Flames

GP: 78 | W: 43 | L: 23 | OTL: 12 | P: 98
GF: 231 | GA: 207 | PP%: 20.28% | PK%: 79.86%
DG: Benoit Talbot | Morale : 81 | Moyenne d'Équipe : 69
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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
1Patrik Laine (R)X100.006542848684869789577498625687589383770
2Dylan LarkinX100.006745808775929782898480686465638484760
3Devin SetoguchiX100.008849846177798181647582747699814672730
4Jake Guentzel (R)X100.007743808563869980747273655473546484720
5Jeremy MorinX100.007356766474807972687876647276795685700
6Danton Heinen (R)X100.006241868270829578667667675368525962700
7Joel Armia (R)X100.006741807279809472656967705770548183690
8Oscar Lindberg (R)X100.006741817274788677807274635873545981690
9Adrian Kempe (R)X100.006844737674819673786970635472527983690
10Devin Shore (R)X100.006341867673849870717065666668565384680
11Jeremy WilliamsX100.00191996473545773376285758399995958670
12Daniel Carr (R)X100.006142806969767568556766635366523781640
13Matt Dumba (R)X100.007543848166939879309081796275708585770
14Jamie McBainX100.005321996978747394558677866981793484750
15Mark PysykX100.007142846973839576306970786166587782710
16Andrew Campbell (R)X100.008544686779858688495245814560614473710
17Haydn Fleury (R)X100.007041856684788666306765705262518782670
18Thomas Chabot (R)X100.006342846574779073306974625270518382660
Rayé
1Alan Quine (R)X100.006841827072776862796358635862527119620
2Andreas Martinsen (R)X100.007445646086649357505962645558533650620
3Michael McCarron (R)X100.007151536193639158545956665256518120610
4Darren Dietz (R)X100.009949786475678769256153685053494919660
5Julian Melchiori (R)X100.004931846680576381254647695466734218630
6Jim VandermeerX100.00999916078828435123339544699992219620
7Rinat Valiev (R)X100.006743735184527658305756625057506620590
MOYENNE D'ÉQUIPE100.00694377707676867252676768587162626468
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
1Johan Holmqvist100.00685975787496969696779099992183810
2Alexandar Georgiev (R)100.00737297737690818080715072624444760
Rayé
1Magnus Hellberg (R)100.00718682847281728173707479785554760
2Jared Coreau (R)100.00717180917181777676705167613719740
3Spencer Martin (R)100.00575573807070656867725658528719650
MOYENNE D'ÉQUIPE100.0068698181738478807872647570494474
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Darryl Sutter99968396999993CAN6012,000,000$


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
1Patrik LaineFlames (CGY)RW78445094132201681753799919011.61%39172422.1114203450242202132616244.90%6088338121.093180009106
2Dylan LarkinFlames (CGY)C78295685145001601882417715612.03%38171221.961220323724201142427254.96%18256725100.99218000686
3Matt DumbaFlames (CGY)D72124557928012413317071687.06%97169323.53102232412660112212200.00%05650000.6700000330
4Jake GuentzelFlames (CGY)LW78242650125601811052345712010.26%26140217.985813312110000347355.45%1105925020.7101000534
5Jeremy MorinFlames (CGY)LW7225184388515160831674710714.97%35133118.5098171916710131243453.19%942125210.6527210451
6Danton HeinenFlames (CGY)C75152237-5240117153216611216.94%33128417.123710171720001422246.47%11902622000.5800000232
7Alexander WennbergFlamesC51122335-211207311317339856.94%1794618.5551419311460005741255.48%1058279000.7426000311
8Mark PysykFlames (CGY)D78328311930012513710433392.88%103171722.0200051800002191000.00%02351000.3602000112
9Devin SetoguchiFlames (CGY)RW7315163108014885167541008.98%29129217.71426151820004422147.52%1012123000.4805000202
10Jamie McBainFlames (CGY)D6992130-3806212412461587.26%101165023.926915282200004221140.00%03448000.3601000032
11Oscar LindbergFlames (CGY)C7871825312010686179511313.91%3196612.39000260000221253.34%6583715000.5211000002
12Joel ArmiaFlames (CGY)RW78141024522010165128437210.94%2396212.341012130001112356.10%412620000.5000000212
13Adrian KempeFlames (CGY)LW7813720-63201246815941898.18%2295412.241122200004371148.33%602713010.4200000122
14Daniel CarrFlames (CGY)LW78951415220864370124412.86%137369.440001500001580025.00%121010000.3800000000
15Devin Shore Flames (CGY)C787613610042428624518.14%105487.03000120112141047.22%1801414000.4701000001
16Jeremy WilliamsFlames (CGY)RW5839125201387325514.11%63906.7400003000000033.33%998000.6133000100
17Thomas ChabotFlames (CGY)D7811112934074906423221.56%55126316.19000244000051000.00%01734000.1900000000
