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Senators
GP: 17 | W: 7 | L: 9 | OTL: 1 | P: 15
GF: 38 | GA: 46 | PP%: 11.90% | PK%: 73.81%
DG: Chris Paquet | Morale : 75 | Moyenne d’équipe : 61
Prochains matchs #236 vs Canucks

Centre de jeu
Senators
7-9-1, 15pts
0
FINAL
3 Checkers
10-6-0, 20pts
Team Stats
L2SéquenceW3
3-4-1Fiche domicile5-3-0
4-5-0Fiche domicile5-3-0
5-5-0Derniers 10 matchs5-5-0
2.24Buts par match 3.81
2.71Buts contre par match 2.50
11.90%Pourcentage en avantage numérique16.36%
73.81%Pourcentage en désavantage numérique89.47%
Wranglers
12-4-1, 25pts
4
FINAL
3 Senators
7-9-1, 15pts
Team Stats
W1SéquenceL2
6-2-0Fiche domicile3-4-1
6-2-1Fiche domicile4-5-0
6-3-1Derniers 10 matchs5-5-0
3.18Buts par match 2.24
2.24Buts contre par match 2.71
25.00%Pourcentage en avantage numérique11.90%
72.92%Pourcentage en désavantage numérique73.81%
Senators
7-9-1, 15pts
2026-10-29
Canucks
4-10-3, 11pts
Statistiques d’équipe
L2SéquenceOTL1
3-4-1Fiche domicile2-5-1
4-5-0Fiche visiteur2-5-2
5-5-010 derniers matchs1-7-2
2.24Buts par match 2.24
2.71Buts contre par match 2.24
11.90%Pourcentage en avantage numérique10.00%
73.81%Pourcentage en désavantage numérique83.67%
Checkers
10-6-0, 20pts
2026-10-31
Senators
7-9-1, 15pts
Statistiques d’équipe
W3SéquenceL2
5-3-0Fiche domicile3-4-1
5-3-0Fiche visiteur4-5-0
5-5-010 derniers matchs5-5-0
3.81Buts par match 2.24
2.50Buts contre par match 2.24
16.36%Pourcentage en avantage numérique11.90%
89.47%Pourcentage en désavantage numérique73.81%
Senators
7-9-1, 15pts
2026-11-02
Wranglers
12-4-1, 25pts
Statistiques d’équipe
L2SéquenceW1
3-4-1Fiche domicile6-2-0
4-5-0Fiche visiteur6-2-1
5-5-010 derniers matchs6-3-1
2.24Buts par match 3.18
2.71Buts contre par match 3.18
11.90%Pourcentage en avantage numérique25.00%
73.81%Pourcentage en désavantage numérique72.92%
Meneurs d'équipe
Buts
Easton Cowan
6
Passes
Axel Sandin-Pellikka
13
Points
Axel Sandin-Pellikka
15
Plus/Moins
Easton Cowan
6
Hunter ShepardVictoires
Hunter Shepard
7
Hunter ShepardPourcentage d’arrêts
Hunter Shepard
0.894

Statistiques d’équipe
Buts pour
38
2.24 GFG
Tirs pour
445
26.18 Avg
Pourcentage en avantage numérique
11.9%
5 GF
Début de zone offensive
41.6%
Buts contre
46
2.71 GAA
Tirs contre
431
25.35 Avg
Pourcentage en désavantage numérique
73.8%%
11 GA
Début de la zone défensive
39.7%
Informations de l'équipe

Directeur généralChris Paquet
EntraîneurRyan Huska
DivisionAtlantic Division
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,592
Billets de saison0


