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Gulls
GP: 60 | W: 32 | L: 19 | OTL: 9 | P: 73
GF: 140 | GA: 143 | PP%: 28.35% | PK%: 72.97%
DG: Roger Storoschuk | Morale : 53 | Moyenne d’équipe : 60
Prochains matchs #931 vs Silver Knights

Centre de jeu
Islanders
32-19-9, 73pts
3
0 Gulls
32-19-9, 73pts
Team Stats
SOL1SéquenceW1
15-9-6Fiche domicile19-8-3
17-10-3Fiche domicile13-11-6
5-3-2Derniers 10 matchs3-3-4
3.42Buts par match 2.33
3.07Buts contre par match 2.38
18.99%Pourcentage en avantage numérique28.35%
76.61%Pourcentage en désavantage numérique72.97%
Eagles
17-26-15, 49pts
2
4 Gulls
32-19-9, 73pts
Team Stats
L3SéquenceW1
9-15-6Fiche domicile19-8-3
8-11-9Fiche domicile13-11-6
2-6-2Derniers 10 matchs3-3-4
2.21Buts par match 2.33
3.09Buts contre par match 2.38
35.61%Pourcentage en avantage numérique28.35%
68.94%Pourcentage en désavantage numérique72.97%
Gulls
32-19-9, 73pts
Jour 74
Silver Knights
24-22-12, 60pts
Statistiques d’équipe
W1SéquenceL2
19-8-3Fiche domicile17-9-4
13-11-6Fiche visiteur7-13-8
3-3-410 derniers matchs1-6-3
2.33Buts par match 2.43
2.38Buts contre par match 2.43
28.35%Pourcentage en avantage numérique30.83%
72.97%Pourcentage en désavantage numérique71.79%
Bruins
34-19-8, 76pts
Jour 76
Gulls
32-19-9, 73pts
Statistiques d’équipe
W1SéquenceW1
15-8-6Fiche domicile19-8-3
19-11-2Fiche visiteur13-11-6
5-3-210 derniers matchs3-3-4
2.25Buts par match 2.33
2.13Buts contre par match 2.33
30.00%Pourcentage en avantage numérique28.35%
64.10%Pourcentage en désavantage numérique72.97%
Gulls
32-19-9, 73pts
Jour 77
Checkers
25-25-9, 59pts
Statistiques d’équipe
W1SéquenceL2
19-8-3Fiche domicile15-10-5
13-11-6Fiche visiteur10-15-4
3-3-410 derniers matchs6-4-0
2.33Buts par match 2.34
2.38Buts contre par match 2.34
28.35%Pourcentage en avantage numérique30.77%
72.97%Pourcentage en désavantage numérique69.17%
Meneurs d'équipe
Buts
Cole Smith
26
Passes
Cole Smith
38
Points
Cole Smith
64
Ryan LombergPlus/Moins
Ryan Lomberg
14
Victoires
Spencer Knight
11
Pourcentage d’arrêts
Will Cranley
0.918

Statistiques d’équipe
Buts pour
140
2.33 GFG
Tirs pour
977
16.28 Avg
Pourcentage en avantage numérique
28.3%
36 GF
Début de zone offensive
33.5%
Buts contre
143
2.38 GAA
Tirs contre
1162
19.37 Avg
Pourcentage en désavantage numérique
73.0%%
40 GA
Début de la zone défensive
39.9%
Informations de l'équipe

Directeur généralRoger Storoschuk
EntraîneurRick Tocchet
DivisionDivision 1
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,837
Billets de saison1,500


Informations de la formation

Équipe Pro26
Équipe Mineure18
Limite contact 44 / 100
Espoirs70


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
1Cole SmithXX98.0089957279776588644963608225666764846803032,500,000$
2Mikael Pyyhtia (R)X100.006541968667629062555861752554546376650241897,500$
3Ryan LombergXX100.0080948182665297623462596625697163806503131,500,000$
4Sam LaffertyXXX100.0080458783765577625757596725697162706403122,200,000$
5Dakota JoshuaXXX100.009970826978637464546163672566676551640291900,000$
6Bradly Nadeau (R)X100.0070638473657982665061686166464666776302031,422,000$
7Jared DavidsonX100.007167797069798461785464606246466273620233842,000$
8Cole Schwindt (R)X100.007444997976546159686456642550506069610241934,000$
9Rhett Pitlick (R)XXX100.0073629981633732587368446042464655725702531,352,000$
10Julian Lutz (R)X100.0077729365744848485047436143464652685302231,258,000$
11Francesco Arcuri (R)X100.0076748682764546425537435942464649635202231,268,000$
12Jan RuttaX100.0069438585767271632552528425717461787003522,900,000$
13Matt GrzelcykX100.0064419472658199742569477125747863646903221,800,000$
14Connor MackeyX100.0074815867817784512545426140494951706102911,319,000$
15Elias Salomonsson (R)X100.0074708768726568522549426040464653725902131,284,000$
16Dysin MayoX100.0069706265706873522541495846464652625702921,934,000$
17Marek Alscher (R)X100.0076748165766469452536396038464649755702231,286,000$
18Kyle Masters (R)X100.0075669561663837462536415939454449185202331,037,000$
Rayé
1Ryder RolstonX100.008075946877555459505559645646466057590241825,000$
2Brandon CoeX92.177674856576525348504745604546465258530241925,000$
3Riley Hughes (R)XXX100.0077728762724342496147466244444453205202531,319,000$
MOYENNE D’ÉQUIPE99.53766685737260685746535265385354576560
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
1Spencer Knight100.006968667873647167696761575867796702422,472,000$
2Will Cranley (R)100.004440507845904650918145444460666002431,075,000$
Rayé
1Brett Brochu (R)100.004440506345894549908145444460245802331,000,000$
2Devin Cooley100.005240508257565157585730444454205502821,750,000$
3Vadim Zherenko100.00495063844950505550503044445120530251846,667$
MOYENNE D’ÉQUIPE100.0052485677547053567267424747584259
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Rick Tocchet83788383848476CAN5445,000,000$


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Cole SmithGulls (ANA)LW/RW5826386411278510587155499016.77%26122921.2010122232950110355349.33%2233317121.04161025853
2Ryan LombergGulls (ANA)LW/RW6025184314383082100131366519.08%22124920.82426147620271075237.70%2522829010.6922204623
3Mikael PyyhtiaGulls (ANA)LW60112233840597774215014.86%16112218.7044815780001233144.00%4251814000.5900000324
4Jan RuttaGulls (ANA)D6082129329553958836369.09%57148324.725510191120003102300%03836000.3900001153
5Sam LaffertyGulls (ANA)C/LW/RW60101626-112315648770255114.29%13106617.781011190112604249.39%6582017000.4900021402
6Bradly NadeauGulls (ANA)LW6010142443010917966274815.15%18118719.800553240114792255.38%652013000.4011200331
7Anthony BeauvillierDucksLW33121022-1320354990234313.33%1272521.9834716660000532142.19%128288010.6101000122
8Rhett PitlickGulls (ANA)C/LW/RW6061521-755626746154513.04%990815.14178854000001043.08%652213100.4606001141
9Ryder RolstonGulls (ANA)RW4861420-27555444292414.29%1180216.722101211841014331040.23%174118000.5024001011
10Dysin MayoGulls (ANA)D6021719-2953597896521263.08%66156726.120445107000198000%0845000.2400043121
11Jared DavidsonGulls (ANA)C6081018-3435775740131520.00%896516.093699310000131057.33%75128000.3702001005
12Cole SchwindtGulls (ANA)RW5941115100192927112014.81%63355.690110241011252052.48%28278000.8900000311
13Connor MackeyGulls (ANA)D5816748820684714477.14%15100717.3600004011011000%0420000.1400211010
14Dakota JoshuaGulls (ANA)C/LW/RW235272221026151281341.67%230713.3710113000020163.33%3065000.4600020101
15Matt GrzelcykGulls (ANA)D592242201337167912.50%1271912.20202230000129010%029000.1100000001
16Jordan GreenwayDucksLW/RW2022255159040%04321.8301121011240066.67%600000.9200010000
17Elias SalomonssonGulls (ANA)D60112-230104774211174.76%29129121.52000371000170000%0923000.0300101000
18Marek AlscherGulls (ANA)D600222302054707420%39109618.270001490000125000%0329000.0400103000
19Kyle MastersGulls (ANA)D16000000010000%0271.740000000000000%00000000000000
20Josh MansonDucksD2000040231000%24422.340000000002000%01300000000000
21Brandon CoeGulls (ANA)RW6000012032150110%03505.840000400000000%22300000000000
22Julian LutzGulls (ANA)LW6000020019103110%02123.5400000000000050.00%20100000000000
23Francesco ArcuriGulls (ANA)C560002001330000%01302.3300000000000051.85%271100000000000
Statistiques d’équipe totales ou en moyenne113413722135885862601074114097732255714.02%3631787415.7636619714294045927880291346.98%2414273310240.40622181222322829
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
1Jake AllenDucks37211240.8882.2321760581726367110.80010370132
2Spencer KnightGulls (ANA)2511640.8582.4013270453374199100.50082337210
3Will CranleyGulls (ANA)40110.9182.381260056127000.6673023000
Statistiques d’équipe totales ou en moyenne66321990.8802.30363009139116159321216060342


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
Bradly NadeauGulls (ANA)LW202005-05-05CANYes172 Lbs5 ft11NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,422,000$495,161$0$0$No1,422,000$1,422,000$-------1,422,000$1,422,000$-------NoNo-------Lien
Brandon CoeGulls (ANA)RW242001-12-01CANNo190 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm925,000$322,098$0$0$No---------------------------Lien
Brett BrochuGulls (ANA)G232002-09-09CANYes176 Lbs6 ft0NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,000,000$348,214$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien
Cole SchwindtGulls (ANA)RW242001-04-25CANYes203 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm934,000$325,232$0$0$No---------------------------Lien
Cole SmithGulls (ANA)LW/RW301995-10-28USANo195 Lbs6 ft3NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm2,500,000$870,536$0$0$No2,500,000$2,500,000$-------2,500,000$2,500,000$-------NoNo-------Lien
Connor MackeyGulls (ANA)D291996-09-12USANo205 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm1,319,000$459,295$0$0$No---------------------------Lien
Dakota JoshuaGulls (ANA)C/LW/RW291996-05-15USANo206 Lbs6 ft3NoNoN/ANoYes1FalseFalsePro & Farm900,000$313,393$0$0$No---------------------------Lien
Devin CooleyGulls (ANA)G281997-05-25USANo188 Lbs6 ft5NoNoAssign ManuallyNoNo22024-09-10FalseFalsePro & Farm1,750,000$609,375$0$0$No1,750,000$--------1,750,000$--------No--------Lien
Dysin MayoGulls (ANA)D291996-08-17CANNo190 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm1,934,000$673,446$0$0$No1,934,000$--------1,934,000$--------No--------Lien / Lien NHL
Elias SalomonssonGulls (ANA)D212004-08-31SWEYes189 Lbs6 ft2NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,284,000$447,107$0$0$No1,284,000$1,284,000$-------1,284,000$1,284,000$-------NoNo-------Lien
Francesco ArcuriGulls (ANA)C222003-06-13CANYes200 Lbs6 ft1NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,268,000$441,536$0$0$No1,268,000$1,268,000$-------1,268,000$1,268,000$-------NoNo-------Lien
Jan RuttaGulls (ANA)D351990-07-29CZENo204 Lbs6 ft3NoNoAssign ManuallyNoNo22024-09-16FalseFalsePro & Farm2,900,000$1,009,821$0$0$No2,900,000$--------2,900,000$--------No--------Lien / Lien NHL
Jared DavidsonGulls (ANA)C232002-07-07CANNo183 Lbs6 ft0NoNoN/ANoNo32025-05-01FalseFalsePro & Farm842,000$293,196$0$0$No842,000$842,000$-------842,000$842,000$-------NoNo-------Lien
Julian LutzGulls (ANA)LW222004-02-29GERYes192 Lbs6 ft2NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,258,000$438,054$0$0$No1,258,000$1,258,000$-------1,258,000$1,258,000$-------NoNo-------Lien
Kyle MastersGulls (ANA)D232003-04-09ABYes175 Lbs6 ft1NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,037,000$361,098$0$0$No1,037,000$1,037,000$-------1,037,000$1,037,000$-------NoNo-------Lien
Marek AlscherGulls (ANA)D222004-04-07CZEYes196 Lbs6 ft3NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,286,000$447,804$0$0$No1,286,000$1,286,000$-------1,286,000$1,286,000$-------NoNo-------Lien
Matt GrzelcykGulls (ANA)D321994-01-05USANo180 Lbs5 ft10NoNoAssign ManuallyNoNo22024-09-10FalseFalsePro & Farm1,800,000$626,786$0$0$No1,800,000$--------1,800,000$--------No--------Lien / Lien NHL
Mikael PyyhtiaGulls (ANA)LW242001-12-17FINYes176 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm897,500$312,522$0$0$No---------------------------Lien
Rhett PitlickGulls (ANA)C/LW/RW252001-02-07USAYes170 Lbs5 ft10NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,352,000$470,786$0$0$No1,352,000$1,352,000$-------1,352,000$1,352,000$-------NoNo-------Lien
Riley HughesGulls (ANA)C/LW/RW252000-06-27USAYes194 Lbs6 ft2NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,319,000$459,295$0$0$No1,319,000$1,319,000$-------1,319,000$1,319,000$-------NoNo-------Lien
Ryan LombergGulls (ANA)LW/RW311994-12-09CANNo184 Lbs5 ft9NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm1,500,000$522,321$0$0$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------Lien / Lien NHL
Ryder RolstonGulls (ANA)RW242001-10-31USANo200 Lbs6 ft2NoNoN/ANoNo12025-05-01FalseFalsePro & Farm825,000$287,277$0$0$No---------------------------Lien
Sam LaffertyGulls (ANA)C/LW/RW311995-03-06USANo205 Lbs6 ft2NoNoAssign ManuallyNoNo22024-09-10FalseFalsePro & Farm2,200,000$766,071$0$0$No2,200,000$--------2,200,000$--------No--------Lien / Lien NHL
Spencer KnightGulls (ANA)G242001-04-19USANo191 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm2,472,000$860,786$0$0$No2,472,000$--------925,000$--------No--------Lien
Vadim ZherenkoGulls (ANA)G252001-03-15RUSNo207 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm846,667$294,822$0$0$No---------------------------Lien
Will CranleyGulls (ANA)G242002-02-26CANYes185 Lbs6 ft4NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,075,000$374,330$0$0$No1,075,000$1,075,000$-------1,075,000$1,075,000$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2625.73191 Lbs6 ft22.231,417,160$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jared DavidsonSam LaffertyCole Smith40122
2Ryan LombergMikael PyyhtiaBradly Nadeau30122
3Cole SmithRyan LombergJared Davidson20122
4Ryan LombergCole SmithRhett Pitlick10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaDysin Mayo35122
2Connor MackeyElias Salomonsson30122
3Marek AlscherDysin Mayo25122
4Dysin MayoJan Rutta10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jared DavidsonBradly NadeauCole Smith60122
2Mikael PyyhtiaRhett PitlickRyan Lomberg40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaDysin Mayo60122
2Marek AlscherElias Salomonsson40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Cole SmithRyan Lomberg60122
2Mikael PyyhtiaBradly Nadeau40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Marek AlscherDysin Mayo60122
2Jan RuttaElias Salomonsson40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Ryan Lomberg60122Jan RuttaDysin Mayo60122
2Cole Smith40122Marek AlscherElias Salomonsson40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Ryan LombergCole Smith60122
2Mikael PyyhtiaJared Davidson40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dysin MayoMarek Alscher60122
2Elias SalomonssonJan Rutta40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mikael PyyhtiaRyan LombergCole SmithJan RuttaConnor Mackey
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mikael PyyhtiaRyan LombergCole SmithJan RuttaConnor Mackey
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Ryan Lomberg, Cole Smith, Rhett PitlickRyan Lomberg, Cole SmithRyan Lomberg
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Marek Alscher, Jan Rutta, Dysin MayoDysin MayoJan Rutta, Dysin Mayo
Tirs de pénalité
Jared Davidson, Cole Smith, Rhett Pitlick, Ryan Lomberg, Mikael Pyyhtia
Gardien
#1 : Spencer Knight, #2 : Will Cranley


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
1Admirals11000000312000000000001100000031221.000369002636729152382884423161215100.00%10100.00%039380049.13%42095344.07%32163450.63%102837010976581508759
2Americans2010010025-31010000002-21000010023-110.250246002636729312382884423148132440300.00%7271.43%039380049.13%42095344.07%32163450.63%102837010976581508759
3Barracuda3110100036-3100010002112110000015-440.66735801263672939238288442314183443300.00%12375.00%039380049.13%42095344.07%32163450.63%102837010976581508759
4Bears1010000002-2000000000001010000002-200.00000000263672992382884423192714000%10100.00%039380049.13%42095344.07%32163450.63%102837010976581508759
5Bruins3020001069-32010001045-11010000024-220.333691510263672943238288442315018266122100.00%8362.50%039380049.13%42095344.07%32163450.63%102837010976581508759
6Canucks11000000312000000000001100000031221.00033600263672921238288442311481115000%3166.67%139380049.13%42095344.07%32163450.63%102837010976581508759
7Comets211000005321010000002-21100000051420.5005813002636729222382884423130921265240.00%8187.50%239380049.13%42095344.07%32163450.63%102837010976581508759
8Condors4310000089-1220000004132110000048-460.7508142201263672976238288442318833667012325.00%8275.00%039380049.13%42095344.07%32163450.63%102837010976581508759
9Crunch32100000972321000009720000000000040.667914230026367294523828844231381237526466.67%6266.67%039380049.13%42095344.07%32163450.63%102837010976581508759
10Eagles11000000422110000004220000000000021.00044800263672910238288442316522711100.00%10100.00%039380049.13%42095344.07%32163450.63%102837010976581508759
11Griffins2000020057-21000010023-11000010034-120.50058130026367292023828844231531133375120.00%40100.00%039380049.13%42095344.07%32163450.63%102837010976581508759
12IceHogs1010000002-2000000000001010000002-200.00000000263672992382884423191018100.00%000%039380049.13%42095344.07%32163450.63%102837010976581508759
13Islanders2110000057-22110000057-20000000000020.50059140026367293923828844231641010447114.29%5180.00%039380049.13%42095344.07%32163450.63%102837010976581508759
14Marlies21000100330110000003211000010001-130.750358002636729222382884423117714356233.33%20100.00%039380049.13%42095344.07%32163450.63%102837010976581508759
15Monsters11000000202000000000001100000020221.0002240126367299238288442311729122150.00%20100.00%039380049.13%42095344.07%32163450.63%102837010976581508759
16Moose2010100057-21010000014-31000100043120.5005914002636729232382884423132811504250.00%3166.67%039380049.13%42095344.07%32163450.63%102837010976581508759
17Penguins2010010058-31000010012-11010000046-210.25059140026367292823828844231312321385360.00%8450.00%039380049.13%42095344.07%32163450.63%102837010976581508759
18Phantoms11000000422110000004220000000000021.00046100026367293423828844231207417200.00%2150.00%039380049.13%42095344.07%32163450.63%102837010976581508759
19Reign2020000037-41010000035-21010000002-200.0003470026367293423828844231722220338112.50%10460.00%039380049.13%42095344.07%32163450.63%102837010976581508759
20Roadrunners22000000624110000003121100000031241.00068140026367293823828844231461014315240.00%20100.00%039380049.13%42095344.07%32163450.63%102837010976581508759
21Rocket1000000123-1000000000001000000123-110.50024600263672915238288442311044162150.00%2150.00%039380049.13%42095344.07%32163450.63%102837010976581508759
22Senators21000010523110000002021000001032141.000571201263672930238288442311933038300.00%5180.00%039380049.13%42095344.07%32163450.63%102837010976581508759
23Silver Knights42101000761210010005142110000025-360.750712190226367298323828844231692734688112.50%7271.43%039380049.13%42095344.07%32163450.63%102837010976581508759
24Stars2010001078-1100000105411010000024-220.5007815002636729452382884423149131342400.00%4175.00%139380049.13%42095344.07%32163450.63%102837010976581508759
25Thunderbirds200000021012-21000000145-11000000167-120.5001015250026367295523828844231802628317342.86%4250.00%039380049.13%42095344.07%32163450.63%102837010976581508759
26Wild30300000615-91010000023-120200000412-800.000610160026367296123828844231126305846300.00%14471.43%039380049.13%42095344.07%32163450.63%102837010976581508759
27Wolf Pack54000100133103300000010192100010032190.90013233603263672963238288442316132289413323.08%9188.89%039380049.13%42095344.07%32163450.63%102837010976581508759
28Wolves33000000945110000004222200000052361.000915240026367295823828844231571825619333.33%10370.00%039380049.13%42095344.07%32163450.63%102837010976581508759
Total60261903633140143-33015802221776215301111014126381-18730.60814022136119263672997723828844231116236358610741273628.35%1484072.97%439380049.13%42095344.07%32163450.63%102837010976581508759
_Since Last GM Reset60261903633140143-33015802221776215301111014126381-18730.60814022136119263672997723828844231116236358610741273628.35%1484072.97%439380049.13%42095344.07%32163450.63%102837010976581508759
_Vs Conference361911021217870817104020104223191997001113647-11480.6677812620419263672957423828844231629205383620692028.99%942474.47%339380049.13%42095344.07%32163450.63%102837010976581508759
_Vs Division14128011102429-5683010101486845001001021-11291.036243862042636729253238288442312849816522931516.13%401270.00%139380049.13%42095344.07%32163450.63%102837010976581508759

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6073W11402213619771162363586107419
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6026193633140143
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3015822217762
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
30111114126381
Derniers 10 matchs
WLOTWOTL SOWSOL
330202
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1273628.35%1484072.97%4
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
238288442312636729
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
39380049.13%42095344.07%32163450.63%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
102837010976581508759


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
212Crunch1Gulls4WSommaire du match
332Gulls3Canucks1WSommaire du match
440Gulls0Condors6LSommaire du match
558Bruins4Gulls2LSommaire du match
780Islanders4Gulls5WSommaire du match
888Gulls1Silver Knights5LSommaire du match
10105Gulls3Wolves1WSommaire du match
11116Wolf Pack0Gulls5WSommaire du match
12132Silver Knights1Gulls4WSommaire du match
13153Gulls2Wolf Pack0WSommaire du match
15169Wild3Gulls2LSommaire du match
16190Condors0Gulls1WSommaire du match
17200Gulls1Wild7LSommaire du match
18211Gulls1Silver Knights0WSommaire du match
19230Bruins1Gulls2WXXSommaire du match
20250Moose4Gulls1LSommaire du match
21252Gulls0Barracuda5LSommaire du match
22266Gulls4Condors2WSommaire du match
24286Gulls1Barracuda0WSommaire du match
26300Crunch1Gulls3WSommaire du match
27319Reign5Gulls3LSommaire du match
28331Gulls0Reign2LSommaire du match
29348Comets2Gulls0LSommaire du match
30362Gulls4Moose3WXSommaire du match
31376Gulls2Americans3LXSommaire du match
32394Penguins2Gulls1LXSommaire du match
34406Gulls1Wolf Pack2LXSommaire du match
35420Gulls3Admirals1WSommaire du match
36435Stars4Gulls5WXXSommaire du match
37456Americans2Gulls0LSommaire du match
39474Roadrunners1Gulls3WSommaire du match
40487Gulls2Stars4LSommaire du match
41501Gulls3Griffins4LXSommaire du match
42512Gulls2Wolves1WSommaire du match
43527Phantoms2Gulls4WSommaire du match
44545Barracuda1Gulls2WXSommaire du match
45565Condors1Gulls3WSommaire du match
46579Gulls4Penguins6LSommaire du match
47590Gulls5Comets1WSommaire du match
48604Gulls6Thunderbirds7LXXSommaire du match
49620Silver Knights0Gulls1WXSommaire du match
50641Wolves2Gulls4WSommaire du match
51649Gulls3Roadrunners1WSommaire du match
52661Gulls0IceHogs2LSommaire du match
53681Crunch5Gulls2LSommaire du match
54701Senators0Gulls2WSommaire du match
56716Gulls3Senators2WXXSommaire du match
57729Wolf Pack0Gulls2WSommaire du match
58747Gulls3Wild5LSommaire du match
59760Wolf Pack1Gulls3WSommaire du match
61780Gulls2Monsters0WSommaire du match
62785Gulls0Marlies1LXSommaire du match
63799Gulls2Bruins4LSommaire du match
64806Marlies2Gulls3WSommaire du match
66833Griffins3Gulls2LXSommaire du match
68859Gulls0Bears2LSommaire du match
69866Gulls2Rocket3LXXSommaire du match
70878Thunderbirds5Gulls4LXXSommaire du match
71895Islanders3Gulls0LSommaire du match
73919Eagles2Gulls4WSommaire du match
74931Gulls-Silver Knights-
76948Bruins-Gulls-
77965Gulls-Checkers-
78972Gulls-Phantoms-
80986Admirals-Gulls-
821015Heat-Gulls-
831033Gulls-Islanders-
841043IceHogs-Gulls-
861065Monsters-Gulls-
871080Gulls-Canucks-
881086Gulls-Crunch-
891102Marlies-Gulls-
901115Gulls-Eagles-
911129Gulls-Wild-
921144Wild-Gulls-
941165Gulls-Heat-
951172Wolves-Gulls-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
971198Canucks-Gulls-
981207Gulls-Canucks-
1001228Canucks-Gulls-
1011240Gulls-Bruins-
1031262Bears-Gulls-
1051279Checkers-Gulls-
1061286Gulls-Crunch-
1071296Gulls-Condors-
1101322Rocket-Gulls-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4020
Assistance37,97117,134
Assistance PCT63.29%57.11%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
13 1837 - 61.23% 92,455$2,773,662$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
5,696,988$ 3,684,617$ 3,684,617$ 5,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
32,898$ 2,438,049$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,201,920$ 39 77,541$ 3,024,099$




Gulls 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

Gulls 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

Gulls 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

Gulls 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

Gulls 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