Connexion

Senators
GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Noddan | Morale : 40 | Moyenne d’équipe : 57
Prochain matchs #13 vs Americans
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Senators
0-0-0, 0pts
2022-09-15
Americans
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Senators
0-0-0, 0pts
2022-09-17
Marlies
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Bruins
0-0-0, 0pts
2022-09-20
Senators
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Meneurs d'équipe

Statistiques d’équipe
Buts pour
0
0.00 GFG
Tirs pour
0
0.00 Avg
Pourcentage en avantage numérique
0.0%
0 GF
Début de zone offensive
0.0%
Buts contre
0
0.00 GAA
Tirs contre
0
0.00 Avg
Pourcentage en désavantage numérique
0.0%
0 GA
Début de la zone défensive
0.0%
Information d’équipe

Directeur généralNoddan
EntraîneurKen Gernander
DivisionAtlantic Division
ConférenceEastern Conference
CapitaineClark Bishop
Assistant #1Phillip Di Giuseppe
Assistant #2Nicolas Beaudin


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison0


Information formation

Équipe Pro29
Équipe Mineure19
Limite contact 48 / 90
Espoirs27


Historique d'équipe

Saison actuelle0-0-0 (0PTS)
Historique90-48-22 (0.563%)
Apparitions séries éliminatoires 2
Historique séries éliminatoires (W-L)2-8
Stanley Cup0


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 moyen
1Quinton Byfield (R)0X100.00565082569174595768646362715262040590203925,000$
2Alexander Holtz (R)0XXX100.00574477608260506440676660745262040590203850,000$
3Clark Bishop (C)0X100.00774477558360415560625861596069040570261825,000$
4Phillip Di Giuseppe (A)0X100.005050755783602063406862626156660405702811,300,000$
5Adam Raska (R)0X100.00984078597760465340615757595164040560213850,000$
6Jimmy Huntington0X100.00505075558360395960656062605463040560232925,000$
7Nathan Todd0X100.00505075548460275760636062605664040550261750,000$
8Brandon Gignac0X100.00504175587960265840646062605564040550241750,000$
9Walker Duehr0X100.00504875518760495640625962605463040550241925,000$
10Maksim Sushko0X100.00504975538260415340605962605262040540231900,000$
11Felix Bibeau (R)0XXX100.00504775558060225260615662585161040530231750,000$
12Erik N Gustafsson0X100.006144896383786767207062686161690406303011,000,000$
13Hunter Drew0XX100.00945875598260525940646157615265040580231900,000$
14Johnathan Kovacevic0X100.00505275528760526820646365625363040580252750,000$
15Nicolas Beaudin (A)0X100.005037755876605366206357615952620405702311,300,000$
16Victor Berglund0X100.00504175578060276920636268615161040570232925,000$
17Matthew Cairns (R)0X100.00505375488860456220605568585362040560241750,000$
18Wyatt Newpower (R)0X100.00504475538460336520625968605161040560241925,000$
Rayé
1Blake Murray (R)0XXX100.00504375548260425140605662585161040540213750,000$
2Jack Badini (R)0X100.00505175518460245160605562585262040530241800,000$
3Maxim Golod (R)0X100.00504175557960105240615662585060040520222925,000$
4Zack Hayes (R)0X100.00505875459260326520625768595362040560231925,000$
5Dmitry Semykin (R)0X100.00505375488860196220605768595161040550222750,000$
MOYENNE D’ÉQUIPE100.0056477655836138593963596361536304056
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
1Victor Brattstrom100.0058666389626260636259617169040630
2Jet Greaves (R)100.0055666383596056606057586566040610
Rayé
1Anton Khudobin100.0059656282656363656460638977040650
2Jonas Johansson100.0051686589565655575653557570040600
3Kaden Fulcher (R)100.0048585587525251525249517068040560
4Callum Booth100.0043535087484746484844467169040530
MOYENNE D’ÉQUIPE100.005263608657575558575456747004060
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ken Gernander75757575757575USA538500,000$


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
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


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 restantPlafond 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
Adam RaskaSenators (OTT)RW219/25/2001Yes178 Lbs5 ft10NoNoNo3Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$850,000$Lien
Alexander HoltzSenators (OTT)C/LW/RW201/23/2002Yes195 Lbs6 ft0NoNoNo3Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$850,000$Lien
Anton Khudobin (contrat à 1 volet)Senators (OTT)G365/7/1986No194 Lbs5 ft11NoNoNo1Pro & Farm3,500,000$3,462,963$3,500,000$3,462,963$2,375,000$2,349,868$NoLien
Blake MurraySenators (OTT)C/LW/RW217/5/2001Yes190 Lbs6 ft2NoNoNo3Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$750,000$Lien
Brandon GignacSenators (OTT)LW2411/7/1997No185 Lbs5 ft11NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Callum BoothSenators (OTT)G257/1/1997No194 Lbs6 ft4NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Clark BishopSenators (OTT)C263/29/1996No197 Lbs6 ft1NoNoNo1Pro & Farm825,000$816,270$825,000$816,270$0$0$NoLien
Dmitry SemykinSenators (OTT)D222/24/2000Yes212 Lbs6 ft3NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Erik N GustafssonSenators (OTT)D303/14/1992No197 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$NoLien
Felix BibeauSenators (OTT)C/LW/RW233/31/1999Yes187 Lbs6 ft0NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Hunter DrewSenators (OTT)RW/D2310/21/1998No191 Lbs6 ft2NoNoNo1Pro & Farm900,000$890,476$900,000$890,476$0$0$NoLien
Jack BadiniSenators (OTT)C241/19/1998Yes202 Lbs6 ft0NoNoNo1Pro & Farm800,000$791,534$800,000$791,534$0$0$NoLien
Jet GreavesSenators (OTT)G217/1/2001Yes170 Lbs6 ft0NoNoNo3Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$925,000$Lien
Jimmy HuntingtonSenators (OTT)C2311/18/1998No200 Lbs6 ft0NoNoNo2Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$Lien
Johnathan KovacevicSenators (OTT)D257/12/1997No208 Lbs6 ft4NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Jonas Johansson (contrat à 1 volet)Senators (OTT)G277/1/1995No220 Lbs6 ft5NoNoNo2Pro & Farm1,395,053$1,380,291$1,395,053$1,380,291$270,053$267,195$No1,395,053$Lien
Kaden FulcherSenators (OTT)G247/1/1998Yes201 Lbs6 ft3NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Maksim SushkoSenators (OTT)RW232/10/1999No194 Lbs6 ft0NoNoNo1Pro & Farm900,000$890,476$900,000$890,476$0$0$NoLien
Matthew CairnsSenators (OTT)D244/27/1998Yes213 Lbs6 ft3NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Maxim GolodSenators (OTT)LW228/18/2000Yes182 Lbs6 ft0NoNoNo2Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$Lien
Nathan ToddSenators (OTT)C2612/2/1995No200 Lbs6 ft1NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Nicolas BeaudinSenators (OTT)D2310/7/1999No168 Lbs5 ft11NoNoNo1Pro & Farm1,300,000$1,286,243$1,300,000$1,286,243$0$0$NoLien
Phillip Di GiuseppeSenators (OTT)LW2810/9/1993No200 Lbs6 ft0NoNoNo1Pro & Farm1,300,000$1,286,243$1,300,000$1,286,243$0$0$NoLien
Quinton ByfieldSenators (OTT)C208/19/2002Yes220 Lbs6 ft5NoNoNo3Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$925,000$Lien
Victor BerglundSenators (OTT)D238/2/1999No183 Lbs6 ft0NoNoNo2Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$Lien
Victor BrattstromSenators (OTT)G257/1/1997No198 Lbs6 ft5YesNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Walker DuehrSenators (OTT)RW2411/23/1997No210 Lbs6 ft2NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Wyatt NewpowerSenators (OTT)D2412/9/1997Yes194 Lbs6 ft3NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Zack HayesSenators (OTT)D234/24/1999Yes231 Lbs6 ft3NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2924.14197 Lbs6 ft11.59998,105$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Alexander HoltzQuinton ByfieldAdam Raska40122
2Phillip Di GiuseppeClark BishopWalker Duehr30122
3Brandon GignacJimmy HuntingtonMaksim Sushko20122
4Felix BibeauNathan ToddQuinton Byfield10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Erik N GustafssonHunter Drew40122
2Johnathan KovacevicNicolas Beaudin30122
3Victor BerglundWyatt Newpower20122
4Matthew CairnsErik N Gustafsson10122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Alexander HoltzQuinton ByfieldAdam Raska60122
2Phillip Di GiuseppeClark BishopWalker Duehr40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Erik N GustafssonHunter Drew60122
2Johnathan KovacevicNicolas Beaudin40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Quinton ByfieldAlexander Holtz60122
2Phillip Di GiuseppeClark Bishop40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Erik N GustafssonHunter Drew60122
2Johnathan KovacevicNicolas Beaudin40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Quinton Byfield60122Erik N GustafssonHunter Drew60122
2Alexander Holtz40122Johnathan KovacevicNicolas Beaudin40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Quinton ByfieldAlexander Holtz60122
2Phillip Di GiuseppeClark Bishop40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Erik N GustafssonHunter Drew60122
2Johnathan KovacevicNicolas Beaudin40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Alexander HoltzQuinton ByfieldAdam RaskaErik N GustafssonHunter Drew
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Alexander HoltzQuinton ByfieldAdam RaskaErik N GustafssonHunter Drew
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Jimmy Huntington, Nathan Todd, Brandon GignacJimmy Huntington, Nathan ToddBrandon Gignac
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Victor Berglund, Wyatt Newpower, Matthew CairnsVictor BerglundWyatt Newpower, Matthew Cairns
Tirs de pénalité
Quinton Byfield, Alexander Holtz, Hunter Drew, Phillip Di Giuseppe, Clark Bishop
Gardien
#1 : Victor Brattstrom, #2 : Jet Greaves
Lignes d’attaque personnalisées en prolongation
Quinton Byfield, Alexander Holtz, Hunter Drew, Phillip Di Giuseppe, Clark Bishop, Adam Raska, Adam Raska, Jimmy Huntington, Walker Duehr, Nathan Todd, Brandon Gignac
Lignes de défense personnalisées en prolongation
Erik N Gustafsson, Hunter Drew, Johnathan Kovacevic, Nicolas Beaudin, Victor Berglund


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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
00N/A0000000000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 matchs
WLOTWOTL SOWSOL
000000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
000.00%000.00%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
00000000
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
000.00%000.00%000.00%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
000000


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
7 - 2022-09-1513Senators-Americans-
9 - 2022-09-1730Senators-Marlies-
12 - 2022-09-2049Bruins-Senators-
14 - 2022-09-2265Bears-Senators-
16 - 2022-09-2477Roadrunners-Senators-
18 - 2022-09-2692Stars-Senators-
21 - 2022-09-29113Wild-Senators-
23 - 2022-10-01129Senators-Checkers-
26 - 2022-10-04148Senators-Crunch-
28 - 2022-10-06163Silver Knights-Senators-
30 - 2022-10-08183Phantoms-Senators-
33 - 2022-10-11200Canucks-Senators-
35 - 2022-10-13213Senators-Comets-
37 - 2022-10-15225Senators-Phantoms-
39 - 2022-10-17244Islanders-Senators-
41 - 2022-10-19257Americans-Senators-
44 - 2022-10-22274Comets-Senators-
46 - 2022-10-24299Senators-Barracuda-
48 - 2022-10-26315Senators-Silver Knights-
50 - 2022-10-28323Senators-Gulls-
52 - 2022-10-30345Senators-Reign-
55 - 2022-11-02362Wolf Pack-Senators-
57 - 2022-11-04376Senators-Wolf Pack-
58 - 2022-11-05383Barracuda-Senators-
61 - 2022-11-08406Reign-Senators-
63 - 2022-11-10423Senators-Stars-
65 - 2022-11-12434Senators-Admirals-
67 - 2022-11-14451Gulls-Senators-
69 - 2022-11-16466Rocket-Senators-
72 - 2022-11-19485Senators-Griffins-
73 - 2022-11-20497Senators-Wild-
75 - 2022-11-22514Senators-Moose-
77 - 2022-11-24528Bears-Senators-
78 - 2022-11-25534Griffins-Senators-
82 - 2022-11-29546Bruins-Senators-
84 - 2022-12-01566Senators-Bears-
86 - 2022-12-03585Senators-Griffins-
87 - 2022-12-04593Americans-Senators-
89 - 2022-12-06601Monsters-Senators-
93 - 2022-12-10632Firebirds-Senators-
95 - 2022-12-12645Admirals-Senators-
98 - 2022-12-15672Senators-Roadrunners-
100 - 2022-12-17678Senators-Eagles-
102 - 2022-12-19704Senators-Thunderbirds-
104 - 2022-12-21712Penguins-Senators-
106 - 2022-12-23730Senators-Penguins-
107 - 2022-12-24738Moose-Senators-
111 - 2022-12-28766Islanders-Senators-
113 - 2022-12-30782Senators-Marlies-
114 - 2022-12-31792Rocket-Senators-
117 - 2023-01-03803Senators-Rocket-
128 - 2023-01-14834Condors-Senators-
130 - 2023-01-16850Heat-Senators-
131 - 2023-01-17858Senators-Islanders-
134 - 2023-01-20878IceHogs-Senators-
136 - 2023-01-22897Thunderbirds-Senators-
137 - 2023-01-23903Senators-Bruins-
141 - 2023-01-27933Senators-Wolves-
142 - 2023-01-28940Senators-Rocket-
145 - 2023-01-31959Griffins-Senators-
147 - 2023-02-02976Senators-Wolf Pack-
149 - 2023-02-04996Monsters-Senators-
151 - 2023-02-061009Senators-IceHogs-
154 - 2023-02-091035Senators-Firebirds-
156 - 2023-02-111050Senators-Canucks-
157 - 2023-02-121058Senators-Heat-
159 - 2023-02-141071Senators-Condors-
161 - 2023-02-161080Eagles-Senators-
163 - 2023-02-181102Marlies-Senators-
165 - 2023-02-201115Senators-Penguins-
166 - 2023-02-211125Senators-Bruins-
168 - 2023-02-231139Crunch-Senators-
170 - 2023-02-251160Senators-Comets-
172 - 2023-02-271170Checkers-Senators-
175 - 2023-03-021193Phantoms-Senators-
177 - 2023-03-041210Marlies-Senators-
178 - 2023-03-051220Senators-Monsters-
180 - 2023-03-071232Senators-Wolves-
182 - 2023-03-091245Senators-Checkers-
184 - 2023-03-111267Crunch-Senators-
186 - 2023-03-131277Wolves-Senators-
189 - 2023-03-161302Senators-Americans-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance0.00%0.00%
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
41 0 - 0.00%0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
25,450$ 2,405,000$ 2,405,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
12,725$ 25,450$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 187 12,725$ 2,379,575$




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
11823524068452041832141171204332988513411812025131069881032043515552835857419290289210669106523777942391879873843.68%1073270.09%21042180757.66%805151453.17%535101152.92%171692615738051692814
11823524068452041832141171204332988513411812025131069881032043515552835857419290289210669106523777942391879873843.68%1073270.09%21042180757.66%805151453.17%535101152.92%171692615738051692814
Total Saison régulière164704801216810408366428234240866419617026823624041026212196162064087021110416701701483858041784213218201304754158847837581747643.68%2146470.09%42084361457.66%1610302853.17%1070202252.92%343318523146161033851629
Séries éliminatoires
1151400000415-112110000045-130300000010-10247110003108023352201834223834125.00%9455.56%0296942.03%4110937.61%265844.83%83321084810859
1151400000415-112110000045-130300000010-10247110003108023352201834223834125.00%9455.56%0296942.03%4110937.61%265844.83%83321084810859
Total Séries éliminatoires102800000830-2242200000810-260600000020-20481422000620160467044036684461668225.00%18855.56%05813842.03%8221837.61%5211644.83%1666421797216118