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Marlies

GP: 79 | W: 52 | L: 25 | OTL: 2 | P: 106
GF: 386 | GA: 234 | PP%: 23.63% | PK%: 78.38%
DG: | Morale : 50 | Moyenne d'Équipe : 60
Prochain matchs #1231 vs Bears
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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 SP
1Andy AndreoffXX100.00654479607894955864595962607568050630
2Nathan BastianX100.00724981608783695952566458596362050620
3Mackenzie MacEachernX100.00723886617872636054586360586966050620
4Morgan GeekieX100.00653691608294935864595661586163050620
5Mitchell StephensX100.00593593627380746165605958606362050610
6Remi ElieX100.00813688598173625653585759586764050610
7Austin PoganskiX100.00633593587791875762595358556563050600
8Anders BjorkXX100.00543592587277625653605759566563050600
9Clark BishopX100.00703982587775645763565659536563050600
10Marian Studenic (R)X100.00533691577092895659555456556163050590
11Ryan SproulX100.00713692588792895630575361467166050620
12Rasmus Sandin (R)X100.00563690607185795930625356515962050600
13Urho Vaakanainen (R)X100.00553593637473626230575456466062050600
14Dylan BlujusX100.00653981558285795430535056486965050580
Rayé
1Ben ThomsonX100.00694370558490855356545157527166050590
2Beck MalenstynX100.00653982548094955355525255536163050580
3Blake SpeersX100.00583787556985795462535255546362050580
4Hudson ElynuikX100.00633977568571625465565357526163050580
5Matheson IacopelliX100.00683885558278725453515155526965050580
6Tyler VeselX100.00523595555892885458555153526965050580
7Tanner KaspickX100.00613788547487815355525254506163050580
8Vili SaarijarviX100.00563691585893915730545153506362050580
MOYENNE D'ÉQUIPE100.0063388758768478565256555754656405060
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
1Stuart Skinner100.0071656388706971706971706165050620
Rayé
MOYENNE D'ÉQUIPE100.007165638870697170697170616505062
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Andy AndreoffMarlies (TOR)C/LW7945571024914011622539111226511.51%38158620.08514195115901182034460.83%181000021.2926000439
2Mackenzie MacEachernMarlies (TOR)LW7945549960562020913144713033710.07%19154019.518513481400001686154.12%17000031.2825004774
3Morgan GeekieMarlies (TOR)C7936609659355103206372982659.68%14145518.42291147142000036160.20%196500011.3201001466
4Austin WagnerMaple LeafsLW593856945138101841133358824411.34%17136023.06391229106101101202448.79%41200041.38130001243
5Nathan BastianMarlies (TOR)RW79345387501801461103911072748.70%20142318.026814421570001691355.46%11900011.2202000276
6Anders BjorkMarlies (TOR)LW/RW753145766180541173078220210.10%13139918.6626834135000004155.56%10800021.0900000255
7Mitchell StephensMarlies (TOR)C793145762900312073121012259.94%25136817.321125110001216162.72%167900121.1101000225
8Rasmus SandinMarlies (TOR)D7910637351260737713146867.63%100168421.334913451380113153010.00%000000.8700000210
9Ryan SproulMarlies (TOR)D79194665556752471011575712612.10%118189824.045510591630001150400.00%000000.6800100272
10Urho VaakanainenMarlies (TOR)D75135164562208168158571108.23%91179023.875510541540003144040.00%000000.7100000223
11Remi ElieMarlies (TOR)LW792932612842023099309891989.39%18132516.78011120000204456.90%11600000.9211000332
12Clark BishopMarlies (TOR)C791144555556101868913739858.03%69133516.9000000000052160.34%34800000.8200002410
13Austin PoganskiMarlies (TOR)RW791933522512051114249761607.63%12130616.54000030003765158.33%15600000.8000000110
14Dylan BlujusMarlies (TOR)D7983745524952295410135587.92%99163220.67257331300001128100.00%000000.5500000001
15Marian StudenicMarlies (TOR)RW7912294154802940108286911.11%64133116.8600000000003055.56%1800000.6200000012
16Michael McLeodMaple LeafsC411222061191611.11%26516.3100000000000064.44%4500000.6100000000
