Canadiens

GP: 51 | W: 12 | L: 30 | T: 5 | P: 33
GF: 135 | GA: 185 | PP%: 16.46% | PK%: 76.72%
DG: Sébastien Régnier | Morale : 18 | Moyenne d'Équipe : 64
Prochain matchs #362 vs Harvard
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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
1Pavol Demitra (R)X97.007051807865777078777674737335359918680203250,000$
2Marc HabscheidX100.006946816571747271697670666670663127670302310,000$
3Gaetan DuchesneX100.006551746571798069636963756284812230670311735,000$
4Stu BarnesX100.006349737470727271657569786438398120660231378,000$
5Randy GilhenX100.005839866772747766647160765869743331660301500,000$
6Paul MacDermidX100.008479426474717167646966746263693235660301500,000$
7Rich SutterX100.008579436468757667656861726063723332650301500,000$
8Troy LoneyX100.008579416279757865576264806258533420650301500,000$
9Daniel MaroisX100.007560647173727367606973676945436728650251445,000$
10Martin RucinskyX100.005344706875676572657570656532288931630222400,000$
11Jere Lehtinen (R)X100.005845737172676769637162785829339731630203650,000$
12Daniel LacroixX100.006666486876646656566158725831357620590242255,000$
13Steve FinnX100.008072436674676954515651824967675324660271500,000$
14Brad Werenka (R)X100.007152737075737268627259785436347531650242400,000$
15Marc BergevinX100.007050726475727265616954735150564620650281505,000$
16Marc LaforgeX100.006264436479687067566153774744556720640253435,000$
17Link GaetzX100.008676506082676963586552815034366835640252345,000$
18Bob BoughnerX100.008076446276717264586849774432328924630223422,000$
Rayé
1Travis Green (R)X67.395846777275656768647067696437308214630231375,000$
2Pierre SevignyX100.006355697174636463576358595628288920580222220,000$
3Patrick Traverse (R)X100.006350796266585959566337703531329620570191350,000$
MOYENNE D'ÉQUIPE98.30705963677370716661686073574648652564
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
1Frederic Chabot100.00676872726964798375697049556714680
2Andre Racicot100.00727070707066738475707035387620660
Rayé
1J.C. Bergeron (R)100.00686675767366687971706628288220640
MOYENNE D'ÉQUIPE100.0069687273716573827470693740751866
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Alain Vigneault71787077707890CAN31295,000$


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
1Teppo NumminenCanadiensD4272936-34013779233667.61%58103724.7051217662080000206100.00%000000.6900000102
2Pavol DemitraCanadiens (MTL)RW40191635-12180581161143210616.67%885521.40511163820001111011249.80%76900010.8200000222
3Randy GilhenCanadiens (MTL)C51101727060109582195012.20%1076915.084482617410141082149.38%96600000.7000000113
4Brad WerenkaCanadiens (MTL)D51111425-13620867269255315.94%81119623.465914462451011210210.00%000000.4200000200
5Marc HabscheidCanadiens (MTL)LW511013232355577610527729.52%593018.2437103422620231510053.23%6200000.4900000212
6Stu BarnesCanadiens (MTL)C4691221-191604812310230798.82%788519.2646103621000021590148.06%115900000.4700000112
7Marc BergevinCanadiens (MTL)D4841721-1436057434310399.30%4597720.374610312230001129000.00%000000.4300000001
8Daniel MaroisCanadiens (MTL)RW5111718-53951043997276711.34%670813.89437241330000300056.72%6700000.5100010102
9Steve FinnCanadiens (MTL)D4761117-18401214141122614.63%4691019.38246191450110141100.00%000000.3700000122
10Martin RucinskyCanadiens (MTL)LW4910717-128052168114614.71%252210.666511221120001163149.02%5100000.6500000010
11Jere LehtinenCanadiens (MTL)RW5131417-4802138479406.38%1257011.19066138901121310053.01%8300000.6000000001
12Paul MacDermidCanadiens (MTL)RW5161016-47810136398328527.23%568413.43235181400001230150.00%5200100.4700101010
13Travis GreenCanadiens (MTL)C4931215-1203716926494.35%158011.851451255000041045.31%65100000.5200000000
14Gaetan DuchesneCanadiens (MTL)LW517714-118019719333587.53%1180915.871121412700001300150.64%15600000.3500000001
15Link GaetzCanadiens (MTL)D5121113-1411620129473312176.06%7086616.9804414820000133000.00%000000.3000202201
16Bob BoughnerCanadiens (MTL)D356410-14681087383062320.00%3965318.684261788000081000.00%000000.3100002010
17Rich SutterCanadiens (MTL)RW47279-15511564364712284.26%34239.010223230001120053.33%3000000.4300100100
18Shjon PodeinCanadiensLW16549-5140232340131812.50%229418.3820212370111491147.92%4800000.6100000001
19Marc LaforgeCanadiens (MTL)D32088-52403025157130.00%3151616.15011437000070000.00%000000.3100000000
20Troy LoneyCanadiens (MTL)LW31268-6371542254013345.00%832910.62000170000110043.75%1600000.4900012010
21Daniel LacroixCanadiens (MTL)C19123-2120161714377.14%323212.25011160000100043.20%25000000.2600000000
22Bob ProbertCanadiensLW9112-12610181291411.11%09810.97101210000310028.57%1400000.4100001010
23Paul RanheimCanadiensLW1000000024310.00%02323.33000250000700100.00%200000.0000000000
Stats d'équipe Total ou en Moyenne919135229364-1597529011471147133739294810.10%4531487916.195391144455258444818195312948.38%437600110.4900428141220
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
1Frederic ChabotCanadiens (MTL)44102850.8833.3624300013611660210.0000429233
2Andre RacicotCanadiens (MTL)162600.8564.4265120483340000.0000942000
Stats d'équipe Total ou en Moyenne60123450.8773.5830822018415000210.00005151233


