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Connexion

Senators
GP: 80 | W: 31 | L: 43 | OTL: 6 | P: 68
GF: 329 | GA: 398 | PP%: 21.43% | PK%: 72.75%
DG: Didier Theodore | Morale : 20 | Moyenne d’équipe : 64
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Centre de jeu
Condors
40-33-7, 87pts
2
FINAL
4 Senators
31-43-6, 68pts
Team Stats
W2SéquenceL1
18-19-3Fiche domicile21-17-2
22-14-4Fiche domicile10-26-4
5-3-2Derniers 10 matchs4-6-0
4.24Buts par match 4.11
4.15Buts contre par match 4.98
21.14%Pourcentage en avantage numérique21.43%
78.13%Pourcentage en désavantage numérique72.75%
Condors
40-33-7, 87pts
8
FINAL
3 Senators
31-43-6, 68pts
Team Stats
W2SéquenceL1
18-19-3Fiche domicile21-17-2
22-14-4Fiche domicile10-26-4
5-3-2Derniers 10 matchs4-6-0
4.24Buts par match 4.11
4.15Buts contre par match 4.98
21.14%Pourcentage en avantage numérique21.43%
78.13%Pourcentage en désavantage numérique72.75%
Meneurs d'équipe
Buts
Zachary Sanford
68
Passes
Christoph Bertschy
87
Points
Zachary Sanford
133
Plus/Moins
Grant Besse
5
Victoires
David Rittich
24
Pourcentage d’arrêts
David Rittich
0.852

Statistiques d’équipe
Buts pour
329
4.11 GFG
Tirs pour
2705
33.81 Avg
Pourcentage en avantage numérique
21.4%
66 GF
Début de zone offensive
36.2%
Buts contre
398
4.98 GAA
Tirs contre
2586
32.33 Avg
Pourcentage en désavantage numérique
72.8%%
91 GA
Début de la zone défensive
35.3%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,762
Billets de saison300


Informations de la formation

Équipe Pro31
Équipe Mineure20
Limite contact 51 / 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
1Zachary Sanford (R)X100.007622738270847582707476707764584341740242950,000$
2Christoph Bertschy (R)X100.006927827878827275717472707762504240720241750,000$
3C.J Suess (R)X100.007631777578676372667277677049524536700242850,000$
4Kevin RooneyX100.006645767469737469776973647454533540690252600,000$
5Marc Michaelis (R)X100.007539747065756168687472706451495130680232750,000$
6Mason Appleton (R)X100.005436817267667170797872555746465124670221650,000$
7Carl Grundstrom (R)X100.007052866768736767686668637045476530670212900,000$
8Grant Besse (R)X100.006132757265746571716568647349513026660242750,000$
9Tomas HykaX100.006034756761626164798264555847482622640251500,000$
10Arttu Ruotsalainen (R)X100.005137706560706968535683536645454924630212600,000$
11Akil Thomas (R)X100.007043575467486356455857445340406619540182500,000$
12Bryce Kindopp (R)X100.005833615463525855555061535641416719540191500,000$
13Jordan SchmaltzX100.007338827875787371517468817173543926740252975,000$
14Keegan LoweX100.007027797680877070567369776068533840730252800,000$
15Joonas Lyytinen (R)X100.007129807167606667437252805753504320690232600,000$
16Nikita NesterovX100.006925807568716967507168676753513826680251600,000$
17Mason Geertsen (R)X100.007145786265577867506054676050483940640232500,000$
18Martin Fehervary (R)X100.005840697256516279388452574443436820620192500,000$
Rayé
1Jacob De La Rose (R)X85.557023867179857364707474817461484931720231850,000$
2Anton Karlsson (R)X100.006526697761645475606762687145464528650223600,000$
3Vitaly Abramov (R)X100.005335777470656371576576486944445918640202500,000$
4David Kase (R)X100.006533656260616661636167516544444420600211500,000$
5Cliff Pu (R)X100.005625705362625264566069366542424717570202500,000$
6Ivan Morozov (R)X100.005237595659495757525258454640406518530182500,000$
7Jonas Siegenthaler (R)X100.006126866264567057336750784845454733640211500,000$
8Gustav Forsling (R)X100.007033756155686061426267585545454919610222500,000$
9Alec Regula (R)X100.005841625452585964445051654340406818560182500,000$
MOYENNE D’ÉQUIPE99.46653474686667666758676662635047482765
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 Rittich99.00676584615980835754837653535841680263950,000$
2Arvid Soderblom100.00536476505163695355745841417138590191500,000$
Rayé
1Olivier Rodrigue (R)100.00426852545055575869544540406920550184500,000$
2Olle Eriksson Ek100.00564961556159515752545841415720550191500,000$
MOYENNE D’ÉQUIPE99.7555626855556465565866594444643059
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mario Lemieux58697272515555CAN5421,000,000$


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)LW796865133-2412001609539215323617.35%55180222.811424385625400032245449.09%1659044141.4845000695
2Christoph BertschySenators (Ott)C804487131-2126014118633112021813.29%49184423.061522375225500032673151.17%28324640031.4214000783
3C.J SuessSenators (Ott)LW80333568-1595131802118114415.64%22118714.845381511200041192144.44%544915011.1500000240
4Jacob De La RoseSenators (Ott)C79264268-51201191492135811412.21%29139117.62310132420100041503151.19%9674023000.9812000321
5Jordan SchmaltzSenators (Ott)D7175259-3841512115814246684.93%129199628.1221416252490003248200%03772000.5900001211
6Kevin RooneySenators (Ott)C80193352-93008193180449010.56%1898512.321011190001651054.49%4572616001.0500000332
7Mason AppletonSenators (Ott)RW74203050-43205963134508414.93%20118616.03371023150000021149.80%2552421100.8400000135
8Marc MichaelisSenators (Ott)LW75193049-1132010675172448811.05%2297713.031567770003562344.12%343119001.0001000133
9Keegan LoweSenators (Ott)D8073441-3858013016012662615.56%129215726.973912232750002257000%03477000.3800000021
10Grant BesseSenators (Ott)RW7315223753605668118346812.71%1493612.822351086000002155.17%292210000.7900000202
11Nikita NesterovSenators (Ott)D80102333-15157111085364011.76%87161820.235510111880001192010%02449000.4100000110
12Carl GrundstromSenators (Ott)RW80102131-35300957611539598.70%29134716.852469216000000150.00%801519000.4600000002
13Joonas LyytinenSenators (Ott)D6932427-11380811057232334.17%71143520.81235111730111174100%01050000.3800000000
14Anton KarlssonSenators (Ott)LW7116925-172806046125527112.80%126789.55101131013884041.67%123614010.7400000021
15Jonas SiegenthalerSenators (Ott)D7211112514021906318281.59%62101714.13101441000275000%0231000.2400000001
16Tomas HykaSenators (Ott)RW507512-2080262156103012.50%104018.0310110000000040.00%10103000.6000000000
17David KaseSenators (Ott)RW4152752203216155833.33%43819.3000003000000033.33%617000.3700000000
18Martin FehervarySenators (Ott)D28077-540918185110%1431611.310000300009000%044000.4400000000
19Vitaly AbramovSenators (Ott)LW22257-600722710167.41%31667.550000000002000%461000.8400000000
20Arttu RuotsalainenSenators (Ott)C42336-13802017339229.09%53187.5800000000020150.00%9462000.3800000000
21Mason GeertsenSenators (Ott)D80134-522054583921132.56%5596512.0600007000029000%0238000.0800000001
22Gustav ForslingSenators (Ott)D21011000321000%2643.050000000008000%000000.3100000000
23Alec RegulaSenators (Ott)D8011320121310%4567.080000000000000%001000.3500000000
24Bryce KindoppSenators (Ott)RW240110140888120%31636.8000000000000050.00%201000.1200000000
25Akil ThomasSenators (Ott)C3000-100100000%0103.3300000000030020.00%50000000000000
26Ivan MorozovSenators (Ott)C2000000000000%000.330000000000000%00000000000000
27Cliff PuSenators (Ott)RW4000000000000%000.240000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne1468316546862-24768715159316982677933150511.80%8482340715.94611091702732325112301981261551.06%5006515557290.74612001283828
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)66242830.8524.823326202671801864240.900106020101
2Arvid SoderblomSenators (Ott)3571530.8414.98149400124779397420.50022060001
Statistiques d’équipe totales ou en moyenne101314360.8484.874821203912580126166128080102


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
Akil ThomasSenators (Ott)C182000-01-01Yes195 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Alec RegulaSenators (Ott)D182000-01-01Yes208 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Anton KarlssonSenators (Ott)LW221996-01-01Yes194 Lbs5 ft11NoNoN/ANoNo3FalseFalsePro & Farm600,000$2,985$0$0$No800,000$800,000$-------NoNo-------
Arttu RuotsalainenSenators (Ott)C211997-01-01Yes181 Lbs5 ft8NoNoN/ANoNo2FalseFalsePro & Farm600,000$2,985$0$0$No600,000$--------No--------
Arvid SoderblomSenators (Ott)G191999-01-01No180 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Bryce KindoppSenators (Ott)RW191999-01-01Yes185 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
C.J SuessSenators (Ott)LW241994-01-01Yes190 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm850,000$4,229$0$0$No850,000$--------No--------
Carl GrundstromSenators (Ott)RW211997-01-01Yes194 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm900,000$4,478$0$0$No900,000$--------No--------
Christoph BertschySenators (Ott)C241994-01-01Yes182 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm750,000$3,731$0$0$No------------------
Cliff PuSenators (Ott)RW201998-01-01Yes185 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------
David KaseSenators (Ott)RW211997-01-01Yes169 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
David RittichSenators (Ott)G261992-01-01No206 Lbs6 ft3NoNoN/ANoNo3FalseFalsePro & Farm950,000$4,726$0$0$No1,500,000$2,500,000$-------NoNo-------
Grant BesseSenators (Ott)RW241994-01-01Yes185 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm750,000$3,731$0$0$No750,000$--------No--------
Gustav ForslingSenators (Ott)D221996-01-01Yes186 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------
Ivan MorozovSenators (Ott)C182000-01-01Yes178 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Jacob De La Rose (sur la masse salariale)Senators (Ott)C231995-01-01Yes185 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm850,000$4,229$0$0$Yes------------------
Jonas SiegenthalerSenators (Ott)D211997-01-01Yes210 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Joonas LyytinenSenators (Ott)D231995-01-01Yes189 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm600,000$2,985$0$0$No600,000$--------No--------
Jordan SchmaltzSenators (Ott)D251993-01-01No180 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm975,000$4,851$0$0$No975,000$--------No--------
Keegan LoweSenators (Ott)D251993-01-01No200 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm800,000$3,980$0$0$No800,000$--------No--------
Kevin RooneySenators (Ott)C251993-01-01No190 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm600,000$2,985$0$0$No600,000$--------No--------
Marc MichaelisSenators (Ott)LW231995-01-01Yes187 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm750,000$3,731$0$0$No750,000$--------No--------
Martin FehervarySenators (Ott)D191999-01-01Yes199 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Mason AppletonSenators (Ott)RW221996-01-01Yes193 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm650,000$3,234$0$0$No------------------
Mason GeertsenSenators (Ott)D231995-01-01Yes185 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------
Nikita NesterovSenators (Ott)D251993-01-01No191 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm600,000$2,985$0$0$No------------------
Olivier RodrigueSenators (Ott)G182000-01-01Yes158 Lbs6 ft1NoNoN/ANoNo4FalseFalsePro & Farm500,000$2,488$0$0$No500,000$500,000$500,000$------NoNoNo------Lien
Olle Eriksson EkSenators (Ott)G191999-01-01No189 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Tomas HykaSenators (Ott)RW251993-01-01No160 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Vitaly AbramovSenators (Ott)LW201998-01-01Yes181 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------
Zachary SanfordSenators (Ott)LW241994-01-01Yes185 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm950,000$4,726$0$0$No1,250,000$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3121.84187 Lbs6 ft11.81634,677$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Zachary SanfordChristoph BertschyMason Appleton40014
2C.J SuessKevin RooneyCarl Grundstrom30023
3Marc MichaelisArttu RuotsalainenGrant Besse20122
4Zachary SanfordAkil ThomasTomas Hyka10131
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan SchmaltzKeegan Lowe40032
