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Senators
GP: 22 | W: 10 | L: 10 | OTL: 2 | P: 22
GF: 76 | GA: 77 | PP%: 26.00% | PK%: 70.97%
DG: Brendan Cwik | Morale : 48 | Moyenne d’équipe : 57
Prochains matchs #356 vs Checkers

Centre de jeu
Senators
10-10-2, 22pts
3
1 Moose
9-10-4, 22pts
Team Stats
W2SéquenceSOL1
7-3-1Fiche domicile3-6-2
3-7-1Fiche domicile6-4-2
5-4-1Derniers 10 matchs4-4-2
3.45Buts par match 2.00
3.50Buts contre par match 2.61
26.00%Pourcentage en avantage numérique20.34%
70.97%Pourcentage en désavantage numérique82.22%
Moose
9-10-4, 22pts
0
2 Senators
10-10-2, 22pts
Team Stats
SOL1SéquenceW2
3-6-2Fiche domicile7-3-1
6-4-2Fiche domicile3-7-1
4-4-2Derniers 10 matchs5-4-1
2.00Buts par match 3.45
2.61Buts contre par match 3.50
20.34%Pourcentage en avantage numérique26.00%
82.22%Pourcentage en désavantage numérique70.97%
Checkers
9-8-5, 23pts
Jour 30
Senators
10-10-2, 22pts
Statistiques d’équipe
L1SéquenceW2
6-4-2Fiche domicile7-3-1
3-4-3Fiche visiteur3-7-1
3-5-210 derniers matchs5-4-1
2.55Buts par match 3.45
3.00Buts contre par match 3.45
30.61%Pourcentage en avantage numérique26.00%
70.45%Pourcentage en désavantage numérique70.97%
Senators
10-10-2, 22pts
Jour 31
Thunderbirds
16-4-2, 34pts
Statistiques d’équipe
W2SéquenceW10
7-3-1Fiche domicile8-3-1
3-7-1Fiche visiteur8-1-1
5-4-110 derniers matchs10-0-0
3.45Buts par match 4.59
3.50Buts contre par match 4.59
26.00%Pourcentage en avantage numérique36.67%
70.97%Pourcentage en désavantage numérique81.16%
Phantoms
10-12-0, 20pts
Jour 32
Senators
10-10-2, 22pts
Statistiques d’équipe
L1SéquenceW2
5-6-0Fiche domicile7-3-1
5-6-0Fiche visiteur3-7-1
4-6-010 derniers matchs5-4-1
3.09Buts par match 3.45
3.32Buts contre par match 3.45
25.00%Pourcentage en avantage numérique26.00%
67.16%Pourcentage en désavantage numérique70.97%
Meneurs d'équipe
Buts
Alexandre Texier
14
Passes
Tyson Kozak
19
Points
Tyson Kozak
25
Plus/Moins
Nate Smith
12
Victoires
Domenic DiVincentiis
6
Pourcentage d’arrêts
Akira Schmid
0.859

Statistiques d’équipe
Buts pour
76
3.45 GFG
Tirs pour
648
29.45 Avg
Pourcentage en avantage numérique
26.0%
13 GF
Début de zone offensive
39.7%
Buts contre
77
3.50 GAA
Tirs contre
471
21.41 Avg
Pourcentage en désavantage numérique
71.0%%
18 GA
Début de la zone défensive
29.9%
Informations de l'équipe

Directeur généralBrendan Cwik
EntraîneurBob Woods
DivisionDivision 2
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,192
Billets de saison1,500


Informations de la formation

Équipe Pro24
Équipe Mineure18
Limite contact 42 / 100
Espoirs117


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
1Tyson Kozak (R)X100.007743968068566962706166712546466758630231850,000$
2Logan Brown (R)X100.0086868666865654658063657061444466466202731,530,000$
3Hunter Haight (R)X100.0072668767677883597351626258454561646002131,314,000$
4Brad Lambert (R)X100.0071658674667783587162496146454559606002211,200,000$
5Nate SmithX100.0070658265657377577155556051454559615802731,409,000$
6Brendan Brisson (R)XXX100.007371787272677156695749614647475659580241925,000$
7Jakub BrabenecX100.0076699366707277526549516148454557545702231,107,000$
8Massimo Rizzo (R)X100.0075679265686163546852516148454557545602431,341,000$
9Cross HanasX100.007671866471525254504756625345455752550241925,000$
10Lukas SvejkovskyX100.006860858060363252503861575845455656530241925,000$
11Adam MechuraXXX100.0081739980733230445538446342444452435202311,000,000$
12Daemon Hunt (R)X100.007874886875707552254742623846465448600231902,500$
13Hunter McDonald (R)X100.0073786165797886482539416039454552585902331,192,000$
14Simon LundmarkX100.0076728664727481472537416139454553565902531,161,000$
15Mac HollowellX100.006561756661697353255439573745455356570271971,000$
16Aleksi Heimosalmi (R)X100.0070638665646773472537425740454552545602231,277,000$
17Luke Reid (R)X100.0079709981714547412528396037454549555602431,338,000$
18Hardy Haman AktellX100.0076748163744241502547396137454550525502731,154,000$
Rayé
1Alexandre TexierXX97.7367428976746254662564736380656667406402611,000,000$
2Henri NikkanenX100.008477996278383551645146654445455439540241925,000$
3Gavin HainX100.0073698262694140506344506048444454395202531,096,000$
MOYENNE D’ÉQUIPE99.89756786697159625350495162464646565357
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 SPÂgeContratSalaire
1Domenic DiVincentiis (R)100.005454687655545157525330444454565502111,000,000$
2Ales Stezka100.005148608052515055515130444451415302911,000,000$
Rayé
1Akira Schmid100.004852658346485054484895484950565302531,272,000$
MOYENNE D’ÉQUIPE100.0051516480515150555051524546525154
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bob Woods40404040404040CAN5211,000,000$


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’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
1Tyson KozakSenators (OTT)C2261925-15533347330368.22%942419.290664420001230062.07%29206001.1802100131
2Alexandre TexierSenators (OTT)LW/RW20141024-555313883343716.87%1544122.0541513400001422136.55%539169001.0902010300
3Brad LambertSenators (OTT)C22101222840263874213513.51%438417.46134533000030256.15%187143001.1501000013
4Hunter HaightSenators (OTT)C2271118121210382943202516.28%837717.14235734000001053.33%15133000.9502101120
5Brendan BrissonSenators (OTT)C/LW/RW2281018-61810482965214112.31%841718.970002200114302057.58%992110000.8601002004
6Nate SmithSenators (OTT)C22771412115392342133216.67%439818.101232340001101052.17%23104010.7001001200
7Daemon HuntSenators (OTT)D223912-1211543353519158.57%3455925.41101330000133000%01112000.4300030000
8Logan BrownSenators (OTT)C115611-1135151629101717.24%422120.123147220003181045.95%3776000.9911001101
9Jakub BrabenecSenators (OTT)C22527-355271926101219.23%430213.77000111012182050.00%8104010.4600010100
10Mac HollowellSenators (OTT)D2207732202515181170%1241518.89022247011125000%027000.3400000010
11Hunter McDonaldSenators (OTT)D22156270204531287123.57%3054024.59101446000130000%089000.2200112100
12Lukas SvejkovskySenators (OTT)RW2242610018103782710.81%226912.23000010000191075.00%4131000.4500000000
13Massimo RizzoSenators (OTT)C22325-40019142571912.00%325911.7900000000000133.33%651000.3900000000
14Cross HanasSenators (OTT)LW2232519532262352013.04%424611.1900000000180042.31%5274000.4100010010
15Simon LundmarkSenators (OTT)D22044-134202935201070%1850623.04000030000125000%0912000.1601112000
16Adam MechuraSenators (OTT)C/LW/RW130330009612670%11189.1000000000000066.67%954000.5101000000
17Hardy Haman AktellSenators (OTT)D220224951076550%223010.460000000009000%014000.1700010000
18Aleksi HeimosalmiSenators (OTT)D22022-22010196340%828412.9200000000049000%007000.1400000000
19Luke ReidSenators (OTT)D220117001033200%11305.940000000001000%002000.1500000000
20Henri NikkanenSenators (OTT)C9000000020000%0131.4900000000000050.00%20000000000000
Statistiques d’équipe totales ou en moyenne405761161922624011050742964824235811.73%171654016.15131831503901231735010444.75%1010172108020.591124991089
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
1Domenic DiVincentiisSenators (OTT)116410.8282.93594012916999200.8005110000
2Ales StezkaSenators (OTT)114410.8433.625630034217132400.6005112001
3Akira SchmidSenators (OTT)60200.8594.21171001285532000020000
Statistiques d’équipe totales ou en moyenne28101020.8413.391329017547128480102222001


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Adam MechuraSenators (OTT)C/LW/RW232003-01-31CZENo194 Lbs6 ft3NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm1,000,000$741,071$0$0$No---------------------------Lien
Akira SchmidSenators (OTT)G252000-05-12SUINo190 Lbs6 ft5NoNoN/ANoNo32025-10-22FalseFalsePro & Farm1,272,000$942,643$0$0$No1,272,000$1,272,000$-------1,272,000$1,272,000$-------NoNo-------Lien
Aleksi HeimosalmiSenators (OTT)D222003-05-08FINYes170 Lbs5 ft11NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,277,000$946,348$0$0$No1,277,000$1,277,000$-------1,277,000$1,277,000$-------NoNo-------Lien
Ales StezkaSenators (OTT)G291997-01-06CZENo190 Lbs6 ft4NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm1,000,000$741,071$0$0$No---------------------------Lien
Alexandre TexierSenators (OTT)LW/RW261999-09-13FRANo201 Lbs6 ft1NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm1,000,000$741,071$0$0$No---------------------------Lien
Brad LambertSenators (OTT)C222003-12-19FINYes173 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm1,200,000$889,286$0$0$No---------------------------Lien
Brendan BrissonSenators (OTT)C/LW/RW242001-10-22USAYes198 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm925,000$685,491$0$0$No---------------------------Lien
Cross HanasSenators (OTT)LW242002-01-05USANo190 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm925,000$685,491$0$0$No---------------------------Lien
Daemon HuntSenators (OTT)D232002-05-15CANYes201 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm902,500$668,817$0$0$No---------------------------Lien
Domenic DiVincentiisSenators (OTT)G212004-03-04CANYes194 Lbs6 ft2NoNoAssign ManuallyNoNo12026-01-09FalseFalsePro & Farm1,000,000$741,071$0$0$No---------830,556$-----------------Lien
Gavin HainSenators (OTT)C252000-04-03USANo194 Lbs5 ft11NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,096,000$812,214$0$0$No1,096,000$1,096,000$-------1,096,000$1,096,000$-------NoNo-------Lien
Hardy Haman AktellSenators (OTT)D271998-07-04SWENo198 Lbs6 ft3NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,154,000$855,196$0$0$No1,154,000$1,154,000$-------1,154,000$1,154,000$-------NoNo-------Lien
Henri NikkanenSenators (OTT)C242001-04-28FINNo200 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm925,000$685,491$0$0$No---------------------------Lien
Hunter HaightSenators (OTT)C212004-04-04CANYes181 Lbs5 ft11NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,314,000$973,768$0$0$No1,314,000$1,314,000$-------1,314,000$1,314,000$-------NoNo-------Lien
Hunter McDonaldSenators (OTT)D232002-05-11USAYes205 Lbs6 ft4NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,192,000$883,357$0$0$No1,192,000$1,192,000$-------1,192,000$1,192,000$-------NoNo-------Lien
Jakub BrabenecSenators (OTT)C222003-09-11CZENo185 Lbs6 ft1NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,107,000$820,366$0$0$No1,107,000$1,107,000$-------1,107,000$1,107,000$-------NoNo-------Lien
Logan BrownSenators (OTT)C271998-03-05USAYes222 Lbs6 ft7NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,530,000$1,133,839$0$0$No1,530,000$1,530,000$-------1,530,000$1,530,000$-------NoNo-------Lien
Lukas SvejkovskySenators (OTT)RW242001-11-28USANo165 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm925,000$685,491$0$0$No---------------------------Lien
Luke ReidSenators (OTT)D242001-09-26CANYes192 Lbs6 ft0NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,338,000$991,554$0$0$No1,338,000$1,338,000$-------1,338,000$1,338,000$-------NoNo-------Lien
Mac HollowellSenators (OTT)D271998-09-26CANNo170 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm971,000$719,580$0$0$No---------------------------Lien
Massimo RizzoSenators (OTT)C242001-06-13CANYes185 Lbs5 ft11NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,341,000$993,777$0$0$No1,341,000$1,341,000$-------1,341,000$1,341,000$-------NoNo-------Lien
Nate SmithSenators (OTT)C271998-10-19USANo177 Lbs6 ft0NoNoN/ANoNo32025-10-22FalseFalsePro & Farm1,409,000$1,044,170$0$0$No1,409,000$1,409,000$-------1,409,000$1,409,000$-------NoNo-------Lien
Simon LundmarkSenators (OTT)D252000-10-08SWENo193 Lbs6 ft2NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,161,000$860,384$0$0$No1,161,000$1,161,000$-------1,161,000$1,161,000$-------NoNo-------Lien
Tyson KozakSenators (OTT)C232002-12-29CANYes185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm850,000$629,911$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2424.25190 Lbs6 ft12.001,117,271$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tyson KozakLogan BrownBrendan Brisson40122
2Hunter HaightBrad LambertNate Smith30122
3Jakub BrabenecBrendan BrissonMassimo Rizzo20122
4Lukas SvejkovskyCross HanasTyson Kozak10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Hunter McDonaldSimon Lundmark40122
2Daemon HuntMac Hollowell30122
3Daemon HuntAleksi Heimosalmi20122
4Luke ReidDaemon Hunt10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tyson KozakLogan BrownBrendan Brisson60122
2Hunter HaightBrad LambertNate Smith40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Hunter McDonaldMac Hollowell60122
2Daemon HuntSimon Lundmark40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Brad LambertTyson Kozak60122
2Brendan BrissonJakub Brabenec40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Hunter McDonaldAleksi Heimosalmi60122
2Daemon HuntMac Hollowell40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Tyson Kozak60122Simon LundmarkDaemon Hunt60122
2Cross Hanas40122Hunter McDonaldLuke Reid40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Tyson KozakBrendan Brisson60122
2Brad LambertMassimo Rizzo40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Hunter McDonaldDaemon Hunt60122
2Luke ReidAleksi Heimosalmi40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tyson KozakLogan BrownBrad LambertDaemon HuntHunter McDonald
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tyson KozakLogan BrownBrad LambertDaemon HuntHunter McDonald
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Brad Lambert, Hunter Haight, Tyson KozakTyson Kozak, Hunter HaightLukas Svejkovsky
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Hardy Haman Aktell, Hunter McDonald, Daemon HuntDaemon HuntSimon Lundmark, Daemon Hunt
Tirs de pénalité
Brendan Brisson, Logan Brown, Tyson Kozak, Brad Lambert, Hunter Haight
Gardien
#1 : Domenic DiVincentiis, #2 : Ales Stezka


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
TotalDomicileVisiteur
# 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
1Admirals10001000651100010006510000000000021.0006101600142436331163230252132910132111100.00%4250.00%017639944.11%13930146.18%13730644.77%420198404242505230
2Barracuda2010000159-4000000000002010000159-410.25057120014243636516323025213461914415120.00%7357.14%017639944.11%13930146.18%13730644.77%420198404242505230
3Bruins1000000112-11000000112-10000000000010.5001120014243632716323025213165223000%10100.00%017639944.11%13930146.18%13730644.77%420198404242505230
4Comets21100000844110000006151010000023-120.500811190014243636916323025213372342556350.00%6183.33%017639944.11%13930146.18%13730644.77%420198404242505230
5Condors1010000016-5000000000001010000016-500.000112001424363201632302521332131919300.00%3233.33%017639944.11%13930146.18%13730644.77%420198404242505230
6Eagles1100000010371100000010370000000000021.00010152500142436333163230252132738245120.00%4175.00%017639944.11%13930146.18%13730644.77%420198404242505230
7Heat1010000035-2000000000001010000035-200.00034700142436326163230252132641626100.00%30100.00%017639944.11%13930146.18%13730644.77%420198404242505230
8IceHogs2110000057-2000000000002110000057-220.50058130014243636616323025213521533437228.57%9544.44%017639944.11%13930146.18%13730644.77%420198404242505230
9Monsters21100000761211000007610000000000020.5007111800142436352163230252132488656233.33%50100.00%017639944.11%13930146.18%13730644.77%420198404242505230
10Moose22000000514110000002021100000031241.00057120114243633516323025213117113311100.00%30100.00%017639944.11%13930146.18%13730644.77%420198404242505230
11Phantoms1010000047-31010000047-30000000000000.00046100014243633816323025213331014204125.00%20100.00%017639944.11%13930146.18%13730644.77%420198404242505230
12Rocket302010001114-31000100054120200000610-420.3331119300014243639616323025213732925654125.00%10370.00%117639944.11%13930146.18%13730644.77%420198404242505230
13Wild11000000422000000000001100000042221.000471100142436314163230252132514215200.00%10100.00%017639944.11%13930146.18%13730644.77%420198404242505230
14Wolves21100000660211000006600000000000020.5006915001424363761632302521340113357500.00%4175.00%017639944.11%13930146.18%13730644.77%420198404242505230
Total22810020027677-11153020014734131137000012943-14220.5007611619201142436364816323025213471171240507501326.00%621870.97%117639944.11%13930146.18%13730644.77%420198404242505230
_Since Last GM Reset22810020027677-11153020014734131137000012943-14220.5007611619201142436364816323025213471171240507501326.00%621870.97%117639944.11%13930146.18%13730644.77%420198404242505230
_Vs Conference1658010024856-87320100125196926000012337-14140.43848741220014243634851632302521334513717838338923.68%461567.39%117639944.11%13930146.18%13730644.77%420198404242505230
_Vs Division7470100130181233201000188104150000112102110.78630477701142436317916323025213144496713616531.25%21861.90%017639944.11%13930146.18%13730644.77%420198404242505230

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2222W27611619264847117124050701
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
2281020027677
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
115320014734
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
113700012943
Derniers 10 matchs
WLOTWOTL SOWSOL
540001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
501326.00%621870.97%1
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
163230252131424363
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
17639944.11%13930146.18%13730644.77%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
420198404242505230


Derniers matchs 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
19Senators3IceHogs2WSommaire du match
216Senators2Barracuda3LXXSommaire du match
333Comets1Senators6WSommaire du match
551Monsters4Senators7WSommaire du match
771Wolves5Senators2LSommaire du match
989Senators3Barracuda6LSommaire du match
10104Phantoms7Senators4LSommaire du match
11121Senators3Rocket6LSommaire du match
12134Wolves1Senators4WSommaire du match
13151Senators2IceHogs5LSommaire du match
14161Senators3Rocket4LSommaire du match
15177Eagles3Senators10WSommaire du match
17197Monsters2Senators0LSommaire du match
18209Senators2Comets3LSommaire du match
19225Admirals5Senators6WXSommaire du match
20243Senators1Condors6LSommaire du match
22259Rocket4Senators5WXSommaire du match
24279Senators4Wild2WSommaire du match
25290Bruins2Senators1LXXSommaire du match
26307Senators3Heat5LSommaire du match
27321Senators3Moose1WSommaire du match
28334Moose0Senators2WSommaire du match
30356Checkers-Senators-
31374Senators-Thunderbirds-
32387Phantoms-Senators-
33400Senators-Roadrunners-
34415Islanders-Senators-
35432Thunderbirds-Senators-
37447Senators-Admirals-
38468Silver Knights-Senators-
39475Senators-Monsters-
40492Senators-Islanders-
41510Reign-Senators-
42526Monsters-Senators-
43536Senators-Penguins-
45561Griffins-Senators-
46575Senators-Canucks-
47592Americans-Senators-
48612Senators-Condors-
49625Senators-Phantoms-
50633Marlies-Senators-
51653Senators-Silver Knights-
52665Eagles-Senators-
53683Admirals-Senators-
54701Senators-Gulls-
56716Gulls-Senators-
57733Senators-Americans-
58745Senators-Crunch-
59756Wild-Senators-
60774Senators-Stars-
61784Senators-Bears-
63797Bears-Senators-
65819Penguins-Senators-
66831Senators-Rocket-
67849Canucks-Senators-
68863Senators-Wolf Pack-
70879Wolf Pack-Senators-
71897Senators-IceHogs-
72910Heat-Senators-
74925Senators-Comets-
75941Rocket-Senators-
77961Senators-Bruins-
78967Senators-Wolves-
79983Crunch-Senators-
811002Senators-IceHogs-
821013Senators-Barracuda-
831025Condors-Senators-
841045Barracuda-Senators-
861064Barracuda-Senators-
871077Senators-Barracuda-
881087Senators-Checkers-
901105Stars-Senators-
911127Condors-Senators-
921134Senators-Marlies-
931150Senators-Griffins-
951167IceHogs-Senators-
961177Senators-Bruins-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
971196IceHogs-Senators-
981209Senators-Eagles-
1001223Senators-Wolves-
1011234Wolves-Senators-
1031258Comets-Senators-
1051284Comets-Senators-
1061290Senators-Monsters-
1081308Roadrunners-Senators-
1091315Senators-Reign-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance15,6698,447
Assistance PCT71.22%76.79%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
32 2192 - 73.08% 91,448$1,005,927$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
940,728$ 2,681,450$ 2,681,450$ 1,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
23,942$ 681,816$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
2,926,333$ 83 32,870$ 2,728,210$




Senators Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Senators Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Senators Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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

Senators Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Senators Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA