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Crunch
GP: 0 | W: 0 | L: 0
GF: 0 | GA: 0 | PP%: 0% | PK%: 0%
DG: Guillaume Cazes | Morale : 1 | Moyenne d’équipe : 62
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Meneurs d'équipe

Statistiques d’équipe
Informations de l'équipe

Directeur généralGuillaume Cazes
EntraîneurMichel Therrien
DivisionDivision Sud-Est
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance
Billets de saison300


Informations de la formation

Équipe Pro25
Équipe Mineure19
Limite contact 44 / 56
Espoirs21


Historique d'équipe

Saison actuelle0-0
Historique44-31-8 (0.530%)
Apparitions en séries éliminatoires 1
Historique en séries éliminatoires (W-L)7 - 6 (0.538%)
Coupe Stanley0


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
Âge
Contrat
Salaire
1Stefan NoesenXX100.0060419069747080726767736968705746436503211,200,000$
2Mackenzie EntwistleXX100.007145887371738572606869746165486849650252900,000$
3Johan SundstromX100.0057459469737073706671686966635350396403221,100,000$
4Kyle Maclean (R)X100.007250907270707572617172696645456054640251900,000$
5JC LiponXX100.0073698171707570706168716970494753486403121,200,000$
6Antoine MorandX100.006244947268727268717067696048466060630262750,000$
7James SheppardXX100.0069558668726768676563647062716130606303621,000,000$
8Tomas HykaXX100.0057439573696665676361646960494550616103221,000,000$
9Corey TrivinoX100.0060439772716470666562636662464538506003521,000,000$
10Adam MascherinXX100.006245827269666963636265616049456041600261750,000$
11Dominik UherXX100.006546756873646861706162656057524418590321700,000$
12Graham BlackX100.005639877171625564675856686255544350590321700,000$
13Trevor CarrickX100.0077656773717576734573737060605351466503011,300,000$
14Klas DahlbeckX100.0062439368747178694568666963665047526403311,250,000$
15Kasper KotkansaloX100.006644867271717266456666725650476062630262750,000$
16Tommy MillerX100.006644867269697067456764735649476055630262750,000$
17Jett Woo (R)X100.007265657270707068456766706045457041620243750,000$
18Thomas SchemitschX100.006445897073677063456663685452465752620283900,000$
Rayé
1Par LindholmXX100.0061479471687678716870707370645147406503311,300,000$
2Jonathan MatsumotoX100.0060458967686765656564626562494525195903821,000,000$
3Nick WolffX100.007663707275686662456360655546455719610283800,000$
4Luke GreenX100.006748907068676757456260675746455820600271750,000$
5Jeremy RoyX100.006548887068686058456461655746455819600273700,000$
MOYENNE D’ÉQUIPE100.00654986717169716757666568615449524362
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
Âge
Contrat
Salaire
1Dustin Tokarski100.007879797679778481828480636238586603521,500,000$
2Linden Rowat100.00746968757576817978797246523870620351900,000$
Rayé
MOYENNE D’ÉQUIPE100.0076747476777783808082765557386464
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Michel Therrien72798496999939CAN624100,000$


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’équipe
POS
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
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’équipe
GP
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’équipe
POS
Âge
Date de naissance
Pays
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
Forcer UFA
Rappel d'urgence
Type
Salaire actuel
Plafond salarial
Plafond salarial restant
Exclus du plafond 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
Plafond salarial année 2
Plafond salarial année 3
Plafond salarial année 4
Plafond salarial année 5
Plafond salarial année 6
Plafond salarial année 7
Plafond salarial année 8
Plafond salarial année 9
Plafond salarial année 10
Non-échange année 2
Non-échange année 3
Non-échange année 4
Non-échange année 5
Non-échange année 6
Non-échange année 7
Non-échange année 8
Non-échange année 9
Non-échange année 10
Lien
Adam MascherinCrunch (TB )LW/RW261998-06-06CANNo205 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Antoine MorandCrunch (TB )C261999-02-18CANNo184 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Corey TrivinoCrunch (TB )C351990-01-12CANNo193 Lbs6 ft1NoNoFree AgentNoNo22024-02-06FalseFalsePro & Farm1,000,000$0$0$No1,000,000$--------1,000,000$--------No--------Lien
Dominik UherCrunch (TB )LW/RW321992-12-31CHENo202 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Dustin TokarskiCrunch (TB )G351989-09-16CANNo198 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm1,500,000$0$0$No1,500,000$--------1,500,000$--------No--------Lien
Graham BlackCrunch (TB )C321993-01-13CANNo185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
JC LiponCrunch (TB )LW/RW311993-07-10CANNo189 Lbs6 ft0NoNoTrade2024-07-27NoNo2FalseFalsePro & Farm1,200,000$0$0$No1,200,000$--------1,200,000$--------No--------Lien
James SheppardCrunch (TB )LW/RW361988-04-25CANNo215 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm1,000,000$0$0$No1,000,000$--------1,000,000$--------No--------Lien
Jeremy RoyCrunch (TB )D271997-05-14CANNo187 Lbs6 ft0NoNoN/ANoNo32024-04-29FalseFalsePro & Farm700,000$0$0$No700,000$700,000$-------700,000$700,000$-------NoNo-------Lien
Jett WooCrunch (TB )D242000-07-27CANYes205 Lbs6 ft0NoNoProspectNoNo32024-06-05FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Johan SundstromCrunch (TB )C321992-09-21SWENo201 Lbs6 ft2NoNoFree AgentNoNo22024-07-22FalseFalsePro & Farm1,100,000$0$0$No1,100,000$--------1,100,000$--------No--------Lien
Jonathan MatsumotoCrunch (TB )C381986-10-13CANNo185 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm1,000,000$0$0$No1,000,000$--------1,000,000$--------No--------Lien
Kasper KotkansaloCrunch (TB )D261998-11-16FINNo205 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Klas DahlbeckCrunch (TB )D331991-07-06SWENo207 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$0$0$No---------------------------Lien
Kyle MacleanCrunch (TB )LW251999-04-29USAYes190 Lbs6 ft1NoNoTrade2024-06-27NoNo12024-06-27FalseFalsePro & Farm900,000$0$0$No---------------------------Lien
Linden RowatCrunch (TB )G351989-06-27CANNo177 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm900,000$0$0$No---------------------------Lien
Luke GreenCrunch (TB )D271998-01-12CANNo187 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Mackenzie EntwistleCrunch (TB )LW/RW251999-07-14CANNo184 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien
Nick WolffCrunch (TB )D281996-07-21USANo229 Lbs6 ft6NoNoN/ANoNo32024-04-29FalseFalsePro & Farm800,000$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien
Par LindholmCrunch (TB )LW/RW331991-10-05SWENo182 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,300,000$0$0$No---------------------------Lien
Stefan NoesenCrunch (TB )LW/RW321993-02-12USANo205 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm1,200,000$0$0$No---------------------------Lien
Thomas SchemitschCrunch (TB )D281996-10-26CANNo201 Lbs6 ft5NoNoN/ANoNo32024-04-29FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------Lien
Tomas HykaCrunch (TB )LW/RW321993-03-23CZENo185 Lbs5 ft10NoNoFree AgentNoNo22024-01-31FalseFalsePro & Farm1,000,000$0$0$No1,000,000$--------1,000,000$--------No--------Lien
Tommy MillerCrunch (TB )D261999-03-06USANo181 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Trevor CarrickCrunch (TB )D301994-07-04CANNo196 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm1,300,000$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2530.16195 Lbs6 ft11.76954,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Stefan NoesenJC LiponJohan Sundstrom25122
2Antoine MorandJames SheppardCorey Trivino25122
3Adam MascherinTomas HykaKyle Maclean25122
4Kyle MacleanJohan SundstromJC Lipon25122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Trevor CarrickKlas Dahlbeck34122
2Kasper KotkansaloTommy Miller34122
3Jett WooThomas Schemitsch32122
4Kasper KotkansaloTrevor Carrick0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Stefan NoesenJC LiponKyle Maclean50122
2Johan SundstromAntoine MorandAdam Mascherin50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Thomas SchemitschTrevor Carrick50122
2Kasper KotkansaloTommy Miller50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Johan SundstromKyle Maclean50122
2JC LiponAdam Mascherin50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Thomas SchemitschTrevor Carrick50122
2Kasper KotkansaloTommy Miller50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Johan Sundstrom50122Thomas SchemitschTrevor Carrick50122
2Adam Mascherin50122Kasper KotkansaloTommy Miller50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Johan SundstromKyle Maclean50122
2Adam MascherinJC Lipon50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Thomas SchemitschTrevor Carrick50122
2Kasper KotkansaloTommy Miller50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Stefan NoesenJohan SundstromKyle MacleanKasper KotkansaloTrevor Carrick
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Stefan NoesenJohan SundstromKyle MacleanKasper KotkansaloTrevor Carrick
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Johan Sundstrom, Adam Mascherin, Kyle MacleanJohan Sundstrom, Adam MascherinAdam Mascherin
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Tommy Miller, Thomas Schemitsch, Kasper KotkansaloKasper KotkansaloThomas Schemitsch, Kasper Kotkansalo
Tirs de pénalité
Johan Sundstrom, Kyle Maclean, Adam Mascherin, JC Lipon, Antoine Morand
Gardien
#1 : Dustin Tokarski, #2 : Linden Rowat


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
Total
Domicile
Visiteur
#
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
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%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
Jour
Match
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 billets3515
Assistance0%0%
Assistance PCT0%0%

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

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
0$ 2,385,000$ 2,385,000$ 100,000$0$
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$ 1 0$ 0$




Crunch 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
1Alexander Khokhlachev8127437011299612720313.30%16143717.75515202411274150.29%00.9713
2Par Lindholm82263561125326324110.79%10144017.56511165211264554.96%00.8514
3Tomas Jurco82183553168689216311.04%20153418.7189173100022054.31%00.6914
4Stefan Noesen822429531416695421611.11%9136016.5949134700005248.89%10.7828
5Trevor Carrick73104151398134651079.35%88165322.6531114391013400%00.6200

Crunch 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
1Dustin Tokarski58302050.8973.0531712216115660300.60923
2Andrey Makarov31131010.9092.59155102677390001.00010
3Linden Rowat51110.8703.8023700151150000.3333

Crunch Statistiques de l'Équipe de Carrière

Total
Domicile
Visiteur
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
158238310323527424826412015022111341221241181601024140126149527449376704102818510247982879782266242067954914152546023.62%2253982.67%31428288349.53%1366269650.67%691133551.76%1979135419196051072539
Total Saison régulière8238310323527424826412015022111341221241181601024140126149527449376704102818510247982879782266242067954914152546023.62%2253982.67%31428288349.53%1366269650.67%691133551.76%1979135419196051072539
Séries éliminatoires
1513760000044413624000001920-17520000025214144481125001513151363113116126841711510022238923.68%411368.29%121342450.24%22747947.39%11923251.29%3062113109617286
Total Séries éliminatoires13760000044413624000001920-17520000025214144481125001513151363113116126841711510022238923.68%411368.29%121342450.24%22747947.39%11923251.29%3062113109617286

Crunch 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
1Par Lindholm1084123211164318.60%120220.25112500012251.67%01.1900
2James Sheppard1374116919113023.33%323117.84011200000042.31%00.9500
3Trevor Carrick1347111182161822.22%2230423.4412370000000%00.7200
4Mikkel Boedker1137108268387.89%120718.84112200001029.55%00.9700
5Simon Benoit13010101121711260%1831324.11033110001000%00.6400

Crunch 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
1Andrey Makarov74300.9172.68426001922800000
2Dustin Tokarski63210.8843.65362002218900000