Phantoms

GP: 76 | W: 43 | L: 26 | OTL: 7 | P: 93
GF: 195 | GA: 146 | PP%: 16.94% | PK%: 86.70%
DG: Kriss Cardenas | Morale : 67 | 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 SP
1Colin McDonaldX100.007135935784939156585554585585795077620
2Seth GriffithXXX100.005237896267939161736456586271665577620
3Adam TambelliniXX100.006536925782949356605654585569656077610
4Tomas HykaX100.005235936365786562566461585971665377610
5Filip Zadina (R)X100.005635936473867263565961586359629177610
6Cory ConacherXXX100.005039816065787159626157585678704577600
7Chris ThorburnX100.007737725990726457545553585286764277600
8Scott KosmachukX100.005439825769908556585457535669656477590
9Patrick EavesXX100.006035935673725955565753565285754677580
10Landon FerraroXXX100.005340785769726856605654575575686477570
11Alex BiegaX100.009037756370756161307556685379714977660
12Oscar FantenbergX100.008143856276817461306759685375683674660
13Griffin ReinhartX100.007336905889949556305452594869658077650
14Cameron GaunceX100.006145796281876961306055674777695851640
15Andrew CampbellX100.007138845487928953305251574579715174630
16Matt TennysonX100.006637895981786658305753594677694677620
17Brian CooperX100.005337885566777154305650514771665541570
Rayé
MOYENNE D'ÉQUIPE100.00643886597683765847595559537569567361
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
1Peter Budaj100.00757472777473757473757487913476740
2Al Montoya100.00706866806968706968706984883031700
Rayé
MOYENNE D'ÉQUIPE100.0073716979727173727173728690325472
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Vellucci74717256827769USA5341,000,000$


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
1Seth GriffithPhantoms (Phi)C/LW/RW76143044820054192191671317.33%8183324.13314174130800072854059.40%193600000.48411000423
2Cory ConacherPhantoms (Phi)C/LW/RW761726432602075109190521248.95%3140418.476915382770000184150.74%80800010.6101121113
3Colin McDonaldPhantoms (Phi)RW7619224113840173691302811614.62%12191925.2578153930800013393356.81%47000000.43411000444
4Oscar FantenbergPhantoms (Phi)D76152641-61064085811254510712.00%75175723.12101525872890001276120.00%000000.4700314055
5Tomas HykaPhantoms (Phi)RW7615243961204389226661346.64%7144719.04110113522600031303048.76%12100000.5437000212
6Alex BiegaPhantoms (Phi)D7683139-511202101018836529.09%94162821.4361016722810110255200.00%000000.4800000240
7Adam TambelliniPhantoms (Phi)C/LW761322355375137921294210610.08%10149119.62211133730410121173152.53%81100100.4703001213
8Filip ZadinaPhantoms (Phi)RW76181634173204087192571159.38%8110014.4824615530001754141.25%8000010.6223000423
9Cameron GauncePhantoms (Phi)D4411182934210314382244813.41%4492821.1010515621750000158000.00%000000.6200002052
10Patrick EavesPhantoms (Phi)LW/RW76141428104209544109357912.84%8115715.2345910123000012071.93%5700000.4800000512
11Tomas JurcoPhiladelphia FlyersLW/RW3813152863155289130369410.00%891824.1737103514300041812051.40%46500010.6115001511
12Matt TennysonPhantoms (Phi)D76223252836050403510245.71%44106614.03000050000113100.00%000000.4700000030
13Landon FerraroPhantoms (Phi)C/LW/RW667172422412553647824708.97%483012.58000117000002053.10%67800000.5800113012
14Griffin ReinhartPhantoms (Phi)D76517221056096456716577.46%75160321.09189352930002272020.00%000000.2700000115
15Andrew CampbellPhantoms (Phi)D76217192875159727356175.71%36103613.64000226000023000.00%000000.3700111221
16Christian FolinPhiladelphia FlyersD265141946115734235192414.29%2960223.1758132588000086200.00%000000.6300102310
17Chris ThorburnPhantoms (Phi)RW76538151558295115329.80%64936.49000020001672061.18%8500000.3200001001
18Chris CarlislePhiladelphia FlyersD2703311401621340.00%71816.7400003000017000.00%000000.3300000000
19Brian CooperPhantoms (Phi)D44033160333050.00%82225.0600003000010000.00%000000.2700000000
20Scott KosmachukPhantoms (Phi)RW7630362915135130623.08%11852.43101418000000055.56%2700000.3211102000
21Marian StudenicPhiladelphia FlyersRW53101-10061011549.09%11913.61000020000000157.30%8900000.1011000000
Stats d'équipe Total ou en Moyenne136218734152815994715514601263192158613499.73%4882199816.15611141755382971112222431351155.14%562700130.4816438518353537
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
1Peter BudajPhantoms (Phi)26131030.9121.99153601515810000.714142653411
2Al MontoyaPhantoms (Phi)10000.8572.7344002140000.0000023000
Stats d'équipe Total ou en Moyenne27131030.9112.01158001535950000.714142676411


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 Cap 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 TambelliniPhantoms (Phi)C/LW241994-11-01No191 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$NoLien
Al MontoyaPhantoms (Phi)G341985-02-13No200 Lbs6 ft2NoNoNo1Pro & Farm750,000$0$0$NoLien
Alex BiegaPhantoms (Phi)D311988-04-04No199 Lbs5 ft10NoNoNo2Pro & Farm2,500,000$0$0$No2,500,000$Lien
Andrew CampbellPhantoms (Phi)D311988-02-04No205 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$NoLien
Brian CooperPhantoms (Phi)D251993-11-01No182 Lbs5 ft9NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Cameron GauncePhantoms (Phi)D291990-03-19No204 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$0$0$NoLien
Chris ThorburnPhantoms (Phi)RW361983-06-03No235 Lbs6 ft3NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Colin McDonaldPhantoms (Phi)RW341984-09-30No219 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Cory ConacherPhantoms (Phi)C/LW/RW291989-12-14No180 Lbs5 ft8NoNoNo1Pro & Farm500,000$0$0$NoLien
Filip ZadinaPhantoms (Phi)RW191999-11-27Yes195 Lbs6 ft0NoNoNo1Pro & Farm0$0$NoLien
Griffin ReinhartPhantoms (Phi)D251994-01-24No212 Lbs6 ft4NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Landon FerraroPhantoms (Phi)C/LW/RW271991-08-08No173 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Matt TennysonPhantoms (Phi)D291990-04-23No205 Lbs6 ft2NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Oscar FantenbergPhantoms (Phi)D271991-10-07No206 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Patrick EavesPhantoms (Phi)LW/RW351984-05-01No203 Lbs5 ft11NoNoNo3Pro & Farm2,500,000$0$0$No2,500,000$2,500,000$Lien
Peter BudajPhantoms (Phi)G361982-09-18No196 Lbs6 ft1NoNoNo1Pro & Farm1,920,000$0$0$NoLien
Scott KosmachukPhantoms (Phi)RW251994-01-24No185 Lbs5 ft11NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Seth GriffithPhantoms (Phi)C/LW/RW261993-01-04No190 Lbs5 ft9NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Tomas HykaPhantoms (Phi)RW261993-03-23No160 Lbs5 ft11NoNoNo1Pro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1928.84197 Lbs6 ft01.89724,737$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Adam TambelliniSeth GriffithColin McDonald40122
2Landon FerraroCory ConacherTomas Hyka30122
3Patrick EavesColin McDonaldFilip Zadina20122
4Adam TambelliniSeth GriffithChris Thorburn10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Oscar FantenbergAlex Biega40122
2Griffin ReinhartCameron Gaunce30122
3Andrew CampbellMatt Tennyson20122
4Brian CooperOscar Fantenberg10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Adam TambelliniSeth GriffithColin McDonald60122
2Landon FerraroCory ConacherTomas Hyka40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Oscar FantenbergAlex Biega60122
2Griffin ReinhartCameron Gaunce40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Colin McDonaldSeth Griffith60122
2Adam TambelliniTomas Hyka40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Oscar FantenbergAlex Biega60122
2Griffin ReinhartCameron Gaunce40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Colin McDonald60122Oscar FantenbergAlex Biega60122
2Seth Griffith40122Griffin ReinhartCameron Gaunce40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Colin McDonaldSeth Griffith60122
2Adam TambelliniTomas Hyka40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Oscar FantenbergAlex Biega60122
2Griffin ReinhartCameron Gaunce40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Adam TambelliniSeth GriffithColin McDonaldOscar FantenbergAlex Biega
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Adam TambelliniSeth GriffithColin McDonaldOscar FantenbergAlex Biega
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Scott Kosmachuk, Filip Zadina, Chris ThorburnScott Kosmachuk, Filip ZadinaChris Thorburn
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Andrew Campbell, Matt Tennyson, Brian CooperAndrew CampbellMatt Tennyson, Brian Cooper
Tirs de Pénalité
Colin McDonald, Seth Griffith, Adam Tambellini, Tomas Hyka, Filip Zadina
Gardien
#1 : Peter Budaj, #2 : Al Montoya


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
1Americans21100000440110000003121010000013-220.500461000645072173761865563359367393511218.18%10370.00%01379242056.98%1181217454.32%569109252.11%205414741648521919478
2Bears1264000113222106330000018144631000111486150.6253258900264507217343618655633593059216123047817.02%55983.64%11379242056.98%1181217454.32%569109252.11%205414741648521919478
3Bruins61400100610-43110010056-13030000014-330.25061016006450721712461865563359140356510325416.00%28292.86%01379242056.98%1181217454.32%569109252.11%205414741648521919478
4Checkers8800000046103644000000263234400000020713161.0004686132026450721732261865563359161445317827933.33%23291.30%01379242056.98%1181217454.32%569109252.11%205414741648521919478
5Comets2110000067-11010000026-41100000041320.50061218006450721755618655633593420182417211.76%9188.89%01379242056.98%1181217454.32%569109252.11%205414741648521919478
6Crunch22000000633110000003211100000031241.0006111700645072175461865563359581724388112.50%12191.67%01379242056.98%1181217454.32%569109252.11%205414741648521919478
7Devils411000116512010000114-32100001051450.625691511645072178361865563359732275792428.33%23386.96%01379242056.98%1181217454.32%569109252.11%205414741648521919478
8Marlies22000000918110000004131100000050541.0009172601645072178661865563359441116344250.00%7185.71%01379242056.98%1181217454.32%569109252.11%205414741648521919478
9Monsters430001001275210001006422200000063370.875122032006450721710461865563359672255892727.41%14285.71%01379242056.98%1181217454.32%569109252.11%205414741648521919478
10Penguins1225001312232-10623000011116-5602001301116-5120.50022325401645072172446186556335929778173212721013.89%761086.84%01379242056.98%1181217454.32%569109252.11%205414741648521919478
11Rocket21100000550110000003211010000023-120.5005914006450721748618655633593313223412325.00%9188.89%01379242056.98%1181217454.32%569109252.11%205414741648521919478
12Senators2010001034-1100000102111010000013-220.500347006450721733618655633593713183810220.00%9188.89%01379242056.98%1181217454.32%569109252.11%205414741648521919478
13Sound Tigers6220002015105311000106513110001095480.66715254001645072171436186556335911340791142727.41%31487.10%01379242056.98%1181217454.32%569109252.11%205414741648521919478
14Thunderbirds623001001214-23120000067-13110010067-150.417122335006450721713461865563359136355112616637.50%22577.27%01379242056.98%1181217454.32%569109252.11%205414741648521919478
Total763426014831951464938181400222100782238161201261956827930.6121953425371864507217192261865563359169649095114603606116.94%3614886.70%11379242056.98%1181217454.32%569109252.11%205414741648521919478
16Wolf Pack623010001112-13120000046-23110100076160.5001120310064507217112618655633591624110212633618.18%33390.91%01379242056.98%1181217454.32%569109252.11%205414741648521919478
_Since Last GM Reset763426014831951464938181400222100782238161201261956827930.6121953425371864507217192261865563359169649095114603606116.94%3614886.70%11379242056.98%1181217454.32%569109252.11%205414741648521919478
_Vs Conference541920013831131058271011002225658-2279901161574710620.5741131893021564507217124061865563359125236075210292733713.55%2813587.54%11379242056.98%1181217454.32%569109252.11%205414741648521919478
_Vs Division22860113145414113400111262061152010201921-2260.5914580125016450721751661865563359484131235408862023.26%971485.57%01379242056.98%1181217454.32%569109252.11%205414741648521919478

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7693L519534253719221696490951146018
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7634261483195146
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
381814022210078
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
38161212619568
Derniers 10 Matchs
WLOTWOTL SOWSOL
460000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3606116.94%3614886.70%1
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
6186556335964507217
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
1379242056.98%1181217454.32%569109252.11%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
205414741648521919478


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
4 - 2019-09-0513Sound Tigers1Phantoms3WSommaire du Match
10 - 2019-09-1135Thunderbirds1Phantoms4WSommaire du Match
11 - 2019-09-1252Phantoms2Thunderbirds3LXSommaire du Match
17 - 2019-09-1873Penguins3Phantoms4WSommaire du Match
18 - 2019-09-1989Phantoms1Penguins5LSommaire du Match
19 - 2019-09-2096Phantoms2Sound Tigers3LSommaire du Match
22 - 2019-09-23103Phantoms0Wolf Pack1LSommaire du Match
25 - 2019-09-26124Phantoms4Devils1WSommaire du Match
26 - 2019-09-27134Phantoms3Bears1WSommaire du Match
31 - 2019-10-02146Phantoms1Devils0WXXSommaire du Match
32 - 2019-10-03162Devils2Phantoms0LSommaire du Match
38 - 2019-10-09185Thunderbirds2Phantoms1LSommaire du Match
39 - 2019-10-10198Checkers0Phantoms7WSommaire du Match
43 - 2019-10-14219Checkers0Phantoms6WSommaire du Match
45 - 2019-10-16227Phantoms0Bruins1LSommaire du Match
46 - 2019-10-17244Phantoms3Thunderbirds1WSommaire du Match
52 - 2019-10-23268Bears1Phantoms3WSommaire du Match
53 - 2019-10-24281Bruins3Phantoms1LSommaire du Match
59 - 2019-10-30313Phantoms2Rocket3LSommaire du Match
60 - 2019-10-31324Phantoms1Senators3LSommaire du Match
61 - 2019-11-01334Phantoms5Marlies0WSommaire du Match
64 - 2019-11-04343Monsters1Phantoms4WSommaire du Match
66 - 2019-11-06352Bears1Phantoms5WSommaire du Match
67 - 2019-11-07369Monsters3Phantoms2LXSommaire du Match
73 - 2019-11-13394Senators1Phantoms2WXXSommaire du Match
74 - 2019-11-14409Phantoms4Penguins3WXXSommaire du Match
78 - 2019-11-18427Bears3Phantoms2LSommaire du Match
80 - 2019-11-20439Crunch2Phantoms3WSommaire du Match
81 - 2019-11-21456Phantoms4Bears2WSommaire du Match
85 - 2019-11-25467Phantoms1Penguins0WXXSommaire du Match
87 - 2019-11-27478Bruins2Phantoms1LXSommaire du Match
88 - 2019-11-28494Penguins1Phantoms2WSommaire du Match
94 - 2019-12-04520Phantoms1Bruins2LSommaire du Match
95 - 2019-12-05533Phantoms4Wolf Pack3WSommaire du Match
96 - 2019-12-06547Phantoms1Thunderbirds3LSommaire du Match
101 - 2019-12-11567Devils2Phantoms1LXXSommaire du Match
102 - 2019-12-12580Bears3Phantoms2LSommaire du Match
103 - 2019-12-13590Phantoms5Bears0WSommaire du Match
106 - 2019-12-16597Thunderbirds4Phantoms1LSommaire du Match
108 - 2019-12-18609Phantoms3Wolf Pack2WXSommaire du Match
109 - 2019-12-19625Americans1Phantoms3WSommaire du Match
111 - 2019-12-21638Phantoms2Penguins5LSommaire du Match
113 - 2019-12-23649Bears3Phantoms5WSommaire du Match
115 - 2019-12-25660Rocket2Phantoms3WSommaire du Match
116 - 2019-12-26671Phantoms5Sound Tigers1WSommaire du Match
122 - 2020-01-01683Phantoms2Sound Tigers1WXXSommaire du Match
123 - 2020-01-02700Phantoms1Bears0WXXSommaire du Match
129 - 2020-01-08723Phantoms4Comets1WSommaire du Match
130 - 2020-01-09745Wolf Pack1Phantoms2WSommaire du Match
131 - 2020-01-10751Wolf Pack3Phantoms1LSommaire du Match
136 - 2020-01-15771Sound Tigers4Phantoms2LSommaire du Match
137 - 2020-01-16781Phantoms1Bears2LXXSommaire du Match
138 - 2020-01-17801Bears3Phantoms1LSommaire du Match
143 - 2020-01-22816Phantoms5Checkers1WSommaire du Match
144 - 2020-01-23829Phantoms5Checkers3WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29856Phantoms3Crunch1WSommaire du Match
151 - 2020-01-30875Comets6Phantoms2LSommaire du Match
152 - 2020-01-31883Sound Tigers0Phantoms1WXXSommaire du Match
155 - 2020-02-03892Phantoms1Penguins2LXSommaire du Match
157 - 2020-02-05902Checkers2Phantoms6WSommaire du Match
158 - 2020-02-06913Checkers1Phantoms7WSommaire du Match
162 - 2020-02-10937Penguins2Phantoms1LXXSommaire du Match
164 - 2020-02-12949Bruins1Phantoms3WSommaire du Match
165 - 2020-02-13963Marlies1Phantoms4WSommaire du Match
171 - 2020-02-19985Phantoms2Penguins1WXXSommaire du Match
172 - 2020-02-20999Penguins4Phantoms1LSommaire du Match
176 - 2020-02-241021Phantoms1Americans3LSommaire du Match
178 - 2020-02-261028Phantoms4Monsters2WSommaire du Match
179 - 2020-02-271041Phantoms2Monsters1WSommaire du Match
182 - 2020-03-011059Phantoms6Checkers2WSommaire du Match
183 - 2020-03-021063Phantoms4Checkers1WSommaire du Match
186 - 2020-03-051092Penguins4Phantoms2LSommaire du Match
187 - 2020-03-061100Penguins2Phantoms1LSommaire du Match
189 - 2020-03-081105Phantoms0Bears3LSommaire du Match
192 - 2020-03-111119Phantoms0Bruins1LSommaire du Match
193 - 2020-03-121133Wolf Pack2Phantoms1LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,155,448$ 137,700$ 37,250$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 155,508$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 5,864$ 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
14763426014831951464938181400222100782238161201261956827931953425371864507217192261865563359169649095114603606116.94%3614886.70%11379242056.98%1181217454.32%569109252.11%205414741648521919478
Total Saison Régulière763426014831951464938181400222100782238161201261956827931953425371864507217192261865563359169649095114603606116.94%3614886.70%11379242056.98%1181217454.32%569109252.11%205414741648521919478