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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.

Game Filter: Log Filter: Group Filter:
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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%69.28%67.73%
NameUseridGCRPercent wonGCR1GCR2
Hexa Sakkbosa601856136.5/151 = 90.40%18241887
Francis Fahystamandua1845247.0/298 = 82.89%18281861
dax00dax001803131.0/137 = 95.62%17861819
Kevin Paceypanther1784414.0/509 = 81.34%17921775
Carlos Cetinasissa1729588.5/925 = 63.62%17181740
Cameron Milesshatteredglass171015.0/17 = 88.24%17001720
Jochen Muellerleopold_stotch169555.0/92 = 59.78%16811710
H Spetyura168113.0/13 = 100.00%16761686
Gary Giffordpenswift167160.5/85 = 71.18%15711771
Play Testerplaytester166918.5/25 = 74.00%16731665
Fergus Dunihofergus166359.5/97 = 61.34%16631663
Jose Carrilloj_carrillo_vii165585.5/151 = 56.62%16681642
David Paulowichdavid_64162111.0/13 = 84.62%16271615
shift2shiftshift2shift161611.0/19 = 57.89%16271606
Charles Danielfrozen_methane161535.0/64 = 54.69%15851644
Tim O'Lenatim_olena16146.5/8 = 81.25%16171611
Vitya Makovmakov16137.5/8 = 93.75%16081619
Homo Simiaalienum16117.0/8 = 87.50%16001622
Andreas Kaufmannandreas16077.0/7 = 100.00%16091605
Vitya Makovmakov3331594296.0/681 = 43.47%15401648
ctzctz158012.0/17 = 70.59%15561603
kokoszkokosz15787.0/8 = 87.50%15651590
Abdul-Rahman Sibahisibahi157516.0/23 = 69.57%15671583
Pericles Tesone de Souzaperitezz15756.0/6 = 100.00%15751575
attack hippoattackhippo15745.5/7 = 78.57%15691579
erikerik1573129.5/231 = 56.06%16001547
je jujejujeju157336.5/60 = 60.83%15651582
Alexander Trotterqilin15694.0/4 = 100.00%15671571
Stephen Stockmanstevestockman156910.0/16 = 62.50%15751562
Jenard Cabilaomgawalangmagawa156711.0/23 = 47.83%15821552
TH6notath615647.0/12 = 58.33%15611567
Greg Strongmageofmaple156189.0/184 = 48.37%16221501
Thor Slavenskyslavensky15615.0/7 = 71.43%15371584
Raymond Dlewel156013.0/22 = 59.09%15771543
Isaac Felpsattacker14415585.0/6 = 83.33%15591557
John Gallantbigjohn155616.0/28 = 57.14%15511561
Nicola Caridiniccar15543.0/3 = 100.00%15571550
Nicholas Wolffnwolff15549.0/15 = 60.00%15721535
Roberto Lavierirlavieri200315503.0/3 = 100.00%15451555
S Ssim15436.0/9 = 66.67%15311554
carlos carloscarlos154216.0/27 = 59.26%15171567
pallab basupallab154131.0/60 = 51.67%15281553
Tom e4ktome4k15362.0/2 = 100.00%15351536
Eric Greenwoodcavalier15344.0/6 = 66.67%15421526
Todd Witterstoddw15342.0/2 = 100.00%15321535
Neil Spargospargo15333.0/4 = 75.00%15261540
Matthew Montchalinmatthew_montchal15313.0/4 = 75.00%15291533
Jake Palladinocerebralassassin15312.0/2 = 100.00%15281534
Julien Coll Moratfacteurix15302.0/3 = 66.67%15291531
Fred Koktangram15282.0/3 = 66.67%15281529
joe rosenbloombootzilla15282.0/3 = 66.67%15241531
Joseph DiMurotrojh15281.0/1 = 100.00%15331523
Uwe Kreuzercaissus15272.0/2 = 100.00%15251529
Nicholas Wolffmaeko152565.5/142 = 46.13%15491502
Yeinzon Rodríguez Garcíayeinzon15241.0/1 = 100.00%15281519
Adrian Alvarez de la Campaadrian15233.5/6 = 58.33%15241523
Chuck Leegyw6t152317.5/39 = 44.87%15161529
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%15181519
Richard Titlertitle15181.0/1 = 100.00%15191518
Angel47 Usmanangel4715181.0/1 = 100.00%15181518
David Levinsmidrael15181.0/1 = 100.00%15181518
jj15181.0/1 = 100.00%15181518
Trevor Savagesavage15181.0/1 = 100.00%15181518
calebblazecalebblaze15181.0/1 = 100.00%15181518
eunchong leeeunchong15181.0/1 = 100.00%15181518
yas kumkumagai15181.0/1 = 100.00%15181518
whitenerdy53whitenerdy5315181.0/1 = 100.00%15181518
Antonio Bruzzitotonno_janggi15181.0/1 = 100.00%15181518
Jan Żmudajanzmuda15171.0/1 = 100.00%15181517
Garrett Smithgmsmith15171.0/2 = 50.00%15241510
Titus Ledbettertbl215171.0/1 = 100.00%15181517
Joe Joycejoejoyce151720.5/57 = 35.96%14761558
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%15131519
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
Georg Spengleravunjahei15129.0/28 = 32.14%15021521
xxmanxxman15111.0/2 = 50.00%15181504
Antoine Fourrièreantoinefourriere15101.5/2 = 75.00%15061515
spiptorben15101.0/2 = 50.00%15111509
mystery playercentipede15092.0/5 = 40.00%15121506
Anthony Viensstarkiller15082.0/4 = 50.00%15001516
Nathanlokor15081.0/2 = 50.00%15111504
xeongreyxeongrey15088.0/17 = 47.06%15141501
pheko Motaungcouriermabovini150635.5/70 = 50.71%15581455
Zachary Wadeazost1215053.0/5 = 60.00%14981513
As Bardhiasbardhi15041.0/2 = 50.00%15071501
Gee Beegdimension15031.0/2 = 50.00%15031502
Christine Bagley-Joneszcherryz15030.5/1 = 50.00%15061500
Colin Adamslionhawk15021.0/2 = 50.00%15051500
Albert Vámosiblackrider_4815021.0/4 = 25.00%15151488
Graeme Neathamgrayhawke15011.0/2 = 50.00%15011502
Hans Henrikssonhasurami15012.0/4 = 50.00%14911512
Tom Trenchtomdench9515010.5/1 = 50.00%15031500
Kent Weschlerperplexedibex15001.0/3 = 33.33%14971504
Colin Weaveruselessgit15001.0/4 = 25.00%14981502
Thom Dimentunwiseowl14982.0/5 = 40.00%14991497
noy noynoy14983.0/7 = 42.86%14881508
Juan Pablo Schweitzer Kirsingerdefender14971.0/2 = 50.00%14941500
Eni Lienili149511.5/46 = 25.00%15101480
Max Fengwowimbob111214941.0/3 = 33.33%14971492
John Smithultimatecoolster14943.0/9 = 33.33%14941494
wyatt wyattquimssarcasm14920.0/1 = 0.00%14961488
Hsa Saidh14920.0/1 = 0.00%14961488
jesus babyboypokechamp14920.0/1 = 0.00%14961487
kunkunkunkun14910.0/1 = 0.00%14961487
Hugo Mendes-Nuneshugo199514910.0/1 = 0.00%14961486
Anders Gustafsonancog14910.0/1 = 0.00%14961485
Bob Brownbobhihih14910.0/1 = 0.00%14951486
Fabner Cruz Gracilianofabner14900.0/1 = 0.00%14961485
don anezdonanez14900.0/1 = 0.00%14961484
Michael Christensenjustsojazz14900.0/1 = 0.00%14961484
hubergerdhubergerd14890.0/1 = 0.00%14961483
Éric Manálangedubble1914890.0/1 = 0.00%14941485
Steve Polleychessfan5914890.0/1 = 0.00%14941484
DFA Productions70nyd014890.0/1 = 0.00%14961482
makomako14890.0/1 = 0.00%14961482
Jason Stehlyjasonstehly14890.0/1 = 0.00%14941484
vikvik14890.0/1 = 0.00%14961481
Hafsteinn Kjartanssonhnr0114890.0/1 = 0.00%14961481
loveokenloveoken14890.0/1 = 0.00%14941483
Matias I.tsatziq14880.0/1 = 0.00%14941483
xerisianxxerisianx14880.0/1 = 0.00%14941482
John Badgerjbadger14880.0/1 = 0.00%14941482
potato imaginatorpotato14880.0/1 = 0.00%14941481
ugo judeugojude14880.0/1 = 0.00%14941481
LuigiMaster285qqzlbpdilchr14870.0/1 = 0.00%14911483
DJ Linickdjlinick14870.0/1 = 0.00%14911482
Ivan Velascoswordandsilver14870.0/1 = 0.00%14911482
Rob Brownsteelhead14860.0/1 = 0.00%14911481
Aurelian Floreacatugo1486235.5/637 = 36.97%15771395
Daniel Zachariasarx148621.0/52 = 40.38%14481524
Bradlee Kingstonbrad1914850.0/1 = 0.00%14891482
Luis Menendezpleyades2114850.0/1 = 0.00%14881483
Mike Smolowitzmjs170114850.0/1 = 0.00%14891481
Brock Sampsonthe_iron_kenyan14850.0/1 = 0.00%14881482
Gus Dunihoduniho14850.0/1 = 0.00%14871483
Erlang Shenerlangshen14850.0/1 = 0.00%14891481
Andy Thomasandy_thomas14850.0/1 = 0.00%14881482
Travis Comptonironlance14850.0/1 = 0.00%14891481
Nasmichael Farrismichaeljay14850.0/1 = 0.00%14881481
Derek Mooseelevatorfarter14841.0/3 = 33.33%14841484
James Sprattwhittlin14840.0/1 = 0.00%14871481
Turk Osterburgtalen3141593141514840.0/1 = 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
Solomon Salamasol71014830.0/1 = 0.00%14841483
Alexandr Kremenakremen14830.0/1 = 0.00%14851481
Julianredpanda148317.0/35 = 48.57%14641502
Antony Vailevichjabberw0cky114830.0/1 = 0.00%14841482
manolo manolomanolo14830.0/1 = 0.00%14851481
scythian blunderq1234514830.0/2 = 0.00%14871478
Dan Kellydankelly14830.0/1 = 0.00%14841481
btstwbtstw14830.0/1 = 0.00%14821483
Roberto Cassanotamerlano14830.0/1 = 0.00%14831482
MichaÅ‚ Jarskihookz14830.0/1 = 0.00%14831482
Andreas Bunkahlebunkahle14820.0/1 = 0.00%14841481
Hung Daobyteboy14820.0/1 = 0.00%14841481
Jose Canceljoche14820.0/1 = 0.00%14841481
Tony Quintanillatony_quintanilla14820.0/1 = 0.00%14841480
sixtysixty14820.0/3 = 0.00%14881477
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
anna colladoapatura_iris14820.0/1 = 0.00%14811482
Minh Dangminhdang14820.0/1 = 0.00%14811482
Thomas Meehanorangeaurochs14820.0/1 = 0.00%14811482
Joseph Grangercdafan14820.0/1 = 0.00%14801483
luigi mattagigino4214820.0/1 = 0.00%14821481
Виктор Байгужаковbajvik14820.0/1 = 0.00%14811482
Robin Sneijderrobinwooter214820.0/1 = 0.00%14821481
ben chewben558214810.0/1 = 0.00%14811481
paulblazepaulblaze14810.0/1 = 0.00%14811481
Harry Gaoharrygao14810.0/1 = 0.00%14811481
14810.0/1 = 0.00%14811481
wonsang leewonsang14810.0/1 = 0.00%14811481
Babo Jeffbabojeff14810.0/1 = 0.00%14811481
y kumyasuhiro14810.0/1 = 0.00%14811481
Ryan Schwartzshunoshi14810.0/1 = 0.00%14811481
Vitali Maslanskivitali_1014810.0/1 = 0.00%14811481
Jun Ocampojunpogi14810.0/2 = 0.00%14881474
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%14761486
Nicholas Archerchess_hunter14810.0/2 = 0.00%14871475
qidb602qidb60214810.0/2 = 0.00%14841477
arcasorarcasor14800.0/1 = 0.00%14791481
Francesco Casalinofrancesco14800.0/2 = 0.00%14851475
László Gadosdani198314801.0/4 = 25.00%14761483
Diego M.diego14800.0/3 = 0.00%14841476
rederikrederik14800.0/1 = 0.00%14791480
legendlegend14790.0/2 = 0.00%14881471
Bn Emnelk11414790.0/2 = 0.00%14851473
voicantvoicant14790.0/1 = 0.00%14771480
Boyko Ahtarovzdra4147810.0/23 = 43.48%14791477
Ivan Kosintsevbombino14780.0/1 = 0.00%14741481
ologyology14780.0/1 = 0.00%14741481
championchampion14780.0/2 = 0.00%14861469
wdtrwdtr14770.0/3 = 0.00%14771476
Alexander Krutikovlonewolf14761.0/4 = 25.00%14721479
Ivan Ivankillbill22514760.0/1 = 0.00%14701481
Frank Istvánistvan6014760.0/2 = 0.00%14861466
andres fuentesxabyer14760.0/2 = 0.00%14791472
trtztrtz gfghtrtztrtz14750.0/2 = 0.00%14781473
Szling Ozecszling_ozec14740.0/3 = 0.00%14761472
tedy efwttei27fmrw7de14740.0/1 = 0.00%14671481
Pablo Denegrideep_thinker14740.0/2 = 0.00%14741473
Charles Gilmancharles_gilman14730.0/2 = 0.00%14761471
Lennon Figueiredogiwseppe14731.0/4 = 25.00%14711476
Kacper Rutkowskikacperrutkowski14710.0/2 = 0.00%14751467
John Twycrossjt14710.0/2 = 0.00%14761466
dfe6631dfe663114710.0/2 = 0.00%14671474
andrewthepawnandrewthepawn14700.0/2 = 0.00%14691472
Armin Liebhartlunaris147019.0/44 = 43.18%14881452
Pat Quexionezsuperpatzermaste14700.0/4 = 0.00%14701469
Travis Comptonblackrood14700.0/2 = 0.00%14671473
Zoli M Zoltánbaltazarprof14690.0/5 = 0.00%14821457
Sergey Biryukovsbiryukov14690.0/4 = 0.00%14721466
Steve Hsteve_201014690.0/2 = 0.00%14641473
Daniel MacDuffdanielmacduff14680.0/3 = 0.00%14681467
cherokee malansailorhertzog14670.0/2 = 0.00%14711464
Memedes Lulagiwseppe314670.0/2 = 0.00%14691466
Adam DeWittchessshogi14670.0/3 = 0.00%14731461
Zac Sparxkrinid14670.0/2 = 0.00%14691465
jeremy diniericharles_bukowski14660.0/2 = 0.00%14671466
A tomiatomi14664.5/16 = 28.12%14611471
Donut Donutdonutdonut14650.0/2 = 0.00%14661465
iuchi45iuchi4514650.0/2 = 0.00%14631466
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%14511467
louisvlouisv14550.0/3 = 0.00%14581453
Graemegraemecn14540.0/3 = 0.00%14511457
Andy Lewickiondraszek14520.0/3 = 0.00%14471457
Dayrom Gilallahukbar14520.0/3 = 0.00%14501453
John Langleyjonners14520.5/4 = 12.50%14521451
Николай Сокольскийalexich14500.0/4 = 0.00%14531447
Michael Schmahlmschmahl14495.0/15 = 33.33%14561443
Linn Russellfreakat14490.0/3 = 0.00%14491449
Adalbertus Kchewoj14481.0/5 = 20.00%14431454
boukineboukine14484.0/11 = 36.36%14321465
Aaron Maynardvopi14461.0/6 = 16.67%14411451
Scott McGrealagentofchaos14467.0/19 = 36.84%14471445
vitaliy ravitztalsterch14442.0/15 = 13.33%14361452
heche60heche6014422.0/12 = 16.67%14411442
Nick Wolffwolff144125.0/71 = 35.21%14111470
Sagi Gabaysagig7214390.5/16 = 3.12%14181460
dmitarzvonimirdmitarzvonimir14380.0/5 = 0.00%14321444
Jeremy Goodjudgmentality143843.5/127 = 34.25%14271448
Joshua Tsamraku14374.5/12 = 37.50%14131462
Evan Jorgensonsabataegalo14370.0/7 = 0.00%14231451
Evert Jan Karmanevertvb14332.5/11 = 22.73%14201446
Phoenix TKartkr10101014332.0/9 = 22.22%14341431
Jon Dannjon_dann14300.0/4 = 0.00%14271433
juan rodriguezrodriguez142911.5/38 = 30.26%14421417
Samuel de Souzasamsou14250.0/6 = 0.00%14251425
Jack Zavierubersketch14240.0/6 = 0.00%14191428
Alan Galetornadic14213.0/20 = 15.00%14161427
Daniil Frolovflowermann14183.0/16 = 18.75%14051431
Arthur Yvrardtorendil14160.0/7 = 0.00%14111421
Matthew La Valleesherman10114156.0/23 = 26.09%13971434
Jeremy Hook10011014132.0/30 = 6.67%14111415
yellowturtleyellowturtle14100.0/10 = 0.00%14111408
John Davischappy14073.0/17 = 17.65%14071408
Evan Jorgensonejorgens14070.0/7 = 0.00%13951418
George Dukegwduke140742.5/117 = 36.32%13571456
darren paullramalam139413.5/100 = 13.50%13581430
Bogot Bogotolbog137512.0/44 = 27.27%13681382
Jarid Carlsonsacredchao137312.0/62 = 19.35%13281417
Сергей Маэстроfantomas13400.0/30 = 0.00%13561323
Diogen Abramelindanko13270.0/35 = 0.00%13151340
Oisín D.sxg132640.5/168 = 24.11%13021350
per hommerbergper3113002.0/47 = 4.26%12941307
Сергей Бугаевскийbugaevsky12843.0/56 = 5.36%12741294
wdtr2wdtr2127316.5/128 = 12.89%12131333

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