Croque-Morts
GP: 82 | W: 48 | L: 26 | T: 3 | P: 104
GF: 315 | GA: 256 | PP%: 21.76% | PK%: 79.50%
DG: Pascal Beaulieu | Morale : 63 | 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
1Dixon Ward (R)X100.006752676675707076677874726840406879670263450,000$
2Luciano BorsatoX100.007152716767707078697677637246515475670281450,000$
3Ray Whitney (R)X100.005541817769717078687774726830309670670222450,000$
4Tony HrkacX100.006044826968717373687669756645475470660283700,000$
5Dave LowryX100.006856646674787865616867746566724824660291550,000$
6Dave McLlwainX100.006146777073757371657470716439485980660272455,000$
7Corey MillenX100.005849696971727468667366766454593980660302580,000$
8Tom ChorskeX100.006344836177717272677670726847465369660281625,000$
9Tom FitzgeraldX100.006647846974717271647166826441426871660262525,000$
10Bryan Smolinski (R) (A)X100.005541786977717175677573686832288970650231500,000$
11Brian Savage (R)X100.006650687073666771637469766435378872650232400,000$
12Blair AytchenumX100.006544886877697072627068796232287580650251440,000$
13Dana MurzynX100.008071546675847170627358785149525378680282515,000$
14Trent YawneyX100.007869555975707062607052835062674873670293627,000$
15Bob Halkidis (A)X100.008272546575757551485648764660585339650281250,000$
16Jeff FinleyX100.007157656377697062586857825343446226650272475,000$
17Richard Smehlik (R)X100.006850716479727367617159815429248280640241510,000$
18Dean Malkoc (R)X100.008374406878727257515554785135427532640253500,000$
Rayé
1Patrik JuhlinX100.005340817272666869667468736434287520640251150,000$
2Brian Holzinger (R)X100.006250707271636462607065746226289048620232220,000$
3Dan Kesa (R)X100.006358646376586057545656715429298820570232230,000$
4Mike KennedyX100.005651695967464652515652495028289520510223145,000$
5Scott Lachance (R)X100.005744796677707266616857785434349647630223480,000$
6Ivan DroppaX100.005844737073686867596355725230269620610223365,000$
7Eric Cairns (R)X100.007062525980545558495938733128289719580203400,000$
MOYENNE D'ÉQUIPE100.00655270677469696761696274594041725464
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
1Byron Dafoe (R)100.00737877747773788479767335318217700
2Jocelyn Thibault (R)100.00737070677775777680747135409927680
Rayé
1Parris Duffus100.00686881787777798581716428338259690
MOYENNE D'ÉQUIPE100.0071727673777578828074693335883469
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Al Arbour80798474999858CAN62295,000$


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
1Ray WhitneyCroque-Morts (ANA)LW7838539129180461512718621514.02%19162920.89818267232500042187253.69%14900111.1200000787
2Dixon WardCroque-Morts (ANA)RW80384280258401891232567217614.84%17169821.231212247233200052315351.54%51800200.9400000952
3Luciano BorsatoCroque-Morts (ANA)LW79353974147151571262205915115.91%11146418.541415297029700061793151.98%40400101.0100010774
4Tony HrkacCroque-Morts (ANA)C8224446813280571751965112412.24%16137216.741017276731600051844352.10%159300000.9900000353
5Dana MurzynCroque-Morts (ANA)D821750679741018097120338414.17%120200624.47112031853550110313000.00%000000.6700110343
6Corey MillenCroque-Morts (ANA)C821947664400601981815411010.50%11126515.4442125472051012194057.84%159400001.0400000321
7Dave McLlwainCroque-Morts (ANA)RW822431559220711182067316211.65%10136216.6151217512530001521154.55%11000000.8100000234
