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Connexion

Gulls
GP: 6 | W: 4 | L: 2 | OTL: 0 | P: 8
GF: 43 | GA: 28 | PP%: 25.00% | PK%: 63.64%
DG: Olivier | Morale : 50 | Moyenne d’équipe : 64
Prochain matchs #95 vs Moose
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Centre de jeu
Gulls
4-2-0, 8pts
1
FINAL
7 Moose
3-2-0, 6pts
Team Stats
W1StreakW3
2-0-0Home Record2-0-0
2-2-0Away Record1-2-0
4-2-0Last 10 Games3-2-0
7.17Goals Per Game6.00
4.67Goals Against Per Game3.60
25.00%Power Play Percentage44.44%
63.64%Penalty Kill Percentage61.54%
Gulls
4-2-0, 8pts
11
FINAL
0 Wild
0-5-0, 0pts
Team Stats
W1StreakL5
2-0-0Home Record0-3-0
2-2-0Away Record0-2-0
4-2-0Last 10 Games0-5-0
7.17Goals Per Game4.00
4.67Goals Against Per Game9.40
25.00%Power Play Percentage26.67%
63.64%Penalty Kill Percentage50.00%
Moose
3-2-0, 6pts
2021-10-26
Gulls
4-2-0, 8pts
Statistiques d’équipe
W3SéquenceW1
2-0-0Fiche domicile2-0-0
1-2-0Fiche visiteur2-2-0
3-2-010 derniers matchs4-2-0
6.00Buts par match 7.17
3.60Buts contre par match 4.67
44.44%Pourcentage en avantage numérique25.00%
61.54%Pourcentage en désavantage numérique63.64%
Americans
5-0-0, 10pts
2021-10-28
Gulls
4-2-0, 8pts
Statistiques d’équipe
W4SéquenceW1
4-0-0Fiche domicile2-0-0
1-0-0Fiche visiteur2-2-0
5-0-010 derniers matchs4-2-0
4.60Buts par match 7.17
2.40Buts contre par match 4.67
33.33%Pourcentage en avantage numérique25.00%
83.33%Pourcentage en désavantage numérique63.64%
Gulls
4-2-0, 8pts
2021-10-29
Wolves
3-2-0, 6pts
Statistiques d’équipe
W1SéquenceOTW1
2-0-0Fiche domicile3-1-0
2-2-0Fiche visiteur0-1-0
4-2-010 derniers matchs3-2-0
7.17Buts par match 4.20
4.67Buts contre par match 3.00
25.00%Pourcentage en avantage numérique21.43%
63.64%Pourcentage en désavantage numérique100.00%
Meneurs d'équipe
Vitek VanecekVictoires
Vitek Vanecek
1
Vitek VanecekPourcentage d’arrêts
Vitek Vanecek
1

Statistiques d’équipe
Buts pour
43
7.17 GFG
Tirs pour
308
51.33 Avg
Pourcentage en avantage numérique
25.0%
3 GF
Début de zone offensive
39.7%
Buts contre
28
4.67 GAA
Tirs contre
294
49.00 Avg
Pourcentage en désavantage numérique
63.6%
4 GA
Début de la zone défensive
35.8%
Information d’équipe

Directeur généralOlivier
DivisionPacifique
ConférenceOuest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Information formation

Équipe Pro26
Équipe Mineure18
Limite contact 44 / 250
Espoirs36


Historique d'équipe

Saison actuelle4-2-0 (8PTS)
Historique266-189-42 (0.535%)
Apparitions séries éliminatoires 5
Historique séries éliminatoires (W-L)27-28
Stanley Cup1


