HOLLYWOOD Oscar

GP: 28 | W: 1 | L: 26 | OTL: 1 | P: 3
GF: 64 | GA: 286 | PP%: 4.17% | PK%: 100.00%
DG: Dom Mailloux | Morale : 92 | Moyenne d'Équipe : 59
Prochain matchs #372 vs LAVAL Rockets
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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
1Melker Karlsson0XX100.006535726570789264706266716563543688690
2Martin Hanzal0X100.007435765798805357756060685977585199660
3Ty Rattie0X100.006935766671776365606663606454517391650
4Jordan Nolan0XX100.006335596987535769676363526465553999630
5Michael Mersch0X100.005889647083505070506464506451505199610
6Ryan Haggerty (R)0X100.005189637074505070506464526450504299600
7Jaret Anderson-Dolan (R)0X100.006235775570785255666060605850507699600
8Anthony Richard0X100.005035677063505070706464506450506199590
9Rhett Gardner (R)0X100.005989726385485063705959505950504499580
10Emile Poirier0X100.005489696280505062505454505450507999560
11Robin Kovacs (R)0X100.004635797665464953305047525354509599540
12Logan Stanley (R)0X100.007089576399505063304843505350504494570
13Rinat Valiev0X100.006189626586465065304843545350506599560
14Stepan Falkovsky (R)0X100.006742725093506153304036605350504499540
15Riley Stillman (R)0X100.005335616377465063314843525350506099540
16William Borgen (R)0X100.005835625883475258304742535250506299540
Rayé
MOYENNE D'ÉQUIPE100.00605668648056556351565455585451589859
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
1Reto Berra100.00746982887577757575737156654799670
2Yann Danis100.0048536861625455585959558476595550
Rayé
MOYENNE D'ÉQUIPE100.0061617575696665676766637071269761
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Pascal Vincent68686868727276CAN481330,000$


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
1Ty RattieHOLLYWOOD Oscar (SEA)RW2835237120522999326235.35%8832311.5400000000001058.82%1700052.2900000022
2Melker KarlssonHOLLYWOOD Oscar (SEA)C/RW55712122010834112314.71%110521.180224110000170065.62%3200012.2701000002
Stats d'équipe Total ou en Moyenne334094913406237133438530.08%8942913.000224110000171063.27%4900062.2801000024
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
Stats d'équipe Total ou en Moyenne0.0000.0000.000


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'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Anthony RichardHOLLYWOOD Oscar (SEA)C221996-12-20No74 Kg178 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$NoLien
Emile PoirierHOLLYWOOD Oscar (SEA)LW241994-12-14No89 Kg188 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$NoLien
Jaret Anderson-DolanHOLLYWOOD Oscar (SEA)C191999-09-12Yes85 Kg180 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Jordan NolanHOLLYWOOD Oscar (SEA)C/RW301989-06-23No100 Kg191 CMNoNoNo6Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Logan StanleyHOLLYWOOD Oscar (SEA)D211998-05-26Yes104 Kg201 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Martin HanzalHOLLYWOOD Oscar (SEA)C321987-02-20No105 Kg198 CMNoNoNo6Sans RestrictionPro & Farm2,500,000$0$0$NoLien
Melker KarlssonHOLLYWOOD Oscar (SEA)C/RW291990-07-18No82 Kg183 CMNoNoNo4Sans RestrictionPro & Farm1,600,000$0$0$NoLien
Michael MerschHOLLYWOOD Oscar (SEA)LW261992-10-02No97 Kg188 CMNoNoNo4Avec RestrictionPro & Farm750,000$0$0$NoLien
Reto BerraHOLLYWOOD Oscar (SEA)G321987-01-03No99 Kg193 CMNoNoNo6Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Rhett GardnerHOLLYWOOD Oscar (SEA)C231996-02-28Yes95 Kg191 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Riley StillmanHOLLYWOOD Oscar (SEA)D211998-03-09Yes89 Kg185 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Rinat ValievHOLLYWOOD Oscar (SEA)D241995-05-11No98 Kg191 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$NoLien
Robin KovacsHOLLYWOOD Oscar (SEA)LW221996-11-16Yes80 Kg183 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$No
Ryan HaggertyHOLLYWOOD Oscar (SEA)RW261993-03-04Yes91 Kg183 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Stepan FalkovskyHOLLYWOOD Oscar (SEA)D221996-12-18Yes102 Kg201 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Ty RattieHOLLYWOOD Oscar (SEA)RW261993-02-05No83 Kg183 CMNoNoNo6Avec RestrictionPro & Farm750,000$0$0$NoLien
William BorgenHOLLYWOOD Oscar (SEA)D221996-12-19Yes89 Kg191 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Yann DanisHOLLYWOOD Oscar (SEA)G381981-06-21No82 Kg180 CMNoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1825.5091 Kg188 CM4.33908,333$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
131122
226122
323122
4Ty Rattie20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
131122
226122
323122
420122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
155122
245122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
245122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
155122
245122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
245122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
15512255122
24512245122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
155122
245122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
245122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , ,
Gardien
#1 : , #2 :
Lignes d'Attaque Perso. en Prol.
, , , , , , , , , Ty Rattie,
Lignes de Défense Perso. en Prol.
, , , ,


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
1BELLEVILLE Senators20200000427-230000000000020200000427-2300.000481200242416047141192170620971232000.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
2BROOKLYN Wolfpack1010000035-2000000000001010000035-200.0003690024241602614119217067622014000.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
3CLEVELAND Monsters1000000156-1000000000001000000156-110.5005914002424160441411921706802609100.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
4CORNWALL Aces1010000068-2000000000001010000068-200.000611170024241606714119217064910017100.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
5HERSEY Bears10100000012-120000000000010100000012-1200.00000000242416031411921706992801000.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
6IOWA Wild20200000824-1620200000824-160000000000000.0008162400242416035141192170622371027200.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
7MANITOBA Moose30300000226-2420200000218-161010000008-800.00023500242416022141192170628868213400.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
8MILWAUKEE Admirals20200000125-2410100000013-1310100000112-1100.00012300242416011141192170617859212500.00%10100.00%011135331.44%17184920.14%11257219.58%238149118517226187
9MONT-LAURIER Sommet30300000135-3410100000013-1320200000122-2100.00012300242416018141192170628778017300.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
10PROVIDENCE Bruins10100000012-1210100000012-120000000000000.000000002424160314119217061172804200.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
11PV Sharapovas20200000015-151010000006-61010000009-900.000000002424160514119217061684906300.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
12ROCKFORD IceHogs10100000011-1110100000011-110000000000000.000000002424160814119217067619013200.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
13SAN DIEGO Gulls10100000411-710100000411-70000000000000.0004812002424160521411921706593604711100.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
14STOCKTON Flames10100000111-1010100000111-100000000000000.00012300242416051411921706832105000.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
15SYRACUSE Crunch2110000013941010000045-11100000094520.5001323360024241609614119217066724224000.00%10100.00%011135331.44%17184920.14%11257219.58%238149118517226187
16TORONTO Marlies10100000112-110000000000010100000112-1100.000123002424160414119217061053308000.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
Total281260000164286-222140140000032149-117141120000132137-10530.054641191830024241605061411921706244771482702414.17%20100.00%011135331.44%17184920.14%11257219.58%238149118517226187
18VICTORIAVILLE Tigres20200000627-2110100000415-1110100000212-1000.000611170024241601214119217062095508000.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
19WILKIES-BARRIE Penguins10100000910-110100000910-10000000000000.000916250024241604814119217067416013000.00%000.00%011135331.44%17184920.14%11257219.58%238149118517226187
_Since Last GM Reset281260000164286-222140140000032149-117141120000132137-10530.054641191830024241605061411921706244771482702414.17%20100.00%011135331.44%17184920.14%11257219.58%238149118517226187
_Vs Conference201190000051204-153100100000028102-7410190000023102-7920.05051941450024241603591411921706176249661701300.00%10100.00%011135331.44%17184920.14%11257219.58%238149118517226187
_Vs Division9011000002483-5930700000423-19604000002060-4000.0002444680024241602221411921706715215491600.00%10100.00%011135331.44%17184920.14%11257219.58%238149118517226187

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
283L11641191835062447714827000
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
28126000164286
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
14014000032149
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
14112000132137
Derniers 10 Matchs
WLOTWOTL SOWSOL
0100000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2414.17%20100.00%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
14119217062424160
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
11135331.44%17184920.14%11257219.58%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
238149118517226187


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 - 2019-07-308MONT-LAURIER Sommet13HOLLYWOOD Oscar0LSommaire du Match
2 - 2019-07-3124HOLLYWOOD Oscar9SYRACUSE Crunch4WSommaire du Match
3 - 2019-08-0130VICTORIAVILLE Tigres15HOLLYWOOD Oscar4LSommaire du Match
4 - 2019-08-0247HOLLYWOOD Oscar0MONT-LAURIER Sommet10LSommaire du Match
6 - 2019-08-0456HOLLYWOOD Oscar2VICTORIAVILLE Tigres12LSommaire du Match
7 - 2019-08-0571MANITOBA Moose12HOLLYWOOD Oscar2LSommaire du Match
9 - 2019-08-0786HOLLYWOOD Oscar1MONT-LAURIER Sommet12LSommaire du Match
10 - 2019-08-08100WILKIES-BARRIE Penguins10HOLLYWOOD Oscar9LSommaire du Match
11 - 2019-08-09107IOWA Wild14HOLLYWOOD Oscar5LSommaire du Match
12 - 2019-08-10127HOLLYWOOD Oscar0PV Sharapovas9LSommaire du Match
14 - 2019-08-12133SYRACUSE Crunch5HOLLYWOOD Oscar4LSommaire du Match
16 - 2019-08-14158PV Sharapovas6HOLLYWOOD Oscar0LSommaire du Match
17 - 2019-08-15169HOLLYWOOD Oscar1BELLEVILLE Senators14LSommaire du Match
18 - 2019-08-16170HOLLYWOOD Oscar1TORONTO Marlies12LSommaire du Match
20 - 2019-08-18189STOCKTON Flames11HOLLYWOOD Oscar1LSommaire du Match
21 - 2019-08-19201HOLLYWOOD Oscar0MANITOBA Moose8LSommaire du Match
22 - 2019-08-20211HOLLYWOOD Oscar5CLEVELAND Monsters6LXXSommaire du Match
24 - 2019-08-22222IOWA Wild10HOLLYWOOD Oscar3LSommaire du Match
25 - 2019-08-23239MILWAUKEE Admirals13HOLLYWOOD Oscar0LSommaire du Match
26 - 2019-08-24257ROCKFORD IceHogs11HOLLYWOOD Oscar0LSommaire du Match
27 - 2019-08-25270HOLLYWOOD Oscar3BROOKLYN Wolfpack5LSommaire du Match
28 - 2019-08-26279HOLLYWOOD Oscar3BELLEVILLE Senators13LSommaire du Match
29 - 2019-08-27289HOLLYWOOD Oscar1MILWAUKEE Admirals12LSommaire du Match
30 - 2019-08-28302HOLLYWOOD Oscar6CORNWALL Aces8LSommaire du Match
31 - 2019-08-29313SAN DIEGO Gulls11HOLLYWOOD Oscar4LR3Sommaire du Match
32 - 2019-08-30333MANITOBA Moose6HOLLYWOOD Oscar0LSommaire du Match
34 - 2019-09-01343PROVIDENCE Bruins12HOLLYWOOD Oscar0LSommaire du Match
35 - 2019-09-02354HOLLYWOOD Oscar0HERSEY Bears12LSommaire du Match
36 - 2019-09-03372LAVAL Rockets-HOLLYWOOD Oscar-
38 - 2019-09-05387HOLLYWOOD Oscar-SYRACUSE Crunch-
39 - 2019-09-06399HOLLYWOOD Oscar-MANITOBA Moose-
40 - 2019-09-07406CLEVELAND Monsters-HOLLYWOOD Oscar-
42 - 2019-09-09423HOLLYWOOD Oscar-LAVAL Rockets-
43 - 2019-09-10433BROOKLYN Wolfpack-HOLLYWOOD Oscar-
45 - 2019-09-12445HOLLYWOOD Oscar-MONT-LAURIER Sommet-
46 - 2019-09-13458WILKIES-BARRIE Penguins-HOLLYWOOD Oscar-
47 - 2019-09-14472HOLLYWOOD Oscar-BRIDGEPORT Sound Tigers-
48 - 2019-09-15483BRIDGEPORT Sound Tigers-HOLLYWOOD Oscar-
49 - 2019-09-16501MONT-LAURIER Sommet-HOLLYWOOD Oscar-
50 - 2019-09-17512HOLLYWOOD Oscar-PROVIDENCE Bruins-
52 - 2019-09-19528VICTORIAVILLE Tigres-HOLLYWOOD Oscar-
53 - 2019-09-20543HOLLYWOOD Oscar-VICTORIAVILLE Tigres-
54 - 2019-09-21548HOLLYWOOD Oscar-TORONTO Marlies-
55 - 2019-09-22562HOLLYWOOD Oscar-CORNWALL Aces-
57 - 2019-09-24570HERSEY Bears-HOLLYWOOD Oscar-
59 - 2019-09-26592STOCKTON Flames-HOLLYWOOD Oscar-
61 - 2019-09-28603UTICA Comets-HOLLYWOOD Oscar-
64 - 2019-10-01621HOLLYWOOD Oscar-STOCKTON Flames-
65 - 2019-10-02636TORONTO Marlies-HOLLYWOOD Oscar-
67 - 2019-10-04651HOLLYWOOD Oscar-PV Sharapovas-
68 - 2019-10-05659TUSCON Roadrunners-HOLLYWOOD Oscar-
70 - 2019-10-07675HOLLYWOOD Oscar-COLORADO Eagles-
71 - 2019-10-08688CORNWALL Aces-HOLLYWOOD Oscar-
73 - 2019-10-10705MONT-LAURIER Sommet-HOLLYWOOD Oscar-
74 - 2019-10-11718HOLLYWOOD Oscar-WILKIES-BARRIE Penguins-
75 - 2019-10-12728HOLLYWOOD Oscar-TUSCON Roadrunners-
76 - 2019-10-13739COLORADO Eagles-HOLLYWOOD Oscar-
77 - 2019-10-14750HOLLYWOOD Oscar-UTICA Comets-
78 - 2019-10-15759HOLLYWOOD Oscar-LEHIGH VALLEY Phantoms-
79 - 2019-10-16772CORNWALL Aces-HOLLYWOOD Oscar-
81 - 2019-10-18790SYRACUSE Crunch-HOLLYWOOD Oscar-
83 - 2019-10-20802HOLLYWOOD Oscar-WILKIES-BARRIE Penguins-
84 - 2019-10-21815PV Sharapovas-HOLLYWOOD Oscar-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
85 - 2019-10-22833HOLLYWOOD Oscar-CHICAGO Wolves-
86 - 2019-10-23844COLORADO Eagles-HOLLYWOOD Oscar-
88 - 2019-10-25860HOLLYWOOD Oscar-SAN DIEGO Gulls-
90 - 2019-10-27871LEHIGH VALLEY Phantoms-HOLLYWOOD Oscar-
91 - 2019-10-28888CHICAGO Wolves-HOLLYWOOD Oscar-
93 - 2019-10-30907HOLLYWOOD Oscar-ROCKFORD IceHogs-
94 - 2019-10-31917LEHIGH VALLEY Phantoms-HOLLYWOOD Oscar-
96 - 2019-11-02936HOLLYWOOD Oscar-STOCKTON Flames-
98 - 2019-11-04943TORONTO Marlies-HOLLYWOOD Oscar-
99 - 2019-11-05952HOLLYWOOD Oscar-TUSCON Roadrunners-
101 - 2019-11-07967BELLEVILLE Senators-HOLLYWOOD Oscar-
102 - 2019-11-08975HOLLYWOOD Oscar-IOWA Wild-
103 - 2019-11-09989HOLLYWOOD Oscar-IOWA Wild-
105 - 2019-11-11998BELLEVILLE Senators-HOLLYWOOD Oscar-
106 - 2019-11-121014HOLLYWOOD Oscar-LEHIGH VALLEY Phantoms-



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
25 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
621,396$ 1,635,000$ 1,592,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 513,454$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 72 18,364$ 1,322,208$




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
32281260000164286-222140140000032149-117141120000132137-1053641191830024241605061411921706244771482702414.17%20100.00%011135331.44%17184920.14%11257219.58%238149118517226187
Total Saison Régulière281260000164286-222140140000032149-117141120000132137-1053641191830024241605061411921706244771482702414.17%20100.00%011135331.44%17184920.14%11257219.58%238149118517226187