Little Stars
GP: 80 | W: 41 | L: 33 | OTL: 6 | P: 88
GF: 380 | GA: 367 | PP%: 25.96% | PK%: 75.92%
DG: François Cloutier | Morale : 42 | Moyenne d'Équipe : 63
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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
1Evgeny Kuznetsov (R)X100.006736827272777474676586667254484942710231975,000$
2Dana TyrellX100.007132807271817772737574696260533444710261825,000$
3Jesse JoensuuX100.007333737274707973657568646967582365690281800,000$
4Ilya Mikheyev (R)X100.007349796667747273746663586645465163660212500,000$
5Scott Kosmachuck (R)X100.007134747271607670557669635947454753660212550,000$
6Joakim Nygard (R)X100.005340797366595579706859598246495352650222500,000$
7Adam Tambellini (R)X100.005929766680726465667180456144434663650214600,000$
8Daniel O'regan (R)X100.006228766660737068707669535544434762640212400,000$
9Michael Mersch (R)X100.006535726972656569635574506954544247640232500,000$
10Sebastian Wannstrom (R)X100.006229686869676464707070485953533362630241350,000$
11Roman Horak (R)X100.005939756859676570726960475146462841620243300,000$
12Zach Budish (R)X100.006932756266626360647069536148463462620241500,000$
13Tyler Wotherspoon (R)X100.007026867473737269507258796253445159710222900,000$
14Patrick Wiercioch (R)X100.006733747465676969486959705253483462670251350,000$
15Eric Knodel (R)X100.007334686966776366426856685156533228660252500,000$
16Anton Cederholm (R)X100.006427826371666654447257784345425762660204750,000$
17Reece Willcox (R)X100.005929737262626963466552735944435062630212375,000$
18Tucker Poolman (R)X100.006633687364595663576548605646454762610224600,000$
Rayé
1Emile Poirier (R)X100.005128786771626460606177486945434920620213550,000$
2Daniil Tarasov (R)X100.006230676167615865696565545954543119610241300,000$
3Jason Dickinson (R)X100.006332726561606668706265507042426443610204500,000$
4Shane Gersich (R)X100.005935766752637272757462375141417320610191500,000$
5Justin Auger (R)X100.005626725462676256596969396645445020580213500,000$
6Radel Fazleev (R)X100.004631696248636160717362435041415620580191500,000$
7Rudolfs Balcers (R)X100.005633655248605249565162455640406920520182500,000$
8Jean-Christophe Beaudin (R)X100.004821595045515860586554364840407720520182500,000$
9Julien Nantel (R)X100.004740625152605551555560394741415220520191500,000$
10Yakov Trenin (R)X100.006030615359564959475149385440405920510182500,000$
11Ville Pokka (R)X100.006236686058626065336461565343435115590211350,000$
12Lawrence Pilut (R)X100.005934675257566261396156525045426420560202500,000$
MOYENNE D'ÉQUIPE100.00623273656465656560676455594746484262
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 SP
1Dustin Tokarski100.00716781686577766967736764563362700
2Connor Knapp100.00725967747568636373667252523062680
Rayé
1Peter Delmas100.00636773687467667264636748483320670
MOYENNE D'ÉQUIPE100.0069647470717168686867695552324868
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Claude Julien82837474596155CAN5121,000,000$


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
1Jesse JoensuuLittle Stars (Dal)LW775781138157151649834412020816.57%49170922.202230526630931481645245.00%1807729131.61261007115
2Scott KosmachuckLittle Stars (Dal)RW79547112518835135852687214920.15%45157919.99192948552990005775348.23%1415523001.5833000668
3Dana TyrellLittle Stars (Dal)C61357410912601081352236713315.70%34134922.12730373221413451993154.46%19303127121.6236000755
4Evgeny KuznetsovLittle Stars (Dal)C60374279-5140931182157113517.21%45126821.141418323520701121622248.08%15393428011.2525000641
5Ilya MikheyevLittle Stars (Dal)RW80323567-2729515273172539918.60%28134116.77151227442480002462051.92%523222001.0013001234
6Daniel O'reganLittle Stars (Dal)C80234063-122407897171539813.45%16114414.313811111351122645048.77%6932319001.1002000120
