Connexion

Moose
GP: 11 | W: 5 | L: 4 | OTL: 2 | P: 12
GF: 42 | GA: 46 | PP%: 18.92% | PK%: 68.85%
DG: Eric Latulippe | Morale : 50 | Moyenne d’équipe : 69
Prochain matchs #175 vs Texas Stars
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Centre de jeu
Moose
5-4-2, 12pts
6
FINAL
2 Admirals
0-7-2, 2pts
Team Stats
OTL1StreakL4
2-2-1Home Record0-5-0
3-2-1Away Record0-2-2
5-3-2Last 10 Games0-7-2
3.82Buts par match 2.78
4.18Buts contre par match 5.22
18.92%Pourcentage en avantage numérique17.86%
68.85%Pourcentage en désavantage numérique75.56%
Thunderbirds
7-2-1, 15pts
5
FINAL
4 Moose
5-4-2, 12pts
Team Stats
W2StreakOTL1
3-1-1Home Record2-2-1
4-1-0Away Record3-2-1
7-2-1Last 10 Games5-3-2
4.10Buts par match 3.82
3.20Buts contre par match 4.18
20.00%Pourcentage en avantage numérique18.92%
96.67%Pourcentage en désavantage numérique68.85%
Moose
5-4-2, 12pts
2022-08-03
Texas Stars
4-4-1, 9pts
Statistiques d’équipe
OTL1SéquenceW1
2-2-1Fiche domicile2-3-0
3-2-1Fiche visiteur2-1-1
5-3-210 derniers matchs4-4-1
3.82Buts par match 3.44
4.18Buts contre par match 3.89
18.92%Pourcentage en avantage numérique13.79%
68.85%Pourcentage en désavantage numérique74.07%
Admirals
0-7-2, 2pts
2022-08-04
Moose
5-4-2, 12pts
Statistiques d’équipe
L4SéquenceOTL1
0-5-0Fiche domicile2-2-1
0-2-2Fiche visiteur3-2-1
0-7-210 derniers matchs5-3-2
2.78Buts par match 3.82
5.22Buts contre par match 4.18
17.86%Pourcentage en avantage numérique18.92%
75.56%Pourcentage en désavantage numérique68.85%
Roadrunners
3-5-0, 6pts
2022-08-07
Moose
5-4-2, 12pts
Statistiques d’équipe
L2SéquenceOTL1
1-4-0Fiche domicile2-2-1
2-1-0Fiche visiteur3-2-1
3-5-010 derniers matchs5-3-2
3.50Buts par match 3.82
4.13Buts contre par match 4.18
9.09%Pourcentage en avantage numérique18.92%
74.19%Pourcentage en désavantage numérique68.85%
Meneurs d'équipe
Buts
Derek Stepan
1
Passes
Derek Stepan
1
Points
Derek Stepan
2
Plus/Moins
Derek Stepan
1
Victoires
Matthew Murray
3
Pourcentage d’arrêts
Matthew Murray
0.915

Statistiques d’équipe
Buts pour
42
3.82 GFG
Tirs pour
380
34.55 Avg
Pourcentage en avantage numérique
18.9%
7 GF
Début de zone offensive
38.9%
Buts contre
46
4.18 GAA
Tirs contre
410
37.27 Avg
Pourcentage en désavantage numérique
68.9%
19 GA
Début de la zone défensive
43.0%
Information d’équipe

Directeur généralEric Latulippe
EntraîneurBenoit Groulx
DivisionCENTRALE
ConférenceOUEST
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Information formation

Équipe Pro28
Équipe Mineure21
Limite contact 49 / 55
Espoirs34


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
1Alex Newhook0XX100.005936947668858673757267637462650507202121,491,667$
2A.J. Greer0X100.00805371668581826568666465696668050720252937,500$
3Patrick Brown0XX100.00813992648079756289636275626970050710301700,000$
4Phillip Di Giuseppe0XX100.00823984657391726656675963657071050700283937,500$
5Ryan Dzingel0X100.006346787372827968746269567273710507003011,546,000$
6Austin Rueschhoff0X100.00908565559978845753555864566567050690251700,000$
7Lukas Vejdemo0X100.00673893647776756379626465626768050690262895,000$
8Mathieu Olivier0X100.00818456608276826162606166586567050690252980,000$
9Kyle Clifford0X100.00798673608374766153606258567873050680311875,000$
10T.J. Tynan0X100.00593491646081846379645863667072050670303910,000$
11Anthony Richard0XX100.006038826365899163576162566366680506702531,067,000$
12Jansen Harkins0X100.00583884607472865869575956616567050650252804,000$
13Kevin Bahl0X100.00877483599882875830705969516264050720221902,500$
14Derrick Pouliot0X100.00653985697483776630745760536970050700282895,000$
15Sami Niku0X100.006237876873817566307358595066680506902511,003,000$
16Paul LaDue0X100.00794092598381795830595766506972050680302768,000$
17Michael Vukojevic0X100.00764278578563815630595358456264050650212925,000$
18Noel Hoefenmayer0X100.00643591597374805830575560476362050640232815,000$
Rayé
1Jakub Lauko0XX100.005934715968848059636156556062640506402241,286,000$
2Cole Fonstad0XX100.00633592566381735761585953566264050630221800,000$
3Justin Almeida0XX100.00563593556571745556555753566362050610231925,000$
4Ethan Keppen0X100.00643979518371645356515054526163050600211800,000$
5Joseph Cecconi0X100.00733574568168825430565358466567050640253931,000$
6Ian McCoshen0X100.00784370548764815330565157456769050640271901,000$
MOYENNE D’ÉQUIPE100.0070468261777879615462596157666705067
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
1Dan Vladar100.0083827986828183828183826473050820254937,500$
2Matthew Murray100.00756667767473757473757464710507402421,375,000$
Rayé
1Magnus Hellberg100.0072717294717072717072717085050760311795,000$
2Evan Fitzpatrick100.00746465857372747372747364710507402411,093,750$
MOYENNE D’ÉQUIPE100.007671718575747675747675667505077
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Benoit Groulx64687372837868CAN5440$


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
1Alex NewhookMoose (WIN)C/LW11951492012046102419.57%219017.323148300002152055.17%2900001.4701000120
2Ryan DzingelMoose (WIN)C1158139001203042816.67%116815.31213430000000054.95%22200001.5401000000
3Kevin BahlMoose (WIN)D110121251403710214110.00%1925122.88033931000042000.00%000000.9500000100
4Sami NikuMoose (WIN)D1129110607131721511.76%921219.3111283000007020.00%000001.0400000000
5Austin RueschhoffMoose (WIN)RW11551071603542461720.83%216915.43022530000000063.64%1100001.1800000202
6Phillip Di GiuseppeMoose (WIN)LW/RW11369118034223093210.00%321419.521017320002380050.00%1200000.8411000010
7Derrick PouliotMoose (WIN)D11257612026191891411.11%2223221.17022830000141000.00%000000.6000000101
8T.J. TynanMoose (WIN)C11336300638114627.27%514313.03000000001470053.88%21900000.8401000101
9Anthony RichardMoose (WIN)C/LW11246100412249108.33%016515.08000327000000041.18%1700000.7211000000
10Mathieu OlivierMoose (WIN)RW11123-4802218253194.00%116715.19000010001361058.33%1200000.3600000000
11Patrick BrownMoose (WIN)C/RW4123-120714751314.29%18020.080114150000120062.50%10400000.7501000010
12Noel HoefenmayerMoose (WIN)D1121300063126716.67%1620618.7700000000042000.00%000000.2900000000
13Jansen HarkinsMoose (WIN)C1112332057106710.00%1958.7200000000001044.44%900000.6300000010
14Derek StepanJetsC31121002392411.11%35117.1200000000081043.14%5100000.7800000000
15Lukas VejdemoMoose (WIN)C11112-400118412252.44%512911.7800000000000056.13%15500000.3100000000
16Paul LaDueMoose (WIN)D11112-3180251211259.09%2220919.0200000000040000.00%000000.1900000000
17Cole FonstadMoose (WIN)C/LW8022420531000.00%3708.8500000000000025.00%400000.5700000000
18A.J. GreerMoose (WIN)LW1011020215260.00%01919.2301132000050050.00%200001.0400000000
19Kyle CliffordMoose (WIN)LW11101-5601514164106.25%012311.2600000000000050.00%1000000.1600000000
20Jakub LaukoMoose (WIN)C/LW2000-100112020.00%0178.70000000000000100.00%100000.0000000000
21Michael VukojevicMoose (WIN)D4000220302020.00%27518.9200001500003000.00%000000.0000000000
Statistiques d’équipe totales ou en moyenne18740701103311002452523628925711.05%117299616.02712195927900073415254.66%85800000.7326000654
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
1Matthew MurrayMoose (WIN)33000.9153.001802091060000.000033000
2Evan FitzpatrickMoose (WIN)32100.8963.261840010960000.833630000
3Dan VladarMoose (WIN)30110.8436.611270014890000.000027000
4Magnus HellbergMoose (WIN)40210.8914.4817400131190000.000031000
Statistiques d’équipe totales ou en moyenne135420.8884.1466620464100000.83361111000


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 Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire restantSalaire moyenPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
A.J. GreerMoose (WIN)LW251996-12-14No210 Lbs6 ft3NoNoNo2Pro & Farm937,500$937,500$937,500$0$0$No937,500$Lien
Alex NewhookMoose (WIN)C/LW212001-01-28No190 Lbs5 ft10NoNoNo2Pro & Farm1,491,667$1,491,667$1,491,667$0$0$No1,491,667$Lien
Anthony RichardMoose (WIN)C/LW251996-12-20No163 Lbs5 ft10NoNoNo3Pro & Farm1,067,000$1,067,000$650,000$0$0$No1,067,000$1,067,000$Lien
Austin RueschhoffMoose (WIN)RW251997-09-07No230 Lbs6 ft7NoNoNo1Pro & Farm700,000$700,000$700,000$0$0$NoLien
Cole FonstadMoose (WIN)C/LW222000-04-24No165 Lbs5 ft10NoNoNo1Pro & Farm800,000$800,000$700,000$0$0$NoLien
Dan VladarMoose (WIN)G251997-08-20No185 Lbs6 ft5NoNoNo4Pro & Farm937,500$937,500$932,167$0$0$No937,500$937,500$937,500$Lien
Derrick PouliotMoose (WIN)D281994-01-16No196 Lbs6 ft0NoNoNo2Pro & Farm895,000$895,000$895,000$0$0$No895,000$Lien
Ethan KeppenMoose (WIN)LW212001-03-20No212 Lbs6 ft2NoNoNo1Pro & Farm800,000$800,000$700,000$0$0$NoLien
Evan FitzpatrickMoose (WIN)G241998-01-28No206 Lbs6 ft3NoNoNo1Pro & Farm1,093,750$1,093,750$750,000$0$0$NoLien
Ian McCoshenMoose (WIN)D271995-08-05No218 Lbs6 ft3NoNoNo1Pro & Farm901,000$901,000$0$0$NoLien
Jakub LaukoMoose (WIN)C/LW222000-03-28No169 Lbs6 ft0NoNoNo4Pro & Farm1,286,000$1,286,000$786,667$0$0$No1,286,000$1,286,000$1,286,000$Lien
Jansen HarkinsMoose (WIN)C251997-05-23No182 Lbs6 ft1NoNoNo2Pro & Farm804,000$804,000$650,000$0$0$No804,000$Lien
Joseph CecconiMoose (WIN)D251997-05-23No210 Lbs6 ft2NoNoNo3Pro & Farm931,000$931,000$650,000$0$0$No931,000$931,000$Lien
Justin AlmeidaMoose (WIN)C/LW231999-02-06No165 Lbs5 ft11NoNoNo1Pro & Farm925,000$925,000$925,000$0$0$NoLien
Kevin BahlMoose (WIN)D222000-06-27No230 Lbs6 ft6NoNoNo1Pro & Farm902,500$902,500$902,500$0$0$NoLien
Kyle CliffordMoose (WIN)LW311991-01-13No214 Lbs6 ft2NoNoNo1Pro & Farm875,000$875,000$875,000$0$0$NoLien
Lukas VejdemoMoose (WIN)C261996-01-25No198 Lbs6 ft1NoNoNo2Pro & Farm895,000$895,000$650,000$0$0$No895,000$Lien
Magnus HellbergMoose (WIN)G311991-04-04No209 Lbs6 ft6NoNoNo1Pro & Farm795,000$795,000$795,000$0$0$NoLien
Mathieu OlivierMoose (WIN)RW251997-02-11No210 Lbs6 ft2NoNoNo2Pro & Farm980,000$980,000$9,800,000$0$0$No980,000$Lien
Matthew MurrayMoose (WIN)G241998-02-02No194 Lbs6 ft1NoNoNo2Pro & Farm1,375,000$1,375,000$1,375,000$0$0$No1,375,000$Lien
Michael VukojevicMoose (WIN)D212001-06-08No207 Lbs6 ft3NoNoNo2Pro & Farm925,000$925,000$925,000$0$0$No925,000$Lien
Noel HoefenmayerMoose (WIN)D231999-01-06No191 Lbs6 ft0NoNoNo2Pro & Farm815,000$815,000$815,000$0$0$No815,000$Lien
Patrick BrownMoose (WIN)C/RW301992-05-29No210 Lbs6 ft1NoNoNo1Pro & Farm700,000$700,000$700,000$0$0$NoLien
Paul LaDueMoose (WIN)D301992-09-06No200 Lbs6 ft3NoNoNo2Pro & Farm768,000$768,000$700,000$0$0$No768,000$Lien
Phillip Di GiuseppeMoose (WIN)LW/RW281993-10-09No193 Lbs6 ft0NoNoNo3Pro & Farm937,500$937,500$650,000$0$0$No937,500$937,500$Lien
Ryan DzingelMoose (WIN)C301992-03-09No190 Lbs6 ft0NoNoNo1Pro & Farm1,546,000$1,546,000$525,000$0$0$NoLien
Sami NikuMoose (WIN)D251996-10-10No176 Lbs6 ft1NoNoNo1Pro & Farm1,003,000$1,003,000$525,000$0$0$NoLien
T.J. TynanMoose (WIN)C301992-02-25No160 Lbs5 ft8NoNoNo3Pro & Farm910,000$910,000$650,000$0$0$No910,000$910,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2825.50196 Lbs6 ft11.86964,158$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1A.J. GreerPatrick BrownPhillip Di Giuseppe28122
2Alex NewhookRyan DzingelAustin Rueschhoff27122
3Anthony RichardLukas VejdemoMathieu Olivier25122
4Kyle CliffordT.J. TynanJansen Harkins20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kevin BahlNoel Hoefenmayer35122
2Michael VukojevicDerrick Pouliot33122
3Paul LaDueSami Niku32122
4Michael VukojevicKevin Bahl0122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1A.J. GreerPatrick BrownPhillip Di Giuseppe50122
2Alex NewhookRyan DzingelAustin Rueschhoff50104
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sami NikuDerrick Pouliot50122
2Michael VukojevicKevin Bahl50113
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Patrick BrownA.J. Greer50131
2T.J. TynanPhillip Di Giuseppe50131
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kevin BahlPaul LaDue50131
2Derrick PouliotNoel Hoefenmayer50131
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Patrick Brown50140Kevin BahlPaul LaDue50140
2T.J. Tynan50140Derrick PouliotNoel Hoefenmayer50140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Patrick BrownAustin Rueschhoff50023
2Alex NewhookPhillip Di Giuseppe50023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sami NikuDerrick Pouliot50023
2Noel HoefenmayerKevin Bahl50023
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Alex NewhookRyan DzingelPhillip Di GiuseppeSami NikuPaul LaDue
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Phillip Di GiuseppeLukas VejdemoMathieu OlivierKevin BahlPaul LaDue
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Alex Newhook, Patrick Brown, Ryan DzingelLukas Vejdemo, Anthony RichardAlex Newhook
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Kevin Bahl, Derrick Pouliot, Sami NikuPaul LaDueMichael Vukojevic, Sami Niku
Tirs de pénalité
Alex Newhook, Ryan Dzingel, Phillip Di Giuseppe, A.J. Greer, Patrick Brown
Gardien
#1 : Dan Vladar, #2 : Matthew Murray
Lignes d’attaque personnalisées en prolongation
Alex Newhook, Phillip Di Giuseppe, Patrick Brown, Austin Rueschhoff, Lukas Vejdemo, Mathieu Olivier, Mathieu Olivier, Ryan Dzingel, A.J. Greer, T.J. Tynan, Anthony Richard
Lignes de défense personnalisées en prolongation
Kevin Bahl, Sami Niku, Derrick Pouliot, Noel Hoefenmayer, Paul LaDue