8Bryan SmolinskiCroque-Morts (ANA)C8223325532260291621644615214.02%9125615.3324621142000034148.97%155000010.8800000423
9Trent YawneyCroque-Morts (ANA)D80143852108201238898306314.29%115192224.0381321733340110289110.00%000000.5400000233
10Richard SmehlikCroque-Morts (ANA)D829324119375337679375011.39%90154218.81459502070111178200.00%000000.5300001010
11Tom FitzgeraldCroque-Morts (ANA)RW801525401026046112134599011.19%7104713.1024619940002535049.59%12300000.7600000122
12Brian SavageCroque-Morts (ANA)LW81121628-3320735598295912.24%57088.751343220000752049.37%7900000.7900000301
13Jeff FinleyCroque-Morts (ANA)D5452025918066445121409.80%56113020.9321012251940001188000.00%000000.4400000012
14Scott LachanceCroque-Morts (ANA)D5432225251401142328229.38%4179814.78033313000040200.00%000000.6300000011
15Bob HalkidisCroque-Morts (ANA)D63717247129351593955153612.73%64132721.07426352350000204200.00%000000.3600223021
16Blair AytchenumCroque-Morts (ANA)RW821210221220264885226814.12%115997.32000011013791042.62%6100000.7300000102
17Brian HolzingerCroque-Morts (ANA)C52712198140287856193212.50%85099.790000000001173047.81%64000000.7500000102
18Dave LowryCroque-Morts (ANA)LW4559144200762844124011.36%364814.422134290001711051.28%3900000.4300000010
19Tom ChorskeCroque-Morts (ANA)LW73681468031436321559.52%35076.9500026000071055.00%4000000.5500000003
20Dean MalkocCroque-Morts (ANA)D49281020100012930236148.70%3774615.2400017000055000.00%000000.2700000000
21Eric CairnsCroque-Morts (ANA)D28044363550139230.00%2141114.7100003000034000.00%000000.1900010000
22Patrik JuhlinCroque-Morts (ANA)RW6000120021120.00%0355.9700000000000071.43%1400000.0000000000
Stats d'équipe Total ou en Moyenne147631555987425593060164018482442756174812.90%6742399316.26891602497003381235312598481252.24%691400420.7300354464744
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
1Jocelyn ThibaultCroque-Morts (ANA)3018800.8852.94157101776710100.00002725100
2Byron DafoeCroque-Morts (ANA)37161730.8663.352062421158600000.0000377110
3Parris DuffusCroque-Morts (ANA)2714600.9002.87131821636300110.00001850201
Stats d'équipe Total ou en Moyenne94483130.8823.0949526425521610210.00008282411


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
Blair AytchenumCroque-Morts (ANA)RW251996-02-09 9:08:37 PMNo210 Lbs6 ft2NoNoNo1Pro & Farm440,000$44,000$324$No
Bob HalkidisCroque-Morts (ANA)D281993-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo1Pro & Farm250,000$25,000$184$No
Brian HolzingerCroque-Morts (ANA)C231998-02-09 9:08:37 PMYes190 Lbs5 ft11NoNoNo2Pro & Farm220,000$22,000$162$No220,000$
Brian SavageCroque-Morts (ANA)LW231998-02-09 9:08:37 PMYes192 Lbs6 ft2NoNoNo2Pro & Farm400,000$40,000$294$No400,000$
Bryan SmolinskiCroque-Morts (ANA)C231998-02-09 9:08:37 PMYes209 Lbs6 ft1NoNoNo1Pro & Farm500,000$50,000$368$No
Byron DafoeCroque-Morts (ANA)G241997-02-09 9:08:37 PMYes190 Lbs5 ft11NoNoNo1Pro & Farm300,000$30,000$221$No
Corey MillenCroque-Morts (ANA)C301991-02-09 9:08:37 PMNo184 Lbs6 ft0NoNoNo2Pro & Farm580,000$58,000$426$No580,000$
Dan KesaCroque-Morts (ANA)RW231998-02-09 9:08:37 PMYes208 Lbs6 ft0NoNoNo2Pro & Farm230,000$23,000$169$No230,000$
Dana MurzynCroque-Morts (ANA)D281993-02-09 9:08:37 PMNo200 Lbs6 ft2NoNoNo2Pro & Farm515,000$51,500$379$No515,000$
Dave LowryCroque-Morts (ANA)LW291992-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo1Pro & Farm550,000$55,000$404$No
Dave McLlwainCroque-Morts (ANA)RW271994-02-09 9:08:37 PMNo185 Lbs6 ft1NoNoNo2Pro & Farm455,000$45,500$335$No455,000$
Dean MalkocCroque-Morts (ANA)D251996-02-09 9:08:37 PMYes210 Lbs6 ft3NoNoNo3Pro & Farm500,000$50,000$368$No500,000$500,000$
Dixon WardCroque-Morts (ANA)RW261995-02-09 9:08:37 PMYes200 Lbs6 ft0NoNoNo3Pro & Farm450,000$45,000$331$No450,000$450,000$
Eric CairnsCroque-Morts (ANA)D202001-02-09 9:08:37 PMYes220 Lbs6 ft5NoNoNo3Pro & Farm400,000$40,000$294$No400,000$400,000$
Ivan DroppaCroque-Morts (ANA)D221999-02-09 9:08:37 PMNo185 Lbs6 ft2NoNoNo3Pro & Farm365,000$36,500$268$No365,000$365,000$
Jeff FinleyCroque-Morts (ANA)D271994-02-09 9:08:37 PMNo205 Lbs6 ft2NoNoNo2Pro & Farm475,000$47,500$349$No475,000$
Jocelyn ThibaultCroque-Morts (ANA)G192001-08-11 10:49:31 AMYes170 Lbs5 ft11NoNoNo3Pro & Farm250,000$25,000$184$No250,000$250,000$
Luciano BorsatoCroque-Morts (ANA)LW281993-02-09 9:08:37 PMNo165 Lbs5 ft10NoNoNo1Pro & Farm450,000$45,000$331$No
Mike KennedyCroque-Morts (ANA)C221999-02-09 9:08:37 PMNo200 Lbs6 ft0NoNoNo3Pro & Farm145,000$14,500$107$No145,000$145,000$
Parris DuffusCroque-Morts (ANA)G241997-02-09 9:08:37 PMNo192 Lbs6 ft2NoNoNo1Pro & Farm300,000$30,000$221$No
Patrik JuhlinCroque-Morts (ANA)RW251996-02-09 9:08:37 PMNo194 Lbs6 ft1NoNoNo1Pro & Farm150,000$15,000$110$No
Ray WhitneyCroque-Morts (ANA)LW221999-02-09 9:08:37 PMYes175 Lbs5 ft10NoNoNo2Pro & Farm450,000$45,000$331$No450,000$
Richard SmehlikCroque-Morts (ANA)D241997-02-09 9:08:37 PMYes222 Lbs6 ft3NoNoNo1Pro & Farm510,000$51,000$375$No
Scott LachanceCroque-Morts (ANA)D221999-02-09 9:08:37 PMYes209 Lbs6 ft1NoNoNo3Pro & Farm480,000$48,000$353$No480,000$480,000$
Tom ChorskeCroque-Morts (ANA)LW281993-02-09 9:08:37 PMNo212 Lbs6 ft1NoNoNo1Pro & Farm625,000$62,500$460$No
Tom FitzgeraldCroque-Morts (ANA)RW261995-02-09 9:08:37 PMNo191 Lbs6 ft0NoNoNo2Pro & Farm525,000$52,500$386$No525,000$
Tony HrkacCroque-Morts (ANA)C281993-02-09 9:08:37 PMNo170 Lbs5 ft11NoNoNo3Pro & Farm700,000$70,000$515$No700,000$700,000$
Trent YawneyCroque-Morts (ANA)D291992-02-09 9:08:37 PMNo195 Lbs6 ft3NoNoNo3Pro & Farm627,000$62,700$461$No627,000$627,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2825.00196 Lbs6 ft11.96422,929$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Luciano BorsatoCorey MillenDixon Ward35122
2Ray WhitneyTony HrkacDave McLlwain30122
3Dave LowryBryan SmolinskiTom Fitzgerald20122
4Tom ChorskeLuciano BorsatoBlair Aytchenum15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dana MurzynTrent Yawney35122
2Jeff FinleyBob Halkidis30122
3Richard SmehlikDean Malkoc20122
4Dana MurzynTrent Yawney15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Luciano BorsatoCorey MillenDixon Ward60122
2Ray WhitneyTony HrkacDave McLlwain40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dana MurzynTrent Yawney60122
2Jeff FinleyBob Halkidis40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Luciano BorsatoRay Whitney60122
2Dixon WardDave Lowry40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dana MurzynTrent Yawney60122
2Jeff FinleyBob Halkidis40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Luciano Borsato60122Dana MurzynTrent Yawney60122
2Ray Whitney40122Jeff FinleyBob Halkidis40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Luciano BorsatoRay Whitney60122
2Dixon WardDave Lowry40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dana MurzynTrent Yawney60122
2Jeff FinleyBob Halkidis40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Luciano BorsatoCorey MillenDixon WardDana MurzynTrent Yawney
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Luciano BorsatoCorey MillenDixon WardDana MurzynTrent Yawney
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brian Savage, Tom Chorske, Tom FitzgeraldBrian Savage, Tom ChorskeTom Fitzgerald
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Richard Smehlik, Dean Malkoc, Jeff FinleyRichard SmehlikDean Malkoc, Jeff Finley
Tirs de Pénalité
Luciano Borsato, Ray Whitney, Dixon Ward, Dave Lowry, Dave McLlwain
Gardien
#1 : Jocelyn Thibault, #2 : Byron Dafoe


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 Rouges87100000412417431000001811744000000231310140.875417511601113110902269784821821162077982139511631.37%38878.95%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
2As107300000393365410000020119532000001922-3140.7003969108001131109023057848218211627776120198551120.00%571377.19%11462279852.25%1449274052.88%701137650.94%1966133419186471072531
3Banshees5320000015123321000009722110000065160.6001526410011311090211978482182116127456310916212.50%28678.57%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
4Canadiens531010002313102010100089-1330000001541180.800234063001131109021717848218211611444429526519.23%20480.00%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
5Chiefs6321000029209431000002212102011000078-170.58329518000113110902200784821821161394354139331030.30%26676.92%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
6Citadelles531001002116522000000927311001001214-270.7002138590011311090215478482182116160485911922836.36%24675.00%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
7Harvard522100001918122000000945302100001014-450.5001934530011311090213778482182116127285110218527.78%22481.82%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
8Isotopes6320010023185412001001416-22200000092770.5832341640111311090216878482182116155437611124312.50%27677.78%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
9Pacifiques de la route614001001422-83120000059-430200100913-430.25014274110113110902151784821821161605110311528310.71%36877.78%11462279852.25%1449274052.88%701137650.94%1966133419186471072531
10Riverman632001002417731200000910-132000100157870.5832443670011311090219578482182116155536310631516.13%26484.62%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
11Snipers53200000201732110000088032100000129360.6002034540011311090212978482182116167426110717529.41%26580.77%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
12Spoonman's53100100181623200010011922110000077070.7001830480111311090214478482182116132446211427829.63%27485.19%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
13Wolves1053110002930-1421100001113-26320100018171130.65029518001113110902300784821821162427810018661813.11%43881.40%01462279852.25%1449274052.88%701137650.94%1966133419186471072531
Total8246263250031525659412413112001531213241221321300162135271040.63431555987414113110902244278482182116216267493616404098921.76%4008279.50%21462279852.25%1449274052.88%701137650.94%1966133419186471072531
