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Game Courier Ratings for %

This file reads data on finished games and calculates Game Courier Ratings (GCR's) for each player. These will be most meaningful for single Chess variants, though they may be calculated across variants. This page is presently in development, and the method used is experimental. I may change the method in due time. How the method works is described below.

There may be a delay while it reads the database and calculates results.

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SELECT * FROM FinishedGames WHERE Rated='on'

Warning: You are viewing ratings based on a wildcard that includes all Chess variants played on Game Courier. This is not as meaningful as ratings based on a single variant, which you may find in the Related menu for each preset.

Game Courier Ratings for %
Accuracy:68.59%69.15%67.09%
NameUseridGCRPercent wonGCR1GCR2
Hexa Sakkbosa601848136.5/151 = 90.40%18181878
Francis Fahystamandua1840223.0/270 = 82.59%18281851
dax00dax001799106.0/112 = 94.64%17931804
Kevin Paceypanther1775318.0/393 = 80.92%17751774
Carlos Cetinasissa1723527.5/845 = 62.43%17141731
Cameron Milesshatteredglass170215.0/17 = 88.24%16891714
Jochen Muellerleopold_stotch169555.0/92 = 59.78%16811709
H Spetyura167513.0/13 = 100.00%16631688
Gary Giffordpenswift167260.5/85 = 71.18%15741769
Fergus Dunihofergus166459.5/97 = 61.34%16651663
Play Testerplaytester165718.5/25 = 74.00%16501664
Jose Carrilloj_carrillo_vii165785.5/151 = 56.62%16601654
David Paulowichdavid_64161911.0/13 = 84.62%16231615
shift2shiftshift2shift161511.0/19 = 57.89%16221607
Charles Danielfrozen_methane161335.0/64 = 54.69%15861641
Vitya Makovmakov16127.5/8 = 93.75%16051620
Homo Simiaalienum16127.0/8 = 87.50%16001624
Tim O'Lenatim_olena16096.5/8 = 81.25%16121606
Andreas Kaufmannandreas16077.0/7 = 100.00%16091605
ctzctz158212.0/17 = 70.59%15491615
Vitya Makovmakov3331578271.0/646 = 41.95%15261630
kokoszkokosz15757.0/8 = 87.50%15591590
Abdul-Rahman Sibahisibahi157316.0/23 = 69.57%15701576
attack hippoattackhippo15725.5/7 = 78.57%15641579
je jujejujeju157036.5/60 = 60.83%15601580
erikerik1570118.5/214 = 55.37%15861553
Alexander Trotterqilin15674.0/4 = 100.00%15651570
Stephen Stockmanstevestockman156610.0/16 = 62.50%15691562
TH6notath615617.0/12 = 58.33%15551566
Jenard Cabilaomgawalangmagawa156011.0/23 = 47.83%15691551
pallab basupallab155928.0/44 = 63.64%15771541
Raymond Dlewel155913.0/22 = 59.09%15751543
Isaac Felpsattacker14415585.0/6 = 83.33%15591557
Greg Strongmageofmaple155579.0/166 = 47.59%16151495
Nicola Caridiniccar15543.0/3 = 100.00%15571550
Nicholas Wolffnwolff15499.0/15 = 60.00%15711528
Roberto Lavierirlavieri200315493.0/3 = 100.00%15441555
S Ssim15436.0/9 = 66.67%15311554
John Gallantbigjohn154314.0/24 = 58.33%15281557
carlos carloscarlos153816.0/27 = 59.26%15171558
Tom e4ktome4k15372.0/2 = 100.00%15371536
Eric Greenwoodcavalier15344.0/6 = 66.67%15441523
Todd Witterstoddw15342.0/2 = 100.00%15321535
Matthew Montchalinmatthew_montchal15313.0/4 = 75.00%15291533
Neil Spargospargo15313.0/4 = 75.00%15201542
Jake Palladinocerebralassassin15312.0/2 = 100.00%15291532
Julien Coll Moratfacteurix15292.0/3 = 66.67%15281530
Joseph DiMurotrojh15281.0/1 = 100.00%15321524
Fred Koktangram15282.0/3 = 66.67%15281527
Nicholas Wolffmaeko152865.5/142 = 46.13%15461510
Uwe Kreuzercaissus15282.0/2 = 100.00%15251530
joe rosenbloombootzilla15272.0/3 = 66.67%15251530
Anthony Viensstarkiller15242.0/3 = 66.67%15251524
Adrian Alvarez de la Campaadrian15243.5/6 = 58.33%15241523
Yeinzon Rodríguez Garcíayeinzon15231.0/1 = 100.00%15281519
von raidervonraider15191.0/1 = 100.00%15211518
Larry Wheelerbrainburner15191.0/1 = 100.00%15201519
dicepawndicepawn15191.0/1 = 100.00%15191518
michirmichir15191.0/1 = 100.00%15191519
Chuck Leegyw6t151917.5/39 = 44.87%15061531
Todor Tchervenkovtchervenkov15181.0/1 = 100.00%15171519
Richard Titlertitle15181.0/1 = 100.00%15181518
yas kumkumagai15181.0/1 = 100.00%15181518
Trevor Savagesavage15181.0/1 = 100.00%15181518
David Levinsmidrael15181.0/1 = 100.00%15181518
eunchong leeeunchong15181.0/1 = 100.00%15181518
whitenerdy53whitenerdy5315181.0/1 = 100.00%15181518
Antonio Bruzzitotonno_janggi15181.0/1 = 100.00%15181518
Angel47 Usmanangel4715181.0/1 = 100.00%15181518
jj15181.0/1 = 100.00%15181518
calebblazecalebblaze15181.0/1 = 100.00%15181518
Jan Żmudajanzmuda15171.0/1 = 100.00%15181517
Titus Ledbettertbl215171.0/1 = 100.00%15181517
Hesham Husseinegy_sniper15171.0/1 = 100.00%15181516
M Wintherkalroten15171.0/1 = 100.00%15161518
bosa6bosa615171.0/1 = 100.00%15151519
Garrett Smithgmsmith15161.0/2 = 50.00%15241508
Georges-Clounet Jesuispartoutgeorgesclounet15161.0/1 = 100.00%15141518
Antonio Barratotonno15161.0/1 = 100.00%15141517
Aaron Smithzirtoc15152.5/5 = 50.00%15101520
pink sockpickett_aaron15152.0/3 = 66.67%15151515
Simon Langley-Evansslangers15151.5/2 = 75.00%15131516
xxmanxxman15121.0/2 = 50.00%15191505
Antoine Fourrièreantoinefourriere15111.5/2 = 75.00%15071515
mystery playercentipede15082.0/5 = 40.00%15111506
Nathanlokor15081.0/2 = 50.00%15101506
Zachary Wadeazost1215063.0/5 = 60.00%14991513
xeongreyxeongrey15058.0/17 = 47.06%15091501
Aurelian Floreacatugo1505219.5/542 = 40.50%16111399
Joe Joycejoejoyce150520.5/55 = 37.27%14801530
pheko Motaungcouriermabovini150435.5/70 = 50.71%15581451
As Bardhiasbardhi15031.0/2 = 50.00%15071500
Christine Bagley-Joneszcherryz15020.5/1 = 50.00%15051500
Gee Beegdimension15021.0/2 = 50.00%15021502
Tom Trenchtomdench9515020.5/1 = 50.00%15041500
Colin Adamslionhawk15021.0/2 = 50.00%15051500
Albert Vámosiblackrider_4815021.0/4 = 25.00%15141490
Graeme Neathamgrayhawke15011.0/2 = 50.00%14991504
noy noynoy15013.0/7 = 42.86%14911511
Hans Henrikssonhasurami15002.0/4 = 50.00%14891511
Kent Weschlerperplexedibex14991.0/3 = 33.33%14971501
Georg Spengleravunjahei14999.0/28 = 32.14%14831514
Colin Weaveruselessgit14981.0/4 = 25.00%14991498
Thom Dimentunwiseowl14982.0/5 = 40.00%14981497
Juan Pablo Schweitzer Kirsingerdefender14981.0/2 = 50.00%14951500
Max Fengwowimbob111214941.0/3 = 33.33%14961492
John Smithultimatecoolster14943.0/9 = 33.33%14881499
arxarx149313.0/30 = 43.33%15041482
Hsa Saidh14920.0/1 = 0.00%14961487
Hugo Mendes-Nuneshugo199514910.0/1 = 0.00%14961487
Bob Brownbobhihih14910.0/1 = 0.00%14951488
wyatt wyattquimssarcasm14910.0/1 = 0.00%14951487
jesus babyboypokechamp14910.0/1 = 0.00%14951486
kunkunkunkun14910.0/1 = 0.00%14951486
Eni Lienili149011.5/46 = 25.00%15031478
don anezdonanez14900.0/1 = 0.00%14961485
Michael Christensenjustsojazz14900.0/1 = 0.00%14961484
hubergerdhubergerd14900.0/1 = 0.00%14961484
Fabner Cruz Gracilianofabner14890.0/1 = 0.00%14961483
DFA Productions70nyd014890.0/1 = 0.00%14961482
makomako14890.0/1 = 0.00%14961482
vikvik14890.0/1 = 0.00%14961481
loveokenloveoken14890.0/1 = 0.00%14931484
Hafsteinn Kjartanssonhnr0114880.0/1 = 0.00%14961481
Jason Stehlyjasonstehly14880.0/1 = 0.00%14931484
John Badgerjbadger14880.0/1 = 0.00%14941482
Éric Manálangedubble1914880.0/1 = 0.00%14931483
ugo judeugojude14880.0/1 = 0.00%14941481
Steve Polleychessfan5914880.0/1 = 0.00%14931482
xerisianxxerisianx14870.0/1 = 0.00%14941481
LuigiMaster285qqzlbpdilchr14870.0/1 = 0.00%14911483
DJ Linickdjlinick14870.0/1 = 0.00%14911482
Ivan Velascoswordandsilver14860.0/1 = 0.00%14911481
Rob Brownsteelhead14860.0/1 = 0.00%14911481
Bradlee Kingstonbrad1914850.0/1 = 0.00%14891482
Mike Smolowitzmjs170114850.0/1 = 0.00%14891481
Gus Dunihoduniho14850.0/1 = 0.00%14871483
Luis Menendezpleyades2114850.0/1 = 0.00%14871483
Andy Thomasandy_thomas14850.0/1 = 0.00%14881482
Brock Sampsonthe_iron_kenyan14850.0/1 = 0.00%14881482
Nasmichael Farrismichaeljay14850.0/1 = 0.00%14881481
Travis Comptonironlance14850.0/1 = 0.00%14881481
Erlang Shenerlangshen14840.0/1 = 0.00%14881481
Derek Mooseelevatorfarter14841.0/3 = 33.33%14841484
James Sprattwhittlin14840.0/1 = 0.00%14871481
manolo manolomanolo14840.0/1 = 0.00%14861482
Talen Storlatalen3141593141514840.0/1 = 0.00%14861481
Antony Vailevichjabberw0cky114840.0/1 = 0.00%14861481
Jeremy Goodyamorezu14840.0/1 = 0.00%14851482
yi fang liuliuyifang14830.0/1 = 0.00%14861481
andy lewickiherlocksholmes14830.0/1 = 0.00%14851481
trtztrtz gfghtrtztrtz14830.0/1 = 0.00%14851481
Thomas Meehanorangeaurochs14830.0/1 = 0.00%14831483
Joseph Grangercdafan14830.0/1 = 0.00%14841482
luigi mattagigino4214830.0/1 = 0.00%14841481
Andreas Bunkahlebunkahle14830.0/1 = 0.00%14831482
Roberto Cassanotamerlano14830.0/1 = 0.00%14841481
btstwbtstw14830.0/1 = 0.00%14821483
Dan Kellydankelly14830.0/1 = 0.00%14841481
MichaÅ‚ Jarskihookz14830.0/1 = 0.00%14831482
Jose Canceljoche14820.0/1 = 0.00%14841481
Tony Quintanillatony_quintanilla14820.0/1 = 0.00%14841480
Hung Daobyteboy14820.0/1 = 0.00%14831481
cdpowercdpower14820.0/1 = 0.00%14831481
anna colladoapatura_iris14820.0/1 = 0.00%14811482
Ronald Brierleybenwb14820.0/1 = 0.00%14821481
Paolo Porsiapillau14820.0/1 = 0.00%14821481
Minh Dangminhdang14820.0/1 = 0.00%14811482
Виктор Байгужаковbajvik14820.0/1 = 0.00%14811482
Robin Sneijderrobinwooter214820.0/1 = 0.00%14821481
sixtysixty14810.0/3 = 0.00%14881475
Mark Thompsonmarkthompson14810.0/2 = 0.00%14911472
Harry Gaoharrygao14810.0/1 = 0.00%14811481
paulblazepaulblaze14810.0/1 = 0.00%14811481
Vitali Maslanskivitali_1014810.0/1 = 0.00%14811481
wonsang leewonsang14810.0/1 = 0.00%14811481
Ryan Schwartzshunoshi14810.0/1 = 0.00%14811481
y kumyasuhiro14810.0/1 = 0.00%14811481
Babo Jeffbabojeff14810.0/1 = 0.00%14811481
14810.0/1 = 0.00%14811481
ben chewben558214810.0/1 = 0.00%14811481
Abe Anonapostateabe14810.0/1 = 0.00%14811481
blundermanblunderman14810.0/1 = 0.00%14801482
Jun Ocampojunpogi14810.0/2 = 0.00%14861475
Uri Bruckbruck14800.0/2 = 0.00%14921469
arcasorarcasor14800.0/1 = 0.00%14791481
Nicholas Archerchess_hunter14800.0/2 = 0.00%14871473
qidb602qidb60214800.0/2 = 0.00%14841477
Julianredpanda148017.0/35 = 48.57%14601500
Giuseppe Acciarocoopwie14802.0/5 = 40.00%14741486
scythian blunderq1234514800.0/2 = 0.00%14871473
László Gadosdani198314801.0/4 = 25.00%14701489
rederikrederik14800.0/1 = 0.00%14781481
Francesco Casalinofrancesco14790.0/2 = 0.00%14851474
legendlegend14790.0/2 = 0.00%14891469
Diego M.diego14780.0/3 = 0.00%14821475
voicantvoicant14780.0/1 = 0.00%14771480
Bn Emnelk11414780.0/2 = 0.00%14851471
championchampion14780.0/2 = 0.00%14841471
Ivan Kosintsevbombino14780.0/1 = 0.00%14741481
ologyology14770.0/1 = 0.00%14731481
Alexander Krutikovlonewolf14771.0/4 = 25.00%14751479
Frank Istvánistvan6014760.0/2 = 0.00%14841468
wdtrwdtr14760.0/3 = 0.00%14771475
Ivan Ivankillbill22514760.0/1 = 0.00%14701481
andres fuentesxabyer14750.0/2 = 0.00%14791471
Szling Ozecszling_ozec14730.0/3 = 0.00%14761471
Lennon Figueiredogiwseppe14731.0/4 = 25.00%14711476
Pablo Denegrideep_thinker14730.0/2 = 0.00%14741473
Charles Gilmancharles_gilman14730.0/2 = 0.00%14751471
Michael Huntkronsteen3314720.0/2 = 0.00%14701474
andrewthepawnandrewthepawn14720.0/2 = 0.00%14721472
Kacper Rutkowskikacperrutkowski14710.0/2 = 0.00%14741469
dfe6631dfe663114710.0/2 = 0.00%14731469
John Twycrossjt14710.0/2 = 0.00%14741468
Travis Comptonblackrood14690.0/2 = 0.00%14651474
Zoli M Zoltánbaltazarprof14680.0/5 = 0.00%14801457
vitaliy ravitztalsterch14680.0/5 = 0.00%14631472
Daniel MacDuffdanielmacduff14670.0/3 = 0.00%14661469
Memedes Lulagiwseppe314670.0/2 = 0.00%14691466