2Joonas LyytinenNikita Nesterov30032
3Mason GeertsenMartin Fehervary20122
4Jordan SchmaltzKeegan Lowe10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Zachary SanfordChristoph BertschyMason Appleton60005
2C.J SuessKevin RooneyCarl Grundstrom40005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan SchmaltzKeegan Lowe60005
2Joonas LyytinenNikita Nesterov40005
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Christoph BertschyZachary Sanford60140
2Kevin RooneyC.J Suess40140
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan SchmaltzKeegan Lowe60140
2Joonas LyytinenNikita Nesterov40140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Christoph Bertschy60140Jordan SchmaltzKeegan Lowe60140
2Kevin Rooney40140Joonas LyytinenNikita Nesterov40140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Christoph BertschyZachary Sanford60122
2Kevin RooneyC.J Suess40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan SchmaltzKeegan Lowe60122
2Joonas LyytinenNikita Nesterov40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Zachary SanfordChristoph BertschyMason AppletonJordan SchmaltzKeegan Lowe
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Zachary SanfordChristoph BertschyMason AppletonJordan SchmaltzKeegan Lowe
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Marc Michaelis, Mason Appleton, Carl GrundstromMarc Michaelis, Mason AppletonMarc Michaelis
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Nikita Nesterov, Mason Geertsen, Martin FehervaryNikita NesterovNikita Nesterov, Mason Geertsen
Tirs de pénalité
Zachary Sanford, Christoph Bertschy, C.J Suess, Kevin Rooney, Marc Michaelis
Gardien
#1 : David Rittich, #2 : Arvid Soderblom
Lignes d’attaque personnalisées en prolongation
Zachary Sanford, Christoph Bertschy, C.J Suess, Kevin Rooney, Marc Michaelis, Mason Appleton, Mason Appleton, Carl Grundstrom, Grant Besse, Tomas Hyka, Arttu Ruotsalainen
Lignes de défense personnalisées en prolongation
Jordan Schmaltz, Keegan Lowe, Joonas Lyytinen, Nikita Nesterov, 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
1Admirals624000002431-73210000013121303000001119-840.3332441651092118113920392496980321177656612035822.86%331360.61%1915178051.40%877174050.40%727140351.82%1748100616597401422709
2Americans62300010292813120000015141311000101414060.5002943721092118113919892496980321192887612823626.09%38976.32%0915178051.40%877174050.40%727140351.82%1748100616597401422709
3Barracuda312000001317-421100000911-21010000046-220.333132134009211811391129249698032110022186910330.00%9366.67%0915178051.40%877174050.40%727140351.82%1748100616597401422709
4Bears20100001613-71010000039-61000000134-110.25069150092118113970924969803217519846400.00%4175.00%0915178051.40%877174050.40%727140351.82%1748100616597401422709
5Canucks211000001114-3110000007611010000048-420.5001118290092118113965924969803217826204210330.00%10550.00%0915178051.40%877174050.40%727140351.82%1748100616597401422709
6Checkers211000001011-1110000004221010000069-320.500101626009211811396292496980321562116418225.00%80100.00%0915178051.40%877174050.40%727140351.82%1748100616597401422709
7Comets20200000914-51010000035-21010000069-300.00091423009211811396492496980321662622362150.00%11281.82%0915178051.40%877174050.40%727140351.82%1748100616597401422709
8Condors321000001312121100000710-31100000062440.66713213400921181139103924969803219530206411218.18%10190.00%0915178051.40%877174050.40%727140351.82%1748100616597401422709
9Crunch20100100710-31010000035-21000010045-110.25071017009211811396292496980321621815495120.00%5260.00%0915178051.40%877174050.40%727140351.82%1748100616597401422709
10Eagles2110000078-1110000004221010000036-320.50071118009211811397092496980321611314546233.33%70100.00%0915178051.40%877174050.40%727140351.82%1748100616597401422709
11Griffins321000001415-11100000054121100000911-240.667142539009211811399592496980321982626421218.33%13376.92%0915178051.40%877174050.40%727140351.82%1748100616597401422709
12Icehogs72202100312924100210020182312000001111090.6433151820092118113925692496980321214666914342614.29%28871.43%0915178051.40%877174050.40%727140351.82%1748100616597401422709
13Islander2110000016142110000009541010000079-220.5001624400092118113975924969803217027264010440.00%13653.85%0915178051.40%877174050.40%727140351.82%1748100616597401422709
14Little Stars312000001015-5211000008801010000027-520.33310182800921181139729249698032191364558600.00%16568.75%0915178051.40%877174050.40%727140351.82%1748100616597401422709
15Marlies30200010715-81010000016-52010001069-320.333712190092118113910892496980321882618689111.11%9277.78%0915178051.40%877174050.40%727140351.82%1748100616597401422709
16Moose30300000815-71010000035-220200000510-500.000814220092118113910292496980321893528638337.50%14471.43%0915178051.40%877174050.40%727140351.82%1748100616597401422709
17Penguins312000001416-2211000008801010000068-220.333142539009211811391069249698032110731205312541.67%10550.00%0915178051.40%877174050.40%727140351.82%1748100616597401422709
18Phantoms724001002636-10312000001417-3412001001219-750.3572644701092118113925192496980321231615014322522.73%25868.00%0915178051.40%877174050.40%727140351.82%1748100616597401422709
19Punishers22000000853110000005411100000031241.0008152300921181139589249698032164182050200.00%9188.89%0915178051.40%877174050.40%727140351.82%1748100616597401422709
20Reign312000001014-421100000810-21010000024-220.3331016261092118113992924969803219522204514214.29%10280.00%0915178051.40%877174050.40%727140351.82%1748100616597401422709
21Rocket403000101821-3201000101111020200000710-320.250182846009211811391479249698032114549306819421.05%15193.33%0915178051.40%877174050.40%727140351.82%1748100616597401422709
22Silver Knights21100000910-1110000005411010000046-220.50091423109211811396892496980321603016368225.00%8275.00%0915178051.40%877174050.40%727140351.82%1748100616597401422709
23Thunderbirds2100010010911000010056-11100000053230.750102030009211811396492496980321622114327228.57%7185.71%0915178051.40%877174050.40%727140351.82%1748100616597401422709
24Wolfpack30200100713-61010000025-32010010058-310.16771118109211811391049249698032110635185114321.43%9366.67%0915178051.40%877174050.40%727140351.82%1748100616597401422709
25Wranglers311000101213-1100000107612110000057-240.667122133009211811399892496980321104362658900.00%13469.23%0915178051.40%877174050.40%727140351.82%1748100616597401422709
Total80254302541329398-6940171702220179193-144082600321150205-55680.42532954287160921181139270592496980321258684770115993086621.43%3349172.75%1915178051.40%877174050.40%727140351.82%1748100616597401422709
_Since Last GM Reset80254302541329398-6940171702220179193-144082600321150205-55680.42532954287160921181139270592496980321258684770115993086621.43%3349172.75%1915178051.40%877174050.40%727140351.82%1748100616597401422709
_Vs Conference51152802240205246-412591102120113124-11266170012092122-30440.43120533754240921181139176592496980321162852644710112144119.16%2175873.27%1915178051.40%877174050.40%727140351.82%1748100616597401422709
_Vs Division1969021108488-410430210048444926000103644-8190.5008413521920921181139657924969803215832192113911002020.00%993069.70%1915178051.40%877174050.40%727140351.82%1748100616597401422709

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8068L132954287127052586847701159960
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8025432541329398
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4017172220179193
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
408260321150205
Derniers 10 matchs
WLOTWOTL SOWSOL
360010
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3086621.43%3349172.75%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
92496980321921181139
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
915178051.40%877174050.40%727140351.82%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1748100616597401422709


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
14Icehogs6Senators7WXR1Sommaire du match
317Senators5Icehogs3WSommaire du match
419Senators3Phantoms2WSommaire du match
740Admirals5Senators8WR1Sommaire du match
1160Icehogs4Senators5WR1Sommaire du match
1268Senators4Admirals5LSommaire du match
1580Senators4Americans3WXXR1Sommaire du match
1791Senators4Phantoms5LXSommaire du match
18100Phantoms3Senators4WSommaire du match
23124Phantoms9Senators7LSommaire du match
25131Senators2Moose5LSommaire du match
27144Admirals2Senators4WR1Sommaire du match
29156Senators4Wranglers2WSommaire du match
31167Senators5Marlies4WXXSommaire du match
33177Americans5Senators4LR1Sommaire du match
37196Reign3Senators6WSommaire du match
39209Senators6Penguins8LSommaire du match
42220Senators5Americans7LR1Sommaire du match
44228Admirals5Senators1LSommaire du match
46244Senators2Reign4LSommaire du match
48252Senators5Rocket7LSommaire du match
50259Penguins5Senators3LSommaire du match
53271Senators2Little Stars7LSommaire du match
55285Crunch5Senators3LSommaire du match
58298Senators2Wolfpack4LSommaire du match
60305Senators6Griffins5WSommaire du match
61312Moose5Senators3LSommaire du match
64330Senators3Wolfpack4LXSommaire du match
65338Thunderbirds6Senators5LXSommaire du match
68356Senators1Phantoms4LSommaire du match
70363Eagles2Senators4WSommaire du match
72382Senators4Silver Knights6LSommaire du match
74388Punishers4Senators5WSommaire du match
79412Marlies6Senators1LSommaire du match
83433Penguins3Senators5WSommaire du match
85443Senators3Eagles6LSommaire du match
88460Comets5Senators3LSommaire du match
90471Senators5Americans4WR1Sommaire du match
93486Rocket5Senators4LSommaire du match
96501Senators6Comets9LSommaire du match
98513Canucks6Senators7WSommaire du match
100523Senators4Crunch5LXSommaire du match
101535Senators5Thunderbirds3WSommaire du match
104543Griffins4Senators5WSommaire du match
106560Senators6Checkers9LSommaire du match
108567Rocket6Senators7WXXSommaire du match
112586Senators2Rocket3LSommaire du match
114594Wolfpack5Senators2LSommaire du match
116608Senators4Admirals9LR1Sommaire du match
118620Icehogs6Senators5LXR1Sommaire du match
122641Bears9Senators3LSommaire du match
125659Senators7Islander9LSommaire du match
126669Little Stars4Senators2LSommaire du match
131693Senators1Wranglers5LSommaire du match
132697Barracuda6Senators7WSommaire du match
135717Americans2Senators5WR1Sommaire du match
137727Senators3Griffins6LSommaire du match
139738Senators3Admirals5LR1Sommaire du match
141747Barracuda5Senators2LSommaire du match
143764Senators3Punishers1WSommaire du match
144771Checkers2Senators4WSommaire du match
147793Icehogs2Senators3WXR1Sommaire du match
149799Senators3Bears4LXXSommaire du match
153820Americans7Senators6LR1Sommaire du match
156831Senators1Marlies5LSommaire du match
158842Senators3Moose5LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
159848Senators4Canucks8LSommaire du match
161856Silver Knights4Senators5WSommaire du match
166877Little Stars4Senators6WSommaire du match
170899Phantoms5Senators3LSommaire du match
171907Senators2Icehogs3LR1Sommaire du match
173917Senators6Condors2WSommaire du match
175928Islander5Senators9WSommaire du match
176936Senators4Barracuda6LSommaire du match
181956Reign7Senators2LSommaire du match
184976Wranglers6Senators7WXXSommaire du match
185986Senators4Phantoms8LSommaire du match
1891001Senators4Icehogs5LR1Sommaire du match
1911013Condors2Senators4WSommaire du match
2001040Condors8Senators3LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance73,83936,629
Assistance PCT92.30%91.57%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2762 - 92.06% 174,140$6,965,585$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,926,864$ 1,967,500$ 1,967,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,366$ 1,924,659$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 1 14,764$ 14,764$




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