Senators

GP: 5 | W: 2 | L: 2 | OTL: 1 | P: 5
GF: 7 | GA: 12 | PP%: 8.70% | PK%: 70.00%
DG: Marc-André Bilodeau Lamontagne | Morale : 48 | Moyenne d'Équipe : 61
Prochain matchs #86 vs Americans
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Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SP
1Adam CracknellX100.007036915985786658625958605484743949610
2A.J. GreerX100.006540806185766860615960615565637549610
3Matt ReadXX100.005636905968827058545759625682733949600
4Justin BaileyX100.006536905989766858555756605467646949600
5Boris Katchouk (R)X100.006538845880949556525354575561637749600
6Glenn Gawdin (R)X100.006139825976928958666054575663626349600
7Joshua Ho-SangXX100.005236916069856959626157585365638041590
8Gabriel FontaineX100.006436925678949354585553565263626349590
9Taylor FedunX100.005437896278756961306657665579714449630
10Joakim RyanX100.006443886369735762307056675271664746620
11Cody GoloubefX100.006439836077796659305754594678706149610
12Dakota MermisX100.005536905973817058305753574669755149600
13Jordan SchmaltzX100.005836915978766458306153594771667749600
14Andreas EnglundX100.005940795881847157305453594565637549600
15Tim ErixonX100.006538865480797353305452554875686749600
16Kyle CumiskeyX100.005336915868827657306051544682735249600
Rayé
1Carsen Twarynski (R)X100.006538855680939155585453565463626345590
2Vladislav KamenevX100.006138855779645057735758625865637445580
3Brad Morrison (R)X100.005336925669898355615453575263626345580
4Max McCormickX100.006539825970746658545257565473675045580
5Kole Lind (R)X100.005736905673908455595552545361636445580
6Logan O'ConnorX100.005336925869777156545857595465635345580
7Grayson DowningX100.006242735473756953565451525073675845560
8Matt TaorminaX100.005437895568807454305552534682735245580
9Michael Prapavessis (R)X100.006236925476787253305451544665636238580
MOYENNE D'ÉQUIPE100.00603887587681735747575558517066614759
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
1Pheonix Copley100.00797876867877797877797873774244760
2Chris Driedger100.00777573877675777675777669735149740
Rayé
1Evan Fitzpatrick (R)100.00706664856968706968706961657045680
MOYENNE D'ÉQUIPE100.0075737186747375747375746872544673
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Benoit Groulx71727574797473CAN5151,000,000$


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOS GP 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
1Adam CracknellSenators (Ott)RW5224-2401110157713.33%213026.031123160001141054.55%3300000.6100000001
2Matt ReadSenators (Ott)C/RW5022-200611145100.00%111623.35011316000060061.90%12600000.3400000010
3Joakim RyanSenators (Ott)D50220115766150.00%210921.89011518000015000.00%000000.3700010001
4Jordan SchmaltzSenators (Ott)D5112-1005140425.00%67214.500000200004000.00%100000.5500000001
5Cody GoloubefSenators (Ott)D51121603213067.69%79719.50101520000011000.00%000000.4100000000
6Boris KatchoukSenators (Ott)LW51121209214137.14%012925.960006210001100050.00%800000.3100000010
7Glenn GawdinSenators (Ott)C50221206419490.00%010721.51000120000000056.25%9600000.3700000000
8A.J. GreerSenators (Ott)LW5011-26010462110.00%212925.890112170001140075.00%800000.1500000000
9Dakota MermisSenators (Ott)D51011204361416.67%18817.75000218000011000.00%000000.2300000000
10Justin BaileySenators (Ott)RW51011205613587.69%011723.54000118000061055.56%1800000.1700000010
11Kyle CumiskeySenators (Ott)D5011100212000.00%1387.680000000000000.00%000000.5200000000
12Joshua Ho-SangSenators (Ott)C/RW1000100003000.00%11515.770001300000000.00%000000.0000000000
13Gabriel FontaineSenators (Ott)C5000020156240.00%19418.8900006000070050.00%8000000.0000000000
14Andreas EnglundSenators (Ott)D5000080121010.00%06412.88000010000400100.00%100000.0000000000
15Taylor FedunSenators (Ott)D50000204510070.00%1011422.83000718000117000.00%000000.0000000000
16Tim ErixonSenators (Ott)D5000-220402000.00%45711.590000000004000.00%100000.0000000000
Stats d'équipe Total ou en Moyenne7671320-2495786213428795.22%38148419.542463620200041312056.72%37200000.2700010033
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
1Pheonix CopleySenators (Ott)52210.8802.5927801121000000.000050100
2Chris DriedgerSenators (Ott)10001.0000.0024000100000.000005000
Stats d'équipe Total ou en Moyenne62210.8912.3830201121100000.000055100


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
A.J. GreerSenators (Ott)LW221996-12-14No210 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$NoLien
Adam CracknellSenators (Ott)RW331985-07-15No209 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm500,000$0$0$NoLien
Andreas EnglundSenators (Ott)D231996-01-21No189 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Boris KatchoukSenators (Ott)LW211998-06-18Yes199 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Brad MorrisonSenators (Ott)C221997-01-04Yes171 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Carsen TwarynskiSenators (Ott)LW211997-11-24Yes198 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Chris DriedgerSenators (Ott)G251994-05-18No205 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Cody GoloubefSenators (Ott)D291989-11-30No200 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm500,000$0$0$NoLien
Dakota MermisSenators (Ott)D251994-01-05No195 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Evan FitzpatrickSenators (Ott)G211998-01-28Yes206 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm0$0$NoLien
Gabriel FontaineSenators (Ott)C221997-04-30No201 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Glenn GawdinSenators (Ott)C221997-03-25Yes191 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Grayson DowningSenators (Ott)C271992-04-18No195 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Joakim RyanSenators (Ott)D261993-06-17No185 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Jordan SchmaltzSenators (Ott)D251993-10-08No190 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Joshua Ho-SangSenators (Ott)C/RW231996-01-22No173 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm900,000$0$0$NoLien
Justin BaileySenators (Ott)RW241995-07-01No214 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Kole LindSenators (Ott)RW201998-10-16Yes178 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Kyle CumiskeySenators (Ott)D321986-12-02No180 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm300,000$0$0$NoLien
Logan O'ConnorSenators (Ott)RW221996-08-14No175 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Matt ReadSenators (Ott)C/RW331986-06-14No188 Lbs5 ft10NoNoNo2Sans RestrictionPro & Farm2,150,000$0$0$NoLien
Matt TaorminaSenators (Ott)D321986-10-20No189 Lbs5 ft10NoNoNo1Sans RestrictionPro & Farm500,000$0$0$NoLien
Max McCormickSenators (Ott)LW271992-05-01No188 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Michael PrapavessisSenators (Ott)D281991-06-01Yes193 Lbs6 ft1NoNoNo4Sans RestrictionPro & Farm300,000$0$0$NoLien
Pheonix CopleySenators (Ott)G271992-01-18No200 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm1,000,000$0$0$NoLien
Taylor FedunSenators (Ott)D311988-06-04No201 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Tim ErixonSenators (Ott)D281991-02-24No200 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm500,000$0$0$NoLien
Vladislav KamenevSenators (Ott)C221996-08-12No194 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2825.46193 Lbs6 ft12.21494,643$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1A.J. GreerMatt ReadAdam Cracknell40122
2Boris KatchoukGlenn GawdinJustin Bailey30122
3Adam CracknellGabriel FontaineA.J. Greer20122
4Justin BaileyMatt ReadBoris Katchouk10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Taylor FedunJoakim Ryan40122
2Cody GoloubefDakota Mermis30122
3Jordan SchmaltzTim Erixon20122
4Andreas EnglundKyle Cumiskey10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1A.J. GreerMatt ReadAdam Cracknell60122
2Boris KatchoukGlenn GawdinJustin Bailey40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Taylor FedunJoakim Ryan60122
2Cody GoloubefDakota Mermis40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Adam CracknellA.J. Greer60122
2Matt ReadJustin Bailey40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Taylor FedunJoakim Ryan60122
2Cody GoloubefDakota Mermis40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Adam Cracknell60122Taylor FedunJoakim Ryan60122
2A.J. Greer40122Cody GoloubefDakota Mermis40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Adam CracknellA.J. Greer60122
2Matt ReadJustin Bailey40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Taylor FedunJoakim Ryan60122
2Cody GoloubefDakota Mermis40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
A.J. GreerMatt ReadAdam CracknellTaylor FedunJoakim Ryan
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
A.J. GreerMatt ReadAdam CracknellTaylor FedunJoakim Ryan
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Gabriel Fontaine, Glenn Gawdin, Boris KatchoukGabriel Fontaine, Glenn GawdinBoris Katchouk
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jordan Schmaltz, Tim Erixon, Andreas EnglundJordan SchmaltzTim Erixon, Andreas Englund
Tirs de Pénalité
Adam Cracknell, A.J. Greer, Matt Read, Justin Bailey, Boris Katchouk
Gardien
#1 : Pheonix Copley, #2 : Chris Driedger


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Comets1010000003-3000000000001010000003-300.00000000313016514237123121213300.00%5180.00%09315460.39%7914753.74%396758.21%13295109346032
2Devils11000000101110000001010000000000021.000123013130185142371246418600.00%10100.00%09315460.39%7914753.74%396758.21%13295109346032
3Moose21000100550000000000002100010055030.75051015003130785142371381425388225.00%10370.00%09315460.39%7914753.74%396758.21%13295109346032
Total52200100712-52110000024-23110010058-350.5007132001313013151423711103749782328.70%20670.00%09315460.39%7914753.74%396758.21%13295109346032
5Wolf Pack1010000014-31010000014-30000000000000.00011200313019514237125589600.00%4250.00%09315460.39%7914753.74%396758.21%13295109346032
_Since Last GM Reset52200100712-52110000024-23110010058-350.5007132001313013151423711103749782328.70%20670.00%09315460.39%7914753.74%396758.21%13295109346032
_Vs Conference4210010079-22110000024-22100010055050.6257132001313011551423718725376520210.00%15566.67%09315460.39%7914753.74%396758.21%13295109346032
_Vs Division2000000024-22000000024-20000000000000.000235013130375142371491112271200.00%5260.00%09315460.39%7914753.74%396758.21%13295109346032

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
55L17132013111037497801
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
5220100712
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
211000024
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
311010058
Derniers 10 Matchs
WLOTWOTL SOWSOL
220100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2328.70%20670.00%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
51423713130
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
9315460.39%7914753.74%396758.21%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
13295109346032


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
4 - 2019-09-0512Senators0Comets3LSommaire du Match
10 - 2019-09-1138Senators2Moose1WSommaire du Match
11 - 2019-09-1249Senators3Moose4LXSommaire du Match
15 - 2019-09-1664Devils0Senators1WSommaire du Match
17 - 2019-09-1871Wolf Pack4Senators1LSommaire du Match
18 - 2019-09-1986Americans-Senators-
22 - 2019-09-23105Devils-Senators-
24 - 2019-09-25108Griffins-Senators-
25 - 2019-09-26121Griffins-Senators-
29 - 2019-09-30137Senators-Rocket-
31 - 2019-10-02140Senators-Crunch-
32 - 2019-10-03157Senators-Crunch-
38 - 2019-10-09183Marlies-Senators-
39 - 2019-10-10196Marlies-Senators-
43 - 2019-10-14218Comets-Senators-
45 - 2019-10-16225Marlies-Senators-
46 - 2019-10-17236Sound Tigers-Senators-
49 - 2019-10-20253Senators-Checkers-
50 - 2019-10-21258Senators-Checkers-
53 - 2019-10-24279Senators-Comets-
57 - 2019-10-28305Senators-Rocket-
59 - 2019-10-30309Comets-Senators-
60 - 2019-10-31324Phantoms-Senators-
66 - 2019-11-06351Rocket-Senators-
67 - 2019-11-07365Bruins-Senators-
68 - 2019-11-08378Senators-Marlies-
71 - 2019-11-11387Senators-Rocket-
73 - 2019-11-13394Senators-Phantoms-
74 - 2019-11-14410Senators-Devils-
78 - 2019-11-18430Senators-Americans-
80 - 2019-11-20436Senators-Monsters-
81 - 2019-11-21449Senators-Monsters-
85 - 2019-11-25464Senators-Marlies-
86 - 2019-11-26473Rocket-Senators-
88 - 2019-11-28491Devils-Senators-
92 - 2019-12-02513Senators-Rocket-
94 - 2019-12-04519Checkers-Senators-
95 - 2019-12-05534Checkers-Senators-
99 - 2019-12-09553Monsters-Senators-
101 - 2019-12-11564Senators-Griffins-
102 - 2019-12-12579Senators-Griffins-
106 - 2019-12-16599Senators-Rocket-
108 - 2019-12-18605Senators-Crunch-
109 - 2019-12-19621Senators-Comets-
115 - 2019-12-25656Marlies-Senators-
116 - 2019-12-26674Marlies-Senators-
123 - 2020-01-02705Senators-Devils-
124 - 2020-01-03711Senators-Bears-
126 - 2020-01-05714Senators-Marlies-
129 - 2020-01-08727Senators-Rocket-
130 - 2020-01-09741Rocket-Senators-
131 - 2020-01-10753Senators-Marlies-
134 - 2020-01-13765Crunch-Senators-
136 - 2020-01-15769Monsters-Senators-
137 - 2020-01-16783Monsters-Senators-
139 - 2020-01-18804Rocket-Senators-
143 - 2020-01-22823Senators-Devils-
144 - 2020-01-23834Senators-Americans-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29860Moose-Senators-
151 - 2020-01-30872Moose-Senators-
156 - 2020-02-04896Senators-Monsters-
157 - 2020-02-05898Senators-Monsters-
160 - 2020-02-08931Senators-Marlies-
164 - 2020-02-12947Rocket-Senators-
165 - 2020-02-13959Rocket-Senators-
169 - 2020-02-17979Comets-Senators-
171 - 2020-02-19986Senators-Bruins-
172 - 2020-02-201002Senators-Sound Tigers-
176 - 2020-02-241019Crunch-Senators-
179 - 2020-02-271042Senators-Wolf Pack-
183 - 2020-03-021064Crunch-Senators-
185 - 2020-03-041073Bears-Senators-
186 - 2020-03-051090Monsters-Senators-
190 - 2020-03-091108Marlies-Senators-
193 - 2020-03-121128Senators-Marlies-
194 - 2020-03-131142Americans-Senators-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
36 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
98,764$ 138,500$ 64,020$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 11,132$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 177 5,869$ 1,038,813$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1452200100712-52110000024-23110010058-357132001313013151423711103749782328.70%20670.00%09315460.39%7914753.74%396758.21%13295109346032
Total Saison Régulière52200100712-52110000024-23110010058-357132001313013151423711103749782328.70%20670.00%09315460.39%7914753.74%396758.21%13295109346032