Connexion

Moose
GP: 19 | W: 8 | L: 7 | OTL: 4 | P: 20
GF: 61 | GA: 62 | PP%: 19.05% | PK%: 75.95%
DG: Eric Latulippe | Morale : 50 | Moyenne d’équipe : 68
Prochain matchs #328 vs Iowa Wild
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Centre de jeu
Moose
8-7-4, 20pts
2
FINAL
3 Iowa Wild
12-6-2, 26pts
Team Stats
W1StreakW3
4-3-3Home Record8-0-1
4-4-1Away Record4-6-1
5-4-1Last 10 Games6-2-2
3.21Buts par match 3.40
3.26Buts contre par match 2.70
19.05%Pourcentage en avantage numérique21.18%
75.95%Pourcentage en désavantage numérique81.82%
Eagles
11-8-1, 23pts
1
FINAL
2 Moose
8-7-4, 20pts
Team Stats
L1StreakW1
5-4-0Home Record4-3-3
6-4-1Away Record4-4-1
6-3-1Last 10 Games5-4-1
3.85Buts par match 3.21
3.95Buts contre par match 3.26
18.42%Pourcentage en avantage numérique19.05%
73.91%Pourcentage en désavantage numérique75.95%
Iowa Wild
12-6-2, 26pts
2022-12-02
Moose
8-7-4, 20pts
Statistiques d’équipe
W3SéquenceW1
8-0-1Fiche domicile4-3-3
4-6-1Fiche visiteur4-4-1
6-2-210 derniers matchs5-4-1
3.40Buts par match 3.21
2.70Buts contre par match 3.26
21.18%Pourcentage en avantage numérique19.05%
81.82%Pourcentage en désavantage numérique75.95%
Moose
8-7-4, 20pts
2022-12-04
Bears
10-9-1, 21pts
Statistiques d’équipe
W1SéquenceL2
4-3-3Fiche domicile5-4-0
4-4-1Fiche visiteur5-5-1
5-4-110 derniers matchs5-5-0
3.21Buts par match 3.40
3.26Buts contre par match 3.30
19.05%Pourcentage en avantage numérique21.92%
75.95%Pourcentage en désavantage numérique76.92%
Moose
8-7-4, 20pts
2022-12-05
Gulls
12-6-0, 24pts
Statistiques d’équipe
W1SéquenceL1
4-3-3Fiche domicile6-3-0
4-4-1Fiche visiteur6-3-0
5-4-110 derniers matchs7-3-0
3.21Buts par match 3.89
3.26Buts contre par match 3.22
19.05%Pourcentage en avantage numérique31.37%
75.95%Pourcentage en désavantage numérique80.28%
Meneurs d'équipe
Buts
Kevin Bahl
2
Passes
Kevin Bahl
4
Points
Kevin Bahl
6
Plus/Moins
Kevin Bahl
-3
Victoires
Dan Vladar
5
Pourcentage d’arrêts
Dan Vladar
0.92

Statistiques d’équipe
Buts pour
61
3.21 GFG
Tirs pour
677
35.63 Avg
Pourcentage en avantage numérique
19.0%
12 GF
Début de zone offensive
40.3%
Buts contre
62
3.26 GAA
Tirs contre
695
36.58 Avg
Pourcentage en désavantage numérique
75.9%
19 GA
Début de la zone défensive
43.7%
Information d’équipe

Directeur généralEric Latulippe
EntraîneurBenoit Groulx
DivisionCENTRALE
ConférenceOUEST
CapitainePhillip Di Giuseppe
Assistant #1Alex Newhook
Assistant #2Anthony Richard


Informations de l’aréna

Capacité3,000
Assistance2,432
Billets de saison300


Information formation

Équipe Pro26
Équipe Mineure22
Limite contact 48 / 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 Newhook (A)0XX100.005936947668858673757267637462650507202121,491,667$
2Phillip Di Giuseppe (C)0XX100.00823984657391726656675963657071050700293937,500$
3Austin Rueschhoff0X100.00908565559978845753555864566567050690251700,000$
4Mathieu Olivier0X100.00818456608276826162606166586567050690252980,000$
5Lukas Vejdemo0X100.00673893647776756379626465626768050680262895,000$
6Kyle Clifford0X100.00798673608374766153606258567873050680311875,000$
7T.J. Tynan0X100.00593491646081846379645863667072050670303910,000$
8Anthony Richard (A)0XX100.006038826365899163576162566366680506702531,067,000$
9Jakub Lauko0XX100.005934715968848059636156556062640506402241,286,000$
10Jansen Harkins0X100.00583884607472865869575956616567050640252804,000$
11Cole Fonstad0XX100.00633592566381735761585953566264050620221800,000$
12Justin Almeida0XX100.00563593556571745556555753566362050610231925,000$
13Dean Kukan46X100.006636896578868162307159635269710507002941,261,000$
14Sami Niku0X100.006237876873817566307358595066680506902611,003,000$
15Paul LaDue0X100.00794092598381795830595766506972050680302768,000$
16Michael Vukojevic0X100.00764278578563815630595358456264050650212925,000$
17Joseph Cecconi0X100.00733574568168825430565358466567050640253931,000$
18Noel Hoefenmayer0X100.00643591597374805830575560476362050640232815,000$
Rayé
1Calvin Thurkauf0XX100.00673593628177785966615856596763050660251750,000$
2Jonathon Martin0X100.00754264568377785558565457536769050650271750,000$
3Ethan Keppen0X100.00643979518371645356515054526163050600211800,000$
4Ian McCoshen0X100.00784370548764815330565157456769050640271901,000$
MOYENNE D’ÉQUIPE100.0069448260777779605261585956666705066
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$
2Magnus Hellberg100.0072717294717072717072717085050750311795,000$
Rayé
1Evan Fitzpatrick100.00746465857372747372747364710507402411,093,750$
2Matthew Murray100.00756667767473757473757464710507402421,375,000$
MOYENNE D’ÉQUIPE100.007671718575747675747675667505076
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/LW181372066025298345213.27%637821.0231417531013512148.02%17700011.0601000210
2Dean KukanMoose (WIN)D19216181010021274813274.17%3242922.601562257000163100.00%000000.8400000011
3Anthony RichardMoose (WIN)C/LW1971017-320121260183411.67%532917.3514510530000100051.72%2900001.0301000030
4Lukas VejdemoMoose (WIN)C196915-20054656143710.71%131416.5602210510001121052.05%48800000.9501000130
5Mathieu OlivierMoose (WIN)RW1985137260662963145412.70%835418.6732514560110480042.86%2100000.7301000110
6Sami NikuMoose (WIN)D1921113-36014253912165.13%2340421.261122052000135000.00%000000.6400000001
7Paul LaDueMoose (WIN)D1921012318040141851711.11%2636919.44123622000155000.00%000000.6500000002
8Kyle CliffordMoose (WIN)LW195611840231732133215.63%325413.3900026000002046.15%2600000.8600000003
9T.J. TynanMoose (WIN)C193690209675115415.88%634518.210112220002651054.94%48600000.5201000000
10Phillip Di GiuseppeMoose (WIN)LW/RW18437-512045326120436.56%536020.011126410001381152.17%2300000.3900000200
11Jansen HarkinsMoose (WIN)C193478003412351913.04%126814.14000000001200046.78%34200000.5200000000
12Austin RueschhoffMoose (WIN)RW17156840106017258204.00%227416.14011446000070031.58%1900000.4411200002
13Kevin BahlJetsD11246-32354410222109.09%1524021.821121130000028000.00%000000.5000100001
14Jakub LaukoMoose (WIN)C/LW19134-1801422217134.76%41879.8600000000000055.32%9400000.4300000000
15Noel HoefenmayerMoose (WIN)D1612366018473614.29%917911.210000100009000.00%000000.3300000000
16Joseph CecconiMoose (WIN)D110223801713210.00%91029.300000000005000.00%000000.3900000000
17Michael VukojevicMoose (WIN)D14022212035912270.00%820814.88011722000016000.00%000000.1900000000
18Justin AlmeidaMoose (WIN)C/LW12101-10021085512.50%3957.9500000000030025.00%800000.2100000000
19Cole FonstadMoose (WIN)C/LW16011-10091014260.00%21288.0600000000000037.63%9300000.1600000000
20Ian McCoshenMoose (WIN)D5000-2601150020.00%37515.130000000000000.00%000000.0000000000
21Ethan KeppenMoose (WIN)LW1000000010000.00%055.770000000000000.00%000000.0000000000
Statistiques d’équipe totales ou en moyenne3296110616740189154504516611944429.23%171530616.13122234131519112114738250.33%180600010.63163006910
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
1Dan VladarMoose (WIN)105230.9202.9660900303740000.6676109210
2Magnus HellbergMoose (WIN)62400.9093.1835800192080000.000068000
3Matthew MurrayMoose (WIN)31110.8944.0018000121130000.000032000
Statistiques d’équipe totales ou en moyenne198740.9123.19114800616950000.66761919210


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
Alex NewhookMoose (WIN)C/LW212001-01-28No190 Lbs5 ft10NoNoNo2Pro & Farm1,491,667$1,146,819$1,491,667$0$0$No1,491,667$Lien
Anthony RichardMoose (WIN)C/LW251996-12-20No163 Lbs5 ft10NoNoNo3Pro & Farm1,067,000$820,327$650,000$0$0$No1,067,000$1,067,000$Lien
Austin RueschhoffMoose (WIN)RW251997-09-07No230 Lbs6 ft7NoNoNo1Pro & Farm700,000$538,172$700,000$0$0$NoLien
Calvin ThurkaufMoose (WIN)C/LW251997-06-27No204 Lbs6 ft2NoNoNo1Pro & Farm750,000$576,612$750,000$0$0$NoLien
Cole FonstadMoose (WIN)C/LW222000-04-24No165 Lbs5 ft10NoNoNo1Pro & Farm800,000$615,053$700,000$0$0$NoLien
Dan VladarMoose (WIN)G251997-08-20No185 Lbs6 ft5NoNoNo4Pro & Farm937,500$720,766$932,167$0$0$No937,500$937,500$937,500$Lien
Dean KukanMoose (WIN)D291993-07-08No190 Lbs6 ft2NoNoNo4Pro & Farm1,261,000$969,478$767,000$0$0$No1,261,000$1,261,000$1,261,000$Lien
Ethan KeppenMoose (WIN)LW212001-03-20No212 Lbs6 ft2NoNoNo1Pro & Farm800,000$615,053$700,000$0$0$NoLien
Evan FitzpatrickMoose (WIN)G241998-01-28No206 Lbs6 ft3NoNoNo1Pro & Farm1,093,750$840,893$750,000$0$0$NoLien
Ian McCoshenMoose (WIN)D271995-08-05No218 Lbs6 ft3NoNoNo1Pro & Farm901,000$692,704$0$0$NoLien
Jakub LaukoMoose (WIN)C/LW222000-03-28No169 Lbs6 ft0NoNoNo4Pro & Farm1,286,000$988,698$786,667$0$0$No1,286,000$1,286,000$1,286,000$Lien
Jansen HarkinsMoose (WIN)C251997-05-23No182 Lbs6 ft1NoNoNo2Pro & Farm804,000$618,129$650,000$0$0$No804,000$Lien
Jonathon MartinMoose (WIN)RW271995-08-23No215 Lbs6 ft2NoNoNo1Pro & Farm750,000$576,612$750,000$0$0$NoLien
Joseph CecconiMoose (WIN)D251997-05-23No210 Lbs6 ft2NoNoNo3Pro & Farm931,000$715,768$650,000$0$0$No931,000$931,000$Lien
Justin AlmeidaMoose (WIN)C/LW231999-02-06No165 Lbs5 ft11NoNoNo1Pro & Farm925,000$711,155$925,000$0$0$NoLien
Kyle CliffordMoose (WIN)LW311991-01-13No214 Lbs6 ft2NoNoNo1Pro & Farm875,000$672,715$875,000$0$0$NoLien
Lukas VejdemoMoose (WIN)C261996-01-25No198 Lbs6 ft1NoNoNo2Pro & Farm895,000$688,091$650,000$0$0$No895,000$Lien
Magnus HellbergMoose (WIN)G311991-04-04No209 Lbs6 ft6NoNoNo1Pro & Farm795,000$611,209$795,000$0$0$NoLien
Mathieu OlivierMoose (WIN)RW251997-02-11No210 Lbs6 ft2NoNoNo2Pro & Farm980,000$753,440$9,800,000$0$0$No980,000$Lien
Matthew MurrayMoose (WIN)G241998-02-02No194 Lbs6 ft1NoNoNo2Pro & Farm1,375,000$1,057,123$1,375,000$0$0$No1,375,000$Lien
Michael VukojevicMoose (WIN)D212001-06-08No207 Lbs6 ft3NoNoNo2Pro & Farm925,000$711,155$925,000$0$0$No925,000$Lien
Noel HoefenmayerMoose (WIN)D231999-01-06No191 Lbs6 ft0NoNoNo2Pro & Farm815,000$626,586$815,000$0$0$No815,000$Lien
Paul LaDueMoose (WIN)D301992-09-06No200 Lbs6 ft3NoNoNo2Pro & Farm768,000$590,451$700,000$0$0$No768,000$Lien
Phillip Di GiuseppeMoose (WIN)LW/RW291993-10-09No193 Lbs6 ft0NoNoNo3Pro & Farm937,500$720,766$650,000$0$0$No937,500$937,500$Lien
Sami NikuMoose (WIN)D261996-10-10No176 Lbs6 ft1NoNoNo1Pro & Farm1,003,000$771,123$525,000$0$0$NoLien
T.J. TynanMoose (WIN)C301992-02-25No160 Lbs5 ft8NoNoNo3Pro & Farm910,000$699,623$650,000$0$0$No910,000$910,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2625.46194 Lbs6 ft11.96952,939$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anthony RichardT.J. TynanPhillip Di Giuseppe30122
2Alex NewhookLukas VejdemoAustin Rueschhoff29122
3Kyle CliffordJansen HarkinsMathieu Olivier28122
4Justin AlmeidaJakub LaukoCole Fonstad13122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joseph CecconiSami Niku35122
2Dean KukanMichael Vukojevic33122
3Noel HoefenmayerPaul LaDue32122
4Sami NikuDean Kukan0122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anthony RichardLukas VejdemoMathieu Olivier50122
2Alex NewhookT.J. TynanAustin Rueschhoff50104
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sami NikuPaul LaDue50122
2Dean KukanMichael Vukojevic50113
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Lukas VejdemoMathieu Olivier50131
2T.J. TynanAnthony Richard50131
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dean KukanSami Niku50131
2Michael VukojevicPaul LaDue50131
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Anthony Richard50140Dean KukanSami Niku50140
2T.J. Tynan50140Michael VukojevicPaul LaDue50140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Anthony RichardT.J. Tynan50023
2Lukas VejdemoAustin Rueschhoff50023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dean KukanSami Niku50023
2Paul LaDueMichael Vukojevic50023
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Anthony RichardAlex NewhookAustin RueschhoffDean KukanSami Niku
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Alex NewhookAustin RueschhoffMathieu OlivierDean KukanPaul LaDue
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Alex Newhook, Mathieu Olivier, Anthony RichardMathieu Olivier, Kyle CliffordJansen Harkins
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Sami Niku, Dean Kukan, Paul LaDueMichael VukojevicMichael Vukojevic, Sami Niku
Tirs de pénalité
Mathieu Olivier, Austin Rueschhoff, Anthony Richard, T.J. Tynan, Lukas Vejdemo
Gardien
#1 : Dan Vladar, #2 : Magnus Hellberg
Lignes d’attaque personnalisées en prolongation
Lukas Vejdemo, Alex Newhook, T.J. Tynan, Cole Fonstad, Jakub Lauko, Mathieu Olivier, Mathieu Olivier, Anthony Richard, Austin Rueschhoff, Jansen Harkins, Kyle Clifford
Lignes de défense personnalisées en prolongation
Paul LaDue, Sami Niku, Dean Kukan, Joseph Cecconi, Michael Vukojevic


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
1Admirals2100010010911000010056-11100000053230.7501019290022192016621722223410783220508337.50%100100.00%135572149.24%41078252.43%14428850.00%452309452142246121
2Eagles320001001394210001006601100000073450.833132437002219201104217222234101093330739333.33%15380.00%035572149.24%41078252.43%14428850.00%452309452142246121
3Firebirds22000000835110000005141100000032141.000815230022192018621722223410921814559111.11%70100.00%035572149.24%41078252.43%14428850.00%452309452142246121
4IceHogs1010000025-3000000000001010000025-300.0002460022192013121722223410459429500.00%2150.00%035572149.24%41078252.43%14428850.00%452309452142246121
5Iowa Wild5220000113130321000009722010000146-250.50013233600221920119421722223410155424512415320.00%16756.25%035572149.24%41078252.43%14428850.00%452309452142246121
6Phantoms1010000002-2000000000001010000002-200.000000002219201182172222341035101233300.00%60100.00%035572149.24%41078252.43%14428850.00%452309452142246121
7Texas Stars2110000010911010000045-11100000064220.5001019290022192016721722223410782728485240.00%14471.43%035572149.24%41078252.43%14428850.00%452309452142246121
8Thunderbirds30200100512-72010010049-51010000013-210.167591400221920111121722223410103233856900.00%9455.56%035572149.24%41078252.43%14428850.00%452309452142246121
Total1987003016162-11043003003334-19440000128280200.5266111317400221920167721722223410695194191468631219.05%791975.95%135572149.24%41078252.43%14428850.00%452309452142246121
_Since Last GM Reset1987003016162-11043003003334-19440000128280200.5266111317400221920167721722223410695194191468631219.05%791975.95%135572149.24%41078252.43%14428850.00%452309452142246121
_Vs Conference188600301616011043003003334-18430000128262200.5566111317400221920165921722223410660184179435601220.00%731973.97%135572149.24%41078252.43%14428850.00%452309452142246121
_Vs Division1666003015357-4933003002833-57330000125241160.500539815100221920157321722223410568166165380511121.57%661971.21%135572149.24%41078252.43%14428850.00%452309452142246121

