Connexion

Comets
GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: MatsLP | Morale : 40 | Moyenne d’équipe : 59
Prochain matchs #12 vs Phantoms
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Comets
0-0-0, 0pts
2022-09-15
Phantoms
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Griffins
0-0-0, 0pts
2022-09-17
Comets
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Gulls
0-0-0, 0pts
2022-09-20
Comets
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Meneurs d'équipe

Statistiques d’équipe
Buts pour
0
0.00 GFG
Tirs pour
0
0.00 Avg
Pourcentage en avantage numérique
0.0%
0 GF
Début de zone offensive
0.0%
Buts contre
0
0.00 GAA
Tirs contre
0
0.00 Avg
Pourcentage en désavantage numérique
0.0%
0 GA
Début de la zone défensive
0.0%
Information d’équipe

Directeur généralMatsLP
EntraîneurJoel Bouchard
DivisionMetropolitan Division
ConférenceEastern Conference
CapitaineLoui Eriksson
Assistant #1Andrew Ladd
Assistant #2Josh Leivo


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison0


Information formation

Équipe Pro30
Équipe Mineure18
Limite contact 48 / 90
Espoirs36


Historique d'équipe

Saison actuelle0-0-0 (0PTS)
Historique106-38-16 (0.663%)
Apparitions séries éliminatoires 2
Historique séries éliminatoires (W-L)14-12
Stanley Cup0


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 moyen
1Andrew Ladd (A)0X100.007751786286836853646263666478860406203621,000,000$
2Loui Eriksson (C)0X100.005140886680807657606757675974830406203711,000,000$
3Sam Steel0X100.005741896679797260756760646053630406102421,000,000$
4Emil Bemstrom0XX100.006643856282745661626364626253630406002312,400,000$
5Jakob Pelletier (R)0X100.00504075627860446540686562635463040590213850,000$
6Rasmus Kupari0X100.007445836084736856646361626153630405902211,200,000$
7Josh Leivo (A)0X100.00574875608360506440676559636874040590292945,000$
8Axel Jonsson-Fjallby0X100.006242816081625560506563636252620405802421,000,000$
9C J Suess0XX100.005943755780604459546462606154640405702821,000,000$
10Joachim Blichfeld0X100.005043755882603961406565626352620405702411,000,000$
11Michal Teply (R)0X100.00504275578260385840646062605262040560212750,000$
12David Gustafsson0X100.00504475568460445946646354625363040560221950,000$
13Ty Smith0X100.00594092677880726820676570635262040640222925,000$
14Tobias Bjornfot0X100.006545955983797364206456725851610406302111,300,000$
15Slater Koekkoek0X100.007243746083683874206856695866720406202821,000,000$
16Ethan Prow0X100.00564176607960567320686568635867040610291750,000$
17Daniil Miromanov0X100.00554677568660517320686565635262040590254750,000$
18Lucas Johansen0X100.005039755979605170206662676155640405902421,000,000$
Rayé
1Emilio Pettersen (R)0X100.00504175577960375640626062605463040550222850,000$
2Jackson Cates0X100.00534377568160435464615761595161040550251925,000$
3Jordan Kawaguchi0X100.005041755778602757606558625951610405502521,000,000$
4Noel Gunler (R)0X100.00503975597860105740626262615261040540213850,000$
5Nathan Legare (R)0X100.00504775518560355340615862595161040540213850,000$
6Olli Juolevi0X100.00614183588070406120605568585262040580241900,000$
7Matthew Hellickson0X100.00503975577860176520625768595563040560241750,000$
8Griffin Mendel (R)0X100.00505075489160106520635668585060040550232750,000$
MOYENNE D’ÉQUIPE100.0057437959826647624164616461566504058
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
1Martin Jones100.0075817887807977818077788374040770
2Akira Schmid (R)100.0062747189656662676663646667040660
Rayé
1Zach Sawchenko100.0059686584646362646360627169040640
2Cale Morris (R)100.0047585584515150525148507370040550
MOYENNE D’ÉQUIPE100.006170678665656366656264737004066
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Joel Bouchard75757575757575CAN488500,000$


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
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


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 restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Akira SchmidComets (NJD)G227/1/2000Yes205 Lbs6 ft5NoNoNo3Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$850,000$Lien
Andrew LaddComets (NJD)LW3612/12/1985No205 Lbs6 ft3NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Axel Jonsson-FjallbyComets (NJD)LW242/10/1998No189 Lbs6 ft1NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
C J SuessComets (NJD)C/LW283/17/1994No190 Lbs5 ft11NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Cale MorrisComets (NJD)G267/1/1996Yes190 Lbs6 ft1NoNoNo0Pro & Farm0$0$NoLien
Daniil Miromanov (contrat à 1 volet)Comets (NJD)D257/11/1997No202 Lbs6 ft4NoNoNo4Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$750,000$750,000$Lien
David GustafssonComets (NJD)C224/11/2000No196 Lbs6 ft2NoNoNo1Pro & Farm950,000$939,947$950,000$939,947$0$0$NoLien
Emil BemstromComets (NJD)C/RW236/1/1999No193 Lbs6 ft0NoNoNo1Pro & Farm2,400,000$2,374,603$2,400,000$2,374,603$0$0$NoLien
Emilio PettersenComets (NJD)LW224/3/2000Yes185 Lbs5 ft10NoNoNo2Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$Lien
Ethan Prow (contrat à 1 volet)Comets (NJD)D2911/17/1992No182 Lbs5 ft11NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Griffin MendelComets (NJD)D232/18/1999Yes220 Lbs6 ft6NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Jackson CatesComets (NJD)C259/26/1997No190 Lbs6 ft0NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Jakob PelletierComets (NJD)LW213/7/2001Yes180 Lbs5 ft10NoNoNo3Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$850,000$Lien
Joachim BlichfeldComets (NJD)RW247/17/1998No190 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$NoLien
Jordan KawaguchiComets (NJD)C255/4/1997No185 Lbs5 ft9NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Josh LeivoComets (NJD)LW295/26/1993No192 Lbs6 ft2NoNoNo2Pro & Farm945,000$935,000$945,000$935,000$0$0$No945,000$Lien
Loui ErikssonComets (NJD)LW377/17/1985No179 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$NoLien
Lucas JohansenComets (NJD)D2411/16/1997No176 Lbs6 ft2NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Martin JonesComets (NJD)G321/10/1990No194 Lbs6 ft4NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Matthew HellicksonComets (NJD)D243/21/1998No175 Lbs6 ft0NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Michal TeplyComets (NJD)RW215/27/2001Yes187 Lbs6 ft3NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Nathan LegareComets (NJD)RW211/11/2001Yes208 Lbs6 ft0NoNoNo3Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$850,000$Lien
Noel GunlerComets (NJD)RW2110/7/2001Yes175 Lbs6 ft1NoNoNo3Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$850,000$Lien
Olli JuoleviComets (NJD)D245/5/1998No182 Lbs6 ft2NoNoNo1Pro & Farm900,000$890,476$900,000$890,476$0$0$NoLien
Rasmus KupariComets (NJD)C223/15/2000No200 Lbs6 ft2NoNoNo1Pro & Farm1,200,000$1,187,302$1,200,000$1,187,302$0$0$NoLien
Sam Steel (contrat à 1 volet)Comets (NJD)C242/3/1998No184 Lbs5 ft11NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Slater KoekkoekComets (NJD)D282/18/1994No193 Lbs6 ft2NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Tobias BjornfotComets (NJD)D214/6/2001No200 Lbs6 ft0NoNoNo1Pro & Farm1,300,000$1,286,243$1,300,000$1,286,243$0$0$NoLien
Ty SmithComets (NJD)D223/24/2000No180 Lbs5 ft11NoNoNo2Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$Lien
Zach SawchenkoComets (NJD)G257/1/1997No185 Lbs6 ft1NoNoNo2Pro & Farm950,000$939,947$950,000$939,947$0$0$No950,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3025.00190 Lbs6 ft11.80949,833$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jakob PelletierSam SteelEmil Bemstrom37023
2Loui ErikssonRasmus KupariJosh Leivo33023
3Axel Jonsson-FjallbyAndrew LaddJoachim Blichfeld20023
4C J SuessDavid GustafssonMichal Teply10023
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ty SmithTobias Bjornfot40023
2Slater KoekkoekEthan Prow30023
3Daniil MiromanovLucas Johansen30023
4Ty SmithSlater Koekkoek0023
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jakob PelletierSam SteelJoachim Blichfeld60005
2Josh LeivoRasmus KupariEmil Bemstrom40005
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ty SmithEthan Prow60005
2Daniil MiromanovLucas Johansen40005
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Andrew LaddAxel Jonsson-Fjallby60140
2Sam SteelLoui Eriksson40140
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tobias BjornfotSlater Koekkoek60140
2Ty SmithEthan Prow40140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Andrew Ladd60140Ty SmithTobias Bjornfot60140
2Sam Steel40140Slater KoekkoekEthan Prow40140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Sam SteelEmil Bemstrom60023
2Andrew LaddLoui Eriksson40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tobias BjornfotTy Smith60023
2Ethan ProwSlater Koekkoek40023
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jakob PelletierSam SteelJosh LeivoTy SmithEthan Prow
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Loui ErikssonAndrew LaddAxel Jonsson-FjallbySlater KoekkoekTobias Bjornfot
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Sam Steel, Andrew Ladd, Rasmus KupariAxel Jonsson-Fjallby, Loui ErikssonEmil Bemstrom
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ty Smith, Tobias Bjornfot, Slater KoekkoekSlater KoekkoekLucas Johansen, Daniil Miromanov
Tirs de pénalité
Joachim Blichfeld, Jakob Pelletier, Josh Leivo, Emil Bemstrom, Andrew Ladd
Gardien
#1 : Martin Jones, #2 : Akira Schmid
Lignes d’attaque personnalisées en prolongation
Sam Steel, Jakob Pelletier, Emil Bemstrom, Andrew Ladd, Rasmus Kupari, Joachim Blichfeld, Joachim Blichfeld, Loui Eriksson, Josh Leivo, Axel Jonsson-Fjallby, David Gustafsson
Lignes de défense personnalisées en prolongation
Ty Smith, Tobias Bjornfot, Slater Koekkoek, Ethan Prow, Daniil Miromanov


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
TotalDomicileVisiteur
# 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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
00N/A0000000000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 matchs
WLOTWOTL SOWSOL
000000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
000.00%000.00%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
00000000
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
000.00%000.00%000.00%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
000000


Derniers matchs 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
7 - 2022-09-1512Comets-Phantoms-
9 - 2022-09-1728Griffins-Comets-
12 - 2022-09-2048Gulls-Comets-
14 - 2022-09-2266Comets-Islanders-
16 - 2022-09-2475Barracuda-Comets-
18 - 2022-09-2693Bears-Comets-
19 - 2022-09-27102Comets-Griffins-
22 - 2022-09-30123Eagles-Comets-
24 - 2022-10-02139Monsters-Comets-
26 - 2022-10-04157Comets-Canucks-
28 - 2022-10-06170Comets-Condors-
30 - 2022-10-08187Comets-Heat-
33 - 2022-10-11197Heat-Comets-
35 - 2022-10-13213Senators-Comets-
37 - 2022-10-15227Roadrunners-Comets-
40 - 2022-10-18249Comets-Rocket-
42 - 2022-10-20264Comets-Marlies-
44 - 2022-10-22274Comets-Senators-
46 - 2022-10-24293Condors-Comets-
48 - 2022-10-26309Marlies-Comets-
50 - 2022-10-28327Comets-Americans-
51 - 2022-10-29336Bears-Comets-
53 - 2022-10-31346Comets-Wolf Pack-
56 - 2022-11-03366Admirals-Comets-
58 - 2022-11-05382Comets-Phantoms-
61 - 2022-11-08403IceHogs-Comets-
64 - 2022-11-11425Islanders-Comets-
67 - 2022-11-14450Comets-Wolf Pack-
68 - 2022-11-15456Stars-Comets-
70 - 2022-11-17473Phantoms-Comets-
72 - 2022-11-19488Checkers-Comets-
75 - 2022-11-22512Comets-Wolves-
76 - 2022-11-23518Comets-Checkers-
78 - 2022-11-25533Bruins-Comets-
83 - 2022-11-30558Bruins-Comets-
85 - 2022-12-02576Comets-Penguins-
87 - 2022-12-04590Wolves-Comets-
90 - 2022-12-07609Comets-Griffins-
91 - 2022-12-08616Thunderbirds-Comets-
93 - 2022-12-10628Wolf Pack-Comets-
96 - 2022-12-13650Comets-Wolves-
99 - 2022-12-16675Comets-Gulls-
100 - 2022-12-17690Comets-Reign-
102 - 2022-12-19697Comets-Barracuda-
105 - 2022-12-22728Comets-Firebirds-
108 - 2022-12-25746Penguins-Comets-
110 - 2022-12-27759Silver Knights-Comets-
112 - 2022-12-29775Comets-Admirals-
113 - 2022-12-30785Comets-Stars-
123 - 2023-01-09810Canucks-Comets-
126 - 2023-01-12824Firebirds-Comets-
128 - 2023-01-14843Comets-Wild-
131 - 2023-01-17857Comets-Monsters-
133 - 2023-01-19874Comets-Thunderbirds-
135 - 2023-01-21886Comets-Penguins-
136 - 2023-01-22900Moose-Comets-
138 - 2023-01-24910Rocket-Comets-
140 - 2023-01-26923Reign-Comets-
142 - 2023-01-28941Phantoms-Comets-
146 - 2023-02-01971Comets-Eagles-
148 - 2023-02-03988Comets-Silver Knights-
150 - 2023-02-051004Comets-Roadrunners-
152 - 2023-02-071015Marlies-Comets-
154 - 2023-02-091029Comets-Bears-
156 - 2023-02-111044Comets-Rocket-
157 - 2023-02-121056Wolves-Comets-
159 - 2023-02-141065Crunch-Comets-
161 - 2023-02-161083Crunch-Comets-
163 - 2023-02-181100Comets-Checkers-
164 - 2023-02-191113Comets-Crunch-
166 - 2023-02-211123Wild-Comets-
169 - 2023-02-241148Comets-Americans-
170 - 2023-02-251160Senators-Comets-
172 - 2023-02-271172Comets-Islanders-
175 - 2023-03-021191Wolf Pack-Comets-
177 - 2023-03-041211Comets-IceHogs-
178 - 2023-03-051222Comets-Moose-
180 - 2023-03-071233Penguins-Comets-
182 - 2023-03-091243Monsters-Comets-
184 - 2023-03-111265Comets-Bruins-
187 - 2023-03-141285Americans-Comets-
189 - 2023-03-161301Comets-Bears-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance0.00%0.00%
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
41 0 - 0.00%0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
27,508$ 2,599,500$ 2,599,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
13,754$ 27,508$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 187 13,754$ 2,571,998$




TotalDomicileVisiteur
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
Saison régulière
118245190464424116873412280324211975444123110140212293291162414146552758105701632071113109698049246878213018661294031.01%451860.00%01017188853.87%812150553.95%565109751.50%1788103015787821605770
118245190464424116873412280324211975444123110140212293291162414146552758105701632071113109698049246878213018661294031.01%451860.00%01017188853.87%812150553.95%565109751.50%1788103015787821605770
Total Saison régulière1649038081288482336146824416064842381508882462202804244186582324828281310414116210140326414222621921960984936156426037322588031.01%903660.00%02034377653.87%1624301053.95%1130219451.50%357720603157156532111540
Séries éliminatoires
1113760000035278633000001213-17430000023149143561962251612260718321418030481146143018337.50%7357.14%018932558.15%15929254.45%9416955.62%312189276120248124
1113760000035278633000001213-17430000023149143561962251612260718321418030481146143018337.50%7357.14%018932558.15%15929254.45%9416955.62%312189276120248124
Total Séries éliminatoires261412000007054161266000002426-214860000046281828701221924410322441214366428360609622922860216637.50%14657.14%037865058.15%31858454.45%18833855.62%625378552240496249