Phantoms

GP: 7 | W: 4 | L: 3 | OTL: 0 | P: 8
GF: 21 | GA: 25 | PP%: 21.21% | PK%: 76.09%
DG: Yannick Bernier | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #82 vs Penguins
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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
1Cole Bardreau (R)XX100.00864582636652625459605968255555635000
2Lane PedersonX100.00717170667168696780636763644444675000
3Gemel SmithXXX100.00696872726874766780596865655656675000
4Melker Karlsson (A)XX100.00674289786562875740605977756669655000
5Mikkel Boedker (C)XX100.00674399857654636232605972617577645000
6Maxim LetunovX100.00777191627170726580666066574444655000
7Nathan BastianX100.00777875627877816250586265594444645000
8Lean Bergmann (R)XX100.00894689757651645126585556254545605000
9Jack Studnicka (R)X100.00716585736575786580616563624444675000
10Evan RodriguesXXX100.00654190776659776165596470756363665000
11Valentin ZykovXX100.00784587718062596425655856254848625000
12Andreas JohnssonXX100.00754389807070757625757158805859714400
13Alex Formenton (R)X100.00727371767367686650616864654444675000
14Mark AltX100.00787781657770764725374262404444535000
15Mark FriedmanX100.00716781646775815125474159394444545000
16Reece Willcox (R)X100.00777092627071784725394061384444535000
17Josh Brook (R)X100.00737179697173804725374159394444525000
18Travis Sanheim (A)X100.00674286807080936725595380256061675000
Rayé
1Givani SmithXX100.00857687667654787025555961254545635000
2Jack KopackaX100.00807298627256565650505765544444605000
3Stelio MattheosX100.00787291557262645550495764544444605000
4Danil Yurtaykin (R)XX100.00696189716160625550604659444444565000
5Tyrell GoulbourneXX100.00727078687069764550414458424444525000
6Luke GreenX100.00756990606940404225284159394444485000
MOYENNE D'ÉQUIPE100.0075628569716571584454566449495061500
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
1Anton Forsberg100.0055617678555750585352304848555000
2Charlie Lindgren100.0051587375485354585252304646535000
Rayé
1Joseph Woll (R)100.0050648080455250554949304444525000
MOYENNE D'ÉQUIPE100.005261767849545157515130464653500
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dominique Ducharme73727068696479CAN493850,000$


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
1Gemel SmithPhantoms (PHI)C/LW/RW7628000720215928.57%114620.893144270000280060.63%12700011.0900000102
2Mikkel BoedkerPhantoms (PHI)LW/RW7347-1206181741517.65%115121.590112210001311039.44%7100000.9300000110
3Evan RodriguesPhantoms (PHI)C/LW/RW72460001121071120.00%112317.691122230000241038.10%2100000.9700000100
4Valentin ZykovPhantoms (PHI)LW/RW7156-180108621216.67%111516.50033227000000020.00%500001.0400000100
5Alex FormentonPhantoms (PHI)LW7066-12077153120.00%111816.87022627000020042.86%700001.0200000000
6Melker KarlssonPhantoms (PHI)C/RW7145-110031392911.11%112818.391121230000270042.86%10500000.7800000000
7Josh BrookPhantoms (PHI)D704411001132110.00%913719.62022222000023000.00%000000.5800000011
8Cole BardreauPhantoms (PHI)C/RW71231003120250.00%0314.4800000000000033.33%300001.9100000010
9Mark AltPhantoms (PHI)D50330801613000.00%17414.870000300000000.00%000000.8100000010
10Mark FriedmanPhantoms (PHI)D721316072222100.00%614120.16213222000026000.00%000000.4300000000
11Travis SanheimPhantoms (PHI)D7033-1100171687110.00%716824.04022426000037000.00%000000.3600000000
12Lane PedersonPhantoms (PHI)C71121401561316.67%0588.31000000001260052.63%5700000.6900000000
13Maxim LetunovPhantoms (PHI)C71122205121250.00%0243.5300017000041070.00%1000001.6200000000
14Jack StudnickaPhantoms (PHI)C70220603812570.00%09713.9600013000000051.14%8800000.4100000000
15Nathan BastianPhantoms (PHI)RW7101-1601617565.88%19213.2800000000000050.00%200000.2200000000
16Reece WillcoxPhantoms (PHI)D410111404221150.00%56015.010000000006100.00%000000.3300000000
17Lean BergmannPhantoms (PHI)LW/RW7000-180975760.00%09513.620000100000000.00%300000.0000000000
Stats d'équipe Total ou en Moyenne11420426209601111301395310914.39%35176415.48714212723900022404049.30%49900010.7000000443
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
1Anton ForsbergPhantoms (PHI)74200.8214.0232800221230000.000070000
2Charlie LindgrenPhantoms (PHI)30100.9251.9095003400000.000007000
Stats d'équipe Total ou en Moyenne104300.8473.5542300251630000.000077000


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 RestantSalaire MoyenSalaire Moyen 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
Alex FormentonPhantoms (PHI)LW201999-09-13Yes190 Lbs6 ft3NoNoNo3Pro & Farm888,333$888,333$888,333$888,333$0$0$No888,333$888,333$
Andreas JohnssonPhantoms (PHI)LW/RW251994-11-21No190 Lbs6 ft0NoNoNo1Pro & Farm787,500$787,500$1,418,750$1,418,750$0$0$NoLien
Anton ForsbergPhantoms (PHI)G271992-11-26No192 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Charlie LindgrenPhantoms (PHI)G261993-12-17No190 Lbs6 ft2NoNoNo1Pro & Farm1,300,000$1,300,000$1,300,000$1,300,000$0$0$NoLien
Cole BardreauPhantoms (PHI)C/RW261993-07-22Yes185 Lbs5 ft10NoNoNo3Pro & Farm700,000$700,000$700,000$700,000$0$0$No700,000$700,000$
Danil YurtaykinPhantoms (PHI)LW/RW221997-07-01Yes165 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Evan RodriguesPhantoms (PHI)C/LW/RW261993-07-28No182 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Gemel Smith (Contrat à 1 Volet)Phantoms (PHI)C/LW/RW261994-04-16No190 Lbs5 ft10NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$100,000$100,000$NoLien
Givani SmithPhantoms (PHI)LW/RW221998-02-27No204 Lbs6 ft2NoNoNo2Pro & Farm913,333$913,333$913,333$913,333$0$0$No913,333$Lien
Jack KopackaPhantoms (PHI)LW221998-05-05No192 Lbs6 ft2NoNoNo2Pro & Farm910,833$910,833$910,000$910,000$0$0$No910,833$Lien
Jack StudnickaPhantoms (PHI)C211999-02-17Yes171 Lbs6 ft1NoNoNo3Pro & Farm863,333$863,333$863,333$863,333$0$0$No863,333$863,333$Lien
Joseph WollPhantoms (PHI)G211998-07-12Yes200 Lbs6 ft3NoNoNo3Pro & Farm850,000$850,000$800,000$800,000$0$0$No800,000$800,000$Lien
Josh BrookPhantoms (PHI)D211999-06-17Yes192 Lbs6 ft1NoNoNo3Pro & Farm910,833$910,833$910,833$910,833$0$0$No910,833$910,833$
Lane PedersonPhantoms (PHI)C221997-08-04No192 Lbs6 ft1NoNoNo3Pro & Farm777,500$777,500$690,000$690,000$0$0$No690,000$690,000$Lien
Lean BergmannPhantoms (PHI)LW/RW211998-10-04Yes205 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Luke GreenPhantoms (PHI)D221998-01-11No188 Lbs6 ft1NoNoNo2Pro & Farm838,333$838,333$850,000$850,000$0$0$No838,333$Lien
Mark AltPhantoms (PHI)D281991-10-17No201 Lbs6 ft4NoNoNo1Pro & Farm650,000$650,000$650,000$650,000$0$0$NoLien
Mark FriedmanPhantoms (PHI)D241995-12-25No185 Lbs5 ft11NoNoNo2Pro & Farm825,000$825,000$825,000$825,000$0$0$No825,000$Lien
Maxim LetunovPhantoms (PHI)C241996-02-19No180 Lbs6 ft4NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Melker KarlssonPhantoms (PHI)C/RW291990-07-18No182 Lbs5 ft10NoNoNo1Pro & Farm2,000,000$2,000,000$2,000,000$2,000,000$0$0$NoLien
Mikkel BoedkerPhantoms (PHI)LW/RW301989-12-15No210 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Nathan BastianPhantoms (PHI)RW221997-12-06No205 Lbs6 ft4NoNoNo3Pro & Farm992,500$992,500$905,000$905,000$0$0$No905,000$905,000$Lien
Reece WillcoxPhantoms (PHI)D261994-05-20Yes183 Lbs6 ft3NoNoNo3Pro & Farm675,000$675,000$675,000$675,000$0$0$No675,000$675,000$
Stelio MattheosPhantoms (PHI)RW211999-06-13No198 Lbs6 ft1NoNoNo2Pro & Farm925,000$925,000$925,000$925,000$0$0$No925,000$Lien
Travis SanheimPhantoms (PHI)D241996-03-28No181 Lbs6 ft3NoNoNo1Pro & Farm1,263,333$1,263,333$1,263,333$1,263,333$0$0$NoLien
Tyrell GoulbournePhantoms (PHI)LW/RW261994-01-25No195 Lbs5 ft11NoNoNo1Pro & Farm775,000$775,000$775,000$775,000$0$0$NoLien
Valentin ZykovPhantoms (PHI)LW/RW251995-05-14No224 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2724.04192 Lbs6 ft11.78957,253$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mikkel BoedkerMelker KarlssonEvan Rodrigues35122
2Alex FormentonGemel SmithValentin Zykov30122
3Lean BergmannJack StudnickaNathan Bastian25122
4Mikkel BoedkerLane PedersonCole Bardreau10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis Sanheim35122
2Mark FriedmanJosh Brook30122
3Mark AltReece Willcox25122
4Travis Sanheim10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mikkel BoedkerMelker KarlssonEvan Rodrigues60122
2Alex FormentonGemel SmithValentin Zykov40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis Sanheim60122
2Mark FriedmanJosh Brook40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Mikkel BoedkerMelker Karlsson60122
2Evan RodriguesGemel Smith40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis Sanheim60122
2Mark FriedmanJosh Brook40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Mikkel Boedker60122Travis Sanheim60122
2Melker Karlsson40122Mark FriedmanJosh Brook40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Mikkel BoedkerMelker Karlsson60122
2Evan RodriguesGemel Smith40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis Sanheim60122
2Mark FriedmanJosh Brook40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mikkel BoedkerMelker KarlssonEvan RodriguesTravis Sanheim
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mikkel BoedkerMelker KarlssonEvan RodriguesTravis Sanheim
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Maxim Letunov, Jack Studnicka, Lane PedersonMaxim Letunov, Jack StudnickaLane Pederson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mark Alt, Reece Willcox, Mark FriedmanMark AltReece Willcox, Mark Friedman
Tirs de Pénalité
Mikkel Boedker, Melker Karlsson, Evan Rodrigues, Gemel Smith, Alex Formenton
Gardien
#1 : Anton Forsberg, #2 : Charlie Lindgren


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
1Admirals11000000321110000003210000000000021.00036900956118444550125918169111.11%90100.00%09216356.44%10122045.91%5311645.69%163115179508138
2Monsters2110000056-1000000000002110000056-120.50051015009561374445501417262711218.18%12375.00%09216356.44%10122045.91%5311645.69%163115179508138
3Sound Tigers20101000810-21010000047-31000100043120.50081624009561434445501531426376233.33%12375.00%09216356.44%10122045.91%5311645.69%163115179508138
Total733010002125-4321000001112-1412010001013-380.5712142630095611404445501163379811533721.21%461176.09%09216356.44%10122045.91%5311645.69%163115179508138
5Wolf Pack2110000057-2110000004311010000014-320.5005101500956142444550144728357228.57%13561.54%09216356.44%10122045.91%5311645.69%163115179508138
_Since Last GM Reset733010002125-4321000001112-1412010001013-380.5712142630095611404445501163379811533721.21%461176.09%09216356.44%10122045.91%5311645.69%163115179508138
_Vs Conference422000001013-31100000043131200000610-440.5001020300095617944455018514546218422.22%25868.00%09216356.44%10122045.91%5311645.69%163115179508138
_Vs Division622000001823-521000000810-2412000001013-340.333183654009561122444550113828809924625.00%371170.27%09216356.44%10122045.91%5311645.69%163115179508138

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
78W1214263140163379811500
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
73310002125
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
32100001112
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
41210001013
Derniers 10 Matchs
WLOTWOTL SOWSOL
430000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
33721.21%461176.09%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
44455019561
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
9216356.44%10122045.91%5311645.69%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
163115179508138


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")
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JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
1 - 2020-09-035Phantoms3Monsters2WSommaire du Match
3 - 2020-09-0518Admirals2Phantoms3WSommaire du Match
4 - 2020-09-0629Sound Tigers7Phantoms4LSommaire du Match
5 - 2020-09-0736Phantoms2Monsters4LSommaire du Match
7 - 2020-09-0948Phantoms4Sound Tigers3WXSommaire du Match
8 - 2020-09-1060Phantoms1Wolf Pack4LSommaire du Match
9 - 2020-09-1167Wolf Pack3Phantoms4WSommaire du Match
11 - 2020-09-1382Penguins-Phantoms-
12 - 2020-09-1492Phantoms-Penguins-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
14 - 2020-09-16108Monsters-Phantoms-



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
2 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 2,484,581$ 2,526,290$ 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$ 5 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