Please rotate your device to landscape mode for a better experience.
Connexion

Moose
GP: 13 | W: 5 | L: 6 | OTL: 2 | P: 12
GF: 24 | GA: 34 | PP%: 12.82% | PK%: 88.00%
DG: Quentin Robb | Morale : 45 | Moyenne d’équipe : 58
Prochains matchs #216 vs Americans

Centre de jeu
Moose
5-6-2, 12pts
3
1 Admirals
8-4-1, 17pts
Team Stats
L1SéquenceW1
3-3-1Fiche domicile5-2-0
2-3-1Fiche domicile3-2-1
4-4-2Derniers 10 matchs5-4-1
1.85Buts par match 3.23
2.62Buts contre par match 3.15
12.82%Pourcentage en avantage numérique43.48%
88.00%Pourcentage en désavantage numérique63.04%
Admirals
8-4-1, 17pts
5
4 Moose
5-6-2, 12pts
Team Stats
W1SéquenceL1
5-2-0Fiche domicile3-3-1
3-2-1Fiche domicile2-3-1
5-4-1Derniers 10 matchs4-4-2
3.23Buts par match 1.85
3.15Buts contre par match 2.62
43.48%Pourcentage en avantage numérique12.82%
63.04%Pourcentage en désavantage numérique88.00%
Moose
5-6-2, 12pts
Jour 18
Americans
9-4-1, 19pts
Statistiques d’équipe
L1SéquenceL1
3-3-1Fiche domicile5-1-0
2-3-1Fiche visiteur4-3-1
4-4-210 derniers matchs7-3-0
1.85Buts par match 4.21
2.62Buts contre par match 4.21
12.82%Pourcentage en avantage numérique26.19%
88.00%Pourcentage en désavantage numérique73.81%
Comets
5-6-2, 12pts
Jour 19
Moose
5-6-2, 12pts
Statistiques d’équipe
W1SéquenceL1
3-3-0Fiche domicile3-3-1
2-3-2Fiche visiteur2-3-1
4-4-210 derniers matchs4-4-2
2.54Buts par match 1.85
3.08Buts contre par match 1.85
25.81%Pourcentage en avantage numérique12.82%
60.00%Pourcentage en désavantage numérique88.00%
Moose
5-6-2, 12pts
Jour 20
Gulls
8-5-0, 16pts
Statistiques d’équipe
L1SéquenceL1
3-3-1Fiche domicile5-2-0
2-3-1Fiche visiteur3-3-0
4-4-210 derniers matchs6-4-0
1.85Buts par match 2.54
2.62Buts contre par match 2.54
12.82%Pourcentage en avantage numérique16.67%
88.00%Pourcentage en désavantage numérique80.00%
Meneurs d'équipe
Derek RyanButs
Derek Ryan
6
Jakub VranaPasses
Jakub Vrana
6
Jakub VranaPoints
Jakub Vrana
11
Plus/Moins
Devin Kaplan
1
James ReimerVictoires
James Reimer
5
Pourcentage d’arrêts
Marcus Hogberg
0.914

Statistiques d’équipe
Buts pour
24
1.85 GFG
Tirs pour
180
13.85 Avg
Pourcentage en avantage numérique
12.8%
5 GF
Début de zone offensive
33.9%
Buts contre
34
2.62 GAA
Tirs contre
289
22.23 Avg
Pourcentage en désavantage numérique
88.0%%
3 GA
Début de la zone défensive
39.7%
Informations de l'équipe

Directeur généralQuentin Robb
EntraîneurBob Essensa
DivisionDivision 4
ConférenceConference 2
CapitaineJohn Klingberg
Assistant #1Adam Boqvist
Assistant #2Tyson Jost


