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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:68.60%69.19%67.13%
NameUseridGCRPercent wonGCR1GCR2
Hexa Sakkbosa601849136.5/151 = 90.40%18181880
Francis Fahystamandua1841228.0/277 = 82.31%18271855
dax00dax001800117.0/123 = 95.12%17921807
Kevin Paceypanther1782357.0/436 = 81.88%17851779
Carlos Cetinasissa1724537.5/858 = 62.65%17151734
Cameron Milesshatteredglass170315.0/17 = 88.24%16961711
Jochen Muellerleopold_stotch169455.0/92 = 59.78%16831704
H Spetyura167413.0/13 = 100.00%16671681
Gary Giffordpenswift167360.5/85 = 71.18%15721774
Fergus Dunihofergus166659.5/97 = 61.34%16651666
Play Testerplaytester166518.5/25 = 74.00%16611668
Jose Carrilloj_carrillo_vii165885.5/151 = 56.62%16621655
David Paulowichdavid_64162011.0/13 = 84.62%16211620
shift2shiftshift2shift161911.0/19 = 57.89%16231614
Charles Danielfrozen_methane161435.0/64 = 54.69%15861641
Homo Simiaalienum16137.0/8 = 87.50%16021624
Vitya Makovmakov16127.5/8 = 93.75%16111613
Tim O'Lenatim_olena16126.5/8 = 81.25%16161608
Andreas Kaufmannandreas16077.0/7 = 100.00%16091605
Vitya Makovmakov3331582271.0/646 = 41.95%15311632
ctzctz158112.0/17 = 70.59%15571604
erikerik1579129.5/231 = 56.06%16101548
kokoszkokosz15787.0/8 = 87.50%15621595
Abdul-Rahman Sibahisibahi157416.0/23 = 69.57%15631584
attack hippoattackhippo15725.5/7 = 78.57%15651579
je jujejujeju157236.5/60 = 60.83%15631581
Alexander Trotterqilin15684.0/4 = 100.00%15651572
Stephen Stockmanstevestockman156510.0/16 = 62.50%15701560
Jenard Cabilaomgawalangmagawa156411.0/23 = 47.83%15731555
TH6notath615637.0/12 = 58.33%15591567
Greg Strongmageofmaple156282.0/170 = 48.24%16251498
Raymond Dlewel155913.0/22 = 59.09%15751543
Isaac Felpsattacker14415585.0/6 = 83.33%15591557
pallab basupallab155429.0/48 = 60.42%15481561
Nicola Caridiniccar15543.0/3 = 100.00%15571550
Nicholas Wolffnwolff15509.0/15 = 60.00%15731527
Roberto Lavierirlavieri200315493.0/3 = 100.00%15441555
John Gallantbigjohn154414.0/25 = 56.00%15371551
S Ssim15436.0/9 = 66.67%15311554
carlos carloscarlos153816.0/27 = 59.26%15131563
Tom e4ktome4k15362.0/2 = 100.00%15361536
Eric Greenwoodcavalier15344.0/6 = 66.67%15421526
Todd Witterstoddw15342.0/2 = 100.00%15321535
Neil Spargospargo15313.0/4 = 75.00%15231540
Matthew Montchalinmatthew_montchal15313.0/4 = 75.00%15291533
Jake Palladinocerebralassassin15312.0/2 = 100.00%15291532
Julien Coll Moratfacteurix15302.0/3 = 66.67%15251534
Joseph DiMurotrojh15291.0/1 = 100.00%15321525
Fred Koktangram15282.0/3 = 66.67%15291526
joe rosenbloombootzilla15272.0/3 = 66.67%15251530
Uwe Kreuzercaissus15272.0/2 = 100.00%15241531
Nicholas Wolffmaeko152765.5/142 = 46.13%15461507
Adrian Alvarez de la Campaadrian15243.5/6 = 58.33%15231524
Yeinzon Rodríguez Garcíayeinzon15231.0/1 = 100.00%15281519
Chuck Leegyw6t152117.5/39 = 44.87%15061536
von raidervonraider15201.0/1 = 100.00%15211519
Larry Wheelerbrainburner15191.0/1 = 100.00%15201519
michirmichir15191.0/1 = 100.00%15191519
dicepawndicepawn15191.0/1 = 100.00%15201518
Todor Tchervenkovtchervenkov15181.0/1 = 100.00%15171519
Garrett Smithgmsmith15181.0/2 = 50.00%15231513
Richard Titlertitle15181.0/1 = 100.00%15181518
calebblazecalebblaze15181.0/1 = 100.00%15181518
Trevor Savagesavage15181.0/1 = 100.00%15181518
