Croque-Morts

GP: 53 | W: 30 | L: 17 | T: 3 | P: 66
GF: 194 | GA: 168 | PP%: 20.45% | PK%: 79.55%
DG: Pascal Beaulieu | Morale : 58 | Moyenne d'Équipe : 65
Prochain matchs #377 vs Snipers
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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)X99.006752676675707076677874726840406867670253450,000$
2Luciano BorsatoX100.007152716767707078697677637246515468670271450,000$
3Ray Whitney (R)X100.005541817769717078687774726830309670670212450,000$
4Tony HrkacX100.006044826968717373687669756645475458660273700,000$
5Dave McLlwainX100.006146777073757371657470716439485971660262455,000$
6Corey MillenX100.005849696971727468667366766454593971660292580,000$
7Tom ChorskeX100.006344836177717272677670726847465357660271625,000$
8Tom FitzgeraldX100.006647846974717271647166826441426859660252525,000$
9Bryan Smolinski (R) (A)X100.005541786977717175677573686832288971650221500,000$
10Brian Savage (R)X100.006650687073666771637469766435378871650222400,000$
11Blair AytchenumX100.006544886877697072627068796232287571650241440,000$
12Brian Holzinger (R)X100.006250707271636462607065746226289057620222220,000$
13Dana MurzynX100.008071546675847170627358785149525371680272515,000$
14Trent YawneyX100.007869555975707062607052835062674871670283627,000$
15Jeff FinleyX100.007157656377697062586857825343446229650262475,000$
16Richard Smehlik (R)X100.006850716479727367617159815429248271640231510,000$
17Dean Malkoc (R)X100.008374406878727257515554785135427529640243500,000$
18Scott Lachance (R)X100.005744796677707266616857785434349656630213480,000$
Rayé
1Dave LowryX100.006856646674787865616867746566724819660281550,000$
2Patrik JuhlinX100.005340817272666869667468736434287519640241150,000$
3Dan Kesa (R)X100.006358646376586057545656715429298820570222230,000$
4Mike KennedyX100.005651695967464652515652495028289520510213145,000$
5Bob Halkidis (A)X100.008272546575757551485648764660585344650271250,000$
6Ivan DroppaX100.005844737073686867596355725230269620610213365,000$
7Eric Cairns (R)X100.007062525980545558495938733128289736580193400,000$
MOYENNE D'ÉQUIPE99.96655270677469696761696274594041725264
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
1Parris Duffus100.00686881787777798581716428338251690
2Jocelyn Thibault (R)98.00737070677775777680747135409936680
Rayé
1Byron Dafoe (R)100.00737877747773788479767335318219700
MOYENNE D'ÉQUIPE99.3371727673777578828074693335883569
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)LW5322355718100321061905315411.58%14110820.91611175422000031315156.94%7200111.0300000265
2Dixon WardCroque-Morts (ANA)RW5120244416660125821535110413.07%10109621.5167134021200021343249.44%35800100.8000000631
3Dana MurzynCroque-Morts (ANA)D53123143153601136578184715.38%83130624.65101222562300110209000.00%000000.6600000321
4Luciano BorsatoCroque-Morts (ANA)LW53232043945597741484010115.54%890717.129716492010004993154.55%18700100.9500010461
5Trent YawneyCroque-Morts (ANA)D5310293913500786366184415.15%70128124.176915492250110196110.00%000000.6100000133
6Bryan SmolinskiCroque-Morts (ANA)C5317223917200181211123610115.18%587616.5313415121000033148.86%110100010.8900000412
7Dave McLlwainCroque-Morts (ANA)RW53162238-16044871345010111.94%993617.6731013391950001491148.00%7500000.8100000214
8Corey MillenCroque-Morts (ANA)C5310283823003814511327718.85%780515.1911112251111012142057.63%98900000.9400000110
9Tony HrkacCroque-Morts (ANA)C53112233516026103106327610.38%1084916.02412163519600041362251.82%93600000.7800000112
10Richard SmehlikCroque-Morts (ANA)D5352025020018505426309.26%60105219.85347351580111138000.00%000000.4800000010
11Brian SavageCroque-Morts (ANA)LW5391120-5280644780254811.25%556210.611231150000692047.14%7000000.7100000201
12Scott LachanceCroque-Morts (ANA)D4021820880634266177.69%2958514.65033311000025100.00%000000.6800000011
13Bob HalkidisCroque-Morts (ANA)D415141988220862539112712.82%3985320.81314221530000133100.00%000000.4500112021
14Tom FitzgeraldCroque-Morts (ANA)RW51810183120175878355010.26%557111.200004300001212057.35%6800000.6300000100
15Blair AytchenumCroque-Morts (ANA)RW5310717-2200163359154916.95%84127.78000001012581046.15%3900000.8200000102
16Brian HolzingerCroque-Morts (ANA)C394913810019674115239.76%739210.070000000001012050.00%50000000.6600000101
17Jeff FinleyCroque-Morts (ANA)D2529112603822228139.09%2853821.55044887000194000.00%000000.4100000012
18Dave LowryCroque-Morts (ANA)LW25268-11204318245218.33%132012.81112140001280044.44%1800000.5000000000
19Tom ChorskeCroque-Morts (ANA)LW44437340142438103310.53%22696.1200010000011043.75%1600000.5200000002
20Dean MalkocCroque-Morts (ANA)D252461520591573528.57%2037915.1600013000027000.00%000000.3200000000
21Eric CairnsCroque-Morts (ANA)D28044363550139230.00%2141114.7100003000034000.00%000000.1900010000
22Patrik JuhlinCroque-Morts (ANA)RW2000100001120.00%0199.71000000000000100.00%100000.0000000000
Stats d'équipe Total ou en Moyenne95419434854212359630100112521578487112012.29%4411553416.285497151438218523522171030952.03%443000320.7000132292929
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)2415500.8882.98120701605380100.00002117100
2Parris DuffusCroque-Morts (ANA)158400.8892.9373801363250000.00001032100
3Byron DafoeCroque-Morts (ANA)2271130.8593.42126440725090000.0000224010
Stats d'équipe Total ou en Moyenne61302030.8783.1432104216813720100.00005353210


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)RW241996-02-09 9:08:37 PMNo210 Lbs6 ft2NoNoNo1Pro & Farm440,000$44,000$16,176$No
Bob HalkidisCroque-Morts (ANA)D271993-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo1Pro & Farm250,000$25,000$9,191$No
Brian HolzingerCroque-Morts (ANA)C221998-02-09 9:08:37 PMYes190 Lbs5 ft11NoNoNo2Pro & Farm220,000$22,000$8,088$No220,000$
Brian SavageCroque-Morts (ANA)LW221998-02-09 9:08:37 PMYes192 Lbs6 ft2NoNoNo2Pro & Farm400,000$40,000$14,706$No400,000$
Bryan SmolinskiCroque-Morts (ANA)C221998-02-09 9:08:37 PMYes209 Lbs6 ft1NoNoNo1Pro & Farm500,000$50,000$18,382$No
Byron DafoeCroque-Morts (ANA)G231997-02-09 9:08:37 PMYes190 Lbs5 ft11NoNoNo1Pro & Farm300,000$30,000$11,029$No
Corey MillenCroque-Morts (ANA)C291991-02-09 9:08:37 PMNo184 Lbs6 ft0NoNoNo2Pro & Farm580,000$58,000$21,324$No580,000$
Dan KesaCroque-Morts (ANA)RW221998-02-09 9:08:37 PMYes208 Lbs6 ft0NoNoNo2Pro & Farm230,000$23,000$8,456$No230,000$
Dana MurzynCroque-Morts (ANA)D271993-02-09 9:08:37 PMNo200 Lbs6 ft2NoNoNo2Pro & Farm515,000$51,500$18,934$No515,000$
Dave LowryCroque-Morts (ANA)LW281992-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo1Pro & Farm550,000$55,000$20,221$No
Dave McLlwainCroque-Morts (ANA)RW261994-02-09 9:08:37 PMNo185 Lbs6 ft1NoNoNo2Pro & Farm455,000$45,500$16,728$No455,000$
Dean MalkocCroque-Morts (ANA)D241996-02-09 9:08:37 PMYes210 Lbs6 ft3NoNoNo3Pro & Farm500,000$50,000$18,382$No500,000$500,000$
Dixon WardCroque-Morts (ANA)RW251995-02-09 9:08:37 PMYes200 Lbs6 ft0NoNoNo3Pro & Farm450,000$45,000$16,544$No450,000$450,000$
Eric CairnsCroque-Morts (ANA)D192001-02-09 9:08:37 PMYes220 Lbs6 ft5NoNoNo3Pro & Farm400,000$40,000$14,706$No400,000$400,000$
Ivan DroppaCroque-Morts (ANA)D211999-02-09 9:08:37 PMNo185 Lbs6 ft2NoNoNo3Pro & Farm365,000$36,500$13,419$No365,000$365,000$
Jeff FinleyCroque-Morts (ANA)D261994-02-09 9:08:37 PMNo205 Lbs6 ft2NoNoNo2Pro & Farm475,000$47,500$17,463$No475,000$
Jocelyn ThibaultCroque-Morts (ANA)G192001-08-11 10:49:31 AMYes170 Lbs5 ft11NoNoNo3Pro & Farm250,000$25,000$9,191$No250,000$250,000$
Luciano BorsatoCroque-Morts (ANA)LW271993-02-09 9:08:37 PMNo165 Lbs5 ft10NoNoNo1Pro & Farm450,000$45,000$16,544$No
Mike KennedyCroque-Morts (ANA)C211999-02-09 9:08:37 PMNo200 Lbs6 ft0NoNoNo3Pro & Farm145,000$14,500$5,331$No145,000$145,000$
Parris DuffusCroque-Morts (ANA)G231997-02-09 9:08:37 PMNo192 Lbs6 ft2NoNoNo1Pro & Farm300,000$30,000$11,029$No
Patrik JuhlinCroque-Morts (ANA)RW241996-02-09 9:08:37 PMNo194 Lbs6 ft1NoNoNo1Pro & Farm150,000$15,000$5,515$No
Ray WhitneyCroque-Morts (ANA)LW211999-02-09 9:08:37 PMYes175 Lbs5 ft10NoNoNo2Pro & Farm450,000$45,000$16,544$No450,000$
Richard SmehlikCroque-Morts (ANA)D231997-02-09 9:08:37 PMYes222 Lbs6 ft3NoNoNo1Pro & Farm510,000$51,000$18,750$No
Scott LachanceCroque-Morts (ANA)D211999-02-09 9:08:37 PMYes209 Lbs6 ft1NoNoNo3Pro & Farm480,000$48,000$17,647$No480,000$480,000$
Tom ChorskeCroque-Morts (ANA)LW271993-02-09 9:08:37 PMNo212 Lbs6 ft1NoNoNo1Pro & Farm625,000$62,500$22,978$No
Tom FitzgeraldCroque-Morts (ANA)RW251995-02-09 9:08:37 PMNo191 Lbs6 ft0NoNoNo2Pro & Farm525,000$52,500$19,301$No525,000$
Tony HrkacCroque-Morts (ANA)C271993-02-09 9:08:37 PMNo170 Lbs5 ft11NoNoNo3Pro & Farm700,000$70,000$25,735$No700,000$700,000$
Trent YawneyCroque-Morts (ANA)D281992-02-09 9:08:37 PMNo195 Lbs6 ft3NoNoNo3Pro & Farm627,000$62,700$23,051$No627,000$627,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2824.04196 Lbs6 ft11.96422,929$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Ray WhitneyBryan SmolinskiDixon Ward35122
2Luciano BorsatoCorey MillenDave McLlwain30122
3Brian SavageTony HrkacTom Fitzgerald20122
4Tom ChorskeBrian HolzingerBlair Aytchenum15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dana MurzynTrent Yawney35122
2Jeff FinleyRichard Smehlik30122
3Dean MalkocScott Lachance20122
4Dana MurzynTrent Yawney15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Ray WhitneyBryan SmolinskiDixon Ward60122
2Luciano BorsatoTony HrkacDave McLlwain40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dana MurzynTrent Yawney60122
2Jeff FinleyRichard Smehlik40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Brian HolzingerDixon Ward60122
2Tony HrkacBlair Aytchenum40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dana MurzynTrent Yawney60122
2Jeff FinleyRichard Smehlik40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Brian Holzinger60122Dana MurzynTrent Yawney60122
2Bryan Smolinski40122Jeff FinleyRichard Smehlik40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Luciano BorsatoDixon Ward60122
2Ray WhitneyTony Hrkac40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dana MurzynTrent Yawney60122
2Jeff FinleyRichard Smehlik40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Luciano BorsatoTony HrkacDixon WardDana MurzynTrent Yawney
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Luciano BorsatoTony HrkacDixon WardDana MurzynTrent Yawney
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Tom Fitzgerald, Tom Chorske, Blair AytchenumTom Fitzgerald, Tom ChorskeBlair Aytchenum
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dean Malkoc, Scott Lachance, Jeff FinleyDean MalkocScott Lachance, Jeff Finley
Tirs de Pénalité
Luciano Borsato, Dixon Ward, Ray Whitney, Tony Hrkac, Dave McLlwain
Gardien
#1 : Parris Duffus, #2 : Jocelyn Thibault


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 Rouges65100000291811321000001293330000001798100.833295786016567602214508508549131506362102401332.50%29679.31%0957182852.35%911172052.97%43788249.55%12828711233418696346
2As7520000027234440000001881031200000915-6100.71427467300656760221450850854913188568013439820.51%38878.95%1957182852.35%911172052.97%43788249.55%12828711233418696346
3Banshees3120000078-1211000005501010000023-120.33371320006567602635085085491377273661900.00%17476.47%0957182852.35%911172052.97%43788249.55%12828711233418696346
4Canadiens42101000171252010100089-12200000093660.7501728450065676021335085085491310233407818316.67%19478.95%0957182852.35%911172052.97%43788249.55%12828711233418696346
5Chiefs6321000029209431000002212102011000078-170.583295180006567602200508508549131394354139331030.30%26676.92%0957182852.35%911172052.97%43788249.55%12828711233418696346
6Citadelles1000010045-1000000000001000010045-110.50048120065676022450850854913441310252150.00%5260.00%0957182852.35%911172052.97%43788249.55%12828711233418696346
7Harvard522100001918122000000945302100001014-450.50019345300656760213750850854913127285110218527.78%22481.82%0957182852.35%911172052.97%43788249.55%12828711233418696346
8Isotopes11000000422000000000001100000042221.000471100656760227508508549132111611400.00%3166.67%0957182852.35%911172052.97%43788249.55%12828711233418696346
9Pacifiques de la route513001001117-63120000059-42010010068-230.3001121320065676021245085085491313041978625312.00%33875.76%1957182852.35%911172052.97%43788249.55%12828711233418696346
10Riverman31100100990211000007611000010023-130.500916250065676027250850854913943043511218.33%18288.89%0957182852.35%911172052.97%43788249.55%12828711233418696346
11Snipers11000000743110000007430000000000021.0007121900656760241508508549133968123133.33%4175.00%0957182852.35%911172052.97%43788249.55%12828711233418696346
12Spoonman's22000000523110000003211100000020241.00058130165676024350850854913441524345240.00%90100.00%0957182852.35%911172052.97%43788249.55%12828711233418696346
Total532817323001941682627178110001048123261192130090873660.623194348542026567602157850850854913137244160010012645420.45%2645479.55%2957182852.35%911172052.97%43788249.55%12828711233418696346
13Wolves943110002630-431110000813-56320100018171110.61126477300656760228650850854913217758916656712.50%41880.49%0957182852.35%911172052.97%43788249.55%12828711233418696346
_Since Last GM Reset53311702300194168262717811000104812326149-1130090873690.651194348542026567602157850850854913137244160010012645420.45%2645479.55%2957182852.35%911172052.97%43788249.55%12828711233418696346
_Vs Conference3118100120010910181610510000574981585-1120052520400.645109199308016567602951508508549138182713795511753318.86%1633379.75%2957182852.35%911172052.97%43788249.55%12828711233418696346
_Vs Division2215601000827111107210000383081284-1100044413320.72782150232016567602714508508549135551942314021352820.74%1082279.63%1957182852.35%911172052.97%43788249.55%12828711233418696346

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5366W319434854215781372441600100102
Tous les Matchs
GPWLOTWOTL TGFGA
532817233194168
Matchs locaux
GPWLOTWOTL TGFGA
2717810110481
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
261191329087
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
2645420.45%2645479.55%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
508508549136567602
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
957182852.35%911172052.97%43788249.55%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12828711233418696346


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-Morts-Snipers-
90 - 2020-12-19385Riverman-Croque-Morts-
92 - 2020-12-21390Croque-Morts-As-
94 - 2020-12-23397Croque-Morts-Riverman-
96 - 2020-12-25402Spoonman's-Croque-Morts-
98 - 2020-12-27413Snipers-Croque-Morts-
100 - 2020-12-29420Croque-Morts-Spoonman's-
101 - 2020-12-30427Ailes Rouges-Croque-Morts-
103 - 2021-01-01431Croque-Morts-Banshees-
105 - 2021-01-03441Citadelles-Croque-Morts-
106 - 2021-01-04447Croque-Morts-Ailes Rouges-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
109 - 2021-01-07455Croque-Morts-Canadiens-
110 - 2021-01-08457Isotopes-Croque-Morts-
112 - 2021-01-10466Isotopes-Croque-Morts-
113 - 2021-01-11473Croque-Morts-As-
115 - 2021-01-13479As-Croque-Morts-
116 - 2021-01-14490Croque-Morts-Pacifiques de la route-
117 - 2021-01-15494Croque-Morts-Isotopes-
118 - 2021-01-16499Citadelles-Croque-Morts-
119 - 2021-01-17505Croque-Morts-Citadelles-
120 - 2021-01-18511Croque-Morts-Snipers-
121 - 2021-01-19517Wolves-Croque-Morts-
122 - 2021-01-20523Croque-Morts-Riverman-
124 - 2021-01-22530Spoonman's-Croque-Morts-
125 - 2021-01-23534Croque-Morts-Citadelles-
126 - 2021-01-24540Croque-Morts-Snipers-
127 - 2021-01-25546Isotopes-Croque-Morts-
130 - 2021-01-28557Isotopes-Croque-Morts-
134 - 2021-02-01572Banshees-Croque-Morts-



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
14 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
807,150$ 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$ 807,150$ 28 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 50 9,406$ 470,300$




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