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The Chess Variant Pages



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:
Tournament Filter: Age Filter: Status Filter:
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:69.47%68.67%68.32%
NameUseridGCRPercent wonGCR1GCR2
Hexa Sakkbosa601863136.5/151 = 90.40%18281897
Francis Fahystamandua1849247.0/298 = 82.89%18251873
dax00dax001828161.0/167 = 96.41%18191836
Kevin Paceypanther1794502.0/621 = 80.84%18021785
Play Testerplaytester177669.5/81 = 85.80%17721781
Carlos Cetinasissa1740636.5/994 = 64.03%17221759
Cameron Milesshatteredglass171215.0/17 = 88.24%17081717
Jochen Muellerleopold_stotch169455.0/92 = 59.78%16851703
H Spetyura168713.0/13 = 100.00%16761697
Gary Giffordpenswift168060.5/85 = 71.18%15821777
Fergus Dunihofergus167463.5/101 = 62.87%16681680
Homo Simiaalienum167121.0/25 = 84.00%16631678
Jose Carrilloj_carrillo_vii166887.5/155 = 56.45%16631672
Tim O'Lenatim_olena165117.5/27 = 64.81%16601642
Vitya Makovmakov3331627367.0/789 = 46.51%15701683
David Paulowichdavid_64162511.0/13 = 84.62%16321618
Stephen Williamsneph162011.0/12 = 91.67%15791661
shift2shiftshift2shift162011.0/19 = 57.89%16191621
Daniel Zachariasarx1618146.0/242 = 60.33%16221614
Charles Danielfrozen_methane161135.0/64 = 54.69%15801642
Vitya Makovmakov16117.5/8 = 93.75%16091614
Andreas Kaufmannandreas16077.0/7 = 100.00%16091605
P. A. Stonemann CSS Dixielandcssdixieland159711.0/15 = 73.33%15971597
Pericles Tesone de Souzaperitezz15888.0/8 = 100.00%15881588
Erik Lerougeerik1582140.5/260 = 54.04%16541511
ctzctz157912.0/17 = 70.59%15541604
kokoszkokosz15767.0/8 = 87.50%15571595
Abdul-Rahman Sibahisibahi157516.0/23 = 69.57%15661585
attack hippoattackhippo15755.5/7 = 78.57%15691580
je jujejujeju157236.5/60 = 60.83%15611583
TH6notath615727.0/12 = 58.33%15711574
Alexander Trotterqilin15704.0/4 = 100.00%15711570
Christine Bagley-Joneszcherryz15703.5/5 = 70.00%15681572
Jenard Cabilaomgawalangmagawa156911.0/23 = 47.83%15831555
Stephen Stockmanstevestockman156810.0/16 = 62.50%15731563
John Gallantbigjohn156416.0/28 = 57.14%15551573
Raymond Dlewel156013.0/22 = 59.09%15771543
Isaac Felpsattacker14415585.0/6 = 83.33%15591557
Thor Slavenskyslavensky15565.0/7 = 71.43%15371574
Nicola Caridiniccar15543.0/3 = 100.00%15571550
Nicholas Wolffnwolff15549.0/15 = 60.00%15741534
Roberto Lavierirlavieri200315503.0/3 = 100.00%15451555
Greg Strongmageofmaple1550105.0/218 = 48.17%16011498
pallab basupallab154931.0/60 = 51.67%15251572
carlos carloscarlos154416.0/27 = 59.26%15251563
S Ssim15436.0/9 = 66.67%15311554
michirmichir15412.0/2 = 100.00%15411541
Nicholas Wolffmaeko154165.5/142 = 46.13%15611521
Sandra#Paul BRANDLYARDsandravers13067515373.0/4 = 75.00%15371537
Tom e4ktome4k15352.0/2 = 100.00%15351536
Neil Spargospargo15343.0/4 = 75.00%15271542
Eric Greenwoodcavalier15344.0/6 = 66.67%15441524
Todd Witterstoddw15342.0/2 = 100.00%15321535
Julien Coll Moratfacteurix15312.0/3 = 66.67%15291534
Matthew Montchalinmatthew_montchal15313.0/4 = 75.00%15291533
Jake Palladinocerebralassassin15312.0/2 = 100.00%15271535
Fred Koktangram15282.0/3 = 66.67%15291527
joe rosenbloombootzilla15282.0/3 = 66.67%15271529
Uwe Kreuzercaissus15272.0/2 = 100.00%15241530
Joseph DiMurotrojh15261.0/1 = 100.00%15331519
Chuck Leegyw6t152417.5/39 = 44.87%15151534
Yeinzon Rodríguez Garcíayeinzon15241.0/1 = 100.00%15281520
Adrian Alvarez de la Campaadrian15243.5/6 = 58.33%15231524
Tom Westtwrecks15211.0/1 = 100.00%15241519
von raidervonraider15201.0/1 = 100.00%15191520
dicepawndicepawn15201.0/1 = 100.00%15211518
Larry Wheelerbrainburner15191.0/1 = 100.00%15211518
Natalia Dolindowhitetiger15191.0/1 = 100.00%15201519
Joe Joycejoejoyce151921.5/62 = 34.68%14771562
Dougbughouse15191.0/1 = 100.00%15201518
Todor Tchervenkovtchervenkov15181.0/1 = 100.00%15191518
Richard Titlertitle15181.0/1 = 100.00%15191518
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
jj15181.0/1 = 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
Garrett Smithgmsmith15171.0/2 = 50.00%15241511
Jan Żmudajanzmuda15171.0/1 = 100.00%15181517
Titus Ledbettertbl215171.0/1 = 100.00%15181517
M Wintherkalroten15171.0/1 = 100.00%15181516
Hesham Husseinegy_sniper15171.0/1 = 100.00%15171517
bosa6bosa615171.0/1 = 100.00%15151519
Aaron Smithzirtoc15162.5/5 = 50.00%15121520
Georges-Clounet Jesuispartoutgeorgesclounet15161.0/1 = 100.00%15131519
Antonio Barratotonno15161.0/1 = 100.00%15141518
pink sockpickett_aaron15152.0/3 = 66.67%15151515
Simon Langley-Evansslangers15151.5/2 = 75.00%15131516
xxmanxxman15131.0/2 = 50.00%15191508
Georg Spengleravunjahei15139.0/28 = 32.14%15041522
Leon Careyleoncarey15121.0/1 = 100.00%15071518
Max Kovalmaxkoval15121.0/1 = 100.00%15061519
spiptorben15121.0/2 = 50.00%15121512
pheko Motaungcouriermabovini151135.5/70 = 50.71%15621459
Nathanlokor15101.0/2 = 50.00%15111509
Antoine Fourrièreantoinefourriere15091.5/2 = 75.00%15081511
mystery playercentipede15092.0/5 = 40.00%15131505
Anthony Viensstarkiller15082.0/4 = 50.00%15011515
xeongreyxeongrey15088.0/17 = 47.06%15151500
As Bardhiasbardhi15071.0/2 = 50.00%15121501
Zachary Wadeazost1215063.0/5 = 60.00%14991513
Albert Vámosiblackrider_4815031.0/4 = 25.00%15161490
Gee Beegdimension15021.0/2 = 50.00%15021502
Graeme Neathamgrayhawke15021.0/2 = 50.00%15001504
Colin Adamslionhawk15021.0/2 = 50.00%15051500
Hans Henrikssonhasurami15022.0/4 = 50.00%14911512
Tom Trenchtomdench9515010.5/1 = 50.00%15011502
noy noynoy15003.0/7 = 42.86%14881512
Colin Weaveruselessgit15001.0/4 = 25.00%14991500
Kent Weschlerperplexedibex15001.0/3 = 33.33%15011498
Thom Dimentunwiseowl14992.0/5 = 40.00%15001497
N Wolffpoint01iv14991.0/2 = 50.00%14961502
Eni Lienili149911.5/46 = 25.00%15191478
Juan Pablo Schweitzer Kirsingerdefender14971.0/2 = 50.00%14951499
John Smithultimatecoolster14953.0/9 = 33.33%14951495
Max Fengwowimbob111214941.0/3 = 33.33%14971492
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%14961486
kunkunkunkun14910.0/1 = 0.00%14961486
Hugo Mendes-Nuneshugo199514910.0/1 = 0.00%14971485
Fabner Cruz Gracilianofabner14910.0/1 = 0.00%14971484
Ricardo Florentinoricmf14900.0/1 = 0.00%14941487
Bob Brownbobhihih14900.0/1 = 0.00%14971484
potato imaginatorpotato14900.0/1 = 0.00%14941486
ugo judeugojude14900.0/1 = 0.00%14951485
Urvish Desaiurvishdesai14900.0/1 = 0.00%14941486
wyatt wyattquimssarcasm14900.0/1 = 0.00%14971483
John Badgerjbadger14900.0/1 = 0.00%14951484
xerisianxxerisianx14900.0/1 = 0.00%14941485
jesus babyboypokechamp14900.0/1 = 0.00%14971482
Samuel Hoskinscouriergame14890.0/1 = 0.00%14951484
loveokenloveoken14890.0/1 = 0.00%14941484
Milton Haddockmiltonhaddock14890.0/1 = 0.00%14951483
Hsa Saidh14890.0/1 = 0.00%14971481
Steve Polleychessfan5914890.0/1 = 0.00%14951484
makomako14890.0/1 = 0.00%14961482
Esperllynmogik14890.0/1 = 0.00%14961482
Jason Stehlyjasonstehly14890.0/1 = 0.00%14951483
Hafsteinn Kjartanssonhnr0114890.0/1 = 0.00%14961481
Anders Gustafsonancog14890.0/1 = 0.00%14961481
Matias I.tsatziq14890.0/1 = 0.00%14961481
Éric Manálangedubble1914880.0/1 = 0.00%14951482
Ben Reinigerbenr14880.0/1 = 0.00%14951481
Dmitry Strelyabba8314880.0/1 = 0.00%14931482
Erlang Shenerlangshen14870.0/1 = 0.00%14931481
Ivan Velascoswordandsilver14870.0/1 = 0.00%14911483
Rob Brownsteelhead14870.0/1 = 0.00%14911483
DJ Linickdjlinick14870.0/1 = 0.00%14911482
Dead Accountqqzlbpdilchr14860.0/1 = 0.00%14911481
Bradlee Kingstonbrad1914860.0/1 = 0.00%14891482
Mike Smolowitzmjs170114850.0/1 = 0.00%14891481
Andy Thomasandy_thomas14850.0/1 = 0.00%14881483
Brock Sampsonthe_iron_kenyan14850.0/1 = 0.00%14871483
Nasmichael Farrismichaeljay14850.0/1 = 0.00%14881482
Luis Menendezpleyades2114850.0/1 = 0.00%14881482
Gus Dunihoduniho14850.0/1 = 0.00%14891481
Travis Comptonironlance14850.0/1 = 0.00%14881481
Alexandr Kremenakremen14850.0/1 = 0.00%14881481
Julianredpanda148517.0/35 = 48.57%14641505
Siwakorn Songragskyhistory14840.0/1 = 0.00%14861483
Jacob Eugenioe45w14840.0/1 = 0.00%14861482
Derek Mooseelevatorfarter14841.0/3 = 33.33%14841484
Doge Masterdogemaster14840.0/1 = 0.00%14871481
James Sprattwhittlin14840.0/1 = 0.00%14871481
higuyzzz91028 Charles Kimdallastexas14840.0/1 = 0.00%14861481
scythian blunderq1234514840.0/2 = 0.00%14881479
Jeremy Goodyamorezu14840.0/1 = 0.00%14851482
andy lewickiherlocksholmes14830.0/1 = 0.00%14861481
yi fang liuliuyifang14830.0/1 = 0.00%14861481
Turk Osterburgtalen3141593141514830.0/1 = 0.00%14851481
sixtysixty14830.0/3 = 0.00%14871480
Ronald Brierleybenwb14830.0/1 = 0.00%14841483
Jun Ocampojunpogi14830.0/2 = 0.00%14891478
dghanddghand14830.0/1 = 0.00%14841482
Solomon Salamasol71014830.0/1 = 0.00%14831483
anon anonchessvar114830.0/1 = 0.00%14841481
Antony Vailevichjabberw0cky114830.0/1 = 0.00%14831482
Dan Kellydankelly14830.0/1 = 0.00%14841481
Paolo Porsiapillau14830.0/1 = 0.00%14851480
Andreas Bunkahlebunkahle14830.0/1 = 0.00%14831482
MichaÅ‚ Jarskihookz14820.0/1 = 0.00%14821483
manolo manolomanolo14820.0/1 = 0.00%14841481
Jose Canceljoche14820.0/1 = 0.00%14831482
Roberto Cassanotamerlano14820.0/1 = 0.00%14841481
Tony Quintanillatony_quintanilla14820.0/1 = 0.00%14821483
wabbawabba14820.0/1 = 0.00%14841481
cdpowercdpower14820.0/1 = 0.00%14841480
btstwbtstw14820.0/1 = 0.00%14831481
Hung Daobyteboy14820.0/1 = 0.00%14831481
Uri Bruckbruck14820.0/2 = 0.00%14921473
legendlegend14820.0/2 = 0.00%14901474
Nicholas Archerchess_hunter14820.0/2 = 0.00%14881477
László Gadosdani198314821.0/4 = 25.00%14781486
Aurelian Floreacatugo1482251.5/722 = 34.83%15581406
anna colladoapatura_iris14820.0/1 = 0.00%14811482
Minh Dangminhdang14820.0/1 = 0.00%14811482
Robin Sneijderrobinwooter214820.0/1 = 0.00%14811482
Joseph Grangercdafan14820.0/1 = 0.00%14811482
Виктор Байгужаковbajvik14820.0/1 = 0.00%14821481
luigi mattagigino4214820.0/1 = 0.00%14801483
Thomas Meehanorangeaurochs14820.0/1 = 0.00%14821481
Boyko Ahtarovzdra4148110.0/23 = 43.48%14881475
Abe Anonapostateabe14810.0/1 = 0.00%14811481
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
14810.0/1 = 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
Giuseppe Acciarocoopwie14812.0/5 = 40.00%14751487
blundermanblunderman14810.0/1 = 0.00%14821480
Mark Thompsonmarkthompson14810.0/2 = 0.00%14931469
arcasorarcasor14800.0/1 = 0.00%14791481
Diego M.diego14800.0/3 = 0.00%14851475
rederikrederik14800.0/1 = 0.00%14781481
championchampion14800.0/2 = 0.00%14841475
Bn Emnelk11414790.0/2 = 0.00%14831474
voicantvoicant14790.0/1 = 0.00%14761481
Francesco Casalinofrancesco14780.0/2 = 0.00%14841472
Ivan Kosintsevbombino14780.0/1 = 0.00%14751481
ologyology14780.0/1 = 0.00%14741481
trtztrtz gfghtrtztrtz14770.0/2 = 0.00%14821472
qidb602qidb60214770.0/2 = 0.00%14841470
andres fuentesxabyer14770.0/2 = 0.00%14801474
Frank Istvánistvan6014760.0/2 = 0.00%14851467
Ivan Ivankillbill22514760.0/1 = 0.00%14711481
Alexander Krutikovlonewolf14761.0/4 = 25.00%14721479
Francisco Magalhãeslowcarbknight14760.0/1 = 0.00%14701481
wdtrwdtr14750.0/3 = 0.00%14791471
tedy efwttei27fmrw7de14750.0/1 = 0.00%14691481
Nathan Holdenlinsolv14750.0/1 = 0.00%14681482
Szling Ozecszling_ozec14740.0/3 = 0.00%14771471
John Twycrossjt14740.0/2 = 0.00%14741474
Charles Gilmancharles_gilman14730.0/2 = 0.00%14731474
Lennon Figueiredogiwseppe14731.0/4 = 25.00%14711476
Pablo Denegrideep_thinker14730.0/2 = 0.00%14761471
Sergey Biryukovsbiryukov14720.0/4 = 0.00%14721472
Pat Quexionezsuperpatzermaste14710.0/4 = 0.00%14731469
Kacper Rutkowskikacperrutkowski14700.0/2 = 0.00%14731467
Steve Hsteve_201014700.0/2 = 0.00%14681473
Travis Comptonblackrood14700.0/2 = 0.00%14701471
cherokee malansailorhertzog14700.0/2 = 0.00%14761465
dfe6631dfe663114700.0/2 = 0.00%14661474
danielmacduffdanielmacduff14700.0/3 = 0.00%14671472
Zoli M Zoltánbaltazarprof14700.0/5 = 0.00%14831457
Jean-Louis Cazauxtimurthelenk14701.0/5 = 20.00%14701469
andrewthepawnandrewthepawn14690.0/2 = 0.00%14671472
iuchi45iuchi4514690.0/2 = 0.00%14691468
Adam DeWittchessshogi14690.0/3 = 0.00%14751462
A tomiatomi14684.5/16 = 28.12%14611476
jeremy diniericharles_bukowski14680.0/2 = 0.00%14661469