7Adam TambelliniLittle Stars (Dal)LW80253459-2045586611804610213.89%21126715.854111521242000032256.92%654515000.9300001123
8Tyler WotherspoonLittle Stars (Dal)D79134659-121409616816563707.88%143224528.4361521333490223257100.00%04679000.5302000012
9Joakim NygardLittle Stars (Dal)LW80272451-78043601995810113.57%2699812.481233364048723154.00%502613011.0201000604
10Patrick WierciochLittle Stars (Dal)D8083947-12106013715512154566.61%132223027.8861117203530000220110.00%03473000.4200000004
11Anton CederholmLittle Stars (Dal)D8052732-18180711308143296.17%83164520.5704452190110171000.00%0559100.3900000000
12Eric KnodelLittle Stars (Dal)D6052530-10340104855419289.26%62120520.0831481590110117200.00%01732100.5000000100
13Zach BudishLittle Stars (Dal)RW801513280606151103254214.56%176428.0300008000002050.00%141010000.8700000201
14Sebastian WannstromLittle Stars (Dal)RW8071623-13300895111332666.19%1886810.86011000004290143.18%442310000.5300000011
15Michael MerschLittle Stars (Dal)LW70111122-51605237110317210.00%86198.840110110111171055.56%273510000.7100000100
16Reece WillcoxLittle Stars (Dal)D8041822034044776227226.45%81112714.10101462000059200.00%0831000.3900000000
17Roman HorakLittle Stars (Dal)C629918-7155573984264810.71%1262210.03000010110330050.37%2701612000.5800000110
18Jason DickinsonLittle Stars (Dal)C5731518-28027337321404.11%34547.9800000000010048.88%17894000.7901000000
19Tucker PoolmanLittle Stars (Dal)D801781128070453415182.94%5599212.4100004000043000.00%0520000.1600000000
20Emile PoirierLittle Stars (Dal)LW13527620322381021.74%31058.1501102000011075.00%434001.3200000000
21Ville PokkaLittle Stars (Dal)D21033640131319320.00%1024411.6500000000011000.00%0514000.2500000000
22Daniil TarasovLittle Stars (Dal)RW1011000100120.00%12121.5001105000000033.33%311000.9300000000
Stats d'équipe Total ou en Moyenne14403766331009-9361525168416132814908153013.36%8922368516.45101175276337287391221401756371350.81%5190540535470.851129102413638
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)48211540.8644.502401001801320686420.643143842010
2Dustin TokarskiLittle Stars (Dal)46201820.8624.492434401821319626300.667124238201
Stats d'équipe Total ou en Moyenne94413360.8634.4948354036226391312720.654268080211


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 RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Adam TambelliniLittle Stars (Dal)LW211994-01-01Yes185 Lbs6 ft4NoNoNo4Pro & Farm600,000$0$0$No600,000$600,000$600,000$
Anton CederholmLittle Stars (Dal)D201995-01-01Yes185 Lbs6 ft2NoNoNo4Pro & Farm750,000$0$0$No750,000$750,000$750,000$
Connor KnappLittle Stars (Dal)G251990-01-01No206 Lbs6 ft6NoNoNo1Pro & Farm300,000$0$0$No
Dana TyrellLittle Stars (Dal)C261989-01-01No185 Lbs5 ft10NoNoNo1Pro & Farm825,000$0$0$No
Daniel O'reganLittle Stars (Dal)C211994-01-01Yes169 Lbs5 ft9NoNoNo2Pro & Farm400,000$0$0$No400,000$
Daniil TarasovLittle Stars (Dal)RW241991-01-01Yes185 Lbs6 ft0NoNoNo1Pro & Farm300,000$0$0$No
Dustin TokarskiLittle Stars (Dal)G261989-01-01No198 Lbs5 ft11NoNoNo1Pro & Farm800,000$0$0$No
Emile PoirierLittle Stars (Dal)LW211994-01-01Yes185 Lbs6 ft1NoNoNo3Pro & Farm550,000$0$0$No550,000$550,000$
Eric KnodelLittle Stars (Dal)D251990-01-01Yes216 Lbs6 ft6NoNoNo2Pro & Farm500,000$0$0$No500,000$
Evgeny KuznetsovLittle Stars (Dal)C231992-01-01Yes172 Lbs6 ft0NoNoNo1Pro & Farm975,000$0$0$No
Ilya MikheyevLittle Stars (Dal)RW211994-01-01Yes195 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$
Jason DickinsonLittle Stars (Dal)C201995-01-01Yes185 Lbs6 ft2NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$
Jean-Christophe BeaudinLittle Stars (Dal)C181997-01-01Yes196 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Jesse JoensuuLittle Stars (Dal)LW281987-01-01No209 Lbs6 ft4NoNoNo1Pro & Farm800,000$0$0$No
