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Little Stars
GP: 80 | W: 35 | L: 34 | OTL: 11 | P: 81
GF: 311 | GA: 322 | PP%: 18.15% | PK%: 79.66%
DG: Francois Cloutier | Morale : 26 | Moyenne d’équipe : 65
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Centre de jeu
Marlies
42-34-4, 88pts
5
FINAL
8 Little Stars
35-34-11, 81pts
Team Stats
OTW1StreakL1
24-15-1Home Record15-19-6
18-19-3Away Record20-15-5
3-7-0Last 10 Games3-6-1
4.26Buts par match 3.89
4.33Buts contre par match 4.03
25.31%Pourcentage en avantage numérique18.15%
73.98%Pourcentage en désavantage numérique79.66%
Crunch
43-32-5, 91pts
6
FINAL
5 Little Stars
35-34-11, 81pts
Team Stats
W1StreakL1
19-18-3Home Record15-19-6
24-14-2Away Record20-15-5
7-2-1Last 10 Games3-6-1
4.25Buts par match 3.89
4.11Buts contre par match 4.03
24.00%Pourcentage en avantage numérique18.15%
72.76%Pourcentage en désavantage numérique79.66%
Meneurs d'équipe
Buts
Daniel O'regan
43
Passes
Daniel O'regan
84
Points
Daniel O'regan
127
Plus/Moins
Wiley Sherman
22
Victoires
Connor Knapp
18
Pourcentage d’arrêts
Connor Knapp
0.897

Statistiques d’équipe
Buts pour
311
3.89 GFG
Tirs pour
2725
34.06 Avg
Pourcentage en avantage numérique
18.2%
55 GF
Début de zone offensive
37.6%
Buts contre
322
4.03 GAA
Tirs contre
2591
32.39 Avg
Pourcentage en désavantage numérique
79.7%%
59 GA
Début de la zone défensive
35.6%
Informations de l'équipe

Directeur généralFrancois Cloutier
EntraîneurMike Yeo
DivisionGunther-Sabetzki
ConférenceLouis-Magnus
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,783
Billets de saison300


Informations de la formation

Équipe Pro33
Équipe Mineure19
Limite contact 52 / 250
Espoirs0


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
1Ilya Mikheyev (R)X100.007749817071787675777469637259544348710232950,000$
2Jordan LaValleeX100.006938786568737369658177626877721639710311900,000$
3Adam Tambellini (R)X100.006529787184787367717784526758483846700232600,000$
4Daniel O'regan (R)X100.006828807168797671748173596259483946700232900,000$
5Henrik Borgstrom (R)X100.007240777276717470747571646748426946690201500,000$
6Joakim Nygard (R)X100.005940817374656278737263638451544446680242900,000$
7Jason Dickinson (R)X100.006933767067677373746972577547465346670222500,000$
8Michael MerschX100.006935767472656572676177567258573517670251800,000$
9Alex Belzile (R)X100.006843837468707267646872566753514144670261750,000$
10Emile Poirier (R)X100.005633827277666763636681537247453834660231550,000$
11Shane Gersich (R)X100.006337806958687477787867425343435717650213700,000$
12Roman HorakX100.006239756959696769737065515249522446640261300,000$
13Matt Luff (R)X100.006635736573616160627183466845455846640201500,000$
14Justin Auger (R)X100.005829755867726760617476436947463946630231500,000$
15Radel Fazleev (R)X100.005134736756696664747669465243434317620212550,000$
16Jonathan Dahlen (R)X100.005424677046534972646066546643425317600201500,000$
17Filip Chytil (R)X100.006042746166645966566460496040408017590182500,000$
18Anton Cederholm (R)X100.007126846978747264527967825464464629720222750,000$
19Wiley Sherman (R)X100.006736877668827771677968746863465731720221950,000$
20Eric KnodelX100.007634727069806768467058705767592636690271900,000$
21Reece Willcox (R)X100.006629777668667567527160736556494241680232800,000$
22Tucker Poolman (R)X100.007233727470646368627154676052513946670242600,000$
23Ville Pokka (R)X100.006637766962656567416864665646474150650233600,000$
24Connor Mackey (R)X100.006346756168656766426157646045474826630212500,000$
25Lawrence Pilut (R)X100.006336695561596666446858575547445017600223500,000$
Rayé
1Joey Anderson (R)X100.005942676564546255625663585641416917580191500,000$
2Givani Smith (R)X100.006846595967507960506359524941416719580191500,000$
3Rudolfs Balcers (R)X100.005936695751635553615767506042425420570203250,000$
4Jean-Christophe Beaudin (R)X100.005024635647536165617060405242426120560203250,000$
5Yakov Trenin (R)X100.006434645864605364525655405842424620550204250,000$
MOYENNE D’ÉQUIPE100.00643675676667676762706757635148473365
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
1Michael Houser (R)100.00688252756672688182686255534946700253995,000$
2Danil Tarasov (R)100.00684565777348455766447940408411580182500,000$
Rayé
1Connor Knapp90.74725668777572666376697261552523700271950,000$
MOYENNE D’ÉQUIPE96.9169616276716460677560715249532766
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Yeo61646867353766CAN412750,000$


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
1Daniel O'reganLittle Stars (Dal)C804384127-54201321553158419313.65%44178622.331225375226812351885352.55%25276332021.42150001045
2Ilya MikheyevLittle Stars (Dal)RW76345690-92401459729510819111.53%40161521.26918275125500051106247.22%1445226021.11212000665
3Jordan LaValleeLittle Stars (Dal)LW68424385-84001231062587916116.28%38155822.931113243323220282013452.31%2816031111.09110000474
4Adam TambelliniLittle Stars (Dal)LW803442766300130932428513314.05%33150618.83511162621901161791347.95%735421021.0107000453
5Joakim NygardLittle Stars (Dal)LW80253459710056882035813012.32%25100012.500222410001352147.92%483122011.1823000442
6Henrik BorgstromLittle Stars (Dal)C8030265604001491252116210014.22%28131716.47729212120006685347.39%10173626000.8514000414
7Jason DickinsonLittle Stars (Dal)C80242145102009274169609414.20%1794211.78000040002563145.76%4483515000.9600000022
8Alex BelzileLittle Stars (Dal)RW71172744-11208976125377813.60%23111115.6645916181000003150.98%513115000.7900000004
9Eric KnodelLittle Stars (Dal)D8042731-2176017313812248543.28%141215126.89347242860003236000.00%02877000.2911000211
10Reece WillcoxLittle Stars (Dal)D7922931-25957414610027392.00%96177522.48044132130110181000.00%02757000.3500100011
11Matt LuffLittle Stars (Dal)RW801018288400782773195113.70%1992111.51022043000001148.00%252112000.6100000101
12Wiley ShermanLittle Stars (Dal)D52225272218053897620332.63%72117622.63235101180004164000.00%03127000.4601000002
13Tucker PoolmanLittle Stars (Dal)D80422269680117917524245.33%80158819.8512361830001151100.00%02041100.3300000002
14Emile PoirierLittle Stars (Dal)LW63111425120173486355712.79%54847.69000250002500145.45%11246001.0300000110
15Roman HorakLittle Stars (Dal)C8081523-36055419137558.79%46187.7300000000041158.18%220157000.7400000021
16Justin AugerLittle Stars (Dal)RW808917-3100401951223515.69%96718.39000010000000246.15%1395000.5100000011
17Anton CederholmLittle Stars (Dal)D4221315-614053936931322.90%73113427.01123101670001127000.00%02740000.2600000020
18Ville PokkaLittle Stars (Dal)D801131413261058795928211.69%79119214.91011155000086000.00%0934100.2301101000
19Michael MerschLittle Stars (Dal)LW404610-74025238623484.65%113649.1100002000050137.50%8157000.5500000001
20Connor MackeyLittle Stars (Dal)D55246-2240244022899.09%4365111.8400004000041000.00%0516000.1800000000
21Joey AndersonLittle Stars (Dal)RW15101-260111042525.00%11067.070000000000100.00%200000.1900000000
22Filip ChytilLittle Stars (Dal)C11000-100000000.00%0111.030000000009000.00%100000.00%00000000
23Lawrence PilutLittle Stars (Dal)D17000-160772130.00%61307.690000000002000.00%015000.00%00000000
24Radel FazleevLittle Stars (Dal)C11000000001100.00%0201.83000000000160062.50%800000.00%00000000
25Shane GersichLittle Stars (Dal)LW11000-100000000.00%050.53000000000000100.00%100000.00%00000000
Statistiques d’équipe totales ou en moyenne1491308528836457715170116512735899154611.26%8872384215.9955941492672509347441920322450.72%4878594522380.70844201363739
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
1Connor KnappLittle Stars (Dal)35181020.8973.1917884095925475200.583122930212
2Michael HouserLittle Stars (Dal)53152090.8734.142696001861460749100.606334435211
3Danil TarasovLittle Stars (Dal)112400.8494.963752031205124110.00%0715000
Statistiques d’équipe totales ou en moyenne993534110.8803.854861603122590134841458080423


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 restantPlafond 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
Adam TambelliniLittle Stars (Dal)LW231994-01-01Yes185 Lbs6 ft4NoNoNo2Pro & Farm600,000$0$0$No600,000$Lien
Alex BelzileLittle Stars (Dal)RW261991-01-01Yes197 Lbs5 ft10NoNoNo1Pro & Farm750,000$0$0$NoLien
Anton CederholmLittle Stars (Dal)D221995-01-01Yes185 Lbs6 ft2NoNoNo2Pro & Farm750,000$0$0$No750,000$Lien
Connor Knapp (sur la masse salariale)Little Stars (Dal)G271990-01-01No206 Lbs6 ft6NoNoNo1Pro & Farm950,000$0$0$Yes
Connor MackeyLittle Stars (Dal)D211996-01-01Yes190 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Daniel O'reganLittle Stars (Dal)C231994-01-01Yes169 Lbs5 ft9NoNoNo2Pro & Farm900,000$0$0$No950,000$Lien
Danil TarasovLittle Stars (Dal)G181999-01-01Yes196 Lbs6 ft6NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Emile PoirierLittle Stars (Dal)LW231994-01-01Yes185 Lbs6 ft1NoNoNo1Pro & Farm550,000$0$0$NoLien
Eric KnodelLittle Stars (Dal)D271990-01-01No216 Lbs6 ft6NoNoNo1Pro & Farm900,000$0$0$No
Filip ChytilLittle Stars (Dal)C181999-01-01Yes210 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Givani SmithLittle Stars (Dal)RW191998-01-01Yes205 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLien
Henrik BorgstromLittle Stars (Dal)C201997-01-01Yes198 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$NoLien
Ilya MikheyevLittle Stars (Dal)RW231994-01-01Yes195 Lbs6 ft3NoNoNo2Pro & Farm950,000$0$0$No1,250,000$Lien
Jason DickinsonLittle Stars (Dal)C221995-01-01Yes185 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Jean-Christophe BeaudinLittle Stars (Dal)C201997-01-01Yes196 Lbs6 ft1NoNoNo3Pro & Farm250,000$0$0$No250,000$250,000$Lien
Joakim NygardLittle Stars (Dal)LW241993-01-01Yes179 Lbs6 ft0NoNoNo2Pro & Farm900,000$0$0$No950,000$Lien
Joey AndersonLittle Stars (Dal)RW191998-01-01Yes190 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$NoLien
Jonathan DahlenLittle Stars (Dal)LW201997-01-01Yes181 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$NoLien
Jordan LaValleeLittle Stars (Dal)LW311986-01-01No225 Lbs6 ft3NoNoNo1Pro & Farm900,000$0$0$No
Justin AugerLittle Stars (Dal)RW231994-01-01Yes185 Lbs6 ft7NoNoNo1Pro & Farm500,000$0$0$NoLien
Lawrence PilutLittle Stars (Dal)D221995-01-01Yes194 Lbs5 ft11NoNoNo3Pro & Farm500,000$0$0$No550,000$550,000$Lien
Matt LuffLittle Stars (Dal)RW201997-01-01Yes190 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLien
Michael HouserLittle Stars (Dal)G251992-01-01Yes185 Lbs6 ft1NoNoNo3Pro & Farm995,000$0$0$No995,000$2,000,000$Lien
Michael MerschLittle Stars (Dal)LW251992-01-01No218 Lbs6 ft2NoNoNo1Pro & Farm800,000$0$0$No
Radel FazleevLittle Stars (Dal)C211996-01-01Yes192 Lbs5 ft11NoNoNo2Pro & Farm550,000$0$0$No550,000$Lien
Reece WillcoxLittle Stars (Dal)D231994-01-01Yes184 Lbs6 ft3NoNoNo2Pro & Farm800,000$0$0$No850,000$Lien
Roman HorakLittle Stars (Dal)C261991-01-01No170 Lbs6 ft0NoNoNo1Pro & Farm300,000$0$0$No
Rudolfs BalcersLittle Stars (Dal)LW201997-01-01Yes180 Lbs5 ft11NoNoNo3Pro & Farm250,000$0$0$No250,000$300,000$Lien
Shane GersichLittle Stars (Dal)LW211996-01-01Yes175 Lbs5 ft11NoNoNo3Pro & Farm700,000$0$0$No800,000$900,000$Lien
Tucker PoolmanLittle Stars (Dal)D241993-01-01Yes185 Lbs6 ft2NoNoNo2Pro & Farm600,000$0$0$No600,000$Lien
Ville PokkaLittle Stars (Dal)D231994-01-01Yes205 Lbs5 ft11NoNoNo3Pro & Farm600,000$0$0$No600,000$650,000$Lien
Wiley ShermanLittle Stars (Dal)D221995-01-01Yes185 Lbs6 ft6NoNoNo1Pro & Farm950,000$0$0$NoLien
Yakov TreninLittle Stars (Dal)C201997-01-01Yes201 Lbs6 ft2NoNoNo4Pro & Farm250,000$0$0$No250,000$250,000$250,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3322.45192 Lbs6 ft21.82627,121$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jordan LaValleeDaniel O'reganIlya Mikheyev40122
2Adam TambelliniHenrik BorgstromAlex Belzile30122
3Joakim NygardJason DickinsonMatt Luff20122
4Michael MerschRoman HorakJustin Auger10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Anton CederholmWiley Sherman40122
2Eric KnodelReece Willcox30122
3Tucker PoolmanVille Pokka20122
4Connor MackeyLawrence Pilut10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jordan LaValleeDaniel O'reganIlya Mikheyev60122
2Adam TambelliniHenrik BorgstromAlex Belzile40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Anton CederholmWiley Sherman60122
2Eric KnodelReece Willcox40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jordan LaValleeIlya Mikheyev60122
2Adam TambelliniDaniel O'regan40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Anton CederholmWiley Sherman60122
2Eric KnodelReece Willcox40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jordan LaVallee60122Anton CederholmWiley Sherman60122
2Ilya Mikheyev40122Eric KnodelReece Willcox40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jordan LaValleeIlya Mikheyev60122
2Adam TambelliniDaniel O'regan40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Anton CederholmWiley Sherman60122
2Eric KnodelReece Willcox40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jordan LaValleeDaniel O'reganIlya MikheyevAnton CederholmWiley Sherman
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jordan LaValleeDaniel O'reganIlya MikheyevAnton CederholmWiley Sherman
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Emile Poirier, Shane Gersich, Radel FazleevEmile Poirier, Shane GersichRadel Fazleev
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Tucker Poolman, Ville Pokka, Connor MackeyTucker PoolmanVille Pokka, Connor Mackey
Tirs de pénalité
Jordan LaVallee, Ilya Mikheyev, Adam Tambellini, Daniel O'regan, Henrik Borgstrom
Gardien
#1 : Michael Houser, #2 : Danil Tarasov


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
1Admirals31100001912-31010000017-62100000185330.500915240093100112101168949308845811135265313215.38%13284.62%0934183550.90%889173751.18%651130649.85%174699016687481454723
2Barracuda21100000871110000004131010000046-220.50081422009310011210748949308845856171037500.00%50100.00%0934183550.90%889173751.18%651130649.85%174699016687481454723
3Bears402000021823-5302000011216-41000000167-120.25018325000931001121014489493088458139512412910110.00%12375.00%0934183550.90%889173751.18%651130649.85%174699016687481454723
4Comets6240000024213312000001192312000001312140.33324406400931001121021889493088458172573613234617.65%18572.22%0934183550.90%889173751.18%651130649.85%174699016687481454723
5Condors22000000844110000003121100000053241.000813210093100112106589493088458683110352150.00%50100.00%0934183550.90%889173751.18%651130649.85%174699016687481454723
6Crunch312000001415-120200000912-31100000053220.333142438109310011210848949308845897303453700.00%17382.35%0934183550.90%889173751.18%651130649.85%174699016687481454723
7Devils311000011517-220100001615-91100000092730.50015254000931001121012389493088458972816599111.11%8362.50%0934183550.90%889173751.18%651130649.85%174699016687481454723
8Eagles30101001511-62010000129-71000100032130.50059140093100112109989493088458108431659800.00%9188.89%0934183550.90%889173751.18%651130649.85%174699016687481454723
9Griffins210000016511000000123-11100000042230.75061117009310011210528949308845854161038900.00%5180.00%0934183550.90%889173751.18%651130649.85%174699016687481454723
10Heat21100000101001010000057-21100000053220.5001016260093100112106789493088458592018427571.43%9188.89%1934183550.90%889173751.18%651130649.85%174699016687481454723
11Icehogs20101000660100010004311010000023-120.500610160093100112106689493088458763216381119.09%8362.50%0934183550.90%889173751.18%651130649.85%174699016687481454723
12Marlies5220010025241321000001713420100100811-350.50025386300931001121015989493088458160544211623417.39%21861.90%0934183550.90%889173751.18%651130649.85%174699016687481454723
13Monsters20100100412-81010000018-71000010034-110.25048120093100112106089493088458672326446350.00%13376.92%0934183550.90%889173751.18%651130649.85%174699016687481454723
14Moose421010001513211000000431311010001110160.7501527420093100112101348949308845813336168817211.76%8187.50%0934183550.90%889173751.18%651130649.85%174699016687481454723
15Penguins311000011319-621000001111101010000028-630.500132437009310011210109894930884589539356711327.27%15753.33%0934183550.90%889173751.18%651130649.85%174699016687481454723
16Phantoms311000101183110000008352010001035-240.6671116270093100112101008949308845810044166813215.38%80100.00%1934183550.90%889173751.18%651130649.85%174699016687481454723
17Punishers624000002131-10321000001516-130300000615-940.33321335400931001121020689493088458204556310327518.52%29775.86%0934183550.90%889173751.18%651130649.85%174699016687481454723
18Rampage6410000128181032100000119232000001179890.75028487600931001121020889493088458184654213833824.24%22290.91%0934183550.90%889173751.18%651130649.85%174699016687481454723
19Reign312000001113-22110000078-11010000045-120.33311193000931001121095894930884588931206910330.00%10370.00%0934183550.90%889173751.18%651130649.85%174699016687481454723
20Rocket21100000910-11010000036-31100000064220.500916250093100112106689493088458752018394250.00%9277.78%0934183550.90%889173751.18%651130649.85%174699016687481454723
21Senators20200000711-41010000045-11010000036-300.000710170093100112105589493088458641814504125.00%7185.71%0934183550.90%889173751.18%651130649.85%174699016687481454723
22Sound Tigers311000018801000000134-12110000054130.5008122000931001121010489493088458822518689111.11%9188.89%0934183550.90%889173751.18%651130649.85%174699016687481454723
23Thunderbirds31200000111011010000034-12110000086220.33311203100931001121010289493088458953230558112.50%15286.67%1934183550.90%889173751.18%651130649.85%174699016687481454723
24Wolfpack320000101147110000004132100001073461.0001117280093100112109989493088458934516751317.69%80100.00%0934183550.90%889173751.18%651130649.85%174699016687481454723
25Wolves31100010141041010000034-121000010116540.6671423370093100112101208949308845811339195210220.00%70100.00%0934183550.90%889173751.18%651130649.85%174699016687481454723
Total80293403239311322-1140141901006153178-254015150223315814414810.506311520831109310011210272589493088458259188659117073035518.15%2905979.66%3934183550.90%889173751.18%651130649.85%174699016687481454723
_Since Last GM Reset80293403239311322-1140141901006153178-254015150223315814414810.506311520831109310011210272589493088458259188659117073035518.15%2905979.66%3934183550.90%889173751.18%651130649.85%174699016687481454723
_Vs Conference46162001027182187-5247120000590110-20229801022927715450.48918230748910931001121016168949308845814795093499901792916.20%1693479.88%1934183550.90%889173751.18%651130649.85%174699016687481454723
_Vs Division1889000017370395400000373439350000136360170.4727312119400931001121063289493088458560177141373941920.21%691479.71%0934183550.90%889173751.18%651130649.85%174699016687481454723

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8081L131152083127252591886591170710
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8029343239311322
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4014191006153178
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4015152233158144
Derniers 10 matchs
WLOTWOTL SOWSOL
360001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3035518.15%2905979.66%3
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
894930884589310011210
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
934183550.90%889173751.18%651130649.85%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
174699016687481454723


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
2 - 2022-10-287Rampage2Little Stars1BLR1Sommaire du match
5 - 2022-10-3126Little Stars5Rampage6ALXXSommaire du match
7 - 2022-11-0236Bears5Little Stars4BLSommaire du match
9 - 2022-11-0446Little Stars2Moose4ALSommaire du match
12 - 2022-11-0762Little Stars2Punishers5ALR1Sommaire du match
13 - 2022-11-0871Comets4Little Stars3BLSommaire du match
16 - 2022-11-1185Little Stars1Sound Tigers3ALSommaire du match
18 - 2022-11-1392Punishers2Little Stars4BWR1Sommaire du match
21 - 2022-11-16111Devils6Little Stars5BLXXSommaire du match
23 - 2022-11-18129Little Stars1Phantoms4ALSommaire du match
25 - 2022-11-20137Little Stars2Comets4ALR1Sommaire du match
27 - 2022-11-22145Marlies5Little Stars3BLSommaire du match
29 - 2022-11-24152Little Stars3Wolfpack2AWXXSommaire du match
31 - 2022-11-26163Little Stars5Thunderbirds1AWSommaire du match
33 - 2022-11-28177Eagles2Little Stars1BLXXSommaire du match
36 - 2022-12-01192Little Stars6Wolves2AWSommaire du match
38 - 2022-12-03200Little Stars4Marlies5ALXSommaire du match
39 - 2022-12-04207Punishers7Little Stars3BLR1Sommaire du match
43 - 2022-12-08222Little Stars5Heat3AWSommaire du match
45 - 2022-12-10232Punishers7Little Stars8BWR1Sommaire du match
47 - 2022-12-12248Little Stars6Rocket4AWSommaire du match
49 - 2022-12-14257Little Stars4Griffins2AWSommaire du match
50 - 2022-12-15260Comets1Little Stars5BWR1Sommaire du match
55 - 2022-12-20283Sound Tigers4Little Stars3BLXXSommaire du match
57 - 2022-12-22294Little Stars5Moose4AWXSommaire du match
59 - 2022-12-24300Little Stars2Icehogs3ALSommaire du match
61 - 2022-12-26310Wolves4Little Stars3BLSommaire du match
63 - 2022-12-28323Little Stars3Eagles2AWXSommaire du match
66 - 2022-12-31337Monsters8Little Stars1BLSommaire du match
68 - 2023-01-02352Little Stars4Barracuda6ALSommaire du match
70 - 2023-01-04363Penguins8Little Stars7BLXXSommaire du match
72 - 2023-01-06373Little Stars4Marlies6ALSommaire du match
76 - 2023-01-10389Griffins3Little Stars2BLXXSommaire du match
77 - 2023-01-11399Little Stars3Monsters4ALXSommaire du match
81 - 2023-01-15416Admirals7Little Stars1BLSommaire du match
85 - 2023-01-19435Little Stars5Condors3AWSommaire du match
86 - 2023-01-20442Devils9Little Stars1BLSommaire du match
89 - 2023-01-23461Icehogs3Little Stars4BWXSommaire du match
91 - 2023-01-25470Little Stars4Rampage2AWR1Sommaire du match
93 - 2023-01-27483Little Stars9Devils2AWSommaire du match
95 - 2023-01-29492Penguins3Little Stars4BWSommaire du match