Informations de l’aréna

Capacité3,000
Assistance2,870
Billets de saison1,500


Informations de la formation

Équipe Pro27
Équipe Mineure19
Limite contact 46 / 100
Espoirs149


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
1Phillip Di GiuseppeX98.0092469373705960613170576963676865456403231,750,000$
2Jakub VranaX98.0065429181715659623661745969697169516402931,600,000$
3Chris WagnerXX100.0085908576724788585550567263707462506303431,600,000$
4Derek RyanXX100.0069428971665466608762576975747762496303912,250,000$
5Tyson Jost (A)XXX98.0077577676685670635261596025717463506202732,000,000$
6Ross JohnstonXX100.0096995671895262622557556525646561496103112,160,000$
7Alex Barre-BouletXX100.0068638167635755668065636260444464496002821,524,000$
8Taylor WardX100.007576746776778355504957625445456049590271972,000$
9Kurtis MacDermidX100.0082997274904448582550555925656558495803122,000,000$
10Wyatt BongiovanniX100.0075708566705250615050676464444464495802611,063,333$
11Chase WoutersX100.0069677365675556546851535950444457495502521,064,000$
12Devin Kaplan (R)X100.0081739980734546445038446342444453405302231,265,000$
13Oliver KylingtonX100.0059418787675946602555487025636459496302832,000,000$
14Adam Boqvist (A)X100.0063419069706456742563516325646562496202531,484,000$
15Chase PriskieX100.0075708766707377612554576350454560476102912,157,000$
16Dillon HeatheringtonX100.0081817862816874472537416237454651495903012,126,000$
17Gustav OlofssonX100.0079768564766266512545446339454453435803121,200,000$
18Nikolas BrouillardX100.0067627766625455532550425740454553495503011,041,000$
19Connor Kelley (R)X100.0081739980733230412528396237444450405402331,330,000$
Rayé
1Joseph BlandisiX74.7365676066677174647861635859454561406003112,190,000$
2Kevin ConleyXXX100.0074727962724443486044476045444452375202811,026,000$
3Travis HoweX100.0071834260834445455040445842444448375003111,007,000$
4Kalan Lind (R)X100.0059644780643230445038445242444447374802031,326,000$
5John Klingberg (C)X81.9165427968707139592561506925768060376303331,750,000$
MOYENNE D’ÉQUIPE97.94746779717255575644525363455455584659
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
1James Reimer100.006154577866567064666183727363576403732,211,000$
2Marcus Hogberg (R)100.005952529665526959655971505060516203132,180,000$
Rayé
1Thomas Milic100.004440506543425051464730444446444702231,025,000$
MOYENNE D’ÉQUIPE100.0055495380585063585956615556565158
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bob Essensa45444345434337TUR812800,000$


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
1Jakub VranaMoose (WPG)LW135611-540222422131722.73%527821.41224532000081041.48%17688000.7901000020
2Derek RyanMoose (WPG)C/RW13617-72012142671623.08%224418.82101829000020171.43%742000.5711000201
3Phillip Di GiuseppeMoose (WPG)LW13156-7001919164156.25%328521.991234320000150052.78%3653000.4211000000
4Tyson JostMoose (WPG)C/LW/RW13325-64023202071515.00%225319.470000160001171040.00%2072000.4000000010
5Chase PriskieMoose (WPG)D13055-61210191711470%1433425.70000137000019000%074000.3000011001
6Oliver KylingtonMoose (WPG)D13044-5007154230%823518.140000100009000%314000.3400000000
7Joseph BlandisiMoose (WPG)C10044-375191611280%421221.270220200112180057.83%8356000.3800001100
8Adam KlapkaJetsRW11314-216101313182916.67%423721.620110211012181039.44%7165000.3400101111
9Adam BoqvistMoose (WPG)D13033-2006159320%1025319.4801122800007000%094000.2400000001
10Chris WagnerMoose (WPG)C/RW13213-818102314115518.18%526220.16011128000091053.33%1564000.2300101010
11Dillon HeatheringtonMoose (WPG)D13022-6235142811030%430623.56000227000020000%006000.1300001000
12Alex Barre-BouletMoose (WPG)C/RW130221403103000%21229.4100005000000058.33%1201000.3300000000
13Taylor WardMoose (WPG)RW13202-260131860133.33%417813.7400007000000040.00%5034000.2200000000
14Kurtis MacDermidMoose (WPG)LW130110201282320%11229.4400004000020050.00%211000.1600000000
15Nikolas BrouillardMoose (WPG)D13101-3205840225.00%422016.97101238000016000%001000.0900000000
16Gustav OlofssonMoose (WPG)D4000000020000%1307.550000000000000%00100000000000
17John KlingbergMoose (WPG)D9000-2757244000%717919.9000000000020000%00500000001000
18Wyatt BongiovanniMoose (WPG)LW13000100200000%0211.670000000000000%00000000000000
19Chase WoutersMoose (WPG)C13000000101000%0262.0100000000000057.14%70000000000000
20Devin KaplanMoose (WPG)RW2000100000000%194.990000100000000%00000000000000
21Connor KelleyMoose (WPG)D2000000000000%010.990000000000000%00000000000000
22Ross JohnstonMoose (WPG)LW/RW13000-100521100%0493.8300000000000044.44%180000000000000
Statistiques d’équipe totales ou en moyenne246233760-62107452252671805310512.78%81386715.7259142533311251864145.80%5006261000.3123216454
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
1James ReimerMoose (WPG)135620.8782.627100131254148001.0002130020
2Marcus HogbergMoose (WPG)20000.9142.437400335190000013000
Statistiques d’équipe totales ou en moyenne155620.8822.6078501342891670021313020


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
Adam BoqvistMoose (WPG)D252000-08-15SWENo191 Lbs6 ft0NoNoN/ANoNo32025-10-22FalseFalsePro & Farm1,484,000$1,258,750$0$0$No1,484,000$1,484,000$-------1,484,000$1,484,000$-------NoNo-------Lien
Alex Barre-BouletMoose (WPG)C/RW281997-05-21QUENo178 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm1,524,000$1,292,679$0$0$No1,524,000$--------1,524,000$--------No--------Lien / Lien NHL
Chase PriskieMoose (WPG)D291996-03-19USANo197 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm2,157,000$1,829,598$0$0$No---------------------------Lien
Chase WoutersMoose (WPG)C252000-02-08SKWNo182 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm1,064,000$902,500$0$0$No1,064,000$--------1,064,000$--------No--------Lien
Chris WagnerMoose (WPG)C/RW341991-05-27USANo192 Lbs6 ft0NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm1,600,000$1,357,143$0$0$No1,600,000$1,600,000$-------1,600,000$1,600,000$-------NoNo-------Lien / Lien NHL
Connor KelleyMoose (WPG)D232002-07-30USAYes195 Lbs6 ft2NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,330,000$1,128,125$0$0$No1,330,000$1,330,000$-------1,330,000$1,330,000$-------NoNo-------Lien
Derek RyanMoose (WPG)C/RW391986-12-29USANo185 Lbs5 ft10NoNoFree AgentNoNo12025-08-28FalseFalsePro & Farm2,250,000$1,908,482$0$0$No---------------------------Lien / Lien NHL
Devin KaplanMoose (WPG)RW222004-01-10USAYes199 Lbs6 ft2NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,265,000$1,072,991$0$0$No1,265,000$1,265,000$-------1,265,000$1,265,000$-------NoNo-------Lien
Dillon HeatheringtonMoose (WPG)D301995-05-09CANNo215 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm2,126,000$1,803,304$0$0$No---------------------------Lien
Gustav OlofssonMoose (WPG)D311994-12-01SWENo201 Lbs6 ft3NoNoFree AgentNoNo22024-09-18FalseFalsePro & Farm1,200,000$1,017,857$0$0$No1,200,000$--------1,200,000$--------No--------Lien
Jakub VranaMoose (WPG)LW291996-02-28CZENo197 Lbs6 ft0NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm1,600,000$1,357,143$0$0$No1,600,000$1,600,000$-------1,600,000$1,600,000$-------NoNo-------Lien / Lien NHL
James ReimerMoose (WPG)G371988-03-15CANNo200 Lbs6 ft2NoNoAssign ManuallyNoNo32025-12-08FalseFalsePro & Farm2,211,000$1,875,402$0$0$No2,211,000$2,211,000$-------2,211,000$2,211,000$-------NoNo-------Lien / Lien NHL
John KlingbergMoose (WPG)D331992-08-14SWENo185 Lbs6 ft2NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm1,750,000$1,484,375$0$0$No1,750,000$1,750,000$-------1,750,000$1,750,000$-------NoNo-------Lien / Lien NHL
Joseph BlandisiMoose (WPG)C311994-07-18CANNo183 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm2,190,000$1,857,589$0$0$No---------------------------Lien / Lien NHL
Kalan LindMoose (WPG)LW202005-01-25SKYes170 Lbs6 ft0NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,326,000$1,124,732$0$0$No1,326,000$1,326,000$-------1,326,000$1,326,000$-------NoNo-------Lien
Kevin ConleyMoose (WPG)C/LW/RW281997-02-17USANo198 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm1,026,000$870,268$0$0$No---------------------------Lien
Kurtis MacDermidMoose (WPG)LW311994-03-25CANNo233 Lbs6 ft5NoNoFree AgentNoNo22024-09-18FalseFalsePro & Farm2,000,000$1,696,429$0$0$No2,000,000$--------2,000,000$--------No--------Lien / Lien NHL
Marcus HogbergMoose (WPG)G311994-11-25SWEYes234 Lbs6 ft5NoNoAssign ManuallyNoNo32025-12-08FalseFalsePro & Farm2,180,000$1,849,107$0$0$No2,180,000$2,180,000$-------2,180,000$2,180,000$-------NoNo-------Lien
Nikolas BrouillardMoose (WPG)D301995-02-07QUENo172 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm1,041,000$882,991$0$0$No---------------------------Lien
Oliver KylingtonMoose (WPG)D281997-05-19SWENo183 Lbs6 ft0NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm2,000,000$1,696,429$0$0$No2,000,000$2,000,000$-------2,000,000$2,000,000$-------NoNo-------Lien
Phillip Di GiuseppeMoose (WPG)LW321993-10-09CANNo193 Lbs6 ft0NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm1,750,000$1,484,375$0$0$No1,750,000$1,750,000$-------1,750,000$1,750,000$-------NoNo-------Lien
Ross JohnstonMoose (WPG)LW/RW311994-02-18CANNo232 Lbs6 ft5NoNoN/ANoNo1FalseFalsePro & Farm2,160,000$1,832,143$0$0$No---------------------------Lien / Lien NHL
Taylor WardMoose (WPG)RW271998-03-31CANNo207 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm972,000$824,464$0$0$No---------------------------Lien
Thomas MilicMoose (WPG)G222003-04-13BCNo179 Lbs6 ft0NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,025,000$869,420$0$0$No1,025,000$1,025,000$-------1,025,000$1,025,000$-------NoNo-------Lien
Travis HoweMoose (WPG)RW311994-02-10USANo229 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm1,007,000$854,152$0$0$No---------------------------Lien
Tyson JostMoose (WPG)C/LW/RW271998-03-14CANNo187 Lbs5 ft11NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm2,000,000$1,696,429$0$0$No2,000,000$2,000,000$-------2,000,000$2,000,000$-------NoNo-------Lien / Lien NHL
Wyatt BongiovanniMoose (WPG)LW261999-07-24USANo193 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,063,333$901,934$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2728.89197 Lbs6 ft12.111,603,753$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Phillip Di GiuseppeJakub VranaChris Wagner40122
2Tyson JostRoss JohnstonDerek Ryan30122
3Jakub VranaPhillip Di GiuseppeTyson Jost20122
4Phillip Di GiuseppeTaylor WardJakub Vrana10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Adam BoqvistChase Priskie40122
2Oliver KylingtonDillon Heatherington30122
3Dillon HeatheringtonAdam Boqvist20122
4Nikolas BrouillardChase Priskie10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tyson JostJakub VranaPhillip Di Giuseppe60122
2Derek RyanTaylor WardChris Wagner40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Chase PriskieNikolas Brouillard60122
2Adam BoqvistDillon Heatherington40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Phillip Di GiuseppeChris Wagner60122
2Jakub VranaTyson Jost40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dillon HeatheringtonOliver Kylington60122
2Chase PriskieNikolas Brouillard40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Phillip Di Giuseppe60122Dillon HeatheringtonOliver Kylington60122
2Jakub Vrana40122Nikolas BrouillardChase Priskie40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Chris WagnerJakub Vrana60122
2Phillip Di GiuseppeTaylor Ward40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nikolas BrouillardChase Priskie60122
2Dillon HeatheringtonOliver Kylington40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jakub VranaChris WagnerPhillip Di GiuseppeDillon HeatheringtonChase Priskie
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jakub VranaChris WagnerPhillip Di GiuseppeDillon HeatheringtonChase Priskie
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Phillip Di Giuseppe, Tyson Jost, Jakub VranaPhillip Di Giuseppe, Jakub VranaJakub Vrana
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dillon Heatherington, Chase Priskie, Nikolas BrouillardDillon HeatheringtonChase Priskie, Dillon Heatherington
Tirs de pénalité
Jakub Vrana, Chris Wagner, Phillip Di Giuseppe, Derek Ryan, Tyson Jost
Gardien
#1 : James Reimer, #2 : Marcus Hogberg


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
1Admirals311001008801010000045-12100010043130.5008122000109425044785838226204910110.00%50100.00%06816840.48%9219746.70%6913152.67%21971236144329172
2Americans1010000006-6000000000001010000006-600.00000000109427447858336182814400.00%30100.00%06816840.48%9219746.70%6913152.67%21971236144329172
3Checkers11000000312110000003120000000000021.00035800109421544785831521122200.00%30100.00%06816840.48%9219746.70%6913152.67%21971236144329172
4Condors1010000025-31010000025-30000000000000.0002460010942184478583481024144125.00%20100.00%06816840.48%9219746.70%6913152.67%21971236144329172
5Eagles2010001023-11010000013-21000001010120.50021301109422644785833112648800.00%3166.67%06816840.48%9219746.70%6913152.67%21971236144329172
6Heat3110010045-1210001004311010000002-230.500461000109423144785834168438112.50%40100.00%16816840.48%9219746.70%6913152.67%21971236144329172
7Penguins11000000312110000003120000000000021.00035800109421944785831214242150.00%2150.00%06816840.48%9219746.70%6913152.67%21971236144329172
8Stars1010000025-3000000000001010000025-300.000246001094214447858324661111100.00%3166.67%06816840.48%9219746.70%6913152.67%21971236144329172
Total1346002102434-10733001001718-161300110716-9120.462243761011094218044785832898110722539512.82%25388.00%16816840.48%9219746.70%6913152.67%21971236144329172
_Since Last GM Reset1346002102434-10733001001718-161300110716-9120.462243761011094218044785832898110722539512.82%25388.00%16816840.48%9219746.70%6913152.67%21971236144329172
_Vs Conference1245002102229-7632001001513261300110716-9120.50022335501109421624478583241718321135411.43%23386.96%16816840.48%9219746.70%6913152.67%21971236144329172
_Vs Division145002103121320010031201300110000126.00035800109421944785831214242150.00%2150.00%06816840.48%9219746.70%6913152.67%21971236144329172

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1312L12437611802898110722501
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
134602102434
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
73301001718
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
6130110716
Derniers 10 matchs
WLOTWOTL SOWSOL
440200
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
39512.82%25388.00%1
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
447858310942
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
6816840.48%9219746.70%6913152.67%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
21971236144329172


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
18Checkers1Moose3WSommaire du match
224Condors5Moose2LSommaire du match
441Moose0Americans6LSommaire du match
554Moose2Stars5LSommaire du match
666Heat2Moose1LXSommaire du match
774Moose1Admirals2LXSommaire du match
990Moose0Heat2LSommaire du match
10112Penguins1Moose3WSommaire du match
11129Heat1Moose3WSommaire du match
12140Moose1Eagles0WXXSommaire du match
14162Eagles3Moose1LSommaire du match
16188Moose3Admirals1WSommaire du match
17199Admirals5Moose4LSommaire du match
18216Moose-Americans-
19229Comets-Moose-
20250Moose-Gulls-
22262Stars-Moose-
23274Moose-Admirals-
24289Moose-Monsters-
26302Reign-Moose-
27321Senators-Moose-
28334Moose-Senators-
29349Moose-Barracuda-
30362Gulls-Moose-
31378Barracuda-Moose-
33399Moose-Rocket-
34414Marlies-Moose-
35434Bruins-Moose-
37449Moose-Wolf Pack-
38467Wolf Pack-Moose-
39479Moose-Thunderbirds-
40493Moose-Crunch-
41511Checkers-Moose-
42524Bears-Moose-
43540Moose-Islanders-
44554Moose-Roadrunners-
45570Checkers-Moose-
46582Moose-Condors-
47598Monsters-Moose-
48616Rocket-Moose-
49629Moose-Reign-
50644Moose-Bruins-
52663Canucks-Moose-
53684Griffins-Moose-
54702Moose-Wild-
56715Admirals-Moose-
57723Moose-Eagles-
58746Phantoms-Moose-
60763Moose-Checkers-
61778Comets-Moose-
63794Moose-Comets-
64813Stars-Moose-
65829Moose-Condors-
67842Wolves-Moose-
68851Moose-Wolves-
69872Americans-Moose-
70888Moose-Americans-
72902Condors-Moose-
74926Moose-Penguins-
75938Islanders-Moose-
76954Moose-Heat-
78969IceHogs-Moose-
79985Moose-Heat-
811000Thunderbirds-Moose-
821019Moose-Bears-
831029Heat-Moose-
851055Crunch-Moose-
861059Moose-Marlies-
871074Moose-IceHogs-
881089Americans-Moose-
901109Moose-Canucks-
911121Moose-Stars-
921135Penguins-Moose-
931151Moose-Checkers-
941162Roadrunners-Moose-
951176Moose-Canucks-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
971189Penguins-Moose-
981212Moose-Silver Knights-
991218Wild-Moose-
1021247Silver Knights-Moose-
1041271Eagles-Moose-
1051277Moose-Penguins-
1071303Eagles-Moose-
1081307Moose-Phantoms-
1091313Moose-Griffins-
1101323Moose-Stars-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets2510
Assistance13,2166,872
Assistance PCT94.40%98.17%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
36 2870 - 95.66% 84,956$594,689$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
795,260$ 4,330,133$ 4,330,133$ 800,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
38,662$ 673,829$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
3,058,401$ 95 45,805$ 4,351,475$




Moose 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

Moose 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

Moose 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

Moose 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

Moose 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