Flyers

GP: 82 | W: 43 | L: 26 | OTL: 13 | P: 99
GF: 229 | GA: 225 | PP%: 20.74% | PK%: 80.05%
DG: Libre | Morale : 51 | Moyenne d'Équipe : 68
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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
1Matthew Tkachuk (R)X100.007044688281889381677984806159588875750
2J.T. Compher (R)X100.006141757573887970837172825374557366700
3Artturi Lehkonen (R)X100.007235757470849569646867766759536871680
4Jesperi Kotkaniemi (R)X100.006535727077829269827066686753519174670
5Brett Howden (R)X100.006735796882827967836964756653518062660
6Colin McdonaldX100.007549676278767475606672506790845261660
7Tom Kuhnhackl (R)X100.007035756580798664566464805864525171660
8Brian FlynnX100.004128957072697363875756816499875868650
9Andy Andreoff (R)X100.008048636575717166746764595668575372630
10Travis Boyd (R)X100.005835766869736868686964665266514731630
11Sam Steel (R)X100.005335727070596170706667675451507861620
12Micheal Haley (R)X100.007565566373705862656261626169532625600
13Zach Werenski (R)X100.006535837382929572307893715677608758730
14Derek Forbort (R)X100.007035756690869564306764805664587968700
15Mark Borowiecki (R)X100.008640766277646980307478725674724369690
16Dylan OlsenX100.006819996080727282507572686780765371690
17Brandon Manning (R)X100.007948736476788374306876725872673569690
18Matt Tennyson (R)X100.007050676377739387448165705864654282690
Rayé
1Iiro Pakarinen (R)X100.007241816277717955545860725574714054620
2Michael LattaX100.006850586176438962825958656279744719610
3Mikhail Vorobyev (R)X100.005335676979565769695859605451506220590
4Jyrki Jokipakka (R)X100.006735966875707179256062726361614620660
5Jacob Larsson (R)X100.006235766180708461305956615852518020610
MOYENNE D'ÉQUIPE100.00673975677774797058676770606861605666
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
1Michael Garnett100.00645077807299999999789399992363810
2Collin Delia (R)100.00807694827983858483795174664271790
Rayé
1Jason Bacashihua100.00715071747095959595738493992619780
2Alex Lyon (R)100.00766897787579818079755170643720750
MOYENNE D'ÉQUIPE100.0073618579748990908976708482324378
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Terry Murray88767779999880CAN691600,000$


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
1Matthew TkachukFlyers (PHI)LW8238559341022023919237310821210.19%52182022.201824428129510192963642.01%6389232021.02823211956
2J.T. CompherFlyers (PHI)RW78363066153151711672818316312.81%38166021.291715325227001162642750.35%1414342000.79623111562
3Jesperi KotkaniemiFlyers (PHI)C82193857-89315150243192551249.90%32145917.7981523312390001491150.94%16452316000.7805210304
4Artturi LehkonenFlyers (PHI)RW822629551500171144325971758.00%32157819.25391238231112111624354.20%1315727000.70617000454
5Brett HowdenFlyers (PHI)C8216385410475151228149458910.74%29158119.2851823232731013883053.43%18792723000.6815001030
6Zach WerenskiFlyers (PHI)D741432461426011517718773837.49%105187825.3971118383040115305410.00%06849000.4901000461
7Tom KuhnhacklFlyers (PHI)LW82131932-868015513014446949.03%19139016.9514511220000004335.90%781417000.4611000222
8Matt TennysonFlyers (PHI)D8242630-141194513214111754523.42%92154818.893811101310002161200.00%03235000.3900405012
9Derek ForbortFlyers (PHI)D8142428217151921719528434.21%119201224.854610232910112321010.00%02160000.2800001103
10Colin McdonaldFlyers (PHI)RW74151328660201656419747967.61%2294112.721125211013631051.52%332810000.6036121125
11Mark BorowieckiFlyers (PHI)D82421252521016415412657393.17%83164320.0434781490112178000.00%03440000.3000011003
12Brian FlynnFlyers (PHI)LW827121967529859819577.14%3197911.95000070000211145.61%571417000.3912010101
13Dylan OlsenFlyers (PHI)D8221618020771188535362.35%78139717.040332740002113010.00%02044000.2614000001
14Travis BoydFlyers (PHI)C525914714069919715465.15%1465012.520003330001443048.97%38856000.4300000301
15Andy AndreoffFlyers (PHI)LW8256110315103477822576.41%167138.700000401111022046.67%30116000.3100001001
16Brandon ManningFlyers (PHI)D824711-898201541217725295.19%76131716.07325662000278020.00%02930000.1711112001
17Sam SteelFlyers (PHI)C825510-116047788236586.10%277028.5700000000061243.81%3881910000.2801000000
18Micheal HaleyFlyers (PHI)LW20033410022135320.00%11587.9501103000090061.54%1301000.3800000000
19Iiro PakarinenFlyers (PHI)RW74022-91556558238210.00%155707.71000010000460040.91%4426000.0700001000
20Jyrki JokipakkaFlyers (PHI)D9101-200111463416.67%813615.130000000006100.00%009000.1500000000
21Michael LattaFlyers (PHI)C3000001402621115110.00%62016.7100000000010057.33%7511000.0000000000
Stats d'équipe Total ou en Moyenne14762183856032694817024082457274886414917.93%8952434216.497312119433126184610502322322849.93%5540540481020.50288911815333037
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
1Michael GarnettFlyers (PHI)70362560.9162.554101201742076820300.736537011784
2Collin DeliaFlyers (PHI)197170.9192.499390039480229200.629351270051
Stats d'équipe Total ou en Moyenne894326130.9172.5450412021325561049500.6938882817135


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
Alex LyonFlyers (PHI)G271992-12-09 07:25:34Yes201 Lbs6 ft1NoNoNo2Pro & Farm750,000$0$0$No750,000$
Andy AndreoffFlyers (PHI)LW281991-05-17 23:11:13Yes203 Lbs6 ft1NoNoNo2Pro & Farm575,000$0$0$No575,000$
Artturi LehkonenFlyers (PHI)RW241995-07-04 08:48:34Yes177 Lbs6 ft0NoNoNo1Pro & Farm839,167$0$0$No
Brandon ManningFlyers (PHI)D291990-06-04 17:11:13Yes205 Lbs6 ft1NoNoNo1Pro & Farm900,000$0$0$No
Brett HowdenFlyers (PHI)C221998-03-29 03:03:41Yes195 Lbs6 ft3NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$
Brian FlynnFlyers (PHI)LW311988-07-26 05:11:13No184 Lbs6 ft1NoNoNo2Pro & Farm575,000$0$0$No575,000$
Colin McdonaldFlyers (PHI)RW351984-09-30 05:11:13No215 Lbs6 ft1NoNoNo2Pro & Farm575,000$0$0$No575,000$
Collin DeliaFlyers (PHI)G251994-06-20 07:49:44Yes208 Lbs6 ft2NoNoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$
Derek ForbortFlyers (PHI)D281992-03-04 05:11:13Yes219 Lbs6 ft4NoNoNo3Pro & Farm1,250,000$0$0$No1,250,000$1,250,000$
Dylan OlsenFlyers (PHI)D291991-01-03 11:11:13No225 Lbs6 ft2NoNoNo2Pro & Farm1,250,000$0$0$No1,250,000$
Iiro PakarinenFlyers (PHI)RW281991-08-25 23:11:13Yes212 Lbs6 ft1NoNoNo2Pro & Farm575,000$0$0$No575,000$
J.T. CompherFlyers (PHI)RW251995-04-08 08:55:06Yes193 Lbs6 ft0NoNoNo1Pro & Farm925,000$0$0$No
Jacob LarssonFlyers (PHI)D231997-04-29 08:51:10Yes197 Lbs6 ft2NoNoNo1Pro & Farm894,166$0$0$No
Jason BacashihuaFlyers (PHI)G371982-09-20 17:11:14No189 Lbs5 ft11NoNoNo1Pro & Farm1,500,000$0$0$No
Jesperi KotkaniemiFlyers (PHI)C192000-07-06 03:08:04Yes184 Lbs6 ft2NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$
Jyrki JokipakkaFlyers (PHI)D281991-08-20 23:11:13Yes196 Lbs6 ft3NoNoNo2Pro & Farm700,000$0$0$No700,000$
Mark BorowieckiFlyers (PHI)D301989-07-12 11:11:13Yes211 Lbs6 ft2NoNoNo1Pro & Farm900,000$0$0$No
Matt TennysonFlyers (PHI)D301990-04-23 17:11:13Yes205 Lbs6 ft2NoNoNo1Pro & Farm800,000$0$0$No
Matthew TkachukFlyers (PHI)LW221997-12-11 08:57:18Yes202 Lbs6 ft2NoNoNo1Pro & Farm925,000$0$0$No
Michael GarnettFlyers (PHI)G371982-11-25 17:11:14No217 Lbs6 ft1NoNoNo3Pro & Farm1,500,000$0$0$No1,500,000$1,500,000$
Michael LattaFlyers (PHI)C281991-05-25 23:11:13No215 Lbs6 ft0NoNoNo1Pro & Farm575,000$0$0$No
Micheal HaleyFlyers (PHI)LW341986-03-30 06:40:13Yes205 Lbs5 ft11NoNoNo3Pro & Farm575,000$0$0$No575,000$575,000$
Mikhail VorobyevFlyers (PHI)C231997-01-05 08:21:53Yes194 Lbs6 ft2NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$
Sam SteelFlyers (PHI)C221998-02-03 03:05:49Yes186 Lbs5 ft11NoNoNo3Pro & Farm863,333$0$0$No863,333$863,333$
Tom KuhnhacklFlyers (PHI)LW281992-01-21 17:39:57Yes196 Lbs6 ft2NoNoNo3Pro & Farm600,000$0$0$No600,000$600,000$
Travis BoydFlyers (PHI)C261993-09-14 07:33:39Yes185 Lbs5 ft11NoNoNo3Pro & Farm800,000$0$0$No800,000$800,000$
Zach WerenskiFlyers (PHI)D221997-07-19 08:59:11Yes209 Lbs6 ft2NoNoNo1Pro & Farm925,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2727.41201 Lbs6 ft12.00872,099$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matthew TkachukJesperi KotkaniemiJ.T. Compher35122
2Tom KuhnhacklBrett HowdenArtturi Lehkonen35122
3Brian FlynnTravis BoydColin Mcdonald25122
4Andy AndreoffSam SteelMicheal Haley5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach WerenskiDerek Forbort35122
2Brandon ManningMatt Tennyson35122
3Dylan OlsenMark Borowiecki30122
4Zach WerenskiDerek Forbort0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matthew TkachukJesperi KotkaniemiJ.T. Compher60122
2Tom KuhnhacklBrett HowdenArtturi Lehkonen40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach WerenskiDerek Forbort60122
2Brandon ManningMatt Tennyson40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Matthew TkachukJ.T. Compher60122
2Artturi LehkonenJesperi Kotkaniemi40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach WerenskiDerek Forbort60122
2Brandon ManningMatt Tennyson40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Matthew Tkachuk60122Zach WerenskiDerek Forbort60122
2J.T. Compher40122Brandon ManningMatt Tennyson40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Matthew TkachukJ.T. Compher60122
2Artturi LehkonenJesperi Kotkaniemi40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Zach WerenskiDerek Forbort60122
2Brandon ManningMatt Tennyson40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matthew TkachukJesperi KotkaniemiJ.T. CompherZach WerenskiDerek Forbort
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matthew TkachukJesperi KotkaniemiJ.T. CompherZach WerenskiDerek Forbort
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Micheal Haley, Colin Mcdonald, Brian FlynnMicheal Haley, Colin McdonaldBrian Flynn
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dylan Olsen, Mark Borowiecki, Brandon ManningDylan OlsenMark Borowiecki, Brandon Manning
Tirs de Pénalité
Matthew Tkachuk, J.T. Compher, Artturi Lehkonen, Jesperi Kotkaniemi, Brett Howden
Gardien
#1 : Collin Delia, #2 : Michael Garnett


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
Total82292603111122292254411610010861291141541131602136100111-11990.60422938561400538181312748961940826108255689595024083527320.74%3767580.05%41139219451.91%1052217848.30%575110052.27%1806102417857801453720
_Since Last GM Reset82292603111122292254411610010861291141541131602136100111-11990.60422938561400538181312748961940826108255689595024083527320.74%3767580.05%41139219451.91%1052217848.30%575110052.27%1806102417857801453720
_Vs Conference5720170317917116832912601055103891428811021246879-11700.61417128645700538181311856961940826108177859781817302956522.03%3196779.00%41139219451.91%1052217848.30%575110052.27%1806102417857801453720
_Vs Division313140314687110-231636010335257-51508021133553-18270.4358714122800538181319929619408261089443155349761983718.69%2084279.81%21139219451.91%1052217848.30%575110052.27%1806102417857801453720

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8299W222938561427482556895950240800
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
822926311112229225
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4116101086129114
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4113162136100111
Derniers 10 Matchs
WLOTWOTL SOWSOL
510004
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3527320.74%3767580.05%4
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
96194082610853818131
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
1139219451.91%1052217848.30%575110052.27%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1806102417857801453720


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
2 - 2019-10-079Islanders5Flyers6WXXR5Sommaire du Match
4 - 2019-10-0920Flyers2Capitals3LXXR5Sommaire du Match
6 - 2019-10-1130Devils2Flyers3WSommaire du Match
8 - 2019-10-1342Flyers1Devils2LXXSommaire du Match
9 - 2019-10-1450Flyers1Penguins4LR5Sommaire du Match
12 - 2019-10-1764Capitals9Flyers8LXXSommaire du Match
15 - 2019-10-2078Flyers2Rangers3LSommaire du Match
17 - 2019-10-2288Canadiens3Flyers6WR2Sommaire du Match
20 - 2019-10-25104Islanders5Flyers2LSommaire du Match
23 - 2019-10-28123Rangers3Flyers4WXSommaire du Match
26 - 2019-10-31143Flyers3Capitals7LR5Sommaire du Match
27 - 2019-11-01148Penguins2Flyers5WR5Sommaire du Match
28 - 2019-11-02150Flyers1Bruins3LSommaire du Match
30 - 2019-11-04160Flyers3Islanders4LXR5Sommaire du Match
34 - 2019-11-08177Penguins5Flyers2LR5Sommaire du Match
36 - 2019-11-10190Flyers4Rangers3WXSommaire du Match
38 - 2019-11-12201Red Wings2Flyers3WR2Sommaire du Match
40 - 2019-11-14215Flyers1Sharks3LSommaire du Match
42 - 2019-11-16224Flyers4Penguins3WXXR5Sommaire du Match
43 - 2019-11-17232Predators2Flyers1LSommaire du Match
46 - 2019-11-20246Flyers4Oilers1WSommaire du Match
48 - 2019-11-22256Bruins1Flyers3WR2Sommaire du Match
51 - 2019-11-25273Ducks3Flyers1LSommaire du Match
53 - 2019-11-27284Flyers2Islanders4LR5Sommaire du Match
55 - 2019-11-29295Flyers8Blues2WSommaire du Match
57 - 2019-12-01303Sharks4Flyers1LSommaire du Match
61 - 2019-12-05321Blues2Flyers4WSommaire du Match
64 - 2019-12-08335Flyers3Red Wings2WR2Sommaire du Match
66 - 2019-12-10345Islanders2Flyers3WXXSommaire du Match
68 - 2019-12-12361Flyers2Predators1WSommaire du Match
70 - 2019-12-14369Canucks1Flyers3WSommaire du Match
72 - 2019-12-16382Flyers1Rangers2LSommaire du Match
75 - 2019-12-19394Oilers2Flyers1LSommaire du Match
77 - 2019-12-21406Flyers3Canucks2WSommaire du Match
79 - 2019-12-23417Flames1Flyers2WSommaire du Match
82 - 2019-12-26437Flyers1Predators5LSommaire du Match
83 - 2019-12-27442Red Wings5Flyers6WXXR2Sommaire du Match
86 - 2019-12-30458Flyers3Bruins2WSommaire du Match
88 - 2020-01-01466Islanders4Flyers3LR5Sommaire du Match
92 - 2020-01-05487Senateurs1Flyers3WR2Sommaire du Match
94 - 2020-01-07497Flyers2Red Wings1WXXR2Sommaire du Match
97 - 2020-01-10510Rangers2Flyers1LSommaire du Match
100 - 2020-01-13531Wild1Flyers2WXXSommaire du Match
102 - 2020-01-15539Flyers5Capitals6LXXR5Sommaire du Match
105 - 2020-01-18554Flyers3Maple Leafs1WSommaire du Match
106 - 2020-01-19561Kings2Flyers3WXXSommaire du Match
109 - 2020-01-22579Stars1Flyers2WXXSommaire du Match
112 - 2020-01-25597Flyers1Wild3LSommaire du Match
114 - 2020-01-27603Penguins2Flyers4WR5Sommaire du Match
116 - 2020-01-29614Flyers1Kings2LSommaire du Match
118 - 2020-01-31626Devils3Flyers2LXXSommaire du Match
120 - 2020-02-02632Flyers4Sabres1WR2Sommaire du Match
122 - 2020-02-04645Flyers2Ducks3LXXSommaire du Match
124 - 2020-02-06653Flyers1Bruins3LR2Sommaire du Match
125 - 2020-02-07658Canadiens1Flyers2WR2Sommaire du Match
128 - 2020-02-10676Capitals4Flyers2LSommaire du Match
130 - 2020-02-12686Flyers3Avalanche1WSommaire du Match
132 - 2020-02-14701Avalanche1Flyers2WSommaire du Match
134 - 2020-02-16712Flyers2Devils5LSommaire du Match
136 - 2020-02-18725Senateurs4Flyers5WXXR2Sommaire du Match
137 - 2020-02-19731Flyers1Penguins3LR5Sommaire du Match
141 - 2020-02-23745Flyers2Maple Leafs4LSommaire du Match
142 - 2020-02-24755Blackhawks5Flyers4LXXSommaire du Match
146 - 2020-02-28773Canadiens2Flyers4WR2Sommaire du Match
148 - 2020-03-01784Flyers3Islanders2WXSommaire du Match
150 - 2020-03-03798Capitals4Flyers3LXXR5Sommaire du Match
152 - 2020-03-05807Flyers1Devils2LSommaire du Match
155 - 2020-03-08823Devils3Flyers1LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
157 - 2020-03-10831Flyers2Canadiens1WR2Sommaire du Match
159 - 2020-03-12844Flyers2Sabres1WSommaire du Match
160 - 2020-03-13849Rangers2Flyers3WXXSommaire du Match
162 - 2020-03-15861Flyers4Senateurs2WR2Sommaire du Match
164 - 2020-03-17869Flyers3Stars2WXXSommaire du Match
166 - 2020-03-19879Sabres3Flyers2LXXR2Sommaire du Match
169 - 2020-03-22895Flyers1Flames4LSommaire du Match
170 - 2020-03-23899Flyers3Canadiens4LXXR2Sommaire du Match
172 - 2020-03-25909Bruins5Flyers4LXXSommaire du Match
176 - 2020-03-29928Flyers3Senateurs1WR2Sommaire du Match
178 - 2020-03-31935Maple Leafs1Flyers5WR2Sommaire du Match
181 - 2020-04-03952Flyers2Blackhawks3LXXSommaire du Match
183 - 2020-04-05959Maple Leafs2Flyers5WR2Sommaire du Match
187 - 2020-04-09978Sabres2Flyers3WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets4525
Assistance56,18137,548
Assistance PCT68.51%91.58%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2286 - 76.20% 90,166$3,696,811$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,901,536$ 2,354,667$ 1,622,167$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
12,393$ 2,301,519$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 15,551$ 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
Saison Régulière
1378253701546202229-2739131701413101114-1339122000133101115-14502023345363148836614266793491380458254585077820733586417.88%3647778.85%61081202853.30%1098199355.09%576108053.33%1747100916477251349680
1482292603111122292254411610010861291141541131602136100111-119922938561400538181312748961940826108255689595024083527320.74%3767580.05%41139219451.91%1052217848.30%575110052.27%1806102417857801453720
Total Saison Régulière16054630461518431454-2380292702499230228280253602269201226-25149431719115031101164147455415189518531630166510117451728448171013719.30%74015279.46%102220422252.58%2150417151.55%1151218052.80%355320343432150528031400