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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:69.13%68.65%68.13%
NameUseridGCRPercent wonGCR1GCR2
Hexa Sakkbosa601859136.5/151 = 90.40%18251893
Francis Fahystamandua1845247.0/298 = 82.89%18291861
dax00dax001818146.0/152 = 96.05%18111825
Kevin Paceypanther1786449.0/549 = 81.79%17961776
Carlos Cetinasissa1732603.5/947 = 63.73%17251738
Cameron Milesshatteredglass171115.0/17 = 88.24%17011720
Jochen Muellerleopold_stotch170155.0/92 = 59.78%16801722
H Spetyura168213.0/13 = 100.00%16791686
Gary Giffordpenswift167860.5/85 = 71.18%15791777
Play Testerplaytester167218.5/25 = 74.00%16711673
Jose Carrilloj_carrillo_vii166387.5/155 = 56.45%16691657
Fergus Dunihofergus166259.5/97 = 61.34%16621661
David Paulowichdavid_64162411.0/13 = 84.62%16241623
shift2shiftshift2shift162011.0/19 = 57.89%16251615
Tim O'Lenatim_olena16156.5/8 = 81.25%16181612
Charles Danielfrozen_methane161435.0/64 = 54.69%15851644
Homo Simiaalienum16147.0/8 = 87.50%16051623
Vitya Makovmakov16137.5/8 = 93.75%16121613
Vitya Makovmakov3331608316.0/707 = 44.70%15591658
Andreas Kaufmannandreas16077.0/7 = 100.00%16091605
Pericles Tesone de Souzaperitezz15888.0/8 = 100.00%15881588
ctzctz157912.0/17 = 70.59%15561603
kokoszkokosz15787.0/8 = 87.50%15611595
erikerik1577140.5/259 = 54.25%16181535
Abdul-Rahman Sibahisibahi157516.0/23 = 69.57%15641586
attack hippoattackhippo15745.5/7 = 78.57%15711578
je jujejujeju157336.5/60 = 60.83%15661580
Alexander Trotterqilin15704.0/4 = 100.00%15691571
Stephen Stockmanstevestockman156810.0/16 = 62.50%15721564
Jenard Cabilaomgawalangmagawa156811.0/23 = 47.83%15791556
TH6notath615667.0/12 = 58.33%15611572
Raymond Dlewel156013.0/22 = 59.09%15771543
Thor Slavenskyslavensky15595.0/7 = 71.43%15391579
Isaac Felpsattacker14415585.0/6 = 83.33%15591557
John Gallantbigjohn155716.0/28 = 57.14%15421571
Greg Strongmageofmaple155693.0/194 = 47.94%16081504
Nicholas Wolffnwolff15559.0/15 = 60.00%15731536
Nicola Caridiniccar15543.0/3 = 100.00%15571550
Roberto Lavierirlavieri200315493.0/3 = 100.00%15441555
pallab basupallab154531.0/60 = 51.67%15321558
Daniel Zachariasarx154344.0/91 = 48.35%15251561
S Ssim15436.0/9 = 66.67%15311554
carlos carloscarlos154116.0/27 = 59.26%15181565
michirmichir15402.0/2 = 100.00%15411540
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%15271540
Nicholas Wolffmaeko153365.5/142 = 46.13%15591507
Matthew Montchalinmatthew_montchal15313.0/4 = 75.00%15291533
Jake Palladinocerebralassassin15312.0/2 = 100.00%15271534
Julien Coll Moratfacteurix15302.0/3 = 66.67%15291532
Fred Koktangram15282.0/3 = 66.67%15291528
Joseph DiMurotrojh15281.0/1 = 100.00%15331523
joe rosenbloombootzilla15282.0/3 = 66.67%15231533
Uwe Kreuzercaissus15272.0/2 = 100.00%15241530
Yeinzon Rodríguez Garcíayeinzon15241.0/1 = 100.00%15281519
Adrian Alvarez de la Campaadrian15233.5/6 = 58.33%15231524
Chuck Leegyw6t152217.5/39 = 44.87%15141531
von raidervonraider15201.0/1 = 100.00%15211519
Larry Wheelerbrainburner15201.0/1 = 100.00%15211519
dicepawndicepawn15191.0/1 = 100.00%15211518
Joe Joycejoejoyce151920.5/57 = 35.96%14771561
Todor Tchervenkovtchervenkov15181.0/1 = 100.00%15181519
Garrett Smithgmsmith15181.0/2 = 50.00%15231513
Richard Titlertitle15181.0/1 = 100.00%15191518
yas kumkumagai15181.0/1 = 100.00%15181518
eunchong leeeunchong15181.0/1 = 100.00%15181518
whitenerdy53whitenerdy5315181.0/1 = 100.00%15181518
Angel47 Usmanangel4715181.0/1 = 100.00%15181518
David Levinsmidrael15181.0/1 = 100.00%15181518
Antonio Bruzzitotonno_janggi15181.0/1 = 100.00%15181518
calebblazecalebblaze15181.0/1 = 100.00%15181518
Trevor Savagesavage15181.0/1 = 100.00%15181518
jj15181.0/1 = 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
Aaron Smithzirtoc15162.5/5 = 50.00%15131519
Leon Careyleoncarey15161.0/1 = 100.00%15141518
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
xxmanxxman15151.0/2 = 50.00%15161513
spiptorben15111.0/2 = 50.00%15121510
Nathanlokor15101.0/2 = 50.00%15101509
Antoine Fourrièreantoinefourriere15091.5/2 = 75.00%15081511
mystery playercentipede15092.0/5 = 40.00%15111507
pheko Motaungcouriermabovini150935.5/70 = 50.71%15621455
Georg Spengleravunjahei15089.0/28 = 32.14%15021515
xeongreyxeongrey15078.0/17 = 47.06%15101504
Anthony Viensstarkiller15072.0/4 = 50.00%15001513
Zachary Wadeazost1215063.0/5 = 60.00%14991513
As Bardhiasbardhi15051.0/2 = 50.00%15091501
Gee Beegdimension15031.0/2 = 50.00%15031502
Christine Bagley-Joneszcherryz15020.5/1 = 50.00%15051500
Colin Adamslionhawk15021.0/2 = 50.00%15051500
Graeme Neathamgrayhawke15021.0/2 = 50.00%15001504
Albert Vámosiblackrider_4815021.0/4 = 25.00%15161488
Tom Trenchtomdench9515010.5/1 = 50.00%15021501
Hans Henrikssonhasurami15012.0/4 = 50.00%14911512
Kent Weschlerperplexedibex15001.0/3 = 33.33%14981502
Colin Weaveruselessgit14981.0/4 = 25.00%14991498
Thom Dimentunwiseowl14982.0/5 = 40.00%15001496
noy noynoy14983.0/7 = 42.86%14901506
Juan Pablo Schweitzer Kirsingerdefender14971.0/2 = 50.00%14941500
Eni Lienili149611.5/46 = 25.00%15141478
John Smithultimatecoolster14943.0/9 = 33.33%14941495
Max Fengwowimbob111214941.0/3 = 33.33%14961492
Anders Gustafsonancog14920.0/1 = 0.00%14961488
Michael Christensenjustsojazz14920.0/1 = 0.00%14961488
kunkunkunkun14920.0/1 = 0.00%14961487
Fabner Cruz Gracilianofabner14910.0/1 = 0.00%14961486
jesus babyboypokechamp14910.0/1 = 0.00%14961486
Hsa Saidh14910.0/1 = 0.00%14951486
Bob Brownbobhihih14910.0/1 = 0.00%14951486
wyatt wyattquimssarcasm14900.0/1 = 0.00%14961485
Hugo Mendes-Nuneshugo199514900.0/1 = 0.00%14961484