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1920W16111317467769519419146800
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
198703016162
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
104303003334
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
94400012828
Derniers 10 matchs
WLOTWOTL SOWSOL
540001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
631219.05%791975.95%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
217222234102219201
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
35572149.24%41078252.43%14428850.00%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
452309452142246121


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 - 2022-10-164Moose2IceHogs5ALSommaire du match
3 - 2022-10-1817Moose1Thunderbirds3ALSommaire du match
4 - 2022-10-1930Thunderbirds3Moose2BLXSommaire du match
6 - 2022-10-2151Moose5Admirals3AWSommaire du match
9 - 2022-10-2462Iowa Wild2Moose4BWSommaire du match
11 - 2022-10-2682Eagles5Moose4BLXSommaire du match
16 - 2022-10-31111Admirals6Moose5BLXSommaire du match
20 - 2022-11-04130Iowa Wild2Moose3BWSommaire du match
22 - 2022-11-06150Moose2Iowa Wild3ALSommaire du match
24 - 2022-11-08168Iowa Wild3Moose2BLSommaire du match
25 - 2022-11-09181Moose0Phantoms2ALSommaire du match
29 - 2022-11-13195Texas Stars5Moose4BLSommaire du match
31 - 2022-11-15208Moose6Texas Stars4AWSommaire du match
32 - 2022-11-16218Moose7Eagles3AWSommaire du match
34 - 2022-11-18233Moose3Firebirds2AWSommaire du match
37 - 2022-11-21247Thunderbirds6Moose2BLSommaire du match
38 - 2022-11-22265Firebirds1Moose5BWSommaire du match
40 - 2022-11-24283Moose2Iowa Wild3ALXXSommaire du match
43 - 2022-11-27300Eagles1Moose2BWSommaire du match
48 - 2022-12-02328Iowa Wild-Moose-
50 - 2022-12-04348Moose-Bears-
51 - 2022-12-05355Moose-Gulls-
53 - 2022-12-07368Admirals-Moose-
58 - 2022-12-12395Wranglers-Moose-
60 - 2022-12-14416Moose-Roadrunners-
62 - 2022-12-16428Americans-Moose-
64 - 2022-12-18449Thunderbirds-Moose-
65 - 2022-12-19458Moose-Griffins-
68 - 2022-12-22478Moose-Condors-
73 - 2022-12-27492Gulls-Moose-
75 - 2022-12-29506Moose-Rockets-
77 - 2022-12-31522Texas Stars-Moose-
78 - 2023-01-01527Moose-IceHogs-
82 - 2023-01-05552IceHogs-Moose-
86 - 2023-01-09579Moose-Roadrunners-
87 - 2023-01-10588Roadrunners-Moose-
91 - 2023-01-14614Barracuda-Moose-
92 - 2023-01-15633Gulls-Moose-
94 - 2023-01-17652Moose-Silver Knights-
96 - 2023-01-19663Moose-Reign-
98 - 2023-01-21672Moose-Wolf Pack-
99 - 2023-01-22683Checkers-Moose-
101 - 2023-01-24705Moose-W-B/Scranton Penguins-
102 - 2023-01-25715Wolves-Moose-
104 - 2023-01-27737Admirals-Moose-
106 - 2023-01-29751Moose-Admirals-
108 - 2023-01-31765Moose-Canucks-
110 - 2023-02-02782islanders-Moose-
112 - 2023-02-04794Moose-Texas Stars-
115 - 2023-02-07811Canucks-Moose-
118 - 2023-02-10835Moose-Marlies-
120 - 2023-02-12841Eagles-Moose-
122 - 2023-02-14861Moose-Eagles-
123 - 2023-02-15872Reign-Moose-
126 - 2023-02-18881Moose-Phantoms-
128 - 2023-02-20902Roadrunners-Moose-
130 - 2023-02-22917Moose-Crunch-
131 - 2023-02-23934Roadrunners-Moose-
133 - 2023-02-25947Moose-Binghamton Senateurs-
135 - 2023-02-27952Moose-Iowa Wild-
137 - 2023-03-01968Moose-Admirals-
139 - 2023-03-03982Phantoms-Moose-
144 - 2023-03-081005Texas Stars-Moose-
145 - 2023-03-091022Moose-Texas Stars-
147 - 2023-03-111039Moose-Roadrunners-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-03-131046Thunderbirds-Moose-
150 - 2023-03-141059Moose-Barracuda-
152 - 2023-03-161073Monsters-Moose-
153 - 2023-03-171088Moose-Eagles-
157 - 2023-03-211105Condors-Moose-
158 - 2023-03-221126Moose-Thunderbirds-
161 - 2023-03-251136Comets-Moose-
164 - 2023-03-281163IceHogs-Moose-
166 - 2023-03-301178Moose-Wranglers-
169 - 2023-04-021194IceHogs-Moose-
171 - 2023-04-041215Moose-Firebirds-
174 - 2023-04-071229Providence Bruins-Moose-
177 - 2023-04-101253Silver Knights-Moose-
180 - 2023-04-131267Moose-Thunderbirds-
181 - 2023-04-141278Moose-IceHogs-
182 - 2023-04-151290Firebirds-Moose-
184 - 2023-04-171307Moose-IceHogs-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance14,9129,405
Assistance PCT74.56%94.05%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
31 2432 - 81.06% 98,786$987,864$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,477,642$ 2,896,251$ 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
3,062,378$ 143 13,321$ 1,904,903$




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

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