Florida Panthers

GP: 4 | W: 2 | L: 2 | OTL: 0 | P: 4
GF: 12 | GA: 15 | PP%: 25.00% | PK%: 88.89%
DG: Yannick Ferland | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #101 vs Washington Capitals
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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
1Andreas MartinsenXXX100.0093557875827864605056576055727315100
2Anton LanderXX100.0083558067585959555055555555786715100
3Eric TangradiX100.0056555555565757555055555555717215100
4Radim VrbataX100.0066558983898988766074687655898915100
5Ryan KeslerX99.0097558690998884859173759755879015100
6Jaromir Jagr (A)X100.0075557474858285655065656555999915100
7Josh BaileyXX99.0067558589878789915895798555827715100
8Mark StoneX99.0074558890888885917494868255828015100
9Michael GrabnerXX99.0070559594808491816367878955807815200
10Jannik HansenXX100.0078556584767085736475637155848015100
11Martin HanzalXX100.0098558381999988778466729455888815100
12Nick BoninoX100.0069558980858588809371739455888415100
13Ben LovejoyX100.0085558382838088722565638555877915100
14Mark Giordano (A)X99.0083558095879690962581739855959415100
15Niklas KronwallX100.0082558579968486902580649055828815100
16Zbynek MichalekX100.0055555560555555552555555555828415100
17Tyler WotherspoonX100.0059555960595975592559595955535315100
18Steven KampferX100.0079557272678159672561607155707015700
Rayé
1John KlingbergX86.7674559398839597992599689655828213700
MOYENNE D'ÉQUIPE99.007655797980808075517167785582801510
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
1Ben Bishop100.009289899993939291828155858315100
2Keith Kinkaid96.008780828491918486878855807815100
Rayé
MOYENNE D'ÉQUIPE98.00908586929292888985855583811510
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Claude Julien60757086907254CAN5854,700,000$


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOS GP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Mark GiordanoFlorida PanthersD4066060697450.00%610526.34022511000014000.00%000001.1400000010
2Josh BaileyFlorida PanthersLW/RW415612017121108.33%39924.930331110000201040.00%1000001.2000000010
3Mark StoneFlorida PanthersRW44151001101331130.77%010125.412024110000220064.00%5000110.9800000101
4Michael GrabnerFlorida PanthersLW/RW4325055451951415.79%07518.9010131000007000.00%700001.3200001001
5Niklas KronwallFlorida PanthersD4033020236460.00%69022.58011111000012000.00%000000.6600000000
6Radim VrbataFlorida PanthersRW4022-120448470.00%06917.46011312000000016.67%600000.5700000000
7Ryan KeslerFlorida PanthersC411218081720275.00%28421.02112511000061055.65%12400000.4800000000
8Nick BoninoFlorida PanthersC4202-100291431014.29%26917.28000311000000052.43%10300000.5800000000
9Jannik HansenFlorida PanthersLW/RW4011-500265180.00%04110.4600000000010075.00%400000.4800000000
10Martin HanzalFlorida PanthersC/RW4101-5205661916.67%24010.0100000000000049.02%5100000.5000000000
11Andreas MartinsenFlorida PanthersC/LW/RW4000-120114040.00%0215.4100001000000042.31%2600000.0000000000
12Anton LanderFlorida PanthersC/LW4000-120121050.00%1194.790000000000000.00%100000.0000000000
13Ben LovejoyFlorida PanthersD4000040425010.00%78421.17000411000011000.00%000000.0000000000
14Eric TangradiFlorida PanthersLW4000020001000.00%0225.610000100000000.00%200000.0000000000
15Jaromir JagrFlorida PanthersRW4000-500002120.00%04010.0200000000000050.00%200000.0000000000
16John KlingbergFlorida PanthersD2000-400142000.00%64723.920001300008000.00%000000.0000000000
17Zbynek MichalekFlorida PanthersD4000-520600000.00%05513.850000000008000.00%000000.0000000000
18Tyler WotherspoonFlorida PanthersD4000-5401011030.00%65313.450000200005000.00%000000.0000000000
19Steven KampferFlorida PanthersD2000400121000.00%14120.890000600000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne72122133-264355988127291029.45%42116416.1748123011900001202051.81%38600110.5700001122
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
1Ben BishopFlorida Panthers31200.8594.331800013920000.000031000
2Keith KinkaidFlorida Panthers11000.9562.0060002450000.000013100
Stats d'équipe Total ou en Moyenne42200.8913.7524000151370000.000044100


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial 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 Link
Andreas MartinsenFlorida PanthersC/LW/RW261990-06-13No220 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$300,000$277,966$No300,000$
Anton LanderFlorida PanthersC/LW251991-04-23No186 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm300,000$300,000$277,966$No300,000$
Ben BishopFlorida PanthersG301986-11-20No209 Lbs6 ft7NoNoNo4Sans RestrictionPro & Farm5,000,000$5,000,000$4,632,768$No5,000,000$5,000,000$5,000,000$
Ben LovejoyFlorida PanthersD321984-02-19No206 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm2,500,000$2,500,000$2,316,384$No
Eric TangradiFlorida PanthersLW271989-02-10No221 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm300,000$300,000$277,966$No
Jannik HansenFlorida PanthersLW/RW301986-03-15No195 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm1,000,000$1,000,000$926,554$No1,000,000$1,000,000$
Jaromir JagrFlorida PanthersRW441972-02-15No230 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm300,000$300,000$277,966$No
John Klingberg (Sur la Masse Salariale)Florida PanthersD241992-08-14No180 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm5,000,000$0$0$Yes5,000,000$
Josh BaileyFlorida PanthersLW/RW271989-02-10No194 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm3,500,000$3,500,000$3,242,938$No3,500,000$3,500,000$
Keith KinkaidFlorida PanthersG271989-07-04No195 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm3,000,000$3,000,000$2,779,661$No3,000,000$3,000,000$
Mark GiordanoFlorida PanthersD331983-10-02No200 Lbs6 ft0NoNoNo2Sans RestrictionPro & Farm5,000,000$5,000,000$4,632,768$No5,000,000$
Mark StoneFlorida PanthersRW241992-05-12No205 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm3,500,000$3,500,000$3,242,938$No3,500,000$
Martin HanzalFlorida PanthersC/RW291987-02-19No226 Lbs6 ft6NoNoNo3Sans RestrictionPro & Farm2,500,000$2,500,000$2,316,384$No2,500,000$2,500,000$
Michael GrabnerFlorida PanthersLW/RW291987-10-04No202 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm3,500,000$3,500,000$3,242,938$No3,500,000$
Nick BoninoFlorida PanthersC281988-04-19No196 Lbs6 ft1NoNoNo4Sans RestrictionPro & Farm2,500,000$2,500,000$2,316,384$No2,500,000$2,500,000$2,500,000$
Niklas KronwallFlorida PanthersD361981-01-11No194 Lbs6 ft0NoNoNo2Sans RestrictionPro & Farm2,496,000$2,496,000$2,312,678$No2,496,000$
Radim VrbataFlorida PanthersRW351981-06-12No194 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm1,000,000$1,000,000$926,554$No1,000,000$
Ryan KeslerFlorida PanthersC321984-08-30No208 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm5,000,000$5,000,000$4,632,768$No
Steven KampferFlorida PanthersD281988-09-23No192 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm500,000$500,000$463,277$No
Tyler WotherspoonFlorida PanthersD231993-03-11No210 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$300,000$277,966$No
Zbynek MichalekFlorida PanthersD341982-12-22No210 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm750,000$750,000$694,915$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2129.67203 Lbs6 ft22.052,297,429$

Somme Salaire 1e Année Somme Salaire 2e Année Somme Salaire 3e Année Somme Salaire 4e Année Somme Salaire 5e Année
48,246,000$38,596,000$17,500,000$7,500,000$0$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Josh BaileyRyan KeslerMark Stone40122
2Michael GrabnerNick BoninoRadim Vrbata30122
3Jannik HansenMartin HanzalJaromir Jagr20122
4Anton LanderAndreas MartinsenEric Tangradi10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark GiordanoSteven Kampfer40122
2Niklas KronwallBen Lovejoy30122
3Tyler WotherspoonZbynek Michalek20122
4Mark GiordanoNiklas Kronwall10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Josh BaileyRyan KeslerMark Stone60122
2Michael GrabnerNick BoninoRadim Vrbata40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark GiordanoSteven Kampfer60122
2Niklas KronwallBen Lovejoy40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Mark StoneJosh Bailey60122
2Ryan KeslerMichael Grabner40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark GiordanoTyler Wotherspoon60122
2Niklas KronwallBen Lovejoy40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Mark Stone60122Mark GiordanoSteven Kampfer60122
2Josh Bailey40122Niklas KronwallBen Lovejoy40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Mark StoneJosh Bailey60122
2Ryan KeslerMichael Grabner40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark GiordanoZbynek Michalek60122
2Niklas KronwallBen Lovejoy40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Josh BaileyRyan KeslerMark StoneMark GiordanoSteven Kampfer
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Josh BaileyRyan KeslerMark StoneMark GiordanoSteven Kampfer
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Eric Tangradi, Nick Bonino, Jannik HansenEric Tangradi, Nick BoninoJannik Hansen
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Tyler Wotherspoon, Zbynek Michalek, Niklas KronwallTyler WotherspoonZbynek Michalek, Niklas Kronwall
Tirs de Pénalité
Mark Stone, Josh Bailey, Ryan Kesler, Michael Grabner, Martin Hanzal
Gardien
#1 : Keith Kinkaid, #2 : Ben Bishop


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
1Columbus Blue Jackets1010000035-21010000035-20000000000000.0003580011103219580341412213133.33%6183.33%08615854.43%8116549.09%336352.38%2518235115
2Philadelphia Flyers11000000422000000000001100000042221.0004711002020402313404514810300.00%40100.00%08615854.43%8116549.09%336352.38%2114267115
3Tampa Bay Lightning1010000004-4000000000001010000004-400.000000000000261151002671717500.00%50100.00%08615854.43%8116549.09%336352.38%2214247126
Total422000001215-32110000089-12110000046-240.500122133005340127623035013742435916425.00%18288.89%08615854.43%8116549.09%336352.38%946495284924
5Vancouver Canucks11000000541110000005410000000000021.000591400221029971303276115360.00%3166.67%08615854.43%8116549.09%336352.38%2416217136
_Since Last GM Reset422000001215-32110000089-12110000046-240.500122133005340127623035013742435916425.00%18288.89%08615854.43%8116549.09%336352.38%946495284924
_Vs Conference31200000711-41010000035-22110000046-220.333712190031309853232201053537481119.09%15193.33%08615854.43%8116549.09%336352.38%694873203617
_Vs Division1010000004-4000000000001010000004-400.000000000000261151002671717500.00%50100.00%08615854.43%8116549.09%336352.38%2214247126

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
44W212213312713742435900
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
42200001215
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
211000089
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
211000046
Derniers 10 Matchs
WLOTWOTL SOWSOL
220000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
16425.00%18288.89%0
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
62303505340
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
8615854.43%8116549.09%336352.38%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
946495284924


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
4 - 2018-09-0827Florida Panthers0Tampa Bay Lightning4LSommaire du Match
9 - 2018-09-1348Columbus Blue Jackets5Florida Panthers3LSommaire du Match
10 - 2018-09-1462Vancouver Canucks4Florida Panthers5WSommaire du Match
13 - 2018-09-1781Florida Panthers4Philadelphia Flyers2WSommaire du Match
16 - 2018-09-20101Florida Panthers-Washington Capitals-
17 - 2018-09-21105Detroit Red Wings-Florida Panthers-
20 - 2018-09-24128Florida Panthers-New York Rangers-
21 - 2018-09-25131Florida Panthers-New York Islanders-
24 - 2018-09-28153Florida Panthers-New Jersey Devils-
29 - 2018-10-03183Winnipeg Jets-Florida Panthers-
30 - 2018-10-04194Florida Panthers-Winnipeg Jets-
36 - 2018-10-10230Edmonton Oilers-Florida Panthers-
38 - 2018-10-12247New York Islanders-Florida Panthers-
39 - 2018-10-13255Ottawa Senators-Florida Panthers-
41 - 2018-10-15271Florida Panthers-Philadelphia Flyers-
43 - 2018-10-17278Florida Panthers-Columbus Blue Jackets-
45 - 2018-10-19298Florida Panthers-New York Rangers-
47 - 2018-10-21312Florida Panthers-Ottawa Senators-
49 - 2018-10-23330Florida Panthers-Tampa Bay Lightning-
50 - 2018-10-24336Florida Panthers-Carolina Hurricanes-
51 - 2018-10-25349Chicago Blackhawks-Florida Panthers-
53 - 2018-10-27363New Jersey Devils-Florida Panthers-
55 - 2018-10-29380Anaheim Ducks-Florida Panthers-
57 - 2018-10-31393Buffalo Sabres-Florida Panthers-
58 - 2018-11-01398Tampa Bay Lightning-Florida Panthers-
61 - 2018-11-04419Boston Bruins-Florida Panthers-
63 - 2018-11-06431Colorado Avalanche-Florida Panthers-
65 - 2018-11-08450New York Rangers-Florida Panthers-
68 - 2018-11-11472Florida Panthers-St. Louis Blues-
70 - 2018-11-13481Florida Panthers-Minnesota Wild-
72 - 2018-11-15497Toronto Maple Leafs-Florida Panthers-
75 - 2018-11-18518Florida Panthers-Buffalo Sabres-
77 - 2018-11-20539Florida Panthers-Toronto Maple Leafs-
79 - 2018-11-22550Florida Panthers-Detroit Red Wings-
80 - 2018-11-23560Florida Panthers-Chicago Blackhawks-
82 - 2018-11-25581Montreal Canadiens-Florida Panthers-
83 - 2018-11-26589Philadelphia Flyers-Florida Panthers-
85 - 2018-11-28606Florida Panthers-Detroit Red Wings-
88 - 2018-12-01622Florida Panthers-Buffalo Sabres-
90 - 2018-12-03637Columbus Blue Jackets-Florida Panthers-
93 - 2018-12-06661Florida Panthers-Pittsburgh Penguins-
95 - 2018-12-08673Florida Panthers-Edmonton Oilers-
96 - 2018-12-09685Florida Panthers-Calgary Flames-
98 - 2018-12-11703Florida Panthers-Vancouver Canucks-
100 - 2018-12-13715Florida Panthers-Montreal Canadiens-
103 - 2018-12-16737Toronto Maple Leafs-Florida Panthers-
104 - 2018-12-17747Florida Panthers-Nashville Predators-
106 - 2018-12-19757San Jose Sharks-Florida Panthers-
113 - 2018-12-26785Nashville Predators-Florida Panthers-
114 - 2018-12-27791Vegas Golden Knights-Florida Panthers-
117 - 2018-12-30813St. Louis Blues-Florida Panthers-
119 - 2019-01-01828Pittsburgh Penguins-Florida Panthers-
121 - 2019-01-03851Florida Panthers-Washington Capitals-
122 - 2019-01-04855Tampa Bay Lightning-Florida Panthers-
124 - 2019-01-06867Dallas Stars-Florida Panthers-
126 - 2019-01-08881Calgary Flames-Florida Panthers-
129 - 2019-01-11906Montreal Canadiens-Florida Panthers-
131 - 2019-01-13919Buffalo Sabres-Florida Panthers-
133 - 2019-01-15931Carolina Hurricanes-Florida Panthers-
135 - 2019-01-17949Los Angeles Kings-Florida Panthers-
137 - 2019-01-19962Florida Panthers-Colorado Avalanche-
138 - 2019-01-20968Florida Panthers-Phoenix Coyotes-
140 - 2019-01-22990Florida Panthers-Vegas Golden Knights-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
142 - 2019-01-241003Carolina Hurricanes-Florida Panthers-
143 - 2019-01-251011Ottawa Senators-Florida Panthers-
145 - 2019-01-271027Florida Panthers-Pittsburgh Penguins-
147 - 2019-01-291034Florida Panthers-Boston Bruins-
148 - 2019-01-301046Minnesota Wild-Florida Panthers-
150 - 2019-02-011062Detroit Red Wings-Florida Panthers-
154 - 2019-02-051091Florida Panthers-San Jose Sharks-
156 - 2019-02-071103Florida Panthers-Los Angeles Kings-
157 - 2019-02-081111Florida Panthers-Anaheim Ducks-
159 - 2019-02-101124Florida Panthers-Dallas Stars-
161 - 2019-02-121141Phoenix Coyotes-Florida Panthers-
163 - 2019-02-141154Boston Bruins-Florida Panthers-
165 - 2019-02-161176Florida Panthers-Toronto Maple Leafs-
166 - 2019-02-171181Florida Panthers-Montreal Canadiens-
168 - 2019-02-191193Florida Panthers-Ottawa Senators-
170 - 2019-02-211203Florida Panthers-Boston Bruins-
172 - 2019-02-231222Washington Capitals-Florida Panthers-
175 - 2019-02-261246New York Islanders-Florida Panthers-
177 - 2019-02-281262New Jersey Devils-Florida Panthers-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité de l'Aréna60005000200040001000
Prix des Billets100603520200
Assistance11,1039,6633,7627,2551,933
Attendance PCT92.53%96.63%94.05%90.69%96.65%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
39 16858 - 93.66% 1,059,053$2,118,106$18000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des CoachsValeur du Cap Salarial Spécial
3,722,020$ 43,246,000$ 34,183,000$ 0$ 0$
Cap Salarial Par JourCap salarial à ce jourTaxe de Luxe TotaleJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
43,246,000$ 3,376,823$ 0$ 20 1

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
41,303,067$ 164 270,881$ 44,424,484$

Total de l'Équipe Éstimé
Dépenses de la Saison ÉstiméesCap Salarial de la Saison ÉstiméCompte Bancaire ActuelCompte Bancaire Projeté
45,406,047$ 43,246,000$ 65,226,907$ 61,123,927$



Charte de Profondeur

Ailier GaucheCentreAilier Droit
Andreas MartinsenAGE:26PO:1OV:0
Anton LanderAGE:25PO:1OV:0
Eric TangradiAGE:27PO:1OV:0
Jamie DevaneAGE:25PO:1OV:0
Josh BaileyAGE:27PO:1OV:0
Michael GrabnerAGE:29PO:1OV:0
Jannik HansenAGE:30PO:1OV:0
Andreas MartinsenAGE:26PO:1OV:0
Anton LanderAGE:25PO:1OV:0
Ben HolmstromAGE:29PO:1OV:0
Brendan WoodsAGE:24PO:1OV:0
*Trevor SmithAGE:31PO:1OV:0
*Mason AppletonAGE:20PO:1OV:0
Ryan KeslerAGE:32PO:1OV:0
John MitchellAGE:31PO:1OV:0
Martin HanzalAGE:29PO:1OV:0
Mark ZengerleAGE:27PO:1OV:0
Reid PetrykAGE:23PO:1OV:0
Nick BoninoAGE:28PO:1OV:0
Andreas MartinsenAGE:26PO:1OV:0
Anthony PelusoAGE:27PO:1OV:0
Radim VrbataAGE:35PO:1OV:0
Jaromir JagrAGE:44PO:1OV:0
*Jens LookeAGE:19PO:1OV:0
Josh BaileyAGE:27PO:1OV:0
Adam ChapieAGE:25PO:1OV:0
Mark StoneAGE:24PO:1OV:0
Michael GrabnerAGE:29PO:1OV:0
Jannik HansenAGE:30PO:1OV:0
Martin HanzalAGE:29PO:1OV:0

Défense #1Défense #2Gardien
Andrew BodnarchukAGE:28PO:1OV:0
Ben LovejoyAGE:32PO:1OV:0
Chris CastoAGE:25PO:1OV:0
Mark GiordanoAGE:33PO:1OV:0
Niklas KronwallAGE:36PO:1OV:0
John KlingbergAGE:24PO:1OV:0
Zbynek MichalekAGE:34PO:1OV:0
*Zach TrotmanAGE:26PO:1OV:0
Tyler WotherspoonAGE:23PO:1OV:0
Steven KampferAGE:28PO:1OV:0
Ben BishopAGE:30PO:1OV:0
Keith KinkaidAGE:27PO:1OV:0
*Adam CarlsonAGE:22PO:1OV:0
Zane McIntyreAGE:24PO:1OV:0

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
Alex GudbransonFlorida Panthers
Markus RuusuFlorida Panthers11153
Pavel ShenFlorida Panthers13181
Taylor RaddyshFlorida Panthers1225
Veeti VainioFlorida Panthers11137

Choix au Repêchage

Année R1R2R3R4R5R6
14Flo Flo
15Flo Bos Flo Tor Flo
16Tor Flo Flo
17Flo Flo Flo Flo Flo Flo
18Flo Flo Flo Flo Flo Flo



[2018-10-08 12:11:15] - TRADE : From Pittsburgh Penguins to Florida Panthers : Steven Kampfer.
[2018-10-08 12:11:15] - TRADE : From Florida Panthers to Pittsburgh Penguins : Y:15-RND:5-Bos.
[2018-09-29 10:52:13] - Team Name Change : San Antonio Rampage changed name to Thunderbirds
[2018-09-29 10:46:59] - Team Name Change : Floride Panthers changed name to Florida Panthers
[2018-09-13 10:12:04] - Adam Chapie was added to Floride Panthers.
[2018-09-09 15:04:55] - Adam Carlson was added to Floride Panthers.
[2018-09-05 22:30:44] - TRADE : From Boston Bruins to Floride Panthers : Y:15-RND:3-Bos.
[2018-09-05 12:45:17] - Ron Hainsey was released.
[2018-09-03 23:14:52] - TRADE : From Calgary Flames to Floride Panthers : Mason Appleton.
[2018-09-03 12:22:31] - TRADE : From Floride Panthers to Boston Bruins : Brad Marchand, Tuukka Rask.
[2018-09-03 12:22:31] - TRADE : From Boston Bruins to Floride Panthers : Mark Stone, Ben Bishop, Taylor Raddysh (P), Y:15-RND:5-Bos.
[2018-07-29 18:28:57] - Floride Panthers drafts Pavel Shen as the #181 overall pick in the Entry Draft of year 13.
[2018-07-26 08:04:21] - Matia Marcantuoni has been deleted from Floride Panthers.
[2018-07-26 08:04:19] - Mason Appelton has been deleted from Floride Panthers.
[2018-07-26 08:04:15] - Eric Knodel has been deleted from Floride Panthers.
[2018-07-26 08:04:12] - Daniel Bernhardt has been deleted from Floride Panthers.
[2018-07-16 20:16:14] - Zach Trotman was added to Floride Panthers.
[2018-07-16 20:16:14] - Jens Looke was added to Floride Panthers.



[2018-10-14 14:40:09] Successfully loaded Florida Panthers lines done with STHS Client - 3.1.2.2
[2018-10-13 15:15:42] Mark Stone from Florida Panthers has scored a Hat Trick!
[2018-10-13 15:11:45] Auto Lines Partial Function has been run for Florida Panthers.
[2018-10-13 15:11:45] Auto Roster Partial Function has been run for Florida Panthers.
[2018-10-13 15:11:45] Steven Kampfer of Florida Panthers was sent to pro.
[2018-10-11 12:46:23] Game 48 - John Klingberg from Florida Panthers is injured (Broken Nose) and is out for 1 week.
[2018-10-08 12:11:15] TRADE : From Pittsburgh Penguins to Florida Panthers : Steven Kampfer.
[2018-10-08 12:11:15] TRADE : From Florida Panthers to Pittsburgh Penguins : Y:15-RND:5-Bos.
[2018-10-01 08:11:44] Successfully loaded Florida Panthers lines done with STHS Client - 3.1.2.2



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
13422000001215-32110000089-12110000046-24122133005340127623035013742435916425.00%18288.89%08615854.43%8116549.09%336352.38%946495284924
Total Saison Régulière422000001215-32110000089-12110000046-24122133005340127623035013742435916425.00%18288.89%08615854.43%8116549.09%336352.38%946495284924
Séries
121147000002735-8624000001620-4523000001115-48275077101555239613013412111336999622937616.22%38684.21%123846151.63%22238457.81%10317160.23%2821972507914473
121147000002735-8624000001620-4523000001115-48275077101555239613013412111336999622937616.22%38684.21%123846151.63%22238457.81%10317160.23%2821972507914473
Total Séries22814000005470-161248000003240-81046000002230-8165410015420301010479226026824222672198192458741216.22%761284.21%247692251.63%44476857.81%20634260.23%564395501159288147