Version obsolète du STHS! Veuillez mettre à jour votre version!
Connexion

Senators
GP: 80 | W: 35 | L: 37 | OTL: 8 | P: 78
GF: 347 | GA: 366 | PP%: 26.01% | PK%: 76.62%
DG: Didier Theodore | Morale : 25 | Moyenne d’équipe : 65
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Centre de jeu
Reign
41-32-7, 89pts
6
FINAL
4 Senators
35-37-8, 78pts
Team Stats
L1StreakL3
21-15-4Home Record19-18-3
20-17-3Away Record16-19-5
5-3-2Last 10 Games4-6-0
4.25Buts par match 4.34
4.18Buts contre par match 4.58
22.94%Pourcentage en avantage numérique26.01%
78.81%Pourcentage en désavantage numérique76.62%
Rocket
38-33-9, 85pts
8
FINAL
3 Senators
35-37-8, 78pts
Team Stats
W2StreakL3
21-15-4Home Record19-18-3
17-18-5Away Record16-19-5
6-4-0Last 10 Games4-6-0
4.46Buts par match 4.34
4.43Buts contre par match 4.58
20.70%Pourcentage en avantage numérique26.01%
75.00%Pourcentage en désavantage numérique76.62%
Meneurs d'équipe
Buts
Zachary Sanford
55
Passes
Zachary Sanford
73
Points
Zachary Sanford
128
Plus/Moins
Jacob De La Rose
7
Victoires
Eric Comrie
26
Pourcentage d’arrêts
Eric Comrie
0.878

Statistiques d’équipe
Buts pour
347
4.34 GFG
Tirs pour
2712
33.90 Avg
Pourcentage en avantage numérique
26.0%
77 GF
Début de zone offensive
36.9%
Buts contre
366
4.58 GAA
Tirs contre
2597
32.46 Avg
Pourcentage en désavantage numérique
76.6%%
72 GA
Début de la zone défensive
34.7%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,767
Billets de saison300


Informations de la formation

Équipe Pro31
Équipe Mineure23
Limite contact 54 / 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
1Tyler PitlickX100.007537827577757373747474676974613534720261950,000$
2Zachary Sanford (R)X100.007322718169817280687374687557534745720231950,000$
3Zemgus Girgensons (R)X100.008034827376787172757478617457504436720231950,000$
4Oliver Bjorkstrand (R)X100.007330887773747972677087566855465746710221950,000$
5Christoph Bertschy (R)X100.006527818074796873707171697955474645700232750,000$
6Jacob De La Rose (R)X100.006923856876837061687271797155465434700222850,000$
7Brendan Perlini (R)X100.006822827675717470646684567247445545690211800,000$
8C.J Suess (R)X100.007331757275645970657076637048504945680231800,000$
9Johan LarssonX100.006637747465746970747673536350473537680251700,000$
10Kevin Rooney (R)X100.006545757268727567787071617352523835680241500,000$
11Grant Besse (R)X100.005832777062716269706366627147493345640231500,000$
12Michael McCarron (R)X100.007746696980578165666865526745454534640224600,000$
13Vitaly Abramov (R)X100.005035747167626069536174416742426523610191500,000$
14Arttu Ruotsalainen (R)X100.004934676158696666515380506344445618600201500,000$
15David Kase (R)X100.006333615857586458605865456442424822570202500,000$
16Cliff Pu (R)X100.005423685161595162545867336341415319550191500,000$
17Bryce Kindopp (R)X100.005732585361515654534959515540407419530182500,000$
18Michael Pezzetta (R)X100.006948614964446548554748345141415618490191500,000$
19Dmitry Sinitsyn (R)X100.007025848072728278447859806161494942730231975,000$
20Jordan Schmaltz (R)X100.007137817674777573537266837067524326730241950,000$
21Keegan Lowe (R)X100.007027777378856770537469745962504245710241500,000$
22Joonas Lyytinen (R)X100.007029796864566363416847795249484723660221500,000$
23Nikita Nesterov (R)X100.006625797465716666477066666548484217660241500,000$
24Mason Geertsen (R)X100.006945785963547663485751675647464345630221500,000$
25Jonas Siegenthaler (R)X100.005726845860576751286144754243435242610202500,000$
Rayé
1Gustav Forsling (R)X100.006833735752666258376065535243435419580211250,000$
MOYENNE D’ÉQUIPE100.00663276686868686658666761645047493365
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
1Eric Comrie100.00728374747676727580766155515022740221800,000$
2Garret Sparks100.00767388656872776167827153494041700242950,000$
Rayé
1David Rittich (R)100.00676585615781845557857651506425680254950,000$
2Scott Wedgewood100.00656470646568686163696048492920640253750,000$
3Olle Eriksson Ek (R)100.00544860545855505449515540406420520182500,000$
MOYENNE D’ÉQUIPE100.0067677564657070616373654948492666
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mario Lemieux58697272515555CAN5311,000,000$


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
1Zachary SanfordSenators (Ott)LW805573128-1412201398935612922315.45%48175421.9312273964236224101996142.22%1358235011.4617000795
2Christoph BertschySenators (Ott)C804360103-284401121872699514215.99%53177122.1518244248221134142164148.06%25513634121.1601000439
3Tyler PitlickSenators (Ott)RW75465096-21220118802526715618.25%29142719.04161935351850000315147.93%1214826021.3426000651
4Oliver BjorkstrandSenators (Ott)RW773740774120100932578214714.40%34128816.738917291900002126254.24%594917021.2023000614
5Jacob De La RoseSenators (Ott)C77214061780117132117326317.95%32142318.493811818814581643149.73%11261722000.8600000133
6Brendan PerliniSenators (Ott)LW80332356428098772296712214.41%23118414.8134797620251312042.00%505413000.9501000233
7Zemgus GirgensonsSenators (Ott)LW57222547-530092821685910813.10%1899417.44448191271015672045.59%683813000.9524000142
8Dmitry SinitsynSenators (Ott)D6983846-241809213813667525.88%132187527.186814192170004228000.00%04161000.4900000033
9Keegan LoweSenators (Ott)D8043539456010811110945413.67%112181722.72066172120221197000.00%02953000.4300000001
10C.J SuessSenators (Ott)LW8018183653208042108527616.67%236908.63011061011311136.84%193012001.0400000101
11Grant BesseSenators (Ott)RW80122436-82206060100305912.00%1089911.24000225000002051.72%291213000.8000000101
12Kevin RooneySenators (Ott)C801323365140776813854719.42%2390511.32000060003420155.29%4162614000.8000000222
13Jordan SchmaltzSenators (Ott)D6023032-20395691129136362.20%109159226.54291192120001184000.00%03152000.4000100100
14Nikita NesterovSenators (Ott)D6621820-628043794821144.17%53120918.3314581130000113000.00%02029000.3300000010
15Mason GeertsenSenators (Ott)D8021719640044744328144.65%47108513.57000220000062000.00%0314000.3500000000
16Joonas LyytinenSenators (Ott)D5621618-524039754424204.55%52103918.5724661060110104000.00%0631000.3500000010
17Jonas SiegenthalerSenators (Ott)D7801313-114014503613160.00%4484010.7700003000026000.00%0128000.3100000000
18Michael McCarronSenators (Ott)C56516-1218039316117388.20%44197.4900000000010054.72%15972000.2900000001
19Johan LarssonSenators (Ott)LW74235-50010144918234.08%12042.7600012000030050.00%4105000.4900000000
20David KaseSenators (Ott)RW34224-52001910126916.67%62788.2000003000000033.33%602000.2900000000
21Vitaly AbramovSenators (Ott)LW5313410043124108.33%21502.84000000000000100.00%152000.5300000001
22Gustav ForslingSenators (Ott)D450225100927300.00%32375.280000300004000.00%012000.1700000000
23Arttu RuotsalainenSenators (Ott)C32101-5406733733.33%11103.4400000000000031.82%2221000.1800000000
24Cliff PuSenators (Ott)RW10000000000000.00%000.060000000000000.00%000000.00%00000000
25Bryce KindoppSenators (Ott)RW23000-320812010.00%1391.7100000000000050.00%201000.00%00000000
Statistiques d’équipe totales ou en moyenne1582331554885-1216075149716172647952144812.50%8602324114.697512720227621628122054182431849.01%4768548482170.76722100323537
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
1Eric ComrieSenators (Ott)54261730.8783.952935001931585761410.909115120103
2Garret SparksSenators (Ott)59232170.8644.373104202261660854200.450205226101
3David RittichSenators (Ott)2161000.8424.978932074469220100.00%01446100
Statistiques d’équipe totales ou en moyenne1345548100.8674.2769334049337141835713111792304


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 restantPlafond salarial 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 10Link
Arttu RuotsalainenSenators (Ott)C201997-01-01Yes181 Lbs5 ft8NoNoNo1Pro & Farm500,000$0$0$NoLien
Brendan PerliniSenators (Ott)LW211996-01-01Yes211 Lbs6 ft3NoNoNo1Pro & Farm800,000$0$0$NoLien
Bryce KindoppSenators (Ott)RW181999-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
C.J SuessSenators (Ott)LW231994-01-01Yes190 Lbs5 ft11NoNoNo1Pro & Farm800,000$0$0$NoLien
Christoph BertschySenators (Ott)C231994-01-01Yes182 Lbs5 ft10NoNoNo2Pro & Farm750,000$0$0$No750,000$Lien
Cliff PuSenators (Ott)RW191998-01-01Yes185 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLien
David KaseSenators (Ott)RW201997-01-01Yes169 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
David RittichSenators (Ott)G251992-01-01Yes206 Lbs6 ft3NoNoNo4Pro & Farm950,000$0$0$No950,000$1,500,000$2,500,000$Lien
Dmitry SinitsynSenators (Ott)D231994-01-01Yes200 Lbs6 ft2NoNoNo1Pro & Farm975,000$0$0$No
Eric ComrieSenators (Ott)G221995-01-01No185 Lbs6 ft1NoNoNo1Pro & Farm800,000$0$0$NoLien
Garret SparksSenators (Ott)G241993-01-01No207 Lbs6 ft2NoNoNo2Pro & Farm950,000$0$0$No950,000$
Grant BesseSenators (Ott)RW231994-01-01Yes185 Lbs5 ft10NoNoNo1Pro & Farm500,000$0$0$NoLien
Gustav ForslingSenators (Ott)D211996-01-01Yes186 Lbs6 ft0NoNoNo1Pro & Farm250,000$0$0$NoLien
Jacob De La RoseSenators (Ott)C221995-01-01Yes185 Lbs6 ft2NoNoNo2Pro & Farm850,000$0$0$No850,000$Lien
Johan LarssonSenators (Ott)LW251992-01-01No206 Lbs5 ft11NoNoNo1Pro & Farm700,000$0$0$No
Jonas SiegenthalerSenators (Ott)D201997-01-01Yes210 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Joonas LyytinenSenators (Ott)D221995-01-01Yes189 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$NoLien
Jordan SchmaltzSenators (Ott)D241993-01-01Yes180 Lbs6 ft0NoNoNo1Pro & Farm950,000$0$0$NoLien
Keegan LoweSenators (Ott)D241993-01-01Yes200 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$No
Kevin RooneySenators (Ott)C241993-01-01Yes190 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLien
Mason GeertsenSenators (Ott)D221995-01-01Yes185 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$NoLien
Michael McCarronSenators (Ott)C221995-01-01Yes185 Lbs6 ft5NoNoNo4Pro & Farm600,000$0$0$No600,000$600,000$600,000$Lien
Michael PezzettaSenators (Ott)LW191998-01-01Yes205 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$NoLien
Nikita NesterovSenators (Ott)D241993-01-01Yes191 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Oliver BjorkstrandSenators (Ott)RW221995-01-01Yes185 Lbs5 ft11NoNoNo1Pro & Farm950,000$0$0$NoLien
Olle Eriksson EkSenators (Ott)G181999-01-01Yes189 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Scott WedgewoodSenators (Ott)G251992-01-01No190 Lbs6 ft2NoNoNo3Pro & Farm750,000$0$0$No750,000$950,000$
Tyler PitlickSenators (Ott)RW261991-01-01No202 Lbs6 ft0NoNoNo1Pro & Farm950,000$0$0$No
Vitaly AbramovSenators (Ott)LW191998-01-01Yes181 Lbs5 ft10NoNoNo1Pro & Farm500,000$0$0$NoLien
Zachary SanfordSenators (Ott)LW231994-01-01Yes185 Lbs6 ft3NoNoNo1Pro & Farm950,000$0$0$NoLien
Zemgus GirgensonsSenators (Ott)LW231994-01-01Yes186 Lbs6 ft1NoNoNo1Pro & Farm950,000$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3122.13191 Lbs6 ft11.48675,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Zachary SanfordChristoph BertschyTyler Pitlick40023
2Zemgus GirgensonsJacob De La RoseOliver Bjorkstrand30122
3Brendan PerliniKevin RooneyGrant Besse20122
4C.J SuessMichael McCarronDavid Kase10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dmitry SinitsynJordan Schmaltz40023
2Keegan LoweJoonas Lyytinen30122
3Nikita NesterovMason Geertsen20122
4Jonas SiegenthalerDmitry Sinitsyn10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Zachary SanfordChristoph BertschyTyler Pitlick50023
2Zemgus GirgensonsJacob De La RoseOliver Bjorkstrand50023
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dmitry SinitsynJordan Schmaltz60023
2Keegan LoweJoonas Lyytinen40023
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Christoph BertschyZachary Sanford60032
2Jacob De La RoseZemgus Girgensons40032
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dmitry SinitsynJordan Schmaltz60122
2Keegan LoweJoonas Lyytinen40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Christoph Bertschy60131Dmitry SinitsynJordan Schmaltz60131
2Jacob De La Rose40131Keegan LoweJoonas Lyytinen40131
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Christoph BertschyZachary Sanford60122
2Jacob De La RoseZemgus Girgensons40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dmitry SinitsynJordan Schmaltz60122
2Keegan LoweJoonas Lyytinen40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Zachary SanfordChristoph BertschyTyler PitlickDmitry SinitsynJordan Schmaltz
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Zachary SanfordChristoph BertschyTyler PitlickDmitry SinitsynJordan Schmaltz
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Christoph Bertschy, Jacob De La Rose, Brendan PerliniChristoph Bertschy, Jacob De La RoseChristoph Bertschy
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Nikita Nesterov, Mason Geertsen, Jonas SiegenthalerNikita NesterovNikita Nesterov, Mason Geertsen
Tirs de pénalité
Tyler Pitlick, Zachary Sanford, Zemgus Girgensons, Oliver Bjorkstrand, Christoph Bertschy
Gardien
#1 : Garret Sparks, #2 : Eric Comrie


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
1Admirals733000012731-44310000015123302000011219-770.50027457200109122112923993390086636201664812832515.63%24675.00%1901181649.61%818170947.86%694139649.71%170396117007351437722
2Barracuda32000001191182100000198111000000103750.83319325100109122112911393390086636994422619555.56%11281.82%1901181649.61%818170947.86%694139649.71%170396117007351437722
3Bears211000001012-21100000062410100000410-620.5001018280010912211297293390086636621812346466.67%6266.67%0901181649.61%818170947.86%694139649.71%170396117007351437722
4Comets21100000642110000004131010000023-120.500610160010912211295393390086636651712391119.09%60100.00%0901181649.61%818170947.86%694139649.71%170396117007351437722
5Condors31100001911-22110000078-11000000123-130.5009172600109122112910093390086636953028516116.67%14192.86%0901181649.61%818170947.86%694139649.71%170396117007351437722
6Crunch2010010079-21000010034-11010000045-110.250710170010912211296393390086636612314376350.00%7271.43%0901181649.61%818170947.86%694139649.71%170396117007351437722
7Devils220000001358110000004311100000092741.0001320330010912211297993390086636582316369444.44%8187.50%1901181649.61%818170947.86%694139649.71%170396117007351437722
8Eagles21100000910-11010000037-41100000063320.5009142300109122112975933900866366618103913323.08%5180.00%0901181649.61%818170947.86%694139649.71%170396117007351437722
9Griffins302000011014-41010000056-12010000158-310.16710192900109122112910293390086636101348437114.29%40100.00%0901181649.61%818170947.86%694139649.71%170396117007351437722
10Heat301000111314-1100000106512010000179-230.500131730001091221129101933900866369933226811654.55%11372.73%0901181649.61%818170947.86%694139649.71%170396117007351437722
11Icehogs614001002034-14311001001217-530300000817-930.25020305000109122112919793390086636211666611123313.04%331263.64%1901181649.61%818170947.86%694139649.71%170396117007351437722
12Little Stars220000001174110000006331100000054141.000111829001091221129649339008663655258427114.29%4175.00%0901181649.61%818170947.86%694139649.71%170396117007351437722
13Marlies3210000013121110000005322110000089-140.66713213400109122112911793390086636922920767685.71%10550.00%0901181649.61%818170947.86%694139649.71%170396117007351437722
14Monsters734000003037-731200000918-9422000002119260.42930477700109122112922493390086636256787415030723.33%371267.57%0901181649.61%818170947.86%694139649.71%170396117007351437722
15Moose30300000716-920200000410-61010000036-300.00071118001091221129909339008663698383048500.00%15473.33%1901181649.61%818170947.86%694139649.71%170396117007351437722
16Penguins20200000713-61010000046-21010000037-400.000713200010912211295293390086636552227426116.67%11372.73%0901181649.61%818170947.86%694139649.71%170396117007351437722
17Phantoms3110001013112201000109901100000042240.6671323360010912211291069339008663610736323712216.67%16287.50%0901181649.61%818170947.86%694139649.71%170396117007351437722
18Punishers210010001275110000005141000100076141.0001220320010912211298293390086636582322336233.33%11190.91%0901181649.61%818170947.86%694139649.71%170396117007351437722
19Rampage5320000024222321000001611521100000811-360.60024426600109122112918493390086636152372811328932.14%14285.71%1901181649.61%818170947.86%694139649.71%170396117007351437722
20Reign3110100014122201010001011-11100000041340.6671425390010912211291139339008663610144165512216.67%8362.50%0901181649.61%818170947.86%694139649.71%170396117007351437722
21Rocket53200000262241010000038-5431000002314960.6002644700010912211291549339008663617852309210220.00%15286.67%1901181649.61%818170947.86%694139649.71%170396117007351437722
22Sound Tigers32100000181351100000064221100000129340.667182846001091221129109933900866368631226314321.43%10280.00%1901181649.61%818170947.86%694139649.71%170396117007351437722
23Thunderbirds30300000816-820200000611-51010000025-300.00081523001091221129919339008663610835245911436.36%12375.00%0901181649.61%818170947.86%694139649.71%170396117007351437722
24Wolfpack20100100811-31010000068-21000010023-110.25081220001091221129669339008663671291433400.00%70100.00%0901181649.61%818170947.86%694139649.71%170396117007351437722
25Wolves21100000131211010000057-21100000085320.50013203300109122112966933900866366221184211218.18%9277.78%0901181649.61%818170947.86%694139649.71%170396117007351437722
Total80313702325347366-1940161801221168183-1540151901104179183-4780.488347571918001091221129271293390086636259787262315322967726.01%3087276.62%8901181649.61%818170947.86%694139649.71%170396117007351437722
_Since Last GM Reset80313702325347366-1940161801221168183-1540151901104179183-4780.488347571918001091221129271293390086636259787262315322967726.01%3087276.62%8901181649.61%818170947.86%694139649.71%170396117007351437722
_Vs Conference49172301125201225-24248110112194115-212591200004107110-3460.46920133153200109122112916569339008663616385503969201644024.39%1985273.74%5901181649.61%818170947.86%694139649.71%170396117007351437722
_Vs Division207110010177102-251054001003647-111027000014155-14160.4007712219900109122112966093390086636668210188389851517.65%943068.09%2901181649.61%818170947.86%694139649.71%170396117007351437722

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8078L334757191827122597872623153200
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8031372325347366
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4016181221168183
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4015191104179183
Derniers 10 matchs
WLOTWOTL SOWSOL
361000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2967726.01%3087276.62%8
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
933900866361091221129
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
901181649.61%818170947.86%694139649.71%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
170396117007351437722


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
2 - 2022-10-288Senators4Admirals5ALR1Sommaire du match
4 - 2022-10-3019Admirals2Senators3BWSommaire du match
5 - 2022-10-3124Senators3Rocket6ALSommaire du match
6 - 2022-11-0134Senators7Monsters5AWR1Sommaire du match
10 - 2022-11-0549Icehogs5Senators6BWSommaire du match
13 - 2022-11-0866Rampage4Senators6BWSommaire du match
14 - 2022-11-0974Senators3Icehogs4ALR1Sommaire du match
17 - 2022-11-1290Senators5Monsters6ALR1Sommaire du match
19 - 2022-11-1499Monsters7Senators1BLSommaire du match
21 - 2022-11-16114Senators6Admirals7ALXXR1Sommaire du match
23 - 2022-11-18125Admirals4Senators5BWSommaire du match
25 - 2022-11-20136Senators5Heat6ALXXSommaire du match
26 - 2022-11-21140Senators9Rocket1AWSommaire du match
29 - 2022-11-24154Barracuda4Senators6BWSommaire du match
31 - 2022-11-26165Senators9Sound Tigers4AWSommaire du match
34 - 2022-11-29180Icehogs8Senators3BLR1Sommaire du match
38 - 2022-12-03203Admirals5Senators2BLSommaire du match
43 - 2022-12-08224Condors2Senators4BWSommaire du match
46 - 2022-12-11241Senators10Barracuda3AWSommaire du match
48 - 2022-12-13249Sound Tigers4Senators6BWSommaire du match
50 - 2022-12-15258Senators4Bears10ALSommaire du match
52 - 2022-12-17268Senators2Admirals7ALR1Sommaire du match
54 - 2022-12-19280Monsters7Senators2BLR1Sommaire du match
56 - 2022-12-21288Senators2Rampage6ALSommaire du match
60 - 2022-12-25307Admirals1Senators5BWR1Sommaire du match
64 - 2022-12-29328Heat5Senators6BWXXSommaire du match
66 - 2022-12-31339Senators4Reign1AWSommaire du match
68 - 2023-01-02351Wolfpack8Senators6BLSommaire du match
70 - 2023-01-04361Senators2Condors3ALXXSommaire du match
73 - 2023-01-07375Senators8Wolves5AWSommaire du match
