Connexion

Little Stars
GP: 80 | W: 44 | L: 29 | OTL: 7 | P: 95
GF: 339 | GA: 314 | PP%: 22.70% | PK%: 79.31%
DG: Francois Cloutier | Morale : 46 | Moyenne d’équipe : 64
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Centre de jeu
Little Stars
44-29-7, 95pts
4
FINAL
8 Eagles
43-31-6, 92pts
Team Stats
L4SéquenceSOW1
24-13-3Fiche domicile22-13-5
20-16-4Fiche domicile21-18-1
5-5-0Derniers 10 matchs6-3-1
4.24Buts par match 3.99
3.93Buts contre par match 3.89
22.70%Pourcentage en avantage numérique19.24%
79.31%Pourcentage en désavantage numérique76.77%
Islander
44-32-4, 92pts
6
FINAL
2 Little Stars
44-29-7, 95pts
Team Stats
W1SéquenceL4
21-15-4Fiche domicile24-13-3
23-17-0Fiche domicile20-16-4
5-3-2Derniers 10 matchs5-5-0
4.51Buts par match 4.24
4.33Buts contre par match 3.93
28.16%Pourcentage en avantage numérique22.70%
78.90%Pourcentage en désavantage numérique79.31%
Meneurs d'équipe
Buts
Daniel O'regan
47
Passes
Daniel O'regan
80
Points
Daniel O'regan
127
Plus/Moins
Reece Willcox
19
Victoires
Michael Houser
33
Pourcentage d’arrêts
Michael Houser
0.896

Statistiques d’équipe
Buts pour
339
4.24 GFG
Tirs pour
2699
33.74 Avg
Pourcentage en avantage numérique
22.7%
69 GF
Début de zone offensive
37.7%
Buts contre
314
3.93 GAA
Tirs contre
2744
34.30 Avg
Pourcentage en désavantage numérique
79.3%%
60 GA
Début de la zone défensive
35.8%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,788
Billets de saison300


Informations de la formation

Équipe Pro31
Équipe Mineure20
Limite contact 51 / 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)X100.0076498273737778757876726674655839487302411,250,000$
2Jason Dickinson (R)X100.007233786970707573767274597749474941690231500,000$
3Joakim NygardX100.006240827577666580757066618553564066690251950,000$
4Shane Gersich (R)X100.006540827160707679798171455644445066680222800,000$
5Emile Poirier (R)X100.005833837178686964656882547348483566670242650,000$
6Matt Luff (R)X100.006535777176656562677184527047475366670214750,000$
7Justin Auger (R)X100.006029786169736962657577487048493666650242600,000$
8Radel Fazleev (R)X100.005337767058716867767771475344443866640221550,000$
9Filip Chytil (R)X100.006144766469656169616663506341417054620191500,000$
10Jonathan Dahlen (R)X100.005625687250545174666369576844434710620213550,000$
11Cal Burke (R)X100.006350796955685359597263446545485966610212500,000$
12Jean-Christophe Beaudin (R)X100.005326655951566268637161435443435319580212250,000$
13Wiley Sherman (R)X100.006936877770837973687670756967485267730234975,000$
14Collin MillerX100.007128767068736976556869775971543341700261500,000$
15Reece Willcox (R)X100.007030767773707869537362756363513866700241850,000$
16Tucker PoolmanX100.007133747673696668647357686258543638680251600,000$
17Samuel Girard (R)X100.006127787667677079458561695049446157680204800,000$
18Ville Pokka (R)X100.006938767365686669476964695850503846670242600,000$
Rayé
1Daniel O'regan (R)X34.157128797073787973768373606366533657710241950,000$
2Joey Anderson (R)X100.006143696765566358645865605842426119600204525,000$
3Givani Smith (R)X100.007048606269528062536561545142425919600204525,000$
4Rudolfs Balcers (R)X100.006038706053665756635970516343434823590212250,000$
5Yakov Trenin (R)X100.006536666166625466575957426043434116570213250,000$
6Jack McBain (R)X100.006838545865547161566555474840408120560182500,000$
7Blade Jenkins (R)X100.005736645754565856535262535440406620550182500,000$
8Bulat Shafigullin (R)X100.005129695654545860515063375542416220530192500,000$
9Connor Mackey (R)X100.006546786668676968465960696247494451650221500,000$
10Lawrence Pilut (R)X100.006638705863606868457059605748454419620232550,000$
MOYENNE D’ÉQUIPE97.65643674676566676862696657624947494364
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 Houser99.00708156746873708283666459564464720262995,000$
2Danil Tarasov100.00715068797554506169518142427657620191500,000$
Rayé
1Michael Giugovaz100.00536355585951675250566645454020560231250,000$
MOYENNE D’ÉQUIPE99.6765656070675962656758704948534763
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Yeo61646867353766CAN421750,000$


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)C784780127-94601421732599716218.15%51177922.811624404225722452225152.56%26524619211.4313000946
2Ilya MikheyevLittle Stars (Dal)RW72326799-15300133922807816011.43%40142119.7472734282341012114249.34%1524827011.3904000547
3Joakim NygardLittle Stars (Dal)LW80375087-32201061002659717713.96%37150718.85109194021113471586343.04%796333021.1511000654
4Jason DickinsonLittle Stars (Dal)C683546811330011899194559618.04%27117517.28611171716621341103150.97%9262119011.3811000762
5Adam TambelliniStarsLW53374178328094762068510917.96%30123023.211310233118624661556453.13%965114201.2724000553
6Shane GersichLittle Stars (Dal)LW80342963510093802307612014.78%19112614.0834715731012695056.58%76447031.1200000454
7Reece WillcoxLittle Stars (Dal)D80643491960011914312349664.88%137200825.114812202521344210100%04458000.4900000111
8Matt LuffLittle Stars (Dal)RW80143549248011171118385911.86%28128016.01371014202000023140.00%752824000.7700000131
9Wiley ShermanLittle Stars (Dal)D678404811809813312865556.25%114188528.1411112152480333211110%06662100.5100000126
10Emile PoirierLittle Stars (Dal)LW80222244131205050157438814.01%1782610.330000140002871050.00%18409001.0601000232
11Radel FazleevLittle Stars (Dal)C8015193412405972142409710.56%1795911.990001331011193153.47%5481913000.7100000113
12Samuel GirardLittle Stars (Dal)D7762329-1332045889735406.19%63129716.8615641330000119100%02426000.4501000002
13Justin AugerLittle Stars (Dal)RW8014112510200774577374918.18%1993211.65101230000033150.00%181612000.5401000001
14Filip ChytilLittle Stars (Dal)C65913229200313880235011.25%95949.15000050001590246.70%18287000.7400000020
15Cal BurkeLittle Stars (Dal)RW8011920480482275253714.67%56257.8200000000001145.45%11118000.6400000101
16Tucker PoolmanLittle Stars (Dal)D68016168580891147126240%86138020.3101151570002132000%01837000.2300000000
17Collin MillerLittle Stars (Dal)D274913-1632053585127187.84%5673927.374261186011375000%01623000.3500000000
18Connor MackeyLittle Stars (Dal)D68010101214041593924120%4586412.7200007000040000%0334000.2300000000
19Ville PokkaLittle Stars (Dal)D53077-82205463351890%5992117.39000173000192000%01035000.1500000000
20Anton CederholmStarsD91452801519191095.26%1224927.75011338101231000%058000.4000000000
21Jean-Christophe BeaudinLittle Stars (Dal)C2632541002111192915.79%32148.2600001000060044.87%7801000.4700000000
22Lawrence PilutLittle Stars (Dal)D31134680152814667.14%1436111.670000300009000%007000.2200000000
23Jonathan DahlenLittle Stars (Dal)LW18303-26079425237.14%41277.080000000000000%173000.4700000001
24Rudolfs BalcersLittle Stars (Dal)LW131125006172114.29%0836.39000000000200100.00%101000.4800000000
25Yakov TreninLittle Stars (Dal)C7000020610020%2324.6100000000000046.67%150000000000000
26Joey AndersonLittle Stars (Dal)RW10000420066420%1787.8500000000010050.00%21200000000000
27Givani SmithLittle Stars (Dal)RW2000000000000%000.140000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne1452340580920655600163116512734967148012.44%8952370516.33691201892492420121729451833431851.60%4930589489580.78516000434144
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
1Michael HouserLittle Stars (Dal)64331950.8963.6135284021220301054410.500126015211
2Danil TarasovLittle Stars (Dal)26101020.8644.5112500094693381110.33332060100
3Michael GiugovazLittle Stars (Dal)11000.8423.60500031912100005000
Statistiques d’équipe totales ou en moyenne91442970.8873.844829403092742144762158080311


