Senators

GP: 48 | W: 20 | L: 22 | OTL: 6 | P: 46
GF: 120 | GA: 142 | PP%: 12.27% | PK%: 85.77%
DG: Farlou Ferland | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #521 vs Condors
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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 SPÂgeContratSalaire
1Alexander Volkov (R)XX100.00757183647181866350625867555555655000223925,000$
2Filip ChlapikX100.00884589777252826239605959535757645000231925,000$
3Joel Farabee (R)X100.006781798463676467347068635349496950002031,425,000$
4Jack RoslovicXX100.00714394796968917049697056256263705000231900,000$
5Marko DanoXX100.00687551767567715650574763455858575000252925,000$
6Michael McLeodX100.008144897970568559746355722547476450002221,363,333$
7Ryan DzingelXX100.006762868271678875357664632564656945002821,800,000$
8Nick PaulXX100.00876987718767786177657072255656715000252750,000$
9Tyson JostXX100.007343898569639072516762672561626850002241,673,333$
10Michael Dal ColleXX100.00804492667461756056605862255556634900242700,000$
11Andreas EnglundX100.00899585747455765725504763635757595000244700,000$
12Christian JarosX100.00764486637655725325574765255454595000242755,000$
13Christian WolaninX100.00727078797055594525284362415757515000252925,000$
14Jake DotchinX100.00707949657956594825394061385656515000264700,000$
15Samuel GirardX100.00695191885983937825704866256263664600221935,833$
16Carl DahlstromX100.00614387618665586125464773755959575000251925,000$
Rayé
MOYENNE D'ÉQUIPE100.0075608275736477624259556539575763490
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
1Antoine Bibeau100.0044526582404350524445304444464500
2Chris Driedger100.0069595784776296697769754545723200
3Artyom Zagidulin (R)100.0051577173495450565252304444534500
Rayé
MOYENNE D'ÉQUIPE100.005556648055536559585545444457410
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
1Jack RoslovicSenators (OTT)C/RW4823264911220481311203510119.17%13102421.34611173420720251633448.80%129700010.9617000642
2Joel FarabeeSenators (OTT)LW4818264412391567100124388214.52%1997920.4069154321101101573041.27%6300000.9017012255
3Filip ChlapikSenators (OTT)C48141529-93407183115247512.17%588918.535611391920000761242.84%69800000.6505000410
4Marko DanoSenators (OTT)LW/RW4891726-124810657683355310.84%775615.762810201520000131043.90%4100000.6900011032
5Michael Dal ColleSenators (OTT)LW/RW428182613300653145183217.78%870016.67235141420221604146.75%7700000.7400000113
6Michael McLeodSenators (OTT)C4815924-163407112398266715.31%1975515.74235125310131402058.40%60100000.6400000124
7Carl DahlstromSenators (OTT)D4841317-6520764340122810.00%2979316.5315625129000025000.00%000000.4300000110
8Dante FabbroSenatorsD134812-118028182851814.29%1023518.08426195900002100.00%000001.0200000210
9Samuel GirardSenators (OTT)D1417821802720132127.69%1333223.721121372000029000.00%000000.4800000101
10Christian WolaninSenators (OTT)D48257-22603626145714.29%2463713.29011272000056000.00%000000.2200000000
11Ryan DzingelSenators (OTT)LW/RW1434711001025397227.69%025117.930111266000001023.08%1300000.5600000201
12Alexander VolkovSenators (OTT)LW/RW1406602553117224120.00%229521.140335730002220040.00%3500000.4100000001
13Nick PaulSenators (OTT)C/LW1415651201721316163.23%219213.78000040005460060.00%1000000.6200000001
14Kevin RooneySenatorsC11235212017301951810.53%223121.060005450001450060.97%26900000.4300000010
15Andreas EnglundSenators (OTT)D14044-21552043220.00%723216.5901117000055000.00%000000.3400100000
16Christian JarosSenators (OTT)D14134780191161416.67%829721.28101565000057000.00%000000.2700000010
17Jake DotchinSenators (OTT)D48033-9775711642110.00%2857812.05000016000059000.00%000000.1000001000
18Tyson JostSenators (OTT)C/LW14123-100410102710.00%21279.11000000004750122.22%900000.4700000010
Stats d'équipe Total ou en Moyenne548106174280-54804074378581422956713.02%198931116.99305484249157233621108916849.86%311300010.60219124202120
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
1Chris DriedgerSenators (OTT)147430.9151.5386403222590100.71414140103
Stats d'équipe Total ou en Moyenne147430.9151.5386403222590100.71414140103


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$380,444$925,000$380,444$0$0$No925,000$925,000$
Andreas EnglundSenators (OTT)D241996-01-21No189 Lbs6 ft3NoNoNo4Pro & Farm700,000$287,903$700,000$287,903$0$0$No700,000$700,000$700,000$Lien
Antoine Bibeau (Contrat à 1 Volet)Senators (OTT)G261994-05-01No207 Lbs6 ft3NoNoNo2Pro & Farm750,000$308,468$750,000$308,468$75,000$30,847$No750,000$Lien
Artyom ZagidulinSenators (OTT)G251995-01-01Yes200 Lbs6 ft0NoNoNo2Pro & Farm750,000$308,468$750,000$308,468$0$0$No750,000$Lien
Carl DahlstromSenators (OTT)D251995-01-28No231 Lbs6 ft4NoNoNo1Pro & Farm925,000$380,444$925,000$380,444$0$0$NoLien
Chris DriedgerSenators (OTT)G261994-05-18No205 Lbs6 ft4NoNoNo2Pro & Farm850,000$349,597$850,000$349,597$0$0$No850,000$Lien
Christian JarosSenators (OTT)D241996-04-02No201 Lbs6 ft3NoNoNo2Pro & Farm755,000$310,524$450,000$185,081$0$0$No755,000$Lien
Christian WolaninSenators (OTT)D251995-03-17No185 Lbs6 ft2NoNoNo2Pro & Farm925,000$380,444$450,000$185,081$0$0$No925,000$Lien
Filip ChlapikSenators (OTT)C231997-06-03No196 Lbs6 ft1NoNoNo1Pro & Farm925,000$380,444$925,000$380,444$0$0$NoLien
Jack RoslovicSenators (OTT)C/RW231997-01-28No187 Lbs6 ft1NoNoNo1Pro & Farm900,000$370,161$900,000$370,161$0$0$NoLien
Jake DotchinSenators (OTT)D261994-03-24No210 Lbs6 ft3NoNoNo4Pro & Farm700,000$287,903$700,000$287,903$0$0$No700,000$700,000$700,000$Lien
Joel FarabeeSenators (OTT)LW202000-02-24Yes164 Lbs6 ft0NoNoNo3Pro & Farm1,425,000$586,089$1,425,000$586,089$0$0$No1,425,000$1,425,000$
Marko DanoSenators (OTT)LW/RW251994-11-30No212 Lbs5 ft11NoNoNo2Pro & Farm925,000$380,444$925,000$380,444$0$0$No925,000$Lien
Michael Dal ColleSenators (OTT)LW/RW241996-06-19No198 Lbs6 ft3NoNoNo2Pro & Farm700,000$287,903$700,000$287,903$0$0$No700,000$Lien
Michael McLeodSenators (OTT)C221998-02-03No187 Lbs6 ft2NoNoNo2Pro & Farm1,363,333$560,726$450,000$185,081$0$0$No1,363,333$Lien
Nick PaulSenators (OTT)C/LW251995-03-20No230 Lbs6 ft4NoNoNo2Pro & Farm750,000$308,468$450,000$185,081$0$0$No750,000$Lien
Ryan DzingelSenators (OTT)LW/RW281992-03-09No190 Lbs6 ft0NoNoNo2Pro & Farm1,800,000$740,323$1,800,000$740,323$0$0$No1,800,000$Lien
Samuel GirardSenators (OTT)D221998-05-12No162 Lbs5 ft10NoNoNo1Pro & Farm935,833$384,899$935,833$384,899$0$0$NoLien
Tyson JostSenators (OTT)C/LW221998-03-14No191 Lbs5 ft11NoNoNo4Pro & Farm1,673,333$688,226$1,673,333$688,226$0$0$No1,673,333$1,673,333$1,673,333$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1924.05197 Lbs6 ft22.21983,026$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Joel FarabeeJack RoslovicAlexander Volkov38122
2Ryan Dzingel30122
3Nick PaulFilip ChlapikMarko Dano27122
4Tyson JostMichael McLeodFilip Chlapik5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Samuel GirardCarl Dahlstrom39122
2Christian JarosChristian Wolanin33122
3Andreas EnglundJake Dotchin28122
4Samuel GirardCarl Dahlstrom0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Joel FarabeeJack RoslovicAlexander Volkov55005
2Ryan DzingelFilip Chlapik45005
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Samuel GirardCarl Dahlstrom55005
2Christian JarosChristian Wolanin45005
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Tyson Jost55230
2Michael McLeodNick Paul45230
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andreas EnglundJake Dotchin55230
2Christian JarosChristian Wolanin45230
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
155140Jake DotchinAndreas Englund55140
2Michael McLeod45140Christian JarosChristian Wolanin45140
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Jack RoslovicJoel Farabee50122
2Ryan Dzingel50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Samuel GirardCarl Dahlstrom50122
2Christian JarosChristian Wolanin50122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Joel FarabeeJack RoslovicFilip ChlapikSamuel GirardCarl Dahlstrom
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nick PaulMichael McLeodCarl DahlstromSamuel Girard
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Joel Farabee, Jack Roslovic, Alexander VolkovJoel Farabee, Jack RoslovicAlexander Volkov
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Christian Wolanin, Jake Dotchin, Samuel GirardChristian WolaninJake Dotchin, Samuel Girard
Tirs de Pénalité
Jack Roslovic, Joel Farabee, Filip Chlapik, Michael McLeod,
Gardien
#1 : Chris Driedger, #2 : Antoine Bibeau


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
1Admirals22000000927110000004041100000052341.000916250141383564230528732833308294913323.08%110100.00%0657130450.38%630130548.28%33970048.43%11337941216353572278
2Bruins60301002818-103010000226-430201000612-640.3338142200413835611230528732833133321011143638.33%42783.33%0657130450.38%630130548.28%33970048.43%11337941216353572278
3Crunch504001001122-112020000048-430200100714-710.100112031004138356993052873283312742669329310.34%31487.10%0657130450.38%630130548.28%33970048.43%11337941216353572278
4Flames1010000025-3000000000001010000025-300.0002460041383567305287328332361417900.00%8187.50%0657130450.38%630130548.28%33970048.43%11337941216353572278
5Griffins623000011821-332000001139430300000512-750.41718284600413835613830528732833153456211830620.00%29582.76%2657130450.38%630130548.28%33970048.43%11337941216353572278
6IceHogs2020000046-21010000023-11010000023-100.0004812004138356343052873283344172850500.00%15473.33%0657130450.38%630130548.28%33970048.43%11337941216353572278
7Marlies532000001174330000009272020000025-360.600111930014138356124305287328339025548435514.29%26292.31%0657130450.38%630130548.28%33970048.43%11337941216353572278
8Monarchs10000010101000000000001000001010121.00010101413835610305287328332341618200.00%80100.00%0657130450.38%630130548.28%33970048.43%11337941216353572278
9Monsters1010000016-5000000000001010000016-500.00011200413835614305287328332391416400.00%7357.14%0657130450.38%630130548.28%33970048.43%11337941216353572278
10Moose1010000015-41010000015-40000000000000.000112004138356213052873283327111218700.00%5180.00%0657130450.38%630130548.28%33970048.43%11337941216353572278
11Penguins3020001069-32020000037-41000001032120.333691500413835647305287328336629215618316.67%70100.00%0657130450.38%630130548.28%33970048.43%11337941216353572278
12Phantoms22000000853110000005321100000032141.0008132100413835637305287328334210104617423.53%40100.00%0657130450.38%630130548.28%33970048.43%11337941216353572278
13Rampage11000000321110000003210000000000021.000369004138356183052873283328512165120.00%6266.67%0657130450.38%630130548.28%33970048.43%11337941216353572278
14Rocket622020001919032001000128430201000711-480.66719284700413835610930528732833119317010133618.18%28485.71%1657130450.38%630130548.28%33970048.43%11337941216353572278
15Sharks11000000303000000000001100000030321.0003690141383562130528732833131618500.00%30100.00%0657130450.38%630130548.28%33970048.43%11337941216353572278
16Soldiers10001000321100010003210000000000021.00033600413835620305287328331541015800.00%40100.00%0657130450.38%630130548.28%33970048.43%11337941216353572278
17Sound Tigers11000000422110000004220000000000021.00048120041383562830528732833296821500.00%40100.00%0657130450.38%630130548.28%33970048.43%11337941216353572278
18Stars1000000145-1000000000001000000145-110.5004812004138356183052873283323103321300.00%8362.50%0657130450.38%630130548.28%33970048.43%11337941216353572278
Total48142204125120142-2223117020036557825315021225585-30460.4791201993190441383569343052873283310503055949062773412.27%2603785.77%3657130450.38%630130548.28%33970048.43%11337941216353572278
19Wolf Pack1010000023-1000000000001010000023-100.00024600413835613305287328332481415300.00%7185.71%0657130450.38%630130548.28%33970048.43%11337941216353572278
20Wolves1000000123-1000000000001000000123-110.500235004138356223052873283318214201000.00%70100.00%0657130450.38%630130548.28%33970048.43%11337941216353572278
_Since Last GM Reset48142204125120142-2223117020036557825315021225585-30460.4791201993190441383569343052873283310503055949062773412.27%2603785.77%3657130450.38%630130548.28%33970048.43%11337941216353572278
_Vs Conference30716031126894-261465010023534116111021103360-27250.41768112180014138356562305287328336471923645421842413.04%1602286.25%1657130450.38%630130548.28%33970048.43%11337941216353572278
_Vs Division28511031026787-20145301002403371408021002754-27190.33967109176014138356582305287328336221753535101632314.11%1562285.90%3657130450.38%630130548.28%33970048.43%11337941216353572278

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4846W2120199319934105030559490604
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4814224125120142
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2311720036557
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2531521225585
Derniers 10 Matchs
WLOTWOTL SOWSOL
440002
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2773412.27%2603785.77%3
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
305287328334138356
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
657130450.38%630130548.28%33970048.43%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
11337941216353572278


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 - 2020-10-1095Marlies0Senators2WSommaire du Match
16 - 2020-10-12105Senators0Griffins1LSommaire du Match
18 - 2020-10-14112Rocket4Senators5WSommaire du Match
21 - 2020-10-17133Crunch6Senators4LSommaire du Match
22 - 2020-10-18136Senators0Bruins4LSommaire du Match
23 - 2020-10-19152Senators2Crunch5LSommaire du Match
24 - 2020-10-20157Bruins2Senators0LSommaire du Match
26 - 2020-10-22177Sound Tigers2Senators4WSommaire du Match
27 - 2020-10-23181Senators2Wolf Pack3LSommaire du Match
28 - 2020-10-24194Senators1Rocket4LSommaire du Match
31 - 2020-10-27206Senators3Phantoms2WSommaire du Match
32 - 2020-10-28215IceHogs3Senators2LSommaire du Match
34 - 2020-10-30227Penguins4Senators1LSommaire du Match
36 - 2020-11-01231Senators4Stars5LXXSommaire du Match
38 - 2020-11-03245Soldiers2Senators3WXSommaire du Match
40 - 2020-11-05258Senators1Monsters6LSommaire du Match
43 - 2020-11-08272Rocket2Senators3WXSommaire du Match
44 - 2020-11-09281Senators2Bruins5LSommaire du Match
45 - 2020-11-10289Senators4Crunch5LXSommaire du Match
46 - 2020-11-11301Phantoms3Senators5WSommaire du Match
48 - 2020-11-13312Senators1Crunch4LSommaire du Match
49 - 2020-11-14321Moose5Senators1LSommaire du Match
50 - 2020-11-15333Senators3Griffins5LSommaire du Match
51 - 2020-11-16341Senators2Flames5LSommaire du Match
52 - 2020-11-17350Griffins1Senators5WSommaire du Match
53 - 2020-11-18357Senators4Bruins3WXSommaire du Match
55 - 2020-11-20374Marlies1Senators4WSommaire du Match
56 - 2020-11-21388Bruins2Senators1LXXSommaire du Match
58 - 2020-11-23401Admirals0Senators4WSommaire du Match
59 - 2020-11-24410Senators5Admirals2WSommaire du Match
60 - 2020-11-25420Senators2Wolves3LXXSommaire du Match
61 - 2020-11-26428Senators2IceHogs3LSommaire du Match
63 - 2020-11-28437Senators3Sharks0WSommaire du Match
64 - 2020-11-29444Bruins2Senators1LXXSommaire du Match
66 - 2020-12-01460Penguins3Senators2LSommaire du Match
67 - 2020-12-02471Senators1Monarchs0WXXSommaire du Match
68 - 2020-12-03480Crunch2Senators0LSommaire du Match
70 - 2020-12-05491Senators1Marlies3LSommaire du Match
71 - 2020-12-06502Rampage2Senators3WSommaire du Match
72 - 2020-12-07515Senators3Penguins2WXXSommaire du Match
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
18 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,576,388$ 1,792,749$ 1,593,416$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,076,001$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 51 21,312$ 1,086,912$




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