Angel47 Usmanangel4715181.0/1 = 100.00%15181518
jj15181.0/1 = 100.00%15181518
whitenerdy53whitenerdy5315181.0/1 = 100.00%15181518
David Levinsmidrael15181.0/1 = 100.00%15181518
Antonio Bruzzitotonno_janggi15181.0/1 = 100.00%15181518
eunchong leeeunchong15181.0/1 = 100.00%15181518
yas kumkumagai15181.0/1 = 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%15161518
Georges-Clounet Jesuispartoutgeorgesclounet15161.0/1 = 100.00%15141518
Antonio Barratotonno15161.0/1 = 100.00%15141517
Aaron Smithzirtoc15152.5/5 = 50.00%15111520
pink sockpickett_aaron15152.0/3 = 66.67%15151515
Simon Langley-Evansslangers15151.5/2 = 75.00%15131516
Joe Joycejoejoyce151420.5/57 = 35.96%14751554
xxmanxxman15121.0/2 = 50.00%15171508
Anthony Viensstarkiller15112.0/4 = 50.00%15071514
Antoine Fourrièreantoinefourriere15101.5/2 = 75.00%15071512
mystery playercentipede15082.0/5 = 40.00%15091508
Nathanlokor15081.0/2 = 50.00%15091507
Aurelian Floreacatugo1507225.5/571 = 39.49%16131400
Zachary Wadeazost1215063.0/5 = 60.00%14991513
pheko Motaungcouriermabovini150535.5/70 = 50.71%15591451
xeongreyxeongrey15058.0/17 = 47.06%15151496
As Bardhiasbardhi15051.0/2 = 50.00%15081501
Georg Spengleravunjahei15049.0/28 = 32.14%14911517
Tom Trenchtomdench9515030.5/1 = 50.00%15041501
Gee Beegdimension15021.0/2 = 50.00%15041501
Christine Bagley-Joneszcherryz15020.5/1 = 50.00%15051500
Colin Adamslionhawk15021.0/2 = 50.00%15051500
noy noynoy15023.0/7 = 42.86%14911513
Hans Henrikssonhasurami15012.0/4 = 50.00%14901512
Albert Vámosiblackrider_4815011.0/4 = 25.00%15141488
Graeme Neathamgrayhawke15011.0/2 = 50.00%15001502
Kent Weschlerperplexedibex14991.0/3 = 33.33%14961502
Colin Weaveruselessgit14981.0/4 = 25.00%14971498
Thom Dimentunwiseowl14982.0/5 = 40.00%15001495
Juan Pablo Schweitzer Kirsingerdefender14971.0/2 = 50.00%14961499
Max Fengwowimbob111214941.0/3 = 33.33%14971492
John Smithultimatecoolster14923.0/9 = 33.33%14911494
Hsa Saidh14920.0/1 = 0.00%14951489
vikvik14910.0/1 = 0.00%14951488
Michael Christensenjustsojazz14910.0/1 = 0.00%14951488
don anezdonanez14910.0/1 = 0.00%14951487
Eni Lienili149111.5/46 = 25.00%15021479
Bob Brownbobhihih14910.0/1 = 0.00%14951486
hubergerdhubergerd14910.0/1 = 0.00%14951486
wyatt wyattquimssarcasm14900.0/1 = 0.00%14951485
Hugo Mendes-Nuneshugo199514900.0/1 = 0.00%14961484
Fabner Cruz Gracilianofabner14900.0/1 = 0.00%14961484
kunkunkunkun14890.0/1 = 0.00%14961483
xerisianxxerisianx14890.0/1 = 0.00%14931485
Daniel Zachariasarx148913.0/31 = 41.94%14841494
jesus babyboypokechamp14890.0/1 = 0.00%14961482
Jason Stehlyjasonstehly14890.0/1 = 0.00%14931484
Hafsteinn Kjartanssonhnr0114890.0/1 = 0.00%14951482
DFA Productions70nyd014890.0/1 = 0.00%14961481
loveokenloveoken14890.0/1 = 0.00%14941484
makomako14880.0/1 = 0.00%14961481
Steve Polleychessfan5914880.0/1 = 0.00%14941483
ugo judeugojude14880.0/1 = 0.00%14941482
Éric Manálangedubble1914880.0/1 = 0.00%14941482
John Badgerjbadger14880.0/1 = 0.00%14941481
spiptorben14880.0/1 = 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
Gus Dunihoduniho14850.0/1 = 0.00%14871483
Luis Menendezpleyades2114850.0/1 = 0.00%14871483
Nasmichael Farrismichaeljay14850.0/1 = 0.00%14881482
Brock Sampsonthe_iron_kenyan14850.0/1 = 0.00%14881482
Andy Thomasandy_thomas14850.0/1 = 0.00%14881481