97 - 2023-01-31505Little Stars5Wolves4AWXXSommaire du match
99 - 2023-02-02517Reign2Little Stars5BWSommaire du match
101 - 2023-02-04524Little Stars4Moose2AWSommaire du match
104 - 2023-02-07542Reign6Little Stars2BLSommaire du match
108 - 2023-02-11560Little Stars2Phantoms1AWXXSommaire du match
110 - 2023-02-13572Senators5Little Stars4BLSommaire du match
112 - 2023-02-15585Little Stars4Sound Tigers1AWSommaire du match
114 - 2023-02-17595Comets4Little Stars3BLR1Sommaire du match
117 - 2023-02-20608Little Stars3Punishers4ALR1Sommaire du match
120 - 2023-02-23620Rampage3Little Stars4BWSommaire du match
122 - 2023-02-25631Little Stars3Admirals4ALXXSommaire du match
125 - 2023-02-28646Condors1Little Stars3BWSommaire du match
127 - 2023-03-02656Little Stars8Rampage1AWR1Sommaire du match
129 - 2023-03-04672Rampage4Little Stars6BWSommaire du match
130 - 2023-03-05679Little Stars8Comets4AWR1Sommaire du match
134 - 2023-03-09696Little Stars5Crunch3AWSommaire du match
135 - 2023-03-10703Barracuda1Little Stars4BWSommaire du match
139 - 2023-03-14725Little Stars3Senators6ALSommaire du match
140 - 2023-03-15730Wolfpack1Little Stars4BWSommaire du match
143 - 2023-03-18745Little Stars4Wolfpack1AWSommaire du match
145 - 2023-03-20754Eagles7Little Stars1BLSommaire du match
149 - 2023-03-24776Moose3Little Stars4BWSommaire du match
151 - 2023-03-26788Little Stars1Punishers6ALR1Sommaire du match
153 - 2023-03-28802Bears5Little Stars3BLSommaire du match
155 - 2023-03-30808Little Stars4Reign5ALSommaire du match
159 - 2023-04-03829Thunderbirds4Little Stars3BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
160 - 2023-04-04832Little Stars6Bears7ALXXSommaire du match
166 - 2023-04-10857Phantoms3Little Stars8BWSommaire du match
169 - 2023-04-13878Heat7Little Stars5BLSommaire du match
171 - 2023-04-15889Little Stars5Admirals1AWSommaire du match
175 - 2023-04-19906Crunch6Little Stars4BLSommaire du match
177 - 2023-04-21916Little Stars3Comets4ALR1Sommaire du match
181 - 2023-04-25933Marlies3Little Stars6BWSommaire du match
184 - 2023-04-28951Bears6Little Stars5BLXXSommaire du match
190 - 2023-05-04976Little Stars2Penguins8ALSommaire du match
192 - 2023-05-06984Rocket6Little Stars3BLSommaire du match
193 - 2023-05-07991Little Stars3Thunderbirds5ALSommaire du match
198 - 2023-05-121009Marlies5Little Stars8BWSommaire du match
203 - 2023-05-171031Crunch6Little Stars5BLSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance74,80936,512
Assistance PCT93.51%91.28%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2783 - 92.77% 83,107$3,324,294$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,951,942$ 2,744,500$ 2,604,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
12,862$ 2,185,335$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 16,964$ 0$




Little Stars 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

Little Stars 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

Little Stars 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

Little Stars 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

Little Stars 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