Informations de la formation

Équipe Pro29
Équipe Mineure19
Limite contact 48 / 70
Espoirs27


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
1Bo GroulxX100.00753980658187826461636774626668075660263850,000$
2Chris WagnerX100.00634173647387866268606665617577075640352800,000$
3Easton Cowan (R)X100.00653879687284866658676362656163075640213873,500$
4Adam SykoraXX100.00683791627182875961586563596264075630222806,666$
5Felix Unger SorumX100.00623693647283856367655759626163075620213831,667$
6Owen SillingerX100.00643780636782816265615964586971075620292800,000$
7Wyatt BongiovanniX100.00643884607388825861576359626769075620272800,000$
8Philippe DaoustX100.00563790626573815867645756596667075610252800,000$
9Viktor NeuchevXX100.00643794617384795962605758566365075610221870,000$
10Hayden HodgsonX100.00776552588670795655545557537072075600302800,000$
11Jake LeschyshynXX100.0063388757727485566055585456676907560N0273775,000$
12Axel Sandin-Pellikka (R)X100.00613892697486886730686364526162075650213918,333$
13Drew HellesonX100.007543806485838462306757725065660756402521,100,000$
14Oliver Bonk (R)X100.00693885677683776630646162486165075640213886,666$
15Dennis GilbertX100.00777369648474716330695065517072075630292800,000$
16Cameron CrottyX100.00734177608679825830635262466769075620272800,000$
17Tobias BjornfotX100.00673890637480825830605963496567075620252775,000$
18Ville OttavainenX100.00824372629182836130605359466466075620241867,500$
Rayé
1Justin ErtelX100.00703981557965725358565457526365075580232800,000$
2Keean WashkurakX100.00584268576769855563545653576567075580252800,000$
3David GoyetteX100.00564073586570795755565452596264075570222891,666$
4Fabian WagnerX100.00553693566471745451535552566264075570222800,000$
5Ivan Ryabkin (R)X100.00604556586973715761595253545961075570193952,222$
6Tyson HindsX100.00733986568482865430555363456365075600231829,444$
7Scott HarringtonX100.00723987548163825230555356467375075590332800,000$
8Michael BuchingerX100.00593881566866805530535452466264075570222838,333$
MOYENNE D’ÉQUIPE100.0066418161757881594960576054656707561
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
1Hunter Shepard100.0075827877747375747375747185075650302800,000$
2Kevin Mandolese100.007475718273727473727473667507564N02631,999,999$
Rayé
1Isaiah Saville100.007273687671707271707271667507563N02631,999,999$
MOYENNE D’ÉQUIPE100.007477727873727473727473687807564
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ryan Huska82857978767174CAN511850,000$


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
1Axel Sandin-PellikkaSenators (OTT)D172131566024222614167.69%2641624.530221137011035100%000000.7200000112
2Easton CowanSenators (OTT)RW176915610026286410389.38%637422.0010110360110130151.52%3300000.8001000220
3Oliver BonkSenators (OTT)D17391256046202061715.00%1841524.44022537101136100%000100.5800000112
4Owen SillingerSenators (OTT)C174610480184039131810.26%533319.6300000000000051.64%39700000.6000000110
5Chris WagnerSenators (OTT)C17549-310021564582711.11%133619.771123350000430150.63%39500000.5401000012
6Bo GroulxSenators (OTT)C17257-411555356013463.33%238522.690007360001360042.78%35300000.3601010200
7Cole KoepkeSenatorsLW952766031223661813.89%521123.500117180001134047.37%1900000.6601000121
8Dennis GilbertSenators (OTT)D17145-31202828951011.11%2334220.15101334000030000%000000.2900000000
9Felix Unger SorumSenators (OTT)RW17325-5208192952610.34%331318.42011338000000043.75%1600000.3200000001
10Viktor NeuchevSenators (OTT)LW/RW17325-24011153410208.82%225815.1900000000011153.85%1300000.3900000100
11Cameron CrottySenators (OTT)D17134-380221495411.11%1534520.31011135000031000%000000.2300000000
12Adam SykoraSenators (OTT)C/LW17213-48016162811277.14%133719.852025380000250042.86%4200000.1801000000
13Drew HellesonSenators (OTT)D17033-595251916470%1526815.7700024000010000%000000.2200100000
14Philippe DaoustSenators (OTT)C17112-1003560716.67%21539.0400014000000060.00%1500000.2600000000
15Tobias BjornfotSenators (OTT)D17022-55518116250%1125715.140000200002000%000000.1600010000
16Wyatt BongiovanniSenators (OTT)C17011-460199171190%128016.48011318000000037.04%2700000.0700000000
17Hayden HodgsonSenators (OTT)RW8000000000000%010.170000000000000%00000000000000
18Jake LeschyshynSenators (OTT)C/LW17000000001000%0150.880000000011000100.00%10000000000000
19Ville OttavainenSenators (OTT)D8000000000000%020.340000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne2973867105-12111153713594451133058.54%136504817.0059146138112342907348.36%131100100.4205120988
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
1Hunter ShepardSenators (OTT)177910.8942.7099900454260000.8005170000
2Kevin MandoleseSenators (OTT)10001.000029000500000017000
Statistiques d’équipe totales ou en moyenne187910.8962.631028004543100051717000