Joakim NygardLittle Stars (Dal)LW221993-01-01Yes179 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Julien NantelLittle Stars (Dal)LW191996-01-01Yes195 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Justin AugerLittle Stars (Dal)RW211994-01-01Yes185 Lbs6 ft7NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$
Lawrence PilutLittle Stars (Dal)D201995-01-01Yes194 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
Michael MerschLittle Stars (Dal)LW231992-01-01Yes218 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$
Patrick WierciochLittle Stars (Dal)D251990-01-01Yes192 Lbs6 ft4NoNoNo1Pro & Farm350,000$0$0$No
Peter DelmasLittle Stars (Dal)G251990-01-01No169 Lbs6 ft2NoNoNo1Pro & Farm575,000$0$0$No
Radel FazleevLittle Stars (Dal)C191996-01-01Yes192 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Reece WillcoxLittle Stars (Dal)D211994-01-01Yes184 Lbs6 ft3NoNoNo2Pro & Farm375,000$0$0$No375,000$
Roman HorakLittle Stars (Dal)C241991-01-01Yes170 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$
Rudolfs BalcersLittle Stars (Dal)LW181997-01-01Yes180 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
Scott KosmachuckLittle Stars (Dal)RW211994-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm550,000$0$0$No550,000$
Sebastian WannstromLittle Stars (Dal)RW241991-01-01Yes180 Lbs6 ft1NoNoNo1Pro & Farm350,000$0$0$No
Shane GersichLittle Stars (Dal)LW191996-01-01Yes175 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Tucker PoolmanLittle Stars (Dal)D221993-01-01Yes185 Lbs6 ft2NoNoNo4Pro & Farm600,000$0$0$No600,000$600,000$600,000$
Tyler WotherspoonLittle Stars (Dal)D221993-01-01Yes210 Lbs6 ft2NoNoNo2Pro & Farm900,000$0$0$No975,000$
Ville PokkaLittle Stars (Dal)D211994-01-01Yes205 Lbs5 ft11NoNoNo1Pro & Farm350,000$0$0$No
Yakov TreninLittle Stars (Dal)C181997-01-01Yes201 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$
Zach BudishLittle Stars (Dal)RW241991-01-01Yes223 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3322.03191 Lbs6 ft11.91534,848$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jesse JoensuuDana TyrellScott Kosmachuck40122
2Adam TambelliniEvgeny KuznetsovIlya Mikheyev30122
3Joakim NygardDaniel O'reganSebastian Wannstrom20122
4Michael MerschRoman HorakZach Budish10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler WotherspoonPatrick Wiercioch40122
2Anton CederholmEric Knodel30122
3Tucker PoolmanReece Willcox20122
4Tyler WotherspoonPatrick Wiercioch10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jesse JoensuuDana TyrellScott Kosmachuck60023
2Adam TambelliniEvgeny KuznetsovIlya Mikheyev40023
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler WotherspoonPatrick Wiercioch60023
2Anton CederholmEric Knodel40023
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Dana TyrellJesse Joensuu60032
2Evgeny KuznetsovScott Kosmachuck40032
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler WotherspoonPatrick Wiercioch60032
2Anton CederholmEric Knodel40032
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Dana Tyrell60032Tyler WotherspoonPatrick Wiercioch60032
2Evgeny Kuznetsov40032Anton CederholmEric Knodel40032
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Dana TyrellJesse Joensuu60023
2Evgeny KuznetsovScott Kosmachuck40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler WotherspoonPatrick Wiercioch60023
2Anton CederholmEric Knodel40023
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jesse JoensuuDana TyrellScott KosmachuckTyler WotherspoonPatrick Wiercioch
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jesse JoensuuDana TyrellScott KosmachuckTyler WotherspoonPatrick Wiercioch
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Evgeny Kuznetsov, Adam Tambellini, Daniel O'reganJoakim Nygard, Michael MerschDaniel O'regan
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Tucker Poolman, Anton Cederholm, Eric KnodelTucker PoolmanAnton Cederholm, Eric Knodel
Tirs de Pénalité
Dana Tyrell, Evgeny Kuznetsov, Jesse Joensuu, Scott Kosmachuck, Adam Tambellini
Gardien
#1 : Connor Knapp, #2 : Dustin Tokarski


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
LigueDomicileVisiteur
# 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
1Admirals30300000617-111010000026-420200000411-700.000691500118132123131078819909244511428235611218.18%11372.73%0975192350.70%922182050.66%740144751.14%171695616767481450725
2Barracuda211000001114-31010000038-51100000086220.50011193000118132123137188199092445711821398450.00%8450.00%0975192350.70%922182050.66%740144751.14%171695616767481450725
3Bears21100000131121010000058-31100000083520.500132235001181321231373881990924456224124813646.15%6266.67%0975192350.70%922182050.66%740144751.14%171695616767481450725
4Checkers42200000161601010000046-2321000001210240.50016264200118132123131258819909244513342349316318.75%18383.33%1975192350.70%922182050.66%740144751.14%171695616767481450725
5Comets612002102525030100200912-3311000101613360.5002539641011813212313209881990924451866844143361027.78%22768.18%0975192350.70%922182050.66%740144751.14%171695616767481450725
6Condors202000001114-31010000068-21010000056-100.00011162710118132123137188199092445651516395120.00%8450.00%1975192350.70%922182050.66%740144751.14%171695616767481450725
7Crunch32100000191452200000017981010000025-340.66719304900118132123131058819909244510845167316531.25%8187.50%1975192350.70%922182050.66%740144751.14%171695616767481450725
8Devils32100000171431100000075221100000109140.6671730470011813212313968819909244593351755201050.00%6183.33%0975192350.70%922182050.66%740144751.14%171695616767481450725
9Eagles420001012017331000101141401100000063360.750202949001181321231314488199092445139442611522627.27%13192.31%0975192350.70%922182050.66%740144751.14%171695616767481450725
10Griffins311000101091210000108531010000024-240.6671015250011813212313119881990924459828146218316.67%7185.71%0975192350.70%922182050.66%740144751.14%171695616767481450725
11Heat311010001815311000000743201010001111040.66718304800118132123131158819909244511139206114535.71%10280.00%1975192350.70%922182050.66%740144751.14%171695616767481450725
12IceHogs3200000113103210000019811100000042250.83313213400118132123131168819909244510841286116531.25%14378.57%1975192350.70%922182050.66%740144751.14%171695616767481450725
13Influenza2110000079-21010000028-61100000051420.5007121900118132123137288199092445692514389111.11%70100.00%1975192350.70%922182050.66%740144751.14%171695616767481450725
14Monsters2010001056-11010000024-21000001032120.5005611001181321231368881990924456821652900.00%30100.00%1975192350.70%922182050.66%740144751.14%171695616767481450725
15Moose21100000871110000006241010000025-320.50081321001181321231374881990924456717635400.00%3166.67%0975192350.70%922182050.66%740144751.14%171695616767481450725
16Penguins32100000121202200000010731010000025-340.667121830001181321231396881990924459641236120630.00%9277.78%0975192350.70%922182050.66%740144751.14%171695616767481450725
17Phantoms20200000711-41010000045-11010000036-300.0007142100118132123136088199092445712214308112.50%7185.71%0975192350.70%922182050.66%740144751.14%171695616767481450725
18Punishers935000014655-94210000123194514000002336-1370.389468112700118132123133258819909244528811489183501224.00%401562.50%1975192350.70%922182050.66%740144751.14%171695616767481450725
19Rampage3210000016115110000009272110000079-240.667162844001181321231394881990924459924405615213.33%20670.00%1975192350.70%922182050.66%740144751.14%171695616767481450725
20Reign211000001091110000008531010000024-220.50010152500118132123137488199092445592020401218.33%10280.00%0975192350.70%922182050.66%740144751.14%171695616767481450725
21Rocket210010001064110000007431000100032141.00010162600118132123137088199092445602414606116.67%70100.00%0975192350.70%922182050.66%740144751.14%171695616767481450725
22Senators3210000016972200000013581010000034-140.667162945001181321231310888199092445903426511119.09%14378.57%0975192350.70%922182050.66%740144751.14%171695616767481450725
23Sound Tigers211000001091110000005321010000056-120.5001019290011813212313768819909244562228359333.33%40100.00%0975192350.70%922182050.66%740144751.14%171695616767481450725
24Thunderbirds62201010292813110100019145311000101014-480.6672948770011813212313190881990924451915668120331236.36%34973.53%0975192350.70%922182050.66%740144751.14%171695616767481450725
25Wolfpack4310000025196211000001211122000000138560.7502548730011813212313156881990924451334520788112.50%10190.00%0975192350.70%922182050.66%740144751.14%171695616767481450725
Total8034330334338036713402012013132111822940142102030169185-16880.550380633101320118132123132814881990924452641892619168438910125.96%2997275.92%9975192350.70%922182050.66%740144751.14%171695616767481450725
_Since Last GM Reset8034330334338036713402012013132111822940142102030169185-16880.550380633101320118132123132814881990924452641892619168438910125.96%2997275.92%9975192350.70%922182050.66%740144751.14%171695616767481450725
_Vs Conference512418023222592352425145013021441083626101301020115127-12610.5982594366951011813212313176388199092445166758742310892617327.97%2045175.00%5975192350.70%922182050.66%740144751.14%171695616767481450725
_Vs Division216901221100108-8103301201514561136000204963-14210.5001001682681011813212313724881990924456652382014461193428.57%963167.71%1975192350.70%922182050.66%740144751.14%171695616767481450725

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8088W1380633101328142641892619168420
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8034333343380367
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4020121313211182
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4014212030169185
Derniers 10 Matchs
WLOTWOTL SOWSOL
630001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
38910125.96%2997275.92%9
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
8819909244511813212313
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
975192350.70%922182050.66%740144751.14%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
171695616767481450725


Derniers Match 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 - 2020-10-109Punishers5Little Stars3LSommaire du Match
4 - 2020-10-1220Little Stars5Punishers9LSommaire du Match
6 - 2020-10-1431Thunderbirds6Little Stars7WXSommaire du Match
7 - 2020-10-1537Little Stars3Punishers9LSommaire du Match
11 - 2020-10-1956Little Stars5Comets7LR1Sommaire du Match
13 - 2020-10-2172Punishers5Little Stars7WSommaire du Match
15 - 2020-10-2381Little Stars3Thunderbirds2WSommaire du Match
17 - 2020-10-2592Eagles5Little Stars4LXXR1Sommaire du Match
20 - 2020-10-28106Little Stars2Thunderbirds8LSommaire du Match
22 - 2020-10-30120Comets5Little Stars4LXR1Sommaire du Match
25 - 2020-11-02134Little Stars8Punishers6WSommaire du Match
28 - 2020-11-05150Penguins5Little Stars7WR2Sommaire du Match
30 - 2020-11-07162Little Stars3Checkers6LSommaire du Match
32 - 2020-11-09175Wolfpack7Little Stars6LSommaire du Match
34 - 2020-11-11184Little Stars7Devils3WSommaire du Match
36 - 2020-11-13196Senators3Little Stars8WR1Sommaire du Match
39 - 2020-11-16212Little Stars5Condors6LSommaire du Match
41 - 2020-11-18223Eagles4Little Stars3LXR1Sommaire du Match
43 - 2020-11-20233Little Stars5Influenza1WSommaire du Match
45 - 2020-11-22243Little Stars4IceHogs2WR1Sommaire du Match
47 - 2020-11-24255Punishers6Little Stars5LXXSommaire du Match
52 - 2020-11-29277Admirals6Little Stars2LSommaire du Match
55 - 2020-12-02295Condors8Little Stars6LSommaire du Match
57 - 2020-12-04306Little Stars3Rocket2WXSommaire du Match
61 - 2020-12-08326Senators2Little Stars5WR1Sommaire du Match
64 - 2020-12-11344Barracuda8Little Stars3LSommaire du Match
67 - 2020-12-14360Little Stars6Eagles3WR1Sommaire du Match
69 - 2020-12-16369Penguins2Little Stars3WSommaire du Match
71 - 2020-12-18376Little Stars5Heat6LSommaire du Match
75 - 2020-12-22396Reign5Little Stars8WR1Sommaire du Match
77 - 2020-12-24407Little Stars3Senators4LR1Sommaire du Match
79 - 2020-12-26421Rampage2Little Stars9WSommaire du Match
81 - 2020-12-28431Little Stars5Punishers8LSommaire du Match
84 - 2020-12-31448Checkers6Little Stars4LR1Sommaire du Match
87 - 2021-01-03461Little Stars3Monsters2WXXSommaire du Match
89 - 2021-01-05475Comets3Little Stars2LR1Sommaire du Match
92 - 2021-01-08486Little Stars7Comets3WSommaire du Match
94 - 2021-01-10501Wolfpack4Little Stars6WSommaire du Match
100 - 2021-01-16523Little Stars2Moose5LSommaire du Match
101 - 2021-01-17530Sound Tigers3Little Stars5WR1Sommaire du Match
104 - 2021-01-20542Little Stars5Rampage4WR1Sommaire du Match
107 - 2021-01-23555Little Stars2Punishers4LSommaire du Match
108 - 2021-01-24559Heat4Little Stars7WSommaire du Match
111 - 2021-01-27579Punishers3Little Stars8WSommaire du Match
113 - 2021-01-29593Little Stars8Bears3WSommaire du Match
115 - 2021-01-31605Monsters4Little Stars2LSommaire du Match
117 - 2021-02-02611Little Stars2Griffins4LSommaire du Match
119 - 2021-02-04623Little Stars5Sound Tigers6LR1Sommaire du Match
121 - 2021-02-06633Little Stars6Heat5WXSommaire du Match
122 - 2021-02-07639Devils5Little Stars7WSommaire du Match
126 - 2021-02-11660Griffins2Little Stars4WSommaire du Match
131 - 2021-02-16684Phantoms5Little Stars4LSommaire du Match
133 - 2021-02-18692Little Stars2Admirals6LSommaire du Match
135 - 2021-02-20703Little Stars2Crunch5LSommaire du Match
137 - 2021-02-22714Thunderbirds3Little Stars8WSommaire du Match
139 - 2021-02-24730Little Stars5Thunderbirds4WXXSommaire du Match
141 - 2021-02-26738Comets4Little Stars3LXR1Sommaire du Match
147 - 2021-03-04762Thunderbirds5Little Stars4LSommaire du Match
149 - 2021-03-06775Little Stars2Admirals5LSommaire du Match
151 - 2021-03-08787Influenza8Little Stars2LSommaire du Match
153 - 2021-03-10796Little Stars4Checkers3WR1Sommaire du Match
158 - 2021-03-15813Bears8Little Stars5LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
161 - 2021-03-18831Little Stars2Rampage5LR1Sommaire du Match
162 - 2021-03-19840Eagles5Little Stars7WSommaire du Match
165 - 2021-03-22853Little Stars8Barracuda6WSommaire du Match
168 - 2021-03-25866Moose2Little Stars6WSommaire du Match
170 - 2021-03-27880Little Stars4Comets3WXXR1Sommaire du Match
172 - 2021-03-29889Rocket4Little Stars7WSommaire du Match
174 - 2021-03-31899Little Stars2Reign4LR1Sommaire du Match
177 - 2021-04-03915Griffins3Little Stars4WXXSommaire du Match
178 - 2021-04-04920Little Stars7Wolfpack5WSommaire du Match
181 - 2021-04-07933Little Stars5Checkers1WR1Sommaire du Match
184 - 2021-04-10944Little Stars6Wolfpack3WSommaire du Match
186 - 2021-04-12950IceHogs4Little Stars3LXXR1Sommaire du Match
188 - 2021-04-14966Little Stars2Penguins5LR2Sommaire du Match
189 - 2021-04-15972Little Stars3Phantoms6LSommaire du Match
191 - 2021-04-17983Crunch7Little Stars10WSommaire du Match
195 - 2021-04-211001Crunch2Little Stars7WSommaire du Match
198 - 2021-04-241015Little Stars3Devils6LSommaire du Match
201 - 2021-04-271029IceHogs4Little Stars6WR1Sommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets4020
Assistance54,12727,364
Assistance PCT67.66%68.41%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
0 2037 - 67.91% 70,881$2,835,241$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,726,854$ 1,765,000$ 2,642,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
8,610$ 1,706,359$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 13,488$ 0$




LigueDomicileVisiteur
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