Urvish Desaiurvishdesai14900.0/1 = 0.00%14941486
don anezdonanez14900.0/1 = 0.00%14961484
Jason Stehlyjasonstehly14900.0/1 = 0.00%14941485
vikvik14890.0/1 = 0.00%14961483
Éric Manálangedubble1914890.0/1 = 0.00%14941484
Matias I.tsatziq14890.0/1 = 0.00%14951484
hubergerdhubergerd14890.0/1 = 0.00%14961482
Hafsteinn Kjartanssonhnr0114890.0/1 = 0.00%14961482
Steve Polleychessfan5914890.0/1 = 0.00%14941484
Samuel Hoskinscouriergame14890.0/1 = 0.00%14951483
DFA Productions70nyd014890.0/1 = 0.00%14961481
loveokenloveoken14890.0/1 = 0.00%14941483
makomako14890.0/1 = 0.00%14961481
John Badgerjbadger14890.0/1 = 0.00%14951482
potato imaginatorpotato14880.0/1 = 0.00%14951482
ugo judeugojude14880.0/1 = 0.00%14951481
xerisianxxerisianx14880.0/1 = 0.00%14951481
DJ Linickdjlinick14870.0/1 = 0.00%14921483
LuigiMaster285qqzlbpdilchr14870.0/1 = 0.00%14921482
Rob Brownsteelhead14870.0/1 = 0.00%14911482
Ivan Velascoswordandsilver14860.0/1 = 0.00%14911481
Mike Smolowitzmjs170114850.0/1 = 0.00%14891482
Brock Sampsonthe_iron_kenyan14850.0/1 = 0.00%14881483
Bradlee Kingstonbrad1914850.0/1 = 0.00%14891481
Luis Menendezpleyades2114850.0/1 = 0.00%14881482
Gus Dunihoduniho14850.0/1 = 0.00%14871483
Travis Comptonironlance14850.0/1 = 0.00%14891481
Nasmichael Farrismichaeljay14850.0/1 = 0.00%14881482
Erlang Shenerlangshen14850.0/1 = 0.00%14891481
Andy Thomasandy_thomas14850.0/1 = 0.00%14881481
Derek Mooseelevatorfarter14841.0/3 = 33.33%14841484
James Sprattwhittlin14840.0/1 = 0.00%14871481
Alexandr Kremenakremen14840.0/1 = 0.00%14861481
yi fang liuliuyifang14840.0/1 = 0.00%14851482
andy lewickiherlocksholmes14840.0/1 = 0.00%14861481
Turk Osterburgtalen3141593141514840.0/1 = 0.00%14861481
Jeremy Goodyamorezu14830.0/1 = 0.00%14861481
scythian blunderq1234514830.0/2 = 0.00%14871479
Solomon Salamasol71014830.0/1 = 0.00%14831483
Julianredpanda148317.0/35 = 48.57%14641502
Antony Vailevichjabberw0cky114830.0/1 = 0.00%14841482
kittredge Drakedghand14830.0/1 = 0.00%14831482
Dan Kellydankelly14830.0/1 = 0.00%14841481
manolo manolomanolo14830.0/1 = 0.00%14841481
Jose Canceljoche14830.0/1 = 0.00%14821483
Nicholas Archerchess_hunter14830.0/2 = 0.00%14861479
MichaÅ‚ Jarskihookz14830.0/1 = 0.00%14831482
Ronald Brierleybenwb14830.0/1 = 0.00%14841481
Hung Daobyteboy14830.0/1 = 0.00%14841481
btstwbtstw14820.0/1 = 0.00%14841481
Andreas Bunkahlebunkahle14820.0/1 = 0.00%14831482
Roberto Cassanotamerlano14820.0/1 = 0.00%14841481
Tony Quintanillatony_quintanilla14820.0/1 = 0.00%14831481
cdpowercdpower14820.0/1 = 0.00%14831481
Paolo Porsiapillau14820.0/1 = 0.00%14841480
Uri Bruckbruck14820.0/2 = 0.00%14911473
sixtysixty14820.0/3 = 0.00%14881476
Jun Ocampojunpogi14820.0/2 = 0.00%14891475
anna colladoapatura_iris14820.0/1 = 0.00%14811482
luigi mattagigino4214820.0/1 = 0.00%14811482
Thomas Meehanorangeaurochs14820.0/1 = 0.00%14801483
Joseph Grangercdafan14820.0/1 = 0.00%14821481
Minh Dangminhdang14820.0/1 = 0.00%14811482
Виктор Байгужаковbajvik14820.0/1 = 0.00%14811482
Robin Sneijderrobinwooter214820.0/1 = 0.00%14821481
Jean-Louis Cazauxtimurthelenk14820.0/1 = 0.00%14821481
Giuseppe Acciarocoopwie14822.0/5 = 40.00%14761487
ben chewben558214810.0/1 = 0.00%14811481
14810.0/1 = 0.00%14811481
wonsang leewonsang14810.0/1 = 0.00%14811481
y kumyasuhiro14810.0/1 = 0.00%14811481
paulblazepaulblaze14810.0/1 = 0.00%14811481
Babo Jeffbabojeff14810.0/1 = 0.00%14811481
Ryan Schwartzshunoshi14810.0/1 = 0.00%14811481
Vitali Maslanskivitali_1014810.0/1 = 0.00%14811481
Harry Gaoharrygao14810.0/1 = 0.00%14811481
Mark Thompsonmarkthompson14810.0/2 = 0.00%14921471
blundermanblunderman14810.0/1 = 0.00%14811481
Abe Anonapostateabe14810.0/1 = 0.00%14811481
Aurelian Floreacatugo1481237.5/661 = 35.93%15651397
legendlegend14810.0/2 = 0.00%14901472
Boyko Ahtarovzdra4148110.0/23 = 43.48%14751487
László Gadosdani198314811.0/4 = 25.00%14781484
Diego M.diego14800.0/3 = 0.00%14831478
arcasorarcasor14800.0/1 = 0.00%14791481
Bn Emnelk11414800.0/2 = 0.00%14831477
Francesco Casalinofrancesco14800.0/2 = 0.00%14821477
rederikrederik14800.0/1 = 0.00%14791480
championchampion14790.0/2 = 0.00%14831475
voicantvoicant14790.0/1 = 0.00%14771480
qidb602qidb60214780.0/2 = 0.00%14841472
Ivan Kosintsevbombino14780.0/1 = 0.00%14741481
ologyology14780.0/1 = 0.00%14741481
andres fuentesxabyer14760.0/2 = 0.00%14791474
Armin Liebhartlunaris147619.0/44 = 43.18%14811471
wdtrwdtr14760.0/3 = 0.00%14781474
Alexander Krutikovlonewolf14761.0/4 = 25.00%14731479
Ivan Ivankillbill22514760.0/1 = 0.00%14701481
Frank Istvánistvan6014760.0/2 = 0.00%14861466
trtztrtz gfghtrtztrtz14750.0/2 = 0.00%14801470
tedy efwttei27fmrw7de14750.0/1 = 0.00%14681481
Francisco Magalhãeslowcarbknight14750.0/1 = 0.00%14671482
Charles Gilmancharles_gilman14740.0/2 = 0.00%14751473
Pablo Denegrideep_thinker14730.0/2 = 0.00%14761471
Lennon Figueiredogiwseppe14731.0/4 = 25.00%14711476
Szling Ozecszling_ozec14730.0/3 = 0.00%14771469
John Twycrossjt14730.0/2 = 0.00%14741472
Pat Quexionezsuperpatzermaste14700.0/4 = 0.00%14711469
Travis Comptonblackrood14700.0/2 = 0.00%14681472
Kacper Rutkowskikacperrutkowski14700.0/2 = 0.00%14741466
andrewthepawnandrewthepawn14700.0/2 = 0.00%14661474
dfe6631dfe663114700.0/2 = 0.00%14671472
Zoli M Zoltánbaltazarprof14690.0/5 = 0.00%14821457
Sergey Biryukovsbiryukov14690.0/4 = 0.00%14731466
Steve Hsteve_201014690.0/2 = 0.00%14691469
Adam DeWittchessshogi14680.0/3 = 0.00%14741462
Daniel MacDuffdanielmacduff14680.0/3 = 0.00%14691466
Memedes Lulagiwseppe314670.0/2 = 0.00%14691466
cherokee malansailorhertzog14670.0/2 = 0.00%14711464
jeremy diniericharles_bukowski14670.0/2 = 0.00%14661468
A tomiatomi14674.5/16 = 28.12%14581475
Zac Sparxkrinid14660.0/2 = 0.00%14691464
iuchi45iuchi4514660.0/2 = 0.00%14651467
Donut Donutdonutdonut14650.0/2 = 0.00%14661465
playshogiplayshogi14640.0/2 = 0.00%14661463
Scott Crawfordmathemagician14640.0/7 = 0.00%14731455
Michael Nelsonmikenels14640.0/2 = 0.00%14611466
michael collinsverderben14631.0/5 = 20.00%14691457
Namik Zadenamik14630.0/2 = 0.00%14611465
andy lewickietaoni14630.0/2 = 0.00%14631463
Michael Huntkronsteen3314580.0/3 = 0.00%14501467
louisvlouisv14550.0/3 = 0.00%14581453
Graemegraemecn14550.0/3 = 0.00%14521458
Andy Lewickiondraszek14530.0/3 = 0.00%14481459
Николай Сокольскийalexich14520.0/4 = 0.00%14551449
John Langleyjonners14520.5/4 = 12.50%14521451
Dayrom Gilallahukbar14520.0/3 = 0.00%14501454
Michael Schmahlmschmahl14505.0/15 = 33.33%14591441
Joshua Tsamraku14495.0/12 = 41.67%14241474
Linn Russellfreakat14490.0/3 = 0.00%14491449
Adalbertus Kchewoj14481.0/5 = 20.00%14431454
Scott McGrealagentofchaos14487.0/19 = 36.84%14491447
Aaron Maynardvopi14471.0/6 = 16.67%14431451
Nick Wolffwolff144625.0/71 = 35.21%14151477
vitaliy ravitztalsterch14452.0/15 = 13.33%14351456
heche60heche6014422.0/12 = 16.67%14421442
boukineboukine14394.0/12 = 33.33%14181461
Sagi Gabaysagig7214390.5/16 = 3.12%14181460
dmitarzvonimirdmitarzvonimir14390.0/5 = 0.00%14341444
Jeremy Goodjudgmentality143743.5/127 = 34.25%14281445
Evert Jan Karmanevertvb14352.5/11 = 22.73%14191451
Evan Jorgensonsabataegalo14340.0/7 = 0.00%14281441
Phoenix TKartkr10101014332.0/9 = 22.22%14351430
Jon Dannjon_dann14300.0/4 = 0.00%14261433
juan rodriguezrodriguez142911.5/38 = 30.26%14431416
Matthew La Valleesherman10114276.0/23 = 26.09%14091445
Jack Zavierubersketch14220.0/6 = 0.00%14191426
Alan Galetornadic14223.0/20 = 15.00%14171427
Daniil Frolovflowermann14193.0/16 = 18.75%14041433
Arthur Yvrardtorendil14160.0/7 = 0.00%14111421
Jeremy Hook10011014112.0/30 = 6.67%14091413
Samuel de Souzasamsou14110.0/8 = 0.00%14111411
yellowturtleyellowturtle14090.0/10 = 0.00%14111408
John Davischappy14093.0/17 = 17.65%14061412
Evan Jorgensonejorgens14080.0/7 = 0.00%13991417
Alisher Bolsaniraja8514010.0/9 = 0.00%14071394
George Dukegwduke139942.5/117 = 36.32%13491450
darren paullramalam139813.5/100 = 13.50%13601436
Митя Стрелецкийsocrat8313960.0/10 = 0.00%13941398
Bogot Bogotolbog138212.0/44 = 27.27%13631401
Jarid Carlsonsacredchao138013.0/68 = 19.12%13451414
Сергей Маэстроfantomas13420.0/30 = 0.00%13521332
Diogen Abramelindanko13310.0/35 = 0.00%13131349
Oisín D.sxg131241.0/184 = 22.28%12811344
per hommerbergper3113042.0/48 = 4.17%12881319
Сергей Бугаевскийbugaevsky12923.0/56 = 5.36%12791306
wdtr2wdtr2127718.5/136 = 13.60%12411312

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