Comets

GP: 5 | W: 5 | L: 0 | OTL: 0 | P: 10
GF: 28 | GA: 2 | PP%: 15.79% | PK%: 100.00%
DG: Francis Lagace | Morale : 57 | Moyenne d'Équipe : 62
Prochain matchs #63 vs Americans
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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
1Alexandre GrenierX100.007238845689939155595553595475685358610
2Austin WagnerX100.008340896274677261556264566163625758610
3Steven FogartyX100.006236905785787156625857595571666258600
4Garrett Pilon (R)X100.005835935972949258625753565262636455600
5John McCarronX100.007337875887746957615756605773675855600
6Justin ScottX100.006439825678939055565354565567646158590
7Tobias LindbergX100.007237895586928854525451575367646058590
8Nolan Stevens (R)X100.006235935580918754625353565465636255590
9Dalton Smith (R)X100.006845655482888253585452565373676655580
10Tyler RandellX100.006341775477827653545251545275685758570
11Chase Pearson (R)X100.006235935478706753615254555363626355560
12Fredrik ClaessonX100.008342826577835863306756725373675658660
13Cale Fleury (R)X100.006636906278918760305956585561637155630
14Dennis Cholowski (R)X100.005937876876826967307165565261638255630
15Yannick WeberX100.007338856372707562306458614779715158630
16Philip SamuelssonX100.006436905479939052305351544575685658610
17Erik Brannstrom (R)X100.005437886465877363306258595460628655610
18Mark FriedmanX100.005437895969847358305653554567646258590
Rayé
MOYENNE D'ÉQUIPE100.00663886597884785747585558536865635760
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
1Jared Coreau100.00728078927170727170727175814558730
2Kasimir Kaskisuo100.00757472837473757473757471755158730
Rayé
1Hunter Miska100.00766563727574767574767567714845710
MOYENNE D'ÉQUIPE100.0074737182737274737274737176485472
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Luke Richardson68676563757075CAN5052,500,000$


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
1Garrett PilonComets (Van)C55510900182561220.00%010621.38011716000091067.39%9200001.8700000012
2Yannick WeberComets (Van)D5010101360828460.00%610020.12000414000016000.00%000001.9900000020
3Dennis CholowskiComets (Van)D52791300201341015.38%510320.74000614000019200.00%000001.7400000101
4Cale FleuryComets (Van)D51675004490911.11%211623.24112418000020000.00%000001.2000000000
5John McCarronComets (Van)RW516794061116129.09%09519.18011216000000050.00%400001.4600000000
6Alexandre GrenierComets (Van)RW5505121001052051525.00%113226.591011160002181072.09%4300010.7500000100
7Austin WagnerComets (Van)LW532596010122591212.00%111022.150000160001150053.33%1500000.9000000010
8Justin ScottComets (Van)C5415520271451528.57%06312.7900000000000079.03%6200001.5600000000
9Fredrik ClaessonComets (Van)D5134640181018245.56%512124.341121018000018000.00%000000.6600000100
10Steven FogartyComets (Van)C51347002894211.11%16513.01000116000090073.68%7600001.2300000001
11Tobias LindbergComets (Van)RW50335403515470.00%07414.99000000000120070.00%1000000.8000000000
12Dalton SmithComets (Van)LW53039100160182816.67%010120.360002160000410100.00%200010.5900000100
13Philip SamuelssonComets (Van)D5022420603110.00%27114.330000000000000.00%000000.5600000000
14Erik BrannstromComets (Van)D5022400453030.00%37615.310000000005000.00%000000.5200000000
15Nolan StevensComets (Van)C52022000282525.00%1438.7400000000000071.43%4900000.9100000010
16Mark FriedmanComets (Van)D5011100001100.00%1102.040000000001000.00%000001.9600000000
17Chase PearsonComets (Van)C5000000010010.00%0112.3000000000050075.00%400000.0000000000
18Tyler RandellComets (Van)RW5000220315330.00%0438.74000000000000100.00%200000.0000000000
Stats d'équipe Total ou en Moyenne9028517911550095712055812513.66%28145116.133473716400031595071.59%35900021.0900000454
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
1Jared CoreauComets (Van)55000.9750.40300032790000.000050101
Stats d'équipe Total ou en Moyenne55000.9750.40300032790000.000050101


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
Alexandre GrenierComets (Van)RW271991-09-05No200 Lbs6 ft5NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Austin WagnerComets (Van)LW221997-06-23No185 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Cale FleuryComets (Van)D201998-10-19Yes201 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Chase PearsonComets (Van)C211997-08-23Yes189 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Dalton SmithComets (Van)LW271992-06-30Yes206 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Dennis CholowskiComets (Van)D211998-02-15Yes195 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Erik BrannstromComets (Van)D191999-09-02Yes173 Lbs5 ft10NoNoNo1Contrat d'EntréePro & Farm0$0$NoLien
Fredrik ClaessonComets (Van)D261992-11-24No196 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm1,000,000$0$0$NoLien
Garrett PilonComets (Van)C211998-04-13Yes188 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Hunter MiskaComets (Van)G231995-07-07No175 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Jared CoreauComets (Van)G271991-11-05No214 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
John McCarronComets (Van)RW271992-04-16No219 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Justin ScottComets (Van)C231995-08-13No202 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Kasimir KaskisuoComets (Van)G251993-10-02No196 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Mark FriedmanComets (Van)D231995-12-25No185 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Nolan StevensComets (Van)C221996-07-22Yes183 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Philip SamuelssonComets (Van)D271991-07-26No194 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Steven FogartyComets (Van)C261993-04-19No210 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Tobias LindbergComets (Van)RW231995-07-22No215 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Tyler RandellComets (Van)RW281991-06-15No198 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm300,000$0$0$NoLien
Yannick WeberComets (Van)D301988-09-23No200 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2124.19196 Lbs6 ft22.57378,571$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Austin WagnerSteven FogartyAlexandre Grenier40122
2Dalton SmithGarrett PilonJohn McCarron30122
3Alexandre GrenierJustin ScottTobias Lindberg20122
4Austin WagnerNolan StevensTyler Randell10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Fredrik ClaessonCale Fleury40122
2Dennis CholowskiYannick Weber30122
3Philip SamuelssonErik Brannstrom20122
4Mark FriedmanFredrik Claesson10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Austin WagnerSteven FogartyAlexandre Grenier60122
2Dalton SmithGarrett PilonJohn McCarron40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Fredrik ClaessonCale Fleury60122
2Dennis CholowskiYannick Weber40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Alexandre GrenierAustin Wagner60122
2Steven FogartyGarrett Pilon40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Fredrik ClaessonCale Fleury60122
2Dennis CholowskiYannick Weber40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Alexandre Grenier60122Fredrik ClaessonCale Fleury60122
2Austin Wagner40122Dennis CholowskiYannick Weber40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Alexandre GrenierAustin Wagner60122
2Steven FogartyGarrett Pilon40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Fredrik ClaessonCale Fleury60122
2Dennis CholowskiYannick Weber40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Austin WagnerSteven FogartyAlexandre GrenierFredrik ClaessonCale Fleury
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Austin WagnerSteven FogartyAlexandre GrenierFredrik ClaessonCale Fleury
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Chase Pearson, Justin Scott, Tobias LindbergChase Pearson, Justin ScottTobias Lindberg
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Philip Samuelsson, Erik Brannstrom, Mark FriedmanPhilip SamuelssonErik Brannstrom, Mark Friedman
Tirs de Pénalité
Alexandre Grenier, Austin Wagner, Steven Fogarty, Garrett Pilon, John McCarron
Gardien
#1 : Jared Coreau, #2 : Kasimir Kaskisuo


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
1Checkers11000000808110000008080000000000021.000814220112511046566188097610400.00%30100.00%011716969.23%8010874.07%608273.17%17313471255433
2Marlies33000000172151100000071622000000101961.0001732490112511013656618805418367610220.00%180100.00%011716969.23%8010874.07%608273.17%17313471255433
3Senators11000000303110000003030000000000021.00035801125110235661880163895120.00%30100.00%011716969.23%8010874.07%608273.17%17313471255433
Total55000000282263300000018117220000001019101.0002851790312511020556618807928509519315.79%240100.00%011716969.23%8010874.07%608273.17%17313471255433
_Since Last GM Reset55000000282263300000018117220000001019101.0002851790312511020556618807928509519315.79%240100.00%011716969.23%8010874.07%608273.17%17313471255433
_Vs Conference4400000025223220000001511422000000101981.0002546710212511018256618806325428614214.29%210100.00%011716969.23%8010874.07%608273.17%17313471255433

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
510W52851792057928509503
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
5500000282
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3300000181
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2200000101
Derniers 10 Matchs
WLOTWOTL SOWSOL
500000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
19315.79%240100.00%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
5661880125110
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
11716969.23%8010874.07%608273.17%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
17313471255433


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
3 - 2019-09-041Marlies1Comets7WSommaire du Match
4 - 2019-09-0512Senators0Comets3WSommaire du Match
10 - 2019-09-1133Checkers0Comets8WSommaire du Match
11 - 2019-09-1245Comets3Marlies0WSommaire du Match
12 - 2019-09-1360Comets7Marlies1WSommaire du Match
15 - 2019-09-1663Americans-Comets-
17 - 2019-09-1872Monsters-Comets-
18 - 2019-09-1985Comets-Crunch-
22 - 2019-09-23104Checkers-Comets-
24 - 2019-09-25111Comets-Americans-
31 - 2019-10-02147Comets-Rocket-
32 - 2019-10-03153Comets-Rocket-
36 - 2019-10-07176Rocket-Comets-
38 - 2019-10-09181Wolf Pack-Comets-
39 - 2019-10-10199Comets-Devils-
43 - 2019-10-14218Comets-Senators-
45 - 2019-10-16224Crunch-Comets-
46 - 2019-10-17237Comets-Wolf Pack-
50 - 2019-10-21259Rocket-Comets-
52 - 2019-10-23270Comets-Americans-
53 - 2019-10-24279Senators-Comets-
57 - 2019-10-28304Comets-Devils-
59 - 2019-10-30309Comets-Senators-
60 - 2019-10-31319Comets-Rocket-
64 - 2019-11-04344Comets-Americans-
66 - 2019-11-06349Thunderbirds-Comets-
67 - 2019-11-07370Comets-Devils-
71 - 2019-11-11383Bruins-Comets-
73 - 2019-11-13391Devils-Comets-
75 - 2019-11-15415Comets-Checkers-
77 - 2019-11-17423Comets-Checkers-
80 - 2019-11-20440Comets-Thunderbirds-
81 - 2019-11-21458Devils-Comets-
86 - 2019-11-26472Devils-Comets-
87 - 2019-11-27476Comets-Crunch-
88 - 2019-11-28490Americans-Comets-
92 - 2019-12-02511Crunch-Comets-
95 - 2019-12-05531Comets-Monsters-
96 - 2019-12-06545Comets-Monsters-
99 - 2019-12-09552Comets-Marlies-
101 - 2019-12-11562Sound Tigers-Comets-
102 - 2019-12-12577Crunch-Comets-
106 - 2019-12-16596Crunch-Comets-
108 - 2019-12-18606Devils-Comets-
109 - 2019-12-19621Senators-Comets-
115 - 2019-12-25661Comets-Americans-
122 - 2020-01-01685Comets-Crunch-
123 - 2020-01-02704Comets-Thunderbirds-
129 - 2020-01-08723Phantoms-Comets-
130 - 2020-01-09740Americans-Comets-
131 - 2020-01-10748Comets-Sound Tigers-
134 - 2020-01-13764Rocket-Comets-
137 - 2020-01-16787Comets-Penguins-
138 - 2020-01-17799Monsters-Comets-
143 - 2020-01-22818Americans-Comets-
144 - 2020-01-23835Comets-Devils-
148 - 2020-01-27852Americans-Comets-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29857Bears-Comets-
151 - 2020-01-30875Comets-Phantoms-
155 - 2020-02-03890Crunch-Comets-
157 - 2020-02-05897Comets-Crunch-
158 - 2020-02-06910Comets-Rocket-
162 - 2020-02-10938Comets-Americans-
164 - 2020-02-12944Thunderbirds-Comets-
165 - 2020-02-13957Wolf Pack-Comets-
169 - 2020-02-17979Comets-Senators-
171 - 2020-02-19984Rocket-Comets-
172 - 2020-02-20997Comets-Crunch-
178 - 2020-02-261029Marlies-Comets-
179 - 2020-02-271043Comets-Crunch-
185 - 2020-03-041074Marlies-Comets-
186 - 2020-03-051088Comets-Wolf Pack-
187 - 2020-03-061101Comets-Bruins-
192 - 2020-03-111116Penguins-Comets-
193 - 2020-03-121129Comets-Bears-
194 - 2020-03-131147Crunch-Comets-



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
35 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
172,848$ 79,500$ 22,180$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 5,330$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 181 13,296$ 2,406,576$




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
1455000000282263300000018117220000001019102851790312511020556618807928509519315.79%240100.00%011716969.23%8010874.07%608273.17%17313471255433
Total Saison Régulière55000000282263300000018117220000001019102851790312511020556618807928509519315.79%240100.00%011716969.23%8010874.07%608273.17%17313471255433