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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:69.35%68.90%68.51%
NameUseridGCRPercent wonGCR1GCR2
Hexa Sakkbosa601859136.5/151 = 90.40%18281889
Francis Fahystamandua1849247.0/298 = 82.89%18231875
dax00dax001828158.0/164 = 96.34%18231833
Kevin Paceypanther1799488.0/597 = 81.74%18081790
Carlos Cetinasissa1737631.5/986 = 64.05%17181755
Cameron Milesshatteredglass171215.0/17 = 88.24%17071718
Jochen Muellerleopold_stotch169755.0/92 = 59.78%16851709
H Spetyura168813.0/13 = 100.00%16801696
Gary Giffordpenswift168160.5/85 = 71.18%15761785
Play Testerplaytester167618.5/25 = 74.00%16791674
Fergus Dunihofergus167463.5/101 = 62.87%16681680
Jose Carrilloj_carrillo_vii166587.5/155 = 56.45%16641665
Tim O'Lenatim_olena164513.5/20 = 67.50%16521639
Daniel Zachariasarx1631116.0/199 = 58.29%16441619
David Paulowichdavid_64162511.0/13 = 84.62%16311619
Vitya Makovmakov3331625341.0/732 = 46.58%15751675
Stephen Williamsneph162411.0/12 = 91.67%15911656
shift2shiftshift2shift162011.0/19 = 57.89%16151624
Homo Simiaalienum16187.0/8 = 87.50%16091627
Charles Danielfrozen_methane161435.0/64 = 54.69%15771650
Vitya Makovmakov16117.5/8 = 93.75%16101613
Andreas Kaufmannandreas16077.0/7 = 100.00%16091605
Pericles Tesone de Souzaperitezz15888.0/8 = 100.00%15881588
ctzctz157912.0/17 = 70.59%15541604
kokoszkokosz15767.0/8 = 87.50%15571595
attack hippoattackhippo15755.5/7 = 78.57%15711580
Abdul-Rahman Sibahisibahi157516.0/23 = 69.57%15661583
Erik Lerougeerik1573140.5/260 = 54.04%16211525
je jujejujeju157236.5/60 = 60.83%15721573
Alexander Trotterqilin15704.0/4 = 100.00%15711570
Stephen Stockmanstevestockman156910.0/16 = 62.50%15741564
Jenard Cabilaomgawalangmagawa156811.0/23 = 47.83%15801555
TH6notath615677.0/12 = 58.33%15591574
John Gallantbigjohn156616.0/28 = 57.14%15601571
Raymond Dlewel156013.0/22 = 59.09%15761543
Isaac Felpsattacker14415585.0/6 = 83.33%15591557
Thor Slavenskyslavensky15565.0/7 = 71.43%15371574
Nicola Caridiniccar15543.0/3 = 100.00%15571550
Nicholas Wolffnwolff15539.0/15 = 60.00%15741532
Greg Strongmageofmaple1552105.0/216 = 48.61%16041500
pallab basupallab155131.0/60 = 51.67%15261576
Roberto Lavierirlavieri200315503.0/3 = 100.00%15451555
Christine Bagley-Joneszcherryz15462.5/4 = 62.50%15471546
carlos carloscarlos154516.0/27 = 59.26%15241567
S Ssim15436.0/9 = 66.67%15311554
michirmichir15412.0/2 = 100.00%15411541
Sandra#Paul BRANDLYARDsandravers13067515403.0/4 = 75.00%15391541
Nicholas Wolffmaeko153765.5/142 = 46.13%15591515
Tom e4ktome4k15362.0/2 = 100.00%15351536
Neil Spargospargo15343.0/4 = 75.00%15271542
Todd Witterstoddw15342.0/2 = 100.00%15331535
Eric Greenwoodcavalier15344.0/6 = 66.67%15441524
Julien Coll Moratfacteurix15312.0/3 = 66.67%15291534
Matthew Montchalinmatthew_montchal15313.0/4 = 75.00%15291533
Jake Palladinocerebralassassin15312.0/2 = 100.00%15271535
joe rosenbloombootzilla15282.0/3 = 66.67%15271529
Fred Koktangram15282.0/3 = 66.67%15291527
Uwe Kreuzercaissus15272.0/2 = 100.00%15241530
Joseph DiMurotrojh15261.0/1 = 100.00%15331519
Chuck Leegyw6t152517.5/39 = 44.87%15141536
Yeinzon Rodríguez Garcíayeinzon15241.0/1 = 100.00%15281520
Adrian Alvarez de la Campaadrian15243.5/6 = 58.33%15231524
Joe Joycejoejoyce152421.5/60 = 35.83%14771570
