Rampage
GP: 11 | W: 4 | L: 7
GF: 48 | GA: 53 | PP%: 23.26% | PK%: 72.00%
DG: Julie Coulombe | Morale : 45 | Moyenne d'Équipe : 62
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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
1Martin HanzalX100.006742657667817375737475686970632579710281995,000$
2Alexandre Grenier (R)X100.006833747478807170707767716765584484700242900,000$
3Blake Pietila (R)X100.007435717575717375707773686553485169700222900,000$
4Max Friberg (R)X100.006331807270736970727568726753514585690232800,000$
5Kyle Rau (R)X100.006721836968817270747468696454524484680232700,000$
6Sebastian Aho (R)X100.004933797854695376636669548740408286650182500,000$
7Thomas Spelling (R)X100.00583175766465677657596551684744396063X0223500,000$
8Lawson Crouse (R)X100.007845656170528070486269604640408785620182500,000$
9Victor Olofsson (R)X100.005128766971716669615571536842417285620191500,000$
10Matthew Highmore (R)X100.006421744962626463656663356241416484570192500,000$
11Anton Karlsson (R)X100.005423596751524266495952556341416365550191500,000$
12Fredrik Olofsson (R)X100.006542495062467159506250424641415966530191500,000$
13Jamie Oleksiak (R)X100.007834717673755969497264755559514451710231800,000$
14Damon Severson (R)X100.0075278669687879735272776568524358857002131,100,000$
15Michael Stone (R)X100.006936807578756775567064726357473741700251999,999$
16Joe Morrow (R)X100.006425747863657376447662695355534586680232550,000$
17Anton Lindholm (R)X100.006431796061596564426250825245445980640201500,000$
18Jakub Zboril (R)X100.006341726360616359336455624640407954600182500,000$
Rayé
1Austin Wuthrich (R)X100.007424646170576971635860555846453722600221500,000$
2Nolan Vesey (R)X100.007334646565477365556254494842435323580201500,000$
3Eric Robinson (R)X100.004930676456626259525471366145456276570202500,000$
4Cameron Darcy (R)X100.004139645646706560666769354547454120570211500,000$
5Vaclav Karabacek (R)X100.005328717142564764525256376741415723540191500,000$
6Kevin Stenlund (R)X100.006029555269525858525952444743415823530192500,000$
7Zachary Senyshyn (R)X100.004030686646534955585349466640407123520182500,000$
8Dylan Sadowy (R)X100.005541554959536353485561394241415226520191500,000$
9Kyle Pettit (R)X100.004541594751595451535561354641415220510191500,000$
10Jeffrey FossX100.007232747372687372626963706167632868690272800,000$
11Louis Belpedio (R)X100.005526644347494943304455424741415020470191500,000$
MOYENNE D'ÉQUIPE100.00623270656364646656646356594846545861
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
1Laurent Brossoit100.00807073777668718171698549455085720
2Ebbe Siönäs100.00446851575156616973644942425685590
Rayé
MOYENNE D'ÉQUIPE100.0062696267646266757267674644538566
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ron Wilson83816466557149USA562500,000$


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
1Martin HanzalRampage (Vgs)C1131518125521254119207.32%625323.0825712350000510054.34%39295001.4200001002
2Blake PietilaRampage (Vgs)LW11106165200181854132418.52%724622.424159360001491072.00%25146001.3000000201
3Alexandre GrenierRampage (Vgs)RW1141014-114016153492911.76%823221.110555360001270055.17%2975001.2100000001
4Max FribergRampage (Vgs)RW116511280121029131720.69%618416.771123280000250033.33%374011.1900000100
5Kyle RauRampage (Vgs)C11561160091424101620.83%215814.412134190001102050.49%10394001.3900000010
6Thomas SpellingRampage (Vgs)RW1155101406837112213.51%111910.8300001000000075.00%493001.6800000001
7Joe MorrowRampage (Vgs)D112793100151522969.09%1221719.74011124000137100.00%056000.8300000000
8Michael StoneRampage (Vgs)D11268212013141211816.67%2228025.52000233000152000.00%0815000.5700000000
9Damon SeversonRampage (Vgs)D110559202228239110.00%1329626.92000322000062000.00%0129000.3400000010
10Jamie OleksiakRampage (Vgs)D102351802521174611.76%919819.86112536000125000.00%058000.5000000100
11Jeffrey FossRampage (Vgs)D714546091085112.50%913919.88011015000128000.00%027000.7200000010
12Lawson CrouseRampage (Vgs)LW1122403002811103420.00%418116.500002280000140010.00%1001000.4400000000
13Victor OlofssonRampage (Vgs)RW1121300055174911.76%4958.67000000000170046.15%1321000.6300000000
14Cameron DarcyRampage (Vgs)C9022000357220.00%19210.2400000000000049.23%6510000.4300000000
15Fredrik OlofssonRampage (Vgs)LW110220401231210.00%1655.99000000000200100.00%101000.6100000000
16Nolan VeseyRampage (Vgs)LW6112-1408252320.00%1416.860000000000000.00%302000.9700000000
17Anton KarlssonRampage (Vgs)LW112023003472228.57%3787.150000200000000.00%321000.5100000000
18Eric RobinsonRampage (Vgs)LW61010001120250.00%0294.980000000001000.00%022000.6700000000
19Anton LindholmRampage (Vgs)D11011-300493340.00%1112611.470000100001000.00%004000.1600000000
20Sebastian AhoRampage (Vgs)C2000-120152210.00%03115.5000018000010043.75%1600000.0000000000
21Jakub ZborilRampage (Vgs)D8000-320212000.00%1526.560000000009000.00%003000.0000000000
22Matthew HighmoreRampage (Vgs)C11000240634110.00%0766.9800000000000048.39%3101000.0000000000
23Zachary SenyshynRampage (Vgs)RW6000000000000.00%000.050000000000000.00%000000.0000000000
24Austin WuthrichRampage (Vgs)RW6000000010000.00%030.5600001000000025.00%400000.0000000000
25Vaclav KarabacekRampage (Vgs)RW6000000100000.00%0111.91000000000100042.86%700000.0000000000
Stats d'équipe Total ou en Moyenne231488112930155524022836113418913.30%121321213.911016264733400074294052.05%7099488010.8000001435
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
1Laurent BrossoitRampage (Vgs)114310.8784.175040035286149100.000083010
2Ebbe SiönäsRampage (Vgs)40300.7796.3816000177740010.000038000
Stats d'équipe Total ou en Moyenne154610.8574.696650052363189110.00001111010


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
Alexandre GrenierRampage (Vgs)RW241991-01-01Yes200 Lbs6 ft5NoNoNo2Pro & Farm900,000$0$0$No995,000$
Anton KarlssonRampage (Vgs)LW191996-01-01Yes194 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Anton LindholmRampage (Vgs)D201995-01-01Yes191 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Austin WuthrichRampage (Vgs)RW221993-01-01Yes190 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$No
Blake PietilaRampage (Vgs)LW221993-01-01Yes200 Lbs5 ft11NoNoNo2Pro & Farm900,000$0$0$No995,000$
Cameron DarcyRampage (Vgs)C211994-01-01Yes190 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Damon SeversonRampage (Vgs)D211994-01-01Yes190 Lbs6 ft1NoNoNo3Pro & Farm1,100,000$0$0$No1,600,000$2,500,000$
Dylan SadowyRampage (Vgs)LW191996-01-01Yes205 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Ebbe SiönäsRampage (Vgs)G201995-01-01No185 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
Eric RobinsonRampage (Vgs)LW201995-01-01Yes197 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$
Fredrik OlofssonRampage (Vgs)LW191996-01-01Yes204 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$No
Jakub ZborilRampage (Vgs)D181997-01-01Yes200 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Jamie OleksiakRampage (Vgs)D231992-01-01Yes255 Lbs6 ft7NoNoNo1Pro & Farm800,000$0$0$No
Jeffrey FossRampage (Vgs)D271988-01-01No205 Lbs6 ft2NoNoNo2Pro & Farm800,000$0$0$No800,000$
Joe MorrowRampage (Vgs)D231992-01-01Yes199 Lbs6 ft0NoNoNo2Pro & Farm550,000$0$0$No600,000$
Kevin StenlundRampage (Vgs)C191996-01-01Yes209 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$
Kyle PettitRampage (Vgs)C191996-01-01Yes200 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$No
Kyle RauRampage (Vgs)C231992-01-01Yes178 Lbs5 ft8NoNoNo2Pro & Farm700,000$0$0$No800,000$
Laurent BrossoitRampage (Vgs)G221993-01-01No202 Lbs6 ft3NoNoNo2Pro & Farm850,000$0$0$No950,000$
Lawson CrouseRampage (Vgs)LW181997-01-01Yes220 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$
Louis BelpedioRampage (Vgs)D191996-01-01Yes196 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Martin HanzalRampage (Vgs)C281987-01-01No226 Lbs6 ft6NoNoNo1Pro & Farm995,000$0$0$No
Matthew HighmoreRampage (Vgs)C191996-01-01Yes188 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
Max FribergRampage (Vgs)RW231992-01-01Yes200 Lbs5 ft11NoNoNo2Pro & Farm800,000$0$0$No850,000$
Michael StoneRampage (Vgs)D251990-01-01Yes207 Lbs6 ft3NoNoNo1Pro & Farm999,999$0$0$No
Nolan VeseyRampage (Vgs)LW201995-01-01Yes210 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$No
Sebastian AhoRampage (Vgs)C181997-01-01Yes176 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Thomas SpellingRampage (Vgs)RW221993-01-01Yes176 Lbs6 ft1NoYesNo3Pro & Farm500,000$0$0$No500,000$500,000$
Vaclav KarabacekRampage (Vgs)RW191996-01-01Yes195 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Victor OlofssonRampage (Vgs)RW191996-01-01Yes181 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Zachary SenyshynRampage (Vgs)RW181997-01-01Yes192 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3120.94199 Lbs6 ft11.61625,645$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Lawson CrouseMartin HanzalAlexandre Grenier40122
2Blake PietilaSebastian AhoMax Friberg30122
3Anton KarlssonKyle RauThomas Spelling20122
4Fredrik OlofssonMatthew HighmoreVictor Olofsson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Michael StoneDamon Severson40122
2Jamie OleksiakJoe Morrow30122
3Anton LindholmFredrik Olofsson30122
4Michael StoneDamon Severson0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Blake PietilaMartin HanzalAlexandre Grenier60122
2Lawson CrouseSebastian AhoMax Friberg40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Michael StoneJamie Oleksiak60122
2Damon SeversonJoe Morrow40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Martin HanzalBlake Pietila60122
2Alexandre GrenierMax Friberg40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Michael StoneDamon Severson60122
2Jamie OleksiakJoe Morrow40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Martin Hanzal60122Michael StoneJamie Oleksiak60122
2Sebastian Aho40122Damon SeversonJoe Morrow40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Martin HanzalBlake Pietila60122
2Alexandre GrenierMax Friberg40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jamie OleksiakDamon Severson60122
2Anton LindholmJoe Morrow40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Blake PietilaSebastian AhoThomas SpellingMichael StoneDamon Severson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Blake PietilaMartin HanzalAlexandre GrenierMichael StoneDamon Severson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Anton Karlsson, Thomas Spelling, Victor OlofssonAnton Karlsson, Thomas SpellingVictor Olofsson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Anton Lindholm, Joe Morrow, Jakub ZborilAnton LindholmJoe Morrow, Jakub Zboril
Tirs de Pénalité
Martin Hanzal, Blake Pietila, Alexandre Grenier, Max Friberg, Kyle Rau
Gardien
#1 : Ebbe Siönäs, #2 : Laurent Brossoit


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
1Little Stars74300000342954310000024195312000001010080.57134589210142014024111013211812397010314322627.27%491275.51%012925350.99%13527149.82%10518556.76%23412623010720196
2Thunderbirds404000001424-1020200000912-320200000512-700.000142337001420140120110132118112551529721419.05%26965.38%012925350.99%13527149.82%10518556.76%23412623010720196
Total1147000004853-56330000033312514000001522-780.36448811291014201403611101321181364121155240431023.26%752172.00%012925350.99%13527149.82%10518556.76%23412623010720196
_Since Last GM Reset1147000004853-56330000033312514000001522-780.36448811291014201403611101321181364121155240431023.26%752172.00%012925350.99%13527149.82%10518556.76%23412623010720196
_Vs Conference1147000004853-56330000033312514000001522-780.36448811291014201403611101321181364121155240431023.26%752172.00%012925350.99%13527149.82%10518556.76%23412623010720196

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
118L3488112936136412115524010
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
114700004853
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
63300003331
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
51400001522
Derniers 10 Matchs
WLOTWOTL SOWSOL
360100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
431023.26%752172.00%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
11013211811420140
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
12925350.99%13527149.82%10518556.76%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
23412623010720196


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 Stars3Rampage7WSommaire du Match
2 - 2020-10-1014Little Stars4Rampage5WSommaire du Match
3 - 2020-10-1122Rampage5Little Stars1WSommaire du Match
4 - 2020-10-1230Rampage2Little Stars3LSommaire du Match
5 - 2020-10-1338Little Stars7Rampage5LSommaire du Match
6 - 2020-10-1446Rampage3Little Stars6LSommaire du Match
7 - 2020-10-1554Little Stars5Rampage7WSommaire du Match
8 - 2020-10-1660Thunderbirds7Rampage6LXSommaire du Match
9 - 2020-10-1764Thunderbirds5Rampage3LSommaire du Match
10 - 2020-10-1868Rampage1Thunderbirds6LSommaire du Match
11 - 2020-10-1972Rampage4Thunderbirds6LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets4020
Assistance10,0825,140
Assistance PCT84.02%85.67%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
34 2537 - 84.57% 88,564$531,384$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 1,939,500$ 1,769,500$ 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