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Senators
GP: 24 | W: 12 | L: 9 | OTL: 3 | P: 27
GF: 106 | GA: 104 | PP%: 27.27% | PK%: 72.73%
DG: Didier Theodore | Morale : 39 | Moyenne d’équipe : 65
Prochains matchs #320 vs Crunch
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Centre de jeu
Gulls
11-10-4, 26pts
3
FINAL
2 Senators
12-9-3, 27pts
Team Stats
L1SéquenceW1
5-5-2Fiche domicile5-7-0
6-5-2Fiche domicile7-2-3
6-3-1Derniers 10 matchs5-4-1
3.92Buts par match 4.42
4.04Buts contre par match 4.33
22.97%Pourcentage en avantage numérique27.27%
79.05%Pourcentage en désavantage numérique72.73%
Senators
12-9-3, 27pts
6
FINAL
4 Gulls
11-10-4, 26pts
Team Stats
W1SéquenceL1
5-7-0Fiche domicile5-5-2
7-2-3Fiche domicile6-5-2
5-4-1Derniers 10 matchs6-3-1
4.42Buts par match 3.92
4.33Buts contre par match 4.04
27.27%Pourcentage en avantage numérique22.97%
72.73%Pourcentage en désavantage numérique79.05%
Crunch
11-8-5, 27pts
Jour 63
Senators
12-9-3, 27pts
Statistiques d’équipe
OTL1SéquenceW1
6-3-3Fiche domicile5-7-0
5-5-2Fiche visiteur7-2-3
6-2-210 derniers matchs5-4-1
3.38Buts par match 4.42
3.71Buts contre par match 4.42
16.35%Pourcentage en avantage numérique27.27%
82.83%Pourcentage en désavantage numérique72.73%
Senators
12-9-3, 27pts
Jour 65
Barracuda
14-10-1, 29pts
Statistiques d’équipe
W1SéquenceSOW1
5-7-0Fiche domicile8-3-1
7-2-3Fiche visiteur6-7-0
5-4-110 derniers matchs5-5-0
4.42Buts par match 4.04
4.33Buts contre par match 4.04
27.27%Pourcentage en avantage numérique15.09%
72.73%Pourcentage en désavantage numérique78.50%
Admirals
10-10-4, 24pts
Jour 68
Senators
12-9-3, 27pts
Statistiques d’équipe
W1SéquenceW1
4-6-2Fiche domicile5-7-0
6-4-2Fiche visiteur7-2-3
6-3-110 derniers matchs5-4-1
4.42Buts par match 4.42
4.63Buts contre par match 4.42
22.77%Pourcentage en avantage numérique27.27%
79.59%Pourcentage en désavantage numérique72.73%
Meneurs d'équipe
Buts
Kiefer Sherwood
15
Passes
Radek Faksa
28
Points
Radek Faksa
36
Plus/Moins
Jonas Siegenthaler
12
Victoires
David Rittich
9
Pourcentage d’arrêts
David Rittich
0.88

Statistiques d’équipe
Buts pour
106
4.42 GFG
Tirs pour
842
35.08 Avg
Pourcentage en avantage numérique
27.3%
30 GF
Début de zone offensive
38.0%
Buts contre
104
4.33 GAA
Tirs contre
764
31.83 Avg
Pourcentage en désavantage numérique
72.7%%
24 GA
Début de la zone défensive
34.9%
Informations de l'équipe

Directeur généralDidier Theodore
EntraîneurMario Lemieux
DivisionJohn-Ahearne
ConférenceRobert-Lebel
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,832
Billets de saison300


Informations de la formation

Équipe Pro28
Équipe Mineure21
Limite contact 49 / 250
Espoirs0


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
1Radek Faksa (R)X100.007345838177737478797376657369573655740253950,000$
2Marc Michaelis (R)X100.007739767168776471687775726754514652710241750,000$
3Kiefer Sherwood (R)X100.007043756781646675746588617049473852700241900,000$
4Carl Grundstrom (R)X100.007252877171767070696971667350495944690221900,000$
5Logan O'Connor (R)X100.007038827072646476696968577349494542670233500,000$
6Vitaly Abramov (R)X100.005635797672676573606877537146465445670211500,000$
7Anton Karlsson (R)X100.006526697865685876607065687347474120660232800,000$
8Arttu Ruotsalainen (R)X100.005237736962726768575984576847474544650221600,000$
9Axel Jonsson-Fjallby (R)X100.007340816262605572737167635946465548650212500,000$
10Bryce Kindopp (R)X100.006133655966566160605766596143436043590204500,000$
11Akil Thomas (R)X100.007346595668496557466160485641415831560191500,000$
12Tyler Angle (R)X100.005444586452676161595652455942436341550192500,000$
13Zac Leslie (R)X100.007947737972767475526969827176533624740252800,000$
14Artem Zub (R)X100.007055848077747980517262766472543846740242975,000$
15Jesse Graham (R)X100.005445758070656974527164725451493151670251800,000$
16Jonas Siegenthaler (R)X100.006326856668607361387054805248474350670223600,000$
17Mason Geertsen (R)X100.007245786467597968546257706252513650660241500,000$
18Martin Fehervary (R)X100.006140727559556580438556624845456251650201500,000$
19Gustav Forsling (R)X100.007134766358706163446670605746464344630231500,000$
20Alec Regula (R)X100.006142635755616066465155674441416048590191500,000$
Rayé
1C.J Suess (R)X99.597931787581716774657278676854544137710251850,000$
2Adam Mascherin (R)X100.005441667354605871636267577546466123630212500,000$
3Cliff Pu (R)X100.005726725464655565586470406743434122590211500,000$
4Ivan Morozov (R)X100.005338615761505958545560474841415820540191500,000$
5Jett Woo (R)X100.005523636145526164336841574043415229550192500,000$
MOYENNE D’ÉQUIPE99.98653973686664656957666662625047484065
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
1David Rittich98.006865856362828459558474595652496902721,500,000$
2Arvid Soderblom100.00596678545666725759766244436456620204600,000$
Rayé
1Olivier Rodrigue100.00437054555457595970574741416234570193500,000$
MOYENNE D’ÉQUIPE99.3357677257576872586172614847594663
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mario Lemieux58697272515555CAN5511,000,000$


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
1Radek FaksaSenators (Ott)C19828362201029388321529.64%1242422.361151620730005551255.71%6391912011.6923101130
2Kiefer SherwoodSenators (Ott)RW24151328-4240332661123324.59%949020.46961521970000191051.22%41134001.1402000101
3C.J SuessSenators (Ott)LW21111627-5140523283255213.25%1345821.856101615840003603038.64%44259001.1812000200
4Christoph BertschySenateursC17101727780283277233512.99%532819.330334551013351249.57%347143011.6412000411
5Marc MichaelisSenators (Ott)LW241116275140463380123813.75%1445819.1243711750001421061.29%31126011.1802000102
6Carl GrundstromSenators (Ott)RW2411718-155272848133322.92%540817.02336574000060048.48%3354000.8802010011
7Vitaly AbramovSenators (Ott)LW248816-340182157193114.04%729312.240001100000110245.45%11102001.0900000111
8Jonas SiegenthalerSenators (Ott)D240141412602629161170%3749320.56033267000147000%0118000.5700000010
9Jesse GrahamSenators (Ott)D2421012-220011453425185.88%3455923.31022392000162200%01020000.4300000000
10Artem ZubSenators (Ott)D234812-58037325129157.84%2959926.06314998011168100%01821000.4000000100
11Arttu RuotsalainenSenators (Ott)C245611-1410018243552114.29%1031813.27123130000090043.20%20634000.6900000001
12Axel Jonsson-FjallbySenators (Ott)LW2473103752164272516.67%31847.7000000000001066.67%695001.0800100001
13Mason GeertsenSenators (Ott)D2417861152428148137.14%1341717.42123149000138000%0412000.3800001000
14Zac LeslieSenators (Ott)D9268-41001921209810.00%2223225.85123537000019000%076000.6900000010
15Logan O'ConnorSenators (Ott)RW24358-24026215319295.66%827211.3700005000010050.00%1268000.5900000000
16Bryce KindoppSenators (Ott)RW243473402562372013.04%21857.7400000000000120.00%515000.7500000001
17Martin FehervarySenators (Ott)D24156-710051517565.88%1124910.400000100006000%016000.4800000001
18Tyler AngleSenators (Ott)C20112240111051520.00%01517.5500000000000044.07%5901000.2600000001
19Akil ThomasSenators (Ott)C141015802311102710.00%315210.9300001000040035.94%6410000.1300000000
20Anton KarlssonSenators (Ott)LW3000-200229120%03712.470000000001000%12100000000000
21Gustav ForslingSenators (Ott)D24000-44041311610%122158.9700002000012000%01600000000000
22Alec RegulaSenators (Ott)D22000160442130%5974.430000000003000%00200000000000
23Jett WooSenators (Ott)D10000-200200000%2434.300000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne470104174278-92012549147783126145412.52%256707615.06295281988581121650911750.37%1499162155030.7941321211811
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
1David RittichSenators (Ott)209620.8803.8110390066550254210.6258186121
2Arvid SoderblomSenators (Ott)103310.8404.884180034213111200.5717618000
Statistiques d’équipe totales ou en moyenne3012930.8694.1214580010076336541152424121


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 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 Non Activé Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 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 MascherinSenators (Ott)LW211998-01-01Yes205 Lbs5 ft10NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Akil ThomasSenators (Ott)C192000-01-01Yes195 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Alec RegulaSenators (Ott)D192000-01-01Yes208 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Anton KarlssonSenators (Ott)LW231996-01-01Yes194 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm800,000$558,416$0$0$No800,000$--------No--------
Artem ZubSenators (Ott)D241995-01-01Yes198 Lbs6 ft2NoNoTrade2024-08-06NoNo2FalseFalsePro & Farm975,000$680,569$0$0$No975,000$--------No--------
Arttu RuotsalainenSenators (Ott)C221997-01-01Yes181 Lbs5 ft8NoNoN/ANoNo1FalseFalsePro & Farm600,000$418,812$0$0$No------------------
Arvid SoderblomSenators (Ott)G201999-01-01No180 Lbs6 ft3NoNoFree AgentNoNo42024-08-21FalseFalsePro & Farm600,000$418,812$0$0$No600,000$600,000$600,000$------NoNoNo------
Axel Jonsson-FjallbySenators (Ott)LW211998-01-01Yes190 Lbs6 ft1NoNoTrade2024-09-07NoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Bryce KindoppSenators (Ott)RW201999-01-01Yes185 Lbs6 ft1NoNoFree AgentNoNo42024-08-21FalseFalsePro & Farm500,000$349,010$0$0$No500,000$500,000$500,000$------NoNoNo------
C.J SuessSenators (Ott)LW251994-01-01Yes190 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm850,000$593,317$0$0$No------------------
Carl GrundstromSenators (Ott)RW221997-01-01Yes194 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm900,000$628,218$0$0$No------------------
Cliff PuSenators (Ott)RW211998-01-01Yes185 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
David RittichSenators (Ott)G271992-01-01No206 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm1,500,000$1,047,030$0$0$No2,500,000$--------No--------
Gustav ForslingSenators (Ott)D231996-01-01Yes186 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Ivan MorozovSenators (Ott)C192000-01-01Yes178 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Jesse GrahamSenators (Ott)D251994-01-01Yes170 Lbs5 ft11NoNoTrade2024-08-08NoNo1FalseFalsePro & Farm800,000$558,416$0$0$No------------------
Jett WooSenators (Ott)D192000-01-01Yes190 Lbs6 ft0NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Jonas SiegenthalerSenators (Ott)D221997-01-01Yes210 Lbs6 ft3NoNoFree AgentNoNo32024-08-21FalseFalsePro & Farm600,000$418,812$0$0$No600,000$600,000$-------NoNo-------
Kiefer SherwoodSenators (Ott)RW241995-01-01Yes194 Lbs6 ft0NoNoTrade2024-09-07NoNo1FalseFalsePro & Farm900,000$628,218$0$0$No------------------
Logan O'ConnorSenators (Ott)RW231996-01-01Yes174 Lbs6 ft0NoNoTrade2024-08-03NoNo3FalseFalsePro & Farm500,000$349,010$0$0$No500,000$500,000$-------NoNo-------
Marc MichaelisSenators (Ott)LW241995-01-01Yes187 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm750,000$523,515$0$0$No------------------
Martin FehervarySenators (Ott)D201999-01-01Yes199 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Mason GeertsenSenators (Ott)D241995-01-01Yes185 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Olivier RodrigueSenators (Ott)G192000-01-01No158 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm500,000$349,010$0$0$No500,000$500,000$-------NoNo-------
Radek FaksaSenators (Ott)C251994-01-01Yes200 Lbs6 ft2NoNoFree Agent2024-08-06NoNo32024-08-21FalseFalsePro & Farm950,000$663,119$0$0$No950,000$950,000$-------NoNo-------
Tyler AngleSenators (Ott)C192000-01-01Yes165 Lbs5 ft10NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Vitaly AbramovSenators (Ott)LW211998-01-01Yes181 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Zac LeslieSenators (Ott)D251994-01-01Yes185 Lbs6 ft0NoNoFree AgentNoNo22024-10-18FalseFalsePro & Farm800,000$558,416$0$0$No800,000$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2822.00188 Lbs6 ft11.79661,607$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Marc MichaelisRadek FaksaKiefer Sherwood40122
2Vitaly AbramovArttu RuotsalainenCarl Grundstrom30122
3Anton KarlssonAkil ThomasLogan O'Connor20122
4Axel Jonsson-FjallbyTyler AngleBryce Kindopp10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zac LeslieArtem Zub40122
2Jesse GrahamJonas Siegenthaler30122
3Mason GeertsenMartin Fehervary20122
4Gustav ForslingAlec Regula10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Marc MichaelisRadek FaksaKiefer Sherwood60014
2Vitaly AbramovArttu RuotsalainenCarl Grundstrom40014
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zac LeslieArtem Zub60014
2Jesse GrahamJonas Siegenthaler40014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Radek FaksaMarc Michaelis60140
2Arttu RuotsalainenVitaly Abramov40140
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zac LeslieArtem Zub60140
2Jesse GrahamJonas Siegenthaler40140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Radek Faksa60140Zac LeslieArtem Zub60140
2Arttu Ruotsalainen40140Jesse GrahamJonas Siegenthaler40140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Radek FaksaMarc Michaelis60023
2Arttu RuotsalainenVitaly Abramov40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zac LeslieArtem Zub60023
2Jesse GrahamJonas Siegenthaler40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Marc MichaelisRadek FaksaKiefer SherwoodZac LeslieArtem Zub
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Marc MichaelisRadek FaksaKiefer SherwoodZac LeslieArtem Zub
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Logan O'Connor, Vitaly Abramov, Anton KarlssonLogan O'Connor, Vitaly AbramovLogan O'Connor
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Martin Fehervary, Gustav Forsling, Alec RegulaMartin FehervaryMartin Fehervary, Gustav Forsling
Tirs de pénalité
Radek Faksa, Marc Michaelis, Kiefer Sherwood, Carl Grundstrom, Logan O'Connor
Gardien
#1 : Arvid Soderblom, #2 : David Rittich, #3 : 0
Lignes d’attaque personnalisées en prolongation
Radek Faksa, Marc Michaelis, Kiefer Sherwood, Carl Grundstrom, Logan O'Connor, Vitaly Abramov, Vitaly Abramov, Anton Karlsson, Axel Jonsson-Fjallby, Arttu Ruotsalainen, Bryce Kindopp
Lignes de défense personnalisées en prolongation
Zac Leslie, Artem Zub, Jesse Graham, Jonas Siegenthaler, Mason Geertsen


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
1Admirals4310000025205211000001192220000001411360.7502541660037313651442802962552512548428619842.11%16381.25%130158951.10%27654051.11%20742049.29%525299503224431215
2Americans312000001113-21010000026-42110000097220.333111930003731365972802962552510129145021523.81%7271.43%030158951.10%27654051.11%20742049.29%525299503224431215
3Canucks1010000035-2000000000001010000035-200.0003580037313653928029625525351116202150.00%3233.33%030158951.10%27654051.11%20742049.29%525299503224431215
4Checkers11000000413110000004130000000000021.0004610003731365302802962552528128254250.00%4175.00%030158951.10%27654051.11%20742049.29%525299503224431215
5Eagles1000000145-1000000000001000000145-110.5004711003731365292802962552527182255120.00%10100.00%030158951.10%27654051.11%20742049.29%525299503224431215
6Gulls3110100010821010000023-12100100085340.6671016260037313651112802962552595328448112.50%40100.00%030158951.10%27654051.11%20742049.29%525299503224431215
7Icehogs301000021317-41010000035-2200000021012-220.3331322351037313651122802962552511042307220630.00%15846.67%030158951.10%27654051.11%20742049.29%525299503224431215
8Little Stars2100001013672100001013670000000000041.0001320330037313657928029625525651623556116.67%9366.67%030158951.10%27654051.11%20742049.29%525299503224431215
9Marlies1010000034-11010000034-10000000000000.000358003731365312802962552532618163133.33%9277.78%030158951.10%27654051.11%20742049.29%525299503224431215
10Penguins11000000651000000000001100000065121.000691500373136540280296255252614625400.00%3166.67%030158951.10%27654051.11%20742049.29%525299503224431215
11Phantoms11000000321000000000001100000032121.000369003731365402802962552535128182150.00%40100.00%030158951.10%27654051.11%20742049.29%525299503224431215
12Thunderbirds21100000711-421100000711-40000000000020.500711180037313655428029625525591122401218.33%11281.82%030158951.10%27654051.11%20742049.29%525299503224431215
13Wolfpack1010000047-31010000047-30000000000000.000481200373136536280296255252674194250.00%20100.00%030158951.10%27654051.11%20742049.29%525299503224431215
Total241090101310610421247000104952-312620100357525270.563106175281103731365842280296255257642582014951103027.27%882472.73%130158951.10%27654051.11%20742049.29%525299503224431215
_Since Last GM Reset241090101310610421247000104952-312620100357525270.563106175281103731365842280296255257642582014951103027.27%882472.73%130158951.10%27654051.11%20742049.29%525299503224431215
_Vs Conference15660100265641615000002127-69510100244377160.5336510917410373136553528029625525498169120286732230.14%551572.73%130158951.10%27654051.11%20742049.29%525299503224431215
_Vs Division1044000024950-1413000001620-46310000233303100.50049821311037313653532802962552533611986208601931.67%381365.79%130158951.10%27654051.11%20742049.29%525299503224431215

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2427W110617528184276425820149510
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
241091013106104
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
124700104952
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
126210035752
Derniers 10 matchs
WLOTWOTL SOWSOL
440011
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1103027.27%882472.73%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
280296255253731365
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
30158951.10%27654051.11%20742049.29%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
525299503224431215


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
13Admirals3Senators7WR1Sommaire du match
415Senators3Phantoms2WSommaire du match
625Senators6Admirals4WR1Sommaire du match
942Marlies4Senators3LSommaire du match
1157Senators6Americans2WR1Sommaire du match
1570Americans6Senators2LSommaire du match
1887Thunderbirds5Senators6WSommaire du match
2097Senators4Icehogs5LXXR1Sommaire du match
22110Senators3Americans5LR1Sommaire du match
24124Admirals6Senators4LSommaire du match
26134Senators2Gulls1WXSommaire du match
28143Icehogs5Senators3LR1Sommaire du match
30155Senators8Admirals7WSommaire du match
32169Senators6Icehogs7LXXR1Sommaire du match
34176Thunderbirds6Senators1LSommaire du match
38197Little Stars1Senators7WSommaire du match
40207Senators3Canucks5LSommaire du match
44224Little Stars5Senators6WXXSommaire du match
48240Senators6Penguins5WSommaire du match
50252Checkers1Senators4WSommaire du match
52267Senators4Eagles5LXXSommaire du match
55277Wolfpack7Senators4LSommaire du match
59296Gulls3Senators2LSommaire du match
61307Senators6Gulls4WSommaire du match
63320Crunch-Senators-
65331Senators-Barracuda-
68348Admirals-Senators-
71366Senators-Americans-
72374Eagles-Senators-
75384Senators-Checkers-
77395Senators-Punishers-
79405Punishers-Senators-
81416Senators-Rockets-
83428Islander-Senators-
87450Senators-Gulls-
89459Phantoms-Senators-
92474Senators-Griffins-
94481Canucks-Senators-
96496Senators-Icehogs-
100510Icehogs-Senators-
105530Rockets-Senators-
108548Senators-Bears-
109558Griffins-Senators-
113578Thunderbirds-Senators-
115588Senators-Admirals-
118604Comets-Senators-
119613Senators-Marlies-
124631Firebirds-Senators-
126644Senators-Thunderbirds-
128656Rockets-Senators-
129663Senators-Little Stars-
132681Wranglers-Senators-
134690Senators-Canucks-
136707Barracuda-Senators-
138720Senators-Islander-
140728Senators-Wolfpack-
142737Moose-Senators-
145760Icehogs-Senators-
149783Griffins-Senators-
152793Senators-Firebirds-
154809Condors-Senators-
156817Senators-Comets-
158827Senators-Phantoms-
160837Gulls-Senators-
161842Senators-Condors-
163853Senators-Crunch-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
166870Americans-Senators-
168878Senators-Phantoms-
171892Senators-Thunderbirds-
172897Penguins-Senators-
173905Senators-Moose-
176922Barracuda-Senators-
180945Bears-Senators-
181951Senators-Moose-
185969Americans-Senators-
187978Senators-Condors-
189987Senators-Wranglers-
1931005Marlies-Senators-
1961023Senators-Wranglers-
2001036Marlies-Senators-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance22,76411,220
Assistance PCT94.85%93.50%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
28 2832 - 94.40% 178,700$2,144,394$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
862,611$ 1,852,500$ 1,777,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,171$ 560,620$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
5,003,586$ 141 14,121$ 1,991,061$




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