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Connexion

Moose
GP: 19 | W: 11 | L: 8
GF: 48 | GA: 40 | PP%: 22.37% | PK%: 73.91%
DG: Luca | Morale : 76 | Moyenne d’équipe : N/A
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Centre de jeu
Express
16-7-0, 32pts
3
FINAL
1 Moose
11-8-0, 22pts
Team Stats
W2SéquenceL2
10-3-0Fiche domicile4-4-0
6-4-0Fiche domicile7-4-0
7-2-1Derniers 10 matchs5-5-0
3.35Buts par match 2.53
2.13Buts contre par match 2.11
34.12%Pourcentage en avantage numérique22.37%
81.82%Pourcentage en désavantage numérique73.91%
Moose
11-8-0, 22pts
0
FINAL
1 Express
16-7-0, 32pts
Team Stats
L2SéquenceW2
4-4-0Fiche domicile10-3-0
7-4-0Fiche domicile6-4-0
5-5-0Derniers 10 matchs7-2-1
2.53Buts par match 3.35
2.11Buts contre par match 2.13
22.37%Pourcentage en avantage numérique34.12%
73.91%Pourcentage en désavantage numérique81.82%
Meneurs d'équipe
Buts
Peyton Krebs
13
Passes
Axel Jonsson Fjallby
14
Points
Peyton Krebs
26
Plus/Moins
Peyton Krebs
6
Victoires
Olivier Rodrigue
7
Pourcentage d’arrêts
Olivier Rodrigue
0.906

Statistiques d’équipe
Buts pour
48
2.53 GFG
Tirs pour
462
24.32 Avg
Pourcentage en avantage numérique
22.4%
17 GF
Début de zone offensive
44.8%
Buts contre
40
2.11 GAA
Tirs contre
429
22.58 Avg
Pourcentage en désavantage numérique
73.9%%
6 GA
Début de la zone défensive
31.2%
Informations de l'équipe

Directeur généralLuca
EntraîneurTravis Green
DivisionNorth Division
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité8,000
Assistance7,962
Billets de saison800


Informations de la formation

Équipe Pro38
Équipe Mineure20
Limite contact 58 / 65
Espoirs24


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
1Peyton KrebsX100.00725287747179947171686670655460086002321,350,000$
2Justin BrazeauXX100.0068509370847891706170707165576407400262650,000$
3Max SassonX100.0055555555555555555555555555465708500241650,000$
4Mitchell RussellXXX100.0055555555555555555555555555465808600232792,750$
5Axel Jonsson FjallbyXX100.00715095737275907062666768655463084002611,100,000$
6Max DomiX100.0066588186778094767579686773586308200293705,000$
7Tyce ThompsonX100.0055555555555555555555555555495706600251866,250$
8Calvin ThurkaufXXX100.0055555555555555555555555555596607900272650,000$
9Jiri KulichX100.00625091717181886464636567654055086002021,500,000$
10Ilya Fedotov (R)XX100.0055555555555555555555555555405508501213975,000$
11Andrew Cristall (R)XX100.00555555555555555555555555554055086011931,500,000$
12Arttu Hyry (R)XXX100.0055555555555555555555555555405508000231795,000$
13Anthony DeAngeloX100.00615088866881797825727268665761087002924,250,000$
14Jett WooX100.00555555555555555555555555555862083002411,378,125$
15Oliver KylingtonX100.0067509282708480742568727365616608700272650,000$
16Filip RoosX100.0066509266738190632564617165485507700251740,250$
17Daniil ChaykaX100.00555555555555555555555555554356030002211,250,000$
18Marshall WarrenX100.0055555555555555555555555555405503100231975,000$
Rayé
1Luke Haymes (R)X100.0055555555555555555555555555405502700213655,000$
2Jordan FrascaX100.0055555555555555555555555555465802000232729,750$
3Theo RochetteX100.0055555555555555555555555555435602000221650,000$
4Artem ShlaineX100.0055555555555555555555555555405502000222825,000$
5Ethan CardwellXX100.0055555555555555555555555555405504400222825,000$
6Jacob QuillanX100.0055555555555555555555555555405502700221650,000$
7Alexander SuvorovXXX100.0055555555555555555555555555405502000221650,000$
8Dylan Peterson (R)X100.0055555555555555555555555555405502101222975,000$
9Michael BenningX100.0055555555555555555555555555405503700222975,000$
10Christian KyrouX100.00555555555555555555555555554055020002121,250,000$
11Jiri TichacekX100.0055555555555555555555555555405502000212650,000$
12Tristan Bertucci (R)X100.0055555555555555555555555555405502301193975,000$
13Artem Duda (R)X100.0055555555555555555555555555405507001203825,000$
14Noah Chadwick (R)X100.0055555555555555555555555555405505201193650,000$
MOYENNE D’ÉQUIPE100.005854646060616359545858595846570560
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
1Arturs Silovs100.005555555555555555555555496108300231787,500$
2Olivier Rodrigue100.0055555555555555555555555563051002411,378,125$
Rayé
1Isak Posch (R)100.005555555555555555555555405506400222655,000$
2Strauss Mann100.005555555555555555555555516107000261682,500$
3Jesper Wallstedt100.0055555555555555555555554755048002211,500,000$
4Carl Lindbom100.005555555555555555555555405506400212700,000$
MOYENNE D’ÉQUIPE100.00555555555555555555555547580630
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Travis Green7780848871741CAN534600,000$


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
1Peyton KrebsMoose (WPG)C19131326640313280232116.25%544523.4753821570002151251.48%270105001.1700000313
2Axel Jonsson FjallbyMoose (WPG)LW/RW1971421500222466164410.61%543823.0716713550002162066.67%30145000.9600000143
3Max DomiMoose (WPG)C1741014-2101025245213317.69%934320.220441048000071055.81%12971000.8100002101
4Jiri KulichMoose (WPG)C196511-400182639133015.38%638020.034268570004162050.50%20223000.5800000011
5Anthony DeAngeloMoose (WPG)D19369-42011204826186.25%1843923.121231260000018100%0159000.4100000100
6Justin BrazeauMoose (WPG)LW/RW19077-8002026285130%629115.350552270001110051.82%13752000.4800000010
7Oliver KylingtonMoose (WPG)D1815629520212621213.85%1538221.25123242000012100%035000.3100010001
8Filip RoosMoose (WPG)D1915631010112822894.55%1840221.18134652000015000%059000.3000110000
9Tyce ThompsonMoose (WPG)C18145155137154126.67%01709.50022230000000043.75%6413000.5800100000
10Max SassonMoose (WPG)C19134-52315292113147.69%729815.7300002000000051.52%3312000.2700111000
11Calvin ThurkaufMoose (WPG)C/LW/RW18314-1115182019101215.79%022212.34112335000002075.00%836000.3600100100
12Andrew CristallMoose (WPG)LW/RW1922417511796722.22%11869.811122230000010100.00%432000.4300001100
13Jett WooMoose (WPG)D190331121024155040%1436919.4301103500009000%011000.1600002000
14Noah ChadwickMoose (WPG)D12213-31410101493222.22%1022618.8821342200005000%004000.2600110000
15Arttu HyryMoose (WPG)C/LW/RW19213-418102216162612.50%329715.6300000000000050.00%635000.2000020001
16Mitchell RussellMoose (WPG)C/LW/RW1920221210151472928.57%629615.6200004000000036.84%1932000.1300011000
17Artem DudaMoose (WPG)D14011-3121018123520%1025218.0200001300005000%047000.0800011010
18Daniil ChaykaMoose (WPG)D3000100511110%35418.140000000000000%01200000000000
19Marshall WarrenMoose (WPG)D7000095434100%412417.720000000000000%01000000001000
20Jiri TichacekMoose (WPG)D2000-300110000%23216.350000100000000%00100000000000
21Tristan BertucciMoose (WPG)D2000000010000%0157.800000000000000%01000000000000
22Dylan PetersonMoose (WPG)C2000000000000%010.630000000000000%00000000000000
23Ilya FedotovMoose (WPG)LW/RW19000000410000%0462.470000100000000%00200000000000
Statistiques d’équipe totales ou en moyenne3414881129-1515811033233446216024610.39%142571916.7717335085575000913511252.00%9028376000.45005898810
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
1Olivier RodrigueMoose (WPG)177620.9062.0994801333522130000170101
2Arturs SilovsMoose (WPG)54000.9092.0920101777450000217010
Statistiques d’équipe totales ou en moyenne2211620.9072.09115002404292580001917111


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
Alexander SuvorovMoose (WPG)C/LW/RW222002-11-30BLRNo159 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm650,000$65,000$0$No---------------------------
Andrew CristallMoose (WPG)LW/RW192005-02-04CANYes174 Lbs5 ft10NoNoN/ANoNo3FalseFalsePro & Farm1,500,000$150,000$0$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------
Anthony DeAngeloMoose (WPG)D291995-10-24USANo180 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm4,250,000$425,000$0$No4,250,000$--------4,250,000$--------No--------
Artem DudaMoose (WPG)D202004-04-08RUSYes187 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm825,000$82,500$0$No825,000$825,000$-------825,000$825,000$-------NoNo-------
Artem ShlaineMoose (WPG)C222002-03-07USANo185 Lbs7 ft1NoNoN/ANoNo2FalseFalsePro & Farm825,000$82,500$0$No825,000$--------825,000$--------No--------
Arttu HyryMoose (WPG)C/LW/RW232001-04-11FINYes100 Lbs4 ft0NoNoFree AgentNoNo12025-06-11FalseFalsePro & Farm795,000$79,500$0$No---------------------------
Arturs SilovsMoose (WPG)G232001-03-22LATNo203 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm787,500$78,750$0$No---------------------------
Axel Jonsson FjallbyMoose (WPG)LW/RW261998-02-10SWENo189 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm1,100,000$110,000$0$No---------------------------
Calvin ThurkaufMoose (WPG)C/LW/RW271997-06-27SUINo203 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm650,000$65,000$0$No650,000$--------650,000$--------No--------
Carl LindbomMoose (WPG)G212003-05-20SWENo185 Lbs7 ft2NoNoN/ANoNo2FalseFalsePro & Farm700,000$70,000$0$No700,000$--------700,000$--------No--------
Christian KyrouMoose (WPG)D212003-09-16CANNo178 Lbs6 ft11NoNoN/ANoNo2FalseFalsePro & Farm1,250,000$125,000$0$No1,250,000$--------1,250,000$--------No--------
Daniil ChaykaMoose (WPG)D222002-10-22RUSNo181 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$125,000$0$No---------------------------
Dylan PetersonMoose (WPG)C222002-01-08USAYes192 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm975,000$97,500$0$No975,000$--------975,000$--------No--------
Ethan CardwellMoose (WPG)LW/RW222002-08-30CANNo180 Lbs7 ft3NoNoN/ANoNo2FalseFalsePro & Farm825,000$82,500$0$No825,000$--------825,000$--------No--------
Filip RoosMoose (WPG)D251999-01-05SWENo190 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm740,250$74,025$0$No---------------------------
Ilya FedotovMoose (WPG)LW/RW212003-03-19RUSYes172 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm975,000$97,500$0$No975,000$975,000$-------975,000$975,000$-------NoNo-------
Isak PoschMoose (WPG)G222002-01-31SWEYes209 Lbs6 ft3NoNoFree AgentNoNo22025-06-11FalseFalsePro & Farm655,000$65,500$0$No655,000$--------655,000$--------No--------
Jacob QuillanMoose (WPG)C222002-02-02CANNo196 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm650,000$65,000$0$No---------------------------
Jesper WallstedtMoose (WPG)G222002-11-14SWENo214 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm1,500,000$150,000$0$No---------------------------
Jett WooMoose (WPG)D242000-07-27CANNo203 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,378,125$137,812$0$No---------------------------
Jiri KulichMoose (WPG)C202004-04-14CZENo186 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm1,500,000$150,000$0$No1,500,000$--------1,500,000$--------No--------
Jiri TichacekMoose (WPG)D212003-01-30CZENo170 Lbs5 ft9NoNoN/ANoNo2FalseFalsePro & Farm650,000$65,000$0$No650,000$--------650,000$--------No--------
Jordan FrascaMoose (WPG)C232001-07-05CANNo183 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm729,750$72,975$0$No729,750$--------729,750$--------No--------
Justin BrazeauMoose (WPG)LW/RW261998-02-02CANNo220 Lbs6 ft5NoNoN/ANoNo2FalseFalsePro & Farm650,000$65,000$0$No650,000$--------650,000$--------No--------
Luke HaymesMoose (WPG)C212003-07-28CANYes192 Lbs6 ft1NoNoFree AgentNoNo32025-06-11FalseFalsePro & Farm655,000$65,500$0$No655,000$655,000$-------655,000$655,000$-------NoNo-------
Marshall WarrenMoose (WPG)D232001-04-20USANo183 Lbs6 ft10NoNoN/ANoNo1FalseFalsePro & Farm975,000$97,500$0$No---------------------------
Max DomiMoose (WPG)C291995-03-02CANNo208 Lbs5 ft10NoNoFree AgentNoNo32025-06-09FalseFalsePro & Farm705,000$70,500$0$No705,000$705,000$-------705,000$705,000$-------NoNo-------
Max SassonMoose (WPG)C242000-09-05USANo181 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm650,000$65,000$0$No---------------------------
Michael BenningMoose (WPG)D222002-01-05CANNo175 Lbs6 ft10NoNoN/ANoNo2FalseFalsePro & Farm975,000$97,500$0$No975,000$--------975,000$--------No--------
Mitchell RussellMoose (WPG)C/LW/RW232001-03-06CANNo194 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm792,750$79,275$0$No792,750$--------792,750$--------No--------
Noah ChadwickMoose (WPG)D192005-05-10CANYes201 Lbs6 ft4NoNoN/ANoNo3FalseFalsePro & Farm650,000$65,000$0$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Oliver Kylington (contrat à 1 volet)Moose (WPG)D271997-05-19SWENo183 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm650,000$650,000$0$No650,000$--------650,000$--------No--------
Olivier RodrigueMoose (WPG)G242000-07-06CANNo159 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm1,378,125$137,812$0$No---------------------------
Peyton KrebsMoose (WPG)C232001-01-26CANNo186 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm1,350,000$135,000$0$No1,350,000$--------1,350,000$--------No--------
Strauss MannMoose (WPG)G261998-08-18USANo174 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm682,500$68,250$0$No---------------------------
Theo RochetteMoose (WPG)C222002-02-20SUINo161 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm650,000$65,000$0$No---------------------------
Tristan BertucciMoose (WPG)D192005-07-12CANYes179 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm975,000$97,500$0$No975,000$975,000$-------975,000$975,000$-------NoNo-------
Tyce ThompsonMoose (WPG)C251999-07-12CANNo175 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm866,250$86,625$0$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3822.95184 Lbs6 ft21.79993,822$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mitchell RussellPeyton KrebsAxel Jonsson Fjallby28014
2Arttu HyryJiri KulichAndrew Cristall28014
3Max DomiJustin BrazeauMax Sasson25023
4Axel Jonsson FjallbyJustin BrazeauPeyton Krebs19032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Oliver KylingtonAnthony DeAngelo34023
2Filip RoosJett Woo33032
3Marshall WarrenDaniil Chayka33032
4Oliver KylingtonAnthony DeAngelo0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Justin BrazeauPeyton KrebsAxel Jonsson Fjallby50014
2Max DomiJiri KulichAndrew Cristall50014
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Oliver KylingtonAnthony DeAngelo50014
2Filip RoosJett Woo50014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Justin BrazeauPeyton Krebs50041
2Axel Jonsson FjallbyJiri Kulich50041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jett WooAnthony DeAngelo50050
2Oliver KylingtonFilip Roos50050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Axel Jonsson Fjallby50041Oliver KylingtonAnthony DeAngelo50050
2Peyton Krebs50041Daniil ChaykaJett Woo50050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Justin BrazeauPeyton Krebs50023
2Axel Jonsson FjallbyJiri Kulich50023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Oliver KylingtonAnthony DeAngelo50023
2Marshall WarrenJett Woo50023
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Justin BrazeauPeyton KrebsAxel Jonsson FjallbyOliver KylingtonAnthony DeAngelo
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Justin BrazeauPeyton KrebsAxel Jonsson FjallbyOliver KylingtonAnthony DeAngelo
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Peyton Krebs, Jiri Kulich, Axel Jonsson FjallbyPeyton Krebs, Axel Jonsson FjallbyPeyton Krebs
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Oliver Kylington, Anthony DeAngelo, Jett WooAnthony DeAngeloAnthony DeAngelo, Jett Woo
Tirs de pénalité
Andrew Cristall, Peyton Krebs, Axel Jonsson Fjallby, Jiri Kulich, Justin Brazeau
Gardien
#1 : Olivier Rodrigue, #2 : Arturs Silovs


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
1Express734000001113-23120000046-24220000077060.42911203101101817312411515518210143563111915213.33%8362.50%020940451.73%14928153.02%11121751.15%369156335194447235
2Rams7430000023176321000001055422000001312180.57123386100101817321811515518210180549012937718.92%9277.78%020940451.73%14928153.02%11121751.15%369156335194447235
3Whalers54100000141042110000056-13300000094580.8001423370110181731201151551821010632378424833.33%6183.33%020940451.73%14928153.02%11121751.15%369156335194447235
Total191180000048408844000001917211740000029236220.579488112902101817346211515518210429142158332761722.37%23673.91%020940451.73%14928153.02%11121751.15%369156335194447235
_Since Last GM Reset191180000048408844000001917211740000029236220.579488112902101817346211515518210429142158332761722.37%23673.91%020940451.73%14928153.02%11121751.15%369156335194447235
_Vs Conference191180000048408844000001917211740000029236220.579488112902101817346211515518210429142158332761722.37%23673.91%020940451.73%14928153.02%11121751.15%369156335194447235

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1922L2488112946242914215833202
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
1911800004840
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
84400001917
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
117400002923
Derniers 10 matchs
WLOTWOTL SOWSOL
550000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
761722.37%23673.91%0
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
115155182101018173
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
20940451.73%14928153.02%11121751.15%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
369156335194447235


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
14Moose1Rams3LSommaire du match
312Moose1Rams2LXSommaire du match
520Rams1Moose4WSommaire du match
728Rams1Moose4WSommaire du match
936Moose3Rams1WSommaire du match
1144Rams3Moose2LXSommaire du match
1352Moose8Rams6WSommaire du match
1558Moose1Whalers0WXSommaire du match
1762Moose5Whalers2WSommaire du match
1966Whalers1Moose2WSommaire du match
2170Whalers5Moose3LSommaire du match
2374Moose3Whalers2WSommaire du match
2985Moose1Express2LSommaire du match
3187Moose3Express2WXSommaire du match
3389Express0Moose2WSommaire du match
3591Express3Moose1LSommaire du match
3793Moose3Express2WXSommaire du match
3995Express3Moose1LSommaire du match
4197Moose0Express1LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité25005500
Prix des billets3512
Assistance19,69444,000
Assistance PCT98.47%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
33 7962 - 99.52% 182,594$1,460,748$8000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
0$ 3,711,524$ 3,711,524$ 600,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 36 0

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




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