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 Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Non Activé 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 10Non-échange Année 2Non-échange Année 3Non-échange Année 4Non-échange Année 5Non-échange Année 6Non-échange Année 7Non-échange Année 8Non-échange Année 9Non-échange Année 10Lien
Blade JenkinsLittle Stars (Dal)LW182000-01-01Yes200 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Bulat ShafigullinLittle Stars (Dal)LW191999-01-01Yes182 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Cal BurkeLittle Stars (Dal)RW211997-01-01Yes185 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Collin MillerLittle Stars (Dal)D261992-01-01No175 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Connor MackeyLittle Stars (Dal)D221996-01-01Yes190 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Daniel O'regan (sur la masse salariale)Little Stars (Dal)C241994-01-01Yes169 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm950,000$4,726$0$0$Yes------------------
Danil TarasovLittle Stars (Dal)G191999-01-01No196 Lbs6 ft6NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Emile PoirierLittle Stars (Dal)LW241994-01-01Yes185 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm650,000$3,234$0$0$No750,000$--------No--------
Filip ChytilLittle Stars (Dal)C191999-01-01Yes210 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Givani SmithLittle Stars (Dal)RW201998-01-01Yes205 Lbs6 ft2NoNoN/ANoNo4FalseFalsePro & Farm525,000$2,612$0$0$No550,000$600,000$625,000$------NoNoNo------
Ilya MikheyevLittle Stars (Dal)RW241994-01-01Yes195 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$6,219$0$0$No------------------
Jack McBainLittle Stars (Dal)C182000-01-01Yes201 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Jason DickinsonLittle Stars (Dal)C231995-01-01Yes185 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Jean-Christophe BeaudinLittle Stars (Dal)C211997-01-01Yes196 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm250,000$1,244$0$0$No250,000$--------No--------
Joakim NygardLittle Stars (Dal)LW251993-01-01No179 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm950,000$4,726$0$0$No------------------
Joey AndersonLittle Stars (Dal)RW201998-01-01Yes190 Lbs5 ft11NoNoN/ANoNo4FalseFalsePro & Farm525,000$2,612$0$0$No550,000$600,000$625,000$------NoNoNo------
Jonathan DahlenLittle Stars (Dal)LW211997-01-01Yes181 Lbs5 ft11NoNoN/ANoNo3FalseFalsePro & Farm550,000$2,736$0$0$No575,000$650,000$-------NoNo-------
Justin AugerLittle Stars (Dal)RW241994-01-01Yes185 Lbs6 ft7NoNoN/ANoNo2FalseFalsePro & Farm600,000$2,985$0$0$No700,000$--------No--------
Lawrence PilutLittle Stars (Dal)D231995-01-01Yes194 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm550,000$2,736$0$0$No550,000$--------No--------
Matt LuffLittle Stars (Dal)RW211997-01-01Yes190 Lbs6 ft2NoNoN/ANoNo4FalseFalsePro & Farm750,000$3,731$0$0$No900,000$995,000$1,250,000$------NoNoNo------
Michael GiugovazLittle Stars (Dal)G231995-01-01No185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm250,000$1,244$0$0$No------------------
Michael HouserLittle Stars (Dal)G261992-01-01No185 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm995,000$4,950$0$0$No2,000,000$--------No--------
Radel FazleevLittle Stars (Dal)C221996-01-01Yes192 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm550,000$2,736$0$0$No------------------
Reece WillcoxLittle Stars (Dal)D241994-01-01Yes184 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm850,000$4,229$0$0$No------------------