P. A. Stonemann CSS Dixielandcssdixieland15221.0/1 = 100.00%15241520
Tom Westtwrecks15221.0/1 = 100.00%15251519
von raidervonraider15201.0/1 = 100.00%15191520
dicepawndicepawn15201.0/1 = 100.00%15221518
Natalia Dolindowhitetiger15201.0/1 = 100.00%15211519
Larry Wheelerbrainburner15191.0/1 = 100.00%15211518
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
Jan Żmudajanzmuda15171.0/1 = 100.00%15181517
Garrett Smithgmsmith15171.0/2 = 50.00%15241511
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%15131520
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%15181508
Leon Careyleoncarey15131.0/1 = 100.00%15081518
spiptorben15131.0/2 = 50.00%15131512
Georg Spengleravunjahei15129.0/28 = 32.14%15041520
pheko Motaungcouriermabovini151135.5/70 = 50.71%15631459
Nathanlokor15101.0/2 = 50.00%15111509
Antoine Fourrièreantoinefourriere15091.5/2 = 75.00%15081511
mystery playercentipede15092.0/5 = 40.00%15121505
xeongreyxeongrey15088.0/17 = 47.06%15161499
Anthony Viensstarkiller15072.0/4 = 50.00%14991515
Zachary Wadeazost1215063.0/5 = 60.00%14981513
As Bardhiasbardhi15051.0/2 = 50.00%15091501
Gee Beegdimension15031.0/2 = 50.00%15031502
Albert Vámosiblackrider_4815031.0/4 = 25.00%15161490
Graeme Neathamgrayhawke15021.0/2 = 50.00%15011504
Colin Adamslionhawk15021.0/2 = 50.00%15051500
Hans Henrikssonhasurami15022.0/4 = 50.00%14921512
Tom Trenchtomdench9515020.5/1 = 50.00%15011502
noy noynoy15013.0/7 = 42.86%14871514
Kent Weschlerperplexedibex14991.0/3 = 33.33%15011498
Colin Weaveruselessgit14991.0/4 = 25.00%14981500
Eni Lienili149911.5/46 = 25.00%15201478
Thom Dimentunwiseowl14992.0/5 = 40.00%15001497
Juan Pablo Schweitzer Kirsingerdefender14971.0/2 = 50.00%14951499
Max Fengwowimbob111214941.0/3 = 33.33%14971492
John Smithultimatecoolster14943.0/9 = 33.33%14951493
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
Ricardo Florentinoricmf14910.0/1 = 0.00%14941487
Fabner Cruz Gracilianofabner14900.0/1 = 0.00%14971484
potato imaginatorpotato14900.0/1 = 0.00%14941486
Bob Brownbobhihih14900.0/1 = 0.00%14971484
Urvish Desaiurvishdesai14900.0/1 = 0.00%14951486
ugo judeugojude14900.0/1 = 0.00%14951485
xerisianxxerisianx14900.0/1 = 0.00%14951485
John Badgerjbadger14900.0/1 = 0.00%14951484
wyatt wyattquimssarcasm14900.0/1 = 0.00%14971483
loveokenloveoken14900.0/1 = 0.00%14951484
Samuel Hoskinscouriergame14900.0/1 = 0.00%14951484
jesus babyboypokechamp14890.0/1 = 0.00%14971482
Steve Polleychessfan5914890.0/1 = 0.00%14951484
Milton Haddockmiltonhaddock14890.0/1 = 0.00%14961483
Hsa Saidh14890.0/1 = 0.00%14971481
makomako14890.0/1 = 0.00%14961482
Jason Stehlyjasonstehly14890.0/1 = 0.00%14951483
Esperllynmogik14890.0/1 = 0.00%14961482
Hafsteinn Kjartanssonhnr0114890.0/1 = 0.00%14961481
Éric Manálangedubble1914890.0/1 = 0.00%14951482
Anders Gustafsonancog14890.0/1 = 0.00%14961481
Matias I.tsatziq14890.0/1 = 0.00%14961481
Ben Reinigerbenr14880.0/1 = 0.00%14951481
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
Erlang Shenerlangshen14850.0/1 = 0.00%14891481
Nasmichael Farrismichaeljay14850.0/1 = 0.00%14881482
Luis Menendezpleyades2114850.0/1 = 0.00%14881482
Siwakorn Songragskyhistory14850.0/1 = 0.00%14871483
Gus Dunihoduniho14850.0/1 = 0.00%14891481
Travis Comptonironlance14850.0/1 = 0.00%14881481
Jacob Eugenioe45w14850.0/1 = 0.00%14871482
Doge Masterdogemaster14850.0/1 = 0.00%14881481
Julianredpanda148517.0/35 = 48.57%14641505
higuyzzz91028 Charles Kimdallastexas14840.0/1 = 0.00%14871481
Aurelian Floreacatugo1484250.5/713 = 35.13%15601408
Derek Mooseelevatorfarter14841.0/3 = 33.33%14841484
scythian blunderq1234514840.0/2 = 0.00%14891479
James Sprattwhittlin14840.0/1 = 0.00%14871481
Boyko Ahtarovzdra4148410.0/23 = 43.48%14911477
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
Jun Ocampojunpogi14830.0/2 = 0.00%14891478
Turk Osterburgtalen3141593141514830.0/1 = 0.00%14861481
Ronald Brierleybenwb14830.0/1 = 0.00%14841483
sixtysixty14830.0/3 = 0.00%14861480
dghanddghand14830.0/1 = 0.00%14841482
Solomon Salamasol71014830.0/1 = 0.00%14831483
anon anonchessvar114830.0/1 = 0.00%14851481
Antony Vailevichjabberw0cky114830.0/1 = 0.00%14831482
Paolo Porsiapillau14830.0/1 = 0.00%14851480
Dan Kellydankelly14830.0/1 = 0.00%14841481
Hung Daobyteboy14830.0/1 = 0.00%14841481
legendlegend14830.0/2 = 0.00%14911474
manolo manolomanolo14830.0/1 = 0.00%14841481
Andreas Bunkahlebunkahle14830.0/1 = 0.00%14831482
MichaÅ‚ Jarskihookz14830.0/1 = 0.00%14821483
wabbawabba14830.0/1 = 0.00%14841481
Jose Canceljoche14820.0/1 = 0.00%14831482
Tony Quintanillatony_quintanilla14820.0/1 = 0.00%14821483
Roberto Cassanotamerlano14820.0/1 = 0.00%14841481
btstwbtstw14820.0/1 = 0.00%14841481
cdpowercdpower14820.0/1 = 0.00%14841480
Uri Bruckbruck14820.0/2 = 0.00%14921473
László Gadosdani198314821.0/4 = 25.00%14781486
Nicholas Archerchess_hunter14820.0/2 = 0.00%14881477
anna colladoapatura_iris14820.0/1 = 0.00%14811482
Minh Dangminhdang14820.0/1 = 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
Giuseppe Acciarocoopwie14812.0/5 = 40.00%14761487
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
blundermanblunderman14810.0/1 = 0.00%14821480
Mark Thompsonmarkthompson14810.0/2 = 0.00%14931469
arcasorarcasor14800.0/1 = 0.00%14791481
Armin Liebhartlunaris148019.0/48 = 39.58%14531507
Diego M.diego14800.0/3 = 0.00%14851475
rederikrederik14800.0/1 = 0.00%14781481
championchampion14790.0/2 = 0.00%14841475
Bn Emnelk11414790.0/2 = 0.00%14831474
voicantvoicant14790.0/1 = 0.00%14761481
Ivan Kosintsevbombino14780.0/1 = 0.00%14751481
Francesco Casalinofrancesco14780.0/2 = 0.00%14841472
ologyology14780.0/1 = 0.00%14741481
andres fuentesxabyer14770.0/2 = 0.00%14801474
qidb602qidb60214770.0/2 = 0.00%14841470
trtztrtz gfghtrtztrtz14760.0/2 = 0.00%14801473
Frank Istvánistvan6014760.0/2 = 0.00%14861467
Alexander Krutikovlonewolf14761.0/4 = 25.00%14721479
Ivan Ivankillbill22514760.0/1 = 0.00%14701481
Francisco Magalhãeslowcarbknight14750.0/1 = 0.00%14691481
wdtrwdtr14750.0/3 = 0.00%14791471
tedy efwttei27fmrw7de14750.0/1 = 0.00%14681482
John Twycrossjt14740.0/2 = 0.00%14741474
Szling Ozecszling_ozec14740.0/3 = 0.00%14771471
Charles Gilmancharles_gilman14740.0/2 = 0.00%14731474
Lennon Figueiredogiwseppe14731.0/4 = 25.00%14711476
Pablo Denegrideep_thinker14730.0/2 = 0.00%14761471
Sergey Biryukovsbiryukov14720.0/4 = 0.00%14731472
Jean-Louis Cazauxtimurthelenk14711.0/5 = 20.00%14711472
Pat Quexionezsuperpatzermaste14710.0/4 = 0.00%14741469
Steve Hsteve_201014710.0/2 = 0.00%14681473
Travis Comptonblackrood14700.0/2 = 0.00%14701471
Kacper Rutkowskikacperrutkowski14700.0/2 = 0.00%14731467
dfe6631dfe663114700.0/2 = 0.00%14661474
Zoli M Zoltánbaltazarprof14700.0/5 = 0.00%14831457
Daniel MacDuffdanielmacduff14700.0/3 = 0.00%14671472
andrewthepawnandrewthepawn14690.0/2 = 0.00%14671472
iuchi45iuchi4514690.0/2 = 0.00%14711468
Adam DeWittchessshogi14690.0/3 = 0.00%14751462
A tomiatomi14684.5/16 = 28.12%14611475
jeremy diniericharles_bukowski14680.0/2 = 0.00%14661469
cherokee malansailorhertzog14680.0/2 = 0.00%14711464
Memedes Lulagiwseppe314670.0/2 = 0.00%14691466
Zac Sparxkrinid14660.0/2 = 0.00%14681465
Donut Donutdonutdonut14660.0/2 = 0.00%14661465
Scott Crawfordmathemagician14650.0/7 = 0.00%14751455
playshogiplayshogi14640.0/2 = 0.00%14661463
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%14501467
Nick Wolffwolff145626.0/72 = 36.11%14131499
louisvlouisv14550.0/3 = 0.00%14571453
Graemegraemecn14550.0/3 = 0.00%14541457
Andy Lewickiondraszek14550.0/3 = 0.00%14481461
Paul Rapoportnumerist14530.0/4 = 0.00%14571449
Николай Сокольскийalexich14520.0/4 = 0.00%14561448
John Langleyjonners14520.5/4 = 12.50%14521451
Вадря Покштяpokshtya14523.0/10 = 30.00%14481455
Dayrom Gilallahukbar14510.0/3 = 0.00%14511452
Michael Schmahlmschmahl14515.0/15 = 33.33%14601441
Scott McGrealagentofchaos14497.0/19 = 36.84%14511447
Joshua Tsamraku14495.0/12 = 41.67%14281470
Linn Russellfreakat14490.0/3 = 0.00%14491449
Aaron Maynardvopi14481.0/6 = 16.67%14441452
Adalbertus Kchewoj14471.0/5 = 20.00%14411454
vitaliy ravitztalsterch14462.0/15 = 13.33%14341458
Jeremy Goodjudgmentality144543.5/127 = 34.25%14351454
heche60heche6014432.0/12 = 16.67%14451442
Sagi Gabaysagig7214390.5/16 = 3.12%14231455
dmitarzvonimirdmitarzvonimir14390.0/5 = 0.00%14341443
Evan Jorgensonsabataegalo14370.0/7 = 0.00%14241451
Phoenix TKartkr10101014332.0/9 = 22.22%14361430
Evert Jan Karmanevertvb14332.5/11 = 22.73%14211446
Jon Dannjon_dann14300.0/4 = 0.00%14271433
juan rodriguezrodriguez142611.5/38 = 30.26%14421410
Matthew La Valleesherman10114256.0/23 = 26.09%14161434
boukineboukine14234.0/13 = 30.77%13981447
Alan Galetornadic14223.0/20 = 15.00%14191424
Jack Zavierubersketch14210.0/6 = 0.00%14181425
Daniil Frolovflowermann14203.0/16 = 18.75%14061434
Arthur Yvrardtorendil14160.0/7 = 0.00%14111421
Jeremy Hook10011014132.0/30 = 6.67%14141412
George Dukegwduke141142.5/117 = 36.32%13511471
John Davischappy14113.0/17 = 17.65%14001422
Samuel de Souzasamsou14110.0/8 = 0.00%14111411
yellowturtleyellowturtle14100.0/10 = 0.00%14131407
Evan Jorgensonejorgens14090.0/7 = 0.00%14001419
Митя Стрелецкийsocrat8314010.0/10 = 0.00%13901411
darren paullramalam139613.5/100 = 13.50%13681423
Bogot Bogotolbog138912.0/44 = 27.27%13781401
Jarid Carlsonsacredchao138213.0/68 = 19.12%13381425
Nakanaka13600.0/11 = 0.00%13441375
Сергей Маэстроfantomas13541.0/31 = 3.23%13761332
Diogen Abramelindanko13340.0/35 = 0.00%13211347
Richard milnersesquipedalian13306.0/46 = 13.04%13311329
Oisín D.sxg131842.0/189 = 22.22%12951342
per hommerbergper3112962.0/52 = 3.85%12731320
Сергей Бугаевскийbugaevsky12953.0/56 = 5.36%12751316
Alisher Bolsaniraja8512880.0/46 = 0.00%12711304
wdtr2wdtr2127920.5/145 = 14.14%12581300

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