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Adam SykoraSenators (OTT)C/LW222004-09-07SVKNo193 Lbs5 ft11NoNoFantasy DraftNoNo22025-07-04FalseFalsePro & Farm806,666$0$0$No806,666$--------806,666$--------No--------Lien / Lien NHL
Axel Sandin-PellikkaSenators (OTT)D212005-03-11SWEYes186 Lbs6 ft0NoNoDraftNoNo32026-05-26FalseFalsePro & Farm918,333$0$0$No918,333$918,333$-------918,333$918,333$-------NoNo-------Lien
Bo GroulxSenators (OTT)C262000-02-06CANNo202 Lbs6 ft2NoNoTrade2026-06-21NoNo32026-06-19FalseFalsePro & Farm850,000$0$0$No850,000$850,000$-------850,000$850,000$-------NoNo-------Lien / Lien NHL
Cameron CrottySenators (OTT)D271999-05-05CANNo213 Lbs6 ft3NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Chris WagnerSenators (OTT)C351991-05-27USANo192 Lbs6 ft0NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
David GoyetteSenators (OTT)C222004-03-27CANNo172 Lbs5 ft10NoNoFantasy DraftNoNo22025-07-06FalseFalsePro & Farm891,666$0$0$No891,666$--------891,666$--------No--------Lien / Lien NHL
Dennis GilbertSenators (OTT)D291996-10-30USANo216 Lbs6 ft2NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Drew HellesonSenators (OTT)D252001-03-26USANo208 Lbs6 ft3NoNoFantasy DraftNoNo22026-06-26FalseFalsePro & Farm1,100,000$0$0$No1,100,000$--------1,100,000$--------No--------Lien / Lien NHL
Easton CowanSenators (OTT)RW212005-05-20CANYes190 Lbs6 ft0NoNoDraftNoNo32026-05-26FalseFalsePro & Farm873,500$0$0$No873,500$873,500$-------873,500$873,500$-------NoNo-------Lien
Fabian WagnerSenators (OTT)LW222004-05-07SWENo170 Lbs5 ft10NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Felix Unger SorumSenators (OTT)RW212005-09-14SWENo190 Lbs6 ft0NoNoFantasy DraftNoNo32025-07-06FalseFalsePro & Farm831,667$0$0$No831,667$831,667$-------831,667$831,667$-------NoNo-------Lien / Lien NHL
Hayden HodgsonSenators (OTT)RW301996-03-02CANNo226 Lbs6 ft2NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Hunter ShepardSenators (OTT)G301995-11-07USANo225 Lbs5 ft11NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Isaiah SavilleSenators (OTT)G262000-09-21USANo193 Lbs6 ft1YesNoAssign ManuallyNoNo32026-06-19FalseFalsePro & Farm1,999,999$0$0$No1,999,999$1,999,999$-------1,999,999$1,999,999$-------NoNo-------Lien
Ivan RyabkinSenators (OTT)C192007-04-25RUSYes185 Lbs5 ft11NoNoDraftNoNo32026-05-26FalseFalsePro & Farm952,222$0$0$No952,222$952,222$-------952,222$952,222$-------NoNo-------Lien
Jake LeschyshynSenators (OTT)C/LW271999-03-10CANNo198 Lbs5 ft11YesNoFantasy DraftNoNo32026-06-26FalseFalsePro & Farm775,000$0$0$No775,000$775,000$-------775,000$775,000$-------NoNo-------Lien / Lien NHL
Justin ErtelSenators (OTT)LW232003-05-27CANNo192 Lbs6 ft2NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Keean WashkurakSenators (OTT)C252001-08-16CANNo184 Lbs5 ft10NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Kevin MandoleseSenators (OTT)G262000-08-22CANNo180 Lbs6 ft4YesNoAssign ManuallyNoNo32026-06-19FalseFalsePro & Farm1,999,999$0$0$No1,999,999$1,999,999$-------1,999,999$1,999,999$-------NoNo-------Lien / Lien NHL
Michael BuchingerSenators (OTT)D222004-04-25CANNo178 Lbs5 ft11NoNoFantasy DraftNoNo22025-07-08FalseFalsePro & Farm838,333$0$0$No838,333$--------838,333$--------No--------Lien / Lien NHL
Oliver BonkSenators (OTT)D212005-01-09CANYes180 Lbs6 ft2NoNoDraftNoNo32026-05-26FalseFalsePro & Farm886,666$0$0$No886,666$886,666$-------886,666$886,666$-------NoNo-------Lien
