Little Stars
GP: 7 | W: 3 | L: 4
GF: 29 | GA: 34 | PP%: 24.49% | PK%: 72.73%
DG: François Cloutier | Morale : 11 | 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)X100.006736827272777474676586667254484952710231975,000$
2Dana TyrellX100.007132807271817772737574696260533454710261825,000$
3Jesse JoensuuX100.007333737274707973657568646967582374690281800,000$
4Ilya Mikheyev (R)X100.007349796667747273746663586645465173660212500,000$
5Scott Kosmachuck (R)X100.007134747271607670557669635947454763660212550,000$
6Joakim Nygard (R)X100.005340797366595579706859598246495362650222500,000$
7Adam Tambellini (R)X100.005929766680726465667180456144434673650214600,000$
8Daniel O'regan (R)X100.006228766660737068707669535544434772640212400,000$
9Michael Mersch (R)X100.006535726972656569635574506954544257640232500,000$
10Sebastian Wannstrom (R)X100.006229686869676464707070485953533372630241350,000$
11Roman Horak (R)X100.005939756859676570726960475146462851620243300,000$
12Zach Budish (R)X100.006932756266626360647069536148463472620241500,000$
13Tyler Wotherspoon (R)X100.007026867473737269507258796253445170710222900,000$
14Patrick Wiercioch (R)X100.006733747465676969486959705253483472670251350,000$
15Eric Knodel (R)X100.007334686966776366426856685156533238660252500,000$
16Anton Cederholm (R)X100.006427826371666654447257784345425772660204750,000$
17Reece Willcox (R)X100.005929737262626963466552735944435072630212375,000$
18Tucker Poolman (R)X100.006633687364595663576548605646454772610224600,000$
Rayé
1Emile Poirier (R)X100.005128786771626460606177486945434920620213550,000$
2Daniil Tarasov (R)X100.006230676167615865696565545954543119610241300,000$
3Jason Dickinson (R)X100.006332726561606668706265507042426441610204500,000$
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)X100.006236686058626065336461565343435120590211350,000$
12Lawrence Pilut (R)X100.005934675257566261396156525045426420560202500,000$
MOYENNE D'ÉQUIPE100.00623273656465656560676455594746484862
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 Tokarski100.00716781686577766967736764563372700
2Connor Knapp100.00725967747568636373667252523072680
Rayé
1Peter Delmas100.00636773687467667264636748483320670
MOYENNE D'ÉQUIPE100.0069647470717168686867695552325568
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)LW74812-680792862114.29%415722.482357410000141029.41%1774001.5300000020
2Ilya MikheyevLittle Stars (Dal)RW75510-2201092241722.73%612317.60336935000000166.67%664001.6200000101
3Dana TyrellLittle Stars (Dal)C76410-60013193141519.35%216223.193259410000191145.98%26154001.2300000200
4Evgeny KuznetsovLittle Stars (Dal)C7178-320816286103.57%415121.67055637000060041.51%5363001.0500000000
5Tyler WotherspoonLittle Stars (Dal)D7167-4175101216576.25%1419327.70112646000119000.00%064000.7200001000
6Daniel O'reganLittle Stars (Dal)C7336-220313107330.00%011316.24112222000071052.78%7222001.0600000000
7Joakim NygardLittle Stars (Dal)LW7134-220131911105.26%28612.3900002000060050.00%441000.9200000000
8Roman HorakLittle Stars (Dal)C7123-20073102310.00%37110.2500000000020055.00%4002000.8400000000
9Adam TambelliniLittle Stars (Dal)LW7213-2801161121018.18%012317.66112535000000033.33%392000.4900000000
10Eric KnodelLittle Stars (Dal)D7123-22011673214.29%614520.80101429000011000.00%025000.4100000000
11Anton CederholmLittle Stars (Dal)D7033-100795110.00%814520.75000029000012000.00%026000.4100000010
12Patrick WierciochLittle Stars (Dal)D7033-56011811510.00%2019928.47033246000018000.00%038000.3000000000
13Sebastian WannstromLittle Stars (Dal)RW7202-20010482425.00%07410.7100000000000075.00%401000.5300000000
14Scott KosmachuckLittle Stars (Dal)RW7112-4208313437.69%2699.86011015000060050.00%610100.5800000000
15Michael MerschLittle Stars (Dal)LW7101-1003311439.09%2446.4000001000000050.00%231000.4500000000
16Zach BudishLittle Stars (Dal)RW7000-140346230.00%0466.570000000000000.00%011000.0000000000
17Reece WillcoxLittle Stars (Dal)D7000-620690100.00%107711.140000000002000.00%002000.0000000000
18Tucker PoolmanLittle Stars (Dal)D7000-420973110.00%77811.180000000000000.00%014000.0000000000
Stats d'équipe Total ou en Moyenne126294877-555951381432397011412.13%90206516.391220325038500011303247.22%4685854100.7500001331
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)52200.8505.24229002013358000.000052001
2Dustin TokarskiLittle Stars (Dal)41200.8704.44189001410852100.000025000
Stats d'équipe Total ou en Moyenne93400.8594.884180034241110100.000077001


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 TyrellEvgeny Kuznetsov40122
2Adam TambelliniDaniel O'reganIlya Mikheyev30122
3Joakim NygardRoman HorakSebastian Wannstrom20122
4Michael MerschEvgeny KuznetsovZach 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 TyrellEvgeny Kuznetsov60014
2Adam TambelliniDaniel O'reganIlya Mikheyev40023
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler WotherspoonPatrick Wiercioch60014
2Anton CederholmEric Knodel40014
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
1Rampage734000002934-53210000010100413000001924-560.4292948770011513023977907202419059138491224.49%22672.73%09419049.47%8316749.70%4411139.64%146791506712263
Total734000002934-53210000010100413000001924-560.4292948770011513023977907202419059138491224.49%22672.73%09419049.47%8316749.70%4411139.64%146791506712263
_Since Last GM Reset734000002934-53210000010100413000001924-560.4292948770011513023977907202419059138491224.49%22672.73%09419049.47%8316749.70%4411139.64%146791506712263
_Vs Conference734000002934-53210000010100413000001924-560.4292948770011513023977907202419059138491224.49%22672.73%09419049.47%8316749.70%4411139.64%146791506712263

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
76L1294877239241905913800
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
73400002934
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
32100001010
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
41300001924
Derniers 10 Matchs
WLOTWOTL SOWSOL
340000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
491224.49%22672.73%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
7790720115130
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
9419049.47%8316749.70%4411139.64%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
146791506712263


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
1 - 2020-10-096Little Stars3Rampage7LR2Sommaire du Match
2 - 2020-10-1014Little Stars4Rampage5LSommaire du Match
3 - 2020-10-1122Rampage5Little Stars1LR2Sommaire du Match
4 - 2020-10-1230Rampage2Little Stars3WSommaire du Match
5 - 2020-10-1338Little Stars7Rampage5WR2Sommaire du Match
6 - 2020-10-1446Rampage3Little Stars6WSommaire du Match
7 - 2020-10-1554Little Stars5Rampage7LR2Sommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets4020
Assistance4,5972,595
Assistance PCT76.62%86.50%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
37 2397 - 79.91% 82,523$247,569$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 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
0$ 0$ 0 0

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