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Connexion

Senators
GP: 61 | W: 30 | L: 24 | OTL: 7 | P: 67
GF: 219 | GA: 236 | PP%: 35.92% | PK%: 70.56%
DG: NFHL | Morale : 92 | Moyenne d’équipe : N/A
Prochains matchs #972 vs Blood Miners

Centre de jeu
Rocket
24-32-5, 53pts
8
FINAL
6 Senators
30-24-7, 67pts
Team Stats
W1SéquenceW1
9-19-2Fiche domicile15-9-6
15-13-3Fiche domicile15-15-1
8-2-0Derniers 10 matchs3-7-0
3.20Buts par match 3.59
4.00Buts contre par match 3.87
27.09%Pourcentage en avantage numérique35.92%
69.69%Pourcentage en désavantage numérique70.56%
Grisards
30-27-5, 65pts
2
FINAL
3 Senators
30-24-7, 67pts
Team Stats
W1SéquenceW1
18-11-1Fiche domicile15-9-6
12-16-4Fiche domicile15-15-1
6-3-1Derniers 10 matchs3-7-0
3.81Buts par match 3.59
3.95Buts contre par match 3.87
26.98%Pourcentage en avantage numérique35.92%
72.73%Pourcentage en désavantage numérique70.56%
Senators
30-24-7, 67pts
Jour 136
Blood Miners
29-25-5, 63pts
Statistiques d’équipe
W1SéquenceSOL1
15-9-6Fiche domicile17-11-2
15-15-1Fiche visiteur12-14-3
3-7-010 derniers matchs2-5-3
3.59Buts par match 3.19
3.87Buts contre par match 3.19
35.92%Pourcentage en avantage numérique24.79%
70.56%Pourcentage en désavantage numérique71.91%
Senators
30-24-7, 67pts
Jour 138
Penguins
33-25-4, 70pts
Statistiques d’équipe
W1SéquenceL1
15-9-6Fiche domicile16-13-1
15-15-1Fiche visiteur17-12-3
3-7-010 derniers matchs4-3-3
3.59Buts par match 3.27
3.87Buts contre par match 3.27
35.92%Pourcentage en avantage numérique28.33%
70.56%Pourcentage en désavantage numérique69.43%
Americans
28-27-6, 62pts
Jour 139
Senators
30-24-7, 67pts
Statistiques d’équipe
W1SéquenceW1
14-11-5Fiche domicile15-9-6
14-16-1Fiche visiteur15-15-1
7-2-110 derniers matchs3-7-0
3.46Buts par match 3.59
3.87Buts contre par match 3.59
32.95%Pourcentage en avantage numérique35.92%
69.49%Pourcentage en désavantage numérique70.56%
Meneurs d'équipe
Buts
Olle Lycksell
37
Passes
Anthony Richard
36
Points
Olle Lycksell
67
Plus/Moins
Gavin White
5
Victoires
Philip Svedeback
22
Pourcentage d’arrêts
Ivan Prosvetov
0.896

Statistiques d’équipe
Buts pour
219
3.59 GFG
Tirs pour
1876
30.75 Avg
Pourcentage en avantage numérique
35.9%
88 GF
Début de zone offensive
37.0%
Buts contre
236
3.87 GAA
Tirs contre
1877
30.77 Avg
Pourcentage en désavantage numérique
70.6%%
73 GA
Début de la zone défensive
35.9%
Informations de l'équipe

Directeur généralNFHL
EntraîneurJeff Halpern
DivisionNorth Division
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité8,000
Assistance7,381
Billets de saison800


Informations de la formation

Équipe Pro32
Équipe Mineure21
Limite contact 53 / 65
Espoirs17


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
1Aidan McDonoughXX100.0060606060607070606060606060506408600251926,100$
2Rafael Harvey-PinardXX100.00625092686875836261646167655662074002521,350,000$
3Bradley MarekXXX100.0060606060607070606060606060445705200241682,500$
4Olle LycksellXX100.0060509273627889716272706665526007800251826,875$
5Anthony RichardX100.0060508872707988696170696765686907100281650,000$
6Lucas CondottaXX100.0063508267827592647366636965405507600272650,000$
7Carter MazurXX100.0060509171657576646164646565405507200221975,000$
8Dalibor DvorskyXXX100.00605092707676906468646365654055085011921,500,000$
9Joey Willis (R)XX100.0060606060607070606060606060465505300193750,000$
10Nolan AllanX100.00725092777482897225686575655057074002141,250,000$
11Simon LundmarkX100.00606060606070706060606060605359079002411,074,938$
12Nikolai KnyzhovX100.0060606060607070606060606060495904500261882,000$
13Michael CallahanX100.0060568962768189662567657165526208500251810,338$
14Drew BavaroX100.0060606060607070606060606060405506100241750,000$
15Theo LindsteinXX100.00606060606070706060606060604055069011921,250,000$
16Frederic BrunetXX100.0062509169758192622563617365405507501212825,000$
17Scott MorrowX100.00605086737982916825706769654055080012211,250,000$
18Dominik Badinka (R)X100.00606060606070706060606060604455052001931,250,000$
Rayé
1Zack MacEwenXX100.0078668566867583696165677065566406600281650,000$
2Lucas CionaXX100.0060606060607070606060606060405505500211700,000$
3Sean TschigerlXX100.0060606060607070606060606060405503200211975,000$
4Jesse NurmiXX100.0060606060607070606060606060405506001192750,000$
5Topi RonniX100.0060606060607070606060606060405504801202975,000$
6Marek Vanacker (R)X100.00606060606070706060606060604655059001831,500,000$
7Andrei Loshko (R)X100.0060606060607070606060606060485507600203750,000$
8Alex Bump (R)X100.0060606060607070606060606060445505900212700,000$
9Gavin WhiteX100.0060606060607070606060606060405504300221750,000$
10Konnor Smith (R)X100.0060606060607070606060606060505505800203825,000$
MOYENNE D’ÉQUIPE100.006157716465737763566362636246570650
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
1Damian Clara100.006070706060606060606060425007801192975,000$
2Philip Svedeback (R)100.006070706060606060606060465507400222750,000$
Rayé
1Ivan Prosvetov100.006070706060606060606060526308100251826,875$
2Anson Thornton100.006070706060606060606060405506800211650,000$
MOYENNE D’ÉQUIPE100.00607070606060606060606045560750
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jeff Halpern6477778163681USA493600,000$


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
1Olle LycksellSenators (OTT)LW/RW58373067-12633570762316012416.02%35118220.3916132952153112111354151.04%3863312131.1316115831
2Anthony RichardSenators (OTT)C58243660-1229573812186010011.01%18117720.291016263511701141044249.53%9613423011.0225100265
3Dalibor DvorskySenators (OTT)C/LW/RW61282957121159293166499016.87%19113418.59161834361551014803050.90%7252815011.0100102126
4Carter MazurSenators (OTT)LW/RW5822305221006676127428317.32%3097116.754131712942024482044.51%1732513001.0700000541
5Nolan AllanSenators (OTT)D61143650-164030819616172708.70%83159126.097142121163033617721100.00%14246000.6311114432
6Zack MacEwenSenators (OTT)LW/RW59212647-18905011777176447811.93%31119120.206111728152011131443148.03%4061522100.7916343310
7Rafael Harvey-PinardSenators (OTT)LW/RW59222143-128207749119427118.49%23100817.0910122221144101182239.47%38209000.8513121224
8Lucas CondottaSenators (OTT)LW/RW49122739-672209180114397410.53%1792818.9681523191051126963147.89%71127000.8411003222
9Michael CallahanSenators (OTT)D6162127-23633550858130337.41%66142923.433811131600004172100%12040000.3800304011
10Scott MorrowSenators (OTT)D5852025-4723047758038366.25%70126521.82369101230115137000%03032000.4000222010
11Frederic BrunetSenators (OTT)C/D4941822-16161048687332325.48%51104321.2938111411501111130217.39%231521000.4213200110
12Aidan McDonoughSenators (OTT)LW/RW5571017-181032566477124459.86%1477914.170002210000340052.80%1251211000.4400302111
13Andrei LoshkoSenators (OTT)RW38411152631556385117197.84%1348812.86000021012130149.09%11049000.6100003003
14Simon LundmarkSenators (OTT)D59178-686404949318123.23%3488615.02112576000063000%0916000.1800215010
15Marek VanackerSenators (OTT)LW23617-749152593972615.38%623510.2401125000003138.10%2176000.5900201100
16Alex BumpSenators (OTT)LW47235-1190403422237238.70%73958.41101222000000046.67%10538000.2512152000
17Joey WillisSenators (OTT)C/LW27055-220101514235100%21826.7500000000000051.65%9102000.5500020000
18Drew BavaroSenators (OTT)D32033-1123517287640%846014.380000100005000%049000.1300010000
19Theo LindsteinSenators (OTT)C/D250333195172212460%1033113.2700006000030037.50%1614000.1800100000
20Konnor SmithSenators (OTT)D19033120015108780%1426213.840000000007000%016000.2300000000
21Dominik BadinkaSenators (OTT)D250331642014159210%1327110.8500000011016000%006000.2200121000
22Bradley MarekSenators (OTT)C/LW/RW22022-117512815390%41577.1500003000190058.33%3610000.2500010000
23Lucas CionaSenators (OTT)LW/RW25022-242202920156170%22389.56000000000100081.25%1624000.1700112000
24Charlie ElickSenatorsD21022240311010%1512.450000000001000%021000.7800000000
25Nikolai KnyzhovSenators (OTT)D10011-137151135110%210810.8601116000011000%003000.1800201000
26Sean TschigerlSenators (OTT)LW/RW7011-28012102120%28712.4500000000000041.67%2402000.2300000000
27Jesse NurmiSenators (OTT)LW/RW19101-14014160216.67%2663.4800000000000026.67%1503000.3000000000
28Gavin WhiteSenators (OTT)D2000500204110%03216.450000000001000%01100000000000
29Topi RonniSenators (OTT)C11000-4262017128350%113512.2800000000000044.68%470200000013000
Statistiques d’équipe totales ou en moyenne1098216351567-157117948512201165187661098311.51%5781809416.4888137225273163671017621397271249.16%3391321333250.63927282444302826
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
1Philip SvedebackSenators (OTT)47221750.8753.582596011551241707410.59122458010
2Ivan ProsvetovSenators (OTT)207420.8963.578910053512289120.66761338010
3Damian ClaraSenators (OTT)51300.8425.352130019120651100314000
Statistiques d’équipe totales ou en moyenne72302470.8793.683701012271873106164286160020


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Aidan McDonoughSenators (OTT)LW/RW251999-11-06USANo190 Lbs6 ft3NoNoN/ANoNo12025-09-08FalseFalsePro & Farm926,100$261,081$92,610$26,108$No---------------------------
Alex BumpSenators (OTT)LW212003-11-20USAYes194 Lbs5 ft10NoNoProspectNoNo22025-08-30FalseFalsePro & Farm700,000$197,340$70,000$19,734$No700,000$--------700,000$--------No--------
Andrei LoshkoSenators (OTT)RW202004-10-07BLRYes183 Lbs5 ft11NoNoProspectNoNo32025-08-20FalseFalsePro & Farm750,000$211,436$75,000$21,144$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Anson ThorntonSenators (OTT)G212003-06-28CANNo181 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm650,000$183,245$65,000$18,324$No---------------------------
Anthony RichardSenators (OTT)C281996-12-20CANNo185 Lbs5 ft10NoNoFree AgentNoNo12025-06-26FalseFalsePro & Farm650,000$183,245$65,000$18,324$No---------------------------
Bradley MarekSenators (OTT)C/LW/RW242000-11-13USANo212 Lbs6 ft3NoNoN/ANoNo12025-09-08FalseFalsePro & Farm682,500$192,407$68,250$19,241$No---------------------------
Carter MazurSenators (OTT)LW/RW222002-03-28USANo170 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm975,000$274,867$97,500$27,487$No---------------------------
Dalibor DvorskySenators (OTT)C/LW/RW192005-06-15SVKNo201 Lbs6 ft1NoNoProspectNoNo22024-08-27FalseFalsePro & Farm1,500,000$422,872$150,000$42,287$No1,500,000$--------1,500,000$--------No--------
Damian ClaraSenators (OTT)G192005-01-13ITANo214 Lbs6 ft6NoNoProspectNoNo22024-08-27FalseFalsePro & Farm975,000$274,867$97,500$27,487$No975,000$--------975,000$--------No--------
Dominik BadinkaSenators (OTT)D192005-11-27CZEYes205 Lbs6 ft1NoNoDraftNoNo32025-08-30FalseFalsePro & Farm1,250,000$352,394$125,000$35,239$No1,250,000$1,250,000$-------1,250,000$1,250,000$-------NoNo-------
Drew BavaroSenators (OTT)D242000-06-10USANo198 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm750,000$211,436$75,000$21,144$No---------------------------
Frederic BrunetSenators (OTT)C/D212003-08-21CANNo196 Lbs6 ft3NoNoProspectNoNo22024-08-27FalseFalsePro & Farm825,000$232,580$82,500$23,258$No825,000$--------825,000$--------No--------
Gavin WhiteSenators (OTT)D222002-11-12CANNo192 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm750,000$211,436$75,000$21,144$No---------------------------
Ivan ProsvetovSenators (OTT)G251999-03-05RUSNo176 Lbs6 ft5NoNoN/ANoNo12025-09-08FalseFalsePro & Farm826,875$233,108$82,688$23,311$No---------------------------
Jesse NurmiSenators (OTT)LW/RW192005-03-07FINNo172 Lbs6 ft0NoNoProspectNoNo22024-08-27FalseFalsePro & Farm750,000$211,436$75,000$21,144$No750,000$--------750,000$--------No--------
Joey WillisSenators (OTT)C/LW192005-05-14USAYes185 Lbs5 ft9NoNoProspectNoNo32025-08-30FalseFalsePro & Farm750,000$211,436$75,000$21,144$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Konnor SmithSenators (OTT)D202004-11-06CANYes216 Lbs6 ft4NoNoProspectNoNo32025-08-20FalseFalsePro & Farm825,000$232,580$82,500$23,258$No825,000$825,000$-------825,000$825,000$-------NoNo-------
Lucas CionaSenators (OTT)LW/RW212003-01-08CANNo223 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm700,000$197,340$70,000$19,734$No---------------------------
Lucas CondottaSenators (OTT)LW/RW271997-11-06CANNo218 Lbs6 ft1NoNoFree AgentNoNo22025-06-26FalseFalsePro & Farm650,000$183,245$65,000$18,324$No650,000$--------650,000$--------No--------
Marek VanackerSenators (OTT)LW182006-04-12CANYes170 Lbs5 ft11NoNoDraftNoNo32025-08-20FalseFalsePro & Farm1,500,000$422,872$150,000$42,287$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------
Michael CallahanSenators (OTT)D251999-09-23USANo199 Lbs6 ft2NoNoN/ANoNo12025-09-08FalseFalsePro & Farm810,338$228,446$81,034$22,845$No---------------------------
Nikolai KnyzhovSenators (OTT)D261998-03-20RUSNo222 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm882,000$248,649$88,200$24,865$No---------------------------
Nolan AllanSenators (OTT)D212003-04-28CANNo195 Lbs6 ft2NoNoN/ANoNo42025-09-08FalseFalsePro & Farm1,250,000$352,394$125,000$35,239$No1,250,000$1,250,000$1,250,000$------1,250,000$1,250,000$1,250,000$------NoNoNo------
Olle LycksellSenators (OTT)LW/RW251999-08-24SWENo163 Lbs5 ft10NoNoN/ANoNo12025-09-08FalseFalsePro & Farm826,875$233,108$82,688$23,311$No---------------------------
Philip SvedebackSenators (OTT)G222002-05-28SWEYes209 Lbs6 ft2NoNoProspectNoNo22025-08-30FalseFalsePro & Farm750,000$211,436$75,000$21,144$No750,000$--------750,000$--------No--------
Rafael Harvey-PinardSenators (OTT)LW/RW251999-01-06CANNo181 Lbs5 ft9NoNoN/ANoNo2FalseFalsePro & Farm1,350,000$380,585$135,000$38,059$No1,350,000$--------1,350,000$--------No--------
Scott MorrowSenators (OTT)D222002-11-01USANo210 Lbs6 ft2NoNoProspectNoNo12024-08-27FalseFalsePro & Farm1,250,000$352,394$125,000$35,239$No---------------------------
Sean TschigerlSenators (OTT)LW/RW212003-04-11CANNo190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm975,000$274,867$97,500$27,487$No---------------------------
Simon LundmarkSenators (OTT)D242000-10-08SWENo201 Lbs6 ft2NoNoN/ANoNo12025-09-08FalseFalsePro & Farm1,074,938$303,041$107,494$30,304$No---------------------------
Theo LindsteinSenators (OTT)C/D192005-01-05SWENo185 Lbs6 ft0NoNoProspectNoNo22024-08-27FalseFalsePro & Farm1,250,000$352,394$125,000$35,239$No1,250,000$--------1,250,000$--------No--------
Topi RonniSenators (OTT)C202004-05-05FINNo185 Lbs6 ft2NoNoProspectNoNo22024-08-27FalseFalsePro & Farm975,000$274,867$97,500$27,487$No975,000$--------975,000$--------No--------
Zack MacEwenSenators (OTT)LW/RW281996-07-08CANNo227 Lbs6 ft4NoNoFree AgentNoNo12025-06-26FalseFalsePro & Farm650,000$183,245$65,000$18,324$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3222.25195 Lbs6 ft11.72919,676$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Theo LindsteinOlle LycksellRafael Harvey-Pinard28122
2Lucas CondottaDalibor DvorskyAnthony Richard28122
3Carter MazurAidan McDonoughJoey Willis25122
4Aidan McDonoughAnthony RichardFrederic Brunet19122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nolan AllanMichael Callahan28122
2Scott MorrowFrederic Brunet28122
3Drew BavaroSimon Lundmark25122
4Nolan AllanMichael Callahan19122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anthony RichardOlle LycksellCarter Mazur50122
2Lucas CondottaDalibor DvorskyAidan McDonough50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nolan AllanMichael Callahan50122
2Scott MorrowFrederic Brunet50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Carter MazurOlle Lycksell50122
2Dalibor DvorskyLucas Condotta50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nolan AllanMichael Callahan50122
2Scott MorrowFrederic Brunet50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Lucas Condotta50122Nolan AllanMichael Callahan50122
2Carter Mazur50122Scott MorrowFrederic Brunet50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Olle LycksellAnthony Richard50122
2Carter MazurLucas Condotta50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nolan AllanMichael Callahan50122
2Scott MorrowFrederic Brunet50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Anthony RichardOlle LycksellFrederic BrunetNolan AllanMichael Callahan
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Anthony RichardOlle LycksellFrederic BrunetNolan AllanMichael Callahan
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Lucas Condotta, Carter Mazur, Frederic BrunetFrederic Brunet, Carter MazurFrederic Brunet
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Michael Callahan, Nolan Allan, Scott MorrowNolan AllanMichael Callahan, Scott Morrow
Tirs de pénalité
Olle Lycksell, Dalibor Dvorsky, Carter Mazur, Frederic Brunet, Lucas Condotta
Gardien
#1 : Philip Svedeback, #2 : Damian Clara


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
1Admirals422000001216-41100000032131200000914-540.50012172900487590121175676346604214648886320630.00%19573.68%1615125549.00%605121749.71%44791948.64%121358411906231300645
2Americans431000002417711000000743321000001713460.7502435590048759012153567634660421233410165261246.15%18666.67%0615125549.00%605121749.71%44791948.64%121358411906231300645
3Bears422000001013-33210000010821010000005-540.50010182811487590121055676346604211343466414535.71%13469.23%0615125549.00%605121749.71%44791948.64%121358411906231300645
4Bills11000000532000000000001100000053221.0005611004875901243567634660422094234375.00%2150.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
5Blossom Bytes30200001713-62010000159-41010000024-210.16771219104875901299567634660429126396414214.29%17476.47%2615125549.00%605121749.71%44791948.64%121358411906231300645
6Bulldogs1010000035-21010000035-20000000000000.0003691048759012335676346604236613206233.33%40100.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
7Crunch1010000026-4000000000001010000026-400.0002350048759012245676346604232912194125.00%6183.33%0615125549.00%605121749.71%44791948.64%121358411906231300645
8Eagles20200000510-50000000000020200000510-500.0005101510487590126856763466042914230373133.33%10550.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
9Gorillas2010001078-1100000104311010000035-220.5007101700487590128456763466042591639394125.00%7185.71%0615125549.00%605121749.71%44791948.64%121358411906231300645
10Griffins20101000550000000000002010100055020.500581300487590124156763466042592023557342.86%9277.78%0615125549.00%605121749.71%44791948.64%121358411906231300645
11Grisards3100100112933100100112930000000000050.833121931004875901298567634660429529626511436.36%12466.67%2615125549.00%605121749.71%44791948.64%121358411906231300645
12Gulls2200000010460000000000022000000104641.00010152500487590126456763466042461027414125.00%6183.33%0615125549.00%605121749.71%44791948.64%121358411906231300645
13Moose31200000712-5211000006601010000016-520.3337142100487590128656763466042812758819333.33%14471.43%0615125549.00%605121749.71%44791948.64%121358411906231300645
14Mountaineers1010000024-2000000000001010000024-200.000246004875901240567634660422451927100.00%20100.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
15Norsemen421000101815331100010131211100000053260.75018264400487590121295676346604215251668914428.57%13376.92%0615125549.00%605121749.71%44791948.64%121358411906231300645
16Octopus11000000514000000000001100000051421.000591400487590122756763466042311436204250.00%30100.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
17Penguins11000000642110000006420000000000021.0006101600487590123956763466042361030175480.00%50100.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
18Phantoms20000011880200000118800000000000030.7508132100487590126456763466042791665337228.57%10550.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
19Rams30300000518-1320200000314-111010000024-200.000581300487590127056763466042932569566350.00%12650.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
20Reign1010000024-21010000024-20000000000000.0002240048759012215676346604222522204250.00%6183.33%0615125549.00%605121749.71%44791948.64%121358411906231300645
21Rocket1010000068-21010000068-20000000000000.0006111700487590123156763466042251218187457.14%4250.00%1615125549.00%605121749.71%44791948.64%121358411906231300645
22Saints1010000026-4000000000001010000026-400.00023500487590122256763466042341115265120.00%5340.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
23Silver Knights11000000422110000004220000000000021.0004711004875901224567634660422684206116.67%20100.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
24Titans320000011266210000017521100000051450.83312183000487590127256763466042722247618337.50%11281.82%0615125549.00%605121749.71%44791948.64%121358411906231300645
25Whalers21000100990000000000002100010099030.75091322004875901256567634660425925323611545.45%11463.64%0615125549.00%605121749.71%44791948.64%121358411906231300645
26White Wolves1000000134-11000000134-10000000000010.500358004875901240567634660422734721800.00%110.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
27Wolf Pack3300000015961100000053222000000106461.00015264100487590121085676346604210528256215640.00%10280.00%0615125549.00%605121749.71%44791948.64%121358411906231300645
28Wolves411011001317-41000010023-1311010001114-350.625132336004875901211856763466042100241427818738.89%16662.50%1615125549.00%605121749.71%44791948.64%121358411906231300645
Total61242403235219236-173011901135109113-431131502100110123-13670.54921935157041487590121876567634660421877578117912202458835.92%2487370.56%7615125549.00%605121749.71%44791948.64%121358411906231300645
_Since Last GM Reset61242403235219236-173011901135109113-431131502100110123-13670.54921935157041487590121876567634660421877578117912202458835.92%2487370.56%7615125549.00%605121749.71%44791948.64%121358411906231300645
_Vs Conference45211402224168170-224106011248787021118011008183-2560.622168267435214875901213785676346604213914188978751826736.81%1875670.05%6615125549.00%605121749.71%44791948.64%121358411906231300645
_Vs Division199502222726111134201122524012653011002021-1300.78972118190114875901261056763466042583169333368652538.46%701874.29%2615125549.00%605121749.71%44791948.64%121358411906231300645

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6167W1219351570187618775781179122041
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6124243235219236
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
301191135109113
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3113152100110123
Derniers 10 matchs
WLOTWOTL SOWSOL
370000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2458835.92%2487370.56%7
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
5676346604248759012
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
615125549.00%605121749.71%44791948.64%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
121358411906231300645


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
18Grisards5Senators4LXXSommaire du match
536Blossom Bytes4Senators1LSommaire du match
855Senators1Moose6LSommaire du match
968Norsemen5Senators3LSommaire du match
1288Senators4Whalers3WSommaire du match
14100Phantoms5Senators4LXXSommaire du match
17122Senators3Wolves1WSommaire du match
18135Moose5Senators1LSommaire du match
21155Senators5Whalers6LXSommaire du match
22161Senators1Admirals6LSommaire du match
24176Bears2Senators3WSommaire du match
28197Grisards2Senators5WSommaire du match
29204Senators11Americans5WSommaire du match
32229Senators2Americans6LSommaire du match
34237Penguins4Senators6WSommaire du match
37264Bulldogs5Senators3LSommaire du match
40281Senators3Gorillas5LSommaire du match
42290Senators5Admirals3WSommaire du match
44304Moose1Senators5WSommaire du match
47328Gorillas3Senators4WXXSommaire du match
49339Senators2Blossom Bytes4LSommaire du match
51358Wolf Pack3Senators5WSommaire du match
53377Senators6Wolves5WXSommaire du match
55391Norsemen5Senators6WXXSommaire du match
56402Senators2Mountaineers4LSommaire du match
59422Titans1Senators4WSommaire du match
61431Senators3Griffins2WXSommaire du match
63452Senators5Octopus1WSommaire du match
66464Phantoms3Senators4WXXSommaire du match
68482Senators6Gulls2WSommaire du match
70495Senators2Wolves8LSommaire du match
71499White Wolves4Senators3LXXSommaire du match
75526Silver Knights2Senators4WSommaire du match
78550Senators2Griffins3LSommaire du match
80559Titans4Senators3LXXSommaire du match
82575Senators2Crunch6LSommaire du match
84590Bears0Senators3WSommaire du match
86604Senators5Titans1WSommaire du match
88619Bears6Senators4LSommaire du match
90628Senators6Wolf Pack3WSommaire du match
92646Senators3Admirals5LSommaire du match
93660Norsemen2Senators4WSommaire du match
96679Senators4Eagles6LSommaire du match
97691Wolves3Senators2LXSommaire du match
100710Senators5Bills3WSommaire du match
102720Admirals2Senators3WSommaire du match
104734Senators0Bears5LSommaire du match
106751Senators4Wolf Pack3WSommaire du match
108762Americans4Senators7WSommaire du match
110779Senators4Americans2WSommaire du match
112793Blossom Bytes5Senators4LXXSommaire du match
114809Senators2Rams4LSommaire du match
115817Senators5Norsemen3WSommaire du match
117827Rams2Senators0LSommaire du match
121854Reign4Senators2LSommaire du match
123872Senators1Eagles4LSommaire du match
125887Rams12Senators3LSommaire du match
126898Senators4Gulls2WSommaire du match
128917Senators2Saints6LSommaire du match
129925Rocket8Senators6LSommaire du match
133951Grisards2Senators3WXSommaire du match
136972Senators-Blood Miners-
138981Senators-Penguins-
139989Americans-Senators-
1411011Whalers-Senators-
1461042Gulls-Senators-
1491065Senators-Whalers-
1501075Wolves-Senators-
1541102Penguins-Senators-
1561115Senators-Grisards-
1571132Senators-Norsemen-
1591140Phantoms-Senators-
1621164Gulls-Senators-
1641175Senators-Grisards-
1671197Blossom Bytes-Senators-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1711222Roadrunners-Senators-
1761252Whalers-Senators-
1771258Senators-Moose-
1801275Senators-Phantoms-
1821284Redhawks-Senators-
1831287Senators-Moose-
1861307Senators-Phantoms-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité25005500
Prix des billets3414
Assistance68,110153,319
Assistance PCT90.81%92.92%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
11 7381 - 92.26% 178,488$5,354,648$8000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,582,683$ 2,942,964$ 2,942,964$ 600,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
18,846$ 2,582,683$ 32 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,963,371$ 53 18,846$ 998,838$




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