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
1Admirals11000000624000000000001100000062421.0006111700191111243135118122112992188225.00%110.00%021639055.38%23743154.99%8918149.17%2561752688514268
2Eagles20200000614-81010000039-61010000035-200.000611170019111126513511812211872630537228.57%15846.67%021639055.38%23743154.99%8918149.17%2561752688514268
3IceHogs21100000770110000004311010000034-120.500714210019111126413511812211733126596116.67%13284.62%021639055.38%23743154.99%8918149.17%2561752688514268
4Iowa Wild2010010069-31010000035-21000010034-110.250610160019111125713511812211861922386116.67%11281.82%021639055.38%23743154.99%8918149.17%2561752688514268
5Roadrunners11000000422000000000001100000042221.0004812001911112341351181221136121219200.00%6266.67%021639055.38%23743154.99%8918149.17%2561752688514268
6Texas Stars10000010431100000104310000000000021.0004480019111124413511812211287424100.00%20100.00%021639055.38%23743154.99%8918149.17%2561752688514268
7Thunderbirds210001009901000010045-11100000054130.750915240019111127313511812211712726527114.29%13469.23%021639055.38%23743154.99%8918149.17%2561752688514268
Total1144002104246-4512001101825-76320010024213120.54542731150019111123801351181221141013112226337718.92%611968.85%021639055.38%23743154.99%8918149.17%2561752688514268
_Since Last GM Reset1144002104246-4512001101825-76320010024213120.54542731150019111123801351181221141013112226337718.92%611968.85%021639055.38%23743154.99%8918149.17%2561752688514268
_Vs Conference1144002104246-4512001101825-76320010024213120.54542731150019111123801351181221141013112226337718.92%611968.85%021639055.38%23743154.99%8918149.17%2561752688514268
_Vs Division1144002104246-4512001101825-76320010024213120.54542731150019111123801351181221141013112226337718.92%611968.85%021639055.38%23743154.99%8918149.17%2561752688514268

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1112OTL1427311538041013112226300
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
114402104246
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
51201101825
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
63201002421
Derniers 10 matchs
WLOTWOTL SOWSOL
530200
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
37718.92%611968.85%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
135118122111911112
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
21639055.38%23743154.99%8918149.17%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2561752688514268


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
1 - 2022-07-1710Moose3IceHogs4ALSommaire du match
2 - 2022-07-1819Eagles9Moose3BLSommaire du match
4 - 2022-07-2042IceHogs3Moose4BWSommaire du match
6 - 2022-07-2259Moose5Thunderbirds4AWSommaire du match
8 - 2022-07-2474Moose4Roadrunners2AWSommaire du match
9 - 2022-07-2579Moose3Iowa Wild4ALXSommaire du match
10 - 2022-07-2696Iowa Wild5Moose3BLSommaire du match
11 - 2022-07-27113Moose3Eagles5ALSommaire du match
12 - 2022-07-28126Texas Stars3Moose4BWXXSommaire du match
14 - 2022-07-30137Moose6Admirals2AWSommaire du match
16 - 2022-08-01155Thunderbirds5Moose4BLXSommaire du match
18 - 2022-08-03175Moose-Texas Stars-
19 - 2022-08-04186Admirals-Moose-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
22 - 2022-08-07217Roadrunners-Moose-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
36 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,699,642$ 3,065,551$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 8 0$ 0$




Moose Leaders statistiques (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


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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 (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