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
1Filip ChytilX100.005435947781828075786771687663660506802111,244,166$
2Carter RowneyXX100.008942856179818362806863866180730506803111,133,333$
3Ryan DonatoXX100.007135947275748870697267647069710506802411,900,000$
4Austin WatsonXX100.009083716786748365616764786377700506802831,500,000$
5Brandon HagelXX100.00766594716882836559696672686564050670221925,000$
6Egor KorshkovXX100.00583592658285786658626863726967050650241925,000$
7Emil BemstromXX100.006835956973778168636667626863640506502121,633,333$
8Aliaksei Protas (R)X100.00867295619472776372605662616264050630194894,167$
9Givani SmithX100.00847974628270746359626360646564050630221913,333$
10Trent FredericX100.007882596581748364716163576265670506302211,137,500$
11Tyler Madden (R)X100.00623593647175766672635856616365050620203925,000$
12Alexander Holtz (R)X100.006435936173727758525657596261630506001841,775,000$
13Deryk EngellandX100.009280765983877557306756924989800506703811,500,000$
14Henri JokiharjuX100.007337897074878569307162685263620506602111,279,166$
15Brendan GuhleX100.00623786707987826530686664536764050650232800,000$
16Olli JuoleviX100.006935956777807665306263695365670506502211,913,333$
17Ian McCoshenX100.00786568558774795530585159457166050600251700,000$
Rayé
1Joshua Ho-SangX100.00603593596960655966635756586965050600241700,000$
2Keegan LoweX100.00705372547989945230535355457571050590271675,000$
3Michael PaliottaX100.00795670528860655230535057457568050580271600,000$
MOYENNE D’ÉQUIPE100.0073528464797779635463616559696705064
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 SPÂgeContratSalaire
1Kaapo Kahkonen100.0083908583828183828183826973050690242725,000$
2Vitek Vanecek100.0083928678828183828183826973050690242716,667$
Rayé
1Jacob Ingham (R)100.0078738584777678777678776165050660203850,000$
2Justus Annunen (R)100.00707674886968706968706961650506202031,050,000$
3Felix Sandstrom100.0069858379686769686769686771050610231925,000$
4Tyler Parsons (R)100.0062737574616062616062616771050570231735,000$
MOYENNE D’ÉQUIPE100.007482818173727473727473667005064
Nom de l’entraîneur 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
1Ryan DonatoGulls (ANA)C/LW6991880013944102720.45%212821.4412339000192068.48%16500012.8000000201
2Emil BemstromGulls (ANA)LW/RW66814900592861621.43%59716.3121349000150066.67%300012.8600000011
3Givani SmithGulls (ANA)RW610313820261451144519.61%39716.2500000000011045.45%1100012.6700000100
4Trent FredericGulls (ANA)C6012123803012198130.00%1110217.0900000000000061.54%3900002.3400000000
5Egor KorshkovGulls (ANA)LW/RW65611900562672719.23%18914.9602239000000062.50%800012.4500000101
6Ian McCoshenGulls (ANA)D61891260274177135.88%3111419.040004900004000.00%000001.5800000010
7Brendan GuhleGulls (ANA)D626834024102113179.52%2314424.0201171000007000.00%000001.1100000020
8Filip ChytilGulls (ANA)C13144000195433.33%02020.5200000000030069.23%1300013.9000000010
9Aliaksei ProtasGulls (ANA)C1033700101200.00%11414.77000000000000100.00%100004.0600000001
10Brandon HagelGulls (ANA)LW/RW60332002252130.00%2254.2600000000000025.00%1200002.3500000000
11Henri JokiharjuGulls (ANA)D11124000020150.00%42424.020000000004100.00%000001.6700000000
12Austin WatsonGulls (ANA)LW/RW12022401060333.33%01919.17000000000100100.00%200002.0900000000
13Deryk EngellandGulls (ANA)D1011400404120.00%22424.530000000014000.00%000000.8200000000
14Carter RowneyGulls (ANA)C/RW1011200437150.00%02222.1000000000040050.00%400000.9000000000
15Alexander HoltzGulls (ANA)RW1000100000010.00%011.750000000000000.00%000000.0000000000
16Olli JuoleviGulls (ANA)D1000000100110.00%12121.770000000003000.00%000000.0000000000
17Tyler MaddenGulls (ANA)C1000100000000.00%000.630000000000000.00%000000.0000000000
Statistiques d’équipe totales ou en moyenne57396210179240143702407718816.25%8694916.6636921490003524064.34%25800052.1300000454
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
1Vitek VanecekGulls (ANA)11001.0000.0060010230000.000010000
Statistiques d’équipe totales ou en moyenne11001.0000.0060010230000.000010000


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 Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Alexander HoltzGulls (ANA)RW182002-01-23Yes192 Lbs6 ft0NoNoNo4Pro & Farm1,775,000$0$0$No1,775,000$1,775,000$1,775,000$Lien NHL
Aliaksei ProtasGulls (ANA)C192001-01-06Yes210 Lbs6 ft6NoNoNo4Pro & Farm894,167$0$0$No888,333$888,333$888,333$Lien NHL
Austin WatsonGulls (ANA)LW/RW281992-01-13No198 Lbs6 ft4NoNoNo3Pro & Farm1,500,000$0$0$No1,500,000$1,500,000$Lien / Lien NHL
Brandon HagelGulls (ANA)LW/RW221998-08-27No174 Lbs5 ft11NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Brendan GuhleGulls (ANA)D231997-07-29No197 Lbs6 ft2NoNoNo2Pro & Farm800,000$0$0$No800,000$Lien / Lien NHL
Carter RowneyGulls (ANA)C/RW311989-05-10No208 Lbs6 ft1NoNoNo1Pro & Farm1,133,333$0$0$NoLien / Lien NHL
Deryk EngellandGulls (ANA)D381982-04-03No212 Lbs6 ft2NoNoNo1Pro & Farm1,500,000$0$0$NoLien / Lien NHL
Egor KorshkovGulls (ANA)LW/RW241996-07-10No180 Lbs6 ft4NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Emil BemstromGulls (ANA)LW/RW211999-06-01No193 Lbs6 ft0NoNoNo2Pro & Farm1,633,333$0$0$No1,633,333$Lien / Lien NHL
Felix SandstromGulls (ANA)G231997-01-12No191 Lbs6 ft2NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Filip ChytilGulls (ANA)C211999-09-05No206 Lbs6 ft2NoNoNo1Pro & Farm1,244,166$0$0$NoLien / Lien NHL
Givani SmithGulls (ANA)RW221998-02-27No210 Lbs6 ft2NoNoNo1Pro & Farm913,333$0$0$NoLien / Lien NHL
Henri JokiharjuGulls (ANA)D211999-06-17No199 Lbs6 ft0NoNoNo1Pro & Farm1,279,166$0$0$NoLien / Lien NHL
Ian McCoshenGulls (ANA)D251995-08-05No218 Lbs6 ft3NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Jacob InghamGulls (ANA)G202000-06-10Yes186 Lbs6 ft4NoNoNo3Pro & Farm850,000$0$0$No850,000$850,000$Lien NHL
Joshua Ho-SangGulls (ANA)RW241996-01-22No173 Lbs6 ft0NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Justus AnnunenGulls (ANA)G202000-03-11Yes210 Lbs6 ft4NoNoNo3Pro & Farm1,050,000$0$0$No1,050,000$1,050,000$Lien NHL
Kaapo KahkonenGulls (ANA)G241996-08-16No215 Lbs6 ft2NoNoNo2Pro & Farm725,000$0$0$No725,000$Lien / Lien NHL
Keegan LoweGulls (ANA)D271993-03-29No191 Lbs6 ft2NoNoNo1Pro & Farm675,000$0$0$NoLien / Lien NHL
Michael PaliottaGulls (ANA)D271993-04-06No207 Lbs6 ft4NoNoNo1Pro & Farm600,000$0$0$NoLien / Lien NHL
Olli JuoleviGulls (ANA)D221998-05-05No182 Lbs6 ft2NoNoNo1Pro & Farm1,913,333$0$0$NoLien / Lien NHL
Ryan DonatoGulls (ANA)C/LW241996-04-09No192 Lbs6 ft0NoNoNo1Pro & Farm1,900,000$0$0$NoLien / Lien NHL
Trent FredericGulls (ANA)C221998-02-11No203 Lbs6 ft2NoNoNo1Pro & Farm1,137,500$0$0$NoLien / Lien NHL
Tyler MaddenGulls (ANA)C201999-11-09Yes152 Lbs5 ft11NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien NHL
Tyler ParsonsGulls (ANA)G231997-09-18Yes185 Lbs6 ft1NoNoNo1Pro & Farm735,000$0$0$NoLien / Lien NHL
Vitek VanecekGulls (ANA)G241996-01-09No187 Lbs6 ft2NoNoNo2Pro & Farm716,667$0$0$No716,667$Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2623.58195 Lbs6 ft21.691,079,808$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Austin WatsonRyan DonatoCarter Rowney40122
2Brandon HagelFilip ChytilEmil Bemstrom30122
3Egor KorshkovTrent FredericGivani Smith20122
4Ryan DonatoAliaksei ProtasAlexander Holtz10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Deryk EngellandHenri Jokiharju40122
2Olli JuoleviBrendan Guhle30122
3Ian McCoshenAliaksei Protas20122
4Deryk EngellandHenri Jokiharju10122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Austin WatsonRyan DonatoCarter Rowney60122
2Brandon HagelFilip ChytilEmil Bemstrom40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Deryk EngellandHenri Jokiharju60122
2Olli JuoleviBrendan Guhle40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Ryan DonatoCarter Rowney60122
2Austin WatsonFilip Chytil40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Deryk EngellandHenri Jokiharju60122
2Olli JuoleviBrendan Guhle40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Ryan Donato60122Deryk EngellandHenri Jokiharju60122
2Carter Rowney40122Olli JuoleviBrendan Guhle40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Ryan DonatoCarter Rowney60122
2Austin WatsonFilip Chytil40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Deryk EngellandHenri Jokiharju60122
2Olli JuoleviBrendan Guhle40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Austin WatsonRyan DonatoCarter RowneyDeryk EngellandHenri Jokiharju
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Austin WatsonRyan DonatoCarter RowneyDeryk EngellandHenri Jokiharju
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Tyler Madden, Egor Korshkov, Givani SmithTyler Madden, Egor KorshkovGivani Smith
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ian McCoshen, Olli Juolevi, Brendan GuhleIan McCoshenOlli Juolevi, Brendan Guhle
Tirs de pénalité
Ryan Donato, Carter Rowney, Austin Watson, Filip Chytil, Brandon Hagel
Gardien
#1 : Vitek Vanecek, #2 : Kaapo Kahkonen


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
TotalDomicileVisiteur
# 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
1Condors1010000068-2000000000001010000068-200.000691500191014041949911505717030100.00%000.00%010519653.57%7017739.55%6012149.59%168130128326335
2Heat11000000835000000000001100000083521.0008132100191014069949911504616429100.00%2150.00%010519653.57%7017739.55%6012149.59%168130128326335
3Moose21100000812-4110000007521010000017-620.5008132100191014071949911501173510487228.57%4325.00%010519653.57%7017739.55%6012149.59%168130128326335
4Wild2200000021516110000001055110000001101141.00021365701191014012794991150743212523133.33%50100.00%010519653.57%7017739.55%6012149.59%168130128326335
Total642000004328152200000017107422000002618880.6674371114011910140308949911502941002615912325.00%11463.64%010519653.57%7017739.55%6012149.59%168130128326335
_Since Last GM Reset642000004328152200000017107422000002618880.6674371114011910140308949911502941002615912325.00%11463.64%010519653.57%7017739.55%6012149.59%168130128326335
_Vs Conference642000004328152200000017107422000002618880.6674371114011910140308949911502941002615912325.00%11463.64%010519653.57%7017739.55%6012149.59%168130128326335
_Vs Division41100000291712200000001710721100000127520.25029497801191014019894991150191672210010330.00%9366.67%010519653.57%7017739.55%6012149.59%168130128326335

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
68W143711143082941002615901
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
64200004328
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
22000001710
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
42200002618
Derniers 10 matchs
WLOTWOTL SOWSOL
420000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
12325.00%11463.64%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
949911501910140
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
10519653.57%7017739.55%6012149.59%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
168130128326335


Derniers matchs 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
2 - 2021-10-137Moose5Gulls7BWSommaire du match
4 - 2021-10-1519Wild5Gulls10BWSommaire du match
7 - 2021-10-1837Gulls8Heat3AWSommaire du match
8 - 2021-10-1949Gulls6Condors8ALSommaire du match
10 - 2021-10-2159Gulls1Moose7ALSommaire du match
12 - 2021-10-2368Gulls11Wild0AWSommaire du match
15 - 2021-10-2695Moose-Gulls-
17 - 2021-10-28107Americans-Gulls-
18 - 2021-10-29115Gulls-Wolves-
20 - 2021-10-31128Rocket-Gulls-
22 - 2021-11-02142Devils-Gulls-
25 - 2021-11-05160Roadrunners-Gulls-
27 - 2021-11-07177Rampage-Gulls-
29 - 2021-11-09190Gulls-Comets-
31 - 2021-11-11205Gulls-Palm Springs-
34 - 2021-11-14229Comets-Gulls-
36 - 2021-11-16243Bears-Gulls-
38 - 2021-11-18258Checkers-Gulls-
42 - 2021-11-22283Gulls-Admirals-
44 - 2021-11-24299Gulls-Eagles-
46 - 2021-11-26308Senators-Gulls-
48 - 2021-11-28332Marlies-Gulls-
50 - 2021-11-30345Gulls-Reign-
51 - 2021-12-01351Wolves-Gulls-
53 - 2021-12-03365Heat-Gulls-
56 - 2021-12-06384Gulls-Bears-
57 - 2021-12-07392Gulls-Americans-
59 - 2021-12-09404Gulls-Monsters-
61 - 2021-12-11422Gulls-Penguins-
62 - 2021-12-12432Gulls-Rampage-
65 - 2021-12-15453Palm Springs-Gulls-
67 - 2021-12-17470Roadrunners-Gulls-
70 - 2021-12-20493Gulls-Condors-
71 - 2021-12-21500Gulls-Heat-
73 - 2021-12-23520Gulls-Comets-
77 - 2021-12-27536Barracuda-Gulls-
79 - 2021-12-29551Comets-Gulls-
81 - 2021-12-31561Gulls-Wolves-
83 - 2022-01-02579Gulls-Eagles-
85 - 2022-01-04594Phantoms-Gulls-
87 - 2022-01-06609Griffins-Gulls-
89 - 2022-01-08627Wolf Pack-Gulls-
92 - 2022-01-11644Penguins-Gulls-
95 - 2022-01-14662Gulls-Wild-
96 - 2022-01-15675Gulls-IceHogs-
100 - 2022-01-19703Eagles-Gulls-
102 - 2022-01-21719Crunch-Gulls-
105 - 2022-01-24737Gulls-Bruins-
107 - 2022-01-26752Gulls-Marlies-
108 - 2022-01-27757Gulls-Rocket-
110 - 2022-01-29772Gulls-Senators-
112 - 2022-01-31791Gulls-Griffins-
137 - 2022-02-25828Reign-Gulls-
139 - 2022-02-27845Sound Tigers-Gulls-
141 - 2022-03-01859Bruins-Gulls-
144 - 2022-03-04879Wolves-Gulls-
146 - 2022-03-06897Barracuda-Gulls-
148 - 2022-03-08911Gulls-IceHogs-
150 - 2022-03-10925Gulls-Admirals-
152 - 2022-03-12937Gulls-Devils-
153 - 2022-03-13948Gulls-Sound Tigers-
155 - 2022-03-15955Gulls-Wolf Pack-
158 - 2022-03-18981Thunderbirds-Gulls-
161 - 2022-03-211003Admirals-Gulls-
163 - 2022-03-231018IceHogs-Gulls-
165 - 2022-03-251033Palm Springs-Gulls-
166 - 2022-03-261045Gulls-Barracuda-
169 - 2022-03-291067Stars-Gulls-
171 - 2022-03-311082Stars-Gulls-
172 - 2022-04-011089Gulls-Roadrunners-
174 - 2022-04-031107Condors-Gulls-
177 - 2022-04-061127Heat-Gulls-
180 - 2022-04-091148Gulls-Phantoms-
181 - 2022-04-101158Gulls-Checkers-
183 - 2022-04-121166Gulls-Thunderbirds-
185 - 2022-04-141184Gulls-Crunch-
188 - 2022-04-171215Monsters-Gulls-
190 - 2022-04-191226Reign-Gulls-
194 - 2022-04-231259Gulls-Reign-
195 - 2022-04-241269Rampage-Gulls-
197 - 2022-04-261285Gulls-Barracuda-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
200 - 2022-04-291309Gulls-Stars-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
39 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
181,584$ 2,807,500$ 854,583$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 181,584$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 188 13,968$ 2,625,984$




TotalDomicileVisiteur
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
482363102256212194184123110112312192294113200113391102-11942123705823406965712383074478482726047991394200254510118.53%6008685.67%51341286246.86%1441326944.08%517118943.48%1977131819756481035516
582125901226181329-148415300020490164-74417290102291165-7438181303484310795049239307607798244181121728318301813217.68%1263373.81%0734222233.03%1005354828.33%387127730.31%147810432574569915391
68244260314433423410041211302032179122574123130111215511243107334596930140137999138220125612801261270582246821312075325.60%1933780.83%32023347958.15%1499278353.86%733131755.66%2196159117505471024539
78243280133432124081412115001131611214041221301221160119411013215668871101281088137910116112831320265873650920242183917.89%2194479.91%32063337461.14%1544281754.81%765134257.00%2231163617175411015535
8825118031454281982304125803113223911324126100003220510798122428771119918019012011140620132313491367245072640819011664426.51%1803083.33%12032330961.41%1461252957.77%853141260.41%242618521586491961520
982422501356357256101412410012221911236841181500134166133331053576009571501511089235330114711951170352398636420101794122.91%1603478.75%01527316648.23%1512356542.41%644136947.04%192513902075554981479
10642000004328152200000017107422000002618884371114011910140308949911502941002615912325.00%11463.64%010519653.57%7017739.55%6012149.59%168130128326335
Total Saison régulière498232189011122331187614793972481218707791798272325925011110204514148947561385751876327751531024197645644952029294649067856769184155386345212057150831320.76%148926882.00%1298251860852.80%85321868845.65%3959802749.32%12404896211808338359983017
Séries éliminatoires
41257000002526-15230000011101734000001416-210254570010681028607587109413124245315981515.31%971584.54%112140330.02%19051037.25%6816940.24%27017032610616277
6514000001324-1120200000610-431200000714-72132033000525154047514225373281351218.33%13284.62%16817040.00%9022839.47%348540.00%10770147396732
72516900000817110127500000393451394000004237532811512321002926248660277276290912270196729711318.31%951287.37%047695549.84%494106946.21%20340949.63%615420624195334168
8624000001619-3312000001011-13120000068-24162945000101523401016370239733214516743.75%16381.25%111725146.61%11323148.92%399839.80%14097144417437
9734000002223-13210000010100413000001213-1622436511010562910898084290893618126311.54%17476.47%015730651.31%13932143.30%5812347.15%1781222066110249
Total Séries éliminatoires55272800000157163-62512130000076751301515000008188-75415728844522060425018310589557595210762953715052233917.49%2383684.87%3939208545.04%1026235943.49%40288445.48%13128801449444742365