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Senateurs
GP: 82 | W: 30 | L: 45 | OTL: 7 | P: 67
GF: 241 | GA: 302 | PP%: 17.28% | PK%: 76.39%
DG: Claude-Etienne Landry | Morale : 25 | Moyenne d’équipe : 68
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Centre de jeu
Senateurs
30-45-7, 67pts
5
FINAL
4 Predators
45-24-13, 103pts
Team Stats
W3SéquenceSOL1
15-22-4Fiche domicile21-14-6
15-23-3Fiche domicile24-10-7
5-3-2Derniers 10 matchs6-2-2
2.94Buts par match 3.22
3.68Buts contre par match 3.00
17.28%Pourcentage en avantage numérique21.98%
76.39%Pourcentage en désavantage numérique84.32%
Flyers
38-36-8, 84pts
4
FINAL
5 Senateurs
30-45-7, 67pts
Team Stats
L1SéquenceW3
19-20-2Fiche domicile15-22-4
19-16-6Fiche domicile15-23-3
5-4-1Derniers 10 matchs5-3-2
2.93Buts par match 2.94
3.16Buts contre par match 3.68
15.00%Pourcentage en avantage numérique17.28%
81.25%Pourcentage en désavantage numérique76.39%
Meneurs d'équipe
Buts
Denis Malgin
35
Passes
Sonny Milano
45
Points
Denis Malgin
71
Plus/Moins
Nathan Bastian
14
Victoires
Scott Wedgewood
27
Pourcentage d’arrêts
Scott Wedgewood
0.896

Statistiques d’équipe
Buts pour
241
2.94 GFG
Tirs pour
2607
31.79 Avg
Pourcentage en avantage numérique
17.3%
42 GF
Début de zone offensive
37.9%
Buts contre
302
3.68 GAA
Tirs contre
2695
32.87 Avg
Pourcentage en désavantage numérique
76.4%%
68 GA
Début de la zone défensive
38.2%
Informations de l'équipe

Directeur généralClaude-Etienne Landry
EntraîneurAndre Tourigny
DivisionAtlantique
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,889
Billets de saison2,100


Informations de la formation

Équipe Pro35
Équipe Mineure18
Limite contact 53 / 60
Espoirs42


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
1Sonny Milano (R)X100.0071458575778386804094956625768169377602722,000,000$
2Alexandre Grenier (R)X100.009978336877798398184847255797231567503223,000,000$
3Nick Paul (R)X100.0079557475878688828175767825798169397402921,000,000$
4Denis Malgin (R)X100.0077409181748185794089866725797967337402733,000,000$
5Alexandre Texier (R)X100.0087537670788984787979737675717469317202421,500,000$
6Alex Formenton (R)X100.007338958178797275747175852573756650720241900,000$
7Isac Lundestrom (R)X100.006640927882858372727064732572715940690242700,000$
8Max Jones (R)X100.007868627387838376507068662574715928680262800,000$
9Nathan Bastian (R)X100.007865687485838073506966712572715941680262700,000$
10Matthew Peca (R)X100.007463876775556167747569745385785525660313700,000$
11MacKenzie Entwistle (R)X100.007945897682827870716563672571615226660241811,667$
12Parker Kelly (R)X100.008965717578827869506361732568605324660242762,500$
13Kole Sherwood (R)X100.008077866177565659507367636275725826620271750,000$
14Jonas Siegenthaler (R)X100.0073507282878885774076669325767159537702722,000,000$
15Jakob Chychrun (R)X100.0066506975879082824086787425787967717502632,000,000$
16Sebastian Aho (R)X100.006845847774858677407567752575766440720282700,000$
17Haydn Fleury (R)X100.0064457972868276684074627525687664256902711,000,000$
18Andreas Englund (R)X100.008076677378828269406360712568796751690283900,000$
19Ben Harpur (R)X100.0073557969918383704064627125688169516902921,000,000$
Rayé
1Justin AbdelkaderX100.0090388760788090846384847586999919267503712,500,000$
2Mark Kastelic (R)X100.008783577291797672886467702572594920670252821,667$
3Rem Pitlick (R)X100.006545777576828071506966652571706019660272575,000$
4Leo KomarovX100.0077469959767395557253598080989437196503711,500,000$
5Ross Johnston (R)X100.007165556590757366406260642564807019630301575,000$
6Michael Carcone (R)X100.005461527254666770456865622569555019610272750,000$
7Brett Murray (R)X100.006679856479596646566257656070716319590251775,000$
8Marco Rossi (R)X100.006040647161606065626559622565505020591223863,333$
9Filip Hallander (R)X100.006240716964626263436256602563515020581233764,167$
10Jake Lucchini (R)X100.005240746758676866446560502564585019582292575,000$
11Alex Turcotte (R)X100.006140716963595859415653602560505020560232894,167$
12Tim Erixon (R)X100.004716996776607060517355706191904820640331575,000$
13Nicolas Meloche (R)X100.006268986976576479257871643748475020640261750,000$
14Alec Regula (R)X100.006646606879647152257167625264675516620231866,667$
MOYENNE D’ÉQUIPE100.00725376717875767151716770367371563167
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
1Scott Wedgewood (R)100.008481818482999995957175849058538503121,500,000$
2Joey Daccord (R)100.00746771667177807879723061545056710272750,000$
Rayé
MOYENNE D’ÉQUIPE100.0079747675778890878772537372545578
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Andre Tourigny9177777571661CAN4932,000,000$


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
1Sonny MilanoSenateurs (OTT)LW82264571-1160201611482355715311.06%40169620.69410141618700022442139.53%2534820010.8403121473
2Denis MalginSenateurs (OTT)RW81353671-23181013011429710916511.78%31155019.141110212519200061093041.86%1299121010.9201011853
3Alexandre GrenierSenateurs (OTT)RW77283260-13316160217119285881529.82%31137617.878210321681125851027.78%1084124100.870112416313
4Nick PaulSenateurs (OTT)C77233558-23126601231861745310513.22%29140718.2851318241861012406052.97%17652426010.8201435434
5Alex FormentonSenateurs (OTT)LW8225285302084932377013210.55%19111213.571453381013394149.62%1336120000.9500000332
6Justin AbdelkaderSenateurs (OTT)LW77202646-362210131148242641718.26%42161520.98410142319400042285049.74%3924436010.5703002323
7Isac LundestromSenateurs (OTT)C82162642100065122119296113.45%29106613.011122410001173251.86%8602715000.7900000122
8Nathan BastianSenateurs (OTT)RW8217223914763015675146458911.64%26108413.220221110001760241.43%702513000.7200141032
9Alexandre TexierSenateurs (OTT)C73142539-177335143162115297612.17%31125117.1534771530111111051.94%14421323000.6200205232
10Sebastian AhoSenateurs (OTT)D8232124143620731269647283.13%100179221.86145111620116188020%02867000.2700202020
11Jakob ChychrunSenateurs (OTT)D8021820-1795251041206535373.08%101163220.4114541240003158000%03244000.2500212000
12Jonas SiegenthalerSenateurs (OTT)D6921618-2697451171439831332.04%84162423.54077142020111205000%03362000.2200143102
13Haydn FleurySenateurs (OTT)D7131013-1534066874322146.98%73138119.46011294000297100%01637000.1900000010
14Max JonesSenateurs (OTT)LW504812-10372538388115484.94%124348.70000020004340175.00%8185000.5500302020
15Andreas EnglundSenateurs (OTT)D823912-2514595104895728215.26%72133416.28303443000040110%01037000.1800667000
16Ben HarpurSenateurs (OTT)D8221012187351011076026283.33%79160319.5600021150001133100%0846000.1511115101
17Matthew PecaSenateurs (OTT)C59459-32029394614348.70%84237.1800000000010048.51%134117000.4200000101
18Alec RegulaSenateurs (OTT)D4906614755248221060%3176915.7100002000045000%0519000.1600010000
19Mark KastelicSenateurs (OTT)C372462321044362911206.90%63128.4500000000010057.95%17654000.3800002000
20MacKenzie EntwistleSenateurs (OTT)RW43134-8553323349232.94%83267.5800000000000042.86%723000.2500001000
21Nicolas MelocheSenateurs (OTT)D11022-31010487220%1116014.550000300001000%017000.2500002000
22Tim ErixonSenateurs (OTT)D6011-400162110%78914.960000100002000%024000.2200000000
23Parker KellySenateurs (OTT)LW4101-1003250120.00%0266.720000000000000%010000.7400000000
24Kole SherwoodSenateurs (OTT)RW3000000330000%0186.20000000000000100.00%10000000000000
Statistiques d’équipe totales ou en moyenne1441231388619-193132060019822042249579514009.26%8702409216.7242721141701924347421765281050.77%5478546540140.51110352757313428
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
1Scott WedgewoodSenateurs (OTT)71273570.8963.393964402242154889260.44496913325
2Joey DaccordSenateurs (OTT)2131000.8734.20972006853423701001369000
Statistiques d’équipe totales ou en moyenne92304570.8913.55493740292268811262798282325


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 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
Alec RegulaSenateurs (OTT)D232000-08-06 14:20:17Yes207 Lbs6 ft4NoNoN/ANoNo1Pro & Farm866,667$0$0$No------------------
Alex FormentonSenateurs (OTT)LW241999-09-13 05:14:28Yes165 Lbs6 ft2NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------
Alex TurcotteSenateurs (OTT)C232001-02-26 04:28:15Yes185 Lbs5 ft11NoNoN/ANoNo2Pro & Farm894,167$0$0$No894,167$--------No--------
Alexandre GrenierSenateurs (OTT)RW321991-09-05 23:11:13Yes202 Lbs6 ft5NoNoN/ANoNo2Pro & Farm3,000,000$0$0$No3,000,000$--------No--------
Alexandre TexierSenateurs (OTT)C241999-09-13 04:56:56Yes187 Lbs6 ft0NoNoN/ANoNo2Pro & Farm1,500,000$0$0$No1,500,000$--------No--------
Andreas EnglundSenateurs (OTT)D281996-01-21 12:32:58Yes189 Lbs6 ft3NoNoN/ANoNo3Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------
Ben HarpurSenateurs (OTT)D291995-01-12 12:35:07Yes231 Lbs6 ft6NoNoN/ANoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------
Brett MurraySenateurs (OTT)LW251998-07-20 14:22:09Yes216 Lbs6 ft4NoNoN/ANoNo1Pro & Farm775,000$0$0$No------------------
Denis MalginSenateurs (OTT)RW271997-01-18 04:18:34Yes182 Lbs5 ft9NoNoN/ANoNo3Pro & Farm3,000,000$0$0$No3,000,000$3,000,000$-------NoNo-------
Filip HallanderSenateurs (OTT)LW232000-06-29 02:08:27Yes190 Lbs6 ft1NoNoN/ANoNo3Pro & Farm764,167$0$0$No764,167$764,167$-------NoNo-------
Haydn FleurySenateurs (OTT)D271996-07-08 04:00:49Yes208 Lbs6 ft4NoNoTrade2024-01-17NoNo1Pro & Farm1,000,000$0$0$No------------------
Isac LundestromSenateurs (OTT)C241999-11-06 05:03:37Yes193 Lbs6 ft0NoNoN/ANoNo2Pro & Farm700,000$0$0$No700,000$--------No--------
Jake LucchiniSenateurs (OTT)LW291995-05-09 12:19:38Yes174 Lbs6 ft0NoNoN/ANoNo2Pro & Farm575,000$0$0$No575,000$--------No--------
Jakob ChychrunSenateurs (OTT)D261998-03-31 13:31:18Yes220 Lbs6 ft2NoNoTrade2024-02-25NoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$-------NoNo-------
Joey DaccordSenateurs (OTT)G271996-08-19 03:19:39Yes196 Lbs6 ft2NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------
Jonas SiegenthalerSenateurs (OTT)D271997-05-06 05:01:22Yes218 Lbs6 ft2NoNoN/ANoNo2Pro & Farm2,000,000$0$0$No2,000,000$--------No--------
Justin AbdelkaderSenateurs (OTT)LW371987-02-25 23:11:13No214 Lbs6 ft2NoNoN/ANoNo1Pro & Farm2,500,000$0$0$No------------------
Kole SherwoodSenateurs (OTT)RW271997-01-22 13:01:05Yes212 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------
Leo KomarovSenateurs (OTT)RW371987-01-23 23:11:13No209 Lbs5 ft11NoNoN/ANoNo1Pro & Farm1,500,000$0$0$No------------------
MacKenzie EntwistleSenateurs (OTT)RW241999-07-14 14:25:30Yes184 Lbs6 ft3NoNoN/ANoNo1Pro & Farm811,667$0$0$No------------------
Marco RossiSenateurs (OTT)C222001-09-23 02:10:25Yes183 Lbs5 ft9NoNoN/ANoNo3Pro & Farm863,333$0$0$No863,333$863,333$-------NoNo-------
Mark KastelicSenateurs (OTT)C251999-03-11 03:45:42Yes233 Lbs6 ft3NoNoN/ANoNo2Pro & Farm821,667$0$0$No821,667$--------No--------
Matthew PecaSenateurs (OTT)C311993-04-27 05:46:27Yes182 Lbs5 ft9NoNoN/ANoNo3Pro & Farm700,000$0$0$No700,000$700,000$-------NoNo-------
Max JonesSenateurs (OTT)LW261998-02-17 04:52:50Yes216 Lbs6 ft3NoNoN/ANoNo2Pro & Farm800,000$0$0$No800,000$--------No--------
Michael CarconeSenateurs (OTT)LW271996-05-19 05:47:47Yes170 Lbs5 ft9NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------
Nathan BastianSenateurs (OTT)RW261997-12-06 04:54:49Yes205 Lbs6 ft4NoNoN/ANoNo2Pro & Farm700,000$0$0$No700,000$--------No--------
Nick PaulSenateurs (OTT)C291995-03-20 07:21:55Yes223 Lbs6 ft3NoNoN/ANoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------
Nicolas MelocheSenateurs (OTT)D261997-07-18 04:56:37Yes205 Lbs6 ft3NoNoTrade2024-02-25NoNo1Pro & Farm750,000$0$0$No------------------
Parker KellySenateurs (OTT)LW241999-05-14 10:38:58Yes190 Lbs6 ft0NoNoN/ANoNo2Pro & Farm762,500$0$0$No762,500$--------No--------
Rem PitlickSenateurs (OTT)C271997-04-02 04:58:55Yes186 Lbs5 ft11NoNoN/ANoNo2Pro & Farm575,000$0$0$No575,000$--------No--------
Ross JohnstonSenateurs (OTT)LW301994-02-18 05:48:53Yes230 Lbs6 ft5NoNoN/ANoNo1Pro & Farm575,000$0$0$No------------------
Scott WedgewoodSenateurs (OTT)G311992-08-14 05:11:14Yes207 Lbs6 ft2NoNoN/ANoNo2Pro & Farm1,500,000$0$0$No1,500,000$--------No--------
Sebastian AhoSenateurs (OTT)D281996-02-17 04:06:01Yes186 Lbs5 ft10NoNoN/ANoNo2Pro & Farm700,000$0$0$No700,000$--------No--------
Sonny MilanoSenateurs (OTT)LW271996-05-12 05:11:13Yes194 Lbs6 ft0NoNoN/ANoNo2Pro & Farm2,000,000$0$0$No2,000,000$--------No--------
Tim ErixonSenateurs (OTT)D331991-02-24 23:11:13Yes199 Lbs6 ft2NoNoN/ANoNo1Pro & Farm575,000$0$0$No------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3527.29200 Lbs6 ft11.861,121,691$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sonny MilanoNick PaulDenis Malgin35122
2Alex FormentonAlexandre TexierNathan Bastian35122
3Max JonesIsac LundestromMacKenzie Entwistle25122
4Parker KellyMatthew PecaKole Sherwood5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jonas SiegenthalerJakob Chychrun35122
2Sebastian AhoHaydn Fleury35122
3Ben HarpurAndreas Englund30122
4Jonas SiegenthalerJakob Chychrun0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sonny MilanoNick PaulDenis Malgin60122
2Alex FormentonAlexandre TexierNathan Bastian40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jonas SiegenthalerJakob Chychrun60122
2Sebastian AhoHaydn Fleury40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Sonny MilanoDenis Malgin60122
2Nick PaulAlexandre Texier40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jonas SiegenthalerJakob Chychrun60122
2Sebastian AhoHaydn Fleury40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Sonny Milano60122Jonas SiegenthalerJakob Chychrun60122
2Denis Malgin40122Sebastian AhoHaydn Fleury40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Sonny MilanoDenis Malgin60122
2Nick PaulAlexandre Texier40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jonas SiegenthalerJakob Chychrun60122
2Sebastian AhoHaydn Fleury40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sonny MilanoNick PaulDenis MalginJonas SiegenthalerJakob Chychrun
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sonny MilanoNick PaulDenis MalginJonas SiegenthalerJakob Chychrun
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Isac Lundestrom, Max Jones, Matthew PecaIsac Lundestrom, Max JonesMatthew Peca
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ben Harpur, Andreas Englund, Sebastian AhoBen HarpurAndreas Englund, Sebastian Aho
Tirs de pénalité
Sonny Milano, Denis Malgin, Nick Paul, Alexandre Texier, Alex Formenton
Gardien
#1 : Scott Wedgewood, #2 : Joey Daccord
Lignes d’attaque personnalisées en prolongation
Sonny Milano, Denis Malgin, Nick Paul, Alexandre Texier, Alex Formenton, Isac Lundestrom, Isac Lundestrom, Nathan Bastian, Max Jones, Matthew Peca, MacKenzie Entwistle
Lignes de défense personnalisées en prolongation
Jonas Siegenthaler, Jakob Chychrun, Sebastian Aho, Haydn Fleury, Ben Harpur


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
1Avalanche30200001512-71010000013-22010000149-510.16759141080906837689492377820963050696116.67%10460.00%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
2Blackhawks3120000079-2211000005501010000024-220.3337121920809068310289492377820108351070300.00%50100.00%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
3Blues3120000079-21010000013-22110000066020.33371118008090683100894923778201072926808225.00%8187.50%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
4Bruins531001001715221000100743321000001011-170.700172946008090683155894923778201494418113130620.00%28775.00%11063207751.18%1066209350.93%667131050.92%1777105817867261381683
5Canadiens514000001122-112110000056-130300000616-1020.200111829108090683138894923778201695014213523313.04%26773.08%11063207751.18%1066209350.93%667131050.92%1777105817867261381683
6Canucks30300000717-1020200000413-91010000034-100.000714210080906831058949237782099322067300.00%50100.00%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
7Capitals312000001312120200000811-31100000051420.33313223500809068397894923778209030417810220.00%8187.50%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
8Devils421000011614231100001121201100000042250.6251626420080906831328949237782013539819114428.57%13469.23%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
9Ducks312000008801010000023-12110000065120.3338142200809068388894923778209125297610110.00%7271.43%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
10Flames30200100511-62010010048-41010000013-210.1675914008090683998949237782096361758300.00%6183.33%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
11Flyers3200010011101220000009721000010023-150.83311213200809068310389492377820893247785240.00%11372.73%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
12Islanders312000001213-11100000031220200000912-320.3331221331080906839389492377820983159828112.50%12466.67%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
13Kings30201000612-62010100057-21010000015-420.3336111700809068310289492377820109233960100.00%7185.71%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
14Maple Leafs532000001817132100000111012110000077060.60018335100809068316189492377820149397513422313.64%25484.00%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
15Oilers402011001519-420100100811-32010100078-130.375152641008090683136894923778201445141796233.33%8275.00%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
16Penguins30300000514-920200000411-71010000013-200.0005611008090683103894923778201123337718225.00%16568.75%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
17Predators31101000910-1110000003212010100068-240.667915240080906839289492377820118442577400.00%5260.00%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
18Rangers44000000181081100000031233000000159681.0001830480080906831268949237782011445559317211.76%10190.00%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
19Red Wings523000001823-521100000862312000001017-740.400183048108090683158894923778201536317712525832.00%32875.00%11063207751.18%1066209350.93%667131050.92%1777105817867261381683
20Sabres523000001115-430300000512-72200000063340.400111829008090683134894923778201565513913419210.53%28678.57%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
21Sharks3120000011101110000005232020000068-220.3331118290080906831068949237782011224870500.00%4250.00%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
22Stars31200000710-32110000067-11010000013-220.3337101700809068394894923778201092842708112.50%11372.73%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
23Wild30200001410-61010000024-22010000126-410.1674711108090683107894923778209238682500.00%30100.00%01063207751.18%1066209350.93%667131050.92%1777105817867261381683
Total82274503403241302-6141142201301121149-2841132302102120153-33670.4092414106517080906832607894923778202695856134720102434217.28%2886876.39%31063207751.18%1066209350.93%667131050.92%1777105817867261381683
_Since Last GM Reset82274503403241302-6141142201301121149-2841132302102120153-33670.4092414106517080906832607894923778202695856134720102434217.28%2886876.39%31063207751.18%1066209350.93%667131050.92%1777105817867261381683
_Vs Conference45212100201150165-15231011001017581-6221110001007584-9450.5001502544043080906831400894923778201414461103411521813519.34%2095076.08%31063207751.18%1066209350.93%667131050.92%1777105817867261381683
_Vs Division251113001007592-171256001003638-21367000003954-15230.46075128203208090683746894923778207762517146591192218.49%1393276.98%31063207751.18%1066209350.93%667131050.92%1777105817867261381683

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8267W3241410651260726958561347201070
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8227453403241302
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4114221301121149
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4113232102120153
Derniers 10 matchs
WLOTWOTL SOWSOL
530101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2434217.28%2886876.39%3
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
894923778208090683
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
1063207751.18%1066209350.93%667131050.92%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1777105817867261381683


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
12Senateurs6Rangers4AWSommaire du match
213Senateurs2Bruins1AWSommaire du match
423Devils2Senateurs5BWSommaire du match
741Stars5Senateurs3BLSommaire du match
848Senateurs6Red Wings2AWR5Sommaire du match
1056Senateurs2Canadiens5ALR5Sommaire du match
1371Sabres6Senateurs3BLSommaire du match
1787Maple Leafs5Senateurs6BWR5Sommaire du match
19101Senateurs3Avalanche4ALXXSommaire du match
21110Sabres2Senateurs1BLR5Sommaire du match
24127Devils5Senateurs3BLSommaire du match
26139Senateurs2Sabres1AWR5Sommaire du match
28150Maple Leafs3Senateurs2BLR5Sommaire du match
30160Senateurs3Maple Leafs5ALSommaire du match
33177Oilers6Senateurs4BLSommaire du match
35183Senateurs3Canadiens4ALR5Sommaire du match
39202Oilers5Senateurs4BLXSommaire du match
41213Senateurs4Oilers6ALSommaire du match
43223Senateurs1Avalanche5ALSommaire du match
44232Stars2Senateurs3BWSommaire du match
48251Blues3Senateurs1BLSommaire du match
50263Senateurs4Maple Leafs2AWR5Sommaire du match
52273Flames5Senateurs2BLSommaire du match
54285Senateurs4Sabres2AWR5Sommaire du match
56296Flames3Senateurs2BLXSommaire du match
58309Senateurs2Ducks3ALSommaire du match
60321Senateurs2Flyers3ALXSommaire du match
62328Blackhawks3Senateurs1BLSommaire du match
65342Sabres4Senateurs1BLR5Sommaire du match
67354Senateurs5Islanders6ALSommaire du match
69367Capitals6Senateurs4BLR2Sommaire du match
71377Senateurs4Ducks2AWSommaire du match
73388Senateurs1Canadiens7ALR5Sommaire du match
76400Penguins6Senateurs2BLSommaire du match
80415Islanders1Senateurs3BWSommaire du match
82426Senateurs5Bruins3AWSommaire du match
84436Senateurs5Capitals1AWR2Sommaire du match
86444Senateurs3Bruins7ALSommaire du match
87451Sharks2Senateurs5BWSommaire du match
90463Senateurs2Blackhawks4ALSommaire du match
92474Capitals5Senateurs4BLR2Sommaire du match
94486Senateurs1Kings5ALSommaire du match
97500Avalanche3Senateurs1BLSommaire du match
99510Senateurs3Canucks4ALSommaire du match
101522Maple Leafs2Senateurs3BWR5Sommaire du match
104539Senateurs1Stars3ALSommaire du match
105546Canadiens4Senateurs2BLR5Sommaire du match
110566Devils5Senateurs4BLXXSommaire du match
114582Senateurs3Oilers2AWXSommaire du match
116592Rangers1Senateurs3BWSommaire du match
118602Senateurs3Sharks4ALSommaire du match
120614Blackhawks2Senateurs4BWSommaire du match
122626Senateurs3Sharks4ALSommaire du match
123633Senateurs4Islanders6ALSommaire du match
125644Canadiens2Senateurs3BWR5Sommaire du match
129665Red Wings2Senateurs5BWSommaire du match
132678Senateurs4Blues3AWSommaire du match
134688Predators2Senateurs3BWSommaire du match
136701Senateurs1Flames3ALSommaire du match
138710Senateurs1Red Wings10ALR5Sommaire du match
139714Red Wings4Senateurs3BLSommaire du match
142733Ducks3Senateurs2BLSommaire du match
143738Senateurs3Red Wings5ALR5Sommaire du match
146750Senateurs2Blues3ALSommaire du match
148760Wild4Senateurs2BLSommaire du match
149767Senateurs4Rangers2AWSommaire du match
151778Senateurs1Penguins3ALR2Sommaire du match
153787Penguins5Senateurs2BLSommaire du match
156809Flyers3Senateurs4BWSommaire du match
160829Canucks8Senateurs2BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
162839Senateurs5Rangers3AWSommaire du match
164851Canucks5Senateurs2BLSommaire du match
165859Senateurs4Devils2AWSommaire du match
168875Bruins1Senateurs5BWSommaire du match
171895Senateurs1Wild2ALXXSommaire du match
173902Bruins3Senateurs2BLXSommaire du match
175919Senateurs1Wild4ALSommaire du match
177927Kings4Senateurs1BLSommaire du match
180942Senateurs1Predators4ALSommaire du match
183950Kings3Senateurs4BWXSommaire du match
189969Senateurs5Predators4AWXSommaire du match
191977Flyers4Senateurs5BWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3525
Assistance79,61738,846
Assistance PCT97.09%94.75%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2889 - 96.31% 123,731$5,072,953$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
5,792,058$ 3,925,918$ 1,597,251$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 3,792,106$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 30,704$ 0$




Senateurs 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

Senateurs 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

Senateurs 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

Senateurs 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

Senateurs 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