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Moose
GP: 58 | W: 26 | L: 22 | OTL: 10 | P: 62
GF: 107 | GA: 120 | PP%: 24.58% | PK%: 76.99%
DG: Quentin Robb | Morale : 42 | Moyenne d’équipe : 58
Prochains matchs #926 vs Penguins

Centre de jeu
Moose
26-22-10, 62pts
1
2 Americans
34-18-8, 76pts
Team Stats
L2SéquenceW3
12-12-6Fiche domicile19-6-5
14-10-4Fiche domicile15-12-3
3-5-2Derniers 10 matchs6-4-0
1.84Buts par match 3.33
2.07Buts contre par match 2.90
24.58%Pourcentage en avantage numérique30.00%
76.99%Pourcentage en désavantage numérique70.93%
Condors
33-20-8, 74pts
3
1 Moose
26-22-10, 62pts
Team Stats
L1SéquenceL2
17-11-2Fiche domicile12-12-6
16-9-6Fiche domicile14-10-4
6-2-2Derniers 10 matchs3-5-2
2.66Buts par match 1.84
2.16Buts contre par match 2.07
27.48%Pourcentage en avantage numérique24.58%
72.73%Pourcentage en désavantage numérique76.99%
Moose
26-22-10, 62pts
Jour 74
Penguins
23-27-10, 56pts
Statistiques d’équipe
L2SéquenceW2
12-12-6Fiche domicile12-10-7
14-10-4Fiche visiteur11-17-3
3-5-210 derniers matchs5-5-0
1.84Buts par match 2.07
2.07Buts contre par match 2.07
24.58%Pourcentage en avantage numérique30.15%
76.99%Pourcentage en désavantage numérique68.81%
Islanders
32-19-9, 73pts
Jour 75
Moose
26-22-10, 62pts
Statistiques d’équipe
SOL1SéquenceL2
15-9-6Fiche domicile12-12-6
17-10-3Fiche visiteur14-10-4
5-3-210 derniers matchs3-5-2
3.42Buts par match 1.84
3.07Buts contre par match 1.84
18.99%Pourcentage en avantage numérique24.58%
76.61%Pourcentage en désavantage numérique76.99%
Moose
26-22-10, 62pts
Jour 76
Heat
32-17-11, 75pts
Statistiques d’équipe
L2SéquenceW1
12-12-6Fiche domicile17-8-4
14-10-4Fiche visiteur15-9-7
3-5-210 derniers matchs5-2-3
1.84Buts par match 2.72
2.07Buts contre par match 2.72
24.58%Pourcentage en avantage numérique29.68%
76.99%Pourcentage en désavantage numérique79.61%
Meneurs d'équipe
Tyson JostButs
Tyson Jost
25
Tyson JostPasses
Tyson Jost
20
Tyson JostPoints
Tyson Jost
45
Plus/Moins
Wyatt Bongiovanni
5
James ReimerVictoires
James Reimer
26
Pourcentage d’arrêts
Marcus Hogberg
0.908

Statistiques d’équipe
Buts pour
107
1.84 GFG
Tirs pour
720
12.41 Avg
Pourcentage en avantage numérique
24.6%
29 GF
Début de zone offensive
34.8%
Buts contre
120
2.07 GAA
Tirs contre
982
16.93 Avg
Pourcentage en désavantage numérique
77.0%%
26 GA
Début de la zone défensive
39.8%
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
Assistance2,890
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
1Tyson Jost (A)XXX100.0077577676685670645262625925737661676302832,000,000$
2Phillip Di GiuseppeX100.0092469473705960613170576763686964456303231,750,000$
3Derek RyanXX100.0069429070655466608762586875767960656303912,250,000$
4Ross JohnstonXX100.0096995671895262612557546425666759656103212,160,000$
5Alex Barre-BouletXX100.0068638267635755658064636060464662596002821,524,000$
6Joseph BlandisiX100.0066676166677174637860625759464660446003112,190,000$
7Taylor WardX100.007576756776778354504956605446465957590281972,000$
8Kurtis MacDermidX100.0082997374904448572549545725676756585803222,000,000$
9Wyatt BongiovanniX100.0074708666705250595049656264464662585802611,063,333$
10Chase WoutersX100.0068677465675556526850525750464655605502621,064,000$
11Adam Boqvist (A)X100.0062419169706456742563506325666760616202531,484,000$
12Oliver KylingtonX100.0059418887675946602555476825656657566202832,000,000$
13John Klingberg (C)X100.0064428068707139582559496725778158426203331,750,000$
14Chase PriskieX100.0075708766707377622554576250464659596203012,157,000$
15Dillon HeatheringtonX100.0081817962816874472537426137464750615903012,126,000$
16Gustav OlofssonX100.0078768564766266512544436139464652515803121,200,000$
17Nikolas BrouillardX100.0066627866625455532549425540464652575503111,041,000$
18Connor Kelley (R)X100.0080739981743230412527396137454549345402331,330,000$
Rayé
1Jakub VranaX100.0065429181715659633662755869707268326403031,600,000$
2Chris WagnerXX100.0085908576724788595550567163717461336303431,600,000$
3Devin Kaplan (R)X100.0081739980734546445038446342444453195302231,265,000$
4Kevin ConleyXXX100.0074727962724443486044476045444452205102911,026,000$
5Travis HoweX100.0071834260834445455040445842444448205003211,007,000$
6Kalan Lind (R)X100.0059644780643230445038445242444447204802131,326,000$
MOYENNE D’ÉQUIPE100.00746779717255575644515361455656574858
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 Reimer100.006054577865587367686183747561856503832,211,000$
2Marcus Hogberg (R)100.005952529665527060655971505060736203132,180,000$
Rayé
1Thomas Milic100.004440506543425051464730444446214702331,025,000$
MOYENNE D’ÉQUIPE100.0054495380585164596056615656566058
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
1Tyson JostMoose (WPG)C/LW/RW5825204503558680120427120.83%8122621.15861423710002635249.09%1103214000.7311010735
2Derek RyanMoose (WPG)C/RW581810280115688185225621.18%9119520.6132514750002483159.76%821514000.4725001324
3Jakub VranaMoose (WPG)LW34121527040386363275119.05%1369920.56651114610000243040.72%2211911000.7704000162
4Phillip Di GiuseppeMoose (WPG)LW5181422-2000777570164411.43%10106220.823479680001612039.34%2112216000.4135000220
5Adam BoqvistMoose (WPG)D580202044039865525220%56134323.160222730000230050.00%22128000.3000000023
6Ross JohnstonMoose (WPG)LW/RW5831518-2691563583310219.09%485614.77110111154000001037.69%337614000.4213102114
7Chase PriskieMoose (WPG)D5821416-53715821134629224.35%43145825.141127100000069000%02038000.2200012102
8Chris WagnerMoose (WPG)C/RW356915-74830644839132215.38%1373220.920664500000393049.18%122916000.4103123211
9Alex Barre-BouletMoose (WPG)C/RW587815-7200607859162511.86%797516.82101117000051057.89%399914000.3111000001
10Joseph BlandisiMoose (WPG)C482911-122157344247178.33%876816.001671380112180058.45%1421312000.2900001121
11Taylor WardMoose (WPG)RW586410-132807070154640.00%13100317.303143550001500244.12%2381215000.2027000002
12Oliver KylingtonMoose (WPG)D58088-12204092238100%25118720.47000080000860020.00%51520000.1300000010
13Dillon HeatheringtonMoose (WPG)D58268-1442106194247108.33%34136123.47112372000089000%0326000.1200101020
14Kurtis MacDermidMoose (WPG)LW5834711006649207615.00%367311.610000130001190033.33%1268000.2100000020
15Adam KlapkaJetsRW11314-216101313182916.67%423721.620110211012181039.44%7165000.3400101111
16Nikolas BrouillardMoose (WPG)D58224-101003548112618.18%17102117.621234105000063000%028000.0800000000
17Chase WoutersMoose (WPG)C58213240241830266.67%12684.6400000000002052.00%5032000.2200000001
18Wyatt BongiovanniMoose (WPG)LW58112500281922650.00%12584.460000000003000%122000.1501000001
19Gustav OlofssonMoose (WPG)D4901110018342110%350210.260000200004000%024000.0400000000
20Devin KaplanMoose (WPG)RW9011100330010%1616.800110300000000%000000.3300000000
21John KlingbergMoose (WPG)D4700027517348000%74309.1500000000020000%10700000001000
22Connor KelleyMoose (WPG)D39000-100000000%0360.930000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne1077102163265-893681001025120072024040814.17%2801736016.12294877968951121171221547.01%2004217274000.3110304412192528
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)582620100.8801.933394012109905521110.76730580452
2Marcus HogbergMoose (WPG)50200.9083.2113100776461000058000
Statistiques d’équipe totales ou en moyenne632622100.8821.97352601211698156721305858452


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$516,750$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$530,679$0$0$No1,524,000$--------1,524,000$--------No--------Lien / Lien NHL
Chase PriskieMoose (WPG)D301996-03-19USANo197 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm2,157,000$751,098$0$0$No---------------------------Lien
Chase WoutersMoose (WPG)C262000-02-08SKWNo182 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm1,064,000$370,500$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$557,143$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$463,125$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$783,482$0$0$No---------------------------Lien / Lien NHL
Devin KaplanMoose (WPG)RW222004-01-10USAYes199 Lbs6 ft2NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,265,000$440,491$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$740,304$0$0$No---------------------------Lien
Gustav OlofssonMoose (WPG)D311994-12-01SWENo201 Lbs6 ft3NoNoFree AgentNoNo22024-09-18FalseFalsePro & Farm1,200,000$417,857$0$0$No1,200,000$--------1,200,000$--------No--------Lien
Jakub VranaMoose (WPG)LW301996-02-28CZENo197 Lbs6 ft0NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm1,600,000$557,143$0$0$No1,600,000$1,600,000$-------1,600,000$1,600,000$-------NoNo-------Lien / Lien NHL
James ReimerMoose (WPG)G381988-03-15CANNo200 Lbs6 ft2NoNoAssign ManuallyNoNo32025-12-08FalseFalsePro & Farm2,211,000$769,902$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$609,375$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$762,589$0$0$No---------------------------Lien / Lien NHL
Kalan LindMoose (WPG)LW212005-01-25SKYes170 Lbs6 ft0NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,326,000$461,732$0$0$No1,326,000$1,326,000$-------1,326,000$1,326,000$-------NoNo-------Lien
Kevin ConleyMoose (WPG)C/LW/RW291997-02-17USANo198 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm1,026,000$357,268$0$0$No---------------------------Lien
Kurtis MacDermidMoose (WPG)LW321994-03-25CANNo233 Lbs6 ft5NoNoFree AgentNoNo22024-09-18FalseFalsePro & Farm2,000,000$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$759,107$0$0$No2,180,000$2,180,000$-------2,180,000$2,180,000$-------NoNo-------Lien
Nikolas BrouillardMoose (WPG)D311995-02-07QUENo172 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm1,041,000$362,491$0$0$No---------------------------Lien
Oliver KylingtonMoose (WPG)D281997-05-19SWENo183 Lbs6 ft0NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm2,000,000$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$609,375$0$0$No1,750,000$1,750,000$-------1,750,000$1,750,000$-------NoNo-------Lien
Ross JohnstonMoose (WPG)LW/RW321994-02-18CANNo232 Lbs6 ft5NoNoN/ANoNo1FalseFalsePro & Farm2,160,000$752,143$0$0$No---------------------------Lien / Lien NHL
Taylor WardMoose (WPG)RW281998-03-31CANNo207 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm972,000$338,464$0$0$No---------------------------Lien
Thomas MilicMoose (WPG)G232003-04-13BCNo179 Lbs6 ft0NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,025,000$356,920$0$0$No1,025,000$1,025,000$-------1,025,000$1,025,000$-------NoNo-------Lien
Travis HoweMoose (WPG)RW321994-02-10USANo229 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm1,007,000$350,652$0$0$No---------------------------Lien
Tyson JostMoose (WPG)C/LW/RW281998-03-14CANNo187 Lbs5 ft11NoNoAssign ManuallyNoNo32025-11-06FalseFalsePro & Farm2,000,000$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$370,268$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2729.37197 Lbs6 ft12.111,603,753$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Joseph BlandisiAlex Barre-BouletPhillip Di Giuseppe40122
2Tyson JostRoss JohnstonDerek Ryan30122
3Derek RyanPhillip Di GiuseppeTyson Jost20122
4Derek RyanTaylor WardTyson Jost10122
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 JostRoss JohnstonJoseph Blandisi60122
2Derek RyanTaylor WardPhillip Di Giuseppe40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Chase PriskieNikolas Brouillard60122
2Adam BoqvistDillon Heatherington40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Taylor WardPhillip Di Giuseppe60122
2Derek RyanTyson 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
1Derek Ryan60122Dillon HeatheringtonOliver Kylington60122
2Tyson Jost40122Nikolas BrouillardChase Priskie40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Phillip Di GiuseppeDerek Ryan60122
2Tyson JostTaylor Ward40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nikolas BrouillardChase Priskie60122
2Dillon HeatheringtonOliver Kylington40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Derek RyanPhillip Di GiuseppeTyson JostDillon HeatheringtonChase Priskie
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Derek RyanPhillip Di GiuseppeTyson JostDillon HeatheringtonChase Priskie
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Derek Ryan, Tyson Jost, Taylor WardDerek Ryan, Tyson JostDerek Ryan
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dillon Heatherington, Chase Priskie, Nikolas BrouillardDillon HeatheringtonChase Priskie, Dillon Heatherington
Tirs de pénalité
Taylor Ward, Phillip Di Giuseppe, Ross Johnston, 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
1Admirals522001001616020200000811-33200010085350.50016254100263437159317623828056113355410413430.77%12283.33%032567847.94%36877647.42%24949650.20%96430410386581527778
2Americans41201000812-41100000031230201000511-640.5008111900263437153917623828056993034718225.00%60100.00%032567847.94%36877647.42%24949650.20%96430410386581527778
3Barracuda21000001211110000002021000000101-130.7502350126343715161762382805615611333133.33%30100.00%032567847.94%36877647.42%24949650.20%96430410386581527778
4Bears1010000013-21010000013-20000000000000.00011200263437151217623828056177812000%4250.00%032567847.94%36877647.42%24949650.20%96430410386581527778
5Bruins201010001101010000001-11000100010120.50011201263437152117623828056114640100.00%30100.00%032567847.94%36877647.42%24949650.20%96430410386581527778
6Canucks10000010431100000104310000000000021.00045900263437151917623828056295428100.00%2150.00%032567847.94%36877647.42%24949650.20%96430410386581527778
7Checkers430000101037330000007161000001032181.000101525022634371556176238280565110237313430.77%9188.89%032567847.94%36877647.42%24949650.20%96430410386581527778
8Comets3020010017-62010010015-41010000002-210.1671120026343715231762382805638121054500.00%5180.00%032567847.94%36877647.42%24949650.20%96430410386581527778
9Condors4120000159-42020000038-52100000121130.3755914112634371550176238280567115437310220.00%9188.89%032567847.94%36877647.42%24949650.20%96430410386581527778
10Crunch11000000312000000000001100000031221.000358002634371518176238280562172115200.00%3166.67%032567847.94%36877647.42%24949650.20%96430410386581527778
11Eagles301000203301010000013-22000002020240.6673140226343715301762382805640196601000.00%3166.67%032567847.94%36877647.42%24949650.20%96430410386581527778
12Griffins1000010012-11000010012-10000000000010.50012300263437159176238280561614192150.00%20100.00%032567847.94%36877647.42%24949650.20%96430410386581527778
13Gulls210001007521000010034-11100000041330.7507111800263437153217623828056231113313133.33%4250.00%032567847.94%36877647.42%24949650.20%96430410386581527778
14Heat3110010045-1210001004311010000002-230.5004610002634371531176238280564168438112.50%40100.00%132567847.94%36877647.42%24949650.20%96430410386581527778
15Islanders10000010211000000000001000001021121.000213002634371515176238280563392114200.00%30100.00%032567847.94%36877647.42%24949650.20%96430410386581527778
16Marlies11000000422110000004220000000000021.0004610002634371522176238280568442022100.00%2150.00%032567847.94%36877647.42%24949650.20%96430410386581527778
17Monsters200011006601000010023-11000100043130.75069150026343715311762382805636923378225.00%440.00%032567847.94%36877647.42%24949650.20%96430410386581527778
18Penguins11000000312110000003120000000000021.000358002634371519176238280561214242150.00%2150.00%032567847.94%36877647.42%24949650.20%96430410386581527778
19Phantoms11000000202110000002020000000000021.00023501263437157176238280567221922100.00%10100.00%032567847.94%36877647.42%24949650.20%96430410386581527778
20Reign20200000410-61010000046-21010000004-400.000461000263437152817623828056661912296350.00%6183.33%032567847.94%36877647.42%24949650.20%96430410386581527778
21Roadrunners1010000014-3000000000001010000014-300.0001230026343715817623828056268820200.00%40100.00%032567847.94%36877647.42%24949650.20%96430410386581527778
22Rocket20101000330100010002111010000012-120.500347002634371524176238280562551036100.00%5180.00%032567847.94%36877647.42%24949650.20%96430410386581527778
23Senators2020000015-41010000013-21010000002-200.00012300263437151117623828056358728300.00%110.00%032567847.94%36877647.42%24949650.20%96430410386581527778
24Stars3020010049-52010010024-21010000025-310.167481200263437154717623828056451110446233.33%5180.00%032567847.94%36877647.42%24949650.20%96430410386581527778
25Thunderbirds1000000123-1000000000001000000123-110.500246002634371510176238280563913625200.00%3166.67%032567847.94%36877647.42%24949650.20%96430410386581527778
26Wild1010000023-1000000000001010000023-100.00023500263437152017623828056371461611100.00%3233.33%032567847.94%36877647.42%24949650.20%96430410386581527778
27Wolf Pack21001000514100010001011100000041341.0005101501263437152117623828056114430100.00%20100.00%032567847.94%36877647.42%24949650.20%96430410386581527778
28Wolves211000002111010000001-11100000020220.5002460126343715817623828056175627100.00%3166.67%032567847.94%36877647.42%24949650.20%96430410386581527778
Total58162205753107120-1330912026105966-728710031434854-6620.534107163270110263437157201762382805698228036810251182924.58%1132676.99%132567847.94%36877647.42%24949650.20%96430410386581527778
_Since Last GM Reset58162205753107120-1330912026105966-728710031434854-6620.534107163270110263437157201762382805698228036810251182924.58%1132676.99%132567847.94%36877647.42%24949650.20%96430410386581527778
_Vs Conference321012014416574-9178600300403731526011412537-12350.5476596161052634371542617623828056613175204577782228.21%661183.33%132567847.94%36877647.42%24949650.20%96430410386581527778
_Vs Division13880133022202864002001013-3524011301275271.038223456032634371513617623828056171497821721523.81%24962.50%032567847.94%36877647.42%24949650.20%96430410386581527778

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
5862L21071632707209822803681025110
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
5816225753107120
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3091226105966
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2871031434854
Derniers 10 matchs
WLOTWOTL SOWSOL
350101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1182924.58%1132676.99%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
1762382805626343715
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
32567847.94%36877647.42%24949650.20%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
96430410386581527778


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
18216Moose4Americans3WXSommaire du match
19229Comets3Moose0LSommaire du match
20250Moose4Gulls1WSommaire du match
22262Stars2Moose1LXSommaire du match
23274Moose4Admirals2WSommaire du match
24289Moose4Monsters3WXSommaire du match
26302Reign6Moose4LSommaire du match
27321Senators3Moose1LSommaire du match
28334Moose0Senators2LSommaire du match
29349Moose0Barracuda1LXXSommaire du match
30362Gulls4Moose3LXSommaire du match
31378Barracuda0Moose2WSommaire du match
33399Moose1Rocket2LSommaire du match
34414Marlies2Moose4WSommaire du match
35434Bruins1Moose0LSommaire du match
37449Moose4Wolf Pack1WSommaire du match
38467Wolf Pack0Moose1WXSommaire du match
39479Moose2Thunderbirds3LXXSommaire du match
40493Moose3Crunch1WSommaire du match
41511Checkers0Moose2WSommaire du match
42524Bears3Moose1LSommaire du match
43540Moose2Islanders1WXXSommaire du match
44554Moose1Roadrunners4LSommaire du match
45570Checkers0Moose2WSommaire du match
46582Moose2Condors0WSommaire du match
47598Monsters3Moose2LXSommaire du match
48616Rocket1Moose2WXSommaire du match
49629Moose0Reign4LSommaire du match
50644Moose1Bruins0WXSommaire du match
52663Canucks3Moose4WXXSommaire du match
53684Griffins2Moose1LXSommaire du match
54702Moose2Wild3LSommaire du match
56715Admirals6Moose4LSommaire du match
57723Moose1Eagles0WXXSommaire du match
58746Phantoms0Moose2WSommaire du match
60763Moose3Checkers2WXXSommaire du match
61778Comets2Moose1LXSommaire du match
63794Moose0Comets2LSommaire du match
64813Stars2Moose1LSommaire du match
65829Moose0Condors1LXXSommaire du match
67842Wolves1Moose0LSommaire du match
68851Moose2Wolves0WSommaire du match
69872Americans1Moose3WSommaire du match
70888Moose1Americans2LSommaire du match
72902Condors3Moose1LSommaire du match
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
Assistance57,21629,484
Assistance PCT95.36%98.28%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
13 2890 - 96.33% 85,687$2,570,607$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
3,360,340$ 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$ 2,838,901$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,113,930$ 39 45,805$ 1,786,395$




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