BELLEVILLE Senators

GP: 58 | W: 12 | L: 46 | OTL: 0 | P: 24
GF: 108 | GA: 318 | PP%: 0.00% | PK%: 85.71%
DG: Miguel Tousignant | Morale : 90 | Moyenne d'Équipe : 61
Prochain matchs #761 vs Manitoba Moose
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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
1Michael Raffl0X100.007235706774788066646764666566553494690
2Andrew Mangiapane0X100.006335736867707267666567596752514999650
3Alex Formenton0X100.006535765873785458606060645950507499620
4Matt Puempel0X100.005435666978535469506565526653517799610
5Kurtis Gabriel0X100.007488636086566160505757555852506199600
6Michael McLeod (R)0X100.006047666978586068715756535851508596600
7Andrew Poturalski0X100.005089657066505070506464556450504299590
8Mike Vecchione (R)0X100.005089647069505070705959505950504296580
9Sam Anas0XX100.005089707061505070506060506050504282580
10Bogdan Kiselevich (R)0X100.007335796675766666307165716651503692670
11Casey Nelson0X100.006744786374746962306156706554513799640
12Jimmy Schuldt (R)0X100.005035865478875054305965656050554396620
13Josh Mahura (R)0X100.005135736773565867305757555851506495590
14Calle Rosen (R)0X100.005135656975525269305556525650504296580
15Daniel Brickley (R)0X100.005835696384525263305253525350504396570
Rayé
1Nicklas Jensen0X100.005237736981495163305360545860477141590
MOYENNE D'ÉQUIPE100.00595071667562586546606058615351539261
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
1Dylan Ferguson (R)100.00655656786530656666666250585080550
Rayé
MOYENNE D'ÉQUIPE100.0065565678653065666666625058508055
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
mig60606060616199CAN372500,000$


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
1Sam AnasBELLEVILLE Senators (OTW)C/RW5875118632951661203119025424.12%241109518.8900005000008060.06%626000111.57000101101
Stats d'équipe Total ou en Moyenne5875118632951661203119025424.12%241109518.8900005000008060.06%626000111.57000101101
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
1Dylan FergusonBELLEVILLE Senators (OTW)58124600.9305.3533966130343500010.0000585815108
Stats d'équipe Total ou en Moyenne58124600.9305.3533966130343500010.0000585815108


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
Alex FormentonBELLEVILLE Senators (OTW)LW191999-09-13No75 Kg188 CMNoNoNo1Pro & Farm750,000$229,729$750,000$229,729$0$0$NoLien
Andrew MangiapaneBELLEVILLE Senators (OTW)LW231996-04-04No84 Kg178 CMNoNoNo6Pro & Farm1,100,000$336,936$1,100,000$336,936$0$0$No1,100,000$1,100,000$1,100,000$1,100,000$1,100,000$Lien
Andrew PoturalskiBELLEVILLE Senators (OTW)C251994-01-14No82 Kg178 CMNoNoNo1Pro & Farm750,000$229,729$750,000$229,729$0$0$NoLien
Bogdan KiselevichBELLEVILLE Senators (OTW)D291990-02-14Yes92 Kg183 CMNoNoNo4Pro & Farm750,000$229,729$500,000$153,153$0$0$No750,000$750,000$750,000$
Calle RosenBELLEVILLE Senators (OTW)D251994-02-02Yes85 Kg185 CMNoNoNo4Pro & Farm750,000$229,729$500,000$153,153$0$0$No750,000$750,000$750,000$
Casey NelsonBELLEVILLE Senators (OTW)D271992-07-18No84 Kg185 CMNoNoNo1Pro & Farm800,000$245,045$800,000$245,045$0$0$NoLien
Daniel BrickleyBELLEVILLE Senators (OTW)D241995-03-30Yes92 Kg191 CMNoNoNo4Pro & Farm750,000$229,729$500,000$153,153$0$0$No750,000$750,000$750,000$
Dylan FergusonBELLEVILLE Senators (OTW)G201998-09-20Yes86 Kg185 CMNoNoNo1Pro & Farm750,000$229,729$750,000$229,729$0$0$NoLien
Jimmy SchuldtBELLEVILLE Senators (OTW)D241995-05-11Yes93 Kg185 CMNoNoNo4Pro & Farm750,000$229,729$500,000$153,153$0$0$No750,000$750,000$750,000$
Josh MahuraBELLEVILLE Senators (OTW)D211998-05-05Yes87 Kg183 CMNoNoNo4Pro & Farm750,000$229,729$750,000$229,729$0$0$No750,000$750,000$750,000$
Kurtis GabrielBELLEVILLE Senators (OTW)RW261993-04-20No91 Kg193 CMNoNoNo2Pro & Farm750,000$229,729$750,000$229,729$0$0$No750,000$Lien
Matt PuempelBELLEVILLE Senators (OTW)LW261993-01-24No93 Kg185 CMNoNoNo4Pro & Farm750,000$229,729$750,000$229,729$0$0$No750,000$750,000$750,000$Lien
Michael McLeodBELLEVILLE Senators (OTW)C211998-02-03Yes85 Kg188 CMNoNoNo4Pro & Farm750,000$229,729$500,000$153,153$0$0$No750,000$750,000$750,000$
Michael RafflBELLEVILLE Senators (OTW)LW301988-12-01No91 Kg183 CMNoNoNo5Pro & Farm1,600,000$490,090$1,600,000$490,090$0$0$No1,600,000$1,600,000$1,600,000$1,600,000$Lien
Mike VecchioneBELLEVILLE Senators (OTW)C261993-02-25Yes88 Kg178 CMNoNoNo4Pro & Farm750,000$229,729$500,000$153,153$0$0$No750,000$750,000$750,000$
Nicklas JensenBELLEVILLE Senators (OTW)RW261993-03-06No98 Kg191 CMNoNoNo0Pro & Farm0$0$No
Sam AnasBELLEVILLE Senators (OTW)C/RW261993-06-01No74 Kg173 CMNoNoNo1Pro & Farm750,000$229,729$750,000$229,729$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1724.5987 Kg185 CM2.94779,412$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
131122
2Sam Anas26122
3Sam Anas23122
420122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
131122
226122
323122
420122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
155122
2Sam Anas45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
245122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
155122
245122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
245122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
15512255122
24512245122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
155122
245122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
245122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Sam Anas, , Sam Anas
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , ,
Gardien
#1 : , #2 : Dylan Ferguson
Lignes d'Attaque Perso. en Prol.
, , , , , Sam Anas, Sam Anas, , , ,
Lignes de Défense Perso. en Prol.
, , , ,


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
1BRIDGEPORT Sound Tigers2020000019-81010000014-31010000005-500.00011200502830015338331400013434023000.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
2BROOKLYN Wolfpack2200000015213110000006151100000091841.000152944005028300115338331400010922053000.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
3Binghampton Devils40400000623-1720200000315-122020000038-500.00061218005028300913383314000355105262200.00%10100.00%023376130.62%577266421.66%22285925.84%5083282445353525175
4CHICAGO Wolves20200000212-101010000017-61010000015-400.00024600502830013338331400017940013100.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
5COLORADO Eagles1010000017-6000000000001010000017-600.00012300502830043383314000572729100.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
6CORNWALL Aces11000000743110000007430000000000021.000713200050283005533833140004420024000.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
7HERSEY Bears20200000011-111010000008-81010000003-300.0000000050283008338331400017240014100.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
8HOLLYWOOD Oscar220000001631322000000163130000000000041.00016274300502830015533833140009222242100.00%10100.00%023376130.62%577266421.66%22285925.84%5083282445353525175
9IOWA Wild1010000018-7000000000001010000018-700.00012300502830012338331400011434012000.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
10LAVAL Rockets20200000015-151010000007-71010000008-800.0000000050283005338331400017140213400.00%10100.00%023376130.62%577266421.66%22285925.84%5083282445353525175
11LEHIGH VALLEY Phantoms50500000231-2920200000111-1030300000120-1900.000235105028300253383314000354107435500.00%2150.00%023376130.62%577266421.66%22285925.84%5083282445353525175
12MILWAUKEE Admirals1010000015-41010000015-40000000000000.00012300502830043383314000792008100.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
13MONT-LAURIER Sommet20200000111-101010000016-51010000005-500.00012300502830010338331400016842011100.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
14Manitoba Moose30300000022-2220200000016-161010000006-600.00000000502830020338331400030674424200.00%20100.00%023376130.62%577266421.66%22285925.84%5083282445353525175
15Marlies de Toronto220000001596110000008531100000074341.000152742005028300114338331400012130483000.00%20100.00%023376130.62%577266421.66%22285925.84%5083282445353525175
16PROVIDENCE Bruins1010000006-6000000000001010000006-600.00000000502830063383314000692107000.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
17PV Sharapovas60600000240-3840400000233-312020000007-700.000246005028300383383314000488144425700.00%2150.00%023376130.62%577266421.66%22285925.84%5083282445353525175
18ROCKFORD IceHogs1010000004-41010000004-40000000000000.00000000502830003383314000752204200.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
19SAN DIEGO Gulls11000000211000000000001100000021121.0002460050283005933833140004510039000.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
20STOCKTON Flames50500000129-2820200000112-1130300000017-1700.000112005028300233383314000445119029300.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
21Syracruse Crunch2020000007-7000000000002020000007-700.00000000502830011338331400017534012300.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
Total58124600000108318-210297220000064162-98295240000044156-112240.2071081943021150283001069338331400044521207777495100.00%21385.71%023376130.62%577266421.66%22285925.84%5083282445353525175
23UTICA Comets30300000122-2120200000012-1210100000110-900.000123005028300163383314000222762191000.00%000.00%023376130.62%577266421.66%22285925.84%5083282445353525175
24VICTORIAVILLE Tigres30300000127-261010000007-720200000120-1900.00012300502830018338331400028484419400.00%10100.00%023376130.62%577266421.66%22285925.84%5083282445353525175
25WILKIES-BARRIE Penguins44000000331023220000001621422000000178981.00033579001502830025233833140001944047169300.00%9188.89%023376130.62%577266421.66%22285925.84%5083282445353525175
_Since Last GM Reset58124600000108318-210297220000064162-98295240000044156-112240.2071081943021150283001069338331400044521207777495100.00%21385.71%023376130.62%577266421.66%22285925.84%5083282445353525175
_Vs Conference387310000070215-145195140000047109-62192170000023106-83140.1847012319311502830071033833140003019825674643100.00%18383.33%023376130.62%577266421.66%22285925.84%5083282445353525175
_Vs Division19513000005786-29938000002741-141025000003045-15100.2635710215911502830050633833140001318348533561100.00%12283.33%023376130.62%577266421.66%22285925.84%5083282445353525175

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5824L31081943021069445212077774911
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
5812460000108318
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