75 - 2023-01-09385Thunderbirds4Senators3BLSommaire du match
77 - 2023-01-11395Senators2Comets3ALSommaire du match
79 - 2023-01-13409Condors6Senators3BLSommaire du match
82 - 2023-01-16424Senators3Moose6ALSommaire du match
85 - 2023-01-19434Crunch4Senators3BLXSommaire du match
88 - 2023-01-22453Senators3Sound Tigers5ALSommaire du match
89 - 2023-01-23460Bears2Senators6BWSommaire du match
92 - 2023-01-26477Senators7Rocket5AWSommaire du match
94 - 2023-01-28487Thunderbirds7Senators3BLSommaire du match
96 - 2023-01-30502Senators6Monsters4AWR1Sommaire du match
98 - 2023-02-01512Barracuda4Senators3BLXXSommaire du match
102 - 2023-02-05529Senators3Icehogs6ALR1Sommaire du match
104 - 2023-02-07537Wolves7Senators5BLSommaire du match
106 - 2023-02-09554Senators2Icehogs7ALR1Sommaire du match
108 - 2023-02-11563Rampage2Senators7BWSommaire du match
110 - 2023-02-13572Senators5Little Stars4AWSommaire du match
112 - 2023-02-15587Senators4Phantoms2AWSommaire du match
114 - 2023-02-17592Punishers1Senators5BWSommaire du match
116 - 2023-02-19605Senators3Monsters4ALR1Sommaire du match
118 - 2023-02-21614Senators9Devils2AWSommaire du match
120 - 2023-02-23622Devils3Senators4BWSommaire du match
123 - 2023-02-26641Comets1Senators4BWSommaire du match
126 - 2023-03-01651Senators2Thunderbirds5ALSommaire du match
128 - 2023-03-03663Senators3Penguins7ALSommaire du match
129 - 2023-03-04674Eagles7Senators3BLSommaire du match
132 - 2023-03-07690Senators2Wolfpack3ALXSommaire du match
134 - 2023-03-09698Phantoms7Senators6BLSommaire du match
137 - 2023-03-12716Senators2Griffins4ALSommaire du match
139 - 2023-03-14725Little Stars3Senators6BWSommaire du match
141 - 2023-03-16735Senators7Punishers6AWXSommaire du match
143 - 2023-03-18749Icehogs4Senators3BLXR1Sommaire du match
146 - 2023-03-21762Senators6Eagles3AWSommaire du match
148 - 2023-03-23772Senators4Crunch5ALSommaire du match
150 - 2023-03-25780Phantoms2Senators3BWXXSommaire du match
152 - 2023-03-27792Senators3Griffins4ALXXSommaire du match
154 - 2023-03-29805Penguins6Senators4BLSommaire du match
159 - 2023-04-03828Griffins6Senators5BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
164 - 2023-04-08847Senators4Rocket2AWSommaire du match
166 - 2023-04-10856Moose4Senators1BLSommaire du match
167 - 2023-04-11867Senators6Rampage5AWSommaire du match
170 - 2023-04-14882Moose6Senators3BLSommaire du match
171 - 2023-04-15890Senators5Marlies4AWSommaire du match
176 - 2023-04-20909Marlies3Senators5BWSommaire du match
181 - 2023-04-25931Monsters4Senators6BWR1Sommaire du match
184 - 2023-04-28953Rampage5Senators3BLSommaire du match
185 - 2023-04-29956Senators2Heat3ALSommaire du match
191 - 2023-05-05980Reign5Senators6BWXSommaire du match
193 - 2023-05-07993Senators3Marlies5ALSommaire du match
199 - 2023-05-131012Reign6Senators4BLSommaire du match
204 - 2023-05-181034Rocket8Senators3BLSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance72,99037,671
Assistance PCT91.24%94.18%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2767 - 92.22% 81,893$3,275,701$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
3,077,873$ 2,947,500$ 2,655,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
14,308$ 2,067,531$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 19,163$ 0$




Senators Leaders statistiques (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 (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