Chiefs

GP: 53 | W: 23 | L: 23 | T: 5 | P: 53
GF: 152 | GA: 174 | PP%: 21.40% | PK%: 80.07%
DG: Christian Cheminais | Morale : 53 | Moyenne d'Équipe : 65
Prochain matchs #374 vs Spoonman's
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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
1Mark LambX98.007661676869757675687564785965663956680291458,000$
2Jiri Dopita (R)X99.004537766678676880718176696844486867670253400,000$
3Randy Cunneyworth (C)X100.007262586770717169626665806378851760670322600,000$
4Bobby HolikX100.007458656781747671677369826830328967670221550,000$
5Chris TancillX100.007156717071707173597372696443506832660251531,000$
6Brad DalgarnoX100.006748836279707271627267816051516167660261185,000$
7Jim DowdX100.005744776873707267657568786439486167650262200,000$
8Mick VukotaX100.008983376475818358626955825256545349650271365,000$
9Shane Churla (A)X100.009892276475747464627052775065704761650283500,000$
10Nick KypreosX100.009285366277747662616460805852505534640272450,000$
11Michel Picard (R)X100.005644817173666869636968646640517639630242450,000$
12Donald Brashear (R)X100.008895306785817362526361706035458067630223250,000$
13Glenn FeatherstoneX100.008779436679737358525749854744516870670253635,000$
14Donald DufresneX100.007153716376697069626957835252476067660262468,000$
15Bob BeersX100.007351786674697064647655805247476067660264560,000$
16Jason YorkX100.006449727175727472657568756233348267650231250,000$
17Jiri Slegr (R)X100.005846736677717370647364826036348967650221380,000$
18Frantisek KuceraX100.006450766775727463627250784827336867640252400,000$
Rayé
1Brian Propp (A)X100.00655172637163637667757866728182162680341600,000$
2Len BarrieX100.005959496975687068647472676841547419650241295,000$
3Rob Niedermayer (R)X100.007060757362777570806361776335458020640203250,000$
4Jeff Odgers (R)X100.009395306085807763546262606637557032620253250,000$
5Rob RayX100.009089256476666860565663816232326820610251350,000$
6Marc PotvinX100.007469516174636659586151705040425320590271200,000$
7Grant MarshallX100.006355686470606257566057675627279820570203500,000$
8Davis Payne (R)X100.007770496374606252505460586033288220560232150,000$
MOYENNE D'ÉQUIPE99.88736359667571716662686275604549644964
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)100.00737981808176848582787638388832730
2Mike Dunham (R)100.00687676787372828279717129359757690
Rayé
1Jamie McLennan100.00687271747060667667696738348920630
MOYENNE D'ÉQUIPE100.0070767677756977817673713536913668
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
1Mark LambChiefs (QUE)C53182038-4420114136135329913.33%14115821.8558134221700052595148.39%124000000.6600000333
2Donald DufresneChiefs (QUE)D5372734036046848022478.75%59122323.095813492110000218120.00%000000.5600000120
3Jiri DopitaChiefs (QUE)C53131932-200189120328410.83%987616.5439121810100031453054.80%82300000.7300000211
4Glenn FeatherstoneChiefs (QUE)D5372431012352234658215212.07%57123123.2351217362210110187100.00%000000.5000100251
5Randy CunneyworthChiefs (QUE)LW53121931-1055567701103810310.91%5101519.16311142120210121432054.79%14600000.6100010111
6Jason YorkChiefs (QUE)D5382230-9460537054225114.81%6297718.446511321060000122220.00%000000.6100000302
7Brad DalgarnoChiefs (QUE)RW53151429-8402545137429710.95%486516.34861443213000001046.27%6700000.6700000033
8Brian ProppChiefs (QUE)LW42141428-140296395227114.74%792722.094592116800022123152.73%53100000.6000000305
9Bob BeersChiefs (QUE)D5322527-838076494522374.44%67118422.3511213301970000210000.00%000000.4600000010
10Bobby HolikChiefs (QUE)C53121426-6100429412622929.52%981915.47448271160111791050.33%90600000.6300000110
11Mick VukotaChiefs (QUE)RW4781321-174101184356174914.29%263913.6043710830000101044.00%5000010.6600011103
12Jiri SlegrChiefs (QUE)D5351520-732054576012368.33%5595217.98358291070000108100.00%000000.4200000120
13Chris TancillChiefs (QUE)RW2951318-660222048164410.42%246816.1607712125000001052.94%3400000.7700000012