Travis Comptonironlance14850.0/1 = 0.00%14881481
Erlang Shenerlangshen14850.0/1 = 0.00%14881481
Derek Mooseelevatorfarter14841.0/3 = 33.33%14841484
Antony Vailevichjabberw0cky114840.0/1 = 0.00%14861482
Talen Storlatalen3141593141514840.0/1 = 0.00%14871481
James Sprattwhittlin14840.0/1 = 0.00%14861481
manolo manolomanolo14840.0/1 = 0.00%14861481
Alexandr Kremenakremen14840.0/1 = 0.00%14861481
Jeremy Goodyamorezu14840.0/1 = 0.00%14851482
andy lewickiherlocksholmes14840.0/1 = 0.00%14861481
yi fang liuliuyifang14830.0/1 = 0.00%14861481
trtztrtz gfghtrtztrtz14830.0/1 = 0.00%14851481
Dan Kellydankelly14830.0/1 = 0.00%14841481
Jose Canceljoche14830.0/1 = 0.00%14821483
btstwbtstw14820.0/1 = 0.00%14831482
Andreas Bunkahlebunkahle14820.0/1 = 0.00%14831482
MichaÅ‚ Jarskihookz14820.0/1 = 0.00%14841481
Hung Daobyteboy14820.0/1 = 0.00%14841481
Roberto Cassanotamerlano14820.0/1 = 0.00%14841481
Tony Quintanillatony_quintanilla14820.0/1 = 0.00%14831481
Thomas Meehanorangeaurochs14820.0/1 = 0.00%14811483
luigi mattagigino4214820.0/1 = 0.00%14821482
cdpowercdpower14820.0/1 = 0.00%14831481
Joseph Grangercdafan14820.0/1 = 0.00%14831481
Ronald Brierleybenwb14820.0/1 = 0.00%14821481
anna colladoapatura_iris14820.0/1 = 0.00%14811482
Minh Dangminhdang14820.0/1 = 0.00%14811482
Paolo Porsiapillau14820.0/1 = 0.00%14831480
Виктор Байгужаковbajvik14820.0/1 = 0.00%14821481
Robin Sneijderrobinwooter214820.0/1 = 0.00%14811482
scythian blunderq1234514820.0/2 = 0.00%14871476
Mark Thompsonmarkthompson14810.0/2 = 0.00%14911472
Ryan Schwartzshunoshi14810.0/1 = 0.00%14811481
Babo Jeffbabojeff14810.0/1 = 0.00%14811481
paulblazepaulblaze14810.0/1 = 0.00%14811481
y kumyasuhiro14810.0/1 = 0.00%14811481
14810.0/1 = 0.00%14811481
wonsang leewonsang14810.0/1 = 0.00%14811481
ben chewben558214810.0/1 = 0.00%14811481
Harry Gaoharrygao14810.0/1 = 0.00%14811481
Vitali Maslanskivitali_1014810.0/1 = 0.00%14811481
Nicholas Archerchess_hunter14810.0/2 = 0.00%14871475
blundermanblunderman14810.0/1 = 0.00%14811481
Abe Anonapostateabe14810.0/1 = 0.00%14801482
Julianredpanda148117.0/35 = 48.57%14611501
Jun Ocampojunpogi14810.0/2 = 0.00%14871474
sixtysixty14810.0/3 = 0.00%14871474
Uri Bruckbruck14800.0/2 = 0.00%14921469
Giuseppe Acciarocoopwie14802.0/5 = 40.00%14731487
arcasorarcasor14800.0/1 = 0.00%14791481
Francesco Casalinofrancesco14800.0/2 = 0.00%14821478
rederikrederik14800.0/1 = 0.00%14791480
László Gadosdani198314791.0/4 = 25.00%14721487
Bn Emnelk11414790.0/2 = 0.00%14831476
legendlegend14790.0/2 = 0.00%14891469
Diego M.diego14780.0/3 = 0.00%14831474
voicantvoicant14780.0/1 = 0.00%14771480
championchampion14780.0/2 = 0.00%14841472
qidb602qidb60214780.0/2 = 0.00%14831473
ologyology14780.0/1 = 0.00%14741481
Ivan Kosintsevbombino14780.0/1 = 0.00%14741481
Frank Istvánistvan6014760.0/2 = 0.00%14841468
Alexander Krutikovlonewolf14761.0/4 = 25.00%14721479
Ivan Ivankillbill22514760.0/1 = 0.00%14701481
andres fuentesxabyer14750.0/2 = 0.00%14781471
wdtrwdtr14740.0/3 = 0.00%14771471
Charles Gilmancharles_gilman14730.0/2 = 0.00%14741473
Lennon Figueiredogiwseppe14731.0/4 = 25.00%14711476
Szling Ozecszling_ozec14730.0/3 = 0.00%14751471
Pablo Denegrideep_thinker14730.0/2 = 0.00%14761471
dfe6631dfe663114720.0/2 = 0.00%14711473
andrewthepawnandrewthepawn14710.0/2 = 0.00%14731469
John Twycrossjt14700.0/2 = 0.00%14751466
Kacper Rutkowskikacperrutkowski14700.0/2 = 0.00%14731467
Travis Comptonblackrood14690.0/2 = 0.00%14651474
Zoli M Zoltánbaltazarprof14680.0/5 = 0.00%14801457
Armin Liebhartlunaris146819.0/43 = 44.19%14851452
Boyko Ahtarovzdra4146810.0/23 = 43.48%14641473
Sergey Biryukovsbiryukov14680.0/4 = 0.00%14691467
Steve Hsteve_201014680.0/2 = 0.00%14651470
Memedes Lulagiwseppe314670.0/2 = 0.00%14691466
Daniel MacDuffdanielmacduff14670.0/3 = 0.00%14661468
Pat Quexionezsuperpatzermaste14670.0/4 = 0.00%14711463
cherokee malansailorhertzog14670.0/2 = 0.00%14701464
vitaliy ravitztalsterch14670.0/5 = 0.00%14651469
Zac Sparxkrinid14670.0/2 = 0.00%14691465
jeremy diniericharles_bukowski14660.0/2 = 0.00%14651468
iuchi45iuchi4514660.0/2 = 0.00%14661467
Adam DeWittchessshogi14660.0/3 = 0.00%14731459
Donut Donutdonutdonut14650.0/2 = 0.00%14661465
playshogiplayshogi14640.0/2 = 0.00%14661463
Michael Nelsonmikenels14640.0/2 = 0.00%14611466
andy lewickietaoni14630.0/2 = 0.00%14631463
A tomiatomi14634.5/16 = 28.12%14531474
Namik Zadenamik14630.0/2 = 0.00%14611465
Scott Crawfordmathemagician14630.0/7 = 0.00%14701455
michael collinsverderben14621.0/5 = 20.00%14661457
Michael Huntkronsteen3314620.0/3 = 0.00%14571466
louisvlouisv14550.0/3 = 0.00%14571453
Graemegraemecn14540.0/3 = 0.00%14491458
Andy Lewickiondraszek14520.0/3 = 0.00%14441461
John Langleyjonners14520.5/4 = 12.50%14521451
Dayrom Gilallahukbar14510.0/3 = 0.00%14511452
Николай Сокольскийalexich14500.0/4 = 0.00%14541447
boukineboukine14494.0/11 = 36.36%14291468
Adalbertus Kchewoj14491.0/5 = 20.00%14441454
Michael Schmahlmschmahl14495.0/15 = 33.33%14531445
Linn Russellfreakat14490.0/3 = 0.00%14491449
Nick Wolffwolff144625.0/71 = 35.21%14161475
Aaron Maynardvopi14451.0/6 = 16.67%14391452
Scott McGrealagentofchaos14457.0/19 = 36.84%14441446
Evert Jan Karmanevertvb14392.5/11 = 22.73%14251454
heche60heche6014392.0/12 = 16.67%14371442
dmitarzvonimirdmitarzvonimir14390.0/5 = 0.00%14341444
Evan Jorgensonsabataegalo14390.0/7 = 0.00%14281450
Joshua Tsamraku14384.5/12 = 37.50%14131462
Sagi Gabaysagig7214350.5/16 = 3.12%14161453
Phoenix TKartkr10101014322.0/9 = 22.22%14331431
Jeremy Goodjudgmentality143243.5/127 = 34.25%14241440
Jon Dannjon_dann14300.0/4 = 0.00%14271433
juan rodriguezrodriguez142811.5/38 = 30.26%14401416
Jack Zavierubersketch14260.0/6 = 0.00%14241428
Alan Galetornadic14183.0/20 = 15.00%14101427
Arthur Yvrardtorendil14160.0/7 = 0.00%14111421
Matthew La Valleesherman10114146.0/23 = 26.09%13951433
Daniil Frolovflowermann14143.0/16 = 18.75%13991429
John Davischappy14123.0/17 = 17.65%14021423
yellowturtleyellowturtle14080.0/10 = 0.00%14091408
Jeremy Hook10011014072.0/30 = 6.67%13921421
Evan Jorgensonejorgens14060.0/7 = 0.00%13931418
George Dukegwduke140442.5/117 = 36.32%13561452
darren paullramalam139012.5/93 = 13.44%13621417
Diogen Abramelindanko13790.0/18 = 0.00%13911368
Jarid Carlsonsacredchao137412.0/61 = 19.67%13341413
Bogot Bogotolbog136912.0/44 = 27.27%13631375
Сергей Маэстроfantomas13470.0/28 = 0.00%13651328
sxgsxg134531.5/139 = 22.66%13131376
per hommerbergper3113182.0/43 = 4.65%13051331
wdtr2wdtr2128314.5/109 = 13.30%12211345
Сергей Бугаевскийbugaevsky12823.0/56 = 5.36%12751289

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