18Andrew CampbellFlames (CGY)D761891311151531197627341.32%89151319.910002900000143000.00%0552000.1200000000
19Haydn FleuryFlames (CGY)D741345120941056116221.64%79123116.65000136000066010.00%0847000.0600000000
20Darren DietzFlames (CGY)D150221112024107060.00%1622915.320000000008000.00%008000.1700000000
21Andreas Martinsen Flames (CGY)RW55011-140341893100.00%92284.1600001000020050.00%213000.0900000000
22Julian MelchioriFlames (CGY)D2000120213000.00%23216.330000000004000.00%004000.0000000000
23Alan QuineFlames (CGY)C24000100312000.00%0180.7800003000000037.50%800000.0000000000
24Michael McCarron Flames (CGY)RW25000100621140.00%0512.04000000000360027.27%1101000.0000000000
Stats d'équipe Total ou en Moyenne15212443856291145982021681984289386515808.43%8732388515.70701111812872308336461907362751.55%5967571545460.531363210394033
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
1Johan HolmqvistFlames (CGY)744221110.9242.4044488217823561007410.800657441376
2Magnus HellbergFlames (CGY)71210.9093.293280018197104000.3333451010
Stats d'équipe Total ou en Moyenne814323120.9232.4647778219625531111410.7796878551386


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 Link
Adrian KempeFlames (CGY)LW221996-09-13 05:44:01Yes195 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm894,167$0$0$No
Alan QuineFlames (CGY)C261993-02-25 18:35:24Yes203 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm620,000$0$0$No
Alexandar GeorgievFlames (CGY)G231996-02-10 10:25:08Yes180 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm925,000$0$0$No
Andreas Martinsen Flames (CGY)RW281990-06-12 18:37:17Yes220 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm743,000$0$0$No
Andrew CampbellFlames (CGY)D311988-02-04 05:11:13Yes212 Lbs6 ft4NoNoNo3Sans RestrictionPro & Farm1,250,000$0$0$No
Daniel CarrFlames (CGY)LW271991-10-31 07:15:35Yes194 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm925,000$0$0$No
Danton HeinenFlames (CGY)C231995-07-05 09:18:29Yes188 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm872,500$0$0$No
Darren DietzFlames (CGY)D251993-07-16 06:42:37Yes206 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Devin SetoguchiFlames (CGY)RW321987-01-01 23:11:13No213 Lbs6 ft0NoNoNo3Sans RestrictionPro & Farm1,500,000$0$0$No
Devin Shore Flames (CGY)C241994-07-18 18:38:49Yes205 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm870,000$0$0$No
Dylan LarkinFlames (CGY)C221996-07-30 10:22:37No198 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm1,425,000$0$0$No
Haydn FleuryFlames (CGY)D221996-07-08 04:00:49Yes221 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm1,713,330$0$0$No
Jake GuentzelFlames (CGY)LW241994-10-06 05:45:54Yes181 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm734,167$0$0$No
Jamie McBainFlames (CGY)D311988-02-25 05:11:13No214 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm2,000,000$0$0$No
Jared CoreauFlames (CGY)G271991-11-05 05:47:36Yes220 Lbs6 ft6NoNoNo2Avec RestrictionPro & Farm612,500$0$0$No
Jeremy MorinFlames (CGY)LW281991-04-16 23:11:13No201 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm900,000$0$0$No
Jeremy WilliamsFlames (CGY)RW351984-01-26 05:11:13No198 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm600,000$0$0$No
Jim VandermeerFlames (CGY)D391980-02-21 05:11:13No217 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm600,000$0$0$No
Joel ArmiaFlames (CGY)RW251993-05-30 11:11:13Yes205 Lbs6 ft3NoNoNo3Avec RestrictionPro & Farm800,000$0$0$No
Johan HolmqvistFlames (CGY)G401978-05-24 17:11:14No197 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm1,500,000$0$0$No
Julian MelchioriFlames (CGY)D271991-12-06 23:11:13Yes196 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm575,000$0$0$No
Magnus HellbergFlames (CGY)G281991-04-04 23:11:14Yes192 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm800,000$0$0$No
Mark PysykFlames (CGY)D271992-01-11 05:11:13No203 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Matt DumbaFlames (CGY)D241994-07-25 17:11:13Yes184 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm2,000,000$0$0$No
Michael McCarron Flames (CGY)RW241995-03-07 18:40:02Yes230 Lbs6 ft6NoNoNo1Avec RestrictionPro & Farm1,076,000$0$0$No
Oscar LindbergFlames (CGY)C271991-10-29 23:11:13Yes202 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm900,000$0$0$No
Patrik LaineFlames (CGY)RW211998-04-19 05:49:33Yes208 Lbs6 ft5NoNoNo2Contrat d'EntréePro & Farm925,000$0$0$No
Rinat Valiev Flames (CGY)D231995-05-11 18:42:09Yes215 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm894,000$0$0$No
Spencer MartinFlames (CGY)G231995-06-08 05:53:37Yes213 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm728,333$0$0$No
Thomas ChabotFlames (CGY)D221997-01-30 05:55:22Yes196 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm863,333$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3026.67204 Lbs6 ft21.871,001,544$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jake GuentzelDylan LarkinPatrik Laine34122
2Jeremy MorinDanton HeinenDevin Setoguchi34122
3Adrian KempeOscar LindbergJoel Armia26122
4Daniel CarrDevin Shore Jeremy Williams6122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt DumbaJamie McBain34122
2Mark PysykHaydn Fleury34122
3Thomas ChabotAndrew Campbell32122
4Matt DumbaJamie McBain0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Jake GuentzelDylan LarkinPatrik Laine60122
2Jeremy MorinDanton HeinenDevin Setoguchi40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt DumbaJamie McBain60122
2Mark PysykDaniel Carr40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Patrik LaineDylan Larkin60122
2Devin SetoguchiJake Guentzel40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt DumbaJamie McBain60122
2Mark PysykHaydn Fleury40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Patrik Laine60122Matt DumbaJamie McBain60122
2Dylan Larkin40122Mark PysykHaydn Fleury40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Patrik LaineDylan Larkin60122
2Devin SetoguchiJake Guentzel40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt DumbaJamie McBain60122
2Mark PysykHaydn Fleury40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jake GuentzelDylan LarkinPatrik LaineMatt DumbaJamie McBain
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Jake GuentzelDylan LarkinPatrik LaineMatt DumbaJamie McBain
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Oscar Lindberg, Devin Shore , Adrian KempeOscar Lindberg, Devin Shore Adrian Kempe
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Thomas Chabot, Andrew Campbell, Mark PysykThomas ChabotAndrew Campbell, Mark Pysyk
Tirs de Pénalité
Patrik Laine, Dylan Larkin, Devin Setoguchi, Jake Guentzel, Danton Heinen
Gardien
#1 : Johan Holmqvist, #2 : Alexandar Georgiev


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
1Avalanche43100000161332200000011832110000055060.7501623390071747416145983900809117148452410812433.33%13284.62%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
2Blackhawks40300010615-92010001045-120200000210-820.250681410717474161489839008091171345826106700.00%13469.23%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
3Blues42100001151142100000143121100000118350.6251523380071747416158983900809117135452310914428.57%9277.78%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
4Bruins21000001752110000004131000000134-130.750712190071747416779839008091176820106110110.00%5180.00%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
5Canadiens21001000743100010004311100000031241.00071017007174741670983900809117753312456116.67%6183.33%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
6Canucks64000020281513320000101477320000101486121.0002847750071747416196983900809117185586817442819.05%35391.43%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
7Capitals211000005501010000013-21100000042220.5005813007174741671983900809117692116407228.57%7271.43%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
8Devils200001107701000010045-11000001032130.75071017007174741666983900809117672414477114.29%7271.43%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
9Ducks602020021317-43010000259-43010200088060.500132033007174741619898390080911721259601641317.69%30583.33%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
10Flyers20100010440100000102111010000023-120.500461000717474166498390080911774201250700.00%6350.00%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
11Islanders21000010642110000003211000001032141.0006713007174741673983900809117652786914428.57%4250.00%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
12Kings603000211218-63010001156-130200010712-550.4171219310071747416205983900809117213673414319526.32%17382.35%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
13Maple Leafs22000000725110000003121100000041341.00071320007174741669983900809117461210568112.50%5180.00%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
14Oilers621000032524130100002813-5320000011711670.58325376200717474162279839008091171946087170401025.00%381268.42%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
15Penguins211000005321010000013-21100000040420.5005813017174741655983900809117571810647228.57%5180.00%11037206650.19%1012201850.15%551109550.32%1758104616907091333663
16Predators431000001073211000004402200000063360.7501015250071747416144983900809117121361411818316.67%70100.00%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
17Rangers210000017251000000112-11100000060630.750713200171747416709839008091176120105512216.67%50100.00%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
18Red Wings2110000089-11010000024-21100000065120.50081422007174741661983900809117581712645240.00%6183.33%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
19Sabres211000006511010000024-21100000041320.5006915007174741666983900809117682424554375.00%12375.00%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
20Senateurs22000000734110000003121100000042241.0007916007174741670983900809117582612583133.33%6266.67%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
21Sharks623010001214-23120000067-13110100067-160.500122133007174741622298390080911719072521771500.00%26580.77%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
22Stars41200100711-4211000004402010010037-430.37571219007174741613198390080911713941441075120.00%22386.36%01037206650.19%1012201850.15%551109550.32%1758104616907091333663
Total783123042810231207243913120114810010003918110314213110724980.62823136359412717474162740983900809117255484260021452815720.28%2935979.86%31037206650.19%1012201850.15%551109550.32%1758104616907091333663
24Wild421000011192210000015412110000065150.625111930007174741615498390080911711739181056116.67%9188.89%21037206650.19%1012201850.15%551109550.32%1758104616907091333663
_Since Last GM Reset783123042810231207243913120114810010003918110314213110724980.62823136359412717474162740983900809117255484260021452815720.28%2935979.86%31037206650.19%1012201850.15%551109550.32%1758104616907091333663
_Vs Conference541918031581551541279800037707002710100312185841630.58315524439910717474161928983900809117178858045014811913719.37%2194081.74%21037206650.19%1012201850.15%551109550.32%1758104616907091333663
_Vs Division308903046908821535000253842-415540302152466360.60090144234007174741610489839008091179943163018281292418.60%1462880.82%01037206650.19%1012201850.15%551109550.32%1758104616907091333663

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7898W423136359427402554842600214512
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
78312342810231207
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3913121148100100
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3918113142131107
Derniers 10 Matchs
WLOTWOTL SOWSOL
710002
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2815720.28%2935979.86%3
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
98390080911771747416
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
1037206650.19%1012201850.15%551109550.32%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1758104616907091333663


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 - 2018-10-0113Oilers3Flames2LXXSommaire du Match
5 - 2018-10-0323Flames7Oilers4WSommaire du Match
6 - 2018-10-0425Flames4Sharks2WSommaire du Match
9 - 2018-10-0743Kings1Flames2WXXSommaire du Match
12 - 2018-10-1058Sharks1Flames2WSommaire du Match
16 - 2018-10-1473Ducks5Flames4LXXSommaire du Match
17 - 2018-10-1583Flames6Canucks3WSommaire du Match
20 - 2018-10-1897Canucks2Flames6WSommaire du Match
23 - 2018-10-21108Flames3Ducks2WXSommaire du Match
24 - 2018-10-22120Flames2Stars3LXSommaire du Match
27 - 2018-10-25133Wild3Flames2LXXSommaire du Match
28 - 2018-10-26138Flames1Kings3LSommaire du Match
31 - 2018-10-29152Oilers7Flames4LSommaire du Match
33 - 2018-10-31161Flames1Blues3LSommaire du Match
35 - 2018-11-02171Flames1Blackhawks5LSommaire du Match
37 - 2018-11-04183Ducks2Flames0LSommaire du Match
39 - 2018-11-06198Red Wings4Flames2LSommaire du Match
41 - 2018-11-08204Flames3Islanders2WXXSommaire du Match
44 - 2018-11-11222Avalanche5Flames6WSommaire du Match
46 - 2018-11-13228Flames5Wild2WSommaire du Match
49 - 2018-11-16240Flames6Rangers0WSommaire du Match
51 - 2018-11-18251Flames1Blackhawks5LSommaire du Match
53 - 2018-11-20262Canucks4Flames5WXXSommaire du Match
56 - 2018-11-23277Flyers1Flames2WXXSommaire du Match
58 - 2018-11-25285Flames2Flyers3LSommaire du Match
60 - 2018-11-27300Stars3Flames2LSommaire du Match
62 - 2018-11-29309Flames6Red Wings5WSommaire du Match
64 - 2018-12-01322Flames3Bruins4LXXSommaire du Match
67 - 2018-12-04330Senateurs1Flames3WSommaire du Match
69 - 2018-12-06341Flames2Ducks1WXSommaire du Match
72 - 2018-12-09356Predators2Flames1LSommaire du Match
74 - 2018-12-11372Flames3Kings2WXXSommaire du Match
75 - 2018-12-12378Sharks3Flames2LSommaire du Match
78 - 2018-12-15392Flames3Devils2WXXSommaire du Match
80 - 2018-12-17402Kings2Flames1LSommaire du Match
82 - 2018-12-19412Flames10Blues5WSommaire du Match
84 - 2018-12-21426Sharks3Flames2LSommaire du Match
86 - 2018-12-23442Flames4Maple Leafs1WSommaire du Match
87 - 2018-12-24449Capitals3Flames1LSommaire du Match
89 - 2018-12-26461Flames3Kings7LSommaire du Match
91 - 2018-12-28474Devils5Flames4LXSommaire du Match
94 - 2018-12-31488Flames4Canucks3WXXSommaire du Match
96 - 2019-01-02497Penguins3Flames1LSommaire du Match
98 - 2019-01-04509Flames4Sabres1WSommaire du Match
100 - 2019-01-06521Flames4Penguins0WSommaire du Match
101 - 2019-01-07526Bruins1Flames4WSommaire du Match
104 - 2019-01-10544Kings3Flames2LXXSommaire du Match
106 - 2019-01-12561Flames3Ducks5LSommaire du Match
108 - 2019-01-14567Flames3Canadiens1WSommaire du Match
109 - 2019-01-15574Ducks2Flames1LXXSommaire du Match
112 - 2019-01-18590Flames3Avalanche4LSommaire du Match
114 - 2019-01-20597Flames4Canucks2WSommaire du Match
115 - 2019-01-21604Canadiens3Flames4WXSommaire du Match
118 - 2019-01-24614Flames2Avalanche1WSommaire du Match
119 - 2019-01-25621Blackhawks3Flames1LSommaire du Match
123 - 2019-01-29645Wild1Flames3WSommaire du Match
126 - 2019-02-01657Flames3Oilers4LXXSommaire du Match
129 - 2019-02-04670Islanders2Flames3WSommaire du Match
130 - 2019-02-05680Flames7Oilers3WSommaire du Match
134 - 2019-02-09694Stars1Flames2WSommaire du Match
137 - 2019-02-12706Flames1Wild3LSommaire du Match
139 - 2019-02-14717Sabres4Flames2LSommaire du Match
141 - 2019-02-16721Flames4Senateurs2WSommaire du Match
145 - 2019-02-20742Predators2Flames3WSommaire du Match
148 - 2019-02-23761Rangers2Flames1LXXSommaire du Match
152 - 2019-02-27780Avalanche3Flames5WSommaire du Match
154 - 2019-03-01788Flames0Sharks4LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
157 - 2019-03-04805Maple Leafs1Flames3WSommaire du Match
159 - 2019-03-06815Flames4Predators2WSommaire du Match
161 - 2019-03-08824Flames4Capitals2WSommaire du Match
164 - 2019-03-11839Oilers3Flames2LXXSommaire du Match
166 - 2019-03-13852Blues2Flames1LXXSommaire du Match
168 - 2019-03-15864Flames2Predators1WSommaire du Match
169 - 2019-03-16871Flames1Stars4LSommaire du Match
171 - 2019-03-18878Flames2Sharks1WXSommaire du Match
173 - 2019-03-20886Blues1Flames3WSommaire du Match
178 - 2019-03-25908Blackhawks2Flames3WXXSommaire du Match
183 - 2019-03-30929Canucks1Flames3WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets4525
Assistance58,40232,515
Assistance PCT74.87%83.37%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2331 - 77.71% 79,161$3,087,277$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
4,156,705$ 3,004,633$ 1,689,633$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
16,241$ 2,971,173$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 27,052$ 0$




LigueDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
137831230428102312072439131201148100100039181103142131107249823136359412717474162740983900809117255484260021452815720.28%2935979.86%31037206650.19%1012201850.15%551109550.32%1758104616907091333663
Total Saison Régulière7831230428102312072439131201148100100039181103142131107249823136359412717474162740983900809117255484260021452815720.28%2935979.86%31037206650.19%1012201850.15%551109550.32%1758104616907091333663