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Senators
GP: 82 | W: 48 | L: 27 | OTL: 7 | P: 103
GF: 285 | GA: 253 | PP%: 24.14% | PK%: 80.97%
DG: Alexandre Roberge | Morale : 40 | Moyenne d’équipe : 62

Centre de jeu
Senators
48-27-7, 103pts
0
2 Comets
43-35-4, 90pts
Team Stats
L3SéquenceL1
25-12-4Fiche domicile23-16-2
23-15-3Fiche domicile20-19-2
3-7-0Derniers 10 matchs6-4-0
3.48Buts par match 3.04
3.09Buts contre par match 2.93
24.14%Pourcentage en avantage numérique21.72%
80.97%Pourcentage en désavantage numérique81.51%
Marlies
44-34-4, 92pts
3
2 Senators
48-27-7, 103pts
Team Stats
W5SéquenceL3
27-14-0Fiche domicile25-12-4
17-20-4Fiche domicile23-15-3
7-3-0Derniers 10 matchs3-7-0
3.12Buts par match 3.48
3.06Buts contre par match 3.09
18.29%Pourcentage en avantage numérique24.14%
80.45%Pourcentage en désavantage numérique80.97%
Meneurs d'équipe
Nils AmanButs
Nils Aman
35
Scott MorrowPasses
Scott Morrow
57
Nils AmanPoints
Nils Aman
86
Glenn GawdinPlus/Moins
Glenn Gawdin
21
Jet GreavesVictoires
Jet Greaves
47
Jet GreavesPourcentage d’arrêts
Jet Greaves
0.907

Statistiques d’équipe
Buts pour
285
3.48 GFG
Tirs pour
2821
34.40 Avg
Pourcentage en avantage numérique
24.1%
70 GF
Début de zone offensive
41.2%
Buts contre
253
3.09 GAA
Tirs contre
2667
32.52 Avg
Pourcentage en désavantage numérique
81.0%%
59 GA
Début de la zone défensive
41.1%
Informations de l'équipe

Directeur généralAlexandre Roberge
EntraîneurNolan Pratt
DivisionAtlantic Division
ConférenceEastern Conference
CapitaineJames Malatesta
Assistant #1
Assistant #2Daylan Kuefler


Informations de l’aréna

Capacité5,000
Assistance4,668
Billets de saison3,750


Informations de la formation

Équipe Pro22
Équipe Mineure19
Limite contact 41 / 70
Espoirs30


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
1Matej BlumelXX100.00663786687572886664626763686567040650263925,000$
2Nils AmanXXX100.00693791667677816474676269646567040650261925,000$
3Glenn GawdinXX100.00783975637686876471626063626870040640291925,000$
4James Malatesta (C)XX100.00754068656881806358616260656364040630232925,000$
5Pavol RegendaXX100.00784272598886845661585762566668040620263925,000$
6Joe SnivelyXX100.00563689636580876266615857616971040620301925,000$
7Chase WheatcroftXX100.00703985577972815665585559566365040600242925,000$
8Adam RaskaX100.00686562576669825654575556536466040590243925,000$
9Daylan Kuefler (A)X100.00705167567985665558545257536365040580242925,000$
10Scott Morrow (R)X100.00704178678286726630686064526365040650233925,000$
11Maveric Lamoureux (R)X100.00794562639284706230646065526163040640223925,000$
12Filip RoosX100.00743985588680845630575258476668040610271925,000$
13Dysin MayoX100.00684366587771835630575559476971040600301925,000$
14Daniel WalcottXX100.00633976587274825759555654587173040600321925,000$
15Christian KyrouX100.00573692586668775730595556476264040590222925,000$
16Chad NychukX100.00664076557665665430535256456466040580251925,000$
Rayé
1Martin FrkXX100.00704173687987726663656764687274040660323925,000$
2Trey TaylorX100.00693795557876605430535052456365040580243925,000$
MOYENNE D’ÉQUIPE100.0069427861777878595060586056656704062
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
1Jet Greaves100.00829187728180828180828164710407002521,499,000$
2Kevin Mandolese100.0071797582706971706971706573040640262925,000$
Rayé
1Gabriel Carriere (R)100.0070757178696870696870696573040630253925,000$
2Vyacheslav Peksa (R)100.0060706680595860595860596369040580243925,000$
MOYENNE D’ÉQUIPE100.007179757870697170697170647204064
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Nolan Pratt65717868757076CAN504500,000$


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
1Nils AmanSenators (OTT)C/LW/RW82355186142401132333178521311.04%37170320.776222861235011102639253.44%209000111.0125000873
2Glenn GawdinSenators (OTT)C/RW82344579212801322342677818412.73%16147217.95915244922910161235251.27%172600011.0723000546
3Scott MorrowSenators (OTT)D701557721248101341271235210812.20%107179825.69101626632050001220230%000000.8000101553
4James MalatestaSenators (OTT)C/LW8226436917400117150298782048.72%13137616.789162559228000053344.76%10500001.0001000352
5Matej BlumelSenators (OTT)LW/RW823136671126086156326791999.51%19158919.381011217523300041726248.68%22800020.8414000533
6Maveric LamoureuxSenators (OTT)D732039594104025098149378913.42%101163022.3310919772150113158420%000000.7200000255
7Artyom LevshunovSenatorsD681344570540107117123446910.57%103164424.1891423742070111165300%000000.6900000544
8Pavol RegendaSenators (OTT)LW/RW7718365485210151861755914210.29%20149919.483131623135000062255.24%10500000.7200002007
9Martin FrkSenators (OTT)LW/RW4312364810320119124180531296.67%17109625.5118931114000111642050.22%45400110.8802000542
10Joe SnivelySenators (OTT)C/LW82212647-116030232215711629.77%22134716.4333616920002260352.55%137200000.7000000342
11Dysin MayoSenators (OTT)D821033434121151836611030539.09%95156419.084913461800001157100%000000.5500201121
12Daniel WalcottSenators (OTT)LW/D82112334154801165578245214.10%94167620.45661236204011220731100.00%200000.4100000024
13Filip RoosSenators (OTT)D826263220775180626330429.52%103166620.32145211620000218200%000000.3800000003
14Chase WheatcroftSenators (OTT)C/LW82101727-181808398184551395.43%18113013.7900015000054254.03%12400000.4801000001
15Christian KyrouSenators (OTT)D67618244200365442202114.29%5294114.06101215000112100%000000.5100000002
16Daylan KueflerSenators (OTT)LW821382161201054096216513.54%116688.1500000000052359.46%3700000.6300000211
17Adam RaskaSenators (OTT)RW7531720-1948101337310128962.97%893912.5300011000000034.67%7500000.4300002000
18Hunter HaightSenatorsC7212517760188884316314.29%86308.75000000000920145.69%62600000.5400000031
19Trey TaylorSenators (OTT)D44178-3260559165106.25%3064614.6900000000057000%000000.2500000000
20Chad NychukSenators (OTT)D5523501803481511113.33%193786.890001700003110100.00%100000.2600000000
21Jackson BlakeSenatorsLW/RW1000100004160%01818.15000240000000100.00%10000000000000
Statistiques d’équipe totales ou en moyenne146529957086910380850218221102966882205710.08%8932541917.35821462286382481145422096502651.43%694600250.68516306444950
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
1Jet GreavesSenators (OTT)82472770.9073.0048400124226110220.58817820841
2Kevin MandoleseSenators (OTT)21000.8972.76870043900000076000
3Gabriel CarriereSenators (OTT)10000.8675.2223002150000003000
Statistiques d’équipe totales ou en moyenne85482770.9073.014951012482665022178279841


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 RaskaSenators (OTT)RW242001-09-25CZENo178 Lbs178 CMNoNoTrade2025-10-20NoNo32025-05-20FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Chad NychukSenators (OTT)D252001-03-06CANNo194 Lbs185 CMNoNoTrade2025-09-02NoNo1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
Chase WheatcroftSenators (OTT)C/LW242002-05-28CANNo192 Lbs188 CMNoNoProspectNoNo22024-05-23FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
Christian KyrouSenators (OTT)D222003-09-16CANNo166 Lbs180 CMNoNoProspectNoNo22024-05-23FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
Daniel WalcottSenators (OTT)LW/D321994-02-19CANNo175 Lbs185 CMNoNoN/AYesYes1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
Daylan KueflerSenators (OTT)LW242002-02-10CANNo195 Lbs188 CMNoNoProspectNoNo22024-05-23FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
Dysin MayoSenators (OTT)D301996-08-17CANNo183 Lbs188 CMNoNoN/AYesYes1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
Filip RoosSenators (OTT)D271999-01-05SWENo190 Lbs193 CMNoNoN/ANoNo1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
Gabriel CarriereSenators (OTT)G252000-11-05CANYes188 Lbs188 CMNoNoProspectNoNo32025-06-01FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Glenn GawdinSenators (OTT)C/RW291997-03-25CANNo195 Lbs185 CMNoNoN/AYesYes1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
James MalatestaSenators (OTT)C/LW232003-05-31CANNo193 Lbs175 CMNoNoProspectNoNo22024-05-23FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
Jet GreavesSenators (OTT)G252001-03-30CANNo190 Lbs183 CMNoNoAssign ManuallyNoNo22024-07-04FalseFalsePro & Farm1,499,000$0$0$No1,499,000$--------1,499,000$--------No--------Lien / Lien NHL
Joe SnivelySenators (OTT)C/LW301996-01-01USANo176 Lbs175 CMNoNoN/AYesYes1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
Kevin MandoleseSenators (OTT)G262000-08-22CANNo180 Lbs193 CMNoNoN/ANoNo22024-05-23FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien / Lien NHL
Martin FrkSenators (OTT)LW/RW321993-10-05CZENo210 Lbs185 CMNoNoWaiverNoYes32025-07-23FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Matej BlumelSenators (OTT)LW/RW262000-05-31CZENo205 Lbs183 CMNoNoN/ANoNo3FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Maveric LamoureuxSenators (OTT)D222004-01-13CANYes196 Lbs198 CMNoNoTrade2026-01-03NoNo32025-06-01FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Nils AmanSenators (OTT)C/LW/RW262000-02-07SWENo179 Lbs188 CMNoNoN/ANoNo1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien / Lien NHL
Pavol RegendaSenators (OTT)LW/RW261999-12-07SVKNo211 Lbs193 CMNoNoN/ANoNo3FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Scott MorrowSenators (OTT)D232002-11-01USAYes210 Lbs188 CMNoNoProspectNoNo32025-06-01FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Trey TaylorSenators (OTT)D242002-02-04CANNo190 Lbs188 CMNoNoTrade2025-10-20NoNo32025-07-23FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Vyacheslav PeksaSenators (OTT)G242002-08-27RUSYes181 Lbs191 CMNoNoProspectNoNo32025-06-01FalseFalsePro & Farm925,000$0$0$No925,000$925,000$-------925,000$925,000$-------NoNo-------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2225.86190 Lbs185 CM2.09951,091$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nils AmanMatej Blumel40122
2James MalatestaGlenn GawdinPavol Regenda30122
3Chase WheatcroftJoe SnivelyAdam Raska20122
4Daylan Kuefler10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
140122
2Filip RoosDaniel Walcott30122
3Dysin Mayo20122
4Chad Nychuk10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nils AmanMatej Blumel60122
2James MalatestaGlenn GawdinPavol Regenda40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Filip RoosDaniel Walcott40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Matej Blumel60122
2Nils AmanGlenn Gawdin40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Filip RoosDaniel Walcott40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
16012260122
2Matej Blumel40122Filip RoosDaniel Walcott40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Matej Blumel60122
2Nils AmanGlenn Gawdin40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Filip RoosDaniel Walcott40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nils AmanMatej Blumel
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nils AmanMatej Blumel
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Joe Snively, Chase Wheatcroft, Joe Snively, Chase Wheatcroft
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dysin Mayo, , Chad NychukDysin Mayo, Chad Nychuk
Tirs de pénalité
, Matej Blumel, Nils Aman, Glenn Gawdin, James Malatesta
Gardien
#1 : Jet Greaves, #2 : Kevin Mandolese


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
1Admirals220000001174110000004221100000075241.00011193000100978475586695698036681622476233.33%9366.67%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
2Americans321000001011-1220000006421010000047-340.667101828001009784710386695698036893026649222.22%12191.67%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
3Barracuda2020000026-41010000013-21010000013-200.0002460010097847778669569803657131657700.00%7357.14%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
4Bears3200010012931000010034-12200000095450.8331222340010097847116866956980361113226731317.69%12191.67%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
5Bruins440000002211112200000015962200000072581.00022426400100978471628669569803611022298921523.81%110100.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
6Canucks220000001147110000006241100000052341.00011182900100978477786695698036671312429222.22%50100.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
7Checkers4210000114104220000009362010000157-250.625142640001009784721186695698036105312397600.00%90100.00%11567302451.82%1463301748.49%657130250.46%1965136119446031046516
8Comets3120000079-2211000007701010000002-220.333714210010097847100866956980369126246711327.27%10370.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
9Condors21001000862110000004311000100043141.0008152300100978476586695698036631712396350.00%6183.33%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
10Crunch3030000048-41010000012-12020000036-300.0004711101009784710186695698036982022821119.09%11190.91%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
11Eagles2110000056-1110000003211010000024-220.500591400100978476386695698036722126516233.33%10190.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
12Firebirds21100000651110000004221010000023-120.50061016001009784764866956980365824234310330.00%70100.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
13Griffins412001001315-2211000009722010010048-430.37513243710100978471198669569803612129348911327.27%15473.33%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
14Gulls21001000642110000002111000100043141.0006121800100978475586695698036792022427457.14%11281.82%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
15Heat2010000146-21000000145-11010000001-110.2504711001009784754866956980366723104514214.29%5260.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
16IceHogs2110000036-3110000003211010000004-420.5003690010097847488669569803669151852400.00%9277.78%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
17Marlies4220000016133211000008622110000087140.500162844001009784717586695698036161374610311436.36%16381.25%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
18Monsters3120000048-41010000002-22110000046-220.333481200100978479186695698036109312361900.00%9277.78%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
19Moose22000000835110000006241100000021141.00081523001009784789866956980365411144510220.00%70100.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
20Penguins32100000121202110000078-11100000054140.66712203200100978479586695698036912641855360.00%18572.22%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
21Phantoms310001101183110000006332000011055050.833111627001009784782866956980361003934957228.57%140100.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
22Reign200001109901000010056-11000001043130.7509142300100978477886695698036631510418225.00%5260.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
23Roadrunners20100001710-31000000145-11010000035-210.2507142100100978475686695698036772124473133.33%12466.67%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
24Rocket431000002015521100000910-122000000115660.750203858001009784713986695698036129404610321838.10%17664.71%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
25Silver Knights211000008801010000036-31100000052320.5008142200100978476686695698036631616554125.00%8275.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
26Sound Tigers30300000512-72020000059-41010000003-300.000581300100978479786695698036903118701119.09%9455.56%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
27Stars22000000743110000004311100000031241.0007111800100978477286695698036551416558112.50%8187.50%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
28Thunderbirds22000000862110000002111100000065141.0008152300100978475986695698036693321529444.44%8275.00%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
29Wild2110000089-11010000035-21100000054120.5008152300100978476586695698036602314377114.29%7185.71%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
30Wolf Pack330000001275110000006332200000064261.000122032011009784791866956980369628247212433.33%12283.33%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
31Wolves330000001266220000008351100000043161.0001220320010097847968669569803612528227014321.43%11190.91%01567302451.82%1463301748.49%657130250.46%1965136119446031046516
Total824427024232852533241251200202157130274119150222112812351030.6282855097942110097847282186695698036266774571419702907024.14%3105980.97%11567302451.82%1463301748.49%657130250.46%1965136119446031046516
_Since Last GM Reset824427024232852533241251200202157130274119150222112812351030.6282855097942110097847282186695698036266774571419702907024.14%3105980.97%11567302451.82%1463301748.49%657130250.46%1965136119446031046516
_Vs Conference50271800311174154202515900100998019251290021175741600.6001743114852110097847177886695698036162645043812201724023.26%1863382.26%11567302451.82%1463301748.49%657130250.46%1965136119446031046516
_Vs Division2614100010199831613940000057411613560010142420300.577991832822010097847101086695698036813209226627902325.56%911583.52%11567302451.82%1463301748.49%657130250.46%1965136119446031046516

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
82103L328550979428212667745714197021
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8244272423285253
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4125120202157130
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4119152221128123
Derniers 10 matchs
WLOTWOTL SOWSOL
370000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2907024.14%3105980.97%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
8669569803610097847
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
1567302451.82%1463301748.49%657130250.46%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1965136119446031046516


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
3 - 2025-09-2811Senators3Crunch4LSommaire du match
5 - 2025-09-3027Senators2Checkers3LXXSommaire du match
7 - 2025-10-0241Admirals2Senators4WSommaire du match
9 - 2025-10-0457Senators4Americans7LSommaire du match
10 - 2025-10-0563Firebirds2Senators4WSommaire du match
12 - 2025-10-0777Sound Tigers6Senators3LSommaire du match
15 - 2025-10-1099Condors3Senators4WSommaire du match
17 - 2025-10-12112Phantoms3Senators6WSommaire du match
19 - 2025-10-14135Senators6Bears3WSommaire du match
21 - 2025-10-16149Bruins3Senators7WSommaire du match
22 - 2025-10-17160Senators0IceHogs4LSommaire du match
24 - 2025-10-19168Heat5Senators4LXXSommaire du match
26 - 2025-10-21187Senators5Rocket3WSommaire du match
31 - 2025-10-26218Senators4Bruins1WSommaire du match
33 - 2025-10-28232Senators1Phantoms2LXSommaire du match
34 - 2025-10-29247Roadrunners5Senators4LXXSommaire du match
36 - 2025-10-31258Stars3Senators4WSommaire du match
38 - 2025-11-02271Bruins6Senators8WSommaire du match
40 - 2025-11-04286Reign6Senators5LXSommaire du match
45 - 2025-11-09329Senators4Gulls3WXSommaire du match
47 - 2025-11-11342Senators1Barracuda3LSommaire du match
49 - 2025-11-13359Senators4Reign3WXXSommaire du match
51 - 2025-11-15373Senators5Silver Knights2WSommaire du match
53 - 2025-11-17382Senators6Thunderbirds5WSommaire du match
55 - 2025-11-19405Senators3Stars1WSommaire du match
57 - 2025-11-21411Senators6Rocket2WSommaire du match
59 - 2025-11-23427Wolf Pack3Senators6WSommaire du match
61 - 2025-11-25445Thunderbirds1Senators2WSommaire du match
64 - 2025-11-28467Comets3Senators4WSommaire du match
66 - 2025-11-30486Senators3Monsters1WSommaire du match
68 - 2025-12-02496Senators5Wild4WSommaire du match
70 - 2025-12-04516Senators2Moose1WSommaire du match
73 - 2025-12-07537Penguins2Senators5WSommaire du match
75 - 2025-12-09551IceHogs2Senators3WSommaire du match
76 - 2025-12-10564Senators3Bruins1WSommaire du match
78 - 2025-12-12578Americans1Senators2WSommaire du match
82 - 2025-12-16590Senators3Marlies4LSommaire du match
84 - 2025-12-18606Monsters2Senators0LSommaire du match
87 - 2025-12-21632Bears4Senators3LXSommaire du match
89 - 2025-12-23650Moose2Senators6WSommaire du match
91 - 2025-12-25664Griffins4Senators8WSommaire du match
93 - 2025-12-27680Senators3Roadrunners5LSommaire du match
94 - 2025-12-28691Senators2Eagles4LSommaire du match
96 - 2025-12-30704Checkers2Senators3WSommaire du match
99 - 2026-01-02725Canucks2Senators6WSommaire du match
100 - 2026-01-03737Senators5Wolf Pack4WSommaire du match
103 - 2026-01-06758Rocket4Senators7WSommaire du match
104 - 2026-01-07768Senators3Griffins4LXSommaire du match
106 - 2026-01-09782Senators1Monsters5LSommaire du match
108 - 2026-01-11798Senators7Admirals5WSommaire du match
110 - 2026-01-13813Wolves2Senators4WSommaire du match
111 - 2026-01-14821Silver Knights6Senators3LSommaire du match
114 - 2026-01-17841Eagles2Senators3WSommaire du match
117 - 2026-01-20866Comets4Senators3LSommaire du match
119 - 2026-01-22877Senators5Penguins4WSommaire du match
120 - 2026-01-23890Senators4Wolves3WSommaire du match
122 - 2026-01-25907Senators4Phantoms3WXXSommaire du match
143 - 2026-02-15920Griffins3Senators1LSommaire du match
145 - 2026-02-17939Senators5Marlies3WSommaire du match
148 - 2026-02-20966Senators4Condors3WXSommaire du match
150 - 2026-02-22981Senators0Heat1LSommaire du match
152 - 2026-02-241000Senators2Firebirds3LSommaire du match
154 - 2026-02-261011Senators5Canucks2WSommaire du match
156 - 2026-02-281025Rocket6Senators2LSommaire du match
159 - 2026-03-031043Gulls1Senators2WSommaire du match
160 - 2026-03-041058Barracuda3Senators1LSommaire du match
163 - 2026-03-071079Senators3Bears2WSommaire du match
164 - 2026-03-081084Sound Tigers3Senators2LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
166 - 2026-03-101106Marlies3Senators6WSommaire du match
168 - 2026-03-121119Senators1Wolf Pack0WSommaire du match
169 - 2026-03-131122Senators1Griffins4LSommaire du match
171 - 2026-03-151138Penguins6Senators2LSommaire du match
173 - 2026-03-171152Senators0Crunch2LSommaire du match
176 - 2026-03-201181Senators3Checkers4LSommaire du match
178 - 2026-03-221191Americans3Senators4WSommaire du match
180 - 2026-03-241208Wild5Senators3LSommaire du match
181 - 2026-03-251225Wolves1Senators4WSommaire du match
183 - 2026-03-271234Crunch2Senators1LSommaire du match
185 - 2026-03-291249Checkers1Senators6WSommaire du match
187 - 2026-03-311262Senators0Sound Tigers3LSommaire du match
188 - 2026-04-011279Senators0Comets2LSommaire du match
191 - 2026-04-041304Marlies3Senators2LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité30002000
Prix des billets2515
Assistance115,20376,184
Assistance PCT93.66%92.91%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 4668 - 93.36% 143,252$5,873,337$5000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,583,275$ 2,092,400$ 2,092,400$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 2,083,224$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 13,432$ 0$




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