iuchi45iuchi4514670.0/2 = 0.00%14651469
Steve Hsteve_201014670.0/2 = 0.00%14661468
Sergey Biryukovsbiryukov14670.0/4 = 0.00%14681465
Zac Sparxkrinid14660.0/2 = 0.00%14681465
cherokee malansailorhertzog14660.0/2 = 0.00%14691464
jeremy diniericharles_bukowski14660.0/2 = 0.00%14641469
Adam DeWittchessshogi14660.0/3 = 0.00%14731460
Pat Quexionezsuperpatzermaste14660.0/4 = 0.00%14701462
Boyko Ahtarovzdra4146510.0/23 = 43.48%14601471
Donut Donutdonutdonut14650.0/2 = 0.00%14651465
playshogiplayshogi14640.0/2 = 0.00%14651463
Michael Nelsonmikenels14640.0/2 = 0.00%14621466
Namik Zadenamik14630.0/2 = 0.00%14611465
A tomiatomi14634.5/16 = 28.12%14551471
Scott Crawfordmathemagician14630.0/7 = 0.00%14701455
andy lewickietaoni14620.0/2 = 0.00%14621463
michael collinsverderben14621.0/5 = 20.00%14661457
louisvlouisv14550.0/3 = 0.00%14571453
Graemegraemecn14540.0/3 = 0.00%14501457
Сергей Маэстроfantomas14530.0/5 = 0.00%14491458
John Langleyjonners14520.5/4 = 12.50%14521451
Andy Lewickiondraszek14520.0/3 = 0.00%14421461
Dayrom Gilallahukbar14510.0/3 = 0.00%14501453
Michael Schmahlmschmahl14505.0/15 = 33.33%14551445
Николай Сокольскийalexich14500.0/4 = 0.00%14511448
Armin Liebhartlunaris144916.0/37 = 43.24%14611438
Linn Russellfreakat14490.0/3 = 0.00%14481449
boukineboukine14484.0/11 = 36.36%14281468
Adalbertus Kchewoj14481.0/5 = 20.00%14431454
Aaron Maynardvopi14451.0/6 = 16.67%14381452
Scott McGrealagentofchaos14447.0/19 = 36.84%14451442
Nick Wolffwolff144125.0/71 = 35.21%14161466
heche60heche6014392.0/12 = 16.67%14371442
Evert Jan Karmanevertvb14392.5/11 = 22.73%14261453
Evan Jorgensonsabataegalo14380.0/7 = 0.00%14291447
Joshua Tsamraku14384.5/12 = 37.50%14131463
dmitarzvonimirdmitarzvonimir14380.0/5 = 0.00%14321443
Sagi Gabaysagig7214350.5/16 = 3.12%14101460
Jeremy Goodjudgmentality143243.5/127 = 34.25%14251438
Jon Dannjon_dann14300.0/4 = 0.00%14271433
Phoenix TKartkr10101014292.0/9 = 22.22%14401418
juan rodriguezrodriguez142811.5/38 = 30.26%14401416
Jack Zavierubersketch14250.0/6 = 0.00%14241426
Arthur Yvrardtorendil14160.0/7 = 0.00%14111421
Diogen Abramelindanko14160.0/11 = 0.00%14191412
Alan Galetornadic14153.0/20 = 15.00%14051424
Daniil Frolovflowermann14143.0/16 = 18.75%13971430
Matthew La Valleesherman10114136.0/23 = 26.09%13951432
John Davischappy14113.0/17 = 17.65%13961425
yellowturtleyellowturtle14090.0/10 = 0.00%14071410
Evan Jorgensonejorgens14050.0/7 = 0.00%13931418
George Dukegwduke139742.5/116 = 36.64%13671428
Jeremy Hook10011013972.0/30 = 6.67%13841410
darren paullramalam137510.5/90 = 11.67%13461404
Jarid Carlsonsacredchao137012.0/61 = 19.67%13321408
Bogot Bogotolbog136712.0/44 = 27.27%13581375
sxgsxg134831.5/139 = 22.66%13151381
per hommerbergper3113112.0/41 = 4.88%13061316
wdtr2wdtr2128213.5/103 = 13.11%12181347
Сергей Бугаевскийbugaevsky12773.0/56 = 5.36%12831271

Meaning

The ratings are estimates of relative playing strength. Given the ratings of two players, the difference between their ratings is used to estimate the percentage of games each may win against the other. A difference of zero estimates that each player should win half the games. A difference of 400 or more estimates that the higher rated player should win every game. Between these, the higher rated player is expected to win a percentage of games calculated by the formula (difference/8)+50. A rating means nothing on its own. It is meaningful only in comparison to another player whose rating is derived from the same set of data through the same set of calculations. So your rating here cannot be compared to someone's Elo rating.

Accuracy

Ratings are calculated through a self-correcting trial-and-error process that compares actual outcomes with expected outcomes, gradually changing the ratings to better reflect actual outcomes. With enough data, this process can approach accuracy to a high degree, but error remains an essential element of any trial-and-error process, and without enough data, its results will remain error-ridden. Unfortunately, Chess variants are not played enough to give it a large data set to work with. The data sets here are usually small, and that means the ratings will not be fully accurate.

One measure taken to eke out the most data from the small data sets that are available is to calculate ratings in a holistic manner that incorporates all results into the evaluation of each result. The first step of this is to go through pairs of players in a manner that doesn't concentrate all the games of one player in one stage of the process. This involves ordering the players in a zig-zagging manner that evenly distributes each player throughout the process of evaluating ratings. The second step is to reverse the order that pairs of players are evaluated in, recalculate all the ratings, and average the two sets of ratings. This allows the outcome of every game to affect the rating calculations for every pair of players. One consequence of this is that your rating is not a static figure. Games played by other people may influence your rating even if you have stopped playing. The upside to this is that ratings of inactive players should get more accurate as more games are played by other people.

Fairness

High ratings have to be earned by playing many games. They are not available through shortcuts. In a previous version of the rating system, I focused on accuracy more than fairness, which resulted in some players getting high ratings after playing only a few games. This new rating system curbs rating growth more, so that you have to win many games to get a high rating. One way it curbs rating growth is to base the amount it changes a rating on the number of games played between two players. The more games they play together, the more it approaches the maximum amount a rating may be changed after comparing two players. This maximum amount is equal to the percentage of difference between expectations and actual results times 400. So the amount ratings may change in one go is limited to a range of 0 to 400. The amount of change is further limited by the number of games each player has already played. The more past games a player has played, the more his rating is considered stable, making it less subject to change.

Algorithm

  1. Each finished public game matching the wildcard or list of games is read, with wins and draws being recorded into a table of pairwise wins. A win counts as 1 for the winner, and a draw counts as .5 for each player.
  2. All players get an initial rating of 1500.
  3. All players are sorted in order of decreasing number of games. Ties are broken first by number of games won, then by number of opponents. This determines the order in which pairs of players will have their ratings recalculated.
  4. Initialize the count of all player's past games to zero.
  5. Based on the ordering of players, go through all pairs of players in a zig-zagging order that spreads out the pairing of each player with each of his opponents. For each pair that have played games together, recalculate their ratings as described below:
    1. Add up the number of games played. If none, skip to the next pair of players.
    2. Identify the players as p1 and p2, and subtract p2's rating from p1's.
    3. Based on this score, calculate the percent of games p1 is expected to win.
    4. Subtract this percentage from the percentage of games p1 actually won. // This is the difference between actual outcome and predicted outcome. It may range from -100 to +100.
    5. Multiply this difference by 400 to get the maximum amount of change allowed.
    6. Where n is the number of games played together, multiply the maximum amount of change by (n)/(n+10).
    7. For each player, where p is the number of his past games, multiply this product by (1-(p/(p+800))).
    8. Add this amount to the rating for p1, and subtract it from the rating for p2. // If it is negative, p1 will lose points, and p2 will gain points.
    9. Update the count of each player's past games by adding the games they played together.
  6. Reinitialize all player's past games to zero.
  7. Repeat the same procedure in the reverse zig-zagging order, creating a new set of ratings.
  8. Average both sets of ratings into one set.


Written by Fergus Duniho
WWW Page Created: 6 January 2006