Connexion

Ice Dogs
GP: 0 | W: 0 | L: 0
GF: 0 | GA: 0 | PP%: 0% | PK%: 0%
DG: Daniel Pigeon | Morale : 40 | Moyenne d’équipe : 63
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Meneurs d'équipe

Statistiques d’équipe
Informations de l'équipe

Directeur généralDaniel Pigeon
DivisionDivision 2
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance
Billets de saison0


Informations de la formation

Équipe Pro26
Équipe Mineure22
Limite contact 48 / 250
Espoirs28


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
1Paul ByronX100.008650907550605557555264685389670406903424,000,000$
2Lane PedersonX100.00896575736677426365576659556465040680261735,000$
3Jasper WeatherbyX100.00695288738360556264536158495861040660251842,500$
4Alexander SteenX100.004745558069605564395853553052750406403933,500,000$
5Garrett PilonX100.00545090736560555556506550366062040630252750,000$
6Brendan PerliniX100.00615188737860555545505850447057040620275750,000$
7Mikhail GrigorenkoX100.004745557377605559345451523052650406102931,200,000$
8Kole SherwoodX100.00775090737260555532505050306552040610261735,000$
9Markus HannikainenX100.00474555737060555935555152305266040600302750,000$
10Arnaud Durandeau (R)X100.0054507667647830563650505431585504060N0245750,000$
11Sean MaloneX100.00474555736660555933545052305264040600284750,000$
12Markus GranlundX100.004745557363605559355551523052660406003021,300,000$
13Zachary SenyshynX100.00665063737160555531505050306551040590261700,000$
14Jayce HawrylukX100.00474555736360555833545051305263040590275750,000$
15Andrej SekeraX100.005952857567605555355457614899660406703724,500,000$
16Jacob Bernard-DockerX100.00635979726676375540555164336158040660231925,000$
17Ronnie AttardX100.00625090677882306036505066306056040660241842,500$
18Slater KoekkoekX100.00695278737260555535615058457663040660293850,000$
19Jay BouwmeesterX100.004745558080605565395853553052760406504023,250,000$
20Mac Hollowell (R)X100.00505081725278305536645059315963040630252750,000$
21Niklas HjalmarssonX100.004745557175605563375752543052720406303626,000,000$
22Aaron NessX100.00474555735860556136565153305269040610332650,000$
23Nelson NogierX100.00474555737160555833545051305263040600275750,000$
24Ryan MurphyX100.00474555736160555935555152305266040600302825,000$
Rayé
1Cameron HillisX100.00425090735360555542505050305651065570231842,500$
MOYENNE D’ÉQUIPE100.0057497173686451584054535535606304163
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 SPÂgeContratSalaire
1Joseph Woll100.0070449283825965666575545964040690252750,000$
Rayé
MOYENNE D’ÉQUIPE100.007044928382596566657554596404069
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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 Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Type Salaire actuel Salaire restantPlafond salarial Non Activé 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 10Non-échange Année 2Non-échange Année 3Non-échange Année 4Non-échange Année 5Non-échange Année 6Non-échange Année 7Non-échange Année 8Non-échange Année 9Non-échange Année 10Lien
Aaron NessIce Dogs (DAY)D331990-05-18No184 Lbs5 ft10NoNoN/ANoNo2Pro & Farm650,000$650,000$0$0$No650,000$--------No--------
Alexander SteenIce Dogs (DAY)LW391984-03-01No211 Lbs6 ft0NoNoN/ANoNo3Pro & Farm3,500,000$3,500,000$0$0$No3,500,000$3,500,000$-------NoNo-------
Andrej SekeraIce Dogs (DAY)D371986-06-08No200 Lbs6 ft0NoNoN/ANoNo2Pro & Farm4,500,000$4,500,000$0$0$No4,500,000$--------No--------
Arnaud DurandeauIce Dogs (DAY)LW241999-01-14Yes185 Lbs6 ft0YesNoN/ANoNo5Pro & Farm750,000$750,000$0$0$No750,000$750,000$750,000$750,000$-----YesYesYesYes-----
Brendan PerliniIce Dogs (DAY)LW271996-04-27No211 Lbs6 ft3NoNoN/ANoNo5Pro & Farm750,000$750,000$0$0$No750,000$750,000$750,000$750,000$-----NoNoNoNo-----
Cameron HillisIce Dogs (DAY)C232000-06-24No175 Lbs5 ft9NoNoN/ANoNo1Pro & Farm842,500$842,500$0$0$No------------------
Garrett PilonIce Dogs (DAY)C251998-04-13No191 Lbs6 ft0NoNoN/ANoNo2Pro & Farm750,000$750,000$0$0$No750,000$--------No--------
Jacob Bernard-DockerIce Dogs (DAY)D232000-06-30No190 Lbs6 ft0NoNoN/ANoNo1Pro & Farm925,000$925,000$0$0$No------------------
Jasper WeatherbyIce Dogs (DAY)C251998-01-22No222 Lbs6 ft4NoNoN/ANoNo1Pro & Farm842,500$842,500$0$0$No------------------
Jay BouwmeesterIce Dogs (DAY)D401983-09-27No206 Lbs6 ft4NoNoN/ANoNo2Pro & Farm3,250,000$3,250,000$0$0$No3,250,000$--------No--------
Jayce HawrylukIce Dogs (DAY)C271996-01-01No196 Lbs5 ft11NoNoN/ANoNo5Pro & Farm750,000$750,000$0$0$No750,000$750,000$750,000$750,000$-----NoNoNoNo-----
Joseph WollIce Dogs (DAY)G251998-07-12No203 Lbs6 ft3NoNoN/ANoNo2Pro & Farm750,000$750,000$0$0$No750,000$--------No--------
Kole SherwoodIce Dogs (DAY)RW261997-01-22No212 Lbs6 ft1NoNoN/ANoNo1Pro & Farm735,000$735,000$0$0$No------------------
Lane PedersonIce Dogs (DAY)C261997-08-04No192 Lbs6 ft0NoNoN/ANoNo1Pro & Farm735,000$735,000$0$0$No------------------
Mac HollowellIce Dogs (DAY)D251998-09-26Yes170 Lbs5 ft9NoNoN/ANoNo2Pro & Farm750,000$750,000$0$0$No750,000$--------No--------
Markus GranlundIce Dogs (DAY)RW301993-04-16No180 Lbs6 ft0NoNoN/ANoNo2Pro & Farm1,300,000$1,300,000$0$0$No1,300,000$--------No--------
Markus HannikainenIce Dogs (DAY)LW301993-03-26No200 Lbs6 ft1NoNoN/ANoNo2Pro & Farm750,000$750,000$0$0$No750,000$--------No--------
Mikhail GrigorenkoIce Dogs (DAY)RW291994-05-16No206 Lbs6 ft3NoNoN/ANoNo3Pro & Farm1,200,000$1,200,000$0$0$No1,200,000$1,200,000$-------NoNo-------
Nelson NogierIce Dogs (DAY)D271996-01-01No191 Lbs6 ft2NoNoN/ANoNo5Pro & Farm750,000$750,000$0$0$No750,000$750,000$750,000$750,000$-----NoNoNoNo-----
Niklas HjalmarssonIce Dogs (DAY)D361987-06-06No197 Lbs6 ft3NoNoN/ANoNo2Pro & Farm6,000,000$6,000,000$0$0$No6,000,000$--------No--------
Paul ByronIce Dogs (DAY)LW341989-04-27No158 Lbs5 ft9NoNoN/ANoNo2Pro & Farm4,000,000$4,000,000$0$0$No4,000,000$--------No--------
Ronnie AttardIce Dogs (DAY)D241999-03-20No208 Lbs6 ft3NoNoN/ANoNo1Pro & Farm842,500$842,500$0$0$No------------------
Ryan MurphyIce Dogs (DAY)D301993-03-31No185 Lbs5 ft11NoNoN/ANoNo2Pro & Farm825,000$825,000$0$0$No825,000$--------No--------
Sean MaloneIce Dogs (DAY)C281995-01-01No197 Lbs6 ft0NoNoN/ANoNo4Pro & Farm750,000$750,000$0$0$No750,000$750,000$750,000$------NoNoNo------
Slater KoekkoekIce Dogs (DAY)D291994-02-18No193 Lbs6 ft2NoNoN/ANoNo3Pro & Farm850,000$850,000$0$0$No850,000$850,000$-------NoNo-------
Zachary SenyshynIce Dogs (DAY)LW261997-03-30No205 Lbs6 ft1NoNoN/ANoNo1Pro & Farm700,000$700,000$0$0$No------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2628.77195 Lbs6 ft12.381,478,750$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Markus Granlund34122
230122
3Lane Pederson26122
4Markus Hannikainen10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
134122
230122
326122
4Aaron Ness10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Markus Granlund51122
249122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
151122
249122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
151122
2Markus Granlund49122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
151122
249122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
15112251122
24912249122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
151122
2Markus Granlund49122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
151122
249122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Markus Granlund
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Markus Granlund
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, , Lane Pederson, Lane Pederson
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jacob Bernard-Docker, Ryan Murphy, Jacob Bernard-DockerRyan Murphy,
Tirs de pénalité
, , Markus Granlund, , Lane Pederson
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
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%000%0000%000%000%000000

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
0000000000000
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%000%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%000%000%
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



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets350
Assistance0%0%
Assistance PCT0%0%

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

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 0$ 0$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 0$ 0$




Ice Dogs Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Ice Dogs Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Ice Dogs Statistiques de l'Équipe de Carrière

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

Ice Dogs Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Ice Dogs Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA