Connexion

Senators
GP: 82 | W: 41 | L: 33 | OTL: 8 | P: 90
GF: 302 | GA: 303 | PP%: 17.56% | PK%: 75.88%
DG: Olivier Paquin | Morale : 50 | Moyenne d’équipe : 56
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Centre de jeu
Senators
41-33-8, 90pts
5
FINAL
4 Cabaret Lady Mary Ann
19-56-7, 45pts
Team Stats
L1StreakSOL1
22-18-1Home Record10-28-3
19-15-7Away Record9-28-4
3-5-2Last 10 Games3-6-1
3.68Goals Per Game3.51
3.70Goals Against Per Game5.01
17.56%Power Play Percentage22.42%
75.88%Penalty Kill Percentage70.93%
Manchots
43-30-9, 95pts
2
FINAL
1 Senators
41-33-8, 90pts
Team Stats
W2StreakL1
19-17-5Home Record22-18-1
24-13-4Away Record19-15-7
7-3-0Last 10 Games3-5-2
3.74Goals Per Game3.68
3.45Goals Against Per Game3.70
24.51%Power Play Percentage17.56%
76.39%Penalty Kill Percentage75.88%
Meneurs d'équipe
Buts
Vladimir Sobotka
17
Passes
Stephen Johns
36
Points
Stephen Johns
46
Plus/Moins
Brett Howden
6
Victoires
Keith Kinkaid
34
Pourcentage d’arrêts
Keith Kinkaid
0.909

Statistiques d’équipe
Buts pour
302
3.68 GFG
Tirs pour
3336
40.68 Avg
Pourcentage en avantage numérique
17.6%
49 GF
Début de zone offensive
40.4%
Buts contre
303
3.70 GAA
Tirs contre
3161
38.55 Avg
Pourcentage en désavantage numérique
75.9%
55 GA
Début de la zone défensive
40.5%
Information d’équipe

Directeur généralOlivier Paquin
DivisionEst
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,905
Billets de saison300


Information formation

Équipe Pro24
Équipe Mineure20
Limite contact 44 / 50
Espoirs7


Historique d'équipe

Saison actuelle41-33-8 (90PTS)
Historique41-33-10 (0.488%)
Apparitions séries éliminatoires
Historique séries éliminatoires (W-L)-


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 moyen
1Frans NielsenXXX100.007143997969626858546356758483850506403611,750,000$
2Pat MaroonX100.007991707489599067307058522573780506403211,225,000$
3Tanner JeannotXX100.00994795677662666634618073254545050640236990,000$
4Quinton Byfield (R)X100.00818182748166686278596167584444050620183925,000$
5Brendan PerliniXX100.00654489837955666326555660726464050600241850,000$
6Gabriel BourqueXX100.00834593747249665333545265406971050590301850,000$
7Isaac RatcliffeX100.00878788677965615855595270454444050590213780,833$
8Jayce HawrylukXX100.007944906770545858446058622559590505802411,300,000$
9Jansen HarkinsXX100.00634194676851665958545668255657050580232750,000$
10Kristian ReichelX100.00736590676559605670505862554444050560222560,000$
11Bowen Byram (R)X100.00824467837172616325494760254545050610193894,167$
12Martin MarincinX100.008180836680505053254641703964650506002811,400,000$
13Adam ClendeningX100.00747181637155565425474364415556050570271900,000$
14Nick DeSimoneX100.00787293657258605325523963374444050570252700,000$
15Joseph CecconiX100.00787977617966714725374162394444050570231925,000$
Rayé
1German RubtsovX100.00686784706752544964504460434444050530221925,000$
2Tomas HykaXX100.00413590694550334649474554463734050470271710,000$
3Cam Morrison (R)X100.00394545457436363945393945423230050410221825,000$
4Luke Martin (R)X100.00545584597850703325322950315858050510223700,000$
5Damir Sharipzyanov (R)X100.00394545456836363945393945423230050420241560,000$
MOYENNE D’ÉQUIPE100.0071598267735560544251506142525205057
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 SP
1Keith Kinkaid100.0061506976626163686363306161050620
2Filip Gustavsson100.0055527372555851595655304444050560
Rayé
1Artyom Zagidulin100.0055536670565651585554334844050550
2Kevin Mandolese (R)100.0050546875495050554949304444050530
MOYENNE D’ÉQUIPE100.005552697356565460565531494805057
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Tanner JeannotSenators (Ott)LW/RW715638942539522511342611831513.15%32138619.5213720741850002953435.25%12200021.36030011494
2Frans NielsenSenators (Ott)C/LW/RW6226366284041203274772159.49%4497215.682357670000125048.20%119700101.2825000136
3Brendan PerliniSenators (Ott)LW/RW82203353-314070149266771957.52%23132416.151239400000322138.30%9400000.8012000315
4Isaac RatcliffeSenators (Ott)LW74203151-55410152114219791619.13%32101713.7500036000013150.65%7700001.0000020212
5Pat MaroonSenators (Ott)LW59173451-341514877192631518.85%11125321.2437102615800041313139.81%10300000.8117001504
6Bowen ByramSenators (Ott)D80163147-196752139416550979.70%118175121.9071421792071012146330.00%000000.5400000142
7Stephen JohnsOttawaD58103646-1684101706415447926.49%113135623.3951217751770002114200.00%000000.6800020134
8Vladimir SobotkaOttawaC/LW70172946-7140107118237761907.17%4699714.26134221110002482051.95%58900000.9222000231
9Brett HowdenOttawaC/LW/RW4112304266030139185521226.49%2374018.06268371240001391257.28%93400001.1303000222
10Quinton ByfieldSenators (Ott)C7716223815461085951513310210.60%146047.8514517360003254155.70%75400001.2602020050
11Gabriel BourqueSenators (Ott)LW/RW71142135181406079173261288.09%1093713.20235271060000141142.42%6600000.7501000010
12Martin MarincinSenators (Ott)D82102535-256101186611925798.40%128159519.45358601890111130100.00%000000.4400101012
13Jayce HawrylukSenators (Ott)LW/RW4071926128030437915638.86%652613.16000219000001040.91%4400000.9900000022
14Joseph CecconiSenators (Ott)D71220228375149284315464.65%64124117.49044161070000106100.00%000000.3500010200
15Adam ClendeningSenators (Ott)D76310136640180374624406.52%91135417.820007540001115000.00%000100.1900000001
16Jansen HarkinsSenators (Ott)C/LW296612-5009587617577.89%931310.83000213000040044.78%33500000.7600000001
17Nick DeSimoneSenators (Ott)D36549627566262691419.23%5768318.99101950000041100.00%000000.2600100001
18Andrew PeekeOttawaD3033120527270.00%47224.270001900005000.00%000000.8200000010
19German RubtsovSenators (Ott)C20033-480911106130.00%11517.5600002000020044.35%11500000.4000000000
20Kristian ReichelSenators (Ott)C18213-61007233211256.25%51528.4800000000000058.79%18200000.3901000000
21Tomas HykaSenators (Ott)LW/RW14112-20021105410.00%0926.6100000000000055.56%900000.4300000000
22Luke MartinSenators (Ott)D140110601421210.00%1121515.3700001000010000.00%000000.0900000001
Statistiques d’équipe totales ou en moyenne1148260434694336016518901542289182921178.99%8421874016.3241701114731672112181080331450.98%462100220.74626273333638
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
1Keith KinkaidSenators (Ott)69342760.9093.36392810022024290360.69226686553
2Filip GustavssonSenators (Ott)155410.9074.0379000535670110.50021131110
Statistiques d’équipe totales ou en moyenne84393170.9093.47471810027329960470.679287937663


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Adam ClendeningSenators (Ott)D271992-10-26No196 Lbs6 ft0NoNoNo1Pro & Farm900,000$90,000$0$NoLien
Artyom ZagidulinSenators (Ott)G251995-08-07No180 Lbs6 ft2NoNoNo4Pro & Farm842,500$84,250$0$No842,500$842,500$842,500$Lien
Bowen ByramSenators (Ott)D192001-06-12Yes190 Lbs6 ft1NoNoNo3Pro & Farm894,167$89,417$0$No894,167$894,167$Lien
Brendan PerliniSenators (Ott)LW/RW241996-04-27No212 Lbs6 ft3NoNoNo1Pro & Farm850,000$85,000$0$NoLien
Cam MorrisonSenators (Ott)LW221998-08-27Yes212 Lbs6 ft3NoNoNo1Pro & Farm825,000$82,500$0$NoLien
Damir SharipzyanovSenators (Ott)D241996-02-17Yes205 Lbs6 ft2NoNoNo1Pro & Farm560,000$56,000$0$NoLien
Filip GustavssonSenators (Ott)G221998-06-07No184 Lbs6 ft2NoNoNo1Pro & Farm742,500$74,250$0$NoLien
Frans Nielsen (contrat à 1 volet)Senators (Ott)C/LW/RW361984-04-23No186 Lbs6 ft1NoNoNo1Pro & Farm1,750,000$1,750,000$0$NoLien
Gabriel BourqueSenators (Ott)LW/RW301990-09-23No206 Lbs5 ft10NoNoNo1Pro & Farm850,000$85,000$0$NoLien
German RubtsovSenators (Ott)C221998-06-27No178 Lbs6 ft2NoNoNo1Pro & Farm925,000$92,500$0$NoLien
Isaac RatcliffeSenators (Ott)LW211999-02-15No200 Lbs6 ft6NoNoNo3Pro & Farm780,833$78,083$0$No780,833$780,833$Lien
Jansen HarkinsSenators (Ott)C/LW231997-05-23No182 Lbs6 ft1NoNoNo2Pro & Farm750,000$75,000$0$No750,000$Lien
Jayce HawrylukSenators (Ott)LW/RW241996-01-01No196 Lbs5 ft11NoNoNo1Pro & Farm1,300,000$130,000$0$NoLien
Joseph CecconiSenators (Ott)D231997-05-23No210 Lbs6 ft3NoNoNo1Pro & Farm925,000$92,500$0$NoLien
Keith KinkaidSenators (Ott)G311989-07-03No186 Lbs6 ft3YesNoNo2Pro & Farm612,500$61,250$0$No612,500$Lien
Kevin MandoleseSenators (Ott)G202000-08-22Yes180 Lbs6 ft4NoNoNo4Pro & Farm835,000$83,500$0$No835,000$835,000$835,000$Lien
Kristian ReichelSenators (Ott)C221998-06-11No176 Lbs6 ft0NoNoNo2Pro & Farm560,000$56,000$0$No560,000$Lien
Luke MartinSenators (Ott)D221998-09-20Yes218 Lbs6 ft2NoNoNo3Pro & Farm700,000$70,000$0$No700,000$700,000$Lien
Martin MarincinSenators (Ott)D281992-02-18No210 Lbs6 ft4NoNoNo1Pro & Farm1,400,000$140,000$0$NoLien
Nick DeSimoneSenators (Ott)D251994-11-21No190 Lbs6 ft2NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Lien
Pat MaroonSenators (Ott)LW321988-04-23No238 Lbs6 ft3NoNoNo1Pro & Farm1,225,000$122,500$0$NoLien
Quinton ByfieldSenators (Ott)C182002-08-19Yes215 Lbs6 ft4NoNoNo3Pro & Farm925,000$92,500$0$No925,000$925,000$Lien
Tanner JeannotSenators (Ott)LW/RW231997-05-29No208 Lbs6 ft2YesNoNo6Pro & Farm990,000$99,000$0$No990,000$990,000$990,000$990,000$990,000$Lien
Tomas HykaSenators (Ott)LW/RW271993-03-23No160 Lbs5 ft11NoNoNo1Pro & Farm710,000$71,000$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2424.58197 Lbs6 ft21.96898,021$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tanner JeannotFrans Nielsen40113
2Pat MaroonGabriel Bourque35122
3Jansen HarkinsQuinton ByfieldBrendan Perlini20122
4Isaac RatcliffeKristian ReichelJayce Hawryluk5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Bowen ByramMartin Marincin40122
2Adam ClendeningNick DeSimone40122
3Joseph Cecconi10122
4Bowen ByramMartin Marincin10122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tanner JeannotFrans Nielsen60113
2Pat MaroonBrendan Perlini40113
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Bowen ByramMartin Marincin60113
2Adam ClendeningNick DeSimone40113
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Tanner Jeannot60131
2Frans NielsenPat Maroon40131
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Bowen ByramMartin Marincin60131
2Adam ClendeningNick DeSimone40131
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
160131Bowen ByramMartin Marincin60131
2Frans Nielsen40131Adam ClendeningNick DeSimone40131
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Tanner Jeannot60122
2Frans NielsenPat Maroon40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Bowen ByramMartin Marincin60122
2Adam ClendeningNick DeSimone40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tanner JeannotFrans NielsenBowen ByramMartin Marincin
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tanner JeannotFrans NielsenBowen ByramMartin Marincin
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, Quinton Byfield, Brendan Perlini, Quinton Byfield
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Nick DeSimone, Joseph Cecconi, Nick DeSimoneNick DeSimone, Joseph Cecconi
Tirs de pénalité
, Frans Nielsen, Tanner Jeannot, Pat Maroon,
Gardien
#1 : Keith Kinkaid, #2 : Filip Gustavsson


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
1Admirals2020000025-31010000013-21010000012-100.00023500117958212601138104811017884291641800.00%8187.50%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
2Baby Hawks211000001073110000007251010000035-220.500101828101179582128511381048110178742014438225.00%6183.33%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
3Bears311000011082110000007342010000135-230.5001019290011795821299113810481101781002531681218.33%12191.67%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
4Bruins413000001022-122110000078-120200000314-1120.250101929001179582121681138104811017817539128218211.11%6266.67%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
5Cabaret Lady Mary Ann42101000191632010100088022000000118360.7501937560011795821218211381048110178133292411119526.32%10460.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
6Caroline310010101385100010005412100001084461.000132235001179582121321138104811017810431266510110.00%10190.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
7Chiefs20001001660100010003211000000134-130.7506111700117958212821138104811017867234541119.09%20100.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
8Chill22000000945110000005231100000042241.0009142300117958212911138104811017870218456116.67%40100.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
9Comets20200000211-91010000004-41010000027-500.00022400117958212641138104811017880222138600.00%9188.89%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
10Cougars4310000017116220000009362110000088060.750173047101179582121551138104811017811925299012216.67%12283.33%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
11Crunch411001101215-320100010610-42100010065150.625121931001179582121861138104811017815953411165120.00%17382.35%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
12Heat2020000068-21010000045-11010000023-100.0006121800117958212631138104811017871221239700.00%6266.67%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
13Jayhawks20101000810-21010000025-31000100065120.50081220001179582128311381048110178912616469222.22%8187.50%11407302746.48%1329303643.77%632142544.35%2006141419225971054524
14Las Vegas211000001165110000008261010000034-120.500112031001179582121011138104811017876170525120.00%000.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
15Manchots311001009901010000012-12100010087130.5009172600117958212116113810481101781213435755120.00%8275.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
16Marlies404000001221-920200000611-520200000610-400.00012223420117958212127113810481101782015526981200.00%8362.50%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
17Minnesota211000008621010000024-21100000062420.50081422101179582128411381048110178792214447228.57%7271.43%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
18Monarchs2020000038-51010000036-31010000002-200.000336001179582128511381048110178842528471119.09%9277.78%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
19Monsters31200000913-41010000024-22110000079-220.33391625001179582121011138104811017813744227911327.27%11463.64%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
20Monsters2000000279-21000000145-11000000134-120.5007142100117958212851138104811017891281056700.00%50100.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
21Oceanics21001000963110000006421000100032141.00091423001179582127511381048110178823312475120.00%5180.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
22Oil Kings20100100710-31010000035-21000010045-110.25071320101179582128811381048110178732710405360.00%5340.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
23Phantoms31200000810-22110000067-11010000023-120.33381321101179582121231138104811017810538246310110.00%12466.67%11407302746.48%1329303643.77%632142544.35%2006141419225971054524
24Rocket440000001596220000007432200000085381.00015264100117958212160113810481101781195116988225.00%7271.43%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
25Sharks21100000911-2110000006511010000036-320.50091221001179582126011381048110178903110433133.33%4325.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
26Sound Tigers3300000015105220000009721100000063361.000152944001179582121201138104811017813348426210550.00%11372.73%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
27Spiders312000001218-620200000613-71100000065120.33312213300117958212971138104811017813318167912216.67%8275.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
28Stars21000001972110000005231000000145-130.7509152400117958212921138104811017868198551119.09%4250.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
29Thunder4310000022101221100000972220000001331060.750223961001179582122431138104811017814751189011327.27%9188.89%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
30Wolf Pack320000101394210000109721100000042261.00013213400117958212129113810481101789527176615426.67%5260.00%01407302746.48%1329303643.77%632142544.35%2006141419225971054524
Total82333305335302303-141171803021156154241161502314146149-3900.54930252782970117958212333611381048110178316193356219322794917.56%2285575.88%21407302746.48%1329303643.77%632142544.35%2006141419225971054524
_Since Last GM Reset82333305335302303-141171803021156154241161502314146149-3900.54930252782970117958212333611381048110178316193356219322794917.56%2285575.88%21407302746.48%1329303643.77%632142544.35%2006141419225971054524
_Vs Conference43182101111152164-12221011000108389-621810011016975-6420.4881522624143011795821216941138104811017817575183179851492617.45%1203174.17%11407302746.48%1329303643.77%632142544.35%2006141419225971054524

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8290L130252782933363161933562193270
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8233335335302303
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4117183021156154
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4116152314146149
Derniers 10 matchs
WLOTWOTL SOWSOL
350002
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2794917.56%2285575.88%2
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
11381048110178117958212
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
1407302746.48%1329303643.77%632142544.35%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2006141419225971054524


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
1 - 2021-10-121Senators3Marlies5LSommaire du match
4 - 2021-10-1520Wolf Pack5Senators6WSommaire du match
9 - 2021-10-2051Chiefs2Senators3WXSommaire du match
11 - 2021-10-2262Thunder4Senators1LSommaire du match
13 - 2021-10-2479Minnesota4Senators2LSommaire du match
16 - 2021-10-27105Senators3Las Vegas4LSommaire du match
18 - 2021-10-29115Senators6Jayhawks5WXSommaire du match
20 - 2021-10-31132Senators4Stars5LXXSommaire du match
22 - 2021-11-02143Cougars2Senators4WSommaire du match
24 - 2021-11-04158Sound Tigers5Senators6WSommaire du match
26 - 2021-11-06173Sharks5Senators6WSommaire du match
32 - 2021-11-12207Senators1Bruins8LSommaire du match
34 - 2021-11-14221Senators4Wolf Pack2WSommaire du match
35 - 2021-11-15225Senators6Sound Tigers3WSommaire du match
37 - 2021-11-17242Monarchs6Senators3LSommaire du match
39 - 2021-11-19256Caroline4Senators5WXSommaire du match
41 - 2021-11-21271Senators3Caroline2WXXSommaire du match
43 - 2021-11-23281Senators6Spiders5WSommaire du match
45 - 2021-11-25298Phantoms2Senators3WSommaire du match
46 - 2021-11-26304Senators2Crunch3LXSommaire du match
49 - 2021-11-29323Senators4Cougars6LSommaire du match
50 - 2021-11-30331Senators4Rocket2WSommaire du match
52 - 2021-12-02347Wolf Pack2Senators3WXXSommaire du match
55 - 2021-12-05369Senators3Monsters2WSommaire du match
57 - 2021-12-07378Bruins6Senators3LSommaire du match
59 - 2021-12-09395Senators6Minnesota2WSommaire du match
60 - 2021-12-10405Senators2Heat3LSommaire du match
63 - 2021-12-13432Senators2Comets7LSommaire du match
64 - 2021-12-14436Senators4Oil Kings5LXSommaire du match
67 - 2021-12-17452Senators2Phantoms3LSommaire du match
69 - 2021-12-19470Bruins2Senators4WSommaire du match
71 - 2021-12-21485Senators4Rocket3WSommaire du match
74 - 2021-12-24501Monsters4Senators2LSommaire du match
76 - 2021-12-26519Senators6Cabaret Lady Mary Ann4WSommaire du match
77 - 2021-12-27526Senators6Thunder2WSommaire du match
79 - 2021-12-29542Chill2Senators5WSommaire du match
81 - 2021-12-31558Phantoms5Senators3LSommaire du match
83 - 2022-01-02575Crunch5Senators6WXXSommaire du match
89 - 2022-01-08603Spiders9Senators5LSommaire du match
90 - 2022-01-09612Senators4Manchots2WSommaire du match
93 - 2022-01-12632Cabaret Lady Mary Ann4Senators5WXSommaire du match
95 - 2022-01-14648Thunder3Senators8WSommaire du match
98 - 2022-01-17667Senators1Bears2LSommaire du match
101 - 2022-01-20689Senators4Cougars2WSommaire du match
102 - 2022-01-21693Rocket2Senators3WSommaire du match
105 - 2022-01-24720Baby Hawks2Senators7WSommaire du match
107 - 2022-01-26734Las Vegas2Senators8WSommaire du match
109 - 2022-01-28746Heat5Senators4LSommaire du match
118 - 2022-02-06769Spiders4Senators1LSommaire du match
119 - 2022-02-07774Senators4Crunch2WSommaire du match
122 - 2022-02-10787Bears3Senators7WSommaire du match
123 - 2022-02-11796Senators3Marlies5LSommaire du match
126 - 2022-02-14819Admirals3Senators1LSommaire du match
128 - 2022-02-16833Monsters5Senators4LXXSommaire du match
130 - 2022-02-18843Senators3Oceanics2WXSommaire du match
133 - 2022-02-21874Senators3Monsters4LXXSommaire du match
135 - 2022-02-23885Jayhawks5Senators2LSommaire du match
137 - 2022-02-25901Marlies5Senators2LSommaire du match
138 - 2022-02-26911Stars2Senators5WSommaire du match
140 - 2022-02-28922Crunch5Senators0LSommaire du match
142 - 2022-03-02937Oceanics4Senators6WSommaire du match
144 - 2022-03-04952Rocket2Senators4WSommaire du match
146 - 2022-03-06967Senators4Monsters7LSommaire du match
147 - 2022-03-07977Senators4Chill2WSommaire du match
149 - 2022-03-09988Comets4Senators0LSommaire du match
151 - 2022-03-111005Cougars1Senators5WSommaire du match
154 - 2022-03-141022Senators4Manchots5LXSommaire du match
156 - 2022-03-161038Sound Tigers2Senators3WSommaire du match
158 - 2022-03-181053Senators3Sharks6LSommaire du match
161 - 2022-03-211078Senators1Admirals2LSommaire du match
162 - 2022-03-221082Senators0Monarchs2LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
164 - 2022-03-241095Senators3Baby Hawks5LSommaire du match
166 - 2022-03-261111Senators3Chiefs4LXXSommaire du match
169 - 2022-03-291132Oil Kings5Senators3LSommaire du match
171 - 2022-03-311147Senators2Bears3LXXSommaire du match
172 - 2022-04-011158Senators5Caroline2WSommaire du match
175 - 2022-04-041182Cabaret Lady Mary Ann4Senators3LSommaire du match
177 - 2022-04-061191Senators2Bruins6LSommaire du match
179 - 2022-04-081209Marlies6Senators4LSommaire du match
182 - 2022-04-111228Senators7Thunder1WSommaire du match
184 - 2022-04-131243Senators5Cabaret Lady Mary Ann4WSommaire du match
186 - 2022-04-151263Manchots2Senators1LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5020
Assistance50,57927,521
Assistance PCT61.68%67.12%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 1905 - 63.50% 75,107$3,079,370$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,383,545$ 1,980,250$ 1,980,250$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,590$ 2,383,545$ 23 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 10,590$ 0$




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