Senators

GP: 54 | W: 30 | L: 18 | OTL: 6 | P: 66
GF: 206 | GA: 189 | PP%: 20.11% | PK%: 76.84%
DG: Olivier Paquin | Morale : 50 | Moyenne d'Équipe : 57
Prochain matchs #843 vs Oceanics
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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 Moyen
1Dillon DubeXX100.00784395836663776225676462755252050630212742,500$
2Alex Formenton (R)X100.00727371767367686650616864654444050620202742,500$
3Brendan PerliniXX100.00694490847959716626585960756464050620232850,000$
4Alexandre Texier (R)X100.00674290837163676442657060254747050620203925,000$
5Kevin RooneyX100.00796587687362816066585879255656050620263850,000$
6Troy TerryXX100.00574095776568847436685954535454050620221525,000$
7Jayce HawrylukXX100.008746826767585461386762602557570505902321,300,000$
8Mackenzie MacEachernX100.00816483627253746232546267255555050590254560,000$
9Jeremy BraccoX100.00756596606473775850694964454747050590221700,000$
10Jansen HarkinsX100.00675091676860825436585661255353050580221825,000$
11Isaac Ratcliffe (R)X100.00797979677970765050474863464444050560204780,833$
12Dmitrij JaskinXX100.00703588637552454735474758474946050520262560,000$
13Jan RuttaX100.00674387777668656125524770255758050630291925,000$
14Andrew Peeke (R)X100.00764493767463635725484863254646050600212825,000$
15Thomas SchemitschX100.00797781607768745025384262394444050570221700,000$
16Tyler LewingtonX100.00687152627372754825394159404444050560241525,000$
17Joseph CecconiX100.00817691617652544425343963374444050550222925,000$
Rayé
1Cam Morrison (R)X100.00414545457439394145414145433230050420212825,000$
2Luke Martin (R)X100.00575585607854763525343050325858050520214700,000$
MOYENNE D'ÉQUIPE100.0071568368736169563653526141505005058
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
1Kasimir Kaskisuo100.0056597378575953595658304444050570
2Filip Gustavsson100.0055577172495851615753304444050550
Rayé
1Kent Simpson100.0037454174363333343333333532050390
MOYENNE D'ÉQUIPE100.004954627547504651494831414005050
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Troy TerrySenators (Ott)C/RW5415456023206100203781427.39%894017.422131543146000011041.98%8100011.2800000113
2Alexandre TexierSenators (Ott)C542927561380371112105714313.81%1976414.15761337860005443145.38%96300001.4700000551
3Kevin RooneySenators (Ott)C54223153731593106230631719.57%2979414.7058134411211241084159.80%91800101.3315010417
4Andrew PeekeSenators (Ott)D541233451038013947111398110.81%104129924.07279451691122141200.00%000000.6900000621
5Brendan PerliniSenators (Ott)LW/RW54192443-710039112259771837.34%1597718.105510601630002644235.25%12200010.8813000113
6Mackenzie MacEachernSenators (Ott)LW5419193813360143681845214210.33%2287916.28641024910001295140.21%9700000.8600000131
7Alex FormentonSenators (Ott)LW3613233672556777178471427.30%1177821.6214525981122781243.27%20800000.9303001350
8Jayce HawrylukSenators (Ott)C/RW541516319300120120155461239.68%1373613.64000021014484037.98%59500010.8400000032
9Jeremy BraccoSenators (Ott)RW5472330100018498928707.87%658310.8100000000150043.75%4800001.0300000111
10Joseph CecconiSenators (Ott)D54615211276201501446163013.04%7077614.3821361600003000.00%000000.5400121021
11Vladimir SobotkaOttawaC/LW17910198180335383186610.84%934220.1330322510002230154.63%44300001.1100000010
12Jan RuttaSenators (Ott)D1631518910025334020267.50%3537823.662351943000034100.00%000000.9500000002
13Dillon DubeSenators (Ott)C/RW2061117-42020476718438.96%341620.8204410661123670033.14%50700000.8214000210
14Tyler LewingtonSenators (Ott)D54116174355156265912381.69%77112220.78134151320001119000.00%000000.3000001102
15Gabriel VilardiOttawaC1759140001496618387.58%126915.85000000112331163.49%30400001.0400000003
16Thomas SchemitschSenators (Ott)D5459145541098276023428.33%83112020.74101161340113118100.00%000000.2500020001
17Isaac RatcliffeSenators (Ott)LW374610923547397519615.33%648013.0000000000010046.43%2800000.4200100000
18Jansen HarkinsSenators (Ott)C37268-34020416216483.23%42316.2600001000000039.93%28300000.6900000000
19Dmitrij JaskinSenators (Ott)LW/RW37257-24025253210396.25%72466.6700000000020016.67%1200000.5700000100
20Luke MartinSenators (Ott)D243144406894433.33%1236615.2800001000022100.00%000000.2200000001
Stats d'équipe Total ou en Moyenne8351973445411274105012431152221866116328.88%5341350516.17375895366131956113294728947.08%460900130.80315253262629
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
1Kasimir KaskisuoSenators (Ott)54291660.9073.5330296117819050000.60020540331
2Filip GustavssonSenators (Ott)71200.9621.462460061570000.0000054000
Stats d'équipe Total ou en Moyenne61301860.9113.3732766118420620000.600205454331


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 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 FormentonSenators (Ott)LW201999-09-13Yes190 Lbs6 ft3NoNoNo2Pro & Farm742,500$227,540$74,250$22,754$No742,500$Lien
Alexandre TexierSenators (Ott)C201999-09-13Yes192 Lbs6 ft1NoNoNo3Pro & Farm925,000$283,467$92,500$28,347$No925,000$925,000$Lien
Andrew PeekeSenators (Ott)D211998-03-17Yes198 Lbs6 ft3NoNoNo2Pro & Farm825,000$252,822$82,500$25,282$No825,000$Lien
Brendan PerliniSenators (Ott)LW/RW231996-04-27No212 Lbs6 ft3NoNoNo2Pro & Farm850,000$260,483$85,000$26,048$No850,000$Lien
Cam MorrisonSenators (Ott)LW211998-08-27Yes212 Lbs6 ft3NoNoNo2Pro & Farm825,000$252,822$82,500$25,282$No825,000$Lien
Dillon DubeSenators (Ott)C/RW211998-07-19No183 Lbs5 ft11NoNoNo2Pro & Farm742,500$227,540$74,250$22,754$No742,500$Lien
Dmitrij JaskinSenators (Ott)LW/RW261993-03-23No216 Lbs6 ft2NoNoNo2Pro & Farm560,000$171,612$56,000$17,161$No560,000$Lien
Filip GustavssonSenators (Ott)G211998-06-07No184 Lbs6 ft2NoNoNo2Pro & Farm742,500$227,540$74,250$22,754$No742,500$Lien
Isaac RatcliffeSenators (Ott)LW201999-02-15Yes201 Lbs6 ft6NoNoNo4Pro & Farm780,833$239,287$78,083$23,929$No780,833$780,833$780,833$Lien
Jan RuttaSenators (Ott)D291990-07-29No200 Lbs6 ft3NoNoNo1Pro & Farm925,000$283,467$92,500$28,347$NoLien
Jansen HarkinsSenators (Ott)C221997-05-23No182 Lbs6 ft1NoNoNo1Pro & Farm825,000$252,822$82,500$25,282$NoLien
Jayce HawrylukSenators (Ott)C/RW231996-01-01No186 Lbs5 ft11NoNoNo2Pro & Farm1,300,000$398,387$130,000$39,839$No1,300,000$Lien
Jeremy BraccoSenators (Ott)RW221997-03-17No180 Lbs5 ft9NoNoNo1Pro & Farm700,000$214,516$70,000$21,452$NoLien
Joseph CecconiSenators (Ott)D221997-05-23No209 Lbs6 ft2NoNoNo2Pro & Farm925,000$283,467$92,500$28,347$No925,000$Lien
Kasimir KaskisuoSenators (Ott)G261993-10-01No201 Lbs6 ft2NoNoNo2Pro & Farm925,000$283,467$92,500$28,347$No925,000$Lien
Kent SimpsonSenators (Ott)G271992-03-26No198 Lbs6 ft2NoNoNo1Pro & Farm550,000$168,548$55,000$16,855$NoLien
Kevin RooneySenators (Ott)C261993-05-21No190 Lbs6 ft2NoNoNo3Pro & Farm850,000$260,483$85,000$26,048$No850,000$850,000$Lien
Luke MartinSenators (Ott)D211998-09-20Yes218 Lbs6 ft2NoNoNo4Pro & Farm700,000$214,516$70,000$21,452$No700,000$700,000$700,000$Lien
Mackenzie MacEachernSenators (Ott)LW251994-03-08No190 Lbs6 ft2YesNoNo4Pro & Farm560,000$171,612$56,000$17,161$No560,000$560,000$560,000$Lien
Thomas SchemitschSenators (Ott)D221996-10-25No200 Lbs6 ft4NoNoNo1Pro & Farm700,000$214,516$70,000$21,452$NoLien
Troy TerrySenators (Ott)C/RW221997-09-10No174 Lbs6 ft1NoNoNo1Pro & Farm525,000$160,887$52,500$16,089$NoLien
Tyler LewingtonSenators (Ott)D241994-12-05No189 Lbs6 ft1NoNoNo1Pro & Farm525,000$160,887$52,500$16,089$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2222.91196 Lbs6 ft22.05772,879$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kevin RooneyBrendan Perlini40122
2Mackenzie MacEachernAlexandre TexierTroy Terry30122
3Isaac RatcliffeJayce HawrylukJeremy Bracco20122
4Dmitrij JaskinJansen Harkins10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrew Peeke40122
2Thomas SchemitschTyler Lewington30122
3Joseph Cecconi20122
4Andrew Peeke10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kevin RooneyBrendan Perlini60122
2Mackenzie MacEachernAlexandre TexierTroy Terry40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrew Peeke60122
2Thomas SchemitschTyler Lewington40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kevin Rooney60122
2Brendan PerliniAlexandre Texier40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrew Peeke60122
2Thomas SchemitschTyler Lewington40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Andrew Peeke60122
2Kevin Rooney40122Thomas SchemitschTyler Lewington40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kevin Rooney60122
2Brendan PerliniAlexandre Texier40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrew Peeke60122
2Thomas SchemitschTyler Lewington40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kevin RooneyBrendan PerliniAndrew Peeke
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kevin RooneyBrendan PerliniAndrew Peeke
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Jeremy Bracco, Jayce Hawryluk, Jeremy BraccoJayce Hawryluk
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Joseph Cecconi, , Thomas SchemitschJoseph Cecconi, Thomas Schemitsch
Tirs de Pénalité
, Kevin Rooney, Brendan Perlini, Alexandre Texier, Troy Terry
Gardien
#1 : Kasimir Kaskisuo, #2 : Filip Gustavsson


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
1Admirals1000000134-11000000134-10000000000010.50035800934662644778697800574013431300.00%20100.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
2Baby Hawks11000000505110000005050000000000021.000591401934662660778697800573778277342.86%40100.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
3Bears2110000067-11010000025-31100000042220.500611170093466269577869780057982520499111.11%10280.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
4Bruins321000001064211000008531100000021140.6671019290093466269077869780057119332785900.00%10190.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
5Cabaret Lady Mary Ann220000001248110000009271100000032141.00012172900934662612877869780057742618673133.33%8187.50%1979203748.06%901199445.19%40892244.25%13399511255388684343
6Caroline2010001010100100000105411010000056-120.5001014240093466268977869780057812131592150.00%7357.14%0979203748.06%901199445.19%40892244.25%13399511255388684343
7Chiefs1010000024-21010000024-20000000000000.0002350093466262677869780057288826200.00%4250.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
8Chill1010000035-21010000035-20000000000000.00036900934662646778697800573082266116.67%110.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
9Comets10001000431000000000001000100043121.00048120093466264077869780057441112193266.67%6183.33%0979203748.06%901199445.19%40892244.25%13399511255388684343
10Cougars30200001917-81010000015-420100001812-410.16791524009346626113778697800571333824747228.57%12466.67%1979203748.06%901199445.19%40892244.25%13399511255388684343
11Crunch31100001910-1110000003212010000168-230.50091726009346626132778697800571203119838112.50%7271.43%0979203748.06%901199445.19%40892244.25%13399511255388684343
12Heat21100000954110000007251010000023-120.500916250093466269377869780057671712448337.50%6350.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
13Jayhawks1010000034-1000000000001010000034-100.00036900934662640778697800573810626200.00%3166.67%0979203748.06%901199445.19%40892244.25%13399511255388684343
14Las Vegas22000000945110000005231100000042241.0009152400934662685778697800575514164614321.43%8362.50%0979203748.06%901199445.19%40892244.25%13399511255388684343
15Manchots11000000633000000000001100000063321.0006121800934662656778697800573480254125.00%000.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
16Marlies2020000029-7000000000002020000029-700.0002350093466265977869780057691722599111.11%11190.91%0979203748.06%901199445.19%40892244.25%13399511255388684343
17Minnesota210010001192100010006511100000054141.0001120310093466261627786978005790262065200.00%10460.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
18Monarchs11000000431110000004310000000000021.0004812009346626437786978005726102169333.33%110.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
19Monsters2110000058-31010000026-41100000032120.5005914009346626697786978005777151850400.00%7185.71%0979203748.06%901199445.19%40892244.25%13399511255388684343
20Monsters1000000134-11000000134-10000000000010.500347009346626387786978005736611284125.00%30100.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
21Oil Kings11000000321000000000001100000032121.000358009346626307786978005734136165240.00%30100.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
22Phantoms311000101213-12100001010821010000025-340.66712213300934662696778697800571463848848225.00%14378.57%0979203748.06%901199445.19%40892244.25%13399511255388684343
23Rocket312000001214-21010000036-32110000098120.33312213300934662689778697800571354220849111.11%10190.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
24Sharks1000000123-11000000123-10000000000010.5002460093466264277869780057196929600.00%20100.00%1979203748.06%901199445.19%40892244.25%13399511255388684343
25Sound Tigers20101000810-21010000036-31000100054120.500814220093466268377869780057872515507228.57%4175.00%0979203748.06%901199445.19%40892244.25%13399511255388684343
26Spiders330000001174220000007431100000043161.0001119300093466261107786978005711141247915426.67%12191.67%0979203748.06%901199445.19%40892244.25%13399511255388684343
27Stars1000010034-1000000000001000010034-110.500347009346626447786978005753106173133.33%3166.67%0979203748.06%901199445.19%40892244.25%13399511255388684343
28Thunder321000001284211000007701100000051440.6671220320093466261327786978005789332664400.00%12283.33%2979203748.06%901199445.19%40892244.25%13399511255388684343
Total542518031252061891728139010231129814261290210294913660.611206358564019346626231377869780057206257045613941843720.11%1904476.84%6979203748.06%901199445.19%40892244.25%13399511255388684343
29Wolf Pack3300000018992200000012661100000063361.00018335100934662617977869780057921822661218.33%10460.00%1979203748.06%901199445.19%40892244.25%13399511255388684343
_Since Last GM Reset542518031252061891728139010231129814261290210294913660.611206358564019346626231377869780057206257045613941843720.11%1904476.84%6979203748.06%901199445.19%40892244.25%13399511255388684343
_Vs Conference28159010121029571786000126362111730100039336360.64310218428600934662611447786978005710372902397131051615.24%961881.25%4979203748.06%901199445.19%40892244.25%13399511255388684343

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5466SOL220635856423132062570456139401
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
5425183125206189
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
28139102311298
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2612921029491
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
1843720.11%1904476.84%6
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
778697800579346626
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
979203748.06%901199445.19%40892244.25%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
13399511255388684343


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 - 2020-10-221Senators1Marlies4LSommaire du Match
4 - 2020-10-2520Wolf Pack3Senators6WSommaire du Match
9 - 2020-10-3051Chiefs4Senators2LSommaire du Match
11 - 2020-11-0162Thunder2Senators4WSommaire du Match
13 - 2020-11-0379Minnesota5Senators6WXSommaire du Match
16 - 2020-11-06105Senators4Las Vegas2WSommaire du Match
18 - 2020-11-08115Senators3Jayhawks4LSommaire du Match
20 - 2020-11-10132Senators3Stars4LXSommaire du Match
22 - 2020-11-12143Cougars5Senators1LSommaire du Match
24 - 2020-11-14158Sound Tigers6Senators3LSommaire du Match
26 - 2020-11-16173Sharks3Senators2LXXSommaire du Match
32 - 2020-11-22207Senators2Bruins1WSommaire du Match
34 - 2020-11-24221Senators6Wolf Pack3WSommaire du Match
35 - 2020-11-25225Senators5Sound Tigers4WXSommaire du Match
37 - 2020-11-27242Monarchs3Senators4WSommaire du Match
39 - 2020-11-29256Caroline4Senators5WXXSommaire du Match
41 - 2020-12-01271Senators5Caroline6LSommaire du Match
43 - 2020-12-03281Senators4Spiders3WSommaire du Match
45 - 2020-12-05298Phantoms4Senators5WXXSommaire du Match
46 - 2020-12-06304Senators4Crunch5LXXSommaire du Match
49 - 2020-12-09323Senators4Cougars5LXXSommaire du Match
50 - 2020-12-10331Senators4Rocket5LSommaire du Match
52 - 2020-12-12347Wolf Pack3Senators6WSommaire du Match
55 - 2020-12-15369Senators3Monsters2WSommaire du Match
57 - 2020-12-17378Bruins4Senators3LSommaire du Match
59 - 2020-12-19395Senators5Minnesota4WSommaire du Match
60 - 2020-12-20405Senators2Heat3LSommaire du Match
63 - 2020-12-23432Senators4Comets3WXSommaire du Match
64 - 2020-12-24436Senators3Oil Kings2WSommaire du Match
67 - 2020-12-27452Senators2Phantoms5LSommaire du Match
69 - 2020-12-29470Bruins1Senators5WSommaire du Match
71 - 2020-12-31485Senators5Rocket3WSommaire du Match
74 - 2021-01-03501Monsters6Senators2LSommaire du Match
76 - 2021-01-05519Senators3Cabaret Lady Mary Ann2WSommaire du Match
77 - 2021-01-06526Senators5Thunder1WSommaire du Match
79 - 2021-01-08542Chill5Senators3LSommaire du Match
81 - 2021-01-10558Phantoms4Senators5WSommaire du Match
83 - 2021-01-12575Crunch2Senators3WSommaire du Match
89 - 2021-01-18603Spiders3Senators4WSommaire du Match
90 - 2021-01-19612Senators6Manchots3WSommaire du Match
93 - 2021-01-22632Cabaret Lady Mary Ann2Senators9WSommaire du Match
95 - 2021-01-24648Thunder5Senators3LSommaire du Match
98 - 2021-01-27667Senators4Bears2WSommaire du Match
101 - 2021-01-30689Senators4Cougars7LSommaire du Match
102 - 2021-01-31693Rocket6Senators3LSommaire du Match
105 - 2021-02-03720Baby Hawks0Senators5WSommaire du Match
107 - 2021-02-05734Las Vegas2Senators5WSommaire du Match
109 - 2021-02-07746Heat2Senators7WSommaire du Match
118 - 2021-02-16769Spiders1Senators3WSommaire du Match
119 - 2021-02-17774Senators2Crunch3LSommaire du Match
122 - 2021-02-20787Bears5Senators2LSommaire du Match
123 - 2021-02-21796Senators1Marlies5LSommaire du Match
126 - 2021-02-24819Admirals4Senators3LXXSommaire du Match
128 - 2021-02-26833Monsters4Senators3LXXSommaire du Match
130 - 2021-02-28843Senators-Oceanics-
133 - 2021-03-03874Senators-Monsters-
135 - 2021-03-05885Jayhawks-Senators-
137 - 2021-03-07901Marlies-Senators-
138 - 2021-03-08911Stars-Senators-
140 - 2021-03-10922Crunch-Senators-
142 - 2021-03-12937Oceanics-Senators-
144 - 2021-03-14952Rocket-Senators-
146 - 2021-03-16967Senators-Monsters-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
147 - 2021-03-17977Senators-Chill-
149 - 2021-03-19988Comets-Senators-
151 - 2021-03-211005Cougars-Senators-
154 - 2021-03-241022Senators-Manchots-
156 - 2021-03-261038Sound Tigers-Senators-
158 - 2021-03-281053Senators-Sharks-
161 - 2021-03-311078Senators-Admirals-
162 - 2021-04-011082Senators-Monarchs-
164 - 2021-04-031095Senators-Baby Hawks-
166 - 2021-04-051111Senators-Chiefs-
169 - 2021-04-081132Oil Kings-Senators-
171 - 2021-04-101147Senators-Bears-
172 - 2021-04-111158Senators-Caroline-
175 - 2021-04-141182Cabaret Lady Mary Ann-Senators-
177 - 2021-04-161191Senators-Bruins-
179 - 2021-04-181209Marlies-Senators-
182 - 2021-04-211228Senators-Thunder-
184 - 2021-04-231243Senators-Cabaret Lady Mary Ann-
186 - 2021-04-251263Manchots-Senators-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets5020
Assistance34,34618,158
Assistance PCT61.33%64.85%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
13 1875 - 62.50% 74,302$2,080,460$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,234,425$ 1,700,333$ 1,700,333$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
9,142$ 1,234,425$ 22 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
965,928$ 57 9,142$ 521,094$




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