Rudolfs BalcersLittle Stars (Dal)LW211997-01-01Yes180 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm250,000$1,244$0$0$No300,000$--------No--------
Samuel GirardLittle Stars (Dal)D201998-01-01Yes170 Lbs5 ft10NoNoN/ANoNo4FalseFalsePro & Farm800,000$3,980$0$0$No900,000$1,200,000$1,800,000$------NoNoNo------
Shane GersichLittle Stars (Dal)LW221996-01-01Yes175 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm800,000$3,980$0$0$No900,000$--------No--------
Tucker PoolmanLittle Stars (Dal)D251993-01-01No185 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm600,000$2,985$0$0$No------------------
Ville PokkaLittle Stars (Dal)D241994-01-01Yes205 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm600,000$2,985$0$0$No650,000$--------No--------
Wiley ShermanLittle Stars (Dal)D231995-01-01Yes185 Lbs6 ft6NoNoN/ANoNo4FalseFalsePro & Farm975,000$4,851$0$0$No1,500,000$2,000,000$2,500,000$------NoNoNo------
Yakov TreninLittle Stars (Dal)C211997-01-01Yes201 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm250,000$1,244$0$0$No250,000$250,000$-------NoNo-------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3122.03188 Lbs6 ft12.00611,935$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Joakim NygardJason DickinsonIlya Mikheyev40122
2Shane GersichRadel FazleevMatt Luff30122
3Emile PoirierFilip ChytilJustin Auger20122
4Jonathan DahlenJean-Christophe BeaudinCal Burke10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Wiley ShermanCollin Miller40122
2Reece WillcoxTucker Poolman30122
3Samuel GirardVille Pokka20122
4Wiley ShermanCollin Miller10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Joakim NygardJason DickinsonIlya Mikheyev60023
2Shane GersichRadel FazleevMatt Luff40023
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Wiley ShermanCollin Miller60122
2Reece WillcoxTucker Poolman40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jason DickinsonJoakim Nygard60122
2Radel FazleevShane Gersich40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Wiley ShermanCollin Miller60032
2Reece WillcoxTucker Poolman40032
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jason Dickinson60122Wiley ShermanCollin Miller60032
2Radel Fazleev40122Reece WillcoxTucker Poolman40032
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jason DickinsonJoakim Nygard60023
2Radel FazleevShane Gersich40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Wiley ShermanCollin Miller60122
2Reece WillcoxTucker Poolman40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Joakim NygardJason DickinsonIlya MikheyevWiley ShermanCollin Miller
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Joakim NygardJason DickinsonIlya MikheyevWiley ShermanCollin Miller
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Matt Luff, Emile Poirier, Justin AugerMatt Luff, Emile PoirierMatt Luff
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Tucker Poolman, Samuel Girard, Ville PokkaTucker PoolmanTucker Poolman, Samuel Girard
Tirs de pénalité
Ilya Mikheyev, Joakim Nygard, Jason Dickinson, Shane Gersich, Matt Luff
Gardien
#1 : Michael Houser, #2 : Danil Tarasov
Lignes d’attaque personnalisées en prolongation
Ilya Mikheyev, Joakim Nygard, Jason Dickinson, Shane Gersich, Matt Luff, Emile Poirier, Emile Poirier, Justin Auger, Radel Fazleev, Jonathan Dahlen, Filip Chytil
Lignes de défense personnalisées en prolongation
Wiley Sherman, Collin Miller, Reece Willcox, Tucker Poolman, Samuel Girard


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
1Admirals32100000871110000002112110000066040.667814220087132115995870957852341003518777228.57%90100.00%0964184652.22%912175651.94%668129951.42%168794917367431413699
2Americans22000000954110000004221100000053241.0009122100871321159788709578523463211244300.00%60100.00%0964184652.22%912175651.94%668129951.42%168794917367431413699
3Barracuda211000009631010000034-11100000062420.50091423008713211595787095785234732210419222.22%50100.00%1964184652.22%912175651.94%668129951.42%168794917367431413699
4Bears3210000014122211000009901100000053240.6671426400087132115910587095785234110281850300.00%9188.89%0964184652.22%912175651.94%668129951.42%168794917367431413699
5Canucks714000022534-9302000011218-6412000011316-340.2862543680087132115924087095785234254896816433824.24%331069.70%1964184652.22%912175651.94%668129951.42%168794917367431413699
6Checkers321000001073220000009451010000013-240.6671016260087132115976870957852347134206610440.00%10190.00%0964184652.22%912175651.94%668129951.42%168794917367431413699
7Comets3100011012102100000105412100010076150.83312183000871321159100870957852341053820556116.67%10190.00%1964184652.22%912175651.94%668129951.42%168794917367431413699
8Condors220000001394110000006511100000074341.000132134008713211597087095785234751618347114.29%9188.89%3964184652.22%912175651.94%668129951.42%168794917367431413699
9Crunch32001000171252100100010731100000075261.00017274400871321159122870957852341092724538337.50%12466.67%0964184652.22%912175651.94%668129951.42%168794917367431413699
10Eagles4220000020182211000001064211000001012-240.500203757008713211591238709578523413341248318633.33%12283.33%0964184652.22%912175651.94%668129951.42%168794917367431413699
11Griffins2110000067-11010000035-21100000032120.5006814108713211597987095785234671614409333.33%7185.71%0964184652.22%912175651.94%668129951.42%168794917367431413699
12Icehogs31200000811-3211000007701010000014-320.33381422008713211591048709578523411629226514214.29%11281.82%1964184652.22%912175651.94%668129951.42%168794917367431413699
13Islander30200001815-720200000511-61000000134-110.1678152300871321159101870957852341044720531300.00%10640.00%0964184652.22%912175651.94%668129951.42%168794917367431413699
14Marlies32001000181082100100010731100000083561.0001834520087132115910587095785234963714638112.50%70100.00%1964184652.22%912175651.94%668129951.42%168794917367431413699
15Moose2010100079-2100010004311010000036-320.50071017008713211596087095785234682022303133.33%12375.00%0964184652.22%912175651.94%668129951.42%168794917367431413699
16Penguins330000001486220000008531100000063361.00014233700871321159111870957852341064016661218.33%8275.00%0964184652.22%912175651.94%668129951.42%168794917367431413699
17Phantoms220000001293110000007611100000053241.0001222340087132115978870957852347625143911218.18%7185.71%1964184652.22%912175651.94%668129951.42%168794917367431413699
18Punishers64200000282713210000017170321000001110180.6672846740087132115919887095785234225645212028725.00%26869.23%1964184652.22%912175651.94%668129951.42%168794917367431413699
19Reign20200000810-21010000045-11010000045-100.00081220008713211596187095785234771712437228.57%6266.67%1964184652.22%912175651.94%668129951.42%168794917367431413699
20Rocket302001001015-51000010034-120200000711-410.16710192900871321159898709578523411328246412325.00%12191.67%0964184652.22%912175651.94%668129951.42%168794917367431413699
21Senators3210000015105110000007252110000088040.6671527420087132115991870957852347240126916531.25%60100.00%0964184652.22%912175651.94%668129951.42%168794917367431413699
22Silver Knights31100100131301010000045-12100010098130.50013233600871321159112870957852349533185513323.08%9277.78%1964184652.22%912175651.94%668129951.42%168794917367431413699
23Thunderbirds73400000282713210000015132413000001314-160.4292849770087132115923787095785234237847016232618.75%35780.00%0964184652.22%912175651.94%668129951.42%168794917367431413699
24Wolfpack311001001314-11000010034-1211000001010030.50013223510871321159988709578523410636145913215.38%7271.43%0964184652.22%912175651.94%668129951.42%168794917367431413699
25Wranglers320010001495220000007341000100076161.0001425390087132115910987095785234932524599444.44%12375.00%0964184652.22%912175651.94%668129951.42%168794917367431413699
Total80392904413339314254020130321117415717401916012021651578950.59433957791620871321159269987095785234274489258016543046922.70%2906079.31%12964184652.22%912175651.94%668129951.42%168794917367431413699
_Since Last GM Reset80392904413339314254020130321117415717401916012021651578950.59433957791620871321159269987095785234274489258016543046922.70%2906079.31%12964184652.22%912175651.94%668129951.42%168794917367431413699
_Vs Conference48221801313202197524119011111071034241190020295941540.5632023455471087132115916238709578523416555613649861894121.69%1814674.59%4964184652.22%912175651.94%668129951.42%168794917367431413699
_Vs Division20810000028188-7944000014448-41146000013740-3180.450811382190087132115967587095785234716237190446932122.58%942573.40%2964184652.22%912175651.94%668129951.42%168794917367431413699

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8095L433957791626992744892580165420
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8039294413339314
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4020133211174157
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4019161202165157
Derniers 10 matchs
WLOTWOTL SOWSOL
451000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3046922.70%2906079.31%12
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
87095785234871321159
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
964184652.22%912175651.94%668129951.42%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
168794917367431413699


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
12Little Stars6Thunderbirds1WR1Sommaire du match
25Little Stars6Canucks5WSommaire du match
424Canucks6Little Stars5LXXR1Sommaire du match
741Thunderbirds8Little Stars4LR1Sommaire du match
848Little Stars3Thunderbirds5LSommaire du match
1267Little Stars3Canucks4LXXR1Sommaire du match
1475Punishers3Little Stars6WR1Sommaire du match
1896Bears6Little Stars5LSommaire du match
20110Little Stars4Punishers2WR1Sommaire du match
22119Wranglers1Little Stars3WSommaire du match
26139Crunch3Little Stars5WSommaire du match
28151Little Stars3Punishers2WR1Sommaire du match
30163Punishers4Little Stars9WSommaire du match
32172Little Stars2Comets3LXSommaire du match
36191Checkers3Little Stars5WSommaire du match
39210Barracuda4Little Stars3LSommaire du match
41218Little Stars6Barracuda2WSommaire du match
45236Comets4Little Stars5WXXSommaire du match
47247Little Stars4Punishers6LR1Sommaire du match
49255Little Stars5Bears3WSommaire du match
53271Senators2Little Stars7WSommaire du match
56289Little Stars1Checkers3LSommaire du match
58297Wranglers2Little Stars4WSommaire du match
60307Little Stars7Silver Knights5WSommaire du match
62322Little Stars6Penguins3WSommaire du match
63328Reign5Little Stars4LSommaire du match
66342Little Stars5Comets3WSommaire du match
67350Little Stars8Marlies3WSommaire du match
69360Icehogs3Little Stars5WSommaire du match
72378Rocket4Little Stars3LXSommaire du match
74390Little Stars1Thunderbirds4LR1Sommaire du match
77401Little Stars5Americans3WSommaire du match
79410Icehogs4Little Stars2LSommaire du match
82426Little Stars3Wolfpack5LSommaire du match
83434Eagles2Little Stars8WSommaire du match
87456Silver Knights5Little Stars4LSommaire du match
89468Little Stars1Canucks2LR1Sommaire du match
91474Little Stars3Islander4LXXSommaire du match
93484Little Stars1Icehogs4LSommaire du match
94492Admirals1Little Stars2WSommaire du match
98511Thunderbirds3Little Stars5WR1Sommaire du match
100527Little Stars7Wolfpack5WSommaire du match
102537Griffins5Little Stars3LSommaire du match
104546Little Stars3Moose6LSommaire du match
107562Americans2Little Stars4WSommaire du match
112588Phantoms6Little Stars7WSommaire du match
114595Little Stars3Griffins2WSommaire du match
117613Punishers10Little Stars2LR1Sommaire du match
121635Condors5Little Stars6WSommaire du match
123650Little Stars5Phantoms3WSommaire du match
125660Thunderbirds2Little Stars6WR1Sommaire du match
126669Little Stars4Senators2WSommaire du match
130687Marlies4Little Stars6WSommaire du match
132701Little Stars3Canucks5LR1Sommaire du match
134711Eagles4Little Stars2LSommaire du match
135720Little Stars7Condors4WSommaire du match
138735Little Stars4Reign5LSommaire du match
140740Little Stars7Wranglers6WXSommaire du match
141749Wolfpack4Little Stars3LXSommaire du match
144768Marlies3Little Stars4WXSommaire du match
147788Little Stars7Crunch5WSommaire du match
148795Canucks4Little Stars2LR1Sommaire du match
152815Canucks8Little Stars5LSommaire du match
155825Little Stars3Thunderbirds4LR1Sommaire du match
158843Bears3Little Stars4WSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
160850Little Stars2Admirals3LSommaire du match
164869Moose3Little Stars4WXSommaire du match
166877Little Stars4Senators6LSommaire du match
169895Penguins4Little Stars5WSommaire du match
170900Little Stars2Silver Knights3LXSommaire du match
174920Penguins1Little Stars3WSommaire du match
178943Checkers1Little Stars4WSommaire du match
181961Little Stars4Admirals3WSommaire du match
183971Crunch4Little Stars5WXSommaire du match
184980Little Stars4Rocket6LSommaire du match
186989Little Stars6Eagles4WSommaire du match
188999Islander5Little Stars3LSommaire du match
1901005Little Stars3Rocket5LSommaire du match
1931015Little Stars4Eagles8LSommaire du match
1991035Islander6Little Stars2LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance74,55836,968
Assistance PCT93.20%92.42%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2788 - 92.94% 175,817$7,032,667$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,646,590$ 1,802,000$ 1,672,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,965$ 1,883,534$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 1 12,697$ 12,697$




Little Stars Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

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 des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

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