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Flyers

GP: 47 | W: 24 | L: 22 | OTL: 1 | P: 49
GF: 126 | GA: 133 | PP%: 18.13% | PK%: 81.77%
DG: Francois Gamache | Morale : 57 | Moyenne d'Équipe : 69
Prochain matchs #754 vs Blues
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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
1Claude Giroux (C)XXX100.00573984836985898687847572868093054740
2Tom Wilson (A)X99.00977556729083847158737784697176068720
3James van RiemsdykX100.00574289758781837456737859767973051700
4Jeff SkinnerXXX100.00563984827183867973718056827569067700
5Nazem KadriX100.00785264777382857483767562777873068700
6Micheal FerlandXX100.00906269728179777158737062697568067690
7Tyler BertuzziXX100.00745678737783877256757459676966069690
8Cody EakinX100.00743987687178836784697078667769067680
9Ondrej KaseX100.00543989747283777256737062746965067670
10Evan RodriguesXXX100.00574285706977816879676370697368057660
11Martin NecasXX100.00633988717880776970686763726266067660
12Tobias RiederXXX100.00673983667073826568636176667367067650
13Jacob TroubaX100.00845169738589917230806785567167073710
14Torey Krug (A)X100.00634574786787827730896961637772054710
15Brady SkjeiX100.00844575728587897130746980567167067700
16Justin BraunX100.00814283638185876230735677498273067670
17Devon ToewsX100.00623988697685816830766662547167067670
18Dylan DeMeloX100.00824379637385876230735578517367050660
Rayé
MOYENNE D'ÉQUIPE99.9471467972768384715674696967747006469
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
1Devan Dubnyk98.0091959397908991908991908488067760
2Keith Kinkaid100.0073767481727173727173727985067650
Rayé
MOYENNE D'ÉQUIPE99.008286848981808281808281828706771
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John Tortorella81908289928553USA611100,000$


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
1Claude GirouxFlyersC/LW/RW43112536-1008110144291187.64%685319.852683314911221093151.78%86900000.8401000013
2Jacob TroubaFlyersD47102434-1371151478088275511.36%75115024.496612541531122153100.00%000000.5900201213
3Nazem KadriFlyersC47141327-83157488115316812.17%281517.35391224145000074049.45%100100010.6601001422
4James van RiemsdykFlyersLW45719264204439830687.14%277517.2427919127000060035.59%5900000.6701000031
5Jeff SkinnerFlyersC/LW/RW47141226-92096092297915.22%085318.16358211540001324042.50%8000000.6112000120
6Tom WilsonFlyersRW47111223-491151567111540979.57%2582917.6510121200071722246.55%5800000.5501102321
7Cody EakinFlyersC47912217803611778174911.54%972415.420000000062020151.80%102500000.5800000111
8Brady SkjeiFlyersD4771421-450088537823568.97%46103622.05213411410001157000.00%000000.4100000010
9Micheal FerlandFlyersLW/RW47516210480114439924655.05%568314.5419102796000102043.48%4600000.6111000110
10Torey KrugFlyersD4631720-529526567015424.29%47104622.7536956151000099100.00%000000.3800000210
11Devon ToewsFlyersD4751318780282940112612.50%4786718.4554925141000060010.00%000000.4200000010
12Justin BraunFlyersD44213159480109472911226.90%5374316.91011271011129000.00%000000.4000000120
13Ondrej KaseFlyersRW4777144004308021438.75%152511.18011319000000138.71%3100100.5300000020
14Martin NecasFlyersC/RW477613-280202144134415.91%14259.04022542000002048.48%3300000.6100000011
15Tyler BertuzziFlyersLW/RW4765111181069416628649.09%177816.5740418148000002044.64%5600000.2800002004
16Evan RodriguesFlyersC/LW/RW47268040766409285.00%74138.81000010221710049.78%44600000.3900000101
17Tobias RiederFlyersC/LW/RW47257118042333112316.45%84138.79000000112702036.36%2200000.3400000003
18Dylan DeMeloFlyersD47167-153809243184105.56%2969414.7800002000026010.00%000000.2000000000
19Joel FarabeePhantoms (PHI)LW4011040016150.00%0358.950000000000000.00%100000.5600000000
20Dan HamhuisPhantoms (PHI)D3000000710000.00%94916.5900000000013000.00%000000.0000000000
21Matt ReadPhantoms (PHI)RW5000-300232140.00%1408.1600000000000033.33%300000.0000000000
22Michael PaliottaPhantoms (PHI)D1000-100100000.00%01111.350000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne849123226349-32478501043103613333769749.23%3741376916.22325789330149635824131323749.92%373000110.5127306162120
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
1Devan DubnykFlyers46242110.9042.7727758312813310010.5008461541
2Keith KinkaidFlyers10100.8893.0060003270000.0000146000
Stats d'équipe Total ou en Moyenne47242210.9042.7728358313113580010.50084747541


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
Brady SkjeiFlyersD251994-03-26No210 Lbs6 ft3NoNoNo5Pro & Farm5,250,000$5,250,000$2,307,692$No5,250,000$5,250,000$5,250,000$5,250,000$Lien / Lien NHL
Claude GirouxFlyersC/LW/RW311988-01-12No185 Lbs5 ft11NoNoNo3Pro & Farm8,275,000$8,275,000$3,637,363$No8,275,000$8,275,000$Lien / Lien NHL
Cody EakinFlyersC281991-05-24No183 Lbs6 ft0NoNoNo1Pro & Farm3,850,000$3,850,000$1,692,308$NoLien / Lien NHL
Devan DubnykFlyersG331986-05-04No224 Lbs6 ft6NoNoNo2Pro & Farm4,333,000$4,333,000$1,904,615$No4,333,000$Lien / Lien NHL
Devon ToewsFlyersD251994-02-21No191 Lbs6 ft1NoNoNo1Pro & Farm700,000$700,000$307,692$NoLien / Lien NHL
Dylan DeMeloFlyersD261993-05-01No191 Lbs6 ft0NoNoNo1Pro & Farm900,000$900,000$395,604$NoLien / Lien NHL
Evan RodriguesFlyersC/LW/RW261993-07-28No184 Lbs5 ft11NoNoNo1Pro & Farm2,000,000$2,000,000$879,121$NoLien / Lien NHL
Jacob TroubaFlyersD251994-02-26No209 Lbs6 ft3NoNoNo7Pro & Farm8,000,000$8,000,000$3,516,484$No8,000,000$8,000,000$8,000,000$8,000,000$8,000,000$8,000,000$Lien / Lien NHL
James van RiemsdykFlyersLW301989-05-04No217 Lbs6 ft3NoNoNo4Pro & Farm7,000,000$7,000,000$3,076,923$No7,000,000$7,000,000$7,000,000$Lien / Lien NHL
Jeff SkinnerFlyersC/LW/RW271992-05-16No195 Lbs5 ft11NoNoNo8Pro & Farm9,000,000$9,000,000$3,956,044$No9,000,000$9,000,000$9,000,000$9,000,000$9,000,000$9,000,000$9,000,000$Lien / Lien NHL
Justin BraunFlyersD321987-02-10No205 Lbs6 ft2NoNoNo1Pro & Farm3,800,000$3,800,000$1,670,330$NoLien / Lien NHL
Keith KinkaidFlyersG301989-07-04No186 Lbs6 ft3NoNoNo1Pro & Farm1,750,000$1,750,000$769,231$NoLien / Lien NHL
Martin NecasFlyersC/RW201999-01-15No189 Lbs6 ft2NoNoNo2Pro & Farm1,431,666$1,431,666$629,304$No1,431,666$Lien / Lien NHL
Micheal FerlandFlyersLW/RW271992-04-20No217 Lbs6 ft1NoNoNo4Pro & Farm3,500,000$3,500,000$1,538,462$No3,500,000$3,500,000$3,500,000$Lien / Lien NHL
Nazem KadriFlyersC291990-10-06No192 Lbs6 ft0NoNoNo3Pro & Farm4,500,000$4,500,000$1,978,022$No4,500,000$4,500,000$Lien / Lien NHL
Ondrej KaseFlyersRW231995-11-08No190 Lbs6 ft0NoNoNo2Pro & Farm2,600,000$2,600,000$1,142,857$No2,600,000$Lien / Lien NHL
Tobias RiederFlyersC/LW/RW261993-01-10No186 Lbs5 ft11NoNoNo1Pro & Farm700,000$700,000$307,692$NoLien / Lien NHL
Tom WilsonFlyersRW251994-03-29No220 Lbs6 ft4NoNoNo5Pro & Farm5,166,666$5,166,666$2,271,062$No5,166,666$5,166,666$5,166,666$5,166,666$Lien / Lien NHL
Torey KrugFlyersD281991-04-12No186 Lbs5 ft9NoNoNo1Pro & Farm5,250,000$5,250,000$2,307,692$NoLien / Lien NHL
Tyler BertuzziFlyersLW/RW241995-02-24No199 Lbs6 ft1NoNoNo1Pro & Farm1,400,000$1,400,000$615,385$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2027.00198 Lbs6 ft12.703,970,317$

Somme Salaire 1e Année Somme Salaire 2e Année Somme Salaire 3e Année Somme Salaire 4e Année Somme Salaire 5e Année
79,406,332$59,056,332$50,691,666$37,916,666$27,416,666$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1James van RiemsdykClaude GirouxTom Wilson30023
2Jeff SkinnerNazem KadriTyler Bertuzzi30023
3Micheal FerlandCody EakinOndrej Kase25023
4Tobias RiederEvan RodriguesMartin Necas15023
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brady SkjeiJacob Trouba30023
2Torey KrugJustin Braun30032
3Devon ToewsDylan DeMelo25122
4Torey KrugJacob Trouba15023
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1James van RiemsdykClaude GirouxMicheal Ferland60014
2Jeff SkinnerNazem KadriTyler Bertuzzi40023
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Torey KrugJacob Trouba60023
2Brady SkjeiDevon Toews40023
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Cody EakinTom Wilson60140
2Evan RodriguesTobias Rieder40140
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brady SkjeiJacob Trouba60140
2Torey KrugJustin Braun40140
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Claude Giroux60140Brady SkjeiJacob Trouba60140
2Cody Eakin40140Torey KrugJustin Braun40140
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Claude GirouxJames van Riemsdyk60023
2Nazem KadriJeff Skinner40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Torey KrugJacob Trouba60023
2Brady SkjeiDevon Toews40023
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jeff SkinnerClaude GirouxTom WilsonJacob TroubaTorey Krug
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Claude GirouxCody EakinTom WilsonJacob TroubaBrady Skjei
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Ondrej Kase, Martin Necas, Cody EakinOndrej Kase, Martin NecasClaude Giroux
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Justin Braun, Torey Krug, Brady SkjeiJustin BraunDevon Toews, Torey Krug
Tirs de Pénalité
Claude Giroux, Jeff Skinner, Nazem Kadri, Cody Eakin, Ondrej Kase
Gardien
#1 : Devan Dubnyk, #2 : Keith Kinkaid
Lignes d'Attaque Perso. en Prol.
Claude Giroux, Tom Wilson, Jeff Skinner, Nazem Kadri, Micheal Ferland, Tyler Bertuzzi, Tyler Bertuzzi, Evan Rodrigues, Cody Eakin, Ondrej Kase, Martin Necas
Lignes de Défense Perso. en Prol.
Jacob Trouba, Brady Skjei, Torey Krug, Devon Toews, Justin Braun


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
1Blackhawks311010006601010000003-32100100063340.667691500113171242026188315182800.00%18477.78%0815162450.18%831167049.76%34168150.07%674476223718
2Blue Jackets2020000028-61010000004-41010000024-200.000246000200572216190542024496116.67%10190.00%0815162450.18%831167049.76%34168150.07%473246152612
3Blues10001000651000000000001000100065121.00061016003021319615127910263133.33%40100.00%0815162450.18%831167049.76%34168150.07%2415228146
4Bruins2020000047-31010000023-11010000024-200.00048120012106319123205724213610440.00%8187.50%0815162450.18%831167049.76%34168150.07%493544152512
5Canadiens2110000057-2000000000002110000057-220.50051015001310532117150591714434125.00%70100.00%1815162450.18%831167049.76%34168150.07%463249132312
6Canucks412010001112-13020100069-31100000053240.50011213210325111938334719623409516212.50%19573.68%0815162450.18%831167049.76%34168150.07%966895284825
7Capitals11000000303000000000001100000030321.000358012100294151003786244125.00%20100.00%0815162450.18%831167049.76%34168150.07%2317247115
8Coyotes1010000013-2000000000001010000013-200.0001230001003289150276923400.00%20100.00%0815162450.18%831167049.76%34168150.07%2518206136
9Devils1010000034-11010000034-10000000000000.0003580011102158803074175120.00%20100.00%0815162450.18%831167049.76%34168150.07%2215247125
10Ducks210000016601000000123-11100000043130.7506111700024049915216531414427114.29%7185.71%0815162450.18%831167049.76%34168150.07%493348152612
11Flames11000000523000000000001100000052321.0005914002210361019703351224300.00%5180.00%0815162450.18%831167049.76%34168150.07%2215247126
12Golden Knights1010000045-11010000045-10000000000000.00048120001302456130428122111100.00%6183.33%0815162450.18%831167049.76%34168150.07%1913277136
13Hurricanes2010100056-1000000000002010100056-120.5005813001211661719228582914418225.00%7271.43%0815162450.18%831167049.76%34168150.07%523645142512
14Jets10001000541100010005410000000000021.0005101500130127101151411116345120.00%7271.43%0815162450.18%831167049.76%34168150.07%2215267125
15Kings10001000431100010004310000000000021.0004610000211399151411654175240.00%20100.00%0815162450.18%831167049.76%34168150.07%2820187137
16Lightning3120000068-2211000005411010000014-320.33361117001140611923190862436726116.67%18383.33%0815162450.18%831167049.76%34168150.07%654477223717
17Maple Leafs22000000734110000003031100000043141.0007142101232053151721062171831700.00%8275.00%1815162450.18%831167049.76%34168150.07%473348152312
18Oilers11000000312110000003120000000000021.00035800111034111670299685120.00%30100.00%0815162450.18%831167049.76%34168150.07%2720216115
19Panthers21100000440110000003031010000014-320.500471101211056251615058151847700.00%7185.71%0815162450.18%831167049.76%34168150.07%523643142412
20Penguins3120000069-31010000023-12110000046-220.33367130020406328191608418295610110.00%12466.67%1815162450.18%831167049.76%34168150.07%664575223819
21Predators1010000034-11010000034-10000000000000.000358001200351381402736263266.67%3166.67%0815162450.18%831167049.76%34168150.07%2618227115
22Rangers3110001011101201000106601100000054140.6671119300045138631282579427526614535.71%16381.25%0815162450.18%831167049.76%34168150.07%684578233719
23Red Wings21001000633000000000002100100063341.00061117002211781826322642821466116.67%80100.00%0815162450.18%831167049.76%34168150.07%463250142311
24Sabres211000003301010000001-11100000032120.500369002010612224150572235678112.50%11190.91%0815162450.18%831167049.76%34168150.07%422752142511
25Senateurs1010000014-31010000014-30000000000000.00012300100027117903212825200.00%3166.67%0815162450.18%831167049.76%34168150.07%2216266116
26Stars1010000035-21010000035-20000000000000.0003470020103917101202106216116.67%330.00%0815162450.18%831167049.76%34168150.07%3022176116
Total47162207011126133-724514030115867-9231180400068662490.5211262223481336424010134743043246428135939949610651713118.13%2033781.77%3815162450.18%831167049.76%34168150.07%11217781132348585290
27Wild11000000312110000003120000000000021.0003580002103710171002771026800.00%50100.00%0815162450.18%831167049.76%34168150.07%2719217115
_Since Last GM Reset47162207011126133-724514030115867-9231180400068662490.5211262223481336424010134743043246428135939949610651713118.13%2033781.77%3815162450.18%831167049.76%34168150.07%11217781132348585290
_Vs Conference281015020106676-101238000102529-41677020004147-6260.4646611718303222318577425724725817832268300620971919.59%1191984.03%3815162450.18%831167049.76%34168150.07%653450688209347171
_Vs Division1237010103037-7504000101117-6733010001920-1100.4173048780110117432210710510015357109129253471123.40%491079.59%1815162450.18%831167049.76%34168150.07%2801922959115174

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4749L112622234813471359399496106513
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4716227011126133
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2451430115867
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2311840006866
Derniers 10 Matchs
WLOTWOTL SOWSOL
441001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1713118.13%2033781.77%3
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
4304324642836424010
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
815162450.18%831167049.76%34168150.07%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
11217781132348585290


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 - 2020-10-0610Flyers2Penguins5LSommaire du Match
4 - 2020-10-0828Sabres1Flyers0LR3Sommaire du Match
6 - 2020-10-1041Wild1Flyers3WSommaire du Match
9 - 2020-10-1364Canucks3Flyers1LSommaire du Match
11 - 2020-10-1578Flyers3Red Wings1WSommaire du Match
13 - 2020-10-1791Flyers2Bruins4LSommaire du Match
15 - 2020-10-19106Maple Leafs0Flyers3WSommaire du Match
17 - 2020-10-21124Canucks2Flyers3WXSommaire du Match
18 - 2020-10-22132Flyers2Canadiens5LSommaire du Match
21 - 2020-10-25147Flyers3Blackhawks1WSommaire du Match
23 - 2020-10-27163Flyers6Blues5WXSommaire du Match
25 - 2020-10-29179Senateurs4Flyers1LSommaire du Match
28 - 2020-11-01198Lightning2Flyers4WSommaire du Match
30 - 2020-11-03213Flyers2Penguins1WSommaire du Match
32 - 2020-11-05230Blue Jackets4Flyers0LSommaire du Match
35 - 2020-11-08250Flyers1Panthers4LSommaire du Match
37 - 2020-11-10264Golden Knights5Flyers4LSommaire du Match
40 - 2020-11-13284Flyers3Capitals0WSommaire du Match
41 - 2020-11-14293Predators4Flyers3LSommaire du Match
44 - 2020-11-17316Rangers3Flyers4WXXSommaire du Match
47 - 2020-11-20335Flyers2Blue Jackets4LSommaire du Match
48 - 2020-11-21349Jets4Flyers5WXSommaire du Match
51 - 2020-11-24373Flyers3Red Wings2WXSommaire du Match
52 - 2020-11-25378Penguins3Flyers2LSommaire du Match
55 - 2020-11-28400Flyers1Coyotes3LSommaire du Match
56 - 2020-11-29410Stars5Flyers3LSommaire du Match
59 - 2020-12-02430Flyers4Maple Leafs3WSommaire du Match
60 - 2020-12-03441Bruins3Flyers2LSommaire du Match
63 - 2020-12-06463Flyers1Lightning4LSommaire du Match
65 - 2020-12-08472Kings3Flyers4WXSommaire du Match
67 - 2020-12-10487Flyers5Hurricanes4WXSommaire du Match
69 - 2020-12-12498Flyers5Flames2WSommaire du Match
70 - 2020-12-13510Oilers1Flyers3WSommaire du Match
73 - 2020-12-16531Devils4Flyers3LSommaire du Match
75 - 2020-12-18548Flyers4Ducks3WSommaire du Match
78 - 2020-12-21565Rangers3Flyers2LSommaire du Match
80 - 2020-12-23585Flyers3Canadiens2WSommaire du Match
82 - 2020-12-25595Canucks4Flyers2LSommaire du Match
84 - 2020-12-27611Flyers5Rangers4WSommaire du Match
86 - 2020-12-29625Blackhawks3Flyers0LSommaire du Match
88 - 2020-12-31643Flyers3Sabres2WR3Sommaire du Match
90 - 2021-01-02657Ducks3Flyers2LXXSommaire du Match
92 - 2021-01-04668Flyers3Blackhawks2WXSommaire du Match
95 - 2021-01-07690Lightning2Flyers1LSommaire du Match
98 - 2021-01-10710Flyers5Canucks3WSommaire du Match
100 - 2021-01-12722Panthers0Flyers3WSommaire du Match
102 - 2021-01-14740Flyers0Hurricanes2LSommaire du Match
104 - 2021-01-16754Blues-Flyers-
107 - 2021-01-19778Maple Leafs-Flyers-
109 - 2021-01-21786Flyers-Sharks-
111 - 2021-01-23801Flyers-Bruins-
113 - 2021-01-25814Hurricanes-Flyers-
116 - 2021-01-28838Flyers-Oilers-
118 - 2021-01-30848Avalanche-Flyers-
119 - 2021-01-31860Flyers-Penguins-
121 - 2021-02-02875Flyers-Kings-
123 - 2021-02-04883Senateurs-Flyers-
127 - 2021-02-08908Wild-Flyers-
129 - 2021-02-10924Flyers-Senateurs-
130 - 2021-02-11936Canadiens-Flyers-
133 - 2021-02-14950Flyers-Panthers-
135 - 2021-02-16968Islanders-Flyers-
137 - 2021-02-18984Flyers-Wild-
139 - 2021-02-20996Flyers-Golden Knights-
140 - 2021-02-211005Blue Jackets-Flyers-
142 - 2021-02-231025Flyers-Avalanche-
144 - 2021-02-251035Capitals-Flyers-
147 - 2021-02-281052Flyers-Jets-
149 - 2021-03-021066Flames-Flyers-
152 - 2021-03-051090Flyers-Stars-
153 - 2021-03-061099Islanders-Flyers-
155 - 2021-03-081112Flyers-Blues-
156 - 2021-03-091126Sharks-Flyers-
159 - 2021-03-121151Coyotes-Flyers-
161 - 2021-03-141164Flyers-Devils-
165 - 2021-03-181185Red Wings-Flyers-
167 - 2021-03-201193Flyers-Devils-
169 - 2021-03-221212Sabres-Flyers-
170 - 2021-03-231217Flyers-Islanders-
172 - 2021-03-251223Flyers-Predators-
177 - 2021-03-301247Capitals-Flyers-
179 - 2021-04-011256Flyers-Islanders-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité de l'Aréna60005000200040001000
Prix des Billets100603525200
Assistance137,573112,97845,92291,01422,764
Attendance PCT95.54%94.15%95.67%94.81%94.85%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
17 17094 - 94.97% 615,642$14,775,414$18000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des CoachsValeur du Cap Salarial Spécial
44,124,973$ 79,406,332$ 54,456,332$ 0$ 0$
Cap Salarial Par JourCap salarial à ce jourTaxe de Luxe TotaleJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
79,406,332$ 44,068,964$ 0$ 20 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
10,465,918$ 80 436,848$ 34,947,840$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées Compte Bancaire Actuel Compte Bancaire Projeté
35,542,240$ 30,312,651$ 5,236,329$
Cap Salarial de la Saison ÉstiméCap Salarial DisponibleCap Salarial MaximumAu dessus du Plafond Salarial Minimum
79,406,332$ 2,093,668$ 81,500,000$ 19,206,332$



Charte de Profondeur

Ailier GaucheCentreAilier Droit
Claude GirouxAGE:31PO:0OV:74
James van RiemsdykAGE:30PO:0OV:70
Jeff SkinnerAGE:27PO:0OV:70
Micheal FerlandAGE:27PO:0OV:69
Tyler BertuzziAGE:24PO:0OV:69
Evan RodriguesAGE:26PO:0OV:66
Tobias RiederAGE:26PO:0OV:65
Christoffer EhnAGE:23PO:0OV:64
Joel FarabeeAGE:19PO:0OV:64
J.C. BeaudinAGE:22PO:0OV:61
Claude GirouxAGE:31PO:0OV:74
Jeff SkinnerAGE:27PO:0OV:70
Nazem KadriAGE:29PO:0OV:70
Cody EakinAGE:28PO:0OV:68
Evan RodriguesAGE:26PO:0OV:66
Martin NecasAGE:20PO:0OV:66
Riley NashAGE:30PO:0OV:65
Tobias RiederAGE:26PO:0OV:65
Christoffer EhnAGE:23PO:0OV:64
Mikhail VorobyevAGE:22PO:0OV:62
J.C. BeaudinAGE:22PO:0OV:61
Claude GirouxAGE:31PO:0OV:74
Tom WilsonAGE:25PO:0OV:72
Jeff SkinnerAGE:27PO:0OV:70
Micheal FerlandAGE:27PO:0OV:69
Tyler BertuzziAGE:24PO:0OV:69
Ondrej KaseAGE:23PO:0OV:67
Evan RodriguesAGE:26PO:0OV:66
Martin NecasAGE:20PO:0OV:66
Riley NashAGE:30PO:0OV:65
Martin FrkAGE:26PO:0OV:65
Tobias RiederAGE:26PO:0OV:65
Christian FischerAGE:22PO:0OV:63
Matt ReadAGE:33PO:0OV:63
Keegan KolesarAGE:22PO:0OV:62

Défense #1Défense #2Gardien
Jacob TroubaAGE:25PO:0OV:71
Torey KrugAGE:28PO:0OV:71
Brady SkjeiAGE:25PO:0OV:70
Justin BraunAGE:32PO:0OV:67
Devon ToewsAGE:25PO:0OV:67
Dylan DeMeloAGE:26PO:0OV:66
Dan HamhuisAGE:36PO:0OV:64
Michael PaliottaAGE:26PO:0OV:59
Devan DubnykAGE:33PO:0OV:76
Hunter MiskaAGE:24PO:0OV:65
Keith KinkaidAGE:30PO:0OV:65
Jon GilliesAGE:25PO:0OV:64

Éspoirs

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
Éspoir Nom de l'ÉquipeAnnée de Repêchage Choix Total Information Lien
Andrei MarkovFlyers
Arvid CostmarFlyers9124
Bobby ButlerFlyersLien
Clinston FranklinFlyers4122
Conner HurleyFlyers377
Dan GirardiFlyersLien
Dennis RasmussenFlyers
Greg RalloFlyers
Gustav PosslerFlyers368
Hayden HawkeyFlyers4153
Henri IkonenFlyers
Jakub KindlFlyers
Joel VerminFlyers
Michael HouserFlyers
Viktor LoovFlyers

Choix au Repêchage

Année R1R2R3R4R5R6
10PHI DET
11PHI PHI WIN PHI PHI PHI PHI
12PHI PHI PHI PHI PHI PHI
13PHI PHI PHI PHI PHI PHI
14PHI PHI PHI PHI PHI PHI






[2020-12-17 9:54:56 PM] - TRADE : From Golden Knights to Flyers : James van Riemsdyk (70), Dylan DeMelo (66).
[2020-12-17 9:54:56 PM] - TRADE : From Flyers to Golden Knights : Tyler Johnson (69), Jack Johnson (68).
[2020-11-11 8:28:46 PM] - Matt Read was added to Flyers.
[2020-11-11 8:28:46 PM] - Flyers claimed Matt Read from waivers by Penguins for $0.
[2020-11-11 8:28:37 PM] - Flyers show interest in Matt Read from waiver.
[2020-10-19 7:15:24 PM] - Torey Krug has been selected as assistant for Flyers.
[2020-10-19 7:15:24 PM] - Jeff Skinner is no longer as assistant for Flyers.
[2020-10-19 7:15:24 PM] - Tom Wilson has been selected as assistant for Flyers.
[2020-10-19 7:15:24 PM] - Torey Krug is no longer as assistant for Flyers.
[2020-10-08 7:01:21 PM] - Luke Schenn has been selected as assistant for Phantoms.
[2020-10-08 7:01:21 PM] - Unknown Player is no longer as assistant for Phantoms.
[2020-10-08 7:01:21 PM] - Dillon Heatherington has been selected as assistant for Phantoms.
[2020-10-08 7:01:21 PM] - Unknown Player is no longer as assistant for Phantoms.
[2020-10-08 7:01:21 PM] - Riley Nash has been selected as captain for Phantoms.
[2020-10-08 7:01:21 PM] - Unknown Player is no longer captain for Phantoms.
[2020-10-08 7:01:21 PM] - Torey Krug has been selected as assistant for Flyers.
[2020-10-08 7:01:21 PM] - Unknown Player is no longer as assistant for Flyers.
[2020-09-26 11:21:05 PM] - TRADE : From Flyers to Avalanche : Matt Nieto (66).
[2020-09-26 11:21:05 PM] - TRADE : From Avalanche to Flyers : Ondrej Kase (67).
[2020-07-12 2:48:03 PM] - Flyers drafts Arvid Costmar as the #124 overall pick in the Entry Draft of year 9.
[2020-05-30 7:52:43 PM] - Joel Farabee was added to Flyers.
[2020-05-29 10:11:47 PM] - Flyers are the Playoffs Champions for year 8!



[2021-01-03 11:31:51 PM] Last 30 Days Farm Star : 1 - Ben Street of Devils (20-16-36) / 2 - Matt Puempel of Senators (14-16-30) / 3 - Christoffer Ehn of Phantoms (15-8-23)
[2020-12-25 9:28:44 PM] Christoffer Ehn from Phantoms has scored a Hat Trick!
[2020-12-24 8:50:35 PM] Successfully loaded Flyers lines done with Web Base Client and SQLite Database.
[2020-12-19 7:38:12 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-12-19 7:36:31 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-12-19 7:35:15 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-12-18 10:43:48 PM] Auto Lines Partial Function has been run for Flyers.
[2020-12-17 9:54:56 PM] TRADE : From Golden Knights to Flyers : James van Riemsdyk (70), Dylan DeMelo (66).
[2020-12-17 9:54:56 PM] TRADE : From Flyers to Golden Knights : Tyler Johnson (69), Jack Johnson (68).
[2020-12-16 7:30:16 PM] Christoffer Ehn from Phantoms has scored a Hat Trick!
[2020-12-14 11:02:34 PM] Wild claimed Luke Schenn from waivers by Flyers for $0.
[2020-12-13 10:14:25 PM] Last 7 Days Farm Star : 1 - Ben Street of Devils (11-2-13) / 2 - Kyle Rau of Senators (9-1-10) / 3 - Christian Fischer of Phantoms (6-2-8)
[2020-12-13 10:14:25 PM] Last 7 Days Pro Star : 1 - Tom Wilson of Flyers (5-1-6) / 2 - Johnny Gaudreau of Canucks (4-4-8) / 3 - Viktor Arvidsson of Canadiens (4-1-5)
[2020-12-13 10:14:24 PM] Matt Read from Phantoms has scored a Hat Trick!
[2020-12-13 10:14:17 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-12-13 10:14:17 PM] Luke Schenn of Flyers was sent down to farm.
[2020-12-13 10:14:15 PM] Flyers placed Luke Schenn on waivers.
[2020-12-13 1:40:12 AM] Evan Rodrigues from Flyers is back from Right Leg Injury.
[2020-12-13 1:40:10 AM] Game 498 - Evan Rodrigues from Flyers is injured (Right Leg) and is out for 1 days.
[2020-12-13 1:40:00 AM] Successfully loaded Flyers lines done with Web Base Client and SQLite Database.
[2020-12-10 9:38:34 PM] Successfully loaded Flyers lines done with Web Base Client and SQLite Database.
[2020-12-09 7:34:12 PM] Jack Johnson from Flyers is back from Bruised Right Foot Injury.
[2020-12-08 9:25:05 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-12-02 10:09:59 PM] Auto Lines Partial Function has been run for Flyers.
[2020-12-02 10:09:59 PM] Auto Roster Partial Function has been run for Flyers.
[2020-12-02 10:09:59 PM] Luke Schenn of Flyers was sent to pro.



Pas de Blessure ou de Suspension.


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
282413102233257214434120170013013411222412114021031231022182257456713468481878279991994092038227562383415183687119.29%3244685.80%21663316452.56%1426271052.62%664126852.37%2085147218495961027525
3823525071682301953541171104036117103144118140313211392217023040463438836668222578851836848932105621103116233454613.33%3494686.82%31555301551.58%1336266150.21%601120349.96%2089147018865911030522
482403000732226207194126110030112899294114190043198108-1080226398624057778684235474676483425215062367217962473815.38%2565578.52%11411275851.16%1384266251.99%657123153.37%1998139719036051055521
58247230433228520580412412022101389147412311021221471143394285510795369290968267785586394039222160056416342735620.51%2294082.53%01593297453.56%1396263652.96%741134655.05%2054143218315971072547
682313406632231252-2141141605330125128-341171801302106124-18622314256562079746911263186588085554258668868319353065417.65%2735878.75%11568297352.74%1538290153.02%679126353.76%2037144719165811013510
7824619058222582065241276023211369442411913035011221121092258460718148484838264984389488841239268962418742815419.22%2605280.00%21540293052.56%1447273652.89%614119651.34%2070148418885681000509
8823727042662241943041221102222119902941151602044105104110222440562913755980162315792732735102225165881319403767018.62%3474985.88%21531284053.91%1428279351.13%614119451.42%2036141119136151046525
8823727042662241943041221102222119902941151602044105104110222440562913755980162315792732735102225165881319403767018.62%3474985.88%21531284053.91%1428279351.13%614119451.42%2036141119136151046525
947162207011126133-724514030115867-9231180400068662491262223481336424010134743043246428135939949610651713118.13%2033781.77%3815162450.18%831167049.76%34168150.07%11217781132348585290
Total Saison Régulière70333023803931333220611800261352177109020161713107487420035115312901915161998792661733206136855746163868563367110321665709370737219522195905559653015325274349017.86%258843283.31%16132072511852.58%122142356251.84%55251057652.24%175321230316235512088784479
Séries
22516900000806911117400000382711149500000424203280146226022332223849208289254988642682975201152219.13%1011684.16%050198051.12%508100050.80%19439149.62%678476645204346172
3171070000044413945000002428-4862000002013720448012401820151462122159165164281222423699088.89%66887.88%030761649.84%27255948.66%11523948.12%447312383124213110
440400000913-42020000057-22020000046-2091625004140101283339111628301018112.50%9188.89%06412750.39%5912248.36%386558.46%986993285427
524131100000635941367000003639-311740000027207266311217514241919182825124624487819236188462771519.48%781383.33%051995654.29%48394251.27%19737951.98%611426614190328160
7201640000077463111830000040261498100000372017327713921600302123370122120925615588157138447631117.46%561180.36%038472353.11%36370051.86%17533751.93%503360473142253129
82716110000077752138500000363061486000004145-43277137214102820236830248250272608222273326341152219.13%1312283.21%1521105049.62%566103354.79%22443251.85%691471687220373184
Total Séries11771460000035030347593326000001791572258382000000171146251423506309802711711310614377110781186123027736371038122725334687916.88%4417183.90%12296445251.57%2251435651.68%943184351.17%3030211628979111569785