Owen SillingerSenators (OTT)C291997-09-23CANNo182 Lbs5 ft10NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Philippe DaoustSenators (OTT)C252001-05-11CANNo151 Lbs6 ft0NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Scott HarringtonSenators (OTT)D331993-03-10CANNo204 Lbs6 ft2NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Tobias BjornfotSenators (OTT)D252001-04-06SWENo200 Lbs6 ft0NoNoFantasy DraftNoNo22026-06-26FalseFalsePro & Farm775,000$0$0$No775,000$--------775,000$--------No--------Lien / Lien NHL
Tyson HindsSenators (OTT)D232003-03-12CANNo201 Lbs6 ft3NoNoFantasy DraftNoNo12025-07-08FalseFalsePro & Farm829,444$0$0$No---------------------------Lien / Lien NHL
Viktor NeuchevSenators (OTT)LW/RW222003-10-25RUSNo165 Lbs6 ft2NoNoFantasy DraftNoNo12025-07-04FalseFalsePro & Farm870,000$0$0$No---------------------------Lien / Lien NHL
Ville OttavainenSenators (OTT)D242002-08-12FINNo210 Lbs6 ft5NoNoFantasy DraftNoNo12025-07-04FalseFalsePro & Farm867,500$0$0$No---------------------------Lien / Lien NHL
Wyatt BongiovanniSenators (OTT)C271999-07-24USANo194 Lbs6 ft0NoNoAssign ManuallyNoNo22026-01-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2925.10192 Lbs6 ft12.21919,517$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Philippe DaoustOwen SillingerEaston Cowan40122
2Adam SykoraBo GroulxFelix Unger Sorum30122
3Viktor NeuchevChris WagnerWyatt Bongiovanni20122
4Easton CowanOwen SillingerBo Groulx10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Axel Sandin-PellikkaOliver Bonk40122
2Dennis GilbertCameron Crotty30122
3Tobias BjornfotDrew Helleson20122
4Axel Sandin-PellikkaOliver Bonk10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Wyatt BongiovanniChris WagnerEaston Cowan60122
2Adam SykoraBo GroulxFelix Unger Sorum40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Axel Sandin-PellikkaOliver Bonk60122
2Dennis GilbertCameron Crotty40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Chris WagnerBo Groulx60122
2Adam SykoraEaston Cowan40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Axel Sandin-PellikkaOliver Bonk60122
2Dennis GilbertCameron Crotty40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Chris Wagner60122Axel Sandin-PellikkaOliver Bonk60122
2Bo Groulx40122Dennis GilbertCameron Crotty40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Chris WagnerBo Groulx60122
2Philippe DaoustEaston Cowan40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Axel Sandin-PellikkaOliver Bonk60122
2Dennis GilbertCameron Crotty40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Chris WagnerBo GroulxEaston CowanAxel Sandin-PellikkaOliver Bonk
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Chris WagnerBo GroulxEaston CowanAxel Sandin-PellikkaOliver Bonk
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Wyatt Bongiovanni, Philippe Daoust, Chris WagnerWyatt Bongiovanni, Philippe DaoustChris Wagner
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Oliver Bonk, Axel Sandin-Pellikka, Dennis GilbertAxel Sandin-PellikkaOliver Bonk, Dennis Gilbert
Tirs de pénalité
Adam Sykora, Bo Groulx, Felix Unger Sorum, Easton Cowan, Chris Wagner
Gardien
#1 : Hunter Shepard, #2 : Kevin Mandolese
Lignes d’attaque personnalisées en prolongation
Viktor Neuchev, Bo Groulx, Hayden Hodgson, Easton Cowan, Chris Wagner, Adam Sykora, Owen Sillinger, Felix Unger Sorum, Wyatt Bongiovanni, Philippe Daoust
Lignes de défense personnalisées en prolongation
Axel Sandin-Pellikka, Oliver Bonk, Dennis Gilbert, Cameron Crotty, Drew Helleson


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
1Admirals20101000440000000000002010100044020.5004610001112123471681511171441211245500.00%6433.33%024453945.27%26051550.49%13024253.72%401272403125226111
2Barracuda10001000321100010003210000000000021.0003690011121233116815111714168218500.00%10100.00%024453945.27%26051550.49%13024253.72%401272403125226111
3Bears1010000015-41010000015-40000000000000.0001230011121232216815111714341481911100.00%4175.00%024453945.27%26051550.49%13024253.72%401272403125226111
4Bruins10001000321100010003210000000000021.0003470011121232716815111714289827200.00%4175.00%024453945.27%26051550.49%13024253.72%401272403125226111
5Checkers2110000034-1110000003121010000003-320.500369001112123401681511171446113143100.00%40100.00%024453945.27%26051550.49%13024253.72%401272403125226111
6Condors2020000035-2000000000002020000035-200.000358001112123471681511171448131244200.00%6183.33%024453945.27%26051550.49%13024253.72%401272403125226111
7Crunch32100000981000000000003210000098140.667917260011121239116815111714863214729111.11%6183.33%124453945.27%26051550.49%13024253.72%401272403125226111
8Marlies1000000134-11000000134-10000000000010.5003470011121233816815111714285223300.00%000%024453945.27%26051550.49%13024253.72%401272403125226111
9Rocket1010000023-11010000023-10000000000000.00024600111212320168151117142634225120.00%20100.00%024453945.27%26051550.49%13024253.72%401272403125226111
10Wranglers3120000079-22020000058-31100000021120.333713200011121238216815111714782018589222.22%9366.67%024453945.27%26051550.49%13024253.72%401272403125226111
Total1749030013846-8814020012025-5935010001821-3150.44138671050011121234451681511171443113611137142511.90%421173.81%124453945.27%26051550.49%13024253.72%401272403125226111
_Since Last GM Reset1749030013846-8814020012025-5935010001821-3150.44138671050011121234451681511171443113611137142511.90%421173.81%124453945.27%26051550.49%13024253.72%401272403125226111
_Vs Conference934010012126-5512010011215-342200000911-290.50021375800111212323816815111714248746720621314.29%20385.00%124453945.27%26051550.49%13024253.72%401272403125226111
_Vs Division833010012021-1411010011110142200000911-290.56320355500111212321616815111714214605918720210.00%16287.50%124453945.27%26051550.49%13024253.72%401272403125226111