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
Andre RacicotCanadiens (MTL)G241996-02-09 9:08:37 PMNo166 Lbs5 ft11NoNoNo3Pro & Farm430,000$43,000$16,757$No430,000$430,000$
Bob BoughnerCanadiens (MTL)D221998-02-09 9:08:37 PMNo206 Lbs6 ft0NoNoNo3Pro & Farm422,000$42,200$16,446$No422,000$422,000$
Brad WerenkaCanadiens (MTL)D241996-02-09 9:08:37 PMYes205 Lbs6 ft2NoNoNo2Pro & Farm400,000$40,000$15,588$No400,000$
Daniel LacroixCanadiens (MTL)C241996-02-09 9:08:37 PMNo205 Lbs6 ft2NoNoNo2Pro & Farm255,000$25,500$9,938$No255,000$
Daniel MaroisCanadiens (MTL)RW251995-02-09 9:08:37 PMNo190 Lbs6 ft1NoNoNo1Pro & Farm445,000$44,500$17,342$No
Frederic ChabotCanadiens (MTL)G251995-02-09 9:08:37 PMNo177 Lbs5 ft11NoNoNo1Pro & Farm480,000$48,000$18,706$No
Gaetan DuchesneCanadiens (MTL)LW311989-02-09 9:08:37 PMNo190 Lbs6 ft0NoNoNo1Pro & Farm735,000$73,500$28,643$No
J.C. BergeronCanadiens (MTL)G231997-02-09 9:08:37 PMYes192 Lbs6 ft2NoNoNo2Pro & Farm375,000$37,500$14,614$No375,000$
Jere LehtinenCanadiens (MTL)RW202000-02-09 9:08:37 PMYes185 Lbs6 ft0NoNoNo3Pro & Farm650,000$65,000$25,331$No650,000$650,000$
Link GaetzCanadiens (MTL)D251995-02-09 9:08:37 PMNo240 Lbs6 ft3NoNoNo2Pro & Farm345,000$34,500$13,445$No345,000$
Marc BergevinCanadiens (MTL)D281992-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo1Pro & Farm505,000$50,500$19,680$No
Marc HabscheidCanadiens (MTL)LW301990-02-09 9:08:37 PMNo180 Lbs6 ft1NoNoNo2Pro & Farm310,000$31,000$12,081$No310,000$
Marc LaforgeCanadiens (MTL)D251995-02-09 9:08:37 PMNo215 Lbs6 ft3NoNoNo3Pro & Farm435,000$43,500$16,952$No435,000$435,000$
Martin RucinskyCanadiens (MTL)LW221998-02-09 9:08:37 PMNo206 Lbs6 ft1NoNoNo2Pro & Farm400,000$40,000$15,588$No400,000$
Patrick TraverseCanadiens (MTL)D192001-02-09 9:08:37 PMYes176 Lbs6 ft3NoNoNo1Pro & Farm350,000$35,000$13,640$No
Paul MacDermidCanadiens (MTL)RW301990-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo1Pro & Farm500,000$50,000$19,485$No
Pavol DemitraCanadiens (MTL)RW202000-08-11 10:04:47 AMYes206 Lbs6 ft0NoNoNo3Pro & Farm250,000$25,000$9,743$No250,000$250,000$
Pierre SevignyCanadiens (MTL)LW221998-02-09 9:08:37 PMNo195 Lbs6 ft0NoNoNo2Pro & Farm220,000$22,000$8,574$No220,000$
Randy GilhenCanadiens (MTL)C301990-02-09 9:08:37 PMNo190 Lbs6 ft1NoNoNo1Pro & Farm500,000$50,000$19,485$No
Rich SutterCanadiens (MTL)RW301990-02-09 9:08:37 PMNo170 Lbs5 ft11NoNoNo1Pro & Farm500,000$50,000$19,485$No
Steve FinnCanadiens (MTL)D271993-02-09 9:08:37 PMNo199 Lbs6 ft1NoNoNo1Pro & Farm500,000$50,000$19,485$No
Stu BarnesCanadiens (MTL)C231997-02-09 9:08:37 PMNo174 Lbs5 ft11NoNoNo1Pro & Farm378,000$37,800$14,731$No
Travis Green (Sur la Masse Salariale)Canadiens (MTL)C231997-02-09 9:08:37 PMYes195 Lbs6 ft1NoNoNo1Pro & Farm375,000$37,500$14,614$No
Troy LoneyCanadiens (MTL)LW301990-02-09 9:08:37 PMNo215 Lbs6 ft3NoNoNo1Pro & Farm500,000$50,000$19,485$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2425.08195 Lbs6 ft11.71427,500$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Gaetan DuchesneStu BarnesPavol Demitra35122
2Marc HabscheidRandy GilhenPaul MacDermid30122
3Troy LoneyDaniel LacroixDaniel Marois20122
4Martin RucinskyPavol DemitraRich Sutter15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Steve FinnBrad Werenka35122
2Marc BergevinMarc Laforge30122
3Link GaetzBob Boughner20122
4Steve FinnBrad Werenka15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Gaetan DuchesneStu BarnesPavol Demitra60122
2Marc HabscheidRandy GilhenPaul MacDermid40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Steve FinnBrad Werenka60122
2Marc BergevinMarc Laforge40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Pavol DemitraGaetan Duchesne60122
2Marc HabscheidStu Barnes40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Steve FinnBrad Werenka60122
2Marc BergevinMarc Laforge40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Pavol Demitra60122Steve FinnBrad Werenka60122
2Gaetan Duchesne40122Marc BergevinMarc Laforge40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Pavol DemitraGaetan Duchesne60122
2Marc HabscheidStu Barnes40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Steve FinnBrad Werenka60122
2Marc BergevinMarc Laforge40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Gaetan DuchesneStu BarnesPavol DemitraSteve FinnBrad Werenka
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Gaetan DuchesneStu BarnesPavol DemitraSteve FinnBrad Werenka
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jere Lehtinen, Troy Loney, Daniel MaroisJere Lehtinen, Troy LoneyDaniel Marois
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Link Gaetz, Bob Boughner, Marc BergevinLink GaetzBob Boughner, Marc Bergevin
Tirs de Pénalité
Pavol Demitra, Gaetan Duchesne, Marc Habscheid, Stu Barnes, Paul MacDermid
Gardien
#1 : Frederic Chabot, #2 : Andre Racicot


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 Rouges21000100550110000002111000010034-130.750591400365346051429450440145421303613538.46%15380.00%0853173649.14%843179047.09%41984849.41%11717631250413669327
2As421100001613331110000131211100000031250.6251628440036534601104294504401414045537927518.52%22768.18%0853173649.14%843179047.09%41984849.41%11717631250413669327
3Banshees403001001119-830200100813-51010000036-310.125111627003653460854294504401413742449616425.00%22768.18%1853173649.14%843179047.09%41984849.41%11717631250413669327
4Chiefs706100001221-93021000057-240400000714-710.07112223400365346020242945044014165471311525559.09%431272.09%2853173649.14%843179047.09%41984849.41%11717631250413669327
5Citadelles2110000045-1000000000002110000045-120.50046100036534605042945044014551822458112.50%10280.00%0853173649.14%843179047.09%41984849.41%11717631250413669327
6Croque-Morts412001001217-52020000039-62100010098130.37512203200365346010242945044014133483811119421.05%18383.33%0853173649.14%843179047.09%41984849.41%11717631250413669327
7Harvard514000001324-1130300000718-112110000066020.20013223500365346013342945044014160358113031516.13%36877.78%0853173649.14%843179047.09%41984849.41%11717631250413669327
8Isotopes412100001113-2211000006512011000058-330.3751119300036534601024294504401411925478529310.34%21385.71%1853173649.14%843179047.09%41984849.41%11717631250413669327
9Pacifiques de la route53200000121203120000069-32200000063360.6001221330036534601294294504401414951729023521.74%26388.46%0853173649.14%843179047.09%41984849.41%11717631250413669327
10Riverman1010000034-1000000000001010000034-100.000336003653460134294504401423614165120.00%7271.43%0853173649.14%843179047.09%41984849.41%11717631250413669327
11Snipers413000001320-71010000036-3312000001014-420.250132235003653460964294504401412138557617529.41%24770.83%0853173649.14%843179047.09%41984849.41%11717631250413669327
12Spoonman's613101001922-32010010058-3412100001414040.333193352103653460190429450440141765011116766913.64%43979.07%0853173649.14%843179047.09%41984849.41%11717631250413669327
Total51123050400135185-5026417302006298-3625813202007387-14330.324135229364103653460133342945044014150145375411473225316.46%3057176.72%4853173649.14%843179047.09%41984849.41%11717631250413669327
13Wolves30210000410-630210000410-60000000000010.16748120036534607042945044014692756641317.69%18572.22%0853173649.14%843179047.09%41984849.41%11717631250413669327
_Since Last GM Reset51173000400135185-5026417302006298-36251313-302007387-14380.373135229364103653460133342945044014150145375411473225316.46%3057176.72%4853173649.14%843179047.09%41984849.41%11717631250413669327
_Vs Conference287190020070104-341319102003151-2015610-100003953-14160.28670118188103653460762429450440148122174366752052713.17%1754176.57%4853173649.14%843179047.09%41984849.41%11717631250413669327
_Vs Division18413001004467-23806101001733-161047-100002734-790.2504477121103653460525429450440145011323234491521912.50%1222976.23%2853173649.14%843179047.09%41984849.41%11717631250413669327

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5133L413522936413331501453754114710
Tous les Matchs
GPWLOTWOTL TGFGA
511230045135185
Matchs locaux
GPWLOTWOTL TGFGA
264170236298
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
258130227387
Derniers 10 Matchs
WLOTWOTL T
27010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3225316.46%3057176.72%4
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
429450440143653460
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
853173649.14%843179047.09%41984849.41%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
11717631250413669327


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 - 2020-09-211Canadiens6Spoonman's3WR3Sommaire du Match
2 - 2020-09-2211Spoonman's3Canadiens2LXSommaire du Match
4 - 2020-09-2419As4Canadiens4TXSommaire du Match
6 - 2020-09-2629Banshees6Canadiens5LXSommaire du Match
7 - 2020-09-2733Canadiens2Spoonman's3LR3Sommaire du Match
9 - 2020-09-2942Canadiens2Isotopes2TXSommaire du Match
10 - 2020-09-3049Chiefs3Canadiens3TXR5Sommaire du Match
11 - 2020-10-0153Canadiens3Harvard1WR4Sommaire du Match
13 - 2020-10-0361Harvard9Canadiens2LSommaire du Match
15 - 2020-10-0571As4Canadiens3LSommaire du Match
17 - 2020-10-0775Canadiens2Chiefs3LR5Sommaire du Match
19 - 2020-10-0985Wolves2Canadiens2TXSommaire du Match
21 - 2020-10-1193Canadiens3Banshees6LSommaire du Match
23 - 2020-10-1396Canadiens4Snipers6LSommaire du Match
25 - 2020-10-15104Harvard6Canadiens3LR4Sommaire du Match
27 - 2020-10-17112Canadiens2Chiefs4LSommaire du Match
29 - 2020-10-19119Harvard3Canadiens2LR4Sommaire du Match
31 - 2020-10-21126Canadiens2Croque-Morts3LXSommaire du Match
33 - 2020-10-23132Canadiens1Chiefs3LR5Sommaire du Match
35 - 2020-10-25138As4Canadiens6WSommaire du Match
37 - 2020-10-27146Pacifiques de la route2Canadiens0LSommaire du Match
39 - 2020-10-29155Croque-Morts5Canadiens1LSommaire du Match
41 - 2020-10-31159Canadiens3Harvard5LR4Sommaire du Match
42 - 2020-11-01167Canadiens3Snipers1WSommaire du Match
44 - 2020-11-03173Snipers6Canadiens3LSommaire du Match
46 - 2020-11-05183Wolves4Canadiens1LSommaire du Match
47 - 2020-11-06188Canadiens2Pacifiques de la route1WSommaire du Match
48 - 2020-11-07192Canadiens3Riverman4LSommaire du Match
50 - 2020-11-09201Pacifiques de la route2Canadiens5WSommaire du Match
52 - 2020-11-11211Banshees3Canadiens2LSommaire du Match
53 - 2020-11-12216Canadiens2Chiefs4LR5Sommaire du Match
55 - 2020-11-14225Ailes Rouges1Canadiens2WSommaire du Match
56 - 2020-11-15231Canadiens4Pacifiques de la route2WSommaire du Match
58 - 2020-11-17240Spoonman's5Canadiens3LR3Sommaire du Match
59 - 2020-11-18245Canadiens7Croque-Morts5WSommaire du Match
61 - 2020-11-20248Canadiens2Spoonman's4LR3Sommaire du Match
62 - 2020-11-21259Croque-Morts4Canadiens2LSommaire du Match
65 - 2020-11-24268Isotopes1Canadiens3WSommaire du Match
66 - 2020-11-25275Canadiens4Spoonman's4TXR3Sommaire du Match
67 - 2020-11-26279Canadiens3Snipers7LSommaire du Match
68 - 2020-11-27287Chiefs2Canadiens1LR5Sommaire du Match
70 - 2020-11-29293Canadiens3As1WSommaire du Match
72 - 2020-12-01301Chiefs2Canadiens1LR5Sommaire du Match
73 - 2020-12-02308Canadiens3Ailes Rouges4LXSommaire du Match
74 - 2020-12-03314Isotopes4Canadiens3LSommaire du Match
75 - 2020-12-04322Pacifiques de la route5Canadiens1LSommaire du Match
76 - 2020-12-05326Canadiens3Citadelles1WSommaire du Match
78 - 2020-12-07337Wolves4Canadiens1LSommaire du Match
79 - 2020-12-08339Canadiens1Citadelles4LSommaire du Match
80 - 2020-12-09346Canadiens3Isotopes6LSommaire du Match
82 - 2020-12-11356Banshees4Canadiens1LSommaire du Match
84 - 2020-12-13362Canadiens-Harvard-
86 - 2020-12-15368Canadiens-Riverman-
88 - 2020-12-17373Ailes Rouges-Canadiens-
90 - 2020-12-19383Canadiens-Isotopes-
92 - 2020-12-21387Spoonman's-Canadiens-
94 - 2020-12-23394Canadiens-Ailes Rouges-
96 - 2020-12-25401Chiefs-Canadiens-
98 - 2020-12-27411Canadiens-Wolves-
100 - 2020-12-29415Ailes Rouges-Canadiens-
101 - 2020-12-30425Banshees-Canadiens-
103 - 2021-01-01430Canadiens-Ailes Rouges-
104 - 2021-01-02439Harvard-Canadiens-
106 - 2021-01-04448Canadiens-Pacifiques de la route-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
109 - 2021-01-07455Croque-Morts-Canadiens-
111 - 2021-01-09463Canadiens-Citadelles-
112 - 2021-01-10465As-Canadiens-
113 - 2021-01-11474Canadiens-Snipers-
115 - 2021-01-13480Riverman-Canadiens-
116 - 2021-01-14489Canadiens-Spoonman's-
118 - 2021-01-16497Spoonman's-Canadiens-
120 - 2021-01-18507Riverman-Canadiens-
121 - 2021-01-19514Canadiens-Riverman-
122 - 2021-01-20522Snipers-Canadiens-
123 - 2021-01-21524Canadiens-Wolves-
125 - 2021-01-23536Spoonman's-Canadiens-
126 - 2021-01-24541Canadiens-As-
129 - 2021-01-27551Citadelles-Canadiens-
132 - 2021-01-30561Citadelles-Canadiens-
133 - 2021-01-31566Canadiens-Banshees-
134 - 2021-02-01567Canadiens-Isotopes-
135 - 2021-02-02573Canadiens-Harvard-



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
741,435$ 988,500$ 988,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
988,500$ 741,435$ 23 1

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 53 7,967$ 422,251$




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