_Since Last GM Reset82492602500315256594124131120015312132412513-11300162135271070.65231555987414113110902244278482182116216267493616404098921.76%4008279.50%21462279852.25%1449274052.88%701137650.94%1966133419186471072531
_Vs Conference452715012001671432421128100007162924157-11200968115580.6441672994661211311090213497848218211612083795298512434819.75%2264679.65%21462279852.25%1449274052.88%701137650.94%1966133419186471072531
_Vs Division2820701000109872213931000049351415114-1100060528420.75010919530402113110902874784821821167262333025231673520.96%1382978.99%11462279852.25%1449274052.88%701137650.94%1966133419186471072531

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
82104W131555987424422162674936164014
Tous les Matchs
GPWLOTWOTL TGFGA
824626253315256
Matchs locaux
GPWLOTWOTL TGFGA
412413121153121
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
412213132162135
Derniers 10 Matchs
WLOTWOTL T
72010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4098921.76%4008279.50%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
78482182116113110902
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
1462279852.25%1449274052.88%701137650.94%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1966133419186471072531


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 - 2020-09-213As3Croque-Morts5WSommaire du Match
2 - 2020-09-2212Croque-Morts2As6LSommaire du Match
4 - 2020-09-2418Chiefs4Croque-Morts3LSommaire du Match
6 - 2020-09-2626Croque-Morts8Ailes Rouges5WSommaire du Match
7 - 2020-09-2735Ailes Rouges0Croque-Morts3WSommaire du Match
9 - 2020-09-2945As2Croque-Morts3WSommaire du Match
10 - 2020-09-3048Croque-Morts3Wolves5LSommaire du Match
11 - 2020-10-0155Croque-Morts5As3WSommaire du Match
13 - 2020-10-0363Croque-Morts3Wolves2WXSommaire du Match
15 - 2020-10-0568Wolves3Croque-Morts4WSommaire du Match
17 - 2020-10-0776Croque-Morts5Wolves3WSommaire du Match
19 - 2020-10-0982Pacifiques de la route4Croque-Morts1LSommaire du Match
21 - 2020-10-1189Chiefs2Croque-Morts5WSommaire du Match
23 - 2020-10-13100Ailes Rouges3Croque-Morts5WSommaire du Match
25 - 2020-10-15103Croque-Morts1Wolves3LSommaire du Match
27 - 2020-10-17114Ailes Rouges6Croque-Morts4LSommaire du Match
29 - 2020-10-19120Croque-Morts2Banshees3LSommaire du Match
31 - 2020-10-21126Canadiens2Croque-Morts3WXSommaire du Match
33 - 2020-10-23135Pacifiques de la route2Croque-Morts3WSommaire du Match
35 - 2020-10-25142Croque-Morts3Chiefs4LSommaire du Match
37 - 2020-10-27148Croque-Morts5Ailes Rouges1WSommaire du Match
39 - 2020-10-29155Croque-Morts5Canadiens1WSommaire du Match
41 - 2020-10-31162As1Croque-Morts2WSommaire du Match
42 - 2020-11-01165Croque-Morts2Spoonman's0WSommaire du Match
44 - 2020-11-03174Croque-Morts4Pacifiques de la route5LXSommaire du Match
46 - 2020-11-05180Riverman4Croque-Morts3LSommaire du Match
47 - 2020-11-06186Croque-Morts4Isotopes2WSommaire du Match
48 - 2020-11-07193Spoonman's2Croque-Morts3WSommaire du Match
50 - 2020-11-09202Chiefs4Croque-Morts5WSommaire du Match
52 - 2020-11-11213Riverman2Croque-Morts4WSommaire du Match
53 - 2020-11-12219Croque-Morts4Ailes Rouges3WSommaire du Match
55 - 2020-11-14224Croque-Morts4Chiefs4TXSommaire du Match
57 - 2020-11-16232Wolves1Croque-Morts1TXSommaire du Match
58 - 2020-11-17237Croque-Morts3Harvard5LSommaire du Match
59 - 2020-11-18245Canadiens7Croque-Morts5LSommaire du Match
61 - 2020-11-20254Pacifiques de la route3Croque-Morts1LSommaire du Match
62 - 2020-11-21259Croque-Morts4Canadiens2WSommaire du Match
65 - 2020-11-24266Croque-Morts3Harvard5LSommaire du Match
66 - 2020-11-25273Harvard2Croque-Morts4WSommaire du Match
67 - 2020-11-26281Wolves9Croque-Morts3LSommaire du Match
68 - 2020-11-27289Croque-Morts4Harvard4TXSommaire du Match
70 - 2020-11-29294Croque-Morts2Riverman3LXSommaire du Match
72 - 2020-12-01302Banshees2Croque-Morts1LSommaire du Match
73 - 2020-12-02309Croque-Morts4Citadelles5LXSommaire du Match
74 - 2020-12-03312Croque-Morts3Wolves2WSommaire du Match
75 - 2020-12-04319Harvard2Croque-Morts5WSommaire du Match
77 - 2020-12-06329Snipers4Croque-Morts7WSommaire du Match
78 - 2020-12-07335Croque-Morts2As6LSommaire du Match
79 - 2020-12-08340As2Croque-Morts8WSommaire du Match
80 - 2020-12-09351Croque-Morts2Pacifiques de la route3LSommaire du Match
82 - 2020-12-11355Chiefs2Croque-Morts9WSommaire du Match
84 - 2020-12-13359Croque-Morts3Wolves2WSommaire du Match
86 - 2020-12-15370Banshees3Croque-Morts4WSommaire du Match
88 - 2020-12-17377Croque-Morts5Snipers1WSommaire du Match
90 - 2020-12-19385Riverman4Croque-Morts2LSommaire du Match
92 - 2020-12-21390Croque-Morts5As4WSommaire du Match
94 - 2020-12-23397Croque-Morts7Riverman2WSommaire du Match
96 - 2020-12-25402Spoonman's5Croque-Morts4LXSommaire du Match
98 - 2020-12-27413Snipers4Croque-Morts1LSommaire du Match
100 - 2020-12-29420Croque-Morts5Spoonman's7LSommaire du Match
101 - 2020-12-30427Ailes Rouges2Croque-Morts6WSommaire du Match
103 - 2021-01-01431Croque-Morts4Banshees2WSommaire du Match
105 - 2021-01-03441Citadelles1Croque-Morts4WSommaire du Match
106 - 2021-01-04447Croque-Morts6Ailes Rouges4WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
109 - 2021-01-07455Croque-Morts6Canadiens1WSommaire du Match
110 - 2021-01-08457Isotopes6Croque-Morts4LSommaire du Match
112 - 2021-01-10466Isotopes5Croque-Morts4LSommaire du Match
113 - 2021-01-11473Croque-Morts5As3WSommaire du Match
115 - 2021-01-13479As3Croque-Morts2LSommaire du Match
116 - 2021-01-14490Croque-Morts3Pacifiques de la route5LSommaire du Match
117 - 2021-01-15494Croque-Morts5Isotopes0WSommaire du Match
118 - 2021-01-16499Citadelles1Croque-Morts5WSommaire du Match
119 - 2021-01-17505Croque-Morts5Citadelles4WSommaire du Match
120 - 2021-01-18511Croque-Morts6Snipers3WSommaire du Match
121 - 2021-01-19517Wolves0Croque-Morts3WSommaire du Match
122 - 2021-01-20523Croque-Morts6Riverman2WSommaire du Match
124 - 2021-01-22530Spoonman's2Croque-Morts4WSommaire du Match
125 - 2021-01-23534Croque-Morts3Citadelles5LSommaire du Match
126 - 2021-01-24540Croque-Morts1Snipers5LSommaire du Match
127 - 2021-01-25546Isotopes3Croque-Morts5WSommaire du Match
130 - 2021-01-28557Isotopes2Croque-Morts1LXSommaire du Match
134 - 2021-02-01572Banshees2Croque-Morts4WSommaire 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
1,263,405$ 1,184,200$ 1,184,200$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
1,184,200$ 1,263,405$ 28 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 1 9,406$ 9,406$




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