Memedes Lulagiwseppe314670.0/2 = 0.00%14691466
Zac Sparxkrinid14660.0/2 = 0.00%14681465
Donut Donutdonutdonut14650.0/2 = 0.00%14661465
Máté Csarmaszcsarmi14650.0/3 = 0.00%14761454
Scott Crawfordmathemagician14650.0/7 = 0.00%14741455
playshogiplayshogi14650.0/2 = 0.00%14661463
Armin Liebhartlunaris146419.0/50 = 38.00%14501478
Michael Nelsonmikenels14640.0/2 = 0.00%14611466
michael collinsverderben14641.0/5 = 20.00%14701457
Namik Zadenamik14630.0/2 = 0.00%14611465
andy lewickietaoni14620.0/2 = 0.00%14611464
Michael Huntkronsteen3314580.0/3 = 0.00%14491467
Nick Wolffwolff145626.0/72 = 36.11%14171495
louisvlouisv14550.0/3 = 0.00%14581453
Graemegraemecn14550.0/3 = 0.00%14531457
Andy Lewickiondraszek14550.0/3 = 0.00%14481461
Николай Сокольскийalexich14540.0/4 = 0.00%14611448
John Langleyjonners14520.5/4 = 12.50%14521451
Dayrom Gilallahukbar14510.0/3 = 0.00%14511452
Michael Schmahlmschmahl14515.0/15 = 33.33%14601441
Linn Russellfreakat14490.0/3 = 0.00%14491449
Joshua Tsamraku14485.0/12 = 41.67%14251472
Aaron Maynardvopi14481.0/6 = 16.67%14431453
Scott McGrealagentofchaos14477.0/19 = 36.84%14531442
Adalbertus Kchewoj14471.0/5 = 20.00%14411454
vitaliy ravitztalsterch14462.0/15 = 13.33%14341457
Jeremy Goodjudgmentality144543.5/127 = 34.25%14311460
heche60heche6014432.0/12 = 16.67%14451442
dmitarzvonimirdmitarzvonimir14410.0/5 = 0.00%14391444
Sagi Gabaysagig7214410.5/16 = 3.12%14241458
Paul Rapoportnumerist14370.0/5 = 0.00%14381436
Evan Jorgensonsabataegalo14370.0/7 = 0.00%14241449
Evert Jan Karmanevertvb14352.5/11 = 22.73%14181451
Phoenix TKartkr10101014332.0/9 = 22.22%14361430
Jon Dannjon_dann14300.0/4 = 0.00%14271433
juan rodriguezrodriguez142911.5/38 = 30.26%14421417
Matthew La Valleesherman10114276.0/23 = 26.09%14101443
boukineboukine14234.0/13 = 30.77%13931453
Alan Galetornadic14233.0/20 = 15.00%14211424
Jack Zavierubersketch14210.0/6 = 0.00%14171425
Daniil Frolovflowermann14203.0/16 = 18.75%14061433
mrxx2016mrxx201614170.0/9 = 0.00%14251409
Arthur Yvrardtorendil14160.0/7 = 0.00%14111421
Jeremy Hook10011014152.0/30 = 6.67%14121418
John Davischappy14133.0/17 = 17.65%14011425
Samuel de Souzasamsou14110.0/8 = 0.00%14111411
George Dukegwduke141142.5/117 = 36.32%13501471
yellowturtleyellowturtle14110.0/10 = 0.00%14131408
Evan Jorgensonejorgens14100.0/7 = 0.00%14001419
Вадря Покштяpokshtya14074.0/17 = 23.53%13921422
Митя Стрелецкийsocrat8314030.0/10 = 0.00%13911414
darren paullramalam139713.5/100 = 13.50%13681427
Bogot Bogotolbog138812.0/44 = 27.27%13741402
Jarid Carlsonsacredchao137913.0/68 = 19.12%13461411
Сергей Маэстроfantomas13571.0/31 = 3.23%13631351
Nakanaka13570.0/11 = 0.00%13291384
Diogen Abramelindanko13330.0/35 = 0.00%13181349
Oisín D.sxg131242.0/189 = 22.22%12901335
Сергей Бугаевскийbugaevsky12963.0/56 = 5.36%12911302
wdtr2wdtr2129421.5/147 = 14.63%12701317
per hommerbergper3112852.0/57 = 3.51%12531316
Alisher Bolsaniraja8512820.0/46 = 0.00%12631302
Richard milnersesquipedalian12767.0/97 = 7.22%13031250

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