Chiefs
GP: 82 | W: 42 | L: 31 | T: 7 | P: 93
GF: 261 | GA: 262 | PP%: 22.22% | PK%: 82.03%
DG: Christian Cheminais | Morale : 67 | Moyenne d'Équipe : 65
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Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire
1Slava Kozlov (R)X100.006844777569746875607373807045457090680223600,000$
2Jiri Dopita (R)X100.004537766678676880718176696844486885670263400,000$
3Randy Cunneyworth (C)X100.007262586770717169626665806378851780670332600,000$
4Chris TancillX100.007156717071707173597372696443506853660261531,000$
5Brad DalgarnoX100.006748836279707271627267816051516185660271185,000$
6Jim DowdX100.005744776873707267657568786439486185650272200,000$
7Len BarrieX100.005959496975687068647472676841547434650251295,000$
8Mick VukotaX100.008983376475818358626955825256545370650281365,000$
9Shane Churla (A)X100.009892276475747464627052775065704782650293500,000$
10Nick KypreosX100.009285366277747662616460805852505544640282450,000$
11Rob Niedermayer (R)X100.007060757362777570806361776335458028640203250,000$
12Donald Brashear (R)X100.008895306785817362526361706035458063630223250,000$
13Keith BrownX100.00645176597272736358614985487977962670342200,000$
14Glenn FeatherstoneX100.008779436679737358525749854744516887670263635,000$
15Brian BenningX100.006753676669867466627148814454585562670281100,000$
16Donald DufresneX100.007153716376697069626957835252476059660272468,000$
17Bob BeersX100.007351786674697064647655805247476085660274560,000$
18Jiri Slegr (R)X100.005846736677717370647364826036348985650231380,000$
Rayé
1Mark LambX100.007661676869757675687564785965663951680301458,000$
2Brian Propp (A)X100.00655172637163637667757866728182159680351600,000$
3Bobby HolikX100.007458656781747671677369826830328975670231550,000$
4Michel Picard (R)X100.005644817173666869636968646640517619630252450,000$
5Jeff Odgers (R)X100.009395306085807763546262606637557020620253250,000$
6Rob RayX100.009089256476666860565663816232326820610261350,000$
7Marc PotvinX100.007469516174636659586151705040425320590281200,000$
8Grant MarshallX100.006355686470606257566057675627279820570213500,000$
9Davis Payne (R)X100.007770496374606252505460586033288220560242150,000$
10Jason YorkX100.006449727175727472657568756233348273650241250,000$
11Frantisek KuceraX100.006450766775727463627250784827336851640262400,000$
MOYENNE D'ÉQUIPE100.00726261667471716662686275594650625765
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Felix Potvin (R)100.00737981808176848582787638388837730
2Mike Dunham (R)100.00687676787372828279717129359772690
Rayé
1Jamie McLennan100.00687271747060667667696738348920630
MOYENNE D'ÉQUIPE100.0070767677756977817673713536914368
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Marc Crawford78757976748589CAN33295,000$


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Jiri DopitaChiefs (QUE)C82264066300101551995514313.07%13143117.46819273921700032325153.72%143900000.9200000531
2Brad DalgarnoChiefs (QUE)RW82343064122054782135614415.96%7133516.2912162864333000006144.44%9900010.9600000474
3Bob BeersChiefs (QUE)D82650563600120797735577.79%112182522.2622022523160001327100.00%000000.6100000232
4Glenn FeatherstoneChiefs (QUE)D82134255618953298598348313.27%92190423.2272027573510110294200.00%000000.5800100264
5Mark LambChiefs (QUE)C69242953-66401491751744113213.79%17147821.426121847276000103176149.37%165700000.7200000463
6Randy CunneyworthChiefs (QUE)LW82163450-9675114109173501409.25%9150218.32515203627310152062051.38%18100000.6700010212
7Donald DufresneChiefs (QUE)D6773441-352075979125537.69%75146521.8751116542320000247120.00%000000.5600000120
8Brian ProppChiefs (QUE)LW57211738-24042901342910115.67%7124921.9376132921810132694252.47%66900000.6100000308
9Jason YorkChiefs (QUE)D75132437-14700809175286917.33%79136118.158614381280000183330.00%000000.5400000412
10Bobby HolikChiefs (QUE)C75161935-816064140165431349.70%17119015.8856113314602231351151.90%126600100.5900000221
11Bobby CarpenterNordiquesC458253336029109123321066.50%089119.8211213301840002980054.72%114400000.7400000151
12Slava KozlovChiefs (QUE)LW2862632616037607119718.45%360221.521782111900011101047.66%12800001.0600000113
13Chris TancillChiefs (QUE)RW58112132-112205641109339410.09%296516.6521315252490002301043.66%7100000.6600000113
14Jiri SlegrChiefs (QUE)D8252126-1352081847318496.85%74138116.85358291180000127100.00%000000.3800000120
15Mick VukotaChiefs (QUE)RW76121325-4110101656383277114.46%492712.2043710850000102043.08%6500010.5400011204
16Jim DowdChiefs (QUE)C829152400049810725708.41%77058.60123490000501150.55%73000000.6800000021
17Brian BenningChiefs (QUE)D22516211124032222481320.83%2248722.1555101994011191000.00%000000.8600000102
18Frantisek KuceraChiefs (QUE)D6071017-1348091513171422.58%4595415.913036110001122020.00%000000.3600000210
19Keith BrownChiefs (QUE)D226101640032235101417.14%2253524.3251622980000105010.00%000000.6000000011
20Shane ChurlaChiefs (QUE)RW795712-67810105336820427.35%75997.5901115000002056.25%4800000.4000011111
21Donald BrashearChiefs (QUE)LW585611241557245111259.80%45118.81000000000361046.34%4100000.4300100000
22Nick KypreosChiefs (QUE)LW4937103581073232893510.71%458511.941014420000310055.00%4000000.3400002101
23Len BarrieChiefs (QUE)C3554902011182371321.74%22416.892246470000201047.03%18500000.7500000000
24Michel PicardChiefs (QUE)LW36538-102002738183013.16%33419.4900000000051045.00%2000000.4700000000
25Jeff OdgersChiefs (QUE)RW261121220441921111.11%22328.9400001000000021.43%1400000.1700000000
26Rob RayChiefs (QUE)RW3011160710010.00%0268.700000000000000.00%000000.7700000000
27Rob NiedermayerChiefs (QUE)C701100012033100.00%18612.40000000000360062.20%12700000.2300000000
Stats d'équipe Total ou en Moyenne1521269506775-55103145183317962275645172511.82%6302481816.32931822756263564246323093421551.70%792400120.6200234404544
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien Nom de l'ÉquipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Felix PotvinChiefs (QUE)75372960.8813.18419010122218680500.0000739330
2Mike DunhamChiefs (QUE)195410.8893.1376740403590100.0000973110
Stats d'équipe Total ou en Moyenne94423370.8823.17495714126222270600.00008282440


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Bob BeersChiefs (QUE)D271994-02-09 9:08:37 PMNo200 Lbs6 ft2NoNoNo4Pro & Farm560,000$56,000$412$No560,000$560,000$560,000$
Bobby HolikChiefs (QUE)C231998-02-09 9:08:37 PMNo225 Lbs6 ft3NoNoNo1Pro & Farm550,000$55,000$404$No
Brad DalgarnoChiefs (QUE)RW271994-02-09 9:08:37 PMNo215 Lbs6 ft3NoNoNo1Pro & Farm185,000$18,500$136$No
Brian BenningChiefs (QUE)D281993-02-09 9:08:37 PMNo175 Lbs6 ft0NoNoNo1Pro & Farm100,000$10,000$74$No
Brian ProppChiefs (QUE)LW351986-02-09 9:08:37 PMNo190 Lbs5 ft9NoNoNo1Pro & Farm600,000$60,000$441$No
Chris TancillChiefs (QUE)RW261995-02-09 9:08:37 PMNo185 Lbs5 ft10NoNoNo1Pro & Farm531,000$53,100$390$No
Davis PayneChiefs (QUE)RW241997-02-09 9:08:37 PMYes190 Lbs6 ft1NoNoNo2Pro & Farm150,000$15,000$110$No150,000$
Donald BrashearChiefs (QUE)LW221998-08-11 9:38:29 AMYes237 Lbs6 ft3NoNoNo3Pro & Farm250,000$25,000$184$No250,000$250,000$
Donald DufresneChiefs (QUE)D271994-02-09 9:08:37 PMNo206 Lbs6 ft1NoNoNo2Pro & Farm468,000$46,800$344$No468,000$
Felix PotvinChiefs (QUE)G231998-02-09 9:08:37 PMYes190 Lbs6 ft1NoNoNo1Pro & Farm400,000$40,000$294$No
Frantisek KuceraChiefs (QUE)D261995-02-09 9:08:37 PMNo205 Lbs6 ft2NoNoNo2Pro & Farm400,000$40,000$294$No400,000$
Glenn FeatherstoneChiefs (QUE)D261995-02-09 9:08:37 PMNo215 Lbs6 ft4NoNoNo3Pro & Farm635,000$63,500$467$No635,000$635,000$
Grant MarshallChiefs (QUE)RW212000-02-09 9:08:37 PMNo185 Lbs6 ft1NoNoNo3Pro & Farm500,000$50,000$368$No500,000$500,000$
Jamie McLennanChiefs (QUE)G231998-02-09 9:08:37 PMNo190 Lbs6 ft0NoNoNo1Pro & Farm150,000$15,000$110$No
Jason YorkChiefs (QUE)D241997-02-09 9:08:37 PMNo200 Lbs6 ft2NoNoNo1Pro & Farm250,000$25,000$184$No
Jeff OdgersChiefs (QUE)RW251995-08-11 9:32:17 AMYes200 Lbs6 ft0NoNoNo3Pro & Farm250,000$25,000$184$No250,000$250,000$
Jim DowdChiefs (QUE)C271994-02-09 9:08:37 PMNo190 Lbs6 ft1NoNoNo2Pro & Farm200,000$20,000$147$No200,000$
Jiri DopitaChiefs (QUE)C261995-02-09 9:08:37 PMYes213 Lbs6 ft3NoNoNo3Pro & Farm400,000$40,000$294$No400,000$400,000$
Jiri SlegrChiefs (QUE)D231998-02-09 9:08:37 PMYes216 Lbs6 ft1NoNoNo1Pro & Farm380,000$38,000$279$No
Keith BrownChiefs (QUE)D341987-02-09 9:08:37 PMNo191 Lbs6 ft1NoNoNo2Pro & Farm200,000$20,000$147$No200,000$
Len BarrieChiefs (QUE)C251996-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo1Pro & Farm295,000$29,500$217$No
Marc PotvinChiefs (QUE)C281993-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo1Pro & Farm200,000$20,000$147$No
Mark LambChiefs (QUE)C301991-02-09 9:08:37 PMNo179 Lbs5 ft9NoNoNo1Pro & Farm458,000$45,800$337$No
Michel PicardChiefs (QUE)LW251996-02-09 9:08:37 PMYes190 Lbs5 ft11NoNoNo2Pro & Farm450,000$45,000$331$No450,000$
Mick VukotaChiefs (QUE)RW281993-02-09 9:08:37 PMNo195 Lbs6 ft2NoNoNo1Pro & Farm365,000$36,500$268$No
Mike DunhamChiefs (QUE)G221999-02-09 9:08:37 PMYes195 Lbs6 ft3NoNoNo1Pro & Farm400,000$40,000$294$No
Nick KypreosChiefs (QUE)LW281993-02-09 9:08:37 PMNo210 Lbs6 ft0NoNoNo2Pro & Farm450,000$45,000$331$No450,000$
Randy CunneyworthChiefs (QUE)LW331988-02-09 9:08:37 PMNo180 Lbs6 ft0NoNoNo2Pro & Farm600,000$60,000$441$No600,000$
Rob NiedermayerChiefs (QUE)C202000-08-11 9:28:24 AMYes200 Lbs6 ft2NoNoNo3Pro & Farm250,000$25,000$184$No250,000$250,000$
Rob RayChiefs (QUE)RW261995-02-09 9:08:37 PMNo216 Lbs6 ft0NoNoNo1Pro & Farm350,000$35,000$257$No
Shane ChurlaChiefs (QUE)RW291992-02-09 9:08:37 PMNo201 Lbs6 ft1NoNoNo3Pro & Farm500,000$50,000$368$No500,000$500,000$
Slava KozlovChiefs (QUE)LW221999-02-09 9:08:37 PMYes180 Lbs5 ft10NoNoNo3Pro & Farm600,000$600,000$4,412$No600,000$600,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3226.03199 Lbs6 ft11.84377,406$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Slava KozlovJiri DopitaChris Tancill35014
2Randy CunneyworthJim DowdBrad Dalgarno30122
3Nick KypreosLen BarrieShane Churla20122
4Donald BrashearRob NiedermayerMick Vukota15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Keith BrownGlenn Featherstone35122
2Brian BenningBob Beers30122
3Jiri SlegrDonald Dufresne20122
4Keith BrownGlenn Featherstone15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Slava KozlovLen BarrieChris Tancill60122
2Randy CunneyworthJiri DopitaBrad Dalgarno40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Keith BrownGlenn Featherstone60122
2Brian BenningBob Beers40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Rob NiedermayerChris Tancill60122
2Jiri DopitaRandy Cunneyworth40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Keith BrownGlenn Featherstone60122
2Brian BenningBob Beers40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Slava Kozlov60122Keith BrownGlenn Featherstone60122
2Rob Niedermayer40122Brian BenningBob Beers40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Slava KozlovChris Tancill60122
2Jiri DopitaRandy Cunneyworth40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Keith BrownGlenn Featherstone60122
2Brian BenningBob Beers40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Slava KozlovJiri DopitaChris TancillKeith BrownGlenn Featherstone
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Slava KozlovJiri DopitaChris TancillKeith BrownGlenn Featherstone
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jim Dowd, Shane Churla, Len BarrieJim Dowd, Shane ChurlaLen Barrie
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jiri Slegr, Keith Brown, Brian BenningJiri SlegrGlenn Featherstone, Brian Benning
Tirs de Pénalité
Slava Kozlov, Len Barrie, Jiri Dopita, Randy Cunneyworth, Chris Tancill
Gardien
#1 : Felix Potvin, #2 : Mike Dunham


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Ailes Rouges53200000151502200000064231200000911-260.60015284300918581413269272571223124407610524520.83%37586.49%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
2As531100002014622000000945311100001110170.700203757009185814133692725712231244666117351131.43%30390.00%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
3Banshees631200002415941120000151142200000094580.66724436700918581416469272571223158415213532825.00%24483.33%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
4Canadiens87010000271413440000001477430100001376150.9382750770091858141936927257122322471166180481327.08%62591.94%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
5Citadelles724010002632-6522010002222020200000410-660.429264672009185814161692725712231994810014033824.24%44979.55%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
6Croque-Morts623100002029-921010000871413000001222-1050.41720385800918581413969272571223200586816226623.08%331069.70%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
7Harvard953001002528-342200000911-2531001001617-1110.611254671009185814233692725712232577482197451022.22%40977.50%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
8Isotopes631110002217520011000761431000001511490.750224264009185814183692725712231293054147301033.33%25484.00%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
9Pacifiques de la route532000001515021100000550321000001010060.60015284300918581414869272571223105294811425416.00%24866.67%11416272152.04%1388275850.33%667130151.27%1990132819036431072543
10Riverman606000001026-1640400000818-102020000028-600.00010192900918581417569272571223173448511729310.34%38781.58%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
11Snipers52101100191453110010011922100100085370.7001934530091858141236927257122314546719520525.00%26388.46%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
12Spoonman's926100002025-5513100001014-4413000001011-150.278203656019185814235692725712232665811218646613.04%53884.91%11416272152.04%1388275850.33%667130151.27%1990132819036431072543
13Wolves53101000181802200000095431101000913-480.80018345200918581413369272571223123455910921314.29%26869.23%01416272152.04%1388275850.33%667130151.27%1990132819036431072543
Total82383174200261262-1411914521001331231041191722100128139-11930.5672614817420191858142152692725712232227630103918044149222.22%4628382.03%21416272152.04%1388275850.33%667130151.27%1990132819036431072543
_Since Last GM Reset82453104200261262-14119145210013312310412617-52100128139-111000.6102614817420191858142152692725712232227630103918044149222.22%4628382.03%21416272152.04%1388275850.33%667130151.27%1990132819036431072543
_Vs Conference452715021001441311324108420007771621177-4010067607590.65614426340701918581411696927257122312333225669852345523.50%2483984.27%11416272152.04%1388275850.33%667130151.27%1990132819036431072543
_Vs Division261690010072675137510000333211394-1010039354330.63572132204019185814661692725712237472033605631392920.86%1552285.81%11416272152.04%1388275850.33%667130151.27%1990132819036431072543

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8293W1261481742215222276301039180401
Tous les Matchs
GPWLOTWOTL TGFGA
823831427261262
Matchs locaux
GPWLOTWOTL TGFGA
411914215133123
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
411917212128139
Derniers 10 Matchs
WLOTWOTL T
72100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4149222.22%4628382.03%2
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
692725712239185814
Mises en Jeu
Gagnées en Zone OffensiveTotal en Zone Offensive% Gagnées en Zone Offensive Gagnées en Zone DéfensiveTotal en Zone Défensive% Gagnées en Zone DéfensiveGagnées en Zone NeutreTotal en Zone Neutre% Gagnées en Zone Neutre
1416272152.04%1388275850.33%667130151.27%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1990132819036431072543


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
1 - 2020-09-214Riverman7Chiefs2LSommaire du Match
3 - 2020-09-2315Spoonman's3Chiefs1LSommaire du Match
4 - 2020-09-2418Chiefs4Croque-Morts3WSommaire du Match
6 - 2020-09-2628Chiefs2Harvard3LXSommaire du Match
7 - 2020-09-2734Harvard2Chiefs0LSommaire du Match
9 - 2020-09-2943Citadelles7Chiefs3LSommaire du Match
10 - 2020-09-3049Chiefs3Canadiens3TXSommaire du Match
11 - 2020-10-0156Chiefs0Spoonman's1LSommaire du Match
13 - 2020-10-0362Banshees1Chiefs6WSommaire du Match
15 - 2020-10-0570Chiefs5Harvard4WSommaire du Match
17 - 2020-10-0775Canadiens2Chiefs3WSommaire du Match
19 - 2020-10-0986Ailes Rouges1Chiefs2WSommaire du Match
21 - 2020-10-1189Chiefs2Croque-Morts5LSommaire du Match
23 - 2020-10-1399Banshees3Chiefs3TXSommaire du Match
26 - 2020-10-16108Chiefs2Riverman3LSommaire du Match
27 - 2020-10-17112Canadiens2Chiefs4WSommaire du Match
29 - 2020-10-19121Chiefs3As4LSommaire du Match
31 - 2020-10-21124Chiefs6Snipers4WSommaire du Match
33 - 2020-10-23132Canadiens1Chiefs3WSommaire du Match
35 - 2020-10-25142Croque-Morts3Chiefs4WSommaire du Match
37 - 2020-10-27145Chiefs4As2WSommaire du Match
39 - 2020-10-29154Snipers2Chiefs7WSommaire du Match
41 - 2020-10-31160Chiefs0Wolves6LSommaire du Match
42 - 2020-11-01169Chiefs4Wolves3WXSommaire du Match
44 - 2020-11-03175Banshees2Chiefs2TXSommaire du Match
46 - 2020-11-05184As1Chiefs5WSommaire du Match
47 - 2020-11-06189Chiefs6Harvard3WSommaire du Match
49 - 2020-11-08198Harvard1Chiefs2WSommaire du Match
50 - 2020-11-09202Chiefs4Croque-Morts5LSommaire du Match
52 - 2020-11-11209Chiefs1Harvard6LSommaire du Match
53 - 2020-11-12216Canadiens2Chiefs4WSommaire du Match
55 - 2020-11-14224Croque-Morts4Chiefs4TXSommaire du Match
56 - 2020-11-15228Chiefs1Citadelles4LSommaire du Match
58 - 2020-11-17239Chiefs0Pacifiques de la route5LSommaire du Match
60 - 2020-11-19246Snipers4Chiefs2LSommaire du Match
61 - 2020-11-20252Chiefs5Banshees2WSommaire du Match
63 - 2020-11-22261Harvard2Chiefs3WSommaire du Match
65 - 2020-11-24267Chiefs7Pacifiques de la route4WSommaire du Match
66 - 2020-11-25272Wolves2Chiefs4WSommaire du Match
67 - 2020-11-26282Isotopes3Chiefs3TXSommaire du Match
68 - 2020-11-27287Chiefs2Canadiens1WSommaire du Match
71 - 2020-11-30296Riverman4Chiefs2LSommaire du Match
72 - 2020-12-01301Chiefs2Canadiens1WSommaire du Match
73 - 2020-12-02310Riverman4Chiefs2LSommaire du Match
74 - 2020-12-03315Chiefs0Riverman5LSommaire du Match
76 - 2020-12-05324Chiefs2Ailes Rouges4LSommaire du Match
77 - 2020-12-06328Pacifiques de la route4Chiefs2LSommaire du Match
78 - 2020-12-07336Chiefs4Spoonman's5LSommaire du Match
79 - 2020-12-08343Isotopes3Chiefs4WXSommaire du Match
80 - 2020-12-09350Snipers3Chiefs2LXSommaire du Match
82 - 2020-12-11355Chiefs2Croque-Morts9LSommaire du Match
84 - 2020-12-13360Chiefs0Isotopes3LSommaire du Match
86 - 2020-12-15366Chiefs2Spoonman's3LSommaire du Match
88 - 2020-12-17374Spoonman's6Chiefs0LSommaire du Match
90 - 2020-12-19382Citadelles6Chiefs4LSommaire du Match
92 - 2020-12-21392Wolves3Chiefs5WSommaire du Match
94 - 2020-12-23399Chiefs3Pacifiques de la route1WSommaire du Match
96 - 2020-12-25401Chiefs6Canadiens2WSommaire du Match
98 - 2020-12-27410Citadelles2Chiefs3WSommaire du Match
100 - 2020-12-29419Chiefs2Snipers1WXSommaire du Match
101 - 2020-12-30426Spoonman's2Chiefs2TXSommaire du Match
103 - 2021-01-01434Chiefs2Harvard1WSommaire du Match
104 - 2021-01-02437Chiefs5Isotopes1WSommaire du Match
106 - 2021-01-04444Banshees5Chiefs4LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
109 - 2021-01-07454Harvard6Chiefs4LSommaire du Match
110 - 2021-01-08458Chiefs4Banshees2WSommaire du Match
112 - 2021-01-10468Riverman3Chiefs2LSommaire du Match
113 - 2021-01-11475Chiefs4Spoonman's2WSommaire du Match
114 - 2021-01-12478Chiefs3Citadelles6LSommaire du Match
116 - 2021-01-14486As3Chiefs4WSommaire du Match
117 - 2021-01-15491Chiefs4As4TXSommaire du Match
118 - 2021-01-16498Pacifiques de la route1Chiefs3WSommaire du Match
119 - 2021-01-17502Chiefs5Ailes Rouges4WSommaire du Match
121 - 2021-01-19513Spoonman's0Chiefs5WSommaire du Match
122 - 2021-01-20518Chiefs2Ailes Rouges3LSommaire du Match
123 - 2021-01-21525Spoonman's3Chiefs2LSommaire du Match
124 - 2021-01-22533Chiefs5Isotopes4WSommaire du Match
125 - 2021-01-23535Chiefs5Wolves4WSommaire du Match
127 - 2021-01-25544Citadelles4Chiefs8WSommaire du Match
128 - 2021-01-26548Chiefs5Isotopes3WSommaire du Match
131 - 2021-01-29560Citadelles3Chiefs4WXSommaire du Match
134 - 2021-02-01570Ailes Rouges3Chiefs4WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,409,730$ 1,747,700$ 1,737,700$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
1,747,700$ 1,409,730$ 32 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 1 13,549$ 13,549$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT