert Einstein
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Post #26
Yep, August 28th list:
https://dominating12.com/tutorial/thedominating12/36
https://dominating12.com/tutorial/thedominating12/36
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Post #27
I'm sorry for the delay.
I'll probably publish it tomorrow..
I'll probably publish it tomorrow..
«God doesn't play dice with the World» ~ Albert Einstein
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Post #28
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Post #29
Almost there... Calculations are done, but making the tab requires time. I had to figure out how to automatize it, but didn't.
Sorry, probably sunday or monday I'll publish it. I have to go out a couple of days.
I can reveal that @dimceto is first, followed by hooboy11, braveheart1, clydesdale444, allthingsmustpass, Joeyseven and... all the others.
Sorry, probably sunday or monday I'll publish it. I have to go out a couple of days.
I can reveal that @dimceto is first, followed by hooboy11, braveheart1, clydesdale444, allthingsmustpass, Joeyseven and... all the others.
«God doesn't play dice with the World» ~ Albert Einstein
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Post #30
You guys are just lucky that I missed my train... So here we are.
Later than late, but still sooner than never!
-- Top 36 beta-predominant players -- August 28th, 2020
...
Later than late, but still sooner than never!
-- Top 36 beta-predominant players -- August 28th, 2020
| Ranking | . . . --- Rank & username --- . . . | Rating --- | Total games - | Last session games (sqrt) --- | β-Predominance | -Count- |
| ... | ||||||
| 4 | Lieutenant General @dimceto | 5180 | 1159 | 177 sqrt = (13.304134) | 68,915 | -1- |
| 3 | Lieutenant General @hooboy11 | 5211 | 16873 | 130 sqrt = (11.401754) | 59,415 | -2- |
| 45 | Chief Warrant Officer @braveheart1 | 2420 | 597 | 482 sqrt = (21.954498) | 53,130 | -3- |
| 54 | Unranked @clydesdale444 | 2306 | 31627 | 530 sqrt = (23.021728) | 53,088 | -4- |
| 33 | 2nd Lieutenant @allthingsmustpass | 2645 | 29859 | 371 sqrt = (19.261360) | 50,946 | -5- |
| 5 | Lieutenant General @Joeyseven | 5143 | 1505 | 79 sqrt = (8.888194) | 45,712 | -6- |
| ... | ||||||
| 122 | Command Sergeant @lima | 1760 | 605 | 496 sqrt = (22.271057) | 39,197 | |
| 32 | 2nd Lieutenant @Mdhaglund | 2687 | 536 | 208 sqrt = (14.422205) | 38,752 | -8- |
| 14 | Major @1949midden | 3566 | 770 | 117 sqrt = (10.816653) | 38,572 | |
| 21 | Captain @KOE_KittyKat | 3258 | 5921 | 112 sqrt = (10.583005) | 34,479 | -10- |
| 23 | 2nd Lieutenant @Blagoje_Jovovic | 2995 | 259 | 124 sqrt = (11.135528) | 33,351 | |
| 10 | Lieutenant Colonel @maafi | 3881 | 4995 | 73 sqrt = (8.544003) | 33,159 | -12- |
| ... | ||||||
| 12 | Major @B4rny | 3624 | 1634 | 81 sqrt = (9.000000) | 32,616 | |
| 118 | Com Sergeant @Gottalottabling | 1775 | 610 | 294 sqrt = (17.146428) | 30,435 | |
| 58 | Private @Andies | 2257 | 7770 | 178 sqrt = (13.341664) | 30,112 | -15- |
| 49 | Chief Warrant Officer @God_of_War | 2360 | 457 | an>162 sqrt = (12.727922) | 30,038 | |
| 2 | General @slackbatter | 5831 | 2616 | 26 sqrt = (5.099019) | 29,732 | |
| 34 | Chief Warrant Officer @dwcalvert | 2593 | 2261 | 130 sqrt = (11.401754) | 29,565 | |
| ... | ||||||
| 13 | Major @Henris_1 | 3597 | 10717 | 67 sqrt = (8.185352) | 29,443 | |
| 67 | Warrant Officer @Hoodlum | 2183 | 36251 | 179 sqrt = (13.379088) | 29,207 | -20- |
| 27 | 2nd Lieutenant @TomC | 2756 | 4558 | 111 sqrt = (10.535653) | 29,036 | |
| 89 | Private @cdravis | 1966 | 459 | 218 sqrt = (14.764823) | 29,028 | |
| 37 | Chief Warrant Officer @Texx | 2564 | 16824 | 125 sqrt = (11.180339) | 28,666 | |
| 92 | Sergeant Major @elysium5 | 1955 | 8301 | 200 sqrt = (14.142135) | 27,648 | |
| ... | ||||||
| 81 | Master Sergeant @lucky23 | 2012 | 331 | 183 sqrt = (13.527749) | 27,218 | -25- |
| 1 | General @AlexCheckMate | 6581 | 681 | 16 sqrt = (4.000000) | 26,324 | |
| 18 | Private @Drac | 3382 | 2274 | 59 sqrt = (7.681145) | 25,978 | |
| 30 | 2nd Lieutenant @blackrabbit | 2718 | 886 | 89 sqrt = (9.433981) | 25,642 | |
| 9 | Lieutenant Colonel @OldDogGen | 3896 | 3539 | 41 sqrt = (6.403124) | 24,947 | |
| 78 | Master Sergeant @Barbaro | 2078 | 437 | 144 sqrt = (12.000000) | 24,936 | -30- |
| ... | ||||||
| 19 | Captain @ProblemChild96 | 3353 | 2774 | 54 sqrt = (7.348469) | 24,639 | |
| 136 | Command Sergeant @Newb19 | 1671 | 433 | 215 sqrt = (14.662878) | 24,502 | |
| 98 | Command Sergeant @ggg123 | 1925 | 626 | 160 sqrt = (12.649110) | 24,350 | |
| 53 | Private @Feej | 2308 | 920 | 111 sqrt = (10.535653) | 24,316 | |
| 216 | Sergeant @nperry54 | 1321 | 802 | 320 sqrt = (17.888543) | 23,631 | -35- |
| 48 | Chief Warrant Officer @TimTheGreat | 2373 | 366 | 98 sqrt = (9.899494) | 23,492 |
beta-Predominance, 37th to 100th (click to show)
«God doesn't play dice with the World» ~ Albert Einstein