HOLLYWOOD Oscar

GP: 4 | W: 2 | L: 1 | OTL: 1 | P: 5
GF: 14 | GA: 7 | PP%: 0.00% | PK%: 88.24%
DG: Dom Mailloux | Morale : 99 | Moyenne d'Équipe : 64
Prochain matchs #52 vs MILWAUKEE Admirals
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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
1Michael Mersch0X100.006953855983889058545759605875685799690
2Ryan Haggerty0X100.006151865774848756535558595773675899660
3Rhett Gardner0X100.006846896088717258665759625867645699660
4Emile Poirier0X100.006449835880797856535555595871667899650
5Ty Rattie0X100.006935766671776365606663606454517399650
6Jaret Anderson-Dolan0X100.005843896570767463706158595961627499650
7Anthony Richard0X100.005541906063798159535860575967645799640
8Hudson Elynuik (R)0X100.007051855588757753605254565365636499630
9Cole Bardreau0XX100.005743875967716957545658555773685499620
10Robin Kovacs (R)0X100.004635797665464953305047525354509599540
11Logan Stanley0X100.008463765599858656305453624563628399680
12Dillon Simpson0X100.006746835881889256305554574573675399670
13Rinat Valiev0X100.007252855886838156305553594569656399660
14William Borgen0X100.006451865983857558305756605367646199660
15Riley Stillman0X100.006448866077837259305857655063626499650
16Casey Fitzgerald (R)0X100.005444765859737256305553544865636199600
17Stepan Falkovsky (R)0X100.006742725093506153304036605350504499540
18Luc Snuggerud0X100.005242735066505756304538605550504499520
Rayé
MOYENNE D'ÉQUIPE100.00634683597775745744555459546461639963
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
1Jonas Johansson (R)100.00796361937877797877797869736499700
2Kaapo Kahkonen (R)100.00797068837877797877797867715999690
3Reto Berra100.00746982887577757575737156654799670
Rayé
MOYENNE D'ÉQUIPE100.0077677088777778777677766470579969
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Doug Weight74717474767670USA503400,000$


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
1Michael MerschHOLLYWOOD Oscar (SEA)LW41345208716296.25%210225.600001110000160058.33%4800000.7801000010
2Ryan HaggertyHOLLYWOOD Oscar (SEA)RW413450017156116.67%210225.580001110000160060.00%500000.7801000100
3Ty RattieHOLLYWOOD Oscar (SEA)RW41343408716596.25%07017.58000110000000050.00%600001.1400000000
4Anthony RichardHOLLYWOOD Oscar (SEA)C412320036821312.50%05814.6900000000000059.42%6900001.0200000010
5Jaret Anderson-DolanHOLLYWOOD Oscar (SEA)C421330026166512.50%18220.52000190003100067.86%8400000.7300000000
6Logan StanleyHOLLYWOOD Oscar (SEA)D412341008381112.50%38220.65000510000010100.00%000000.7300000000
7Rhett GardnerHOLLYWOOD Oscar (SEA)C4123440011103810.00%16917.37000111000081070.79%8900000.8601000100
8Cole BardreauHOLLYWOOD Oscar (SEA)C/RW411220045106410.00%05914.9500000000030033.33%300000.6700000001
9Dillon SimpsonHOLLYWOOD Oscar (SEA)D4022420419340.00%38521.49000510000014000.00%000000.4700000000
10Robin KovacsHOLLYWOOD Oscar (SEA)LW41122004161416.67%05513.990000000000000.00%200000.7100000000
11Stepan FalkovskyHOLLYWOOD Oscar (SEA)D411222070113100.00%2379.470000000001000.00%000001.0600000000
12Riley StillmanHOLLYWOOD Oscar (SEA)D41122205241325.00%34310.970000000000000.00%000000.9100000001
13Hudson ElynuikHOLLYWOOD Oscar (SEA)C4022180231130.00%1246.2200000000000069.70%3300001.6100000000
14Rinat ValievHOLLYWOOD Oscar (SEA)D4011220444140.00%37318.40000211000012000.00%000000.2700000000
15Emile PoirierHOLLYWOOD Oscar (SEA)LW41013005313197.69%37017.65000510000000040.00%500000.2800000000
16Casey FitzgeraldHOLLYWOOD Oscar (SEA)D41012003140225.00%35012.600000000006000.00%000000.4000000000
17Luc SnuggerudHOLLYWOOD Oscar (SEA)D4000200322010.00%3369.190000000000000.00%000000.0000000000
18William BorgenHOLLYWOOD Oscar (SEA)D4000200428100.00%17318.45000411000013000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne7214253950360757115141939.27%31118116.410002610900031152064.24%34400000.6603000222
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
1Jonas JohanssonHOLLYWOOD Oscar (SEA)42110.9501.482440161200000.667340101
Stats d'équipe Total ou en Moyenne42110.9501.482440161200000.667340101


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 Salaire RestantSalaire MoyenSalaire Moyen RestantCap 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
Anthony RichardHOLLYWOOD Oscar (SEA)C231996-12-20No74 Kg178 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$Lien
Casey FitzgeraldHOLLYWOOD Oscar (SEA)D231997-02-25Yes85 Kg155 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$
Cole BardreauHOLLYWOOD Oscar (SEA)C/RW271993-07-22No84 Kg178 CMNoNoNo2Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$Lien
Dillon SimpsonHOLLYWOOD Oscar (SEA)D271993-02-10No93 Kg188 CMNoNoNo2Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$Lien
Emile PoirierHOLLYWOOD Oscar (SEA)LW251994-12-14No89 Kg188 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$Lien
Hudson ElynuikHOLLYWOOD Oscar (SEA)C221997-10-12Yes88 Kg196 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$
Jaret Anderson-DolanHOLLYWOOD Oscar (SEA)C201999-09-12No85 Kg180 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Jonas JohanssonHOLLYWOOD Oscar (SEA)G241995-09-19Yes100 Kg196 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$
Kaapo KahkonenHOLLYWOOD Oscar (SEA)G241996-08-16Yes98 Kg188 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$
Logan StanleyHOLLYWOOD Oscar (SEA)D221998-05-26No104 Kg201 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Luc SnuggerudHOLLYWOOD Oscar (SEA)D241995-09-18No84 Kg183 CMNoNoNo2Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$Lien
Michael MerschHOLLYWOOD Oscar (SEA)LW271992-10-02No97 Kg188 CMNoNoNo2Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$Lien
Reto BerraHOLLYWOOD Oscar (SEA)G331987-01-03No99 Kg193 CMNoNoNo4Pro & Farm1,000,000$954,128$1,000,000$954,128$0$0$No1,000,000$1,000,000$1,000,000$Lien
Rhett GardnerHOLLYWOOD Oscar (SEA)C241996-02-28No102 Kg191 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Riley StillmanHOLLYWOOD Oscar (SEA)D221998-03-09No89 Kg185 CMNoNoNo1Pro & Farm750,000$715,596$325,000$310,091$0$0$NoLien
Rinat ValievHOLLYWOOD Oscar (SEA)D251995-05-11No98 Kg191 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$Lien
Robin KovacsHOLLYWOOD Oscar (SEA)LW231996-11-16Yes80 Kg183 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$
Ryan HaggertyHOLLYWOOD Oscar (SEA)RW271993-03-04No91 Kg183 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Stepan FalkovskyHOLLYWOOD Oscar (SEA)D231996-12-18Yes102 Kg201 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Ty RattieHOLLYWOOD Oscar (SEA)RW271993-02-05No83 Kg183 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$Lien
William BorgenHOLLYWOOD Oscar (SEA)D231996-12-19No90 Kg191 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2124.5291 Kg185 CM2.62761,905$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael MerschRhett GardnerRyan Haggerty31122
2Emile PoirierJaret Anderson-DolanTy Rattie26122
3Robin KovacsAnthony RichardCole Bardreau23122
4Michael MerschHudson ElynuikRyan Haggerty20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Logan StanleyDillon Simpson31122
2Rinat ValievWilliam Borgen26122
3Riley StillmanCasey Fitzgerald23122
4Stepan FalkovskyLuc Snuggerud20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael MerschRhett GardnerRyan Haggerty55122
2Emile PoirierJaret Anderson-DolanTy Rattie45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Logan StanleyDillon Simpson55122
2Rinat ValievWilliam Borgen45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Michael MerschRyan Haggerty55122
2Rhett GardnerJaret Anderson-Dolan45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Logan StanleyDillon Simpson55122
2Rinat ValievWilliam Borgen45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Michael Mersch55122Logan StanleyDillon Simpson55122
2Ryan Haggerty45122Rinat ValievWilliam Borgen45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Michael MerschRyan Haggerty55122
2Rhett GardnerJaret Anderson-Dolan45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Logan StanleyDillon Simpson55122
2Rinat ValievWilliam Borgen45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Michael MerschRhett GardnerRyan HaggertyLogan StanleyDillon Simpson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Michael MerschRhett GardnerRyan HaggertyLogan StanleyDillon Simpson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Anthony Richard, Hudson Elynuik, Cole BardreauAnthony Richard, Hudson ElynuikCole Bardreau
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Riley Stillman, Casey Fitzgerald, Stepan FalkovskyRiley StillmanCasey Fitzgerald, Stepan Falkovsky
Tirs de Pénalité
Michael Mersch, Ryan Haggerty, Rhett Gardner, Jaret Anderson-Dolan, Emile Poirier
Gardien
#1 : Jonas Johansson, #2 : Kaapo Kahkonen, #3 : Reto Berra
Lignes d'Attaque Perso. en Prol.
Michael Mersch, Ryan Haggerty, Rhett Gardner, Jaret Anderson-Dolan, Emile Poirier, Ty Rattie, Ty Rattie, Anthony Richard, Hudson Elynuik, Cole Bardreau, Robin Kovacs
Lignes de Défense Perso. en Prol.
Logan Stanley, Dillon Simpson, Rinat Valiev, William Borgen, Riley Stillman


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
1IOWA Wild1010000012-11010000012-10000000000000.0001230047303241594863713427200.00%20100.00%08713663.97%8813664.71%466373.02%1087884285227
2SAN DIEGO Gulls11000000927000000000001100000092721.000916250047305741594861861217200.00%60100.00%08713663.97%8813664.71%466373.02%1087884285227
3Syracruse Crunch1000000101-1000000000001000000101-110.500000004730264159486389817400.00%30100.00%08713663.97%8813664.71%466373.02%1087884285227
4TUSCON Roadrunners11000000422000000000001100000042221.00047110047303641594862731214300.00%6266.67%08713663.97%8813664.71%466373.02%1087884285227
Total4210000114771010000012-132000001135850.62514253900473015141594861203136751100.00%17288.24%08713663.97%8813664.71%466373.02%1087884285227
_Since Last GM Reset4210000114771010000012-132000001135850.62514253900473015141594861203136751100.00%17288.24%08713663.97%8813664.71%466373.02%1087884285227
_Vs Conference2010000113-21010000012-11000000101-110.25012300473058415948675221244600.00%50100.00%08713663.97%8813664.71%466373.02%1087884285227
_Vs Division1010000101-1001000000001000000101-110.500000004730264159486389817400.00%30100.00%08713663.97%8813664.71%466373.02%1087884285227

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
45W114253915112031367500
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4210001147
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
101000012
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3200001135
Derniers 10 Matchs
WLOTWOTL SOWSOL
210001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1100.00%17288.24%0
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
41594864730
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
8713663.97%8813664.71%466373.02%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1087884285227


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 - 2020-08-026HOLLYWOOD Oscar4TUSCON Roadrunners2WSommaire du Match
2 - 2020-08-0317HOLLYWOOD Oscar0Syracruse Crunch1LXXSommaire du Match
3 - 2020-08-0425IOWA Wild2HOLLYWOOD Oscar1LSommaire du Match
4 - 2020-08-0539HOLLYWOOD Oscar9SAN DIEGO Gulls2WR3Sommaire du Match
6 - 2020-08-0752MILWAUKEE Admirals-HOLLYWOOD Oscar-
7 - 2020-08-0872CHICAGO Wolves-HOLLYWOOD Oscar-R3
9 - 2020-08-1086HOLLYWOOD Oscar-BROOKLYN Wolfpack-
10 - 2020-08-1192BRIDGEPORT Sound Tigers-HOLLYWOOD Oscar-R3
11 - 2020-08-12109LAVAL Rockets-HOLLYWOOD Oscar-
12 - 2020-08-13119HOLLYWOOD Oscar-MONT-LAURIER Sommet-R3
13 - 2020-08-14127HOLLYWOOD Oscar-Manitoba Moose-
15 - 2020-08-16146BELLEVILLE Senators-HOLLYWOOD Oscar-R3
17 - 2020-08-18161HOLLYWOOD Oscar-PROVIDENCE Bruins-
18 - 2020-08-19168IOWA Wild-HOLLYWOOD Oscar-R3
19 - 2020-08-20188HOLLYWOOD Oscar-COLORADO Eagles-
20 - 2020-08-21197HOLLYWOOD Oscar-STOCKTON Flames-R3
21 - 2020-08-22205Binghampton Devils-HOLLYWOOD Oscar-
23 - 2020-08-24222Syracruse Crunch-HOLLYWOOD Oscar-R3
24 - 2020-08-25234HOLLYWOOD Oscar-LEHIGH VALLEY Phantoms-
25 - 2020-08-26245Binghampton Devils-HOLLYWOOD Oscar-R3
26 - 2020-08-27263HOLLYWOOD Oscar-SAN DIEGO Gulls-
27 - 2020-08-28274HOLLYWOOD Oscar-MONT-LAURIER Sommet-R3
29 - 2020-08-30281PV Sharapovas-HOLLYWOOD Oscar-
31 - 2020-09-01298HOLLYWOOD Oscar-COLORADO Eagles-R3
32 - 2020-09-02308BRIDGEPORT Sound Tigers-HOLLYWOOD Oscar-
33 - 2020-09-03326BELLEVILLE Senators-HOLLYWOOD Oscar-R3
35 - 2020-09-05340HOLLYWOOD Oscar-VICTORIAVILLE Tigres-
36 - 2020-09-06352LAVAL Rockets-HOLLYWOOD Oscar-R3
37 - 2020-09-07358HOLLYWOOD Oscar-HERSEY Bears-
38 - 2020-09-08377ROCKFORD IceHogs-HOLLYWOOD Oscar-R3
40 - 2020-09-10391HOLLYWOOD Oscar-MILWAUKEE Admirals-
41 - 2020-09-11404HOLLYWOOD Oscar-Quebec Nordiques-R3
42 - 2020-09-12410HOLLYWOOD Oscar-BRIDGEPORT Sound Tigers-
43 - 2020-09-13416TUSCON Roadrunners-HOLLYWOOD Oscar-R3
45 - 2020-09-15436SAN DIEGO Gulls-HOLLYWOOD Oscar-
47 - 2020-09-17454HOLLYWOOD Oscar-LAVAL Rockets-R3
48 - 2020-09-18460Manitoba Moose-HOLLYWOOD Oscar-
49 - 2020-09-19474HOLLYWOOD Oscar-Marlies de Toronto-R3
50 - 2020-09-20490COLORADO Eagles-HOLLYWOOD Oscar-
52 - 2020-09-22504HOLLYWOOD Oscar-Syracruse Crunch-R3
53 - 2020-09-23513STOCKTON Flames-HOLLYWOOD Oscar-
54 - 2020-09-24528HOLLYWOOD Oscar-BROOKLYN Wolfpack-R3
56 - 2020-09-26536HOLLYWOOD Oscar-Manitoba Moose-
57 - 2020-09-27548HERSEY Bears-HOLLYWOOD Oscar-R3
58 - 2020-09-28566MILWAUKEE Admirals-HOLLYWOOD Oscar-
59 - 2020-09-29575HOLLYWOOD Oscar-IOWA Wild-R3
61 - 2020-10-01594Quebec Nordiques-HOLLYWOOD Oscar-
62 - 2020-10-02606HOLLYWOOD Oscar-CHICAGO Wolves-R3
63 - 2020-10-03618IOWA Wild-HOLLYWOOD Oscar-
64 - 2020-10-04633HOLLYWOOD Oscar-Syracruse Crunch-R3
65 - 2020-10-05636HOLLYWOOD Oscar-UTICA Comets-
66 - 2020-10-06647CHICAGO Wolves-HOLLYWOOD Oscar-R3
68 - 2020-10-08668HOLLYWOOD Oscar-UTICA Comets-
69 - 2020-10-09674BROOKLYN Wolfpack-HOLLYWOOD Oscar-R3
70 - 2020-10-10689HOLLYWOOD Oscar-BELLEVILLE Senators-
71 - 2020-10-11699LEHIGH VALLEY Phantoms-HOLLYWOOD Oscar-R3
72 - 2020-10-12716MILWAUKEE Admirals-HOLLYWOOD Oscar-
73 - 2020-10-13727HOLLYWOOD Oscar-Binghampton Devils-R3
75 - 2020-10-15740HOLLYWOOD Oscar-STOCKTON Flames-
76 - 2020-10-16751MONT-LAURIER Sommet-HOLLYWOOD Oscar-R3
78 - 2020-10-18772UTICA Comets-HOLLYWOOD Oscar-
79 - 2020-10-19781HOLLYWOOD Oscar-WILKIES-BARRIE Penguins-R3
80 - 2020-10-20793HOLLYWOOD Oscar-Manitoba Moose-
81 - 2020-10-21802PROVIDENCE Bruins-HOLLYWOOD Oscar-R3
83 - 2020-10-23821HOLLYWOOD Oscar-TUSCON Roadrunners-
84 - 2020-10-24831HERSEY Bears-HOLLYWOOD Oscar-R3
86 - 2020-10-26848HOLLYWOOD Oscar-TUSCON Roadrunners-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
87 - 2020-10-27856Marlies de Toronto-HOLLYWOOD Oscar-R3
89 - 2020-10-29877Quebec Nordiques-HOLLYWOOD Oscar-
90 - 2020-10-30896WILKIES-BARRIE Penguins-HOLLYWOOD Oscar-R3
91 - 2020-10-31906HOLLYWOOD Oscar-PV Sharapovas-
93 - 2020-11-02923VICTORIAVILLE Tigres-HOLLYWOOD Oscar-R3
94 - 2020-11-03929HOLLYWOOD Oscar-ROCKFORD IceHogs-
95 - 2020-11-04939HOLLYWOOD Oscar-PROVIDENCE Bruins-R3
96 - 2020-11-05955HOLLYWOOD Oscar-ROCKFORD IceHogs-
97 - 2020-11-06961LEHIGH VALLEY Phantoms-HOLLYWOOD Oscar-R3
100 - 2020-11-09985VICTORIAVILLE Tigres-HOLLYWOOD Oscar-
103 - 2020-11-121006WILKIES-BARRIE Penguins-HOLLYWOOD Oscar-R3
104 - 2020-11-131011HOLLYWOOD Oscar-PV Sharapovas-
107 - 2020-11-161032Marlies de Toronto-HOLLYWOOD Oscar-R3



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
39 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
77,065$ 1,600,000$ 1,557,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 73,395$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 104 14,679$ 1,526,616$




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
338247601100116874-758412380100064428-364412380010052446-39481162233391046353411372432427512171712062248066211.61%120100.00%034493536.79%435238818.22%306161218.98%6053793589491726218
344210000114771010000012-1320000011358514253900473015141594861203136751100.00%17288.24%08713663.97%8813664.71%466373.02%1087884285227
Total Saison Régulière8667701101130881-751422390100065430-365444380010165451-386131302483781050423711523473486560772912093608817311.37%29293.10%0431107140.24%523252420.72%352167521.01%7144583674519778245