29722000064162
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
29524000044156
Derniers 10 Matchs
WLOTWOTL SOWSOL
460000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
5100.00%21385.71%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
33833140005028300
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
23376130.62%577266421.66%22285925.84%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
5083282445353525175


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 - 2020-01-1510BELLEVILLE Senators1IOWA Wild8LSommaire du Match
2 - 2020-01-1617BELLEVILLE Senators0PROVIDENCE Bruins6LSommaire du Match
3 - 2020-01-1727PV Sharapovas8BELLEVILLE Senators1LSommaire du Match
4 - 2020-01-1847LEHIGH VALLEY Phantoms5BELLEVILLE Senators1LSommaire du Match
5 - 2020-01-1959PV Sharapovas6BELLEVILLE Senators0LSommaire du Match
7 - 2020-01-2173BELLEVILLE Senators1LEHIGH VALLEY Phantoms3LSommaire du Match
9 - 2020-01-2385WILKIES-BARRIE Penguins2BELLEVILLE Senators7WR3Sommaire du Match
11 - 2020-01-2592BELLEVILLE Senators0STOCKTON Flames8LSommaire du Match
13 - 2020-01-27108BELLEVILLE Senators0Manitoba Moose6LSommaire du Match
15 - 2020-01-29125Binghampton Devils7BELLEVILLE Senators2LSommaire du Match
17 - 2020-01-31140UTICA Comets7BELLEVILLE Senators0LSommaire du Match
19 - 2020-02-02148BELLEVILLE Senators0Syracruse Crunch4LSommaire du Match
21 - 2020-02-04162PV Sharapovas11BELLEVILLE Senators0LSommaire du Match
23 - 2020-02-06186STOCKTON Flames6BELLEVILLE Senators1LSommaire du Match
24 - 2020-02-07195BELLEVILLE Senators1VICTORIAVILLE Tigres14LSommaire du Match
26 - 2020-02-09211HOLLYWOOD Oscar2BELLEVILLE Senators7WSommaire du Match
27 - 2020-02-10222BELLEVILLE Senators7Marlies de Toronto4WSommaire du Match
28 - 2020-02-11236BRIDGEPORT Sound Tigers4BELLEVILLE Senators1LSommaire du Match
29 - 2020-02-12250BELLEVILLE Senators0PV Sharapovas4LSommaire du Match
30 - 2020-02-13259BELLEVILLE Senators0LAVAL Rockets8LSommaire du Match
32 - 2020-02-15271PV Sharapovas8BELLEVILLE Senators1LSommaire du Match
33 - 2020-02-16287BELLEVILLE Senators0HERSEY Bears3LSommaire du Match
34 - 2020-02-17294LEHIGH VALLEY Phantoms6BELLEVILLE Senators0LSommaire du Match
36 - 2020-02-19314HERSEY Bears8BELLEVILLE Senators0LSommaire du Match
37 - 2020-02-20325BELLEVILLE Senators8WILKIES-BARRIE Penguins3WR3Sommaire du Match
38 - 2020-02-21341Marlies de Toronto5BELLEVILLE Senators8WSommaire du Match
39 - 2020-02-22356BELLEVILLE Senators1Binghampton Devils4LSommaire du Match
40 - 2020-02-23362BELLEVILLE Senators1UTICA Comets10LSommaire du Match
42 - 2020-02-25373STOCKTON Flames6BELLEVILLE Senators0LSommaire du Match
43 - 2020-02-26393WILKIES-BARRIE Penguins0BELLEVILLE Senators9WR3Sommaire du Match
44 - 2020-02-27401BELLEVILLE Senators9WILKIES-BARRIE Penguins5WSommaire du Match
45 - 2020-02-28415BELLEVILLE Senators0BRIDGEPORT Sound Tigers5LSommaire du Match
46 - 2020-02-29422BELLEVILLE Senators1COLORADO Eagles7LSommaire du Match
47 - 2020-03-01436HOLLYWOOD Oscar1BELLEVILLE Senators9WSommaire du Match
49 - 2020-03-03452BELLEVILLE Senators0LEHIGH VALLEY Phantoms9LSommaire du Match
50 - 2020-03-04461LAVAL Rockets7BELLEVILLE Senators0LSommaire du Match
52 - 2020-03-06479ROCKFORD IceHogs4BELLEVILLE Senators0LSommaire du Match
53 - 2020-03-07492BELLEVILLE Senators0STOCKTON Flames4LSommaire du Match
54 - 2020-03-08502MILWAUKEE Admirals5BELLEVILLE Senators1LSommaire du Match
56 - 2020-03-10519BELLEVILLE Senators0PV Sharapovas3LSommaire du Match
57 - 2020-03-11531Manitoba Moose7BELLEVILLE Senators0LSommaire du Match
59 - 2020-03-13547BELLEVILLE Senators0LEHIGH VALLEY Phantoms8LSommaire du Match
60 - 2020-03-14552BELLEVILLE Senators0MONT-LAURIER Sommet5LSommaire du Match
61 - 2020-03-15565CHICAGO Wolves7BELLEVILLE Senators1LSommaire du Match
62 - 2020-03-16575BELLEVILLE Senators0STOCKTON Flames5LSommaire du Match
63 - 2020-03-17591Binghampton Devils8BELLEVILLE Senators1LSommaire du Match
64 - 2020-03-18603MONT-LAURIER Sommet6BELLEVILLE Senators1LSommaire du Match
66 - 2020-03-20623BELLEVILLE Senators0Syracruse Crunch3LSommaire du Match
67 - 2020-03-21634CORNWALL Aces4BELLEVILLE Senators7WSommaire du Match
68 - 2020-03-22647BELLEVILLE Senators9BROOKLYN Wolfpack1WSommaire du Match
69 - 2020-03-23654BELLEVILLE Senators2Binghampton Devils4LSommaire du Match
70 - 2020-03-24668BROOKLYN Wolfpack1BELLEVILLE Senators6WSommaire du Match
71 - 2020-03-25684Manitoba Moose9BELLEVILLE Senators0LSommaire du Match
73 - 2020-03-27701BELLEVILLE Senators0VICTORIAVILLE Tigres6LSommaire du Match
74 - 2020-03-28710BELLEVILLE Senators2SAN DIEGO Gulls1WSommaire du Match
75 - 2020-03-29724UTICA Comets5BELLEVILLE Senators0LSommaire du Match
76 - 2020-03-30732BELLEVILLE Senators1CHICAGO Wolves5LSommaire du Match
77 - 2020-03-31748VICTORIAVILLE Tigres7BELLEVILLE Senators0LSommaire du Match
78 - 2020-04-01761BELLEVILLE Senators-Manitoba Moose-
80 - 2020-04-03777MONT-LAURIER Sommet-BELLEVILLE Senators-
81 - 2020-04-04788COLORADO Eagles-BELLEVILLE Senators-
82 - 2020-04-05802BELLEVILLE Senators-MILWAUKEE Admirals-
83 - 2020-04-06815CORNWALL Aces-BELLEVILLE Senators-
85 - 2020-04-08832BELLEVILLE Senators-MONT-LAURIER Sommet-
86 - 2020-04-09839BELLEVILLE Senators-TUSCON Roadrunners-
87 - 2020-04-10851SAN DIEGO Gulls-BELLEVILLE Senators-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
88 - 2020-04-11864BELLEVILLE Senators-ROCKFORD IceHogs-
89 - 2020-04-12876VICTORIAVILLE Tigres-BELLEVILLE Senators-
91 - 2020-04-14892PROVIDENCE Bruins-BELLEVILLE Senators-
92 - 2020-04-15901BELLEVILLE Senators-CORNWALL Aces-
93 - 2020-04-16916IOWA Wild-BELLEVILLE Senators-
94 - 2020-04-17926BELLEVILLE Senators-CORNWALL Aces-
95 - 2020-04-18943IOWA Wild-BELLEVILLE Senators-
96 - 2020-04-19951BELLEVILLE Senators-IOWA Wild-
98 - 2020-04-21971Syracruse Crunch-BELLEVILLE Senators-
100 - 2020-04-23989BELLEVILLE Senators-PROVIDENCE Bruins-
101 - 2020-04-241000Syracruse Crunch-BELLEVILLE Senators-
104 - 2020-04-271019TUSCON Roadrunners-BELLEVILLE Senators-
105 - 2020-04-281026BELLEVILLE Senators-HOLLYWOOD Oscar-
107 - 2020-04-301043TUSCON Roadrunners-BELLEVILLE Senators-
108 - 2020-05-011051BELLEVILLE Senators-HOLLYWOOD Oscar-
109 - 2020-05-021058BELLEVILLE Senators-PROVIDENCE Bruins-



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
12 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,176,263$ 1,325,000$ 1,175,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 829,417$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 34 16,441$ 558,994$




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
3358124600000108318-210297220000064162-98295240000044156-112241081943021150283001069338331400044521207777495100.00%21385.71%023376130.62%577266421.66%22285925.84%5083282445353525175
Total Saison Régulière58124600000108318-210297220000064162-98295240000044156-112241081943021150283001069338331400044521207777495100.00%21385.71%023376130.62%577266421.66%22285925.84%5083282445353525175