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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'

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:70.52%69.81%70.58%
NameUseridGCRPercent wonGCR1GCR2
Play Testerplaytester1855290.5/330 = 88.03%18131896
Hexa Sakkbosa601854136.5/151 = 90.40%18271881
Francis Fahystamandua1822247.0/300 = 82.33%18271817
dax00dax001817161.0/167 = 96.41%18271806
Homo Simiaalienum180179.0/99 = 79.80%17811820
Kevin Paceypanther1780623.0/888 = 70.16%17841775
Carlos Cetinasissa1757788.5/1158 = 68.09%17301785
Cameron Milesshatteredglass172015.0/17 = 88.24%17181721
Yaotl Kolotikyolokayotl171643.0/49 = 87.76%16791754
Jochen Muellerleopold_stotch169955.0/92 = 59.78%16831715
H Spetyura169813.0/13 = 100.00%16891707
Fergus Dunihofergus166865.5/103 = 63.59%16701665
Vitya Makovmakov3331664546.0/1098 = 49.73%16451682
Jose Carrilloj_carrillo_vii166188.5/155 = 57.10%16641658
Gary Giffordpenswift165552.5/77 = 68.18%15731737
Tim O'Lenatim_olena163518.5/31 = 59.68%16411630
CSS Dixielandcssdixieland163018.0/25 = 72.00%16061653
David Paulowichdavid_64162812.0/15 = 80.00%16251630
shift2shiftshift2shift161811.0/19 = 57.89%16091628
Stephen Williamsneph161411.0/12 = 91.67%15691659
Vitya Makovmakov16127.5/8 = 93.75%16101614
Charles Danielfrozen_methane161135.0/64 = 54.69%15701651
Andreas Kaufmannandreas16077.0/7 = 100.00%16091605
Erik Lerougeerik1600141.5/262 = 54.01%16681532
Pericles Tesone de Souzaperitezz15888.0/8 = 100.00%15881588
ctzctz157812.0/17 = 70.59%15511605
attack hippoattackhippo15785.5/7 = 78.57%15741582
TH6notath615767.0/12 = 58.33%15691584
Abdul-Rahman Sibahisibahi157616.0/23 = 69.57%15651587
kokoszkokosz15767.0/8 = 87.50%15571595
Jenard Cabilaomgawalangmagawa157311.0/23 = 47.83%15861561
Alexander Trotterqilin15734.0/4 = 100.00%15741572
Plamen Draganovdraganov15734.0/4 = 100.00%15731573
Stephen Stockmanstevestockman157110.0/16 = 62.50%15761567
Christine Bagley-Joneszcherryz15703.5/5 = 70.00%15681571
Raymond Dlewel156113.0/22 = 59.09%15781544
je jujejujeju155936.5/61 = 59.84%15601558
Isaac Felpsattacker14415585.0/6 = 83.33%15591557
Thor Slavenskyslavensky15555.0/7 = 71.43%15341576
Daniel Zachariasarx1555226.0/434 = 52.07%15791530
Nicola Caridiniccar15543.0/3 = 100.00%15571550
Nicholas Wolffnwolff15539.0/15 = 60.00%15771530
Simon Runspeakablegamer15515.0/8 = 62.50%15391563
Roberto Lavierirlavieri200315503.0/3 = 100.00%15451555
carlos carloscarlos154616.0/27 = 59.26%15231568
michirmichir15432.0/2 = 100.00%15421544
S Ssim15436.0/9 = 66.67%15311554
pallab basupallab154031.0/60 = 51.67%15261555
Neil Spargospargo15393.0/4 = 75.00%15321546
Greg Strongmageofmaple1538106.0/219 = 48.40%15811495
Sandra#Paul BRANDLYARDsandravers13067515363.0/4 = 75.00%15341538
Tom e4ktome4k15362.0/2 = 100.00%15351536
Nicholas Wolffmaeko153565.5/141 = 46.45%15601510
Julien Coll Moratfacteurix15342.0/3 = 66.67%15321536
Todd Witterstoddw15342.0/2 = 100.00%15331535
Eric Greenwoodcavalier15344.0/6 = 66.67%15441524
Jake Palladinocerebralassassin15312.0/2 = 100.00%15271535
Matthew Montchalinmatthew_montchal15313.0/4 = 75.00%15291533
Máté Csarmaszcsarmi15307.0/16 = 43.75%15511510
Fred Koktangram15282.0/3 = 66.67%15291527
joe rosenbloombootzilla15282.0/3 = 66.67%15271529
Chuck Leegyw6t152817.5/39 = 44.87%15121543
Uwe Kreuzercaissus15272.0/2 = 100.00%15241530
Joseph DiMurotrojh15261.0/1 = 100.00%15341519
je jujejujejujeju15252.0/2 = 100.00%15131537
Yeinzon Rodríguez Garcíayeinzon15241.0/1 = 100.00%15281520
Adrian Alvarez de la Campaadrian15243.5/6 = 58.33%15241523
dicepawndicepawn15211.0/1 = 100.00%15251518
Tom Westtwrecks15201.0/1 = 100.00%15211519
von raidervonraider15201.0/1 = 100.00%15191520
Larry Wheelerbrainburner15191.0/1 = 100.00%15211518
Dougbughouse15191.0/1 = 100.00%15201518
Georg Spengleravunjahei15199.0/28 = 32.14%15061532
Richard Titlertitle15181.0/1 = 100.00%15191518
Garrett Smithgmsmith15181.0/2 = 50.00%15241512
strings 808017424strings80801742415181.0/1 = 100.00%15181518
Trevor Savagesavage15181.0/1 = 100.00%15181518
yas kumkumagai15181.0/1 = 100.00%15181518
David Levinsmidrael15181.0/1 = 100.00%15181518
whitenerdy53whitenerdy5315181.0/1 = 100.00%15181518
15181.0/1 = 100.00%15181518
Antonio Bruzzitotonno_janggi15181.0/1 = 100.00%15181518
eunchong leeeunchong15181.0/1 = 100.00%15181518
Angel47 Usmanangel4715181.0/1 = 100.00%15181518
calebblazecalebblaze15181.0/1 = 100.00%15181518
Jan Żmudajanzmuda15171.0/1 = 100.00%15181517
Titus Ledbettertbl215171.0/1 = 100.00%15181517
John Gallantbigjohn151716.0/34 = 47.06%14761558
bosa6bosa615171.0/1 = 100.00%15161519
M Wintherkalroten15171.0/1 = 100.00%15181516
Hesham Husseinegy_sniper15171.0/1 = 100.00%15171517
Nobody Importantcomradm15171.0/1 = 100.00%15161518
Samuel Hoskinscouriergame15171.0/2 = 50.00%15281505
Aaron Smithzirtoc15162.5/5 = 50.00%15131520
Georges-Clounet Jesuispartoutgeorgesclounet15161.0/1 = 100.00%15131519
Antonio Barratotonno15161.0/1 = 100.00%15141518
spiptorben15151.0/2 = 50.00%15141515
pink sockpickett_aaron15152.0/3 = 66.67%15151515
Simon Langley-Evansslangers15151.5/2 = 75.00%15131516
xxmanxxman15141.0/2 = 50.00%15191509
Nathanlokor15131.0/2 = 50.00%15131514
Max Kovalmaxkoval15121.0/1 = 100.00%15061519
Leon Careyleoncarey15121.0/1 = 100.00%15071518
pheko Motaungcouriermabovini151135.5/70 = 50.71%15631458
xeongreyxeongrey15108.0/17 = 47.06%15171503
mystery playercentipede15102.0/5 = 40.00%15131506
Antoine Fourrièreantoinefourriere15091.5/2 = 75.00%15081511
Joe Joycejoejoyce150822.5/68 = 33.09%14791538
Zachary Wadeazost1215083.0/5 = 60.00%15031513
As Bardhiasbardhi15081.0/2 = 50.00%15131502
Anthony Viensstarkiller15082.0/4 = 50.00%14991517
Boyko Ahtarovzdra4150610.0/23 = 43.48%14921519
Graeme Neathamgrayhawke15051.0/2 = 50.00%15031508
Natalia Dolindowhitetiger15041.0/2 = 50.00%15031504
Kent Weschlerperplexedibex15031.0/3 = 33.33%15041502
Albert Vámosiblackrider_4815031.0/4 = 25.00%15151490
Gee Beegdimension15021.0/2 = 50.00%15021502
Hans Henrikssonhasurami15022.0/4 = 50.00%14921512
Colin Adamslionhawk15021.0/2 = 50.00%15051500
Tom Trenchtomdench9515020.5/1 = 50.00%15001503
noy noynoy15013.0/7 = 42.86%14851517
Colin Weaveruselessgit15011.0/4 = 25.00%15001502
Anonymous Coderac12314991.0/2 = 50.00%15001498
Eni Lienili149811.5/46 = 25.00%15161481
Thom Dimentunwiseowl14982.0/5 = 40.00%14991497
Juan Pablo Schweitzer Kirsingerdefender14971.0/2 = 50.00%14951499
John Smithultimatecoolster14973.0/9 = 33.33%14971497
Armin Liebhartlunaris149525.0/58 = 43.10%14481541
Max Fengwowimbob111214941.0/3 = 33.33%14971492
Jeremy Thompsonjezzat149414.0/57 = 24.56%14651523
Diceroller is Firecryinto149420.0/38 = 52.63%14541534
DFA Productions70nyd014920.0/1 = 0.00%14961489
don anezdonanez14920.0/1 = 0.00%14961488
Michael Christensenjustsojazz14920.0/1 = 0.00%14961487
hubergerdhubergerd14920.0/1 = 0.00%14961487
vikvik14910.0/1 = 0.00%14971486
kunkunkunkun14910.0/1 = 0.00%14971486
Hugo Mendes-Nuneshugo199514910.0/1 = 0.00%14971485
Fabner Cruz Gracilianofabner14910.0/1 = 0.00%14971484
Bob Brownbobhihih14900.0/1 = 0.00%14971484
Ricardo Florentinoricmf14900.0/1 = 0.00%14931487
ugo judeugojude14900.0/1 = 0.00%14961484
wyatt wyattquimssarcasm14900.0/1 = 0.00%14971483
potato imaginatorpotato14900.0/1 = 0.00%14931486
John Badgerjbadger14900.0/1 = 0.00%14961484
jesus babyboypokechamp14900.0/1 = 0.00%14971482
Urvish Desaiurvishdesai14900.0/1 = 0.00%14931486
Milton Haddockmiltonhaddock14890.0/1 = 0.00%14961483
xerisianxxerisianx14890.0/1 = 0.00%14941485
Hsa Saidh14890.0/1 = 0.00%14971481
Esperllynmogik14890.0/1 = 0.00%14961482
makomako14890.0/1 = 0.00%14961482
loveokenloveoken14890.0/1 = 0.00%14941484
Steve Polleychessfan5914890.0/1 = 0.00%14941484
Matias I.tsatziq14890.0/1 = 0.00%14961481
Anders Gustafsonancog14890.0/1 = 0.00%14961481
Hafsteinn Kjartanssonhnr0114890.0/1 = 0.00%14961481
Jason Stehlyjasonstehly14880.0/1 = 0.00%14941483
Erlang Shenerlangshen14880.0/1 = 0.00%14951481
Éric Manálangedubble1914880.0/1 = 0.00%14941482
Four PlayerChessfourplayerchess14880.0/1 = 0.00%14941482
gwashinggwashing14880.0/1 = 0.00%14911484
Ben Reinigerbenr14880.0/1 = 0.00%14941481
Lamai grouplamai14880.0/1 = 0.00%14941481
zanzibarzanzibar14880.0/1 = 0.00%14921484
Ivan Velascoswordandsilver14870.0/1 = 0.00%14921483
László Gadosdani198314871.0/4 = 25.00%14841491
Rob Brownsteelhead14870.0/1 = 0.00%14911483
DJ Linickdjlinick14870.0/1 = 0.00%14911482
Joseph Yoderjjosseepphh14870.0/1 = 0.00%14861488
Ronald Brierleybenwb14870.0/1 = 0.00%14861487
Dead Accountqqzlbpdilchr14860.0/1 = 0.00%14921481
dghanddghand14860.0/1 = 0.00%14861486
thiago regob3aring14861.0/3 = 33.33%14871486
Lwebato14860.0/1 = 0.00%14871486
Given Familyzantonlan14861.0/3 = 33.33%14891484
anon anonchessvar114860.0/1 = 0.00%14871485
avni avniavni14860.0/1 = 0.00%14871484
François Houdebertfhou14860.0/1 = 0.00%14871484
Bradlee Kingstonbrad1914850.0/1 = 0.00%14891482
Andy Thomasandy_thomas14850.0/1 = 0.00%14881483
Mike Smolowitzmjs170114850.0/1 = 0.00%14891481
john applejohnnyappleseed714850.0/1 = 0.00%14881483
Brock Sampsonthe_iron_kenyan14850.0/1 = 0.00%14871483
William Crewscrewsdude14850.0/1 = 0.00%14881482
Nasmichael Farrismichaeljay14850.0/1 = 0.00%14881482
Luis Menendezpleyades2114850.0/1 = 0.00%14881482
Gus Dunihoduniho14850.0/1 = 0.00%14891481
maolan leonardruby14850.0/1 = 0.00%14881482
Alexandr Kremenakremen14850.0/1 = 0.00%14891481
Travis Comptonironlance14850.0/1 = 0.00%14881481
Paolo Porsiapillau14850.0/1 = 0.00%14881481
Kyle Hagemanfoofoo9914840.0/1 = 0.00%14881480
Derek Mooseelevatorfarter14841.0/3 = 33.33%14841484
Giuseppe Acciarocoopwie14842.0/5 = 40.00%14791489
James Sprattwhittlin14840.0/1 = 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
sixtysixty14830.0/3 = 0.00%14881479
Siwakorn Songragskyhistory14830.0/1 = 0.00%14841483
Jacob Eugenioe45w14830.0/1 = 0.00%14841482
Julianredpanda148317.0/35 = 48.57%14631503
scythian blunderq1234514830.0/2 = 0.00%14871479
Solomon Salamasol71014830.0/1 = 0.00%14821484
Doge Masterdogemaster14830.0/1 = 0.00%14851481
Antony Vailevichjabberw0cky114830.0/1 = 0.00%14821484
higuyzzz91028 Charles Kimdallastexas14830.0/1 = 0.00%14841481
Turk Osterburgtalen3141593141514830.0/1 = 0.00%14841481
manolo manolomanolo14830.0/1 = 0.00%14831483
Nicholas Archerchess_hunter14830.0/2 = 0.00%14881477
Dan Kellydankelly14830.0/1 = 0.00%14841481
Paul2memorysorowthorn14830.0/1 = 0.00%14831482
MichaÅ‚ Jarskihookz14830.0/1 = 0.00%14821483
Andreas Bunkahlebunkahle14830.0/1 = 0.00%14831482
Jose Canceljoche14830.0/1 = 0.00%14831482
Tony Quintanillatony_quintanilla14820.0/1 = 0.00%14821483
Roberto Cassanotamerlano14820.0/1 = 0.00%14841481
btstwbtstw14820.0/1 = 0.00%14841481
Jun Ocampojunpogi14820.0/2 = 0.00%14871478
cdpowercdpower14820.0/1 = 0.00%14841480
legendlegend14820.0/2 = 0.00%14921473
Hung Daobyteboy14820.0/1 = 0.00%14831481
wabbawabba14820.0/1 = 0.00%14831481
Uri Bruckbruck14820.0/2 = 0.00%14921473
Minh Dangminhdang14820.0/1 = 0.00%14811482
anna colladoapatura_iris14820.0/1 = 0.00%14811482
Joseph Grangercdafan14820.0/1 = 0.00%14811482
luigi mattagigino4214820.0/1 = 0.00%14801483
Thomas Meehanorangeaurochs14820.0/1 = 0.00%14821481
Robin Sneijderrobinwooter214820.0/1 = 0.00%14811482
Виктор Байгужаковbajvik14820.0/1 = 0.00%14821481
Wottonwotton14810.0/1 = 0.00%14811481
Harry Gaoharrygao14810.0/1 = 0.00%14811481
y kumyasuhiro14810.0/1 = 0.00%14811481
Ryan Schwartzshunoshi14810.0/1 = 0.00%14811481
ben chewben558214810.0/1 = 0.00%14811481
jj14810.0/1 = 0.00%14811481
Babo Jeffbabojeff14810.0/1 = 0.00%14811481
wonsang leewonsang14810.0/1 = 0.00%14811481
Vitali Maslanskivitali_1014810.0/1 = 0.00%14811481
paulblazepaulblaze14810.0/1 = 0.00%14811481
blundermanblunderman14810.0/1 = 0.00%14811481
Abe Anonapostateabe14810.0/1 = 0.00%14801482
Mark Thompsonmarkthompson14810.0/2 = 0.00%14921469
championchampion14810.0/2 = 0.00%14851476
arcasorarcasor14800.0/1 = 0.00%14791481
andres fuentesxabyer14800.0/2 = 0.00%14821478
trtztrtz gfghtrtztrtz14800.0/2 = 0.00%14861474
Bn Emnelk11414800.0/2 = 0.00%14841476
rederikrederik14800.0/1 = 0.00%14781481
Diego M.diego14800.0/3 = 0.00%14851475
Francesco Casalinofrancesco14790.0/2 = 0.00%14841474
voicantvoicant14790.0/1 = 0.00%14761481
Jeff Bezoscroissantman14790.0/1 = 0.00%14761481
qidb602qidb60214780.0/2 = 0.00%14841473
N Wolffpoint01iv14781.0/3 = 33.33%14731483
ologyology14780.0/1 = 0.00%14751481
Ivan Kosintsevbombino14780.0/1 = 0.00%14741481
John Twycrossjt14770.0/2 = 0.00%14771478
Steve Hsteve_201014760.0/2 = 0.00%14721480
Frank Istvánistvan6014760.0/2 = 0.00%14861467
wdtrwdtr14760.0/3 = 0.00%14801472
Alexander Krutikovlonewolf14761.0/4 = 25.00%14721479
Ivan Ivankillbill22514760.0/1 = 0.00%14701481
Francisco Magalhãeslowcarbknight14750.0/1 = 0.00%14691481
Szling Ozecszling_ozec14750.0/3 = 0.00%14781472
tedy efwttei27fmrw7de14750.0/1 = 0.00%14691481
Nathan Holdenlinsolv14750.0/1 = 0.00%14671482
Todor Tchervenkovtchervenkov14741.0/4 = 25.00%14731474
Aurelian Floreacatugo1474261.5/761 = 34.36%15521396
Charles Gilmancharles_gilman14740.0/2 = 0.00%14731474
Travis Comptonblackrood14740.0/2 = 0.00%14721475
Lennon Figueiredogiwseppe14731.0/4 = 25.00%14711476
Pablo Denegrideep_thinker14730.0/2 = 0.00%14761471
danielmacduffdanielmacduff14730.0/3 = 0.00%14711475
Em Nilddetective4714730.0/2 = 0.00%14751470
cherokee malansailorhertzog14710.0/2 = 0.00%14781464
Kacper Rutkowskikacperrutkowski14710.0/2 = 0.00%14741469
jeremy diniericharles_bukowski14710.0/2 = 0.00%14691473
Pat Quexionezsuperpatzermaste14710.0/4 = 0.00%14721469
Sergey Biryukovsbiryukov14700.0/4 = 0.00%14721469
Вадря Покштяpokshtya147013.0/31 = 41.94%14511489
Zoli M Zoltánbaltazarprof14690.0/5 = 0.00%14821457
dfe6631dfe663114690.0/2 = 0.00%14641474
andrewthepawnandrewthepawn14690.0/2 = 0.00%14661472
A tomiatomi14684.5/16 = 28.12%14591477
iuchi45iuchi4514680.0/2 = 0.00%14661470
Memedes Lulagiwseppe314670.0/2 = 0.00%14691466
Zac Sparxkrinid14660.0/2 = 0.00%14671465
Donut Donutdonutdonut14650.0/2 = 0.00%14661465
playshogiplayshogi14650.0/2 = 0.00%14661463
Scott Crawfordmathemagician14640.0/7 = 0.00%14741455
Michael Nelsonmikenels14640.0/2 = 0.00%14621466
michael collinsverderben14641.0/5 = 20.00%14701458
Namik Zadenamik14630.0/2 = 0.00%14611465
andy lewickietaoni14620.0/2 = 0.00%14611464
Scott McGrealagentofchaos14617.0/18 = 38.89%14581464
Andy Lewickiondraszek14600.0/3 = 0.00%14541466
Graemegraemecn14580.0/3 = 0.00%14561460
Michael Huntkronsteen3314580.0/3 = 0.00%14471468
Николай Сокольскийalexich14560.0/4 = 0.00%14621450
louisvlouisv14560.0/3 = 0.00%14581453
Nick Wolffwolff145426.0/72 = 36.11%14361473
Bob Greenwadebobgreenwade14530.0/3 = 0.00%14491458
John Langleyjonners14520.5/4 = 12.50%14521451
Dayrom Gilallahukbar14510.0/3 = 0.00%14511452
Michael Schmahlmschmahl14515.0/15 = 33.33%14591444
vitaliy ravitztalsterch14512.0/15 = 13.33%14331469
Aaron Maynardvopi14511.0/6 = 16.67%14471454
Joshua Tsamraku14505.0/12 = 41.67%14251474
Linn Russellfreakat14490.0/3 = 0.00%14491449
Adalbertus Kchewoj14481.0/5 = 20.00%14401455
Sagi Gabaysagig7214450.5/16 = 3.12%14281462
A. M. DeWittchessshogi14430.0/5 = 0.00%14481439
Florin Lupusorulittlewolf14430.0/5 = 0.00%14521435
dmitarzvonimirdmitarzvonimir14430.0/5 = 0.00%14391446
heche60heche6014422.0/12 = 16.67%14431442
Jeremy Goodjudgmentality143843.5/127 = 34.25%14381437
Evan Jorgensonsabataegalo14370.0/7 = 0.00%14251448
Evert Jan Karmanevertvb14352.5/11 = 22.73%14181453
Phoenix TKartkr10101014342.0/9 = 22.22%14371430
Alan Galetornadic14313.0/20 = 15.00%14231438
Matthew La Valleesherman10114306.0/23 = 26.09%14161445
Jon Dannjon_dann14300.0/4 = 0.00%14261433
juan rodriguezrodriguez142611.5/38 = 30.26%14361415
Daniil Frolovflowermann14243.0/16 = 18.75%14121436
Jeremy Hook10011014222.0/30 = 6.67%14181427
boukineboukine14204.0/13 = 30.77%13871453
Jack Zavierubersketch14190.0/6 = 0.00%14121426
Arthur Yvrardtorendil14160.0/7 = 0.00%14111421
John Davischappy14133.0/17 = 17.65%14021424
Paul Rapoportnumerist14130.0/7 = 0.00%14141411
Evan Jorgensonejorgens14120.0/7 = 0.00%14031421
yellowturtleyellowturtle14120.0/10 = 0.00%14131410
Samuel de Souzasamsou14110.0/8 = 0.00%14111411
Митя Стрелецкийsocrat8314070.0/10 = 0.00%13971417
Jean-Louis Cazauxtimurthelenk14052.0/15 = 13.33%14041407
Dmitry Strelyabba8314040.0/10 = 0.00%14191389
George Dukegwduke140442.5/117 = 36.32%13521456
darren paullramalam139613.5/99 = 13.64%13761416
Bogot Bogotolbog139112.0/44 = 27.27%13711411
Митя Митяbahram13891.0/17 = 5.88%14061373
mrxx2016mrxx201613790.0/17 = 0.00%13961362
Сергей Маэстроfantomas13551.0/31 = 3.23%13581353
Nakanaka13530.0/11 = 0.00%13211384
Omnia Nihilosacredchao134713.0/73 = 17.81%13251370
Diogen Abramelindanko13360.0/35 = 0.00%13191353
Oisín D.sxg133252.0/252 = 20.63%13091356
Сергей Бугаевскийbugaevsky12913.0/56 = 5.36%12811300
Richard milnersesquipedalian127615.0/274 = 5.47%12931260
Alisher Bolsaniraja8512730.0/46 = 0.00%12521294
wdtr2wdtr2125222.5/202 = 11.14%12621242
per hommerbergper3112362.0/86 = 2.33%11971275

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