17Andy WelinskiMaple LeafsD2011260522020.00%34422.470002400005000.00%000000.4500000000
18Libor HajekMaple LeafsD2000100703120.00%54522.5200011000013000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne1165382707108974045955198717643919114727149.75%7272259519.4043771204511453123321182482659.92%6946001150.96619107475048
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
1Stuart SkinnerMarlies (TOR)79522520.9092.8947116222724850010.81822790430
Stats d'équipe Total ou en Moyenne79522520.9092.8947116222724850010.81822790430


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
Anders BjorkMarlies (TOR)LW/RW221996-08-05No190 Lbs6 ft0NoNoNo2Pro & Farm1,066,667$0$0$No1,066,667$Lien / Lien NHL
Andy AndreoffMarlies (TOR)C/LW271991-05-17No203 Lbs6 ft1NoNoNo1Pro & Farm677,500$0$0$NoLien / Lien NHL
Austin PoganskiMarlies (TOR)RW221996-02-16No198 Lbs6 ft1NoNoNo2Pro & Farm762,500$0$0$No762,500$Lien / Lien NHL
Beck MalenstynMarlies (TOR)LW201998-02-04No198 Lbs6 ft2NoNoNo3Pro & Farm773,333$0$0$No773,333$773,333$Lien / Lien NHL
Ben ThomsonMarlies (TOR)LW251993-01-16No205 Lbs6 ft3NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Blake SpeersMarlies (TOR)C211997-01-02No185 Lbs5 ft11NoNoNo2Pro & Farm935,833$0$0$No935,833$Lien / Lien NHL
Clark BishopMarlies (TOR)C221996-03-29No199 Lbs6 ft1NoNoNo1Pro & Farm713,333$0$0$NoLien / Lien NHL
Dylan BlujusMarlies (TOR)D241994-01-22No191 Lbs6 ft3NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Hudson ElynuikMarlies (TOR)C201997-10-12No194 Lbs6 ft5NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Mackenzie MacEachernMarlies (TOR)LW241994-03-09No190 Lbs6 ft2NoNoNo2Pro & Farm650,000$0$0$No750,000$Lien / Lien NHL
Marian StudenicMarlies (TOR)RW191998-10-28Yes164 Lbs6 ft1NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien / Lien NHL
Matheson IacopelliMarlies (TOR)LW241994-05-15No207 Lbs6 ft2NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Mitchell StephensMarlies (TOR)C211997-02-05No191 Lbs6 ft0NoNoNo2Pro & Farm919,166$0$0$No919,166$Lien / Lien NHL
Morgan GeekieMarlies (TOR)C201998-07-20No192 Lbs6 ft3NoNoNo3Pro & Farm800,000$0$0$No800,000$800,000$Lien / Lien NHL
Nathan BastianMarlies (TOR)RW201997-12-06No205 Lbs6 ft4NoNoNo3Pro & Farm905,000$0$0$No905,000$905,000$Lien / Lien NHL
Rasmus SandinMarlies (TOR)D182000-03-07Yes184 Lbs6 ft0NoNoNo4Pro & Farm925,000$0$0$No894,167$894,167$894,167$Lien / Lien NHL
Remi ElieMarlies (TOR)LW231995-04-16No215 Lbs6 ft1NoNoNo1Pro & Farm735,000$0$0$NoLien / Lien NHL
Ryan SproulMarlies (TOR)D251993-01-13No205 Lbs6 ft4NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Stuart SkinnerMarlies (TOR)G191998-11-01No206 Lbs6 ft4NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien / Lien NHL
Tanner KaspickMarlies (TOR)C201998-01-28No200 Lbs6 ft0NoNoNo3Pro & Farm822,222$0$0$No822,222$822,222$Lien / Lien NHL
Tyler VeselMarlies (TOR)C241994-04-14No182 Lbs5 ft1NoNoNo1Pro & Farm850,000$0$0$NoLien / Lien NHL
Urho VaakanainenMarlies (TOR)D191999-01-01Yes185 Lbs6 ft1NoNoNo4Pro & Farm1,333,333$0$0$No1,302,500$1,302,500$1,302,500$Lien / Lien NHL
Vili SaarijarviMarlies (TOR)D211997-05-15No182 Lbs5 ft1NoNoNo2Pro & Farm930,000$0$0$No930,000$Lien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2321.74194 Lbs6 ft12.04833,647$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Andy AndreoffNathan Bastian30122
2Mackenzie MacEachernMorgan GeekieAnders Bjork30122
3Remi ElieMitchell StephensAustin Poganski25122
4Clark BishopMarian Studenic15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulUrho Vaakanainen30122
2Rasmus SandinDylan Blujus30122
3Clark BishopMarian Studenic25122
4Ryan SproulUrho Vaakanainen15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Andy AndreoffNathan Bastian60122
2Mackenzie MacEachernMorgan GeekieAnders Bjork40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulUrho Vaakanainen60122
2Rasmus SandinDylan Blujus40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Andy Andreoff60122
2Mackenzie MacEachernNathan Bastian40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulUrho Vaakanainen60122
2Rasmus SandinDylan Blujus40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Ryan SproulUrho Vaakanainen60122
2Andy Andreoff40122Rasmus SandinDylan Blujus40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Andy Andreoff60122
2Mackenzie MacEachernNathan Bastian40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan SproulUrho Vaakanainen60122
2Rasmus SandinDylan Blujus40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Andy AndreoffNathan BastianRyan SproulUrho Vaakanainen
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Andy AndreoffNathan BastianRyan SproulUrho Vaakanainen
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mitchell Stephens, Remi Elie, Austin PoganskiMitchell Stephens, Remi ElieAustin Poganski
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Rasmus Sandin, Dylan Blujus, Ryan SproulRasmus SandinDylan Blujus, Ryan Sproul
Tirs de Pénalité
, Andy Andreoff, Mackenzie MacEachern, Nathan Bastian, Morgan Geekie
Gardien
#1 : Stuart Skinner, #2 :


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
1Admirals220000001156110000004221100000073441.000112132001771208471261295127813244567186622150.00%3233.33%01991325861.11%1421260754.51%809134660.10%219816321625495950504
2Americans412000101416-22100001085320200000611-540.50014253900177120847132129512781324451313730897228.57%12375.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
3Barracuda2020000057-21010000023-11010000034-100.0005813001771208478712951278132445672384610220.00%4250.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
4Bears220000002061411000000111101100000095441.00020355500177120847142129512781324454796434375.00%3166.67%01991325861.11%1421260754.51%809134660.10%219816321625495950504
5Bruins4210000111110211000006602100000155050.6251121320017712084714712951278132445117291810215320.00%9188.89%01991325861.11%1421260754.51%809134660.10%219816321625495950504
6Checkers310010101495200010108621100000063361.0001423370017712084715112951278132445103322183600.00%8362.50%01991325861.11%1421260754.51%809134660.10%219816321625495950504
7Comets22000000176111100000010461100000072541.0001731480017712084715812951278132445421163922100.00%30100.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
8Condors220000001921711000000716110000001211141.000193655001771208471861295127813244544124552150.00%20100.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
9Crunch413000001114-32110000054120200000610-420.25011223301177120847124129512781324451655924871119.09%11554.55%01991325861.11%1421260754.51%809134660.10%219816321625495950504
10Devils33000000316252200000019514110000001211161.0003158890017712084727512951278132445721939825120.00%50100.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
11Eagles220000001064110000005321100000053241.0001020300017712084765129512781324458327144011100.00%7271.43%01991325861.11%1421260754.51%809134660.10%219816321625495950504
12Griffins31200000913-41010000024-22110000079-220.3339172600177120847144129512781324451033321949111.11%7271.43%01991325861.11%1421260754.51%809134660.10%219816321625495950504
13Gulls22000000752110000004311100000032141.0007101700177120847591295127813244576246482150.00%30100.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
14Heat22000000173141100000011291100000061541.000173451001771208471891295127813244534144444250.00%20100.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
15IceHogs210000014401000000123-11100000021130.7504711001771208477612951278132445651217464250.00%50100.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
16Monsters31200000550211000005411010000001-120.33359140017712084710512951278132445892518856116.67%9277.78%01991325861.11%1421260754.51%809134660.10%219816321625495950504
17Moose2200000021417110000001111011000000103741.000214061001771208471451295127813244555164375480.00%20100.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
18Penguins3200001026161011000000844210000101812661.00026487400177120847200129512781324451241614866233.33%7357.14%01991325861.11%1421260754.51%809134660.10%219816321625495950504
19Phantoms32100000963110000002022110000076140.667918270117712084711912951278132445100272077700.00%90100.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
20Rampage2110000078-11010000036-31100000042220.50071219001771208477012951278132445651014455120.00%6183.33%11991325861.11%1421260754.51%809134660.10%219816321625495950504
21Reign2020000028-61010000014-31010000014-300.000246001771208475912951278132445562119507114.29%7271.43%01991325861.11%1421260754.51%809134660.10%219816321625495950504
22Roadrunners21000010835110000006241000001021141.00081321001771208476012951278132445812318554125.00%8187.50%01991325861.11%1421260754.51%809134660.10%219816321625495950504
23Rocket3300000015871100000032122000000126661.00015254000177120847123129512781324451123412587228.57%6183.33%01991325861.11%1421260754.51%809134660.10%219816321625495950504
24Senators44000000368282200000019415220000001741381.0003666102001771208473061295127813244511932331264250.00%14192.86%01991325861.11%1421260754.51%809134660.10%219816321625495950504
25Sound Tigers31200000810-2211000006601010000024-220.333815230017712084711312951278132445782019649111.11%4325.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
26Stars220000001789110000008261100000096341.000173047001771208471491295127813244570171060300.00%5180.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
27Thunderbirds41300000131122020000047-32110000094520.2501324370017712084718912951278132445127381811610220.00%8275.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
Total79472501042386234152392411010211891038640231400021197131661060.671386706109212177120847392012951278132445252572745919821824323.63%1854078.38%11991325861.11%1421260754.51%809134660.10%219816321625495950504
29Wild21100000660110000004311010000023-120.5006121800177120847711295127813244572231243900.00%60100.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
30Wolf Pack31200000713-61100000032120200000411-720.3337121900177120847951295127813244510238107410220.00%4175.00%01991325861.11%1421260754.51%809134660.10%219816321625495950504
31Wolves2110000067-11010000024-21100000043120.50061016101771208475512951278132445592814466116.67%6183.33%01991325861.11%1421260754.51%809134660.10%219816321625495950504
_Since Last GM Reset79472501042386234152392411010211891038640231400021197131661060.671386706109212177120847392012951278132445252572745919821824323.63%1854078.38%11991325861.11%1421260754.51%809134660.10%219816321625495950504
_Vs Conference45261401031232140922214501020112565623129000111208436610.67823242365502177120847227412951278132445143940127011261032322.33%1032476.70%01991325861.11%1421260754.51%809134660.10%219816321625495950504
_Vs Division26145000101098128128100010473215146400000624913300.57710920030901177120847116512951278132445874262156672631320.63%671577.61%01991325861.11%1421260754.51%809134660.10%219816321625495950504

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
79106W2386706109239202525727459198212
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7947251042386234
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3924111021189103
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4023140021197131
Derniers 10 Matchs
WLOTWOTL SOWSOL
630001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1824323.63%1854078.38%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
12951278132445177120847
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
1991325861.11%1421260754.51%809134660.10%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
219816321625495950504


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 - 2019-10-021Senators2Marlies8WSommaire du Match
3 - 2019-10-0416Marlies0Monsters1LSommaire du Match
4 - 2019-10-0519Rocket2Marlies3WSommaire du Match
6 - 2019-10-0734Rampage6Marlies3LSommaire du Match
9 - 2019-10-1047Crunch4Marlies1LSommaire du Match
11 - 2019-10-1267Marlies2Griffins6LSommaire du Match
14 - 2019-10-1585Wild3Marlies4WSommaire du Match
15 - 2019-10-1693Marlies9Bears5WSommaire du Match
18 - 2019-10-19116Bruins3Marlies2LSommaire du Match
20 - 2019-10-21129Monsters2Marlies1LSommaire du Match
21 - 2019-10-22133Marlies4Bruins3WSommaire du Match
24 - 2019-10-25156Barracuda3Marlies2LSommaire du Match
25 - 2019-10-26163Marlies7Rocket3WSommaire du Match
28 - 2019-10-29180Bears1Marlies11WSommaire du Match
32 - 2019-11-02210Marlies1Phantoms2LSommaire du Match
35 - 2019-11-05228Reign4Marlies1LSommaire du Match
37 - 2019-11-07237Wolves4Marlies2LSommaire du Match
39 - 2019-11-09254Phantoms0Marlies2WSommaire du Match
40 - 2019-11-10267Marlies2IceHogs1WSommaire du Match
43 - 2019-11-13282Marlies2Sound Tigers4LSommaire du Match
45 - 2019-11-15294Bruins3Marlies4WSommaire du Match
46 - 2019-11-16308Marlies9Penguins4WSommaire du Match
49 - 2019-11-19329Marlies4Wolves3WSommaire du Match
51 - 2019-11-21343Marlies2Roadrunners1WXXSommaire du Match
53 - 2019-11-23351Marlies5Eagles3WSommaire du Match
57 - 2019-11-27379Marlies5Griffins3WSommaire du Match
59 - 2019-11-29396Marlies3Americans6LSommaire du Match
60 - 2019-11-30406Americans3Marlies5WSommaire du Match
63 - 2019-12-03428Marlies6Phantoms4WSommaire du Match
64 - 2019-12-04434Eagles3Marlies5WSommaire du Match
67 - 2019-12-07454Marlies4Rampage2WSommaire du Match
70 - 2019-12-10481Marlies7Comets2WSommaire du Match
72 - 2019-12-12494Marlies6Heat1WSommaire du Match
74 - 2019-12-14506Marlies12Condors1WSommaire du Match
77 - 2019-12-17525Americans2Marlies3WXXSommaire du Match
80 - 2019-12-20550Marlies2Wolf Pack4LSommaire du Match
81 - 2019-12-21557Griffins4Marlies2LSommaire du Match
83 - 2019-12-23569Checkers3Marlies4WXSommaire du Match
87 - 2019-12-27583Marlies12Devils1WSommaire du Match
88 - 2019-12-28594Wolf Pack2Marlies3WSommaire du Match
91 - 2019-12-31616Marlies2Wild3LSommaire du Match
93 - 2020-01-02633Marlies10Moose3WSommaire du Match
95 - 2020-01-04646Sound Tigers3Marlies5WSommaire du Match
97 - 2020-01-06659Condors1Marlies7WSommaire du Match
99 - 2020-01-08675Moose1Marlies11WSommaire du Match
103 - 2020-01-12707Marlies7Thunderbirds1WSommaire du Match
105 - 2020-01-14715Devils4Marlies11WSommaire du Match
107 - 2020-01-16728Heat2Marlies11WSommaire du Match
109 - 2020-01-18747IceHogs3Marlies2LXXSommaire du Match
118 - 2020-01-27770Marlies7Admirals3WSommaire du Match
120 - 2020-01-29776Marlies9Stars6WSommaire du Match
123 - 2020-02-01796Senators2Marlies11WSommaire du Match
125 - 2020-02-03809Thunderbirds3Marlies1LSommaire du Match
127 - 2020-02-05825Marlies2Wolf Pack7LSommaire du Match
129 - 2020-02-07839Gulls3Marlies4WSommaire du Match
130 - 2020-02-08846Marlies5Rocket3WSommaire du Match
133 - 2020-02-11867Roadrunners2Marlies6WSommaire du Match
135 - 2020-02-13881Stars2Marlies8WSommaire du Match
137 - 2020-02-15901Marlies10Senators2WSommaire du Match
138 - 2020-02-16913Marlies3Americans5LSommaire du Match
140 - 2020-02-18921Marlies9Penguins8WXXSommaire du Match
142 - 2020-02-20933Penguins4Marlies8WSommaire du Match
144 - 2020-02-22951Checkers3Marlies4WXXSommaire du Match
147 - 2020-02-25970Marlies4Crunch5LSommaire du Match
149 - 2020-02-27987Marlies2Thunderbirds3LSommaire du Match
151 - 2020-02-291003Comets4Marlies10WSommaire du Match
154 - 2020-03-031028Marlies3Barracuda4LSommaire du Match
156 - 2020-03-051041Marlies1Reign4LSommaire du Match
157 - 2020-03-061048Marlies3Gulls2WSommaire du Match
161 - 2020-03-101070Crunch0Marlies4WSommaire du Match
163 - 2020-03-121083Admirals2Marlies4WSommaire du Match
165 - 2020-03-141101Marlies1Bruins2LXXSommaire du Match
168 - 2020-03-171123Devils1Marlies8WSommaire du Match
170 - 2020-03-191137Sound Tigers3Marlies1LSommaire du Match
172 - 2020-03-211155Monsters2Marlies4WSommaire du Match
174 - 2020-03-231170Thunderbirds4Marlies3LSommaire du Match
176 - 2020-03-251185Marlies2Crunch5LSommaire du Match
177 - 2020-03-261195Marlies6Checkers3WSommaire du Match
179 - 2020-03-281209Marlies7Senators2WSommaire du Match
182 - 2020-03-311231Marlies-Bears-
184 - 2020-04-021242Griffins-Marlies-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
186 - 2020-04-041262Rocket-Marlies-



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
2 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,927,182$ 1,917,388$ 1,845,951$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,927,182$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 7 10,253$ 71,771$




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
Saison Régulière
282224905222247346-9941112303202125181-5641112602020122165-43442474406870289826982310774742774343354964104115822745620.44%4109676.59%21023241142.43%1069287337.21%539134740.01%1724115522126111016480
382116501122177424-247415320002291206-115416330110086218-132221773174940067575032458756890795274421129391116212843913.73%36710471.66%1834237535.12%1100325433.80%466133734.85%13709052640607933386
482126101035167428-261416290102388194-106416320001279234-1552416730947610605746922887537767306041601244106915224805812.08%41412270.53%1967244339.58%1094319134.28%527132739.71%13668732631654964400
582224901244243345-10241152001212134160-264172900032109185-764424338362611867874102929908981100871328091943519332084320.67%2015373.63%31371276549.58%1244270745.95%676140348.18%184713292151559970459
68234400023330427430412117000211611253641132300212143149-6683045018055614181796364011471213126636331497344120972184219.27%1724176.16%11554315049.33%1405321143.76%621134346.24%196514262007559979478
7823434022822932732041161801051147140741181601231146133136829352081321119867814348411551187110782312388350021572184018.35%2214778.73%11828318157.47%1639309852.91%737136953.83%2039145919255601014510
87947250104238623415239241101021189103864023140002119713166106386706109212177120847392012951278132445252572745919821824323.63%1854078.38%11991325861.11%1421260754.51%809134660.10%219816321625495950504
Total Saison Régulière5711823230119262018172324-5072859815007414129351109-174286841730451288821215-33337618173176499310127395614805721029678870677004355241777003485612894186432117.22%197050374.47%1095681958348.86%89722094142.84%4375947246.19%12512878415195404968293219
Séries
6404000001022-1220200000613-72020000049-5010152500532012634494302046326701417.14%13469.23%04213231.82%8117546.29%326648.48%7449117314721
7116500000393635320000023185633000001618-21239661050011141314361381501351342712570275361027.78%31777.42%023145051.33%20642248.82%9619349.74%2621812838414971
Total Séries1569000004958-9734000002931-2835000002027-71249811300016171515621721991781363118896345501122.00%441175.00%027358246.91%28759748.07%12825949.42%33623040111519793