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Flyers

GP: 79 | W: 47 | L: 25 | OTL: 7 | P: 101
GF: 218 | GA: 183 | PP%: 18.46% | PK%: 86.19%
DG: Francois Gamache | Morale : 79 | Moyenne d'Équipe : 69
Prochain matchs #1239 vs Rangers
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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)XXX97.00563887846987958683907871827990084760
2Jeff Skinner (A)XX99.00563982816984957869738059827374084710
3Tyler JohnsonXXX100.00593885786581937779727674757773083710
4Nazem KadriX99.00774572767481867580747658727774070700
5Tom WilsonX98.50958046709083766957727383686967085700
6Cody EakinX100.00713786687379886677697082677571080690
7Tyler BertuzziXX99.00735077707281866856757163726768084680
8Riley NashXXX100.00734288657569916476696378647871084670
9Evan RodriguesXXX100.00564385686781876677736472657167069660
10Tobias RiederXX100.00763692687073806755646273657166074660
11Matt NietoXX100.00593690667075776553686483657368083660
12Martin FrkXX100.00763689687870606752666458667166065650
13Torey KrugX100.00694780786786827730887163567570072720
14Jacob TroubaX98.00804375728489957130826488566970077710
15Brady SkjeiX100.00844178698687916830736472556966083680
16Justin BraunX100.00824483658186896330735882538072066680
17Dan Girardi (A)X100.00853786628083756130726286538575058680
18Jack JohnsonX100.00864583648385956230685683518072082670
Rayé
1Micheal FerlandXX83.22887677728177847158727359747370070690
2Dan HamhuisX100.00684081627881736130725477488777022650
3Devon ToewsX100.00543793647682776330716259536966019640
4Luke SchennX100.00984977598578625830645373487870032640
MOYENNE D'ÉQUIPE98.8174458170768184685273667363757106968
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 Dubnyk100.0095959397949395949395948287083780
2Keith Kinkaid100.0090878582898890898890897884084740
Rayé
MOYENNE D'ÉQUIPE100.009391899092919392919392808608476
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John Tortorella81888688908455USA602100,000$


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/RW793347801480202473249020910.19%15164620.841219318132801131357652.49%212800000.97311000766
2Tyler JohnsonFlyersC/LW/RW76213859-16027179250672098.40%16137718.1251924682850000573051.20%100200200.8638000552
3Jeff SkinnerFlyersC/LW792332551400261001895815812.17%7154119.5171017453250110302248.33%12000010.71311000442
4Torey KrugFlyersD7884048-1557511613010032658.00%77184623.6761319702880111154200.00%000000.5200001213
5Jacob TroubaFlyersD729354461181018711513348876.77%100176924.5881119802920112221110.00%000000.5000000521
6Nazem KadriFlyersC781727449415153159191601318.90%7148219.01512174527202211221051.26%186500000.5939001216
7Tom WilsonFlyersRW792320431711553261261685913013.69%23147518.673471610210162689144.54%11900000.5802001545
8Brady SkjeiFlyersD62102838105801255491316510.99%47129820.9571118642360000139300.00%000000.5900000036
9Micheal FerlandFlyersLW/RW691424385855199411373811110.22%3108815.78591444234000002136.36%7700000.7005001543
10Jack JohnsonFlyersD792262896410152824518334.44%95144718.3214513861012250100.00%000000.3900011023
11Justin BraunFlyersD599172684751077561263914.75%87116519.75538361230001191110.00%000000.4500001240
12Dan GirardiFlyersD617192645601587357133712.28%84123320.22549261210000174000.00%000000.4200000241
13Tyler BertuzziFlyersLW/RW7912132502951086914930988.05%1132916.8324635295000001134.41%9300000.3812001014
14Cody EakinFlyersC7510122263409419311230988.93%16110014.670001101153174052.91%153100000.4011000023
15Evan RodriguesFlyersC/LW/RW6771017-100186611527626.09%984412.61325261090000330154.55%9900000.4011000001
16Tobias RiederFlyersLW/RW808816-932057569819738.16%586910.871124450002680137.50%6400000.3700000013
17Matt NietoFlyersLW/RW7141014-312017748530574.71%1281411.470000000041332042.86%6300000.3400000001
18Riley NashFlyersC/LW/RW796612-9120541087822587.69%97509.490000100021600150.44%67800000.3200000003
19Dan HamhuisFlyersD29371024038271971315.79%3249517.0900017000080100.00%000000.4000000012
20Martin FrkFlyersLW/RW62426-1212040233382212.12%44437.1500004000000146.88%3200000.2700000010
21Luke SchennFlyersD161342140481084412.50%1524815.560000200007000.00%000000.3200000001
22Christian FischerPhantoms (PHI)C/RW39123-7195331016486.25%33118.0000007000060046.00%5000000.1900100002
23Christoffer EhnPhantoms (PHI)C/LW10112-24011065216.67%0777.8000000000050053.01%8300000.5100000100
24Devon ToewsFlyersD17011-22014178380.00%1029617.46011651000014000.00%000000.0700000000
25Dillon HeatheringtonPhantoms (PHI)D2000220100000.00%02914.840000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne1497233428661478315521192044247372917779.42%6772498416.69751272026613225279292574401751.17%800400210.531550117404658
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 DubnykFlyers69412170.9192.2541884315719320000.750406910544
2Keith KinkaidFlyers116400.9171.9661200202420110.00001069100
Stats d'équipe Total ou en Moyenne80472570.9192.2148014317721740110.750407979644


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 SkjeiFlyersD241994-03-26No214 Lbs6 ft3NoNoNo6Pro & Farm5,250,000$5,250,000$196,524$No5,250,000$5,250,000$5,250,000$5,250,000$5,250,000$Lien / Lien NHL
Claude GirouxFlyersC/LW/RW301988-01-12No185 Lbs5 ft11NoNoNo4Pro & Farm8,275,000$8,275,000$309,759$No8,275,000$8,275,000$8,275,000$Lien / Lien NHL
Cody EakinFlyersC271991-05-24No190 Lbs6 ft0NoNoNo2Pro & Farm3,850,000$3,850,000$144,118$No3,850,000$Lien / Lien NHL
Dan GirardiFlyersD341984-04-29No212 Lbs6 ft1NoNoNo1Pro & Farm3,000,000$3,000,000$112,299$NoLien / Lien NHL
Dan HamhuisFlyersD351982-12-13No204 Lbs6 ft1NoNoNo2Pro & Farm1,250,000$1,250,000$46,791$No1,250,000$Lien / Lien NHL
Devan DubnykFlyersG321986-05-04No224 Lbs6 ft6NoNoNo3Pro & Farm4,333,000$4,333,000$162,198$No4,333,000$4,333,000$Lien / Lien NHL
Devon ToewsFlyersD241994-02-21No191 Lbs6 ft1NoNoNo2Pro & Farm700,000$700,000$26,203$No700,000$Lien / Lien NHL
Evan RodriguesFlyersC/LW/RW251993-07-28No176 Lbs5 ft10NoNoNo1Pro & Farm650,000$650,000$24,332$NoLien / Lien NHL
Jack JohnsonFlyersD311987-01-13No227 Lbs6 ft1NoNoNo5Pro & Farm3,250,000$3,250,000$121,658$No3,250,000$3,250,000$3,250,000$3,250,000$Lien / Lien NHL
Jacob TroubaFlyersD241994-02-26No202 Lbs6 ft3NoNoNo1Pro & Farm5,500,000$5,500,000$205,882$NoLien / Lien NHL
Jeff SkinnerFlyersC/LW261992-05-16No187 Lbs5 ft11NoNoNo1Pro & Farm5,725,000$5,725,000$214,305$NoLien / Lien NHL
Justin BraunFlyersD311987-02-10No205 Lbs6 ft2NoNoNo2Pro & Farm3,800,000$3,800,000$142,246$No3,800,000$Lien / Lien NHL
Keith KinkaidFlyersG291989-07-04No195 Lbs6 ft3NoNoNo1Pro & Farm1,250,000$1,250,000$46,791$NoLien / Lien NHL
Luke SchennFlyersD281989-11-02No221 Lbs6 ft2NoNoNo1Pro & Farm800,000$800,000$29,947$NoLien / Lien NHL
Martin FrkFlyersLW/RW251993-10-05No205 Lbs6 ft1NoNoNo1Pro & Farm1,050,000$1,050,000$39,305$NoLien / Lien NHL
Matt NietoFlyersLW/RW251992-11-05No190 Lbs5 ft11NoNoNo2Pro & Farm1,975,000$1,975,000$73,930$No1,975,000$Lien / Lien NHL
Micheal Ferland (Sur la Masse Salariale)FlyersLW/RW261992-04-20No217 Lbs6 ft1NoNoNo1Pro & Farm1,750,000$0$0$YesLien / Lien NHL
Nazem KadriFlyersC281990-10-06No192 Lbs6 ft0NoNoNo4Pro & Farm4,500,000$4,500,000$168,449$No4,500,000$4,500,000$4,500,000$Lien / Lien NHL
Riley NashFlyersC/LW/RW291989-05-09No190 Lbs6 ft1NoNoNo3Pro & Farm2,750,000$2,750,000$102,941$No2,750,000$2,750,000$Lien / Lien NHL
Tobias RiederFlyersLW/RW251993-01-10No186 Lbs5 ft11NoNoNo1Pro & Farm2,000,000$2,000,000$74,866$NoLien / Lien NHL
Tom WilsonFlyersRW241994-03-29No218 Lbs6 ft4NoNoNo6Pro & Farm5,166,666$5,166,666$193,405$No5,166,666$5,166,666$5,166,666$5,166,666$5,166,666$Lien / Lien NHL
Torey KrugFlyersD271991-04-12No186 Lbs5 ft9NoNoNo2Pro & Farm5,250,000$5,250,000$196,524$No5,250,000$Lien / Lien NHL
Tyler BertuzziFlyersLW/RW231995-02-24No190 Lbs6 ft0NoNoNo2Pro & Farm1,400,000$1,400,000$52,406$No1,400,000$Lien / Lien NHL
Tyler JohnsonFlyersC/LW/RW281990-07-29No183 Lbs5 ft8NoNoNo6Pro & Farm5,000,000$5,000,000$187,166$No5,000,000$5,000,000$5,000,000$5,000,000$5,000,000$Lien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2427.50200 Lbs6 ft12.503,269,778$

Somme Salaire 1e Année Somme Salaire 2e Année Somme Salaire 3e Année Somme Salaire 4e Année Somme Salaire 5e Année
78,474,666$56,749,666$38,524,666$31,441,666$18,666,666$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tyler JohnsonClaude GirouxTom Wilson30122
2Jeff SkinnerNazem KadriTyler Bertuzzi30122
3Evan RodriguesCody EakinMatt Nieto25122
4Tobias RiederRiley NashMartin Frk15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Torey KrugJacob Trouba30122
2Justin BraunBrady Skjei30122
3Jack JohnsonDan Girardi25122
4Torey KrugJacob Trouba15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jeff SkinnerClaude GirouxTyler Johnson60122
2Tyler BertuzziNazem KadriTom Wilson40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Torey KrugJacob Trouba60122
2Justin BraunBrady Skjei40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Cody EakinTom Wilson60122
2Riley NashMatt Nieto40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob TroubaDan Girardi60122
2Justin BraunJack Johnson40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Claude Giroux60122Jacob TroubaDan Girardi60122
2Cody Eakin40122Justin BraunJack Johnson40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Claude GirouxJeff Skinner60122
2Nazem KadriTyler Johnson40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Torey KrugJacob Trouba60122
2Justin BraunBrady Skjei40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jeff SkinnerClaude GirouxTyler JohnsonJacob TroubaTorey Krug
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt NietoClaude GirouxTom WilsonJacob TroubaJustin Braun
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Cody Eakin, Evan Rodrigues, Matt NietoEvan Rodrigues, Tobias RiederClaude Giroux
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dan Girardi, Jack Johnson, Jacob TroubaDan GirardiBrady Skjei, Torey Krug
Tirs de Pénalité
Claude Giroux, Jeff Skinner, Tyler Johnson, Nazem Kadri, Tyler Bertuzzi
Gardien
#1 : Devan Dubnyk, #2 : Keith Kinkaid
Lignes d'Attaque Perso. en Prol.
Claude Giroux, Jeff Skinner, Tyler Johnson, Nazem Kadri, Tom Wilson, Torey Krug, Torey Krug, Tyler Bertuzzi, Riley Nash, Evan Rodrigues, Matt Nieto
Lignes de Défense Perso. en Prol.
Jacob Trouba, Brady Skjei, Justin Braun, Jack Johnson, Dan Girardi


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
1Avalanche2020000026-41010000001-11010000025-300.00024600101049221512058123944700.00%14378.57%01493276354.04%1375269051.12%587115550.82%442850152411
2Blackhawks220000001046110000006241100000042241.0001019290071206322241704910104010330.00%50100.00%01493276354.04%1375269051.12%587115550.82%533740132614
3Blue Jackets411001101314-1200001107702110000067-150.6251323360045331083441291215042429616425.00%19289.47%11493276354.04%1375269051.12%587115550.82%986696335427
4Blues2110000035-2110000003211010000003-320.500358000210551821160391213366233.33%30100.00%01493276354.04%1375269051.12%587115550.82%513541152613
5Bruins320000101073210000106421100000043161.0001017270033319239272278022477119421.05%16287.50%01493276354.04%1375269051.12%587115550.82%795768223617
6Canadiens31100010963211000005321000001043140.6679152400431179272625411840349111327.27%17382.35%01493276354.04%1375269051.12%587115550.82%704878213617
7Canucks22000000945110000004221100000052341.000917260004506412262604118324615426.67%11281.82%01493276354.04%1375269051.12%587115550.82%523641142613
8Capitals431000001192211000007702200000042260.750112132014520110354530011730328615320.00%16287.50%01493276354.04%1375269051.12%587115550.82%906099294924
9Coyotes2020000025-31010000002-21010000023-100.00024600101049141817054202246800.00%11281.82%01493276354.04%1375269051.12%587115550.82%483344152613
10Devils4000300112102200020005322000100177070.8751224360022531294439381212636429418527.78%20385.00%01493276354.04%1375269051.12%587115550.82%1027399305024
11Ducks2010010047-31000010023-11010000024-210.250461000220048171615044111044700.00%5180.00%01493276354.04%1375269051.12%587115550.82%463247152612
12Flames22000000532110000002111100000032141.00059140021205015191604810144212216.67%7185.71%01493276354.04%1375269051.12%587115550.82%483345162513
13Golden Knights21100000660110000003211010000034-120.5006111700123054231516075192443500.00%12283.33%01493276354.04%1375269051.12%587115550.82%422853152412
14Hurricanes41300000511-62020000016-52110000045-120.25058130031109932283901282938928112.50%18288.89%01493276354.04%1375269051.12%587115550.82%8757100315125
15Islanders440000002081222000000103722000000105581.0002037570110370160654253081294010238718.42%19384.21%01493276354.04%1375269051.12%587115550.82%1128078284925
16Jets21000010734110000004131000001032141.000712190022225015161666021184211436.36%80100.00%01493276354.04%1375269051.12%587115550.82%503547152613
17Kings2110000057-2110000004221010000015-420.500581300302059201722047814509111.11%5180.00%01493276354.04%1375269051.12%587115550.82%513745132311
18Lightning320000101055110000005322100001052361.0001017270024327123232088530248310220.00%12283.33%01493276354.04%1375269051.12%587115550.82%795469213618
19Maple Leafs311000101064211000007431000001032140.6671016260032419833263578616246511218.18%11281.82%11493276354.04%1375269051.12%587115550.82%775368213819
20Oilers2020000024-21010000012-11010000012-100.0002350001104618820056111649800.00%8275.00%01493276354.04%1375269051.12%587115550.82%463148142512
21Panthers30200001712-51000000145-12020000037-410.167712190013308336252058629316112325.00%8362.50%01493276354.04%1375269051.12%587115550.82%765468223920
22Penguins4130000047-32110000045-12020000002-220.25047110010308931292908335289819210.53%14192.86%01493276354.04%1375269051.12%587115550.82%8556103345023
23Predators1010000004-4000000000001010000004-400.00000000000019667033102224200.00%7185.71%01493276354.04%1375269051.12%587115550.82%2012267126
24Rangers330000001459220000008441100000061561.0001427410056309635253607824317616425.00%12283.33%01493276354.04%1375269051.12%587115550.82%765466213718
25Red Wings31000002770110000003122000000246-240.6677132000223088232728168428147215213.33%6183.33%01493276354.04%1375269051.12%587115550.82%856166213820
26Sabres22000000624220000006240000000000041.00061117001140542119140591630539222.22%15193.33%01493276354.04%1375269051.12%587115550.82%453050142411
27Senateurs320000019631000000134-12200000062450.833916250023411042540368711923739333.33%70100.00%01493276354.04%1375269051.12%587115550.82%795663204121
28Sharks21001000642110000002111000100043141.000612180030217525152785315265911436.36%13284.62%01493276354.04%1375269051.12%587115550.82%523543152714
29Stars22000000817110000003121100000050541.0008162401404057201819053151442600.00%60100.00%01493276354.04%1375269051.12%587115550.82%533943132312
Total7937250426521818335402210022221178631391515020431019741010.6392183946121374587615226177371871893217563377018693636718.46%3334686.19%21493276354.04%1375269051.12%587115550.82%1969136618355921007506
31Wild2020000025-31010000023-11010000002-200.000246101010632322180331616492000.00%80100.00%01493276354.04%1375269051.12%587115550.82%564038152513
_Since Last GM Reset7937250426521818335402210022221178631391515020431019741010.6392183946121374587615226177371871893217563377018693636718.46%3334686.19%21493276354.04%1375269051.12%587115550.82%1969136618355921007506
_Vs Conference502412031551471153226136021228161202411601033665412700.7001472644110247434912146050346245479143242548012132264720.80%2102986.19%21493276354.04%1375269051.12%587115550.82%12488671179375635316
_Vs Division27138031117964151464021104235713740100137298360.66779147226022922246791276249254247632252536441302620.00%1181587.29%11493276354.04%1375269051.12%587115550.82%653450645208343168

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
79101W121839461222612175633770186913
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7937254265218183
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
402210222211786
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
391515204310197
Derniers 10 Matchs
WLOTWOTL SOWSOL
531001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3636718.46%3334686.19%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
7737187189374587615
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
1493276354.04%1375269051.12%587115550.82%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1969136618355921007506


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
3 - 2019-10-0413Blackhawks2Flyers6WSommaire du Match
8 - 2019-10-0945Devils2Flyers3WXSommaire du Match
11 - 2019-10-1273Flyers5Canucks2WSommaire du Match
14 - 2019-10-1588Flyers3Flames2WSommaire du Match
15 - 2019-10-1695Flyers1Oilers2LSommaire du Match
18 - 2019-10-19118Stars1Flyers3WSommaire du Match
20 - 2019-10-21130Golden Knights2Flyers3WSommaire du Match
23 - 2019-10-24151Flyers4Blackhawks2WSommaire du Match
25 - 2019-10-26165Blue Jackets4Flyers3LXSommaire du Match
26 - 2019-10-27174Flyers3Islanders1WSommaire du Match
28 - 2019-10-29182Flyers0Penguins1LSommaire du Match
31 - 2019-11-01196Flyers3Devils4LXXSommaire du Match
32 - 2019-11-02210Maple Leafs3Flyers2LSommaire du Match
35 - 2019-11-05226Hurricanes4Flyers1LSommaire du Match
37 - 2019-11-07240Canadiens2Flyers1LSommaire du Match
39 - 2019-11-09254Flyers3Maple Leafs2WXXSommaire du Match
40 - 2019-11-10268Flyers4Bruins3WSommaire du Match
43 - 2019-11-13283Capitals4Flyers2LSommaire du Match
45 - 2019-11-15298Flyers2Senateurs1WSommaire du Match
46 - 2019-11-16307Islanders3Flyers6WSommaire du Match
49 - 2019-11-19319Flyers2Panthers4LSommaire du Match
51 - 2019-11-21336Flyers3Hurricanes1WSommaire du Match
53 - 2019-11-23349Flames1Flyers2WSommaire du Match
55 - 2019-11-25367Canucks2Flyers4WSommaire du Match
57 - 2019-11-27384Flyers3Blue Jackets5LSommaire du Match
59 - 2019-11-29397Red Wings1Flyers3WSommaire du Match
60 - 2019-11-30404Flyers4Canadiens3WXXSommaire du Match
63 - 2019-12-03428Maple Leafs1Flyers5WSommaire du Match
65 - 2019-12-05442Coyotes2Flyers0LSommaire du Match
67 - 2019-12-07452Senateurs4Flyers3LXXSommaire du Match
71 - 2019-12-11486Flyers2Avalanche5LSommaire du Match
74 - 2019-12-14507Flyers0Wild2LSommaire du Match
75 - 2019-12-15515Flyers3Jets2WXXSommaire du Match
77 - 2019-12-17528Ducks3Flyers2LXSommaire du Match
79 - 2019-12-19540Sabres1Flyers3WR3Sommaire du Match
81 - 2019-12-21558Flyers4Senateurs1WSommaire du Match
83 - 2019-12-23574Rangers3Flyers5WSommaire du Match
88 - 2019-12-28601Flyers4Sharks3WXSommaire du Match
89 - 2019-12-29610Flyers2Ducks4LSommaire du Match
91 - 2019-12-31622Flyers1Kings5LSommaire du Match
93 - 2020-01-02638Flyers3Golden Knights4LSommaire du Match
95 - 2020-01-04650Flyers2Coyotes3LSommaire du Match
98 - 2020-01-07668Flyers1Hurricanes4LSommaire du Match
99 - 2020-01-08676Capitals3Flyers5WSommaire du Match
102 - 2020-01-11695Lightning3Flyers5WSommaire du Match
104 - 2020-01-13711Bruins3Flyers4WXXSommaire du Match
106 - 2020-01-15726Flyers0Blues3LSommaire du Match
107 - 2020-01-16731Canadiens1Flyers4WSommaire du Match
109 - 2020-01-18750Kings2Flyers4WSommaire du Match
112 - 2020-01-21763Penguins3Flyers1LSommaire du Match
122 - 2020-01-31786Flyers0Penguins1LSommaire du Match
123 - 2020-02-01799Avalanche1Flyers0LSommaire du Match
125 - 2020-02-03811Flyers2Red Wings3LXXSommaire du Match
128 - 2020-02-06832Devils1Flyers2WXSommaire du Match
130 - 2020-02-08850Flyers1Capitals0WSommaire du Match
132 - 2020-02-10861Panthers5Flyers4LXXSommaire du Match
133 - 2020-02-11869Flyers7Islanders4WSommaire du Match
135 - 2020-02-13883Flyers1Panthers3LSommaire du Match
137 - 2020-02-15897Flyers2Lightning1WXXSommaire du Match
140 - 2020-02-18920Blue Jackets3Flyers4WXXSommaire du Match
142 - 2020-02-20936Flyers3Blue Jackets2WSommaire du Match
144 - 2020-02-22949Jets1Flyers4WSommaire du Match
147 - 2020-02-25972Sharks1Flyers2WSommaire du Match
150 - 2020-02-28994Rangers1Flyers3WSommaire du Match
152 - 2020-03-011011Flyers6Rangers1WSommaire du Match
155 - 2020-03-041029Flyers3Capitals2WSommaire du Match
156 - 2020-03-051037Hurricanes2Flyers0LSommaire du Match
158 - 2020-03-071057Sabres1Flyers3WR3Sommaire du Match
161 - 2020-03-101073Bruins1Flyers2WSommaire du Match
163 - 2020-03-121085Flyers3Lightning1WSommaire du Match
165 - 2020-03-141098Wild3Flyers2LSommaire du Match
166 - 2020-03-151109Oilers2Flyers1LSommaire du Match
168 - 2020-03-171125Blues2Flyers3WSommaire du Match
171 - 2020-03-201149Flyers5Stars0WSommaire du Match
172 - 2020-03-211159Flyers0Predators4LSommaire du Match
175 - 2020-03-241179Islanders0Flyers4WSommaire du Match
177 - 2020-03-261196Flyers2Red Wings3LXXSommaire du Match
179 - 2020-03-281206Flyers4Devils3WXSommaire du Match
180 - 2020-03-291216Penguins2Flyers3WSommaire du Match
183 - 2020-04-011239Flyers-Rangers-
184 - 2020-04-021246Predators-Flyers-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
186 - 2020-04-041261Flyers-Sabres-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité de l'Aréna60005000200040001000
Prix des Billets100603525200
Assistance230,730191,21475,809152,97537,967
Attendance PCT96.14%95.61%94.76%95.61%94.92%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
1 17217 - 95.65% 619,866$24,794,633$18000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des CoachsValeur du Cap Salarial Spécial
69,446,306$ 76,724,666$ 76,724,666$ 0$ 0$
Cap Salarial Par JourCap salarial à ce jourTaxe de Luxe TotaleJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
76,724,666$ 69,350,112$ 0$ 23 1

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
619,866$ 7 410,827$ 2,875,789$

Total de l'Équipe Éstimé
Dépenses de la Saison ÉstiméesCap Salarial de la Saison ÉstiméCompte Bancaire ActuelCompte Bancaire Projeté
2,915,297$ 76,724,666$ 54,288,086$ 51,992,655$



Charte de Profondeur

Ailier GaucheCentreAilier Droit
Claude GirouxAGE:30PO:0OV:76
Jeff SkinnerAGE:26PO:0OV:71
Tyler JohnsonAGE:28PO:0OV:71
Micheal FerlandAGE:26PO:0OV:69
Tyler BertuzziAGE:23PO:0OV:68
Riley NashAGE:29PO:0OV:67
Evan RodriguesAGE:25PO:0OV:66
Tobias RiederAGE:25PO:0OV:66
Matt NietoAGE:25PO:0OV:66
Martin FrkAGE:25PO:0OV:65
Christoffer EhnAGE:22PO:0OV:63
Claude GirouxAGE:30PO:0OV:76
Jeff SkinnerAGE:26PO:0OV:71
Tyler JohnsonAGE:28PO:0OV:71
Nazem KadriAGE:28PO:0OV:70
Cody EakinAGE:27PO:0OV:69
Riley NashAGE:29PO:0OV:67
Evan RodriguesAGE:25PO:0OV:66
Christian FischerAGE:21PO:0OV:65
Christoffer EhnAGE:22PO:0OV:63
*Martin NecasAGE:19PO:0OV:61
*Mikhail VorobyevAGE:21PO:0OV:60
*J.C. BeaudinAGE:21PO:0OV:59
Claude GirouxAGE:30PO:0OV:76
Tyler JohnsonAGE:28PO:0OV:71
Tom WilsonAGE:24PO:0OV:70
Micheal FerlandAGE:26PO:0OV:69
Tyler BertuzziAGE:23PO:0OV:68
Riley NashAGE:29PO:0OV:67
Evan RodriguesAGE:25PO:0OV:66
Tobias RiederAGE:25PO:0OV:66
Matt NietoAGE:25PO:0OV:66
Christian FischerAGE:21PO:0OV:65
Martin FrkAGE:25PO:0OV:65
Keegan KolesarAGE:21PO:0OV:61
Bobby ButlerAGE:31PO:0OV:60

Défense #1Défense #2Gardien
Torey KrugAGE:27PO:0OV:72
Jacob TroubaAGE:24PO:0OV:71
Brady SkjeiAGE:24PO:0OV:68
Justin BraunAGE:31PO:0OV:68
Dan GirardiAGE:34PO:0OV:68
Jack JohnsonAGE:31PO:0OV:67
Dan HamhuisAGE:35PO:0OV:65
Devon ToewsAGE:24PO:0OV:64
Luke SchennAGE:28PO:0OV:64
Dillon HeatheringtonAGE:23PO:0OV:61
Michael PaliottaAGE:25PO:0OV:59
Devan DubnykAGE:32PO:0OV:78
Keith KinkaidAGE:29PO:0OV:74
Hunter MiskaAGE:23PO:0OV:65
Jon GilliesAGE:24PO: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
Clinston FranklinFlyers4122
Conner HurleyFlyers377
Dennis RasmussenFlyers
Greg RalloFlyers
Gustav PosslerFlyers368
Hayden HawkeyFlyers4153
Henri IkonenFlyers
Jakub KindlFlyers
Joel FarabeeFlyers813
Joel VerminFlyers
Michael HouserFlyers
Viktor LoovFlyers

Choix au Repêchage

Année R1R2R3R4R5R6
9PHI
10PHI DET
11PHI PHI WIN PHI PHI PHI PHI
12PHI PHI PHI PHI PHI PHI
13PHI PHI PHI PHI PHI PHI



[2020-03-15 10:00:42 PM] - TRADE : From Hurricanes to Flyers : Luke Schenn (64).
[2020-01-27 5:56:05 PM] - Jeff Skinner has been selected as assistant for Flyers.
[2020-01-27 5:56:05 PM] - Tyler Johnson is no longer as assistant for Flyers.
[2020-01-27 5:56:05 PM] - Dan Girardi has been selected as assistant for Flyers.
[2020-01-27 5:56:05 PM] - Unknown Player is no longer as assistant for Flyers.
[2020-01-20 8:05:08 PM] - TRADE : From Flyers to Senateurs : Mike Green (69), Shayne Gostisbehere (71), Filip Chytil (65), Y:9-RND:1-PHI, Y:9-RND:3-PHI.
[2020-01-20 8:05:08 PM] - TRADE : From Senateurs to Flyers : Nazem Kadri (70), Torey Krug (72), Dan Girardi (68), Evan Rodrigues (66).
[2019-12-22 11:12:04 PM] - TRADE : From Red Wings to Flyers : Tobias Rieder (66), Y:10-RND:4-DET.
[2019-12-22 11:12:04 PM] - TRADE : From Flyers to Red Wings : Kevan Miller (66), Y:10-RND:2-WSH.
[2019-09-16 7:06:46 PM] - Tyler Johnson has been selected as assistant for Flyers.
[2019-09-16 7:06:46 PM] - Unknown Player is no longer as assistant for Flyers.
[2019-09-16 7:06:46 PM] - Mike Green has been selected as assistant for Flyers.
[2019-09-16 7:06:46 PM] - Claude Giroux is no longer as assistant for Flyers.
[2019-09-16 7:06:46 PM] - Claude Giroux has been selected as captain for Flyers.
[2019-09-16 7:06:46 PM] - Unknown Player is no longer captain for Flyers.
[2019-09-13 10:17:27 AM] - Flyers hired John Tortorella for $100,000 for 2 year(s).
[2019-09-13 10:16:53 AM] - Flyers fired Scott Gordon.
[2019-07-28 3:49:31 PM] - TRADE : From Capitals to Flyers : Tyler Bertuzzi (68), Mikhail Vorobyev (60), Y:10-RND:2-WSH.
[2019-07-28 3:49:31 PM] - TRADE : From Flyers to Capitals : Eric Staal (73), Y:10-RND:4-PHI.
[2019-07-28 3:41:38 PM] - TRADE : From Canadiens to Flyers : Jacob Trouba (71).
[2019-07-28 3:41:38 PM] - TRADE : From Flyers to Canadiens : Vincent Trocheck (71), Matt Cullen (66), Y:10-RND:5-PHI.
[2019-06-19 8:43:12 AM] - TRADE : From Flyers to Panthers : Evgenii Dadonov (72).
[2019-06-19 8:43:12 AM] - TRADE : From Panthers to Flyers : Joel Farabee (P), Y:9-RND:1-PHI.
[2019-06-02 8:30:20 PM] - J.C. Beaudin was added to Flyers.



[2020-03-29 8:53:14 PM] Christoffer Ehn from Phantoms has scored a Hat Trick!
[2020-03-28 9:50:24 PM] Keegan Kolesar from Phantoms has scored a Hat Trick!
[2020-03-20 9:10:36 PM] Martin Necas from Phantoms has scored a Hat Trick!
[2020-03-20 9:10:36 PM] Keegan Kolesar from Phantoms has scored a Hat Trick!
[2020-03-15 10:00:42 PM] TRADE : From Hurricanes to Flyers : Luke Schenn (64).
[2020-03-15 9:58:24 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-03-15 9:58:24 PM] Flyers cannot claim Luke Schenn from waivers because Hurricanes has already claimed him and has priority.
[2020-03-14 7:44:15 PM] Game 1098 - Micheal Ferland from Flyers is injured (Broken Nose) and is out for 1 month.
[2020-03-14 7:44:10 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-03-07 7:32:03 PM] Cody Eakin from Flyers is back from Sprained Left Finger Injury.
[2020-03-06 8:09:17 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-03-05 9:53:25 PM] Auto Lines Partial Function has been run for Flyers.
[2020-03-05 9:53:25 PM] Auto Roster Partial Function has been run for Flyers.
[2020-03-04 11:05:18 PM] Game 1029 - Cody Eakin from Flyers is injured (Sprained Left Finger) and is out for 1 week.
[2020-02-26 7:36:48 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-02-25 9:52:55 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5



Micheal Ferland est dehors pour 1 semaine à cause de Broken Nose Injury.



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
87937250426521818335402210022221178631391515020431019741012183946121374587615226177371871893217563377018693636718.46%3334686.19%21493276354.04%1375269051.12%587115550.82%1969136618355921007506
Total Saison Régulière57127718702829262417051462243286150830151414108957131822851271040131512148107496158117053047475214325735315477617949585258956003383159044477517812249218338617.68%202434383.05%11108232057752.60%99021899652.13%4543866252.45%143051006913111413372063643
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
Total Séries9055350000027322845462521000001431271644301400000130101291102734937661789938382941830936958217281581189518993535716.15%3104984.19%01775340252.18%1685332350.71%719141150.96%2339164522096911196600