Senators

GP: 8 | W: 4 | L: 3 | OTL: 1 | P: 9
GF: 24 | GA: 26 | PP%: 20.41% | PK%: 83.33%
DG: Farlou Ferland | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #95 vs Marlies
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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
1Alexander Volkov (R)XX100.00757183647181866350625867555555655000
2Filip ChlapikX100.00884589777252826239605959535757645000
3Joel Farabee (R)X100.00678179846367646734706863534949695000
4Jack RoslovicXX100.00714394796968917049697056256263705000
5Marko DanoXX100.00687551767567715650574763455858575000
6Michael McLeodX100.00814489797056855974635572254747645000
7Kevin RooneyX100.00786887687359816073605887255656665000
8Ryan DzingelXX100.00676286827167887535766463256465695000
9Matthew PecaXXX100.00764399826156626077625575255151655000
10Tyson JostXX100.00734389856963907251676267256162685000
11Michael Dal ColleXX100.00804492667461756056605862255556635000
12Christian JarosX100.00764486637655725325574765255454595000
13Christian WolaninX100.00727078797055594525284362415757515000
14Jake DotchinX100.00707949657956594825394061385656515000
15Dante Fabbro (R)X100.00714283866877706325484970255151614500
16Carl DahlstromX100.00614387618665586125464773755959575000
Rayé
1Andreas EnglundX100.00899585747455765725504763635757595000
MOYENNE D'ÉQUIPE100.0074588375726275614357556638565662500
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
Rayé
MOYENNE D'ÉQUIPE0.000000000000000000
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Scott Gomez59655659595586USA423850,000$


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
1Carl DahlstromSenators (OTT)D83692807121131427.27%512315.4613482700002000.00%000001.4500000110
2Michael McLeodSenators (OTT)C853818013252442220.83%314918.660224131013201064.41%11800001.0700000011
3Filip ChlapikSenators (OTT)C8257-3001314275147.41%115419.3403311330000160049.25%13400000.9100000000
4Joel FarabeeSenators (OTT)LW8347060121627101111.11%416420.621348380000272055.56%900000.8501000011
5Jack RoslovicSenators (OTT)C/RW84371606191941321.05%217421.812243371012270246.85%22200000.8001000200
6Marko DanoSenators (OTT)LW/RW8347-5409151882316.67%015018.76224536000050060.00%1000000.9300000002
7Dante FabbroSenators (OTT)D6325-460146133823.08%311018.3831483100001100.00%000000.9100000110
8Michael Dal ColleSenators (OTT)LW/RW80331120158116120.00%314618.260004360221110060.00%1500000.4100000001
9Christian WolaninSenators (OTT)D8011020452130.00%08110.170001400000000.00%000000.2500000000
10Jake DotchinSenators (OTT)D8000080931050.00%4779.720000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne78233154-76001021231534412515.03%25133217.09916255225822461124252.36%50800000.8102000445
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
Stats d'équipe Total ou en Moyenne0.0000.0000.000


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 Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Alexander VolkovSenators (OTT)LW/RW221997-08-02Yes191 Lbs6 ft1NoNoNo3Pro & Farm925,000$828,024$925,000$828,024$0$0$No925,000$925,000$
Andreas EnglundSenators (OTT)D241996-01-21No189 Lbs6 ft3NoNoNo4Pro & Farm700,000$626,613$700,000$626,613$0$0$No700,000$700,000$700,000$Lien
Carl DahlstromSenators (OTT)D251995-01-28No231 Lbs6 ft4NoNoNo1Pro & Farm925,000$828,024$925,000$828,024$0$0$NoLien
Christian JarosSenators (OTT)D241996-04-02No201 Lbs6 ft3NoNoNo2Pro & Farm755,000$675,847$450,000$402,823$0$0$No755,000$Lien
Christian WolaninSenators (OTT)D251995-03-17No185 Lbs6 ft2NoNoNo2Pro & Farm925,000$828,024$450,000$402,823$0$0$No925,000$Lien
Dante FabbroSenators (OTT)D221998-06-20Yes189 Lbs6 ft0NoNoNo3Pro & Farm1,491,666$1,335,282$1,491,666$1,335,282$0$0$No1,491,666$1,491,666$
Filip ChlapikSenators (OTT)C231997-06-03No196 Lbs6 ft1NoNoNo1Pro & Farm925,000$828,024$925,000$828,024$0$0$NoLien
Jack RoslovicSenators (OTT)C/RW231997-01-28No187 Lbs6 ft1NoNoNo1Pro & Farm900,000$805,645$900,000$805,645$0$0$NoLien
Jake DotchinSenators (OTT)D261994-03-24No210 Lbs6 ft3NoNoNo4Pro & Farm700,000$626,613$700,000$626,613$0$0$No700,000$700,000$700,000$Lien
Joel FarabeeSenators (OTT)LW202000-02-24Yes164 Lbs6 ft0NoNoNo3Pro & Farm1,425,000$1,275,605$1,425,000$1,275,605$0$0$No1,425,000$1,425,000$
Kevin RooneySenators (OTT)C271993-05-21No190 Lbs6 ft2NoNoNo3Pro & Farm700,000$626,613$700,000$626,613$0$0$No700,000$700,000$Lien
Marko DanoSenators (OTT)LW/RW251994-11-30No212 Lbs5 ft11NoNoNo2Pro & Farm925,000$828,024$925,000$828,024$0$0$No925,000$Lien
Matthew PecaSenators (OTT)C/LW/RW271993-04-27No178 Lbs5 ft8NoNoNo3Pro & Farm1,300,000$1,163,710$1,300,000$1,163,710$0$0$No1,300,000$1,300,000$Lien
Michael Dal ColleSenators (OTT)LW/RW241996-06-19No198 Lbs6 ft3NoNoNo2Pro & Farm700,000$626,613$700,000$626,613$0$0$No700,000$Lien
Michael McLeodSenators (OTT)C221998-02-03No187 Lbs6 ft2NoNoNo2Pro & Farm1,363,333$1,220,403$450,000$402,823$0$0$No1,363,333$Lien
Ryan DzingelSenators (OTT)LW/RW281992-03-09No190 Lbs6 ft0NoNoNo2Pro & Farm1,800,000$1,611,290$1,800,000$1,611,290$0$0$No1,800,000$Lien
Tyson JostSenators (OTT)C/LW221998-03-14No191 Lbs5 ft11NoNoNo4Pro & Farm1,673,333$1,497,903$1,673,333$1,497,903$0$0$No1,673,333$1,673,333$1,673,333$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1724.06193 Lbs6 ft12.471,066,667$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Joel FarabeeJack RoslovicMichael Dal Colle35122
2Marko DanoFilip Chlapik30122
3Michael McLeod25122
4Joel FarabeeJack RoslovicFilip Chlapik10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dante Fabbro35122
2Carl Dahlstrom30122
3Christian WolaninJake Dotchin25122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Joel FarabeeJack RoslovicMichael Dal Colle60122
2Marko DanoFilip Chlapik40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dante Fabbro60122
2Carl Dahlstrom40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Jack RoslovicJoel Farabee60122
2Filip ChlapikMichael McLeod40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Dante FabbroCarl Dahlstrom40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Jack Roslovic6012260122
2Joel Farabee40122Dante FabbroCarl Dahlstrom40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Jack RoslovicJoel Farabee60122
2Filip ChlapikMichael McLeod40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Dante FabbroCarl Dahlstrom40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Joel FarabeeJack RoslovicMichael Dal Colle
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Joel FarabeeJack RoslovicMichael Dal Colle
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Dal Colle, Marko Dano, Michael McLeodMichael Dal Colle, Marko DanoMichael McLeod
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Christian Wolanin, Jake Dotchin, Christian WolaninJake Dotchin,
Tirs de Pénalité
Jack Roslovic, Joel Farabee, Filip Chlapik, Michael McLeod, Michael Dal Colle
Gardien
#1 : , #2 :


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
1Griffins311000011014-4210000018801010000026-430.50010172700126517366525297623305520525.00%14378.57%111221651.85%10119053.16%6212450.00%196140193579648
2Marlies21100000431110000003121010000012-120.50047110012651556652529337163012216.67%8187.50%011221651.85%10119053.16%6212450.00%196140193579648
3Rocket311010001091110000004222010100067-140.66710132300126514966525294817305517317.65%14285.71%111221651.85%10119053.16%6212450.00%196140193579648
Total833010012426-2430000011511440301000915-690.563243761001265117766525291574776140491020.41%36683.33%211221651.85%10119053.16%6212450.00%196140193579648
_Since Last GM Reset833010012426-2430000011511440301000915-690.563243761001265117766525291574776140491020.41%36683.33%211221651.85%10119053.16%6212450.00%196140193579648
_Vs Conference5220100014122220000007343020100079-260.600142034001265110466525298124468529517.24%22386.36%111221651.85%10119053.16%6212450.00%196140193579648
_Vs Division822010002426-2420000001511440201000915-660.375243761001265117766525291574776140491020.41%36683.33%211221651.85%10119053.16%6212450.00%196140193579648

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
89W1243761177157477614000
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
83310012426
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
43000011511
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4031000915
Derniers 10 Matchs
WLOTWOTL SOWSOL
430001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
491020.41%36683.33%2
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
665252912651
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
11221651.85%10119053.16%6212450.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
196140193579648


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
1 - 2020-09-278Senators2Griffins6LSommaire du Match
2 - 2020-09-2816Rocket2Senators4WSommaire du Match
4 - 2020-09-3024Senators3Rocket5LSommaire du Match
5 - 2020-10-0138Griffins4Senators3LXXSommaire du Match
6 - 2020-10-0251Marlies1Senators3WSommaire du Match
8 - 2020-10-0458Senators3Rocket2WXSommaire du Match
10 - 2020-10-0671Senators1Marlies2LSommaire du Match
12 - 2020-10-0884Griffins4Senators5WSommaire du Match
14 - 2020-10-1095Marlies-Senators-
16 - 2020-10-12105Senators-Griffins-
18 - 2020-10-14112Rocket-Senators-
21 - 2020-10-17133Crunch-Senators-
22 - 2020-10-18136Senators-Bruins-
23 - 2020-10-19152Senators-Crunch-
24 - 2020-10-20157Bruins-Senators-
26 - 2020-10-22177Sound Tigers-Senators-
27 - 2020-10-23181Senators-Wolf Pack-
28 - 2020-10-24194Senators-Rocket-
31 - 2020-10-27206Senators-Phantoms-
32 - 2020-10-28215IceHogs-Senators-
34 - 2020-10-30227Penguins-Senators-
36 - 2020-11-01231Senators-Stars-
38 - 2020-11-03245Soldiers-Senators-
40 - 2020-11-05258Senators-Monsters-
43 - 2020-11-08272Rocket-Senators-
44 - 2020-11-09281Senators-Bruins-
45 - 2020-11-10289Senators-Crunch-
46 - 2020-11-11301Phantoms-Senators-
48 - 2020-11-13312Senators-Crunch-
49 - 2020-11-14321Moose-Senators-
50 - 2020-11-15333Senators-Griffins-
51 - 2020-11-16341Senators-Flames-
52 - 2020-11-17350Griffins-Senators-
53 - 2020-11-18357Senators-Bruins-
55 - 2020-11-20374Marlies-Senators-
56 - 2020-11-21388Bruins-Senators-
58 - 2020-11-23401Admirals-Senators-
59 - 2020-11-24410Senators-Admirals-
60 - 2020-11-25420Senators-Wolves-
61 - 2020-11-26428Senators-IceHogs-
63 - 2020-11-28437Senators-Sharks-
64 - 2020-11-29444Bruins-Senators-
66 - 2020-12-01460Penguins-Senators-
67 - 2020-12-02471Senators-Monarchs-
68 - 2020-12-03480Crunch-Senators-
70 - 2020-12-05491Senators-Marlies-
71 - 2020-12-06502Rampage-Senators-
72 - 2020-12-07515Senators-Penguins-
74 - 2020-12-09521Senators-Condors-
75 - 2020-12-10532Bruins-Senators-
77 - 2020-12-12547Marlies-Senators-
78 - 2020-12-13557Senators-Rocket-
79 - 2020-12-14569Crunch-Senators-
80 - 2020-12-15576Senators-Monsters-
82 - 2020-12-17589Monsters-Senators-
85 - 2020-12-20604Senators-Sound Tigers-
86 - 2020-12-21612Moose-Senators-
87 - 2020-12-22623Senators-Soldiers-
88 - 2020-12-23635Senators-Moose-
90 - 2020-12-25643Rocket-Senators-
92 - 2020-12-27658Griffins-Senators-
93 - 2020-12-28667Senators-Penguins-
94 - 2020-12-29674Senators-Crunch-
95 - 2020-12-30682Sound Tigers-Senators-
96 - 2020-12-31700Flames-Senators-
97 - 2021-01-01711Senators-Griffins-
99 - 2021-01-03722Stars-Senators-
100 - 2021-01-04729Senators-Griffins-
102 - 2021-01-06744Monarchs-Senators-
104 - 2021-01-08760Senators-Bruins-
105 - 2021-01-09769Phantoms-Senators-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10784Condors-Senators-
108 - 2021-01-12798Wolf Pack-Senators-
110 - 2021-01-14809Senators-Rampage-
111 - 2021-01-15816Senators-Wolf Pack-
112 - 2021-01-16829Rampage-Senators-
114 - 2021-01-18844Wolves-Senators-
117 - 2021-01-21863Sharks-Senators-
118 - 2021-01-22870Senators-Marlies-
119 - 2021-01-23878Senators-Stars-
120 - 2021-01-24887Senators-Marlies-
122 - 2021-01-26896Crunch-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
37 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
275,608$ 1,813,333$ 1,644,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 186,503$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 111 21,478$ 2,384,058$




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
2020833010012426-2430000011511440301000915-69243761001265117766525291574776140491020.41%36683.33%211221651.85%10119053.16%6212450.00%196140193579648
Total Saison Régulière833010012426-2430000011511440301000915-69243761001265117766525291574776140491020.41%36683.33%211221651.85%10119053.16%6212450.00%196140193579648