Flames

GP: 52 | W: 28 | L: 18 | OTL: 6 | P: 62
GF: 115 | GA: 111 | PP%: 12.22% | PK%: 89.67%
DG: Sebastien Tessier | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #568 vs Marlies
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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 SPÂgeContratSalaire
1Adam BrooksX100.00686381636365666278596261594444635000242925,000$
2Alex Chiasson (C)XX100.007344817878648678256570593673757050002932,275,000$
3Brendan PerliniXX100.006743918479577165255856617564646250002411,999,999$
4Colin White (A)XX100.00715281816770847677716058536464665000231750,000$
5Drake BathersonXX100.00877583777170907654756457254747695000222773,333$
6Jacob de La RoseXX100.00894693777957726062625678256465655300251750,000$
7Owen Tippett (R) (A)XX100.008178886778666766506266686344446850002111,627,500$
8Emil Bemstrom (R)X100.007342958265626968346471542550506850002132,133,333$
9Jaret Anderson-Dolan (R)XX100.00726783796763645974595462514444615000203913,333$
10Nic PetanXXX100.00634191796258576932655566255959635000251500,000$
11Riley Tufte (R)X100.00858878618862655150514666444444565000223995,833$
12Carson SoucyX100.00784589647967785925505478255960634900253775,000$
13Greg PaterynX100.00784590718267685625514784256465624700301800,000$
14Parker Wotherspoon (R)X100.00636264636276835225494156394444535000223854,722$
15Chris BigrasX100.00757183637160635425494165395757555000253700,000$
16Madison BoweyX100.00754481777374696225604875255757635000251902,500$
17Haydn FleuryX100.007645937282626458255650727558596250002321,713,333$
Rayé
MOYENNE D'ÉQUIPE100.0075568573736572634259556642555563500
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
1Carter Hutton100.0065737276725857656365716465655000
2Thatcher Demko100.0066585681656668677566754747664900
Rayé
1Filip Gustavsson100.0050577172475250555050304444514400
MOYENNE D'ÉQUIPE100.006063667661595862636059525261480
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jeremy Colliton77768986514890CAN3731,750,000$


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
1Colin WhiteFlames (CGY)C/RW5212193112403310081316214.81%296618.583912152510000153158.84%97900000.6414000243
2Alex ChiassonFlames (CGY)LW/RW5211182915406972107398210.28%3100319.30371024222000001234.43%6100000.5800000221
3Nic PetanFlames (CGY)C/LW/RW52111829160247471205015.49%180915.571131417229000023141.86%4300000.7200000214
4Emil BemstromFlames (CGY)C52121628-3280607272285616.67%181915.763710152280000143036.73%72700000.6800000223
5Madison BoweyFlames (CGY)D5242226-470089505114307.84%36112121.5731114412320112200000.00%000000.4600000022
6Drake BathersonFlames (CGY)C/RW4571522146075617722469.09%279417.6423529227000021047.06%5100000.5500000402
7Owen TippettFlames (CGY)LW/RW5211112203810574880226413.75%7113421.814262323800022254150.00%7800000.3918011160
8Haydn FleuryFlames (CGY)D5261622-1340464032152818.75%40108420.856410242190110194100.00%000000.4126000212
9Greg PaterynFlames (CGY)D475141910460705047103010.64%43106422.65437302170001192100.00%000000.3600000122
10Carson SoucyFlames (CGY)D49612187400702943152813.95%28109522.37459272310000208200.00%000100.3300000311
11Brendan PerliniFlames (CGY)LW/RW52610166140257055163210.91%1278115.0301135210121133042.11%7600100.4128000130
12Jacob de La RoseFlames (CGY)C/LW476511-34606610751135311.76%1376916.371011900042091052.52%83400100.2900000212
13Riley TufteFlames (CGY)LW52628534053231621237.50%05089.7820223600011530141.18%3400000.3101000310
14Adam BrooksFlames (CGY)C52347-514020593211199.38%255410.660000200011641060.32%44100000.2512000101
15Parker WotherspoonFlames (CGY)D52257-76556620134815.38%3588817.092025380001105000.00%000000.1600100000
16Jaret Anderson-DolanFlames (CGY)C/LW52257-7221029494513394.44%675014.430226620000651063.21%10600000.1914011010
17Chris BigrasFlames (CGY)D52235-8101158826165212.50%2881315.65011460000051010.00%000000.1200102101
Stats d'équipe Total ou en Moyenne864112195307-66824094095088928064112.60%2591495917.313868106266256012314191925751.37%343000300.41833224272724
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
1Thatcher DemkoFlames (CGY)46261550.8811.99277504927760210.65426465212
2Carter HuttonFlames (CGY)72310.8902.0039000131180000.7147646000
Stats d'équipe Total ou en Moyenne53281860.8831.993165041058940210.667335251212


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 Salaire RestantSalaire MoyenSalaire Moyen RestantCap 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
Adam BrooksFlames (CGY)C241996-05-06No174 Lbs5 ft11NoNoNo2Pro & Farm925,000$343,145$450,000$166,935$0$0$No925,000$Lien
Alex ChiassonFlames (CGY)LW/RW291990-10-01No208 Lbs6 ft4NoNoNo3Pro & Farm2,275,000$843,952$2,150,000$797,581$0$0$No2,150,000$2,150,000$Lien
Brendan PerliniFlames (CGY)LW/RW241996-04-27No212 Lbs6 ft3NoNoNo1Pro & Farm1,999,999$741,935$1,999,999$741,935$0$0$NoLien
Carson SoucyFlames (CGY)D251994-07-27No208 Lbs6 ft5NoNoNo3Pro & Farm775,000$287,500$750,000$278,226$0$0$No750,000$750,000$Lien
Carter HuttonFlames (CGY)G341985-12-18No202 Lbs6 ft1NoNoNo1Pro & Farm2,750,000$1,020,161$2,750,000$1,020,161$0$0$NoLien
Chris BigrasFlames (CGY)D251995-02-22No190 Lbs6 ft1NoNoNo3Pro & Farm700,000$259,677$700,000$259,677$0$0$No700,000$700,000$Lien
Colin WhiteFlames (CGY)C/RW231997-01-30No183 Lbs6 ft0NoNoNo1Pro & Farm750,000$278,226$750,000$278,226$0$0$NoLien
Drake BathersonFlames (CGY)C/RW221998-04-26No187 Lbs6 ft1NoNoNo2Pro & Farm773,333$286,882$773,333$286,882$0$0$No773,333$Lien
Emil BemstromFlames (CGY)C211999-06-01Yes181 Lbs5 ft10NoNoNo3Pro & Farm2,133,333$791,398$1,633,333$605,914$0$0$No1,633,333$1,633,333$Lien
Filip GustavssonFlames (CGY)G221998-06-07No184 Lbs6 ft2NoNoNo2Pro & Farm910,833$337,890$450,000$166,935$0$0$No910,833$Lien
Greg PaterynFlames (CGY)D301990-06-20No224 Lbs6 ft3NoNoNo1Pro & Farm800,000$296,774$800,000$296,774$0$0$NoLien
Haydn FleuryFlames (CGY)D231996-07-08No221 Lbs6 ft3NoNoNo2Pro & Farm1,713,333$635,591$1,713,333$635,591$0$0$No1,713,333$Lien
Jacob de La RoseFlames (CGY)C/LW251995-05-19No210 Lbs6 ft3NoNoNo1Pro & Farm750,000$278,226$750,000$278,226$0$0$NoLien
Jaret Anderson-DolanFlames (CGY)C/LW201999-09-11Yes188 Lbs5 ft11NoNoNo3Pro & Farm913,333$338,817$913,333$338,817$0$0$No913,333$913,333$
Madison BoweyFlames (CGY)D251995-04-22No198 Lbs6 ft2NoNoNo1Pro & Farm902,500$334,798$902,500$334,798$0$0$NoLien
Nic PetanFlames (CGY)C/LW/RW251995-03-21No179 Lbs5 ft9NoNoNo1Pro & Farm500,000$185,484$500,000$185,484$0$0$NoLien
Owen TippettFlames (CGY)LW/RW211999-02-15Yes216 Lbs6 ft1NoNoNo1Pro & Farm1,627,500$603,750$450,000$166,935$0$0$NoLien
Parker WotherspoonFlames (CGY)D221997-08-24Yes168 Lbs6 ft0NoNoNo3Pro & Farm854,722$317,074$854,722$317,074$0$0$No854,722$854,722$
Riley TufteFlames (CGY)LW221998-04-09Yes230 Lbs6 ft6NoNoNo3Pro & Farm995,833$369,422$995,833$369,422$0$0$No995,833$995,833$
Thatcher DemkoFlames (CGY)G241995-12-07No192 Lbs6 ft4NoNoNo3Pro & Farm1,050,000$389,516$1,050,000$389,516$0$0$No1,050,000$1,050,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2024.30198 Lbs6 ft22.001,204,986$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Owen TippettColin WhiteDrake Batherson35122
2Nic PetanEmil BemstromAlex Chiasson30122
3Jaret Anderson-DolanJacob de La RoseBrendan Perlini25122
4Riley TufteAdam BrooksAlex Chiasson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Carson SoucyGreg Pateryn35122
2Madison BoweyHaydn Fleury30122
3Chris BigrasParker Wotherspoon25122
4Greg PaterynMadison Bowey10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Owen TippettColin WhiteDrake Batherson60122
2Nic PetanEmil BemstromAlex Chiasson40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Carson SoucyGreg Pateryn60122
2Madison BoweyHaydn Fleury40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Jacob de La RoseOwen Tippett60122
2Adam BrooksRiley Tufte40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Carson SoucyGreg Pateryn60122
2Madison BoweyHaydn Fleury40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Jacob de La Rose60122Carson SoucyGreg Pateryn60122
2Adam Brooks40122Madison BoweyHaydn Fleury40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Colin WhiteOwen Tippett60122
2Jacob de La RoseDrake Batherson40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Haydn FleuryGreg Pateryn60122
2Madison BoweyCarson Soucy40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Owen TippettColin WhiteDrake BathersonCarson SoucyGreg Pateryn
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Riley TufteJacob de La RoseBrendan PerliniCarson SoucyGreg Pateryn
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jaret Anderson-Dolan, Riley Tufte, Brendan PerliniJaret Anderson-Dolan, Riley TufteBrendan Perlini
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Chris Bigras, Parker Wotherspoon, Madison BoweyChris BigrasParker Wotherspoon, Madison Bowey
Tirs de Pénalité
Brendan Perlini, Owen Tippett, Haydn Fleury, Colin White, Jaret Anderson-Dolan
Gardien
#1 : Thatcher Demko, #2 : Carter Hutton


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
1Admirals5300001116106310000118622200000084490.900162339003937341093287309284427723607832618.75%24195.83%0687136650.29%712136152.31%36470451.70%13009031221394647325
2Bruins11000000431110000004310000000000021.00046100039373410212873092844221414176233.33%7185.71%0687136650.29%712136152.31%36470451.70%13009031221394647325
3Condors541000001376211000005503300000082680.80013243701393734109128730928442692575783438.82%270100.00%1687136650.29%712136152.31%36470451.70%13009031221394647325
4Crunch1000010023-1000000000001000010023-110.5002460039373410122873092844225121616100.00%8187.50%0687136650.29%712136152.31%36470451.70%13009031221394647325
5Griffins22000000523110000004221100000010141.000591401393734102828730928442317124114214.29%6183.33%0687136650.29%712136152.31%36470451.70%13009031221394647325
6IceHogs11000000422000000000001100000042221.00047110039373410222873092844216516144125.00%8187.50%0687136650.29%712136152.31%36470451.70%13009031221394647325
7Monarchs614000101119-830200010710-33120000049-540.333111627003937341096287309284421164811111530310.00%41782.93%0687136650.29%712136152.31%36470451.70%13009031221394647325
8Monsters22000000624110000003031100000032141.0006101601393734102428730928442351528397114.29%120100.00%0687136650.29%712136152.31%36470451.70%13009031221394647325
9Moose823000121416-2412000108714110000269-380.500142640003937341014928730928442131288614462711.29%41490.24%0687136650.29%712136152.31%36470451.70%13009031221394647325
10Penguins1010000001-1000000000001010000001-100.000000003937341013287309284421561422300.00%70100.00%0687136650.29%712136152.31%36470451.70%13009031221394647325
11Phantoms10001000431100010004310000000000021.00046100039373410192873092844218512237228.57%60100.00%0687136650.29%712136152.31%36470451.70%13009031221394647325
12Rampage2010100023-12010100023-10000000000020.50024600393734104428730928442361516399111.11%8187.50%0687136650.29%712136152.31%36470451.70%13009031221394647325
13Senators11000000523110000005230000000000021.0005914003937341023287309284427518198112.50%90100.00%0687136650.29%712136152.31%36470451.70%13009031221394647325
14Sharks724000011016-62110000055051300001511-650.3571017270039373410992873092844212426881163412.94%36586.11%0687136650.29%712136152.31%36470451.70%13009031221394647325
15Soldiers21000001871000000000002100000187130.7508152300393734104128730928442388243516212.50%12466.67%0687136650.29%712136152.31%36470451.70%13009031221394647325
16Sound Tigers1010000013-2000000000001010000013-200.000123003937341010287309284422851629400.00%8275.00%0687136650.29%712136152.31%36470451.70%13009031221394647325
17Stars11000000202110000002020000000000021.0002460139373410122873092844215414235120.00%70100.00%0687136650.29%712136152.31%36470451.70%13009031221394647325
Total52231802135115111425109020316052827139001045559-4620.5961151953101439373410889287309284428952606869463113812.22%3003189.67%1687136650.29%712136152.31%36470451.70%13009031221394647325
18Wolf Pack3120000036-33120000036-30000000000020.333358103937341057287309284425811445219210.53%22290.91%0687136650.29%712136152.31%36470451.70%13009031221394647325
19Wolves2110000056-1000000000002110000056-120.500581300393734103528730928442358224616318.75%11190.91%0687136650.29%712136152.31%36470451.70%13009031221394647325
_Since Last GM Reset52231802135115111425109020316052827139001045559-4620.5961151953101439373410889287309284428952606869463113812.22%3003189.67%1687136650.29%712136152.31%36470451.70%13009031221394647325
_Vs Conference1053011002420474201000191453110010056-1130.6502440641139373410169287309284421795814618851815.69%71494.37%0687136650.29%712136152.31%36470451.70%13009031221394647325
_Vs Division833010001415-15220100010913110000046-280.5001423371139373410123287309284421544211416540512.50%55492.73%0687136650.29%712136152.31%36470451.70%13009031221394647325

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5262W111519531088989526068694614
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
5223182135115111
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2510920316052
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2713901045559
Derniers 10 Matchs
WLOTWOTL SOWSOL
260101
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3113812.22%3003189.67%1
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
2873092844239373410
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
687136650.29%712136152.31%36470451.70%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
13009031221394647325


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
1 - 2020-09-272Flames1Moose2LXXSommaire du Match
2 - 2020-09-2812Flames0Sharks3LSommaire du Match
3 - 2020-09-2922Monarchs3Flames2LSommaire du Match
4 - 2020-09-3032Flames4Condors1WSommaire du Match
6 - 2020-10-0245Sharks3Flames1LSommaire du Match
8 - 2020-10-0459Condors2Flames0LSommaire du Match
10 - 2020-10-0667Flames2Monarchs1WSommaire du Match
12 - 2020-10-0880Sharks2Flames4WSommaire du Match
14 - 2020-10-1096Rampage1Flames2WXSommaire du Match
16 - 2020-10-12100Flames1Monarchs3LSommaire du Match
18 - 2020-10-14117Admirals4Flames3LXXSommaire du Match
20 - 2020-10-16123Flames2Sharks1WSommaire du Match
21 - 2020-10-17131Flames5Admirals3WSommaire du Match
23 - 2020-10-19147Moose1Flames3WSommaire du Match
24 - 2020-10-20160Flames2Moose3LXXSommaire du Match
26 - 2020-10-22172Wolf Pack1Flames2WSommaire du Match
27 - 2020-10-23182Monsters0Flames3WSommaire du Match
28 - 2020-10-24193Flames2Condors1WSommaire du Match
30 - 2020-10-26201Flames5Soldiers3WSommaire du Match
32 - 2020-10-28210Admirals1Flames2WXXSommaire du Match
34 - 2020-10-30220Flames0Wolves3LSommaire du Match
36 - 2020-11-01232Wolf Pack3Flames1LSommaire du Match
38 - 2020-11-03247Flames1Sharks3LSommaire du Match
40 - 2020-11-05254Flames2Condors0WSommaire du Match
42 - 2020-11-07265Admirals1Flames3WSommaire du Match
44 - 2020-11-09279Monarchs2Flames3WXXSommaire du Match
45 - 2020-11-10293Bruins3Flames4WSommaire du Match
46 - 2020-11-11300Flames3Admirals1WSommaire du Match
47 - 2020-11-12306Flames0Sharks1LSommaire du Match
49 - 2020-11-14320Flames4IceHogs2WSommaire du Match
50 - 2020-11-15326Stars0Flames2WSommaire du Match
51 - 2020-11-16341Senators2Flames5WSommaire du Match
52 - 2020-11-17351Flames3Soldiers4LXXSommaire du Match
54 - 2020-11-19361Flames0Penguins1LSommaire du Match
55 - 2020-11-20371Monarchs5Flames2LSommaire du Match
56 - 2020-11-21387Condors3Flames5WSommaire du Match
57 - 2020-11-22394Flames2Moose1WSommaire du Match
58 - 2020-11-23406Flames1Moose3LSommaire du Match
60 - 2020-11-25416Moose1Flames2WXXSommaire du Match
62 - 2020-11-27431Phantoms3Flames4WXSommaire du Match
63 - 2020-11-28442Flames5Wolves3WSommaire du Match
64 - 2020-11-29451Flames1Griffins0WSommaire du Match
65 - 2020-11-30458Flames1Monarchs5LSommaire du Match
67 - 2020-12-02468Griffins2Flames4WSommaire du Match
68 - 2020-12-03483Rampage2Flames0LSommaire du Match
70 - 2020-12-05494Flames2Crunch3LXSommaire du Match
71 - 2020-12-06504Flames1Sound Tigers3LSommaire du Match
72 - 2020-12-07509Wolf Pack2Flames0LSommaire du Match
74 - 2020-12-09526Flames2Sharks3LXXSommaire du Match
75 - 2020-12-10531Moose2Flames1LSommaire du Match
77 - 2020-12-12548Moose3Flames2LSommaire du Match
78 - 2020-12-13555Flames3Monsters2WSommaire du Match
79 - 2020-12-14568Marlies-Flames-
80 - 2020-12-15579Flames-Marlies-
82 - 2020-12-17587Crunch-Flames-
84 - 2020-12-19600Flames-Rocket-
86 - 2020-12-21611Admirals-Flames-
87 - 2020-12-22624Flames-Phantoms-
88 - 2020-12-23634Monsters-Flames-
91 - 2020-12-26648Flames-Wolf Pack-
92 - 2020-12-27656Soldiers-Flames-
93 - 2020-12-28670Flames-Monarchs-
94 - 2020-12-29679Monarchs-Flames-
95 - 2020-12-30687Flames-Admirals-
96 - 2020-12-31700Flames-Senators-
97 - 2021-01-01704Wolves-Flames-
99 - 2021-01-03721Rocket-Flames-
100 - 2021-01-04732Flames-Condors-
102 - 2021-01-06742Flames-Admirals-
103 - 2021-01-07750IceHogs-Flames-
104 - 2021-01-08766Stars-Flames-
105 - 2021-01-09774Flames-Stars-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
107 - 2021-01-11789Sound Tigers-Flames-
109 - 2021-01-13801Flames-IceHogs-
110 - 2021-01-14810Penguins-Flames-
112 - 2021-01-16825Sharks-Flames-
113 - 2021-01-17831Flames-Monarchs-
115 - 2021-01-19847Flames-Bruins-
116 - 2021-01-20856Sharks-Flames-
118 - 2021-01-22872Condors-Flames-
119 - 2021-01-23879Flames-Rampage-
121 - 2021-01-25892Condors-Flames-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
16 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,593,475$ 2,409,970$ 2,133,637$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,492,668$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 46 33,548$ 1,543,208$




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