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1715L2386710544543113611137100
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
174930013846
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
81420012025
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
93510001821
Derniers 10 matchs
WLOTWOTL SOWSOL
550000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
42511.90%421173.81%1
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
168151117141112123
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
24453945.27%26051550.49%13024253.72%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
401272403125226111


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
1 - 2026-09-299Senators1Crunch3LSommaire du match
2 - 2026-09-3017Senators1Condors2LSommaire du match
4 - 2026-10-0232Wranglers4Senators2LSommaire du match
7 - 2026-10-0544Bears5Senators1LSommaire du match
9 - 2026-10-0763Senators3Crunch2WSommaire du match
11 - 2026-10-0979Marlies4Senators3LXXSommaire du match
13 - 2026-10-1190Bruins2Senators3WXSommaire du match
14 - 2026-10-12103Senators2Admirals1WXSommaire du match
16 - 2026-10-14117Checkers1Senators3WSommaire du match
17 - 2026-10-15129Senators2Wranglers1WSommaire du match
19 - 2026-10-17145Senators2Condors3LSommaire du match
20 - 2026-10-18153Senators5Crunch3WSommaire du match
22 - 2026-10-20168Rocket3Senators2LSommaire du match
23 - 2026-10-21179Senators2Admirals3LSommaire du match
25 - 2026-10-23191Barracuda2Senators3WXSommaire du match
27 - 2026-10-25206Senators0Checkers3LSommaire du match
29 - 2026-10-27224Wranglers4Senators3LSommaire du match
31 - 2026-10-29236Senators-Canucks-
33 - 2026-10-31248Checkers-Senators-
35 - 2026-11-02263Senators-Wranglers-
37 - 2026-11-04274Bruins-Senators-
39 - 2026-11-06289Condors-Senators-
41 - 2026-11-08306Senators-Crunch-
43 - 2026-11-10319Monsters-Senators-
45 - 2026-11-12333Senators-Bears-
47 - 2026-11-14350IceHogs-Senators-
49 - 2026-11-16362Senators-IceHogs-
51 - 2026-11-18369Admirals-Senators-
63 - 2026-11-30392Senators-Admirals-
65 - 2026-12-02410Wolf Pack-Senators-
67 - 2026-12-04427Senators-Islanders-
68 - 2026-12-05431Bears-Senators-
70 - 2026-12-07448Senators-Bruins-
71 - 2026-12-08460Senators-Comets-
73 - 2026-12-10474Comets-Senators-
76 - 2026-12-13498Phantoms-Senators-
77 - 2026-12-14500Barracuda-Senators-
79 - 2026-12-16522Senators-Monsters-
81 - 2026-12-18538Marlies-Senators-
83 - 2026-12-20556Senators-Wolf Pack-
94 - 2026-12-31562Senators-Penguins-
96 - 2027-01-02573Eagles-Senators-
98 - 2027-01-04591Senators-Wild-
100 - 2027-01-06604Senators-Eagles-
101 - 2027-01-07614Senators-Gulls-
103 - 2027-01-09628Penguins-Senators-
104 - 2027-01-10640Thunderbirds-Senators-
106 - 2027-01-12655Senators-Bruins-
108 - 2027-01-14674Wranglers-Senators-
109 - 2027-01-15683Senators-Reign-
111 - 2027-01-17694Silver Knights-Senators-
114 - 2027-01-20712Griffins-Senators-
117 - 2027-01-23732Rocket-Senators-
118 - 2027-01-24740Senators-Barracuda-
121 - 2027-01-27764Senators-Checkers-
123 - 2027-01-29775Condors-Senators-
125 - 2027-01-31793Rocket-Senators-
126 - 2027-02-01803Senators-Griffins-
128 - 2027-02-03817Senators-Phantoms-
130 - 2027-02-05831Gulls-Senators-
131 - 2027-02-06840Senators-Griffins-
133 - 2027-02-08855Gulls-Senators-
134 - 2027-02-09864Senators-Stars-
136 - 2027-02-11884Senators-Condors-
138 - 2027-02-13899Moose-Senators-
139 - 2027-02-14910Senators-Marlies-
141 - 2027-02-16916Moose-Senators-
142 - 2027-02-17930Senators-Thunderbirds-
145 - 2027-02-20949Griffins-Senators-
146 - 2027-02-21959Senators-Moose-
148 - 2027-02-23970Canucks-Senators-
149 - 2027-02-24986Senators-Silver Knights-
152 - 2027-02-271004Senators-Marlies-
153 - 2027-02-281015Reign-Senators-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
155 - 2027-03-021029Senators-Rocket-
156 - 2027-03-031030Crunch-Senators-
158 - 2027-03-051053Senators-Rocket-
159 - 2027-03-061058Islanders-Senators-
163 - 2027-03-101086Senators-Phantoms-
164 - 2027-03-111093Wild-Senators-
167 - 2027-03-141113Stars-Senators-
171 - 2027-03-181134Crunch-Senators-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5030
Assistance9,2723,465
Assistance PCT57.95%43.31%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
33 1592 - 53.07% 67,397$539,174$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
595,290$ 2,666,600$ 2,666,600$ 850,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 453,625$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
2,224,093$ 145 20,210$ 2,930,450$




Senators Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Senators Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Senators Statistiques de l'Équipe de Carrière

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

Senators Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Senators Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA