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Gulls
GP: 85 | W: 45 | L: 28 | OTL: 12 | P: 102
GF: 187 | GA: 201 | PP%: 26.26% | PK%: 71.71%
DG: Roger Storoschuk | Morale : 57 | Moyenne d’équipe : 60
Prochains matchs #1322 vs Rocket

Centre de jeu
Gulls
45-28-12, 102pts
2
4 Crunch
27-40-16, 70pts
Team Stats
W1SéquenceW2
26-13-3Fiche domicile15-14-13
19-15-9Fiche domicile12-26-3
5-4-1Derniers 10 matchs4-4-2
2.20Buts par match 2.10
2.36Buts contre par match 2.83
26.26%Pourcentage en avantage numérique26.56%
71.71%Pourcentage en désavantage numérique69.65%
Gulls
45-28-12, 102pts
4
3 Condors
47-24-13, 107pts
Team Stats
W1SéquenceSOL1
26-13-3Fiche domicile25-12-5
19-15-9Fiche domicile22-12-8
5-4-1Derniers 10 matchs5-3-2
2.20Buts par match 2.65
2.36Buts contre par match 2.15
26.26%Pourcentage en avantage numérique24.71%
71.71%Pourcentage en désavantage numérique75.11%
Rocket
45-19-20, 110pts
Jour 110
Gulls
45-28-12, 102pts
Statistiques d’équipe
SOL1SéquenceW1
25-7-10Fiche domicile26-13-3
20-12-10Fiche visiteur19-15-9
2-4-410 derniers matchs5-4-1
2.30Buts par match 2.20
2.10Buts contre par match 2.20
32.54%Pourcentage en avantage numérique26.26%
73.33%Pourcentage en désavantage numérique71.71%
Meneurs d'équipe
Buts
Cole Smith
34
Passes
Cole Smith
47
Points
Cole Smith
81
Ryan LombergPlus/Moins
Ryan Lomberg
11
Victoires
Spencer Knight
24
Pourcentage d’arrêts
Will Cranley
0.896

Statistiques d’équipe
Buts pour
187
2.20 GFG
Tirs pour
1305
15.35 Avg
Pourcentage en avantage numérique
26.3%
47 GF
Début de zone offensive
33.9%
Buts contre
201
2.36 GAA
Tirs contre
1621
19.07 Avg
Pourcentage en désavantage numérique
71.7%%
58 GA
Début de la zone défensive
40.0%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance1,831
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 SmithXX100.0089957279776588654963618125676864816803032,500,000$
2Mikael Pyyhtia (R)X98.006541968768629062555761742555556281650241897,500$
3Ryan LombergXX98.0080948082665297633363596625707262816503131,500,000$
4Sam LaffertyXXX99.0080458783765577625757596625707261776403122,200,000$
5Dakota JoshuaXXX100.009870826978637463546062672567686463640301900,000$
6Bradly Nadeau (R)X99.0070638473657982655060686066474765816302131,422,000$
7Jared DavidsonX99.007167797170798461785464596247476181620233842,000$
8Cole Schwindt (R)X100.007444998077546159686356632550506080610251934,000$
9Ryder RolstonX100.008075946877555459505558645646466046590241825,000$
10Rhett Pitlick (R)XXX100.0072629981633732577368445942474754805702531,352,000$
11Brandon CoeX100.007674866576525347504745594547465148530241925,000$
12Julian Lutz (R)X100.0076729466754848475046436043474751795302231,258,000$
13Riley Hughes (R)XXX100.0077728762724342496147466244444453245202531,319,000$
14Jan RuttaX99.0069438585767271642552538425727560827103522,900,000$
15Matt GrzelcykX100.0063419572658199732567477025757962756903221,800,000$
16Connor MackeyX100.0074815867817784512545435940505051796102911,319,000$
17Elias Salomonsson (R)X100.0074708769736568522548425940474752805902131,284,000$
18Dysin MayoX99.0069706265706873532541495846474751735802921,934,000$
19Marek Alscher (R)X100.0075748166776469452535395938474748815702231,286,000$
Rayé
1Francesco Arcuri (R)X100.0075748682764546425536425942464648615202231,268,000$
2Kyle Masters (R)X100.0074669562673837462535415939454549205202331,037,000$
MOYENNE D’ÉQUIPE99.57756685737360685646525264385455576960
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 Knight100.006968667873667368716761585966886802522,472,000$
2Will Cranley (R)100.004440507845904650918145444459806102431,075,000$
Rayé
1Brett Brochu (R)100.004440506345894549908145444460205802331,000,000$
2Devin Cooley100.005240508257565157585730444454205502921,750,000$
3Vadim Zherenko100.00495063844950505550503044445120530251846,667$
MOYENNE D’ÉQUIPE100.0052485677547053567267424747584659
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/RW83344781-81681001531232086012516.35%37176821.31111627461380111606449.51%3094728120.9221411361093
2Ryan LombergGulls (ANA)LW/RW85302858117850119145176518217.05%34177320.86551019109303111478239.03%3923738010.6547235825
3Jan RuttaGulls (ANA)D8511304143157914011750539.40%84210724.797613241610005142310%05044000.3900001265
4Mikael PyyhtiaGulls (ANA)LW85132538-16086109105286312.38%26164419.355611191130112434145.50%5672422000.4613000334
5Bradly NadeauGulls (ANA)LW851519340391512812499326215.15%25172220.273811196711271102243.42%1522720000.3925201541
6Sam LaffertyGulls (ANA)C/LW/RW85112233-17302087134100316611.00%21157218.491011270112824249.08%9273627000.4200031403
7Jared DavidsonGulls (ANA)C85121830-772301218758173520.69%16152918.00381111740001331160.71%1401517000.39212123125
8Rhett PitlickGulls (ANA)C/LW/RW85101828-61210789164186215.63%16132115.5528101089000011145.16%933118100.42416011243
9Dysin MayoGulls (ANA)D85323262128401241288831353.41%95221026.00167121550003134000%01456000.2401053124
10Anthony BeauvillierDucksLW33121022-1320354990234313.33%1272521.9834716660000532142.19%128288010.6101000122
11Ryder RolstonGulls (ANA)RW5861420-27556444292414.29%1180913.962101211841014331040.23%174118000.4924001011
12Cole SchwindtGulls (ANA)RW8461117200274229132520.69%64715.620110251011252152.65%28399000.7200000411
13Dakota JoshuaGulls (ANA)C/LW/RW48731042410523824111829.17%468814.3510117000060256.38%94127000.2900020201
14Connor MackeyGulls (ANA)D83279-71242089762061010.00%21152518.3800004011015000%0729000.1201211010
15Matt GrzelcykGulls (ANA)D842351201945228129.09%1496511.50202231011137010%0411000.1000000001
16Elias SalomonssonGulls (ANA)D85224-12301060103271597.41%42184421.701015104000196000%01330000.0401101010
17Marek AlscherGulls (ANA)D8503303420729417560%51156518.410003820001172000%0435000.0400103000
18Jordan GreenwayDucksLW/RW2022255159040%04321.8301121011240066.67%600000.9200010000
19Kyle MastersGulls (ANA)D31000000210000%0471.530000000000000%00000000000000
20Josh MansonDucksD2000040231000%24422.340000000002000%01300000000000
21Brandon CoeGulls (ANA)RW7000012035181110%04145.9300004000000033.33%62300000000000
22Julian LutzGulls (ANA)LW8500010033216120%03934.6300000000000066.67%30200011000000
23Riley HughesGulls (ANA)C/LW/RW100000001061110%0717.1000000000000033.33%181200000000000
24Francesco ArcuriGulls (ANA)C710002001771000%01812.5500000000000050.00%301100001000000
Statistiques d’équipe totales ou en moyenne1594176285461-4379834014851633130541173813.49%5172544415.96477912620113486713421203341947.17%3322374418240.361867202127433839
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
1Spencer KnightGulls (ANA)50241570.8722.23279908104815439120.824514837531
2Jake AllenDucks37211240.8882.2321760581726367110.80010370132
3Will CranleyGulls (ANA)70110.8962.372030087735000.6673048000
Statistiques d’équipe totales ou en moyenne944528120.8812.245179013193161884123648585663


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)LW212005-05-05CANYes172 Lbs5 ft11NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,422,000$63,482$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$41,295$0$0$No---------------------------Lien
Brett BrochuGulls (ANA)G232002-09-09CANYes176 Lbs6 ft0NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,000,000$44,643$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien
Cole SchwindtGulls (ANA)RW252001-04-25CANYes203 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm934,000$41,696$0$0$No---------------------------Lien
Cole SmithGulls (ANA)LW/RW301995-10-28USANo195 Lbs6 ft3NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm2,500,000$111,607$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$58,884$0$0$No---------------------------Lien
Dakota JoshuaGulls (ANA)C/LW/RW301996-05-15USANo206 Lbs6 ft3NoNoN/ANoYes1FalseFalsePro & Farm900,000$40,179$0$0$No---------------------------Lien
Devin CooleyGulls (ANA)G291997-05-25USANo188 Lbs6 ft5NoNoAssign ManuallyNoNo22024-09-10FalseFalsePro & Farm1,750,000$78,125$0$0$No1,750,000$--------1,750,000$--------No--------Lien
Dysin MayoGulls (ANA)D291996-08-17CANNo190 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm1,934,000$86,339$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$57,321$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$56,607$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$129,464$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$37,589$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$56,161$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$46,295$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$57,411$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$80,357$0$0$No1,800,000$--------1,800,000$--------No--------Lien / Lien NHL
Mikael PyyhtiaGulls (ANA)LW242001-12-17FINYes176 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm897,500$40,067$0$0$No---------------------------Lien
Rhett PitlickGulls (ANA)C/LW/RW252001-02-07USAYes170 Lbs5 ft10NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,352,000$60,357$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$58,884$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$66,964$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$36,830$0$0$No---------------------------Lien
Sam LaffertyGulls (ANA)C/LW/RW311995-03-06USANo205 Lbs6 ft2NoNoAssign ManuallyNoNo22024-09-10FalseFalsePro & Farm2,200,000$98,214$0$0$No2,200,000$--------2,200,000$--------No--------Lien / Lien NHL
Spencer KnightGulls (ANA)G252001-04-19USANo191 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm2,472,000$110,357$0$0$No2,472,000$--------925,000$--------No--------Lien
Vadim ZherenkoGulls (ANA)G252001-03-15RUSNo207 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm846,667$37,798$0$0$No---------------------------Lien
Will CranleyGulls (ANA)G242002-02-26CANYes185 Lbs6 ft4NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,075,000$47,991$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
2625.92191 Lbs6 ft22.231,417,160$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jared DavidsonSam LaffertyCole Smith40122
2Ryan LombergMikael PyyhtiaBradly Nadeau30122
3Mikael PyyhtiaRyan LombergJared Davidson20122
4Ryan LombergDakota JoshuaRhett 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
1Jared DavidsonRyan 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
2Mikael Pyyhtia40122Marek AlscherElias Salomonsson40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Ryan LombergRhett Pitlick60122
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, Mikael Pyyhtia, Rhett PitlickRyan Lomberg, Mikael PyyhtiaRyan Lomberg
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Marek Alscher, Jan Rutta, Dysin MayoDysin MayoJan Rutta, Dysin Mayo
Tirs de pénalité
Jared Davidson, Bradly Nadeau, 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
1Admirals21000010413100000101011100000031241.000461001295192222027941659086156629200.00%30100.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
2Americans2010010025-31010000002-21000010023-110.2502460029519222312794165908648132440300.00%7271.43%0538111048.47%594131145.31%43585750.76%1456506154994621781098
3Barracuda3110100036-3100010002112110000015-440.667358012951922239279416590864183443300.00%12375.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
4Bears2020000018-71010000016-51010000002-200.0001230029519222332794165908629112129000%3233.33%0538111048.47%594131145.31%43585750.76%1456506154994621781098
5Bruins50201020910-1301010106602010001034-160.60091221112951922258279416590867623349422100.00%12375.00%1538111048.47%594131145.31%43585750.76%1456506154994621781098
6Canucks5210010111110211000005503100010166060.600111526002951922265279416590868228367910220.00%14750.00%1538111048.47%594131145.31%43585750.76%1456506154994621781098
7Checkers2110000035-2110000001011010000025-320.500369012951922225279416590862379346233.33%20100.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
8Comets211000005321010000002-21100000051420.50058130029519222222794165908630921265240.00%8187.50%2538111048.47%594131145.31%43585750.76%1456506154994621781098
9Condors53100010121202200000041331100010811-380.80012203201295192221052794165908611544748618527.78%12283.33%0538111048.47%594131145.31%43585750.76%1456506154994621781098
10Crunch5220001013121321000009722010001045-160.60013193200295192228027941659086791848929555.56%9455.56%0538111048.47%594131145.31%43585750.76%1456506154994621781098
11Eagles21000010633110000004221000001021141.000651100295192222827941659086221519404125.00%7185.71%0538111048.47%594131145.31%43585750.76%1456506154994621781098
12Griffins2000020057-21000010023-11000010034-120.500581300295192222027941659086531133375120.00%40100.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
13Heat2020000038-51010000024-21010000014-300.00035810295192223427941659086481135293133.33%5260.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
14IceHogs2010001034-1100000103211010000002-220.5003470029519222192794165908626121933500.00%2150.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
15Islanders3110001089-12110000057-21000001032140.66781321002951922260279416590869419145511218.18%7271.43%0538111048.47%594131145.31%43585750.76%1456506154994621781098
16Marlies3110010046-22110000045-11000010001-130.500461000295192222927941659086261023518225.00%4250.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
17Monsters21000010413100000102111100000020241.0004370129519222162794165908629515373133.33%50100.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
18Moose2010100057-21010000014-31000100043120.50059140029519222232794165908632811504250.00%3166.67%0538111048.47%594131145.31%43585750.76%1456506154994621781098
19Penguins2010010058-31000010012-11010000046-210.250591400295192222827941659086312321385360.00%8450.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
20Phantoms22000000523110000004221100000010141.0005712012951922241279416590863112430300.00%2150.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
21Reign2020000037-41010000035-21010000002-200.00034700295192223427941659086722220338112.50%10460.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
22Roadrunners22000000624110000003121100000031241.000681400295192223827941659086461014315240.00%20100.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
23Rocket1000000123-1000000000001000000123-110.500246002951922215279416590861044162150.00%2150.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
24Senators21000010523110000002021000001032141.0005712012951922230279416590861933038300.00%5180.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
25Silver Knights52201000910-1210010005143120000049-560.60091625122951922294279416590868731369113215.38%8362.50%0538111048.47%594131145.31%43585750.76%1456506154994621781098
26Stars2010001078-1100000105411010000024-220.50078150029519222452794165908649131342400.00%4175.00%1538111048.47%594131145.31%43585750.76%1456506154994621781098
27Thunderbirds200000021012-21000000145-11000000167-120.50010152500295192225527941659086802628317342.86%4250.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
28Wild50400001920-112020000046-230200001514-910.1009142300295192228427941659086198638574400.00%20480.00%1538111048.47%594131145.31%43585750.76%1456506154994621781098
29Wolf Pack54000100133103300000010192100010032190.900132336032951922263279416590866132289413323.08%9188.89%0538111048.47%594131145.31%43585750.76%1456506154994621781098
30Wolves440000001266220000007432200000052381.000122032002951922271279416590866920398311436.36%12375.00%0538111048.47%594131145.31%43585750.76%1456506154994621781098
Total853028047115187201-144218130325110089114312150156487112-251020.60018728547231329519222130527941659086162151779814851794726.26%2055871.71%6538111048.47%594131145.31%43585750.76%1456506154994621781098
_Since Last GM Reset853028047115187201-144218130325110089114312150156487112-251020.60018728547231329519222130527941659086162151779814851794726.26%2055871.71%6538111048.47%594131145.31%43585750.76%1456506154994621781098
_Vs Conference51211503273110103724126030305937222799002435166-15670.65711017028021029519222761279416590869223005038861012726.73%1303473.85%5538111048.47%594131145.31%43585750.76%1456506154994621781098
_Vs Division221312022424154-1399502010211741347002322037-17420.9554165106242951922237127941659086445144235361551120.00%612165.57%1538111048.47%594131145.31%43585750.76%1456506154994621781098

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
85102W1187285472130516215177981485313
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
85302847115187201
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
421813325110089
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
431215156487112
Derniers 10 matchs
WLOTWOTL SOWSOL
540100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1794726.26%2055871.71%6
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
2794165908629519222
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
538111048.47%594131145.31%43585750.76%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1456506154994621781098


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
74931Gulls2Silver Knights4LSommaire du match
76948Bruins1Gulls2WXSommaire du match
77965Gulls2Checkers5LSommaire du match
78972Gulls1Phantoms0WSommaire du match
80986Admirals0Gulls1WXXSommaire du match
821015Heat4Gulls2LSommaire du match
831033Gulls3Islanders2WXXSommaire du match
841043IceHogs2Gulls3WXXSommaire du match
861065Monsters1Gulls2WXXSommaire du match
871080Gulls2Canucks3LXXSommaire du match
881086Gulls2Crunch1WXXSommaire du match
891102Marlies3Gulls1LSommaire du match
901115Gulls2Eagles1WXXSommaire du match
911129Gulls1Wild2LXXSommaire du match
921144Wild3Gulls2LSommaire du match
941165Gulls1Heat4LSommaire du match
951172Wolves2Gulls3WSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
971198Canucks3Gulls1LSommaire du match
981207Gulls1Canucks2LXSommaire du match
1001228Canucks2Gulls4WSommaire du match
1011240Gulls1Bruins0WXXSommaire du match
1031262Bears6Gulls1LSommaire du match
1051279Checkers0Gulls1WSommaire du match
1061286Gulls2Crunch4LSommaire du match
1071296Gulls4Condors3WXXSommaire du match
1101322Rocket-Gulls-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4020
Assistance52,93323,955
Assistance PCT63.02%57.04%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
1 1831 - 61.02% 92,111$3,868,664$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
8,333,382$ 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$ 3,556,581$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
92,111$ 5 77,541$ 387,705$




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