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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:68.98%69.33%67.80%
NameUseridGCRPercent wonGCR1GCR2
Hexa Sakkbosa601854136.5/151 = 90.40%18241884
Francis Fahystamandua1846244.0/294 = 82.99%18291863
dax00dax001798124.0/130 = 95.38%17771819
Kevin Paceypanther1782398.0/489 = 81.39%17881776
Carlos Cetinasissa1725566.5/899 = 63.01%17111738
Cameron Milesshatteredglass171015.0/17 = 88.24%17011719
Jochen Muellerleopold_stotch169555.0/92 = 59.78%16821709
H Spetyura167913.0/13 = 100.00%16781679
Gary Giffordpenswift167160.5/85 = 71.18%15741769
Play Testerplaytester166918.5/25 = 74.00%16731665
Fergus Dunihofergus166659.5/97 = 61.34%16631669
Jose Carrilloj_carrillo_vii165885.5/151 = 56.62%16641652
David Paulowichdavid_64162211.0/13 = 84.62%16231620
shift2shiftshift2shift161511.0/19 = 57.89%16261605
Charles Danielfrozen_methane161435.0/64 = 54.69%15851643
Vitya Makovmakov16137.5/8 = 93.75%16071619
Tim O'Lenatim_olena16136.5/8 = 81.25%16161609
Homo Simiaalienum16127.0/8 = 87.50%16011622
Andreas Kaufmannandreas16077.0/7 = 100.00%16081605
Vitya Makovmakov3331594296.0/681 = 43.47%15411648
ctzctz158012.0/17 = 70.59%15541605
Thor Slavenskyslavensky15785.0/5 = 100.00%15681588
kokoszkokosz15777.0/8 = 87.50%15641590
erikerik1577129.5/231 = 56.06%16021552
attack hippoattackhippo15745.5/7 = 78.57%15691579
Abdul-Rahman Sibahisibahi157416.0/23 = 69.57%15651582
je jujejujeju157336.5/60 = 60.83%15651581
Alexander Trotterqilin15684.0/4 = 100.00%15671569
Stephen Stockmanstevestockman156810.0/16 = 62.50%15761560
Jenard Cabilaomgawalangmagawa156611.0/23 = 47.83%15781554
Greg Strongmageofmaple156485.0/179 = 47.49%16201508
TH6notath615637.0/12 = 58.33%15601566
Raymond Dlewel156013.0/22 = 59.09%15771543
Isaac Felpsattacker14415585.0/6 = 83.33%15591557
Nicola Caridiniccar15543.0/3 = 100.00%15571550
John Gallantbigjohn155216.0/28 = 57.14%15491555
Nicholas Wolffnwolff15529.0/15 = 60.00%15761527
Roberto Lavierirlavieri200315503.0/3 = 100.00%15451555
carlos carloscarlos154316.0/27 = 59.26%15191567
S Ssim15436.0/9 = 66.67%15311554
pallab basupallab154131.0/60 = 51.67%15291553
Tom e4ktome4k15362.0/2 = 100.00%15351536
Eric Greenwoodcavalier15344.0/6 = 66.67%15431525
Todd Witterstoddw15342.0/2 = 100.00%15321535
Neil Spargospargo15333.0/4 = 75.00%15251541
Pericles Tesone de Souzaperitezz15332.0/2 = 100.00%15331533
Matthew Montchalinmatthew_montchal15313.0/4 = 75.00%15291533
Jake Palladinocerebralassassin15312.0/2 = 100.00%15281534
Julien Coll Moratfacteurix15302.0/3 = 66.67%15271533
Fred Koktangram15282.0/3 = 66.67%15281528
Joseph DiMurotrojh15281.0/1 = 100.00%15331523
joe rosenbloombootzilla15282.0/3 = 66.67%15271529
Uwe Kreuzercaissus15272.0/2 = 100.00%15251529
Nicholas Wolffmaeko152565.5/142 = 46.13%15481502
Adrian Alvarez de la Campaadrian15233.5/6 = 58.33%15241523
Yeinzon Rodríguez Garcíayeinzon15231.0/1 = 100.00%15281519
Chuck Leegyw6t152217.5/39 = 44.87%15131531
von raidervonraider15191.0/1 = 100.00%15211518
Larry Wheelerbrainburner15191.0/1 = 100.00%15201519
dicepawndicepawn15191.0/1 = 100.00%15201518
michirmichir15191.0/1 = 100.00%15201519
Todor Tchervenkovtchervenkov15181.0/1 = 100.00%15171519
Richard Titlertitle15181.0/1 = 100.00%15191518
Antonio Bruzzitotonno_janggi15181.0/1 = 100.00%15181518
calebblazecalebblaze15181.0/1 = 100.00%15181518
Angel47 Usmanangel4715181.0/1 = 100.00%15181518
whitenerdy53whitenerdy5315181.0/1 = 100.00%15181518
Trevor Savagesavage15181.0/1 = 100.00%15181518
eunchong leeeunchong15181.0/1 = 100.00%15181518
David Levinsmidrael15181.0/1 = 100.00%15181518
yas kumkumagai15181.0/1 = 100.00%15181518
jj15181.0/1 = 100.00%15181518
Joe Joycejoejoyce151820.5/57 = 35.96%14751560
Jan Żmudajanzmuda15171.0/1 = 100.00%15181517
Titus Ledbettertbl215171.0/1 = 100.00%15181517
Garrett Smithgmsmith15171.0/2 = 50.00%15241510
Hesham Husseinegy_sniper15171.0/1 = 100.00%15161518
M Wintherkalroten15171.0/1 = 100.00%15171517
bosa6bosa615171.0/1 = 100.00%15161518
Aaron Smithzirtoc15162.5/5 = 50.00%15121520
Georges-Clounet Jesuispartoutgeorgesclounet15161.0/1 = 100.00%15141518
Antonio Barratotonno15161.0/1 = 100.00%15151517
pink sockpickett_aaron15152.0/3 = 66.67%15151515
Simon Langley-Evansslangers15151.5/2 = 75.00%15131516
xxmanxxman15111.0/2 = 50.00%15191503
spiptorben15101.0/2 = 50.00%15101511
Antoine Fourrièreantoinefourriere15101.5/2 = 75.00%15061515
mystery playercentipede15092.0/5 = 40.00%15101508
Georg Spengleravunjahei15089.0/28 = 32.14%15001517
Nathanlokor15081.0/2 = 50.00%15101505
Anthony Viensstarkiller15072.0/4 = 50.00%15001514
xeongreyxeongrey15078.0/17 = 47.06%15111503
pheko Motaungcouriermabovini150735.5/70 = 50.71%15571456
Zachary Wadeazost1215063.0/5 = 60.00%14981513
As Bardhiasbardhi15041.0/2 = 50.00%15081501
Gee Beegdimension15031.0/2 = 50.00%15031502
Colin Adamslionhawk15021.0/2 = 50.00%15051500
Christine Bagley-Joneszcherryz15020.5/1 = 50.00%15051500
Albert Vámosiblackrider_4815021.0/4 = 25.00%15151488
Graeme Neathamgrayhawke15021.0/2 = 50.00%15001504
Hans Henrikssonhasurami15012.0/4 = 50.00%14901512
Tom Trenchtomdench9515010.5/1 = 50.00%15031500
Colin Weaveruselessgit14991.0/4 = 25.00%14981499
Kent Weschlerperplexedibex14991.0/3 = 33.33%14991498
noy noynoy14993.0/7 = 42.86%14911506
Thom Dimentunwiseowl14982.0/5 = 40.00%15001495
Juan Pablo Schweitzer Kirsingerdefender14971.0/2 = 50.00%14941500
Daniel Zachariasarx149518.0/42 = 42.86%14801511
Eni Lienili149511.5/46 = 25.00%15091481
Max Fengwowimbob111214941.0/3 = 33.33%14981491
John Smithultimatecoolster14943.0/9 = 33.33%14931495
Hsa Saidh14920.0/1 = 0.00%14961488
Hugo Mendes-Nuneshugo199514920.0/1 = 0.00%14961488
jesus babyboypokechamp14920.0/1 = 0.00%14961487
wyatt wyattquimssarcasm14910.0/1 = 0.00%14961486
Anders Gustafsonancog14910.0/1 = 0.00%14961486
Bob Brownbobhihih14910.0/1 = 0.00%14951486
kunkunkunkun14910.0/1 = 0.00%14951486
don anezdonanez14900.0/1 = 0.00%14961485
Michael Christensenjustsojazz14900.0/1 = 0.00%14961484
hubergerdhubergerd14900.0/1 = 0.00%14961484
DFA Productions70nyd014890.0/1 = 0.00%14961483
vikvik14890.0/1 = 0.00%14961482
Steve Polleychessfan5914890.0/1 = 0.00%14941484
makomako14890.0/1 = 0.00%14961482
Fabner Cruz Gracilianofabner14890.0/1 = 0.00%14961481
Éric Manálangedubble1914890.0/1 = 0.00%14941484
Hafsteinn Kjartanssonhnr0114890.0/1 = 0.00%14961481
loveokenloveoken14880.0/1 = 0.00%14941483
Jason Stehlyjasonstehly14880.0/1 = 0.00%14941482
xerisianxxerisianx14880.0/1 = 0.00%14941481
John Badgerjbadger14880.0/1 = 0.00%14931482
ugo judeugojude14880.0/1 = 0.00%14941481
LuigiMaster285qqzlbpdilchr14870.0/1 = 0.00%14911483
DJ Linickdjlinick14870.0/1 = 0.00%14911482
Ivan Velascoswordandsilver14860.0/1 = 0.00%14911482
Rob Brownsteelhead14860.0/1 = 0.00%14911481
Bradlee Kingstonbrad1914850.0/1 = 0.00%14891482
Mike Smolowitzmjs170114850.0/1 = 0.00%14891481
Luis Menendezpleyades2114850.0/1 = 0.00%14871483
Aurelian Floreacatugo1485234.5/620 = 37.82%15721398
Gus Dunihoduniho14850.0/1 = 0.00%14871483
Brock Sampsonthe_iron_kenyan14850.0/1 = 0.00%14881482
Erlang Shenerlangshen14850.0/1 = 0.00%14891481
Andy Thomasandy_thomas14850.0/1 = 0.00%14881482
Travis Comptonironlance14850.0/1 = 0.00%14881481
Nasmichael Farrismichaeljay14850.0/1 = 0.00%14881481
Derek Mooseelevatorfarter14841.0/3 = 33.33%14841484
James Sprattwhittlin14840.0/1 = 0.00%14871481
Talen Storlatalen3141593141514840.0/1 = 0.00%14861481
Jeremy Goodyamorezu14840.0/1 = 0.00%14851482
yi fang liuliuyifang14830.0/1 = 0.00%14861481
andy lewickiherlocksholmes14830.0/1 = 0.00%14861481
Alexandr Kremenakremen14830.0/1 = 0.00%14851481
manolo manolomanolo14830.0/1 = 0.00%14841483
Julianredpanda148317.0/35 = 48.57%14631503
Antony Vailevichjabberw0cky114830.0/1 = 0.00%14841482
Solomon Salamasol71014830.0/1 = 0.00%14841481
Dan Kellydankelly14830.0/1 = 0.00%14841481
btstwbtstw14830.0/1 = 0.00%14821483
MichaÅ‚ Jarskihookz14830.0/1 = 0.00%14831482
Roberto Cassanotamerlano14830.0/1 = 0.00%14831482
Hung Daobyteboy14820.0/1 = 0.00%14841481
Andreas Bunkahlebunkahle14820.0/1 = 0.00%14841481
Jose Canceljoche14820.0/1 = 0.00%14841481
Tony Quintanillatony_quintanilla14820.0/1 = 0.00%14841480
Uri Bruckbruck14820.0/2 = 0.00%14911473
cdpowercdpower14820.0/1 = 0.00%14831481
Ronald Brierleybenwb14820.0/1 = 0.00%14831481
Paolo Porsiapillau14820.0/1 = 0.00%14831481
sixtysixty14820.0/3 = 0.00%14881475
anna colladoapatura_iris14820.0/1 = 0.00%14811482
Thomas Meehanorangeaurochs14820.0/1 = 0.00%14811482
luigi mattagigino4214820.0/1 = 0.00%14801483
Joseph Grangercdafan14820.0/1 = 0.00%14821481
Виктор Байгужаковbajvik14820.0/1 = 0.00%14811482
Robin Sneijderrobinwooter214820.0/1 = 0.00%14821481
Minh Dangminhdang14820.0/1 = 0.00%14821481
Jun Ocampojunpogi14810.0/2 = 0.00%14881475
paulblazepaulblaze14810.0/1 = 0.00%14811481
Babo Jeffbabojeff14810.0/1 = 0.00%14811481
Vitali Maslanskivitali_1014810.0/1 = 0.00%14811481
14810.0/1 = 0.00%14811481
ben chewben558214810.0/1 = 0.00%14811481
wonsang leewonsang14810.0/1 = 0.00%14811481
Harry Gaoharrygao14810.0/1 = 0.00%14811481
Ryan Schwartzshunoshi14810.0/1 = 0.00%14811481
y kumyasuhiro14810.0/1 = 0.00%14811481
Abe Anonapostateabe14810.0/1 = 0.00%14811481
blundermanblunderman14810.0/1 = 0.00%14801482
Mark Thompsonmarkthompson14810.0/2 = 0.00%14921471
Giuseppe Acciarocoopwie14812.0/5 = 40.00%14751487
Nicholas Archerchess_hunter14810.0/2 = 0.00%14871475
scythian blunderq1234514810.0/2 = 0.00%14881473
arcasorarcasor14800.0/1 = 0.00%14791481
qidb602qidb60214800.0/2 = 0.00%14831477
László Gadosdani198314801.0/4 = 25.00%14761484
rederikrederik14800.0/1 = 0.00%14791480
Bn Emnelk11414790.0/2 = 0.00%14841475
Diego M.diego14790.0/3 = 0.00%14841474
Boyko Ahtarovzdra4147910.0/23 = 43.48%14751484
Francesco Casalinofrancesco14790.0/2 = 0.00%14841473
voicantvoicant14780.0/1 = 0.00%14771480
legendlegend14780.0/2 = 0.00%14881469
Ivan Kosintsevbombino14780.0/1 = 0.00%14741481
ologyology14780.0/1 = 0.00%14741481
championchampion14770.0/2 = 0.00%14851469
wdtrwdtr14760.0/3 = 0.00%14771475
Alexander Krutikovlonewolf14761.0/4 = 25.00%14721479
Ivan Ivankillbill22514760.0/1 = 0.00%14701481
Frank Istvánistvan6014760.0/2 = 0.00%14861466
andres fuentesxabyer14750.0/2 = 0.00%14791471
trtztrtz gfghtrtztrtz14750.0/2 = 0.00%14791471
Pablo Denegrideep_thinker14730.0/2 = 0.00%14741473
Lennon Figueiredogiwseppe14731.0/4 = 25.00%14711476
Charles Gilmancharles_gilman14730.0/2 = 0.00%14761471
Szling Ozecszling_ozec14730.0/3 = 0.00%14771469
John Twycrossjt14710.0/2 = 0.00%14741468
Kacper Rutkowskikacperrutkowski14710.0/2 = 0.00%14741467
andrewthepawnandrewthepawn14700.0/2 = 0.00%14661474
Travis Comptonblackrood14700.0/2 = 0.00%14661474
Armin Liebhartlunaris147019.0/44 = 43.18%14831456
dfe6631dfe663114700.0/2 = 0.00%14691470
Zoli M Zoltánbaltazarprof14690.0/5 = 0.00%14821457
Sergey Biryukovsbiryukov14690.0/4 = 0.00%14701468
Daniel MacDuffdanielmacduff14680.0/3 = 0.00%14671470
Pat Quexionezsuperpatzermaste14680.0/4 = 0.00%14711465
Steve Hsteve_201014680.0/2 = 0.00%14681468
Memedes Lulagiwseppe314670.0/2 = 0.00%14691466
cherokee malansailorhertzog14670.0/2 = 0.00%14711464
jeremy diniericharles_bukowski14670.0/2 = 0.00%14661468
Zac Sparxkrinid14670.0/2 = 0.00%14691465
Adam DeWittchessshogi14670.0/3 = 0.00%14721461
Samuel de Souzasamsou14660.0/2 = 0.00%14661466
A tomiatomi14664.5/16 = 28.12%14591474
iuchi45iuchi4514650.0/2 = 0.00%14631467
Donut Donutdonutdonut14650.0/2 = 0.00%14661465
playshogiplayshogi14640.0/2 = 0.00%14661463
Scott Crawfordmathemagician14640.0/7 = 0.00%14731455
Michael Nelsonmikenels14640.0/2 = 0.00%14611466
andy lewickietaoni14630.0/2 = 0.00%14631463
Namik Zadenamik14630.0/2 = 0.00%14611465
michael collinsverderben14621.0/5 = 20.00%14671457
Michael Huntkronsteen3314590.0/3 = 0.00%14501467
louisvlouisv14550.0/3 = 0.00%14581453
Graemegraemecn14540.0/3 = 0.00%14501458
Andy Lewickiondraszek14530.0/3 = 0.00%14451460
John Langleyjonners14520.5/4 = 12.50%14521451
Dayrom Gilallahukbar14510.0/3 = 0.00%14511452
Николай Сокольскийalexich14510.0/4 = 0.00%14521450
Michael Schmahlmschmahl14505.0/15 = 33.33%14571442
Linn Russellfreakat14490.0/3 = 0.00%14491449
Adalbertus Kchewoj14491.0/5 = 20.00%14451453
boukineboukine14484.0/11 = 36.36%14291467
Scott McGrealagentofchaos14477.0/19 = 36.84%14491444
Aaron Maynardvopi14461.0/6 = 16.67%14411451
vitaliy ravitztalsterch14442.0/15 = 13.33%14361452
Nick Wolffwolff144425.0/71 = 35.21%14141473
heche60heche6014412.0/12 = 16.67%14411442
Sagi Gabaysagig7214380.5/16 = 3.12%14201456
Joshua Tsamraku14384.5/12 = 37.50%14141461
dmitarzvonimirdmitarzvonimir14380.0/5 = 0.00%14311444
Evan Jorgensonsabataegalo14350.0/7 = 0.00%14291441
Evert Jan Karmanevertvb14342.5/11 = 22.73%14201448
Phoenix TKartkr10101014322.0/9 = 22.22%14351429
Jeremy Goodjudgmentality143143.5/127 = 34.25%14221440
Jon Dannjon_dann14300.0/4 = 0.00%14271433
juan rodriguezrodriguez142911.5/38 = 30.26%14421416
Jack Zavierubersketch14220.0/6 = 0.00%14211422
Alan Galetornadic14213.0/20 = 15.00%14161427
Daniil Frolovflowermann14173.0/16 = 18.75%14011433
Matthew La Valleesherman10114166.0/23 = 26.09%13951437
Jeremy Hook10011014162.0/30 = 6.67%14031429
Arthur Yvrardtorendil14160.0/7 = 0.00%14111421
yellowturtleyellowturtle14100.0/10 = 0.00%14111408
George Dukegwduke140842.5/117 = 36.32%13591457
John Davischappy14083.0/17 = 17.65%14071409
Evan Jorgensonejorgens14060.0/7 = 0.00%13951417
darren paullramalam139112.5/98 = 12.76%13571426
Bogot Bogotolbog137712.0/44 = 27.27%13711383
Jarid Carlsonsacredchao137112.0/62 = 19.35%13301413
Сергей Маэстроfantomas13390.0/30 = 0.00%13481329
Oisín D.sxg132837.5/156 = 24.04%13111345
Diogen Abramelindanko13280.0/29 = 0.00%13341321
per hommerbergper3113012.0/46 = 4.35%12911311
Сергей Бугаевскийbugaevsky12823.0/56 = 5.36%12761288
wdtr2wdtr2125514.5/119 = 12.18%11851325

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