Connexion

Philadelphia Flyers
GP: 41 | W: 20 | L: 16 | OTL: 5 | P: 63
GF: 119 | GA: 118 | PP%: 16.34% | PK%: 77.55%
DG: Brad | Morale : 40 | Moyenne d’équipe : 76
Prochains matchs #498 vs Edmonton Oilers

Centre de jeu
Boston Bruins
22-12-7, 70pts
2
FINAL
4 Philadelphia Flyers
20-16-5, 63pts
Team Stats
L2SéquenceW2
10-6-5Fiche domicile11-7-3
12-6-2Fiche visiteur9-9-2
4-4-2Derniers 10 matchs6-3-1
3.02Buts par match 2.90
2.68Buts contre par match 2.88
20.81%Pourcentage en avantage numérique16.34%
83.85%Pourcentage en désavantage numérique77.55%
Philadelphia Flyers
20-16-5, 63pts
4
FINAL
2 Boston Bruins
22-12-7, 70pts
Team Stats
W2SéquenceL2
11-7-3Fiche domicile10-6-5
9-9-2Fiche visiteur12-6-2
6-3-1Derniers 10 matchs4-4-2
2.90Buts par match 3.02
2.88Buts contre par match 2.68
16.34%Pourcentage en avantage numérique20.81%
77.55%Pourcentage en désavantage numérique83.85%
Philadelphia Flyers
20-16-5, 63pts
Jour 96
Edmonton Oilers
22-14-5, 67pts
Statistiques d’équipe
W2SéquenceL1
11-7-3Fiche domicile9-8-3
9-9-2Fiche visiteur13-6-2
6-3-110 derniers matchs4-5-1
2.90Buts par match 2.90
2.88Buts contre par match 2.90
16.34%Pourcentage en avantage numérique14.79%
77.55%Pourcentage en désavantage numérique82.04%
Seattle Kraken
22-14-5, 66pts
Jour 98
Philadelphia Flyers
20-16-5, 63pts
Statistiques d’équipe
W1SéquenceW2
9-6-5Fiche domicile11-7-3
13-8-0Fiche visiteur9-9-2
7-2-110 derniers matchs6-3-1
2.71Buts par match 2.90
2.46Buts contre par match 2.90
23.33%Pourcentage en avantage numérique16.34%
84.35%Pourcentage en désavantage numérique77.55%
Philadelphia Flyers
20-16-5, 63pts
Jour 100
Vegas Golden Knights
20-16-5, 61pts
Statistiques d’équipe
W2SéquenceW1
11-7-3Fiche domicile9-8-3
9-9-2Fiche visiteur11-8-2
6-3-110 derniers matchs5-4-1
2.90Buts par match 2.24
2.88Buts contre par match 2.24
16.34%Pourcentage en avantage numérique19.20%
77.55%Pourcentage en désavantage numérique83.11%
Meneurs d'équipe
Connor McDavidButs
Connor McDavid
22
Elias PetterssonPasses
Elias Pettersson
30
Connor McDavidPoints
Connor McDavid
45
Olli MaattaPlus/Moins
Olli Maatta
13
Philipp GrubauerVictoires
Philipp Grubauer
10
Vitek VanecekPourcentage d’arrêts
Vitek Vanecek
0.917

Statistiques d’équipe
Buts pour
119
2.90 GFG
Tirs pour
1312
32.00 Avg
Pourcentage en avantage numérique
16.3%
25 GF
Début de zone offensive
38.5%
Buts contre
118
2.88 GAA
Tirs contre
1256
30.63 Avg
Pourcentage en désavantage numérique
77.6%%
33 GA
Début de la zone défensive
37.7%
Informations de l'équipe

Directeur généralBrad
DivisionNortheast Division
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

NomWells Fargo Center
Capacité18,000
Assistance14,845
Billets de saison7,560


Informations de la formation

Équipe Pro22
Équipe Mineure25
Limite contact 47 / 250
Espoirs48


Finance

Revenu annuel à ce jour23,727,454$
Dépenses annuelles à ce jour37,981,087$
Revenus de la saison estimés20,337,818$
Dépenses de la saison estimées35,955,482$
Compte bancaire actuel109,757,321$
Compte bancaire projeté94,611,099$


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
Âge
Contrat
Salaire
1Connor McDavid0X100.007847879275979993999590778875820408402725,333,333$
2Elias Pettersson0X100.0062409299709497909090907186717504082N02546,650,000$
3Brock Boeser0X100.007247849372919185679090708675800408002728,280,333$
4Brendan Gallagher0X100.008443849250949683698193738280650407903222,950,000$
5Vladimir Tarasenko0X100.006253828180868780667883727680820407603215,500,500$
6J.T. Miller0X100.0081527677818884777879747376798504075N03114,850,000$
7Michael Rasmussen0X100.009353797799878673827874707271740407502541,850,000$
8Evgenii Dadonov0X100.008540808256868672637980647584770407303523,650,500$
9Phillip Danault0X100.007551777975889174967771707179780407303114,067,000$
10Brett Connolly0X100.009152777672877972657272697480630407103221,100,000$
11Jake Leschyshyn0X100.00784880757079876678686774687777040700251600,000$
12Nathan Bastian0X100.00925564759273716274636669687274040680262600,000$
13Olli Maatta0X100.006049978488979978538473807278830407902911,935,000$
14Haydn Fleury0X100.007550888385818183508770777075830407702731,950,000$
15Tyson Barrie0X100.006842969272959876508469757580770407703215,005,000$
16Jakub Zboril0X100.008244848278828275507766756676820407502731,935,000$
17Luke Schenn0X100.009060866995899367507063765982800407503411,350,000$
18Josh Mahura0X100.00854578857176847050736672687272040730261700,000$
Rayé
1Jake Bean0X97.546038859178797979507967767170760407402642,000,000$
Équipe Mineure
1Luke Glendening0X100.00844973765882777278746961718581040700351600,000$
2Lars Eller0X100.00784773677780797178717364708574040700351600,000$
3Taylor Raddysh0X100.00784283738078796365676571667280040690261700,000$
4Damien Brunner0X100.00544083775682827067697257739075040680381900,000$
5Sam Lafferty0X100.00905469727976756172656569637871040680291500,000$
6Jack McBain (R)0X100.00904975747775836172646371646770040680241700,000$
7Kevin Roy0X100.00563878855076796460686666717960040670311575,000$
8Yanni Gourde0X100.00604073864580796572676965728065040670322900,000$
9Liam O'Brien0X100.00976739608073826054656269607972040660291500,000$
10Michael Pezzetta0X100.00986656647770786065646367627573040660263950,000$
11Nikita Alexandrov0X100.00623577827169776069636271666862040660232900,000$
12Ryan Winterton (R)0X100.00564279768366746050565973636364040640203800,000$
13Colin Miller0X100.007548797983818774507666726779720407303122,500,000$
14Kevin Connauton0X100.007647756985828273507664686383830407203411,000,000$
15Nate Schmidt0X100.00584588767686876953756372638079040720321700,000$
16Isaak Phillips (R)0X100.00755583768674836650696168616581040700222500,000$
17Samuel Bolduc (R)0X100.00715382709372806450636568616881040690232600,000$
18Guillaume Brisebois0X100.00563786885067666450616065647265040650261700,000$
19Justin Bailey0X100.00754782609075766061656367617984040660291500,000$
20Tim Gettinger0X100.00745278639069745968586170617273040650263600,000$
21Riley Tufte0X100.005655716395677560716161726072710406502611,000,000$
22Cale Fleury0X100.00765084738672806653626370617181040700251500,000$
23Connor Mackey0X100.006648418076707068507064636373670406702721,667,000$
MOYENNE D’ÉQUIPE99.9475487878768083706472697069767504071
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
Âge
Contrat
Salaire
1Vitek Vanecek0100.00888083828382838383828277640407902813,267,000$
2Philipp Grubauer0100.00847275808382838383828181660407803212,500,000$
Rayé
1Ville Husso0100.00757578848181828282818078630407702944,000,000$
Équipe Mineure
1Erik Kallgren0100.0082707180747374757573747561040720273550,000$
2Oscar Dansk0100.0068565684716970727069705859040670301950,000$
MOYENNE D’ÉQUIPE100.007971738278777879797777746304075
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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’équipe
POS
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
1Connor McDavidPhiladelphia FlyersC41222345-838207280160408713.75%1586921.207916191340000473054.02%12053915001.0402202622
2Elias PetterssonPhiladelphia FlyersC4115304511953181140447910.71%1177418.89369111060003933249.43%6133815101.1602001144
3Brock BoeserPhiladelphia FlyersRW41172340-134106446142318411.97%2077318.867815241310001172030.77%52349001.0300011131
4Brendan GallagherPhiladelphia FlyersLW41131629-63558249114437011.40%1378519.16336121170000191047.83%463612000.7400001222
5Haydn FleuryPhiladelphia FlyersD41219218261046696324273.17%4090622.110223121011095010%01828000.4600002101
6J.T. MillerPhiladelphia FlyersRW418122010355805271234011.27%1471717.491344800002601044.00%50157100.5600010202
7Phillip DanaultPhiladelphia FlyersRW41128208320534890284513.33%656413.781124290001522054.11%14698010.7100000200
8Olli MaattaPhiladelphia FlyersD41117181311524846831321.47%76110627.0001121020002136000%02034000.3300001011
9Vladimir TarasenkoPhiladelphia FlyersLW419716113610554083174710.84%1771317.3913410981011501037.50%32117100.4500011111
10Evgenii DadonovPhiladelphia FlyersLW414913616070218938604.49%1050912.431013411014253031.25%16253000.5100000031
11Brett ConnollyPhiladelphia FlyersLW4137101471548366521334.62%43809.28011040003381050.00%8135100.5300120000
12Tyson BarriePhiladelphia FlyersD3719101121033484416132.27%2573819.960223114000026000%01624000.2700110001
13Jake LeschyshynPhiladelphia FlyersC4035841754042317189.68%53609.00000000001361043.60%17254000.4400010000
14Jakub ZborilPhiladelphia FlyersD35347-1195424025131312.00%3259717.0610144500004500100.00%1819100.2300000010
15Michael RasmussenPhiladelphia FlyersC415273140593447102310.64%648111.74000060110381047.47%257413000.2900000010
16Jake BeanPhiladelphia FlyersD39246-412024473714245.41%4163916.40101478000155000%0522000.1900000100
17Luke SchennPhiladelphia FlyersD350553805547278130%3265418.7100007011277000%0029000.1500000001
18Josh MahuraPhiladelphia FlyersD2703311180321615780%1436013.3700003000132000%0514000.1700000000
19Nathan BastianPhiladelphia FlyersRW292022140311394522.22%22237.7000000000001057.14%704000.1800000000
20Colin MillerLehigh Valley Phantoms (PHI)D7000-2608106010%210615.1500002300000000%00200000000000
21Sam LaffertyLehigh Valley Phantoms (PHI)RW2000-120510000%0157.670000000000000%00100000000000
Statistiques d’équipe totales ou en moyenne7431222033256944110595490413264197229.20%3851227816.5326396510312462352295220350.52%2605301275510.5304479171817
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’équipe
GP
W
L
OTL
PCT
GAA
MP
PIM
SO
GA
SA
SAR
A
EG
PS %
PSA
ST
BG
S1
S2
S3
1Philipp GrubauerPhiladelphia Flyers2010540.9162.5411806050598275200.20051919400
2Vitek VanecekPhiladelphia Flyers157710.9172.5390100384602171200158111
3Ville HussoPhiladelphia Flyers93510.8993.3453900302961470100915010
Statistiques d’équipe totales ou en moyenne44201760.9132.7026216011813546393354342521


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’équipe
POS
Âge
Date de naissance
Pays
Recrue
Poids
Taille
Non-échange
Disponible pour échange
Acquis Par
Date de la Dernière Transaction
Ballotage forcé
Waiver Possible
Contrat
Date du Signature du Contrat
Forcer UFA
Rappel d'urgence
Type
Salaire actuel
Salaire restant
Plafond salarial
Plafond salarial restant
Exclus du plafond salarial
Salaire année 2
Salaire année 3
Salaire année 4
Salaire année 5
Salaire année 6
Salaire année 7
Salaire année 8
Salaire année 9
Salaire année 10
Plafond salarial année 2
Plafond salarial année 3
Plafond salarial année 4
Plafond salarial année 5
Plafond salarial année 6
Plafond salarial année 7
Plafond salarial année 8
Plafond salarial année 9
Plafond salarial année 10
Non-échange année 2
Non-échange année 3
Non-échange année 4
Non-échange année 5
Non-échange année 6
Non-échange année 7
Non-échange année 8
Non-échange année 9
Non-échange année 10
Lien
Brendan Gallagher (contrat à 1 volet)Philadelphia FlyersLW321992-05-06CANNo183 Lbs5 ft9NoNoFree Agent2024-08-23NoNo22024-10-01FalseFalsePro & Farm2,950,000$1,401,657$0$0$No2,950,000$--------2,950,000$--------No--------Lien / Lien NHL
Brett ConnollyPhiladelphia FlyersLW321992-05-02CANNo198 Lbs6 ft3NoNoTrade2024-12-20NoNo22024-09-23FalseFalsePro & Farm1,100,000$522,652$0$0$No1,100,000$--------1,100,000$--------No--------Lien NHL
Brock Boeser (contrat à 1 volet)Philadelphia FlyersRW271997-02-25USANo207 Lbs6 ft1NoNoTrade2024-04-01NoNo2FalseFalsePro & Farm8,280,333$3,934,302$0$0$No8,280,333$--------8,280,333$--------No--------Lien / Lien NHL
Connor McDavid (contrat à 1 volet)Philadelphia FlyersC271997-01-13CANNo194 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm5,333,333$2,534,070$0$0$No5,333,333$--------5,333,333$--------No--------Lien / Lien NHL
Elias Pettersson (contrat à 1 volet)Philadelphia FlyersC251998-11-12SWENo185 Lbs6 ft2YesNoFree AgentNoNo42024-09-18FalseFalsePro Only6,650,000$3,159,669$0$0$No6,650,000$6,650,000$6,650,000$------6,650,000$6,650,000$6,650,000$------YesYesYes------Lien / Lien NHL
Evgenii Dadonov (contrat à 1 volet)Philadelphia FlyersLW351989-03-12RUSNo185 Lbs5 ft11NoNoFree Agent2024-03-06NoNo22024-09-23FalseFalsePro & Farm3,650,500$1,734,492$0$0$No3,650,500$--------3,650,500$--------No--------Lien / Lien NHL
Haydn FleuryPhiladelphia FlyersD271996-07-08CANNo207 Lbs6 ft3NoNoFree AgentNoNo32024-10-01FalseFalsePro & Farm1,950,000$926,519$0$0$No1,950,000$1,950,000$-------1,950,000$1,950,000$-------NoNo-------Lien / Lien NHL
J.T. Miller (contrat à 1 volet)Philadelphia FlyersRW311993-03-14USANo218 Lbs6 ft1YesNoFree Agent2024-02-14NoNo12024-09-23FalseFalsePro Only4,850,000$2,304,420$0$0$No---------------------------Lien / Lien NHL
Jake BeanPhiladelphia FlyersD261998-06-09CANNo176 Lbs6 ft1NoNoFree Agent2024-06-19NoNo42024-10-01FalseFalsePro & Farm2,000,000$950,276$0$0$No2,000,000$2,000,000$2,000,000$------2,000,000$2,000,000$2,000,000$------NoNoNo------Lien / Lien NHL
Jake LeschyshynPhiladelphia FlyersC251999-03-10USANo195 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm600,000$285,083$0$0$No---------------------------Lien NHL
Jakub ZborilPhiladelphia FlyersD271997-02-21CZENo201 Lbs6 ft1NoNoFree Agent2024-06-19NoNo32024-10-01FalseFalsePro & Farm1,935,000$919,392$0$0$No1,935,000$1,935,000$-------1,935,000$1,935,000$-------NoNo-------Lien NHL
Josh MahuraPhiladelphia FlyersD261998-05-05CANNo190 Lbs6 ft0NoNoTrade2025-02-08NoNo1FalseFalsePro & Farm700,000$332,597$0$0$No---------------------------Lien / Lien NHL
Luke SchennPhiladelphia FlyersD341989-11-02CANNo225 Lbs6 ft2NoNoFree Agent2024-06-19NoNo12024-10-15FalseFalsePro & Farm1,350,000$641,436$0$0$No---------------------------Lien / Lien NHL
Michael RasmussenPhiladelphia FlyersC251999-04-17CANNo212 Lbs6 ft6NoNoFree Agent2024-08-27NoNo42024-10-01FalseFalsePro & Farm1,850,000$879,006$0$0$No1,850,000$1,850,000$1,850,000$------1,850,000$1,850,000$1,850,000$------NoNoNo------Lien / Lien NHL
Nathan BastianPhiladelphia FlyersRW261997-12-06CANNo205 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm600,000$285,083$0$0$No600,000$--------600,000$--------No--------Lien / Lien NHL
Olli MaattaPhiladelphia FlyersD291994-08-22FINNo209 Lbs6 ft2NoNoFree AgentNoNo12024-10-01FalseFalsePro & Farm1,935,000$919,392$0$0$No---------------------------Lien / Lien NHL
Philipp GrubauerPhiladelphia FlyersG321991-11-25DEUNo187 Lbs6 ft1NoNoTrade2024-03-01NoNo1FalseFalsePro & Farm2,500,000$1,187,845$0$0$No---------------------------Lien / Lien NHL
Phillip Danault (contrat à 1 volet)Philadelphia FlyersRW311993-02-24CANNo201 Lbs6 ft1NoNoTrade2025-02-08NoNo12024-09-23FalseFalsePro & Farm4,067,000$1,932,387$0$0$No---------------------------Lien / Lien NHL
Tyson Barrie (contrat à 1 volet)Philadelphia FlyersD321991-07-26CANNo196 Lbs5 ft11NoNoFree AgentNoNo12024-09-23FalseFalsePro & Farm5,005,000$2,378,066$0$0$No---------------------------Lien / Lien NHL
Ville Husso (contrat à 1 volet)Philadelphia FlyersG291995-02-06FINNo209 Lbs6 ft3NoNoTrade2025-02-08NoNo42024-10-07FalseFalsePro & Farm4,000,000$1,900,552$0$0$No4,000,000$4,000,000$4,000,000$------4,000,000$4,000,000$4,000,000$------NoNoNo------Lien / Lien NHL
Vitek Vanecek (contrat à 1 volet)Philadelphia FlyersG281996-01-09CZENo183 Lbs6 ft2NoNoTrade2025-02-21NoNo12024-10-04FalseFalsePro & Farm3,267,000$1,552,276$0$0$No---------------------------Lien / Lien NHL
Vladimir Tarasenko (contrat à 1 volet)Philadelphia FlyersLW321991-12-13RUSNo225 Lbs6 ft0NoNoFree Agent2024-05-29NoNo12024-09-15FalseFalsePro & Farm5,500,500$2,613,497$0$0$No---------------------------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2229.00200 Lbs6 ft12.003,185,167$

Somme salaire 1e année Somme salaire 2e année Somme salaire 3e année Somme salaire 4e année Somme salaire 5e année
70,073,666$40,299,166$18,385,000$14,500,000$0$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Brendan GallagherConnor McDavidJ.T. Miller40014
2Vladimir TarasenkoElias PetterssonBrock Boeser30023
3Evgenii DadonovMichael RasmussenPhillip Danault20014
4Brett ConnollyJake LeschyshynNathan Bastian10041
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Olli MaattaLuke Schenn40041
2Haydn FleuryJosh Mahura30041
3Tyson BarrieJakub Zboril20041
4Haydn FleuryOlli Maatta10041
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Evgenii DadonovConnor McDavidBrock Boeser54005
2Brendan GallagherElias PetterssonJ.T. Miller46005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Haydn FleuryTyson Barrie51014
2Jakub ZborilOlli Maatta49005
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Elias PetterssonJ.T. Miller60050
2Jake LeschyshynVladimir Tarasenko40050
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Olli MaattaJosh Mahura60041
2Haydn FleuryLuke Schenn40050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Michael Rasmussen51140Olli MaattaJosh Mahura55050
2Elias Pettersson49140Haydn FleuryLuke Schenn45050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Connor McDavidPhillip Danault53014
2Elias PetterssonVladimir Tarasenko47014
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Olli MaattaTyson Barrie54014
2Haydn FleuryJakub Zboril46014
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Brendan GallagherConnor McDavidBrock BoeserHaydn FleuryTyson Barrie
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Vladimir TarasenkoElias PetterssonJ.T. MillerJosh MahuraOlli Maatta
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
J.T. Miller, Phillip Danault, Vladimir TarasenkoBrendan Gallagher, Phillip DanaultBrock Boeser
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Luke Schenn, Jakub Zboril, Haydn FleuryLuke SchennTyson Barrie, Jakub Zboril
Tirs de pénalité
Connor McDavid, Elias Pettersson, Brock Boeser, Brendan Gallagher, Vladimir Tarasenko
Gardien
#1 : Vitek Vanecek, #2 : Philipp Grubauer, #3 : 0
Lignes d’attaque personnalisées en prolongation
Connor McDavid, Elias Pettersson, Brock Boeser, Brendan Gallagher, Vladimir Tarasenko, Michael Rasmussen, J.T. Miller, Evgenii Dadonov, Phillip Danault, Brett Connolly
Lignes de défense personnalisées en prolongation
Olli Maatta, Tyson Barrie, Haydn Fleury, Josh Mahura, Luke Schenn


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
Total
Domicile
Visiteur
#
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
1Boston Bruins63200001201823120000089-1320000011293100.5562035550077601864874642189648711824625.00%21480.95%049795252.21%46793250.11%28758948.73%127741355510150
2California Golden Seals211000007431010000023-11100000051430.500711180032207224202805515375312216.67%6183.33%149795252.21%46793250.11%28758948.73%472837173517
3Carolina Hurricanes1010000023-1000000000001010000023-100.000246001010255101003096265120.00%30100.00%049795252.21%46793250.11%28758948.73%2111228169
4Chicago Blackhawks2010010057-21000010034-11010000023-110.16751015001130651623260541722495120.00%11281.82%049795252.21%46793250.11%28758948.73%472844193316
5Colorado Avalanche22000000642110000004311100000021161.00061117003030662124210772423433133.33%9277.78%049795252.21%46793250.11%28758948.73%422645173215
6Columbus Blue Jackets21100000532110000004131010000012-130.5005813002120561419230701523463133.33%9188.89%049795252.21%46793250.11%28758948.73%382149173215
7Detroit Red Wings11000000532110000005320000000000031.00058130002303461414032106263133.33%3233.33%049795252.21%46793250.11%28758948.73%2213227157
8Edmonton Oilers1010000014-31010000014-30000000000000.00011200001030138902913824200.00%4175.00%049795252.21%46793250.11%28758948.73%2212208179
9Florida Panthers22000000835110000004131100000042261.00081422001430712722220731714495120.00%70100.00%049795252.21%46793250.11%28758948.73%482937153417
10Hamilton Mustangs2110000056-1110000003211010000024-230.500591400032074142535071251237200.00%5180.00%049795252.21%46793250.11%28758948.73%432746163015
11Los Angeles Kings2010000157-21000000134-11010000023-110.167581300113059141727356182442400.00%12375.00%049795252.21%46793250.11%28758948.73%442444193618
12Minnesota North Stars11000000422000000000001100000042231.00047110020202914690341210193133.33%5180.00%049795252.21%46793250.11%28758948.73%2213228157
13Montreal Canadiens412001001318-521100000810-22010010058-340.333132134005440124453643013641398215320.00%17570.59%149795252.21%46793250.11%28758948.73%885286346533
14New York Islanders21001000642100010002111100000043150.83361117001221631317312571221407114.29%8187.50%049795252.21%46793250.11%28758948.73%452642193516
15New York Rangers1010000013-21010000013-20000000000000.0001120000102478902398267114.29%4175.00%049795252.21%46793250.11%28758948.73%2212199188
16Pittsburgh Penguins2110000056-1110000003211010000024-230.50057121003206114232406110154312216.67%5260.00%049795252.21%46793250.11%28758948.73%462639173418
17Quebec Nordiques412001001013-3210001007432020000039-640.33310142410253014245554209838371212328.70%6266.67%049795252.21%46793250.11%28758948.73%1046768336836
18Seattle Kraken10001000321000000000001000100032120.667369000111351461413496212150.00%3166.67%049795252.21%46793250.11%28758948.73%2113249188
19Toronto Maple Leafs2110000045-11010000024-21100000021130.5004711000130572019180541210491400.00%5180.00%049795252.21%46793250.11%28758948.73%482937173418
20Vegas Golden Knights11000000431110000004310000000000031.0004590011203991515023111722200.00%4250.00%049795252.21%46793250.11%28758948.73%2315199178
Total4118160230211911812110701201646132089011015557-2630.5121191983172030384921312383441484812563814259361532516.34%1473377.55%249795252.21%46793250.11%28758948.73%927554865362692350
_Since Last GM Reset4118160230211911812110701201646132089011015557-2630.5121191983172030384921312383441484812563814259361532516.34%1473377.55%249795252.21%46793250.11%28758948.73%927554865362692350
_Vs Conference241010012016973-4125501100353411255001013439-5350.4866911418320172625175322426426347212122375541121715.18%761678.95%149795252.21%46793250.11%28758948.73%552329490210408209
_Vs Division1878002015260-8944001002829-1934001012431-7240.44452841362014201805701722071912538165188413881314.77%541474.07%149795252.21%46793250.11%28758948.73%415249368157303157

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4163W21191983171312125638142593620
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4118162302119118
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2110712016461
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
208911015557
Derniers 10 matchs
WLOTWOTL SOWSOL
630001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1532516.34%1473377.55%2
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
38344148483038492
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
49795252.21%46793250.11%28758948.73%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
927554865362692350


Derniers matchs 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
Jour
Match
Équipe visiteuse
Score
Équipe locale
Score
ST
OT
SO
RI
Lien
11Philadelphia Flyers2Chicago Blackhawks3LSommaire du match
317Chicago Blackhawks4Philadelphia Flyers3LXSommaire du match
529California Golden Seals3Philadelphia Flyers2LSommaire du match
843Philadelphia Flyers3Seattle Kraken2WXSommaire du match
1051New York Rangers3Philadelphia Flyers1LSommaire du match
1263Philadelphia Flyers4New York Islanders3WSommaire du match
1578Philadelphia Flyers2Carolina Hurricanes3LSommaire du match
1789Florida Panthers1Philadelphia Flyers4WSommaire du match
20105Philadelphia Flyers2Boston Bruins3LXXSommaire du match
22116Quebec Nordiques1Philadelphia Flyers5WSommaire du match
24129Philadelphia Flyers2Toronto Maple Leafs1WSommaire du match
26140Montreal Canadiens6Philadelphia Flyers2LSommaire du match
28151Pittsburgh Penguins2Philadelphia Flyers3WSommaire du match
30168Boston Bruins5Philadelphia Flyers3LSommaire du match
32178Philadelphia Flyers2Pittsburgh Penguins4LSommaire du match
34191Philadelphia Flyers3Montreal Canadiens4LXSommaire du match
36201New York Islanders1Philadelphia Flyers2WXSommaire du match
38213Philadelphia Flyers4Florida Panthers2WSommaire du match
39222Philadelphia Flyers1Columbus Blue Jackets2LSommaire du match
42237Edmonton Oilers4Philadelphia Flyers1LSommaire du match
46249Philadelphia Flyers5California Golden Seals1WSommaire du match
49261Detroit Red Wings3Philadelphia Flyers5WSommaire du match
52274Philadelphia Flyers4Minnesota North Stars2WSommaire du match
55286Columbus Blue Jackets1Philadelphia Flyers4WSommaire du match
58300Toronto Maple Leafs4Philadelphia Flyers2LSommaire du match
59305Philadelphia Flyers1Quebec Nordiques5LSommaire du match
62323Montreal Canadiens4Philadelphia Flyers6WSommaire du match
65335Quebec Nordiques3Philadelphia Flyers2LXSommaire du match
67348Boston Bruins2Philadelphia Flyers1LSommaire du match
69357Philadelphia Flyers6Boston Bruins4WSommaire du match
70362Philadelphia Flyers2Quebec Nordiques4LSommaire du match
73383Philadelphia Flyers2Montreal Canadiens4LSommaire du match
75393Philadelphia Flyers2Colorado Avalanche1WSommaire du match
77405Vegas Golden Knights3Philadelphia Flyers4WSommaire du match
80418Philadelphia Flyers2Los Angeles Kings3LSommaire du match
82428Los Angeles Kings4Philadelphia Flyers3LXXSommaire du match
84440Colorado Avalanche3Philadelphia Flyers4WSommaire du match
85447Hamilton Mustangs2Philadelphia Flyers3WSommaire du match
88468Philadelphia Flyers2Hamilton Mustangs4LSommaire du match
91477Boston Bruins2Philadelphia Flyers4WSommaire du match
94489Philadelphia Flyers4Boston Bruins2WSommaire du match
96498Philadelphia Flyers-Edmonton Oilers-
98506Seattle Kraken-Philadelphia Flyers-
100521Philadelphia Flyers-Vegas Golden Knights-
103533Philadelphia Flyers-St Louis Blues-
105545St Louis Blues-Philadelphia Flyers-
107556Philadelphia Flyers-Detroit Red Wings-
112575Carolina Hurricanes-Philadelphia Flyers-
114588Philadelphia Flyers-Tampa Bay Lightning-
116593Philadelphia Flyers-New Jersey Devils-
118605Philadelphia Flyers-New York Rangers-
120614New Jersey Devils-Philadelphia Flyers-
123625Tampa Bay Lightning-Philadelphia Flyers-
126637Minnesota North Stars-Philadelphia Flyers-
128651Toronto Maple Leafs-Philadelphia Flyers-
130663Philadelphia Flyers-Toronto Maple Leafs-
132673Pittsburgh Penguins-Philadelphia Flyers-
134688Philadelphia Flyers-Pittsburgh Penguins-
137700Philadelphia Flyers-Florida Panthers-
139712New York Islanders-Philadelphia Flyers-
142723Philadelphia Flyers-New York Rangers-
144735Carolina Hurricanes-Philadelphia Flyers-
146748Philadelphia Flyers-New Jersey Devils-
148760Tampa Bay Lightning-Philadelphia Flyers-
152777Philadelphia Flyers-Tampa Bay Lightning-
154789New Jersey Devils-Philadelphia Flyers-
156802Philadelphia Flyers-Carolina Hurricanes-
158814New York Rangers-Philadelphia Flyers-
161825Philadelphia Flyers-New York Islanders-
163837Florida Panthers-Philadelphia Flyers-
165842Philadelphia Flyers-Quebec Nordiques-
166848Quebec Nordiques-Philadelphia Flyers-
169869Philadelphia Flyers-Montreal Canadiens-
170875Montreal Canadiens-Philadelphia Flyers-
173894Toronto Maple Leafs-Philadelphia Flyers-
174897Philadelphia Flyers-Toronto Maple Leafs-
179919Pittsburgh Penguins-Philadelphia Flyers-
180931Philadelphia Flyers-Pittsburgh Penguins-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité59404860198039601260
Prix des billets93523225188
Assistance108,42883,36133,26563,82922,858
Attendance PCT86.92%81.68%80.00%76.75%86.39%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
18 14845 - 82.47% 1,129,879$23,727,454$18000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineursValeur du plafond salarial spécial
37,981,087$ 75,673,666$ 0$ 0$ 0$
Plafond salarial par jourPlafond salarial à ce jourTaxe de luxe totaleJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 37,981,087$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
20,337,818$ 86 418,087$ 35,955,482$

Total de l’équipe estimé
Dépenses de la saison estimées Compte bancaire actuel Compte bancaire projeté
36,658,274$ 109,757,321$ 94,611,099$



Charte de profondeur

Ailier gaucheCentreAilier droit
Brendan GallagherAGE:32PO:0OV:79
Vladimir TarasenkoAGE:32PO:0OV:76
Evgenii DadonovAGE:35PO:0OV:73
Brett ConnollyAGE:32PO:0OV:71
Luke GlendeningAGE:35PO:0OV:70
Damien BrunnerAGE:38PO:0OV:68
Liam O'BrienAGE:29PO:0OV:66
Michael PezzettaAGE:26PO:0OV:66
Riley TufteAGE:26PO:0OV:65
Connor McDavidAGE:27PO:0OV:84
Elias PetterssonAGE:25PO:0OV:82
Michael RasmussenAGE:25PO:0OV:75
Lars EllerAGE:35PO:0OV:70
Jake LeschyshynAGE:25PO:0OV:70
Jack McBain (R)AGE:24PO:0OV:68
Nikita AlexandrovAGE:23PO:0OV:66
Ryan Winterton (R)AGE:20PO:0OV:64
Brock BoeserAGE:27PO:0OV:80
J.T. MillerAGE:31PO:0OV:75
Phillip DanaultAGE:31PO:0OV:73
Taylor RaddyshAGE:26PO:0OV:69
Nathan BastianAGE:26PO:0OV:68
Sam LaffertyAGE:29PO:0OV:68
Kevin RoyAGE:31PO:0OV:67
Yanni GourdeAGE:32PO:0OV:67
Justin BaileyAGE:29PO:0OV:66
Tim GettingerAGE:26PO:0OV:65

Défense #1Défense #2Gardien
Olli MaattaAGE:29PO:0OV:79
Haydn FleuryAGE:27PO:0OV:77
Tyson BarrieAGE:32PO:0OV:77
Jakub ZborilAGE:27PO:0OV:75
Luke SchennAGE:34PO:0OV:75
Jake BeanAGE:26PO:0OV:74
Colin MillerAGE:31PO:0OV:73
Josh MahuraAGE:26PO:0OV:73
Kevin ConnautonAGE:34PO:0OV:72
Nate SchmidtAGE:32PO:0OV:72
Cale FleuryAGE:25PO:0OV:70
Isaak Phillips (R)AGE:22PO:0OV:70
Samuel Bolduc (R)AGE:23PO:0OV:69
Connor MackeyAGE:27PO:0OV:67
Guillaume BriseboisAGE:26PO:0OV:65
Vitek VanecekAGE:28PO:0OV:79
Philipp GrubauerAGE:32PO:0OV:78
Ville HussoAGE:29PO:0OV:77
Erik KallgrenAGE:27PO:0OV:72
Oscar DanskAGE:30PO:0OV:67

Espoirs

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
Espoir
Nom de l’équipe
Année de repêchage
Choix total
Information
Date de la Dernière Transaction
Lien
0x LTCsPhiladelphia Flyers00
0x RFA Tag (Connor McDavid Y26)Philadelphia Flyers00
19x POS Changes NSHL24Philadelphia Flyers00
1x Match 10x Consecutive Road Game Income (NSHL24)Philadelphia Flyers00
7x TC PTSPhiladelphia Flyers00
Aleksei KolosovPhiladelphia Flyers2149Lien
Alexis BernierPhiladelphia Flyers24115Lien
Andrew GibsonPhiladelphia Flyers2365Lien
Brandon CoePhiladelphia Flyers2095
Calle OdeliusPhiladelphia Flyers2282Lien
Christian KyrouPhiladelphia Flyers2266Lien
Cole HutsonPhiladelphia Flyers2441Lien
Cole O'HaraPhiladelphia Flyers22149Lien
Cole SpicerPhiladelphia Flyers22128Lien
Conner RoulettePhiladelphia Flyers21137Lien
Elias Pettersson (D)Philadelphia Flyers22113Lien
Erik PortilloPhiladelphia Flyers1961
Filip JohanssonPhiladelphia Flyers1866
Graeme ClarkPhiladelphia Flyers2962
Hunter JonesPhiladelphia Flyers1996Lien
Ivan MorozovPhiladelphia Flyers1897
Ivan ZhigalovPhiladelphia Flyers2287Lien
Jesse KiiskinenPhiladelphia Flyers2370Lien
John FarinacciPhiladelphia Flyers1958Lien
Kim SaarinenPhiladelphia Flyers24139Lien
Kirill ZarubinPhiladelphia Flyers24128Lien
Lucas PetterssonPhiladelphia Flyers2437Lien
Maxim BarbashevPhiladelphia Flyers22153Lien
Nathaniel DayPhiladelphia Flyers23153Lien
Oliver KapanenPhiladelphia Flyers21122Lien
Patrick MoynihanPhiladelphia Flyers1984
Quentin MillerPhiladelphia Flyers23138Lien
Redmond SavagePhiladelphia Flyers21140Lien
Rieger LorenzPhiladelphia Flyers2255Lien
Ruslan KhazheyevPhiladelphia Flyers23143Lien
Ryan WintertonPhiladelphia Flyers2192Lien
Ryder DonovanPhiladelphia Flyers19110
Samuel HeleniusPhiladelphia Flyers2148Lien
Samuel HonzekPhiladelphia Flyers2324Lien
Samuel SavoiePhiladelphia Flyers22107Lien
Sean FarrellPhiladelphia Flyers20119
Terik ParascakPhiladelphia Flyers2422Lien
Tomas LavoiePhiladelphia Flyers24149Lien
Ty SmilanicPhiladelphia Flyers2074
Tyler BrennanPhiladelphia Flyers2279Lien
Vladislav FirstovPhiladelphia Flyers1944
William StromgrenPhiladelphia Flyers2143Lien
Zack OstapchukPhiladelphia Flyers2168Lien

Choix au repêchage

Année R1R2R3R4R5R6R7
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26
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29
Choix au repêchage conditionnel




La base de données des nouvelles du STHS n'a pas été trouvée ou corrompu. Veuillez en créer une de la section Gestion des nouvelles de la ligue du site web en étant connecté comme commissaire.




Philadelphia Flyers Historique de transactions

[2025-03-25 3:15:56 PM] TRADE : From Philadelphia Flyers to Vegas Golden Knights : $58,345 (Money).
[2025-03-15 10:22:49 AM] TRADE : From Philadelphia Flyers to Boston Bruins : $67,770 (Money).
[2025-03-13 3:41:12 PM] TRADE : From Philadelphia Flyers to Quebec Nordiques : $1,034,550 (Money).
[2025-03-07 5:02:12 PM] TRADE : From Philadelphia Flyers to Toronto Maple Leafs : $1,073,322 (Money).
[2025-03-05 11:44:56 AM] TRADE : From Philadelphia Flyers to Columbus Blue Jackets : $69,615 (Money).
[2025-02-27 2:52:03 PM] TRADE : From Philadelphia Flyers to Detroit Red Wings : $60,485 (Money).
[2025-02-21 6:10:27 PM] TRADE : From Toronto Maple Leafs to Philadelphia Flyers : Cale Fleury (70), Vitek Vanecek (79).
[2025-02-21 6:10:27 PM] TRADE : From Philadelphia Flyers to Toronto Maple Leafs : Thomas Harley (72).
[2025-02-19 3:42:09 PM] TRADE : From Philadelphia Flyers to Edmonton Oilers : $1,037,317 (Money).



Pas de blessure ou de suspension.


Philadelphia Flyers Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Philadelphia Flyers Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Philadelphia Flyers Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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

Philadelphia Flyers Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Philadelphia Flyers Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA