Connexion

BROOKLYN GRINDERS
GP: 6 | W: 2 | L: 4
GF: 12 | GA: 14 | PP%: 6.67% | PK%: 100.00%
DG: Kyle B | Morale : 44 | Moyenne d’équipe : 64
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Centre de jeu
BROOKLYN GRINDERS
2-4-0, 4pts
3
FINAL
4 HALIFAX HELL
7-3-0, 14pts
Team Stats
L2SéquenceW1
2-1-0Fiche domicile5-0-0
0-3-0Fiche domicile2-3-0
2-4-0Derniers 10 matchs7-3-0
2.00Buts par match 3.20
2.33Buts contre par match 2.40
6.67%Pourcentage en avantage numérique30.43%
100.00%Pourcentage en désavantage numérique89.47%
HALIFAX HELL
7-3-0, 14pts
2
FINAL
1 BROOKLYN GRINDERS
2-4-0, 4pts
Team Stats
W1SéquenceL2
5-0-0Fiche domicile2-1-0
2-3-0Fiche domicile0-3-0
7-3-0Derniers 10 matchs2-4-0
3.20Buts par match 2.00
2.40Buts contre par match 2.33
30.43%Pourcentage en avantage numérique6.67%
89.47%Pourcentage en désavantage numérique100.00%
Meneurs d'équipe
Buts
Nicklas Jensen
2
Passes
Ian Cole
2
Points
Ian Cole
3
Plus/Moins
Tobias Björnfot
2
Victoires
Matt Hackett
2
Pourcentage d’arrêts
Matt Hackett
0.905

Statistiques d’équipe
Buts pour
12
2.00 GFG
Tirs pour
146
24.33 Avg
Pourcentage en avantage numérique
6.7%
1 GF
Début de zone offensive
41.2%
Buts contre
14
2.33 GAA
Tirs contre
147
24.50 Avg
Pourcentage en désavantage numérique
100.0%%
0 GA
Début de la zone défensive
34.2%
Informations de l'équipe

Directeur généralKyle B
EntraîneurDarryl Sutter
DivisionSmythe
ConférenceRosling Conference
Capitaine
Assistant #1
Assistant #2Evgeny Svechnikov


Informations de l’aréna

Capacité3,000
Assistance3,000
Billets de saison300


Informations de la formation

Équipe Pro32
Équipe Mineure22
Limite contact 54 / 66
Espoirs0


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire
1Evgeny Svechnikov (A)XXX100.009981508484938578687470556899950817412721,133,000$
2Nicklas JensenXX100.007950695981808977507470805399990757323111,937,500$
3Nathan BastianX100.00782872898986876848686867559578075722262650,000$
4Christian FischerX100.008199718189867043697161598379063672272890,000$
5Zach Dean (R)X100.0043782787973686567595662575883070631212700,000$
6Kirill Marchenko (R)XX100.001197797476856357566758607472074632231845,000$
7Marco Kasper (R)X100.0042793686575696264605861557070068611203900,000$
8Scott TimminsX100.00605076617670705170505371579192019610341500,000$
9Gage Goncalves (R)X100.00563382747877776249585255566361061612231550,000$
10Brandon SutterXX100.001199657661865384325088769999019600351500,000$
11Dmitri Buchelnikov (R)X100.00261968697268706550595863586560065602193600,000$
12Aleksanteri Kaskimaki (R)X100.0010584676766706462595762485863066592193500,000$
13Jeremy LauzonX100.00871790818390826744665860448373070712263800,000$
14Andrew PeekeX100.00999347868784896534555963448569019712252650,000$
15Matt CorrenteX100.00939326617662688250766961569999050700361600,000$
16Ian ColeX100.00261699558056748450787671589385068670352910,000$
17Mirco MuellerX100.00354996583748773436456714495830326712911,000,000$
18Corson Ceulemans (R)X100.00657079787876656344595169446964074661202800,000$
19Tobias Björnfot (R)X100.0037690757471745944645366507674050641233650,000$
Rayé
1Ryan WhiteX100.00988737617561676575656260689999020650362829,000$
2Mattias TedenbyX100.00111996473667759366562787799990206403431,450,000$
3Cameron AbneyX100.001199657474715940545573589298020612331500,000$
4Dana TyrellXX100.00473695647376795361454770589999020600351500,000$
5Nick PalmieriX100.00322199568269774681394871639390019580341500,000$
6Cross Hanas (R)X100.00544697707465675552525258596358020572211600,000$
7Alexander Campbell (R)X100.00264376687365645456565458556667020572223600,000$
8Carter Mazur (R)X100.0021398697266635243514957546161020552202550,000$
9Luca SbisaX100.006127995880828267506640797899900196903421,030,000$
10Dennis PerssonX100.00366380647569763850413274709999020620351500,000$
MOYENNE D’ÉQUIPE100.0046318269777376635459576658848104564
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
1Matt Hackett100.00706774766870727479656599870537203411,100,000$
2Jakub Málek (R)100.0061636276696164636458586361083632202500,000$
Rayé
1Joseph Woll (R)100.0066747680706869727064578669076702252650,000$
MOYENNE D’ÉQUIPE100.006668717769666870716260837207168
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Darryl Sutter79787691999951CAN5921,132,000$


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
1Matt BoldyBROOKLYN BLAZERSLW/RW6336-1208111651018.75%713322.31011012000050066.67%960000.9000000110
2Rasmus SandinBROOKLYN BLAZERSD6044-4007310640%713622.6900001500001000%055000.5900000100
3Ryan DonatoBROOKLYN BLAZERSC6224-1001126189911.11%513622.77000112000090042.15%12132000.5900000010
4Ian ColeBROOKLYN GRINDERS (BRK)D41230003473114.29%810025.2101101200008000%013000.6000000000
5Marco KasperBROOKLYN GRINDERS (BRK)C4022000321230%16716.75000010000020028.57%1410000.6000000000
6Evgeny SvechnikovBROOKLYN GRINDERS (BRK)C/LW/RW6112-3195278155116.67%610517.61101112000030044.12%3464000.3800001000
7Jeremy LauzonBROOKLYN GRINDERS (BRK)D6112-50013761416.67%914023.3500001100007100%014000.2900000000
8Zach DeanBROOKLYN GRINDERS (BRK)C6112-20051363216.67%19816.4700003000040040.43%9401000.4000000000
9Nicklas JensenBROOKLYN GRINDERS (BRK)LW/RW6202-21610108235108.70%111218.78000211000060057.14%741000.3500020010
10Christian FischerBROOKLYN GRINDERS (BRK)RW60111003513170%17913.3100001100003000%222000.2500000000
11Nathan BastianBROOKLYN GRINDERS (BRK)RW6101-2409513057.69%27512.520000100000100%110000.2700000000
12Matt CorrenteBROOKLYN GRINDERS (BRK)D6011255934120%1579.660000000000000%022000.3500100000
13Aleksanteri KaskimakiBROOKLYN GRINDERS (BRK)C4011100043040%0369.2300000000000066.67%1200000.5400000000
14Dennis PerssonBROOKLYN GRINDERS (BRK)D2000000030000%063.17000000000000100.00%10000000000000
15Mattias TedenbyBROOKLYN GRINDERS (BRK)LW2000000020000%1157.950000000000000%00200000000000
16Andrew PeekeBROOKLYN GRINDERS (BRK)D2000000000000%010.750000000000000%00000000000000
17Tobias BjörnfotBROOKLYN GRINDERS (BRK)D60002004141220%1112520.9100001100009000%00200000000000
18Corson CeulemansBROOKLYN GRINDERS (BRK)D6000-1001095000%39115.290000000000000%00200000000000
19Dmitri BuchelnikovBROOKLYN GRINDERS (BRK)LW4000100664110%0379.49000000000000100.00%10100000000000
20Gage Goncalves BROOKLYN GRINDERS (BRK)C4000-120321100%14411.040000000000000%10200000000000
21Mirco MuellerBROOKLYN GRINDERS (BRK)D6000000000000%1203.470000000006000%00100000000000
22Ryan WhiteBROOKLYN GRINDERS (BRK)RW2000000000000%000.260000000000000%00000000000000
23Luca SbisaBROOKLYN GRINDERS (BRK)D2000000100000%14522.940000200001000%01000000000000
24Kirill MarchenkoBROOKLYN GRINDERS (BRK)LW/RW6000000130110%311018.3500002000000018.75%162400000000000
Statistiques d’équipe totales ou en moyenne114121931-15482013313814646768.22%70178115.6312341330000712041.85%3133538000.3500121230
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
1Matt HackettBROOKLYN GRINDERS (BRK)42200.9052.272380099552000040001
2Jakub MálekBROOKLYN GRINDERS (BRK)20200.9042.501200055232000024000
Statistiques d’équipe totales ou en moyenne62400.9052.3535800141478400064001


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 restantSalaire moyenSalaire moyen 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
Aleksanteri KaskimakiBROOKLYN GRINDERS (BRK)C196/1/2004 3:26:04 AMYes180 Lbs6 ft0NoNoN/ANoNo3Pro & Farm500,000$107,143$40,000$8,571$50,000$10,714$No500,000$500,000$-------NoNo-------
Alexander CampbellBROOKLYN GRINDERS (BRK)LW226/1/2001 8:00:21 AMYes191 Lbs6 ft2NoNoN/ANoNo3Pro & Farm600,000$128,571$40,000$8,571$60,000$12,857$No600,000$600,000$-------NoNo-------
Andrew PeekeBROOKLYN GRINDERS (BRK)D256/1/1998 9:24:05 AMNo213 Lbs6 ft1NoNoN/ANoNo2Pro & Farm650,000$139,286$40,000$8,571$65,000$13,929$No650,000$--------No--------
Brandon SutterBROOKLYN GRINDERS (BRK)C/RW352/14/1989No203 Lbs6 ft3NoNoN/ANoNo1Pro & Farm500,000$107,143$40,000$8,571$50,000$10,714$No------------------
Cameron AbneyBROOKLYN GRINDERS (BRK)RW338/7/1990 5:32:53 AMNo198 Lbs6 ft0NoNoN/ANoNo1Pro & Farm500,000$107,143$40,000$8,571$50,000$10,714$No------------------
Carter MazurBROOKLYN GRINDERS (BRK)LW206/1/2003 7:20:26 AMYes188 Lbs6 ft2NoNoN/ANoNo2Pro & Farm550,000$117,857$40,000$8,571$55,000$11,786$No550,000$--------No--------
Christian FischerBROOKLYN GRINDERS (BRK)RW274/15/1997 3:47:13 AMNo235 Lbs6 ft4NoNoN/ANoNo2Pro & Farm890,000$190,714$40,000$8,571$89,000$19,071$No890,000$--------No--------
Corson CeulemansBROOKLYN GRINDERS (BRK)D205/5/2003 8:36:21 AMYes204 Lbs6 ft4NoNoN/ANoNo2Pro & Farm800,000$171,429$40,000$8,571$80,000$17,143$No800,000$--------No--------
Cross Hanas BROOKLYN GRINDERS (BRK)LW216/1/2002 4:47:11 AMYes185 Lbs6 ft2NoNoN/ANoNo1Pro & Farm600,000$128,571$40,000$8,571$60,000$12,857$No------------------
Dana TyrellBROOKLYN GRINDERS (BRK)C/RW354/23/1989No197 Lbs5 ft11NoNoN/ANoNo1Pro & Farm500,000$107,143$40,000$8,571$50,000$10,714$No------------------
Dennis PerssonBROOKLYN GRINDERS (BRK)D356/2/1988No201 Lbs6 ft1NoNoN/ANoNo1Pro & Farm500,000$107,143$40,000$8,571$50,000$10,714$No------------------
Dmitri BuchelnikovBROOKLYN GRINDERS (BRK)LW196/1/2004 8:51:17 AMYes180 Lbs6 ft0NoNoN/ANoNo3Pro & Farm600,000$128,571$40,000$8,571$60,000$12,857$No600,000$600,000$-------NoNo-------
Evgeny SvechnikovBROOKLYN GRINDERS (BRK)C/LW/RW2710/31/1996 3:00:50 AMNo228 Lbs6 ft5NoNoN/ANoNo2Pro & Farm1,133,000$242,786$40,000$8,571$113,300$24,279$No1,133,000$--------No--------
Gage Goncalves BROOKLYN GRINDERS (BRK)C231/16/2001 5:06:14 AMYes176 Lbs6 ft1NoNoN/ANoNo1Pro & Farm550,000$117,857$40,000$8,571$55,000$11,786$No------------------
Ian ColeBROOKLYN GRINDERS (BRK)D352/21/1989No234 Lbs6 ft1NoNoN/ANoNo2Pro & Farm910,000$195,000$40,000$8,571$91,000$19,500$No910,000$--------No--------
Jakub MálekBROOKLYN GRINDERS (BRK)G206/1/2003 7:52:54 AMYes225 Lbs6 ft4NoNoN/ANoNo2Pro & Farm500,000$107,143$40,000$8,571$50,000$10,714$No500,000$--------No--------
Jeremy LauzonBROOKLYN GRINDERS (BRK)D265/29/1997 4:59:54 AMNo206 Lbs6 ft2NoNoN/ANoNo3Pro & Farm800,000$171,429$40,000$8,571$80,000$17,143$No800,000$800,000$-------NoNo-------
Joseph WollBROOKLYN GRINDERS (BRK)G257/12/1998 2:37:13 AMYes217 Lbs6 ft1NoNoN/ANoNo2Pro & Farm650,000$139,286$40,000$8,571$65,000$13,929$No650,000$--------No--------
Kirill MarchenkoBROOKLYN GRINDERS (BRK)LW/RW237/21/2000 7:25:26 AMYes193 Lbs6 ft3NoNoN/ANoNo1Pro & Farm845,000$181,071$40,000$8,571$84,500$18,107$No------------------
Luca SbisaBROOKLYN GRINDERS (BRK)D341/30/1990No224 Lbs6 ft2NoNoN/ANoNo2Pro & Farm1,030,000$220,714$40,000$8,571$103,000$22,071$No1,030,000$--------No--------
Marco KasperBROOKLYN GRINDERS (BRK)C204/8/2004 6:28:01 AMYes183 Lbs6 ft1NoNoN/ANoNo3Pro & Farm900,000$192,857$40,000$8,571$90,000$19,286$No900,000$900,000$-------NoNo-------
Matt CorrenteBROOKLYN GRINDERS (BRK)D363/17/1988No207 Lbs6 ft0NoNoN/ANoNo1Pro & Farm600,000$128,571$40,000$8,571$60,000$12,857$No------------------
Matt HackettBROOKLYN GRINDERS (BRK)G343/7/1990No190 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,100,000$235,714$40,000$8,571$110,000$23,571$No------------------
Mattias TedenbyBROOKLYN GRINDERS (BRK)LW342/21/1990No195 Lbs5 ft10NoNoN/ANoNo3Pro & Farm1,450,000$310,714$40,000$8,571$145,000$31,071$No1,450,000$1,450,000$-------NoNo-------
Mirco MuellerBROOKLYN GRINDERS (BRK)D293/21/1995 1:36:32 AMNo231 Lbs6 ft6NoNoN/ANoNo1Pro & Farm1,000,000$214,286$40,000$8,571$100,000$21,429$No------------------Lien NHL
Nathan BastianBROOKLYN GRINDERS (BRK)RW2612/6/1997 9:49:39 AMNo214 Lbs6 ft1NoNoN/ANoNo2Pro & Farm650,000$139,286$40,000$8,571$65,000$13,929$No650,000$--------No--------
Nick PalmieriBROOKLYN GRINDERS (BRK)RW347/12/1989No235 Lbs6 ft3NoNoN/ANoNo1Pro & Farm500,000$107,143$40,000$8,571$50,000$10,714$No------------------
Nicklas JensenBROOKLYN GRINDERS (BRK)LW/RW313/6/1993 6:47:41 AMNo230 Lbs6 ft3NoNoN/ANoNo1Pro & Farm1,937,500$415,179$1,550,000$332,143$193,750$41,518$No------------------
Ryan WhiteBROOKLYN GRINDERS (BRK)RW363/17/1988No210 Lbs6 ft0NoNoN/ANoNo2Pro & Farm829,000$177,643$40,000$8,571$82,900$17,764$No829,000$--------No--------
Scott TimminsBROOKLYN GRINDERS (BRK)C349/11/1989No209 Lbs5 ft11NoNoN/ANoNo1Pro & Farm500,000$107,143$40,000$8,571$50,000$10,714$No------------------
Tobias BjörnfotBROOKLYN GRINDERS (BRK)D234/6/2001 4:56:28 AMYes198 Lbs6 ft1NoNoN/ANoNo3Pro & Farm650,000$139,286$40,000$8,571$65,000$13,929$No650,000$650,000$-------NoNo-------
Zach DeanBROOKLYN GRINDERS (BRK)C211/4/2003 8:47:03 AMYes180 Lbs6 ft0NoNoN/ANoNo2Pro & Farm700,000$150,000$40,000$8,571$70,000$15,000$No700,000$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3227.56205 Lbs6 ft21.81763,266$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Brandon SutterAleksanteri KaskimakiKirill Marchenko35014
2Nicklas JensenZach DeanMarco Kasper30014
3Nathan BastianEvgeny SvechnikovGage Goncalves 20122
4Dmitri BuchelnikovAleksanteri KaskimakiChristian Fischer15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ian ColeCorson Ceulemans40122
2Matt CorrenteTobias Björnfot30122
3Corson CeulemansJeremy Lauzon20122
4Corson CeulemansJeremy Lauzon10032
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Evgeny SvechnikovBrandon SutterAleksanteri Kaskimaki50023
2Christian FischerMarco KasperNicklas Jensen50023
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Andrew PeekeIan Cole60122
2Tobias BjörnfotJeremy Lauzon40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Gage Goncalves Nicklas Jensen60032
2Zach DeanChristian Fischer40032
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tobias BjörnfotIan Cole60032
2Jeremy LauzonMirco Mueller40032
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Gage Goncalves 60050Mirco MuellerIan Cole60050
2Evgeny Svechnikov40050Jeremy LauzonMatt Corrente40050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Christian FischerNicklas Jensen60122
2Gage Goncalves Evgeny Svechnikov40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jeremy LauzonCorson Ceulemans60122
2Andrew PeekeIan Cole40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Evgeny SvechnikovAleksanteri KaskimakiBrandon SutterJeremy LauzonIan Cole
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nicklas JensenAleksanteri KaskimakiBrandon SutterJeremy LauzonIan Cole
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nathan Bastian, Kirill Marchenko, Zach DeanNathan Bastian, Marco KasperNicklas Jensen
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Corson Ceulemans, Mirco Mueller, Tobias BjörnfotMatt CorrenteMatt Corrente, Tobias Björnfot
Tirs de pénalité
Evgeny Svechnikov, Kirill Marchenko, Mirco Mueller, Nicklas Jensen, Dmitri Buchelnikov
Gardien
#1 : Matt Hackett, #2 : Jakub Málek
Lignes d’attaque personnalisées en prolongation
Evgeny Svechnikov, Brandon Sutter, Gage Goncalves , Nicklas Jensen, Christian Fischer, Zach Dean, Zach Dean, Kirill Marchenko, Dmitri Buchelnikov, Aleksanteri Kaskimaki,
Lignes de défense personnalisées en prolongation
Ian Cole, Matt Corrente, Jeremy Lauzon, Tobias Björnfot, Corson Ceulemans


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
1HALIFAX HELL624000001214-2321000009543030000039-640.333121931004440146495245014770481331516.67%90100.00%04712936.43%5410750.47%307738.96%114561305611458
Total624000001214-2321000009543030000039-640.333121931004440146495245014770481331516.67%90100.00%04712936.43%5410750.47%307738.96%114561305611458
_Since Last GM Reset624000001214-2321000009543030000039-640.333121931004440146495245014770481331516.67%90100.00%04712936.43%5410750.47%307738.96%114561305611458
_Vs Conference624000001214-2321000009543030000039-640.333121931004440146495245014770481331516.67%90100.00%04712936.43%5410750.47%307738.96%114561305611458
_Vs Division624000001214-2321000009543030000039-640.333121931004440146495245014770481331516.67%90100.00%04712936.43%5410750.47%307738.96%114561305611458

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
64L2121931146147704813300
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
62400001214
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
321000095
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
303000039
Derniers 10 matchs
WLOTWOTL SOWSOL
240000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1516.67%90100.00%0
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
49524504440
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
4712936.43%5410750.47%307738.96%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
114561305611458


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
27BROOKLYN GRINDERS0HALIFAX HELL2ALSommaire du match
415BROOKLYN GRINDERS0HALIFAX HELL3ALSommaire du match
623HALIFAX HELL1BROOKLYN GRINDERS4BWSommaire du match
831HALIFAX HELL2BROOKLYN GRINDERS4BWSommaire du match
1039BROOKLYN GRINDERS3HALIFAX HELL4ALSommaire du match
1247HALIFAX HELL2BROOKLYN GRINDERS1BLSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance6,0003,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
39 3000 - 100.00% 85,000$255,000$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,442,450$ 279,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 32 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 6 0$ 0$




BROOKLYN GRINDERS 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

BROOKLYN GRINDERS 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

BROOKLYN GRINDERS 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

BROOKLYN GRINDERS 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

BROOKLYN GRINDERS 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