14Jim DowdChiefs (QUE)C5351217-4002666515477.69%44548.58022040000370146.39%45700000.7500000011
15Frantisek KuceraChiefs (QUE)D536915-1244081452851321.43%3983615.77303590000102020.00%000000.3600000210
16Donald BrashearChiefs (QUE)LW44369231544174010207.50%44209.56000000000350046.15%3900000.4300100000
17Nick KypreosChiefs (QUE)LW293581501050161661618.75%338813.401014390000190055.17%2900000.4100002101
18Michel PicardChiefs (QUE)LW35538-102002637182713.51%33289.3800000000051042.11%1900000.4900000000
19Shane ChurlaChiefs (QUE)RW50134-847571204615212.17%33847.7001113000000062.96%2700000.2100010010
20Len BarrieChiefs (QUE)C13202-1207064333.33%0644.9700004000000042.86%700000.6200000000
21Jeff OdgersChiefs (QUE)RW261121220441921111.11%22328.9400001000000021.43%1400000.1700000000
22Rob RayChiefs (QUE)RW3011160710010.00%0268.700000000000000.00%000000.7700000000
Stats d'équipe Total ou en Moyenne954152279431-9267440117610581371395102111.09%4101547716.225598153380213712313190023950.47%438900010.5600233212323
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)50222340.8813.2727708015112640500.0000494310
2Mike DunhamChiefs (QUE)111210.8983.1943300232250100.0000449110
Stats d'équipe Total ou en Moyenne61232550.8833.2632038017414890600.00005353420


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)D261994-02-09 9:08:37 PMNo200 Lbs6 ft2NoNoNo4Pro & Farm560,000$56,000$20,588$No560,000$560,000$560,000$
Bobby HolikChiefs (QUE)C221998-02-09 9:08:37 PMNo225 Lbs6 ft3NoNoNo1Pro & Farm550,000$55,000$20,221$No
Brad DalgarnoChiefs (QUE)RW261994-02-09 9:08:37 PMNo215 Lbs6 ft3NoNoNo1Pro & Farm185,000$18,500$6,801$No
Brian ProppChiefs (QUE)LW341986-02-09 9:08:37 PMNo190 Lbs5 ft9NoNoNo1Pro & Farm600,000$60,000$22,059$No
Chris TancillChiefs (QUE)RW251995-02-09 9:08:37 PMNo185 Lbs5 ft10NoNoNo1Pro & Farm531,000$53,100$19,522$No
Davis PayneChiefs (QUE)RW231997-02-09 9:08:37 PMYes190 Lbs6 ft1NoNoNo2Pro & Farm150,000$15,000$5,515$No150,000$
Donald BrashearChiefs (QUE)LW221998-08-11 9:38:29 AMYes237 Lbs6 ft3NoNoNo3Pro & Farm250,000$25,000$9,191$No250,000$250,000$
Donald DufresneChiefs (QUE)D261994-02-09 9:08:37 PMNo206 Lbs6 ft1NoNoNo2Pro & Farm468,000$46,800$17,206$No468,000$
Felix PotvinChiefs (QUE)G221998-02-09 9:08:37 PMYes190 Lbs6 ft1NoNoNo1Pro & Farm400,000$40,000$14,706$No
Frantisek KuceraChiefs (QUE)D251995-02-09 9:08:37 PMNo205 Lbs6 ft2NoNoNo2Pro & Farm400,000$40,000$14,706$No400,000$
Glenn FeatherstoneChiefs (QUE)D251995-02-09 9:08:37 PMNo215 Lbs6 ft4NoNoNo3Pro & Farm635,000$63,500$23,346$No635,000$635,000$
Grant MarshallChiefs (QUE)RW202000-02-09 9:08:37 PMNo185 Lbs6 ft1NoNoNo3Pro & Farm500,000$50,000$18,382$No500,000$500,000$
Jamie McLennanChiefs (QUE)G221998-02-09 9:08:37 PMNo190 Lbs6 ft0NoNoNo1Pro & Farm150,000$15,000$5,515$No
Jason YorkChiefs (QUE)D231997-02-09 9:08:37 PMNo200 Lbs6 ft2NoNoNo1Pro & Farm250,000$25,000$9,191$No
Jeff OdgersChiefs (QUE)RW251995-08-11 9:32:17 AMYes200 Lbs6 ft0NoNoNo3Pro & Farm250,000$25,000$9,191$No250,000$250,000$
Jim DowdChiefs (QUE)C261994-02-09 9:08:37 PMNo190 Lbs6 ft1NoNoNo2Pro & Farm200,000$20,000$7,353$No200,000$
Jiri DopitaChiefs (QUE)C251995-02-09 9:08:37 PMYes213 Lbs6 ft3NoNoNo3Pro & Farm400,000$40,000$14,706$No400,000$400,000$
Jiri SlegrChiefs (QUE)D221998-02-09 9:08:37 PMYes216 Lbs6 ft1NoNoNo1Pro & Farm380,000$38,000$13,971$No
Len BarrieChiefs (QUE)C241996-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo1Pro & Farm295,000$29,500$10,846$No
Marc PotvinChiefs (QUE)C271993-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo1Pro & Farm200,000$20,000$7,353$No
Mark LambChiefs (QUE)C291991-02-09 9:08:37 PMNo179 Lbs5 ft9NoNoNo1Pro & Farm458,000$45,800$16,838$No
Michel PicardChiefs (QUE)LW241996-02-09 9:08:37 PMYes190 Lbs5 ft11NoNoNo2Pro & Farm450,000$45,000$16,544$No450,000$
Mick VukotaChiefs (QUE)RW271993-02-09 9:08:37 PMNo195 Lbs6 ft2NoNoNo1Pro & Farm365,000$36,500$13,419$No
Mike DunhamChiefs (QUE)G211999-02-09 9:08:37 PMYes195 Lbs6 ft3NoNoNo1Pro & Farm400,000$40,000$14,706$No
Nick KypreosChiefs (QUE)LW271993-02-09 9:08:37 PMNo210 Lbs6 ft0NoNoNo2Pro & Farm450,000$45,000$16,544$No450,000$
Randy CunneyworthChiefs (QUE)LW321988-02-09 9:08:37 PMNo180 Lbs6 ft0NoNoNo2Pro & Farm600,000$60,000$22,059$No600,000$
Rob NiedermayerChiefs (QUE)C202000-08-11 9:28:24 AMYes200 Lbs6 ft2NoNoNo3Pro & Farm250,000$25,000$9,191$No250,000$250,000$
Rob RayChiefs (QUE)RW251995-02-09 9:08:37 PMNo216 Lbs6 ft0NoNoNo1Pro & Farm350,000$35,000$12,868$No
Shane ChurlaChiefs (QUE)RW281992-02-09 9:08:37 PMNo201 Lbs6 ft1NoNoNo3Pro & Farm500,000$50,000$18,382$No500,000$500,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2924.93201 Lbs6 ft11.83385,414$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Randy CunneyworthMark LambChris Tancill35122
2Nick KypreosJiri DopitaBrad Dalgarno30122
3Michel PicardBobby HolikMick Vukota20122
4Mark LambJim DowdShane Churla15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Glenn FeatherstoneBob Beers35122
2Donald DufresneJason York30122
3Jiri SlegrFrantisek Kucera20122
4Glenn FeatherstoneBob Beers15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Randy CunneyworthMark LambChris Tancill60122
2Nick KypreosJiri DopitaBrad Dalgarno40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Glenn FeatherstoneBob Beers60122
2Donald DufresneJason York40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Mark LambJiri Dopita60122
2Bobby HolikRandy Cunneyworth40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Glenn FeatherstoneBob Beers60122
2Donald DufresneJason York40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Mark Lamb60122Glenn FeatherstoneBob Beers60122
2Jiri Dopita40122Donald DufresneJason York40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Mark LambJiri Dopita60122
2Bobby HolikRandy Cunneyworth40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Glenn FeatherstoneBob Beers60122
2Donald DufresneJason York40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Randy CunneyworthMark LambChris TancillGlenn FeatherstoneBob Beers
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Randy CunneyworthMark LambChris TancillGlenn FeatherstoneBob Beers
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mark Lamb, Mick Vukota, Jim DowdMark Lamb, Mick VukotaJim Dowd
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jiri Slegr, Frantisek Kucera, Donald DufresneJiri SlegrFrantisek Kucera, Donald Dufresne
Tirs de Pénalité
Mark Lamb, Jiri Dopita, Bobby Holik, 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 Rouges2110000045-1110000002111010000024-220.50048120054484825141448545517411226457114.29%13284.62%0898173451.79%905181449.89%41284148.99%12668401244418698352
2As321000001275110000005142110000076140.66712223400544848275414485455176624427218633.33%18288.89%0898173451.79%905181449.89%41284148.99%12668401244418698352
3Banshees4202000016883102000011651100000052360.7501628440054484821084144854551711124329423521.74%15193.33%0898173451.79%905181449.89%41284148.99%12668401244418698352
4Canadiens760100002112944000000147732010000752130.9292138590054484821654144854551720266148160431227.91%55590.91%0898173451.79%905181449.89%41284148.99%12668401244418698352
5Citadelles20200000411-71010000037-41010000014-300.0004711005448482404144854551758184239600.00%15660.00%0898173451.79%905181449.89%41284148.99%12668401244418698352
6Croque-Morts623100002029-921010000871413000001222-1050.41720385800544848213941448545517200586816226623.08%331069.70%0898173451.79%905181449.89%41284148.99%12668401244418698352
7Harvard742001001921-232100000550421001001416-290.64319345300544848217341448545517203506615835720.00%33681.82%0898173451.79%905181449.89%41284148.99%12668401244418698352
8Isotopes3011100079-2200110007611010000003-330.5007132000544848288414485455177017225710330.00%10280.00%0898173451.79%905181449.89%41284148.99%12668401244418698352
9Pacifiques de la route31200000913-41010000024-22110000079-220.3339162500544848287414485455178121346617317.65%17758.82%1898173451.79%905181449.89%41284148.99%12668401244418698352
10Riverman50500000823-1530300000615-92020000028-600.0008152300544848214241448545517153386910223313.04%31680.65%0898173451.79%905181449.89%41284148.99%12668401244418698352
11Snipers42100100171343110010011921100000064250.6251730470054484821034144854551712436636916531.25%22386.36%0898173451.79%905181449.89%41284148.99%12668401244418698352
12Spoonman's40400000712-51010000013-23030000069-300.00071421005448482117414485455171072238802229.09%18477.78%0898173451.79%905181449.89%41284148.99%12668401244418698352
Total53212352200152174-22261284110079736279151110073101-28530.500152279431005448482137141448545517148941068211762575521.40%2965980.07%1898173451.79%905181449.89%41284148.99%12668401244418698352
13Wolves31101000811-3110000004222010100049-540.6678162400544848283414485455177324327211218.18%16568.75%0898173451.79%905181449.89%41284148.99%12668401244418698352
_Since Last GM Reset53262302200152174-22261284110079736271415-4110073101-28580.547152279431005448482137141448545517148941068211762575521.40%2965980.07%1898173451.79%905181449.89%41284148.99%12668401244418698352
_Vs Conference271690110074731147331000413471396-301003339-6350.64874134208005448482691414485455177511973485881392920.86%1462483.56%0898173451.79%905181449.89%41284148.99%12668401244418698352
_Vs Division18116001004745286200000201551054001002730-3230.6394786133005448482455414485455175121382523981002121.00%1061585.85%0898173451.79%905181449.89%41284148.99%12668401244418698352

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5353L315227943113711489410682117600
Tous les Matchs
GPWLOTWOTL TGFGA
532123225152174
Matchs locaux
GPWLOTWOTL TGFGA
261281147973
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
2791511173101
Derniers 10 Matchs
WLOTWOTL T
08110
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2575521.40%2965980.07%1
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
414485455175448482
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
898173451.79%905181449.89%41284148.99%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12668401244418698352


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's-Chiefs-
90 - 2020-12-19382Citadelles-Chiefs-
92 - 2020-12-21392Wolves-Chiefs-
94 - 2020-12-23399Chiefs-Pacifiques de la route-
96 - 2020-12-25401Chiefs-Canadiens-
98 - 2020-12-27410Citadelles-Chiefs-
100 - 2020-12-29419Chiefs-Snipers-
101 - 2020-12-30426Spoonman's-Chiefs-
103 - 2021-01-01434Chiefs-Harvard-
104 - 2021-01-02437Chiefs-Isotopes-
106 - 2021-01-04444Banshees-Chiefs-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
109 - 2021-01-07454Harvard-Chiefs-
110 - 2021-01-08458Chiefs-Banshees-
112 - 2021-01-10468Riverman-Chiefs-
113 - 2021-01-11475Chiefs-Spoonman's-
114 - 2021-01-12478Chiefs-Citadelles-
116 - 2021-01-14486As-Chiefs-
117 - 2021-01-15491Chiefs-As-
118 - 2021-01-16498Pacifiques de la route-Chiefs-
119 - 2021-01-17502Chiefs-Ailes Rouges-
121 - 2021-01-19513Spoonman's-Chiefs-
122 - 2021-01-20518Chiefs-Ailes Rouges-
123 - 2021-01-21525Spoonman's-Chiefs-
124 - 2021-01-22533Chiefs-Isotopes-
125 - 2021-01-23535Chiefs-Wolves-
127 - 2021-01-25544Citadelles-Chiefs-
128 - 2021-01-26548Chiefs-Isotopes-
131 - 2021-01-29560Citadelles-Chiefs-
134 - 2021-02-01570Ailes Rouges-Chiefs-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
15 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
764,366$ 1,117,700$ 1,117,700$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
1,117,700$ 764,366$ 29 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 50 8,917$ 445,850$




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