Phantoms

GP: 24 | W: 13 | L: 9 | OTL: 2 | P: 28
GF: 64 | GA: 40 | PP%: 17.35% | PK%: 86.09%
DG: Kriss Cardenas | Morale : 52 | Moyenne d'Équipe : 63
Prochain matchs #394 vs Senators
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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
1Tomas JurcoXX100.006238856478817563656261646673677155630
2Colin McDonaldX100.007135935784939156585554585585795058620
3Seth GriffithXXX100.005237896267939161736456586271665558620
4Adam TambelliniXX100.006536925782949356605654585569656058610
5Tomas HykaX100.005235936365786562566461585971665358610
6Filip Zadina (R)X100.005635936473867263565961586359629158610
7Chris ThorburnX100.007737725990726457545553585286764259600
8Cory ConacherXXX100.005039816065787159626157585678704553590
9Marian StudenicX100.005336915770928956595554565561636458590
10Patrick EavesXX100.006035935673725955565753565285754658580
11Scott KosmachukX100.005439825769908556585457535669656459580
12Landon FerraroXXX100.005340785769726856605654575575686457570
13Christian FolinX100.009046796184827359306956754975683663680
14Alex BiegaX100.009037756370756161307556685379714958660
15Oscar FantenbergX100.008143856276817461306759685375683661660
16Griffin ReinhartX100.007336905889949556305452594869658058640
17Andrew CampbellX100.007138845487928953305251574579715158630
18Matt TennysonX100.006637895981786658305753594677694658620
Rayé
1Cameron GaunceX100.006145796281876961306055674777695830640
2Chris CarlisleX100.006436765770777356305452535163645130580
3Brian CooperX100.005337885566777154305650514771665526560
MOYENNE D'ÉQUIPE100.00643885597683765847595559547468565461
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
1Mike McKenna100.00798280777877797877797886902858770
2Peter Budaj100.00757472777473757473757487913458740
Rayé
1Al Montoya100.00706866806968706968706984883026700
MOYENNE D'ÉQUIPE100.0075757378747375747375748690314774
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'ÉquipePOS GP 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
1Alex BiegaPhantoms (Phi)D2421719740056262410188.33%2849720.712351976011082000.00%000000.7600000120
2Christian FolinPhantoms (Phi)D244131755715653633162212.12%2755423.1147112378000080200.00%000000.6100102210
3Tomas JurcoPhantoms (Phi)LW/RW2489176195294673236010.96%356623.60235158100021092055.12%28300010.6001001301
4Oscar FantenbergPhantoms (Phi)D24610165275283235153217.14%2256823.703692380000088110.00%000000.5600100003
5Adam TambelliniPhantoms (Phi)C/LW2467135120483333113718.18%144418.511347781011351052.61%42200100.5900000011
6Seth GriffithPhantoms (Phi)C/LW/RW24391256019434019357.50%150521.070556830002711057.69%55300000.4711000020
7Cory ConacherPhantoms (Phi)C/LW/RW24651142715182352182811.54%240316.822131575000021050.00%2000000.5500021002
8Filip ZadinaPhantoms (Phi)RW24561164011286216338.06%337515.651126360000210053.13%3200000.5900000201
9Tomas HykaPhantoms (Phi)RW2446106008225313387.55%132813.670004420000282037.50%1600000.6100000010
10Colin McDonaldPhantoms (Phi)RW246410728042103573217.14%454322.6311288300001061050.00%5000000.3711000031
11Landon FerraroPhantoms (Phi)C/LW/RW2119101319151020236274.35%224811.8500000000000050.43%23000000.8000111001
12Griffin ReinhartPhantoms (Phi)D2426886011131931610.53%2550120.890331080000188000.00%000000.3200000002
13Patrick EavesPhantoms (Phi)LW/RW245271180191325132120.00%329612.3400000000000066.67%1200000.4700000111
14Matt TennysonPhantoms (Phi)D2416710180131717395.88%1538416.0100001000038100.00%000000.3600000010
15Andrew CampbellPhantoms (Phi)D2415611260331116316.25%1837715.7300017000014000.00%000000.3200000110
16Chris ThorburnPhantoms (Phi)RW24123417522919595.26%31596.64000000000140076.92%1300000.3800001001
17Scott KosmachukPhantoms (Phi)RW24101127157360316.67%1974.0610121000000037.50%800000.2100102000
18Marian StudenicPhantoms (Phi)RW241010005741225.00%0923.8500005000000159.21%7600000.2200000000
Stats d'équipe Total ou en Moyenne429631161791143417544439256918242311.07%159694416.19173350139813112678212254.64%171500110.5223438101314
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
1Mike McKennaPhantoms (Phi)2413920.9231.62144444395080011.0002240211
Stats d'équipe Total ou en Moyenne2413920.9231.62144444395080011.0002240211


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Adam TambelliniPhantoms (Phi)C/LW241994-11-01No191 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Al MontoyaPhantoms (Phi)G341985-02-13No200 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien
Alex BiegaPhantoms (Phi)D311988-04-04No199 Lbs5 ft10NoNoNo2Sans RestrictionPro & Farm2,500,000$0$0$NoLien
Andrew CampbellPhantoms (Phi)D311988-02-04No205 Lbs6 ft4NoNoNo1Sans RestrictionPro & Farm500,000$0$0$NoLien
Brian CooperPhantoms (Phi)D251993-11-01No182 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Cameron GauncePhantoms (Phi)D291990-03-19No204 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Chris CarlislePhantoms (Phi)D241994-12-16No175 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Chris ThorburnPhantoms (Phi)RW361983-06-03No235 Lbs6 ft3NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Christian FolinPhantoms (Phi)D281991-02-09No204 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm1,850,000$0$0$NoLien
Colin McDonaldPhantoms (Phi)RW341984-09-30No219 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Cory ConacherPhantoms (Phi)C/LW/RW291989-12-14No180 Lbs5 ft8NoNoNo1Sans RestrictionPro & Farm500,000$0$0$NoLien
Filip ZadinaPhantoms (Phi)RW191999-11-27Yes195 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm0$0$NoLien
Griffin ReinhartPhantoms (Phi)D251994-01-24No212 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Landon FerraroPhantoms (Phi)C/LW/RW271991-08-08No173 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Marian StudenicPhantoms (Phi)RW201998-10-28No164 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Matt TennysonPhantoms (Phi)D291990-04-23No205 Lbs6 ft2NoNoNo4Sans RestrictionPro & Farm500,000$0$0$NoLien
Mike McKennaPhantoms (Phi)G361983-04-11No183 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm500,000$0$0$NoLien
Oscar FantenbergPhantoms (Phi)D271991-10-07No206 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Patrick EavesPhantoms (Phi)LW/RW351984-05-01No203 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm2,500,000$0$0$NoLien
Peter BudajPhantoms (Phi)G361982-09-18No196 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm1,920,000$0$0$NoLien
Scott KosmachukPhantoms (Phi)RW251994-01-24No185 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Seth GriffithPhantoms (Phi)C/LW/RW261993-01-04No190 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Tomas HykaPhantoms (Phi)RW261993-03-23No160 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Tomas JurcoPhantoms (Phi)LW/RW261992-12-28No188 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm500,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2428.42194 Lbs6 ft11.88717,500$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tomas JurcoSeth GriffithColin McDonald40122
2Cory ConacherAdam TambelliniTomas Hyka30122
3Patrick EavesLandon FerraroFilip Zadina20122
4Colin McDonaldTomas JurcoChris Thorburn10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinOscar Fantenberg40122
2Alex BiegaGriffin Reinhart30122
3Andrew CampbellMatt Tennyson20122
4Christian FolinOscar Fantenberg10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tomas JurcoSeth GriffithColin McDonald60122
2Cory ConacherAdam TambelliniTomas Hyka40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinOscar Fantenberg60122
2Alex BiegaGriffin Reinhart40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Tomas JurcoColin McDonald60122
2Seth GriffithTomas Hyka40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinOscar Fantenberg60122
2Alex BiegaGriffin Reinhart40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Tomas Jurco60122Christian FolinOscar Fantenberg60122
2Colin McDonald40122Alex BiegaGriffin Reinhart40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Tomas JurcoColin McDonald60122
2Seth GriffithTomas Hyka40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinOscar Fantenberg60122
2Alex BiegaGriffin Reinhart40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tomas JurcoSeth GriffithColin McDonaldChristian FolinOscar Fantenberg
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tomas JurcoSeth GriffithColin McDonaldChristian FolinOscar Fantenberg
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Marian Studenic, Scott Kosmachuk, Filip ZadinaMarian Studenic, Scott KosmachukFilip Zadina
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Andrew Campbell, Matt Tennyson, Alex BiegaAndrew CampbellMatt Tennyson, Alex Biega
Tirs de Pénalité
Tomas Jurco, Colin McDonald, Seth Griffith, Tomas Hyka, Filip Zadina
Gardien
#1 : Mike McKenna, #2 : Peter Budaj


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
1Bears330000001138220000008261100000031261.0001121320022103129019318818566826566815426.67%12191.67%143874858.56%34966352.64%15833547.16%645464513164287149
2Bruins2020000014-31010000013-21010000001-100.00012300221031232193188185644142424700.00%110100.00%043874858.56%34966352.64%15833547.16%645464513164287149
3Checkers220000001301322000000130130000000000041.000132437022210312831931881856281219408225.00%70100.00%043874858.56%34966352.64%15833547.16%645464513164287149
4Devils311000105321010000002-22100001051440.66757121122103125819318818566214585519210.53%17288.24%043874858.56%34966352.64%15833547.16%645464513164287149
5Marlies11000000505000000000001100000050521.000591401221031236193188185624481911100.00%30100.00%043874858.56%34966352.64%15833547.16%645464513164287149
6Monsters21000100642210001006420000000000030.7506915002210312471931881856341117451000.00%6183.33%043874858.56%34966352.64%15833547.16%645464513164287149
7Penguins2110000058-3110000004311010000015-420.5005914002210312321931881856681643338225.00%18572.22%043874858.56%34966352.64%15833547.16%645464513164287149
8Rocket1010000023-1000000000001010000023-100.00024600221031223193188185618914124125.00%6183.33%043874858.56%34966352.64%15833547.16%645464513164287149
9Senators1010000013-2000000000001010000013-200.00012300221031215193188185620210144125.00%5180.00%043874858.56%34966352.64%15833547.16%645464513164287149
10Sound Tigers21100000541110000003121010000023-120.5005101500221031241193188185626144336800.00%13284.62%043874858.56%34966352.64%15833547.16%645464513164287149
11Thunderbirds421001001073211000005322100010054150.6251019290022103129919318818569422267711436.36%12283.33%043874858.56%34966352.64%15833547.16%645464513164287149
Total241290021064402412830010040182212460011024222280.583641161801422103125691931881856509159345444981717.35%1151686.09%143874858.56%34966352.64%15833547.16%645464513164287149
13Wolf Pack1010000001-1000000000001010000001-100.00000000221031213193188185623152721300.00%5180.00%043874858.56%34966352.64%15833547.16%645464513164287149
_Since Last GM Reset241290021064402412830010040182212460011024222280.583641161801422103125691931881856509159345444981717.35%1151686.09%143874858.56%34966352.64%15833547.16%645464513164287149
_Vs Conference167700110343048520010022157825000101215-3170.531346094112210312328193188185634511227829674912.16%871385.06%143874858.56%34966352.64%15833547.16%645464513164287149
_Vs Division933001101917232100100660612000101311290.5001936550122103122051931881856200518214627725.93%37489.19%043874858.56%34966352.64%15833547.16%645464513164287149

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2428OTL16411618056950915934544414
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2412902106440
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
128301004018
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
124601102422
Derniers 10 Matchs
WLOTWOTL SOWSOL
540100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
981717.35%1151686.09%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
19318818562210312
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
43874858.56%34966352.64%15833547.16%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
645464513164287149


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.
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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 - 2019-11-13394Senators-Phantoms-
74 - 2019-11-14409Phantoms-Penguins-
78 - 2019-11-18427Bears-Phantoms-
80 - 2019-11-20439Crunch-Phantoms-
81 - 2019-11-21456Phantoms-Bears-
85 - 2019-11-25467Phantoms-Penguins-
87 - 2019-11-27478Bruins-Phantoms-
88 - 2019-11-28494Penguins-Phantoms-
94 - 2019-12-04520Phantoms-Bruins-
95 - 2019-12-05533Phantoms-Wolf Pack-
96 - 2019-12-06547Phantoms-Thunderbirds-
101 - 2019-12-11567Devils-Phantoms-
102 - 2019-12-12580Bears-Phantoms-
103 - 2019-12-13590Phantoms-Bears-
106 - 2019-12-16597Thunderbirds-Phantoms-
108 - 2019-12-18609Phantoms-Wolf Pack-
109 - 2019-12-19625Americans-Phantoms-
111 - 2019-12-21638Phantoms-Penguins-
113 - 2019-12-23649Bears-Phantoms-
115 - 2019-12-25660Rocket-Phantoms-
116 - 2019-12-26671Phantoms-Sound Tigers-
122 - 2020-01-01683Phantoms-Sound Tigers-
123 - 2020-01-02700Phantoms-Bears-
129 - 2020-01-08723Phantoms-Comets-
130 - 2020-01-09745Wolf Pack-Phantoms-
131 - 2020-01-10751Wolf Pack-Phantoms-
136 - 2020-01-15771Sound Tigers-Phantoms-
137 - 2020-01-16781Phantoms-Bears-
138 - 2020-01-17801Bears-Phantoms-
143 - 2020-01-22816Phantoms-Checkers-
144 - 2020-01-23829Phantoms-Checkers-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29856Phantoms-Crunch-
151 - 2020-01-30875Comets-Phantoms-
152 - 2020-01-31883Sound Tigers-Phantoms-
155 - 2020-02-03892Phantoms-Penguins-
157 - 2020-02-05902Checkers-Phantoms-
158 - 2020-02-06913Checkers-Phantoms-
162 - 2020-02-10937Penguins-Phantoms-
164 - 2020-02-12949Bruins-Phantoms-
165 - 2020-02-13963Marlies-Phantoms-
171 - 2020-02-19985Phantoms-Penguins-
172 - 2020-02-20999Penguins-Phantoms-
176 - 2020-02-241021Phantoms-Americans-
178 - 2020-02-261028Phantoms-Monsters-
179 - 2020-02-271041Phantoms-Monsters-
182 - 2020-03-011059Phantoms-Checkers-
183 - 2020-03-021063Phantoms-Checkers-
186 - 2020-03-051092Penguins-Phantoms-
187 - 2020-03-061100Penguins-Phantoms-
189 - 2020-03-081105Phantoms-Bears-
192 - 2020-03-111119Phantoms-Bruins-
193 - 2020-03-121133Wolf Pack-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
26 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
435,024$ 172,200$ 50,250$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 63,936$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 6,042$ 737,124$




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
1424129002106440241283001004018221246001102422228641161801422103125691931881856509159345444981717.35%1151686.09%143874858.56%34966352.64%15833547.16%645464513164287149
Total Saison Régulière24129002106440241283001004018221246001102422228641161801422103125691931881856509159345444981717.35%1151686.09%143874858.56%34966352.64%15833547.16%645464513164287149