Comets

GP: 28 | W: 9 | L: 17 | OTL: 2 | P: 20
GF: 74 | GA: 99 | PP%: 15.23% | PK%: 79.87%
DG: Francis Lagace | Morale : 40 | Moyenne d'Équipe : 59
Prochain matchs #391 vs Devils
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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
1Andrew AgozzinoX100.00605574736763696150606060557371141610
2Steven FogartyX100.00605565627975696050606060555050148590
3Chris BourqueX100.00595567676159735950585855557374147590
4Rod PelleyX100.00775569627568695550555555556465157580
5Justin Scott (R)X100.00735569627969695550555555555050149570
6Mitch MorozX100.00745569637973625550555555555050147570
7Mitchell HeardX100.00595559627569545550555558555050157560
8Tyler RandellX100.00595562647468645550555559555050147560
9Alexandre GrenierX100.00555555555555555550555555557574148540
10Kevin Lynch (R)X100.00565555555556555550555555555050157530
11Tobias LindbergX100.00565555555555555550555555555050144530
12Fredrik ClaessonX100.00965578747977677025636179557473157710
13Jan KostalekX100.00595555605555655525555555555353147540
14Mat ClarkX100.00555555605555635525555555555353157540
15William Wrenn (R)X100.00575555605555615525555555555353147540
16Philip SamuelssonX100.00555555605555665525555555555353147540
Rayé
MOYENNE D'ÉQUIPE100.0063556262666364574256565855585715057
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
1Jeff Glass100.0079707280807071788890556967157740
2Kasimir Kaskisuo100.0075635776717171737977557068157700
Rayé
1Jared Coreau100.0056807089656559775968557069122670
MOYENNE D'ÉQUIPE100.007071668272696776757855706814570
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Darryl Sutter50836377896452CAN5936,400,000$


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
1Steven FogartyComets (Van)C28111829-9195475612024859.17%1762822.461910271050001131052.70%22200000.9200001221
2Andrew AgozzinoComets (Van)LW28111526-32810349811222509.82%864122.917292510102241132052.56%62600000.8103011122
3Justin ScottComets (Van)C28101323-942101004011236938.93%660721.70639421190001740050.00%11600000.7602002230
4Chris BourqueComets (Van)LW28914231220325080265811.25%860321.54178199930361102065.91%4400010.7623000031
5Alexandre GrenierComets (Van)RW2861622-46410913551164411.76%4060821.72381132117000084000.00%000000.7200001011
6William WrennComets (Van)D2851015-3240583441132612.20%3054219.3624627100000010100100.00%100000.5500000001
7Mitch MorozComets (Van)LW286612-518048448117477.41%1237213.29000000001722158.06%6200000.6400000204
8Tobias LindbergComets (Van)RW286511-7435453450154012.00%849917.8323514102000000248.18%27400000.4400001000
9Philip SamuelssonComets (Van)D282810-426034332915176.90%2950918.1912321100000074000.00%000000.3900000100
10Jan KostalekComets (Van)D28268-868054271710411.76%4345416.2200000011161000.00%000000.3500000000
11Tyler RandellComets (Van)RW28224-318027163510285.71%52187.8000000000000071.43%700000.3700000000
Stats d'équipe Total ou en Moyenne30870113183-54372405704677282044929.62%206568418.46233861207846336147067352.29%135200010.642801681110
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
Stats d'équipe Total ou en Moyenne0.0000.0000.000


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 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
Alexandre GrenierComets (Van)RW251991-09-04No200 Lbs6 ft5NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Andrew AgozzinoComets (Van)LW261991-01-02No187 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Chris BourqueComets (Van)LW301986-01-29No174 Lbs5 ft8NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Fredrik ClaessonComets (Van)D241992-11-24No209 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jan KostalekComets (Van)D211995-02-17No181 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Jared CoreauComets (Van)G251991-11-05No235 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jeff GlassComets (Van)G311985-11-18No206 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm750,000$0$0$No
Justin ScottComets (Van)C211995-08-13Yes201 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Kasimir KaskisuoComets (Van)G231993-10-02No201 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Kevin LynchComets (Van)C251991-04-23Yes205 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Mat ClarkComets (Van)D261990-10-16No225 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Mitch MorozComets (Van)LW221994-05-02No214 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
Mitchell HeardComets (Van)C241992-03-11No200 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Philip SamuelssonComets (Van)D251991-07-25No194 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Rod PelleyComets (Van)C321984-08-31No200 Lbs5 ft11NoNoNo4Sans RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Steven FogartyComets (Van)C231993-04-19No212 Lbs6 ft3NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Tobias LindbergComets (Van)RW211995-07-22No201 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Tyler RandellComets (Van)RW251991-06-14No197 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
William WrennComets (Van)D251991-03-16Yes209 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1924.95203 Lbs6 ft11.79323,684$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris BourqueAndrew AgozzinoTobias Lindberg40122
2Justin ScottSteven Fogarty30122
3Mitch MorozTobias LindbergAndrew Agozzino20122
4Tyler RandellSteven FogartyChris Bourque10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alexandre Grenier40122
2William WrennPhilip Samuelsson30122
3Jan Kostalek20122
4Alexandre Grenier10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris BourqueAndrew AgozzinoTobias Lindberg60122
2Justin ScottSteven Fogarty40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alexandre Grenier60122
2William WrennPhilip Samuelsson40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Andrew AgozzinoChris Bourque60122
2Justin Scott40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alexandre Grenier60122
2William WrennPhilip Samuelsson40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Andrew Agozzino60122Alexandre Grenier60122
2Chris Bourque40122William WrennPhilip Samuelsson40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Andrew AgozzinoChris Bourque60122
2Justin Scott40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Alexandre Grenier60122
2William WrennPhilip Samuelsson40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris BourqueAndrew AgozzinoTobias LindbergAlexandre Grenier
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris BourqueAndrew AgozzinoTobias LindbergAlexandre Grenier
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , Mitch Moroz, Mitch Moroz
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Jan Kostalek, William WrennJan Kostalek, William Wrenn
Tirs de Pénalité
Andrew Agozzino, Chris Bourque, Justin Scott, , Tobias Lindberg
Gardien
#1 : , #2 :


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
1Americans40400000216-141010000004-430300000212-1000.00023500282123265262254239191163160802428.33%30583.33%038687044.37%35873748.58%20142547.29%651453714202330159
2Bruins1010000035-21010000035-20000000000000.000347002821232282622542391931812208225.00%6433.33%038687044.37%35873748.58%20142547.29%651453714202330159
3Checkers2200000012392200000012390000000000041.00012223400282123210726225423919482025555120.00%40100.00%038687044.37%35873748.58%20142547.29%651453714202330159
4Crunch2020000069-31010000034-11010000035-200.000691500282123235262254239196319364814214.29%17288.24%138687044.37%35873748.58%20142547.29%651453714202330159
5Devils30300000315-120000000000030300000315-1200.00034700282123255262254239198623314217211.76%13284.62%038687044.37%35873748.58%20142547.29%651453714202330159
6Marlies33000000187111100000063322000000124861.000183149002821232139262254239197320337814214.29%15380.00%138687044.37%35873748.58%20142547.29%651453714202330159
7Monsters1010000003-31010000003-30000000000000.00000000282123216262254239192251916700.00%7185.71%038687044.37%35873748.58%20142547.29%651453714202330159
8Rocket50300011816-82010000125-330200010611-530.300813210028212321162622542391911743591162528.00%18477.78%038687044.37%35873748.58%20142547.29%651453714202330159
9Senators41300000916-720200000310-72110000066020.25091625002821232912622542391910935547925728.00%22672.73%038687044.37%35873748.58%20142547.29%651453714202330159
10Thunderbirds1000010034-11000010034-10000000000010.50035800282123228262254239193312372711100.00%110100.00%038687044.37%35873748.58%20142547.29%651453714202330159
Total28717001217499-251347001013742-515310000203757-20200.35774124198002821232766262254239197312323845921512315.23%1493079.87%338687044.37%35873748.58%20142547.29%651453714202330159
12Wolf Pack210000101055110000005141000001054141.00010172700282123286262254239193316183111218.18%6350.00%138687044.37%35873748.58%20142547.29%651453714202330159
_Since Last GM Reset28717001217499-251347001013742-515310000203757-20200.35774124198002821232766262254239197312323845921512315.23%1493079.87%338687044.37%35873748.58%20142547.29%651453714202330159
_Vs Conference1557001114346-37320010123194825000102027-7140.46743741170028212324552622542391938712621435669811.59%781284.62%138687044.37%35873748.58%20142547.29%651453714202330159

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2820L27412419876673123238459200
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2871701217499
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
134701013742
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1531000203757
Derniers 10 Matchs
WLOTWOTL SOWSOL
180100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1512315.23%1493079.87%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
262254239192821232
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
38687044.37%35873748.58%20142547.29%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
651453714202330159


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 - 2018-09-071Marlies3Comets6WSommaire du Match
4 - 2018-09-0812Senators5Comets1LSommaire du Match
10 - 2018-09-1433Checkers2Comets7WSommaire du Match
11 - 2018-09-1545Comets6Marlies1WSommaire du Match
12 - 2018-09-1660Comets6Marlies3WSommaire du Match
15 - 2018-09-1963Americans4Comets0LSommaire du Match
17 - 2018-09-2172Monsters3Comets0LSommaire du Match
18 - 2018-09-2285Comets3Crunch5LSommaire du Match
22 - 2018-09-26104Checkers1Comets5WSommaire du Match
24 - 2018-09-28111Comets1Americans3LSommaire du Match
31 - 2018-10-05147Comets2Rocket5LSommaire du Match
32 - 2018-10-06153Comets3Rocket2WXXSommaire du Match
36 - 2018-10-10176Rocket2Comets1LXXSommaire du Match
38 - 2018-10-12181Wolf Pack1Comets5WSommaire du Match
39 - 2018-10-13199Comets1Devils4LSommaire du Match
43 - 2018-10-17218Comets3Senators5LSommaire du Match
45 - 2018-10-19224Crunch4Comets3LSommaire du Match
46 - 2018-10-20237Comets5Wolf Pack4WXXSommaire du Match
50 - 2018-10-24259Rocket3Comets1LSommaire du Match
52 - 2018-10-26270Comets0Americans6LSommaire du Match
53 - 2018-10-27279Senators5Comets2LSommaire du Match
57 - 2018-10-31304Comets2Devils6LSommaire du Match
59 - 2018-11-02309Comets3Senators1WSommaire du Match
60 - 2018-11-03319Comets1Rocket4LSommaire du Match
64 - 2018-11-07344Comets1Americans3LSommaire du Match
66 - 2018-11-09349Thunderbirds4Comets3LXSommaire du Match
67 - 2018-11-10370Comets0Devils5LSommaire du Match
71 - 2018-11-14383Bruins5Comets3LSommaire du Match
73 - 2018-11-16391Devils-Comets-
75 - 2018-11-18415Comets-Checkers-
77 - 2018-11-20423Comets-Checkers-
80 - 2018-11-23440Comets-Thunderbirds-
81 - 2018-11-24458Devils-Comets-
86 - 2018-11-29472Devils-Comets-
87 - 2018-11-30476Comets-Crunch-
88 - 2018-12-01490Americans-Comets-
92 - 2018-12-05511Crunch-Comets-
95 - 2018-12-08531Comets-Monsters-
96 - 2018-12-09545Comets-Monsters-
99 - 2018-12-12552Comets-Marlies-
101 - 2018-12-14562Sound Tigers-Comets-
102 - 2018-12-15577Crunch-Comets-
106 - 2018-12-19596Crunch-Comets-
108 - 2018-12-21606Devils-Comets-
109 - 2018-12-22621Senators-Comets-
115 - 2018-12-28661Comets-Americans-
122 - 2019-01-04685Comets-Crunch-
123 - 2019-01-05704Comets-Thunderbirds-
129 - 2019-01-11723Phantoms-Comets-
130 - 2019-01-12740Americans-Comets-
131 - 2019-01-13748Comets-Sound Tigers-
134 - 2019-01-16764Rocket-Comets-
137 - 2019-01-19787Comets-Penguins-
138 - 2019-01-20799Monsters-Comets-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25818Americans-Comets-
144 - 2019-01-26835Comets-Devils-
148 - 2019-01-30852Americans-Comets-
150 - 2019-02-01857Bears-Comets-
151 - 2019-02-02875Comets-Phantoms-
155 - 2019-02-06890Crunch-Comets-
157 - 2019-02-08897Comets-Crunch-
158 - 2019-02-09910Comets-Rocket-
162 - 2019-02-13938Comets-Americans-
164 - 2019-02-15944Thunderbirds-Comets-
165 - 2019-02-16957Wolf Pack-Comets-
169 - 2019-02-20979Comets-Senators-
171 - 2019-02-22984Rocket-Comets-
172 - 2019-02-23997Comets-Crunch-
178 - 2019-03-011029Marlies-Comets-
179 - 2019-03-021043Comets-Crunch-
185 - 2019-03-081074Marlies-Comets-
186 - 2019-03-091088Comets-Wolf Pack-
187 - 2019-03-101101Comets-Bruins-
192 - 2019-03-151116Penguins-Comets-
193 - 2019-03-161129Comets-Bears-
194 - 2019-03-171147Crunch-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
25 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,398,104$ 61,500$ 50,680$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 22,824$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 33,307$ 4,063,454$




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
1328717001217499-251347001013742-515310000203757-202074124198002821232766262254239197312323845921512315.23%1493079.87%338687044.37%35873748.58%20142547.29%651453714202330159
Total Saison Régulière28717001217499-251347001013742-515310000203757-202074124198002821232766262254239197312323845921512315.23%1493079.87%338687044.37%35873748.58%20142547.29%651453714202330159