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Crunch
GP: 36 | W: 16 | L: 17 | OTL: 3 | P: 35
GF: 116 | GA: 119 | PP%: 19.71% | PK%: 76.15%
DG: Guillaume Cazes | Morale : 45 | Moyenne d’équipe : 62
Prochains matchs #570 vs Wolves
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Centre de jeu
Crunch
16-17-3, 35pts
3
FINAL
2 Barracuda
9-19-5, 23pts
Team Stats
L1SéquenceL1
10-4-3Fiche domicile6-10-2
6-13-0Fiche domicile3-9-3
5-5-0Derniers 10 matchs1-7-2
3.22Buts par match 2.70
3.31Buts contre par match 3.42
19.71%Pourcentage en avantage numérique22.22%
76.15%Pourcentage en désavantage numérique73.97%
Crunch
16-17-3, 35pts
5
FINAL
7 Roadrunners
17-13-5, 39pts
Team Stats
L1SéquenceW1
10-4-3Fiche domicile10-6-2
6-13-0Fiche domicile7-7-3
5-5-0Derniers 10 matchs5-4-1
3.22Buts par match 3.51
3.31Buts contre par match 3.14
19.71%Pourcentage en avantage numérique23.08%
76.15%Pourcentage en désavantage numérique78.21%
Wolves
12-15-5, 29pts
2024-11-21
Crunch
16-17-3, 35pts
Statistiques d’équipe
W1SéquenceL1
7-8-3Fiche domicile10-4-3
5-7-2Fiche visiteur6-13-0
5-4-110 derniers matchs5-5-0
2.69Buts par match 3.22
3.28Buts contre par match 3.22
16.67%Pourcentage en avantage numérique19.71%
80.65%Pourcentage en désavantage numérique76.15%
Crunch
16-17-3, 35pts
2024-11-24
Monsters
19-12-4, 42pts
Statistiques d’équipe
L1SéquenceW2
10-4-3Fiche domicile12-2-4
6-13-0Fiche visiteur7-10-0
5-5-010 derniers matchs6-4-0
3.22Buts par match 3.51
3.31Buts contre par match 3.51
19.71%Pourcentage en avantage numérique21.21%
76.15%Pourcentage en désavantage numérique76.40%
Rocket
16-15-6, 38pts
2024-11-25
Crunch
16-17-3, 35pts
Statistiques d’équipe
W1SéquenceL1
9-5-3Fiche domicile10-4-3
7-10-3Fiche visiteur6-13-0
3-5-210 derniers matchs5-5-0
3.08Buts par match 3.22
3.16Buts contre par match 3.22
22.22%Pourcentage en avantage numérique19.71%
77.12%Pourcentage en désavantage numérique76.15%
Meneurs d'équipe
Buts
Laurent Dauphin
13
Passes
Tommy Miller
19
Points
Antoine Morand
27
Plus/Moins
Antoine Morand
8
Victoires
Linden Rowat
8
Pourcentage d’arrêts
Dustin Tokarski
0.9

Statistiques d’équipe
Buts pour
116
3.22 GFG
Tirs pour
1088
30.22 Avg
Pourcentage en avantage numérique
19.7%
27 GF
Début de zone offensive
40.1%
Buts contre
119
3.31 GAA
Tirs contre
1140
31.67 Avg
Pourcentage en désavantage numérique
76.1%%
26 GA
Début de la zone défensive
40.0%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,503
Billets de saison300


Informations de la formation

Équipe Pro26
Équipe Mineure18
Limite contact 44 / 56
Espoirs19


Historique d'équipe

Saison actuelle16-17-3 (35PTS)
Historique60-48-11 (0.504%)
Apparitions en séries éliminatoires 1
Historique en séries éliminatoires (W-L)7-6
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 SPÂgeContratSalaire
1Laurent DauphinXX100.0077487275707578726968697560655255616602911,500,000$
2Stefan NoesenXX100.0060419069747080726767736968705746546503111,200,000$
3Mackenzie Entwistle (C)XX99.007145887371738672606869746165486853650252900,000$
4Par LindholmXX100.0061479471687678716870707370645147506503311,300,000$
5Johan SundstromX100.0057459469737073706671686966635350466403221,100,000$
6Kyle Maclean (R)X98.007250907270707572617172696645456054640251900,000$
7JC LiponXX100.0073698171707572706168716970494753406403121,200,000$
8Antoine MorandX99.006244947268727268717067696048466054630252750,000$
9James SheppardXX100.0069558668726769676563647062716130556303621,000,000$
10Tomas HykaXX100.0057439573696665676361646960494550546103121,000,000$
11Corey TrivinoX100.0060439772716470666562636662464538446003421,000,000$
12Graham BlackX100.005639877171625564675856686255544351590311700,000$
13Trevor CarrickX100.0077656773717576734573737060605351416503011,300,000$
14Klas DahlbeckX100.0062439368747181694568666963665047546403311,250,000$
15Kasper KotkansaloX100.006644867271717266456666725650476054630262750,000$
16Tommy MillerX100.006644867269697067456764735649476054630252750,000$
17Jett Woo (R)X100.007265657270707068456766706045457043620243750,000$
18Thomas SchemitschX100.006445897073677063456663685452465754620283900,000$
Rayé
1Adam MascherinXX100.006245827269666963636265616049456039600261750,000$
2Dominik UherXX100.006546756873646861706162656057524419590311700,000$
3Jonathan MatsumotoX100.0060458967686765656564626562494525265903821,000,000$
4Nick WolffX100.007663707275686662456360655546455720610283800,000$
5Luke GreenX100.006748907068676757456260675746455820600261750,000$
6Jeremy RoyX100.006548887068686058456461655746455819600273700,000$
MOYENNE D’ÉQUIPE99.83664985717169716758666669615449524462
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
1Dustin Tokarski100.007880797679778481828480636238576603521,500,000$
2Linden Rowat95.00746968757576817978797246523852620351900,000$
Rayé
MOYENNE D’ÉQUIPE97.5076757476777783808082765557385564
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’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
1Antoine MorandCrunch (TB )C3691827860116076146211.84%1063917.77178221040002492147.14%83800010.8401000101
2Tommy MillerCrunch (TB )D3671926-3160453248202514.58%4876221.1835826112011079200%000000.6800000210
3Mackenzie EntwistleCrunch (TB )LW/RW3411132431404048107227410.28%1365919.40415241080220582040.96%16600000.7301000214
4Laurent DauphinCrunch (TB )LW/RW261311240100632998297113.27%1044517.156392184000131051.02%4900001.0800000022
5Trevor CarrickCrunch (TB )D31616221535663659163910.17%4665020.993582887000041110%000000.6800001112
6Kyle MacleanCrunch (TB )LW36129210160493178267315.38%560716.871124221011240039.66%5800000.6901000132
7Kasper KotkansaloCrunch (TB )D3651520-316055245715358.77%4275921.1034739112011084200%000000.5300000003
8Corey TrivinoCrunch (TB )C3611920300154656102619.64%650414.03000002023480044.17%56600000.7900000120
9Tomas HykaCrunch (TB )LW/RW369918-56062559115015.25%847513.203141273000001046.34%4100000.7600000220
10Klas DahlbeckCrunch (TB )D363121538021333720328.11%3981822.7313420104000184000%000000.3700000011
11Johan SundstromCrunch (TB )C325914-84017565310439.43%649115.360444410001422046.25%61400000.5700000102
12Par LindholmCrunch (TB )LW/RW306814-46019358422747.14%850216.7504413790000210045.18%16600100.5600000100
13Stefan NoesenCrunch (TB )LW/RW356612-104024169326626.45%750014.291129340002260043.55%6200000.4800000010
14Thomas SchemitschCrunch (TB )D3611011-11201524247144.17%3165018.07000317011158000%000000.3400000010
15Jett WooCrunch (TB )D341910-33156324179115.88%4156616.66000215000016010%000000.3500010100
16Graham BlackCrunch (TB )C33461012015281782723.53%33009.11000050000511047.40%30800000.6700000010
17James SheppardCrunch (TB )LW/RW363710513541214414496.82%652614.61123439000031051.11%4500000.3800001000
18JC LiponCrunch (TB )LW/RW20189110021102810163.57%320910.48000012000090033.33%3000000.8600000000
19Adam MascherinCrunch (TB )LW/RW24178595189287203.57%02239.31022542000000033.33%900000.7200001111
20Nick WolffCrunch (TB )D6022-1601201100%48814.670000100001000%000000.4500000000
21Jeremy RoyCrunch (TB )D1022120000100%01818.400110300000000%000002.1700000000
22Jonathan MatsumotoCrunch (TB )C8101-2002791311.11%18710.990001170000111041.58%10100000.2300000000
23Frederick GaudreauLightningLW/RW7101-82041014367.14%313419.260003150000120050.00%3600000.1500000000
24Dominik UherCrunch (TB )LW/RW3000000001000%051.940000100000000%00000000000000
Statistiques d’équipe totales ou en moyenne648116205321-1724620622604108830281210.66%3401062916.4027447124011363581272916345.58%308900110.6003013141718
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
1Dustin TokarskiCrunch (TB )198810.9003.3710162057571011001719000
2Linden RowatCrunch (TB )208920.8983.04114660585660120.66731917110
Statistiques d’équipe totales ou en moyenne39161730.8993.19216380115113702333636110


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 Plafond 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
Adam MascherinCrunch (TB )LW/RW261998-06-06No205 Lbs5 ft10NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Antoine MorandCrunch (TB )C251999-02-18No184 Lbs5 ft11NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------Lien
Corey TrivinoCrunch (TB )C341990-01-12No193 Lbs6 ft1NoNoFree AgentNoNo22024-02-06Pro & Farm1,000,000$0$0$No1,000,000$--------No--------Lien
Dominik UherCrunch (TB )LW/RW311992-12-31No202 Lbs6 ft0NoNoN/ANoNo1Pro & Farm700,000$0$0$No------------------Lien
Dustin TokarskiCrunch (TB )G351989-09-16 18:01:24No198 Lbs6 ft0NoNoN/ANoNo2Pro & Farm1,500,000$0$0$No1,500,000$--------No--------Lien
Graham BlackCrunch (TB )C311993-01-13No185 Lbs6 ft0NoNoN/ANoNo1Pro & Farm700,000$0$0$No------------------Lien
JC LiponCrunch (TB )LW/RW311993-07-10No189 Lbs6 ft0NoNoTrade2024-07-27NoNo2Pro & Farm1,200,000$0$0$No1,200,000$--------No--------Lien
James SheppardCrunch (TB )LW/RW361988-04-25No215 Lbs6 ft1NoNoN/ANoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------Lien
Jeremy RoyCrunch (TB )D271997-05-14No187 Lbs6 ft0NoNoN/ANoNo32024-04-29Pro & Farm700,000$0$0$No700,000$700,000$-------NoNo-------Lien
Jett WooCrunch (TB )D242000-07-27Yes205 Lbs6 ft0NoNoTrade (Prospect)NoNo32024-06-05Pro & Farm750,000$0$0$No750,000$750,000$-------NoNo-------
Johan SundstromCrunch (TB )C321992-09-21No201 Lbs6 ft2NoNoFree AgentNoNo22024-07-22Pro & Farm1,100,000$0$0$No1,100,000$--------No--------Lien
Jonathan MatsumotoCrunch (TB )C381986-10-13No185 Lbs5 ft10NoNoN/ANoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------Lien
Kasper KotkansaloCrunch (TB )D261998-11-16No205 Lbs6 ft2NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------Lien
Klas DahlbeckCrunch (TB )D331991-07-06No207 Lbs6 ft3NoNoN/ANoNo1Pro & Farm1,250,000$0$0$No------------------Lien
Kyle MacleanCrunch (TB )LW251999-04-29Yes190 Lbs6 ft1NoNoTrade2024-06-27NoNo12024-06-27Pro & Farm900,000$0$0$No------------------Lien
Laurent DauphinCrunch (TB )LW/RW291995-03-27No180 Lbs6 ft1NoNoN/ANoNo12024-04-29Pro & Farm1,500,000$0$0$No------------------Lien
Linden Rowat (sur la masse salariale)Crunch (TB )G351989-06-27No177 Lbs6 ft1NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Luke GreenCrunch (TB )D261998-01-12No187 Lbs6 ft0NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Mackenzie EntwistleCrunch (TB )LW/RW251999-07-14No184 Lbs6 ft3NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Nick WolffCrunch (TB )D281996-07-21No229 Lbs6 ft6NoNoN/ANoNo32024-04-29Pro & Farm800,000$0$0$No800,000$800,000$-------NoNo-------Lien
Par LindholmCrunch (TB )LW/RW331991-10-05No182 Lbs5 ft11NoNoN/ANoNo1Pro & Farm1,300,000$0$0$No------------------Lien
Stefan NoesenCrunch (TB )LW/RW311993-02-12No205 Lbs6 ft1NoNoN/ANoNo1Pro & Farm1,200,000$0$0$No------------------Lien
Thomas SchemitschCrunch (TB )D281996-10-26No201 Lbs6 ft5NoNoN/ANoNo32024-04-29Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------Lien
Tomas HykaCrunch (TB )LW/RW311993-03-23No185 Lbs5 ft10NoNoFree AgentNoNo22024-01-31Pro & Farm1,000,000$0$0$No1,000,000$--------No--------Lien
Tommy MillerCrunch (TB )D251999-03-06No181 Lbs6 ft2NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------Lien
Trevor CarrickCrunch (TB )D301994-07-04No196 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,300,000$0$0$No------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2629.81195 Lbs6 ft11.73975,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Laurent DauphinAntoine MorandMackenzie Entwistle25122
2Par LindholmJohan SundstromJames Sheppard25122
3Stefan NoesenGraham BlackKyle Maclean25122
4Kyle MacleanCorey TrivinoTomas Hyka25122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Trevor CarrickKlas Dahlbeck34122
2Kasper KotkansaloTommy Miller34122
3Jett WooThomas Schemitsch32122
4Kasper KotkansaloKlas Dahlbeck0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mackenzie EntwistlePar LindholmLaurent Dauphin50122
2James SheppardAntoine MorandTomas Hyka50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Trevor CarrickKlas Dahlbeck50122
2Kasper KotkansaloTommy Miller50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Mackenzie EntwistleCorey Trivino50122
2Antoine MorandGraham Black50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Thomas SchemitschKlas Dahlbeck50122
2Kasper KotkansaloTommy Miller50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Antoine Morand50122Thomas SchemitschKlas Dahlbeck50122
2Mackenzie Entwistle50122Kasper KotkansaloTommy Miller50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Mackenzie EntwistleJames Sheppard50122
2Antoine MorandLaurent Dauphin50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Trevor CarrickKlas Dahlbeck50122
2Kasper KotkansaloTommy Miller50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Par LindholmMackenzie EntwistleLaurent DauphinTrevor CarrickKlas Dahlbeck
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Laurent DauphinMackenzie EntwistlePar LindholmTrevor CarrickKlas Dahlbeck
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Mackenzie Entwistle, Laurent Dauphin, Antoine MorandMackenzie Entwistle, Laurent DauphinMackenzie Entwistle
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Klas Dahlbeck, Thomas Schemitsch, Kasper KotkansaloKlas DahlbeckThomas Schemitsch, Kasper Kotkansalo
Tirs de pénalité
Mackenzie Entwistle, Tomas Hyka, Par Lindholm, Antoine Morand, James Sheppard
Gardien
#1 : Linden Rowat, #2 : Dustin Tokarski


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
1Barracuda11000000321000000000001100000032121.0003690042413123635436536663092144250.00%10100.00%0556123744.95%563123445.62%28961247.22%829566870269467232
2Bears2010000158-31000000134-11010000024-210.2505101500424131267354365366656151633700.00%8187.50%0556123744.95%563123445.62%28961247.22%829566870269467232
3BruinsF2020000027-51010000025-31010000002-200.00024600424131254354365366654181238400.00%6266.67%0556123744.95%563123445.62%28961247.22%829566870269467232
4Canucks11000000615110000006150000000000021.000611170042413123335436536663498245120.00%40100.00%1556123744.95%563123445.62%28961247.22%829566870269467232
5Checkers11000000321000000000001100000032121.00036900424131218354365366633111116400.00%3166.67%0556123744.95%563123445.62%28961247.22%829566870269467232
6Comets21100000990110000006511010000034-120.50091423004241312643543653666601712255120.00%6266.67%0556123744.95%563123445.62%28961247.22%829566870269467232
7Condors20200000311-80000000000020200000311-800.0003690042413125535436536666931163510110.00%8362.50%0556123744.95%563123445.62%28961247.22%829566870269467232
8Eagles1010000024-2000000000001010000024-200.00024610424131228354365366647121010300.00%4175.00%0556123744.95%563123445.62%28961247.22%829566870269467232
9Griffins11000000523110000005230000000000021.0005813004241312383543653666411317256233.33%10100.00%0556123744.95%563123445.62%28961247.22%829566870269467232
10Gulls1010000024-21010000024-20000000000000.0002350042413122335436536663315615400.00%30100.00%1556123744.95%563123445.62%28961247.22%829566870269467232
11Icehogs1010000023-11010000023-10000000000000.0002460042413123135436536663311211100.00%10100.00%0556123744.95%563123445.62%28961247.22%829566870269467232
12Iowa Wild21100000550110000004221010000013-220.5005914004241312523543653666821410329111.11%5180.00%0556123744.95%563123445.62%28961247.22%829566870269467232
13Islanders402011001115-4200011007702020000048-430.375111930004241312134354365366614340328419526.32%16662.50%0556123744.95%563123445.62%28961247.22%829566870269467232
14Marlies1010000013-2000000000001010000013-200.000123004241312313543653666289415600.00%2150.00%0556123744.95%563123445.62%28961247.22%829566870269467232
15Moose21100000880000000000002110000088020.50081321004241312563543653666662012308225.00%6266.67%0556123744.95%563123445.62%28961247.22%829566870269467232
16PenguinsF11000000422110000004220000000000021.00048120042413123035436536661910424100.00%20100.00%0556123744.95%563123445.62%28961247.22%829566870269467232
17Reign1010000023-1000000000001010000023-100.000246004241312313543653666307212400.00%000%0556123744.95%563123445.62%28961247.22%829566870269467232
18Roadrunners1010000057-2000000000001010000057-200.0005712104241312233543653666451215182150.00%5340.00%0556123744.95%563123445.62%28961247.22%829566870269467232
19SenatorsF220000001248110000006331100000061541.000122032004241312563543653666539154310550.00%5180.00%0556123744.95%563123445.62%28961247.22%829566870269467232
20Silver Knights10001000431100010004310000000000021.00048120042413122435436536663082114125.00%10100.00%0556123744.95%563123445.62%28961247.22%829566870269467232
21Thunderbirds1000010023-11000010023-10000000000010.500235004241312373543653666309222700.00%10100.00%0556123744.95%563123445.62%28961247.22%829566870269467232
22Wolf Pack32100000121112110000078-11100000053240.6671223351042413121063543653666732726524125.00%12283.33%1556123744.95%563123445.62%28961247.22%829566870269467232
23Wolves22000000826110000005141100000031241.000813210042413126135436536665114183310440.00%90100.00%0556123744.95%563123445.62%28961247.22%829566870269467232
Total36141702201116119-317840220165531219613000005166-15350.4861162053213042413121088354365366611403402546221372719.71%1092676.15%3556123744.95%563123445.62%28961247.22%829566870269467232
_Since Last GM Reset36141702201116119-317840220165531219613000005166-15350.4861162053213042413121088354365366611403402546221372719.71%1092676.15%3556123744.95%563123445.62%28961247.22%829566870269467232
_Vs Conference221090110175714105201101403551257000003536-1240.545751322071042413126773543653666636190162393781823.08%751876.00%1556123744.95%563123445.62%28961247.22%829566870269467232

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
3635L11162053211088114034025462230
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
3614172201116119
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
178422016553
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
1961300005166
Derniers 10 matchs
WLOTWOTL SOWSOL
352000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1372719.71%1092676.15%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
35436536664241312
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
556123744.95%563123445.62%28961247.22%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
829566870269467232


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
2 - 2024-09-0410Wolf Pack3Crunch4BWSommaire du match
4 - 2024-09-0624Crunch0BruinsF2ALSommaire du match
6 - 2024-09-0836Wolves1Crunch5BWSommaire du match
7 - 2024-09-0951Crunch2Condors5ALSommaire du match
11 - 2024-09-1376SenatorsF3Crunch6BWSommaire du match
13 - 2024-09-1593Crunch3Islanders6ALSommaire du match
14 - 2024-09-16103Crunch3Wolves1AWSommaire du match
17 - 2024-09-19119BruinsF5Crunch2BLSommaire du match
20 - 2024-09-22143Islanders4Crunch3BLXSommaire du match
22 - 2024-09-24160Crunch2Moose5ALSommaire du match
24 - 2024-09-26174Wolf Pack5Crunch3BLSommaire du match
27 - 2024-09-29195Bears4Crunch3BLXXSommaire du match
28 - 2024-09-30210Crunch1Marlies3ALSommaire du match
31 - 2024-10-03228Icehogs3Crunch2BLSommaire du match
35 - 2024-10-07246Crunch3Checkers2AWSommaire du match
37 - 2024-10-09262PenguinsF2Crunch4BWSommaire du match
39 - 2024-10-11279Crunch6SenatorsF1AWSommaire du match
41 - 2024-10-13292Crunch2Reign3ALSommaire du match
43 - 2024-10-15303Gulls4Crunch2BLSommaire du match
45 - 2024-10-17323Canucks1Crunch6BWSommaire du match
48 - 2024-10-20340Crunch3Comets4ALSommaire du match
50 - 2024-10-22355Iowa Wild2Crunch4BWSommaire du match
52 - 2024-10-24371Crunch5Wolf Pack3AWSommaire du match
55 - 2024-10-27391Thunderbirds3Crunch2BLXSommaire du match
57 - 2024-10-29408Crunch6Moose3AWSommaire du match
59 - 2024-10-31418Crunch2Bears4ALSommaire du match
61 - 2024-11-02432Griffins2Crunch5BWSommaire du match
63 - 2024-11-04443Crunch1Condors6ALSommaire du match
65 - 2024-11-06460Comets5Crunch6BWSommaire du match
67 - 2024-11-08479Crunch1Iowa Wild3ALSommaire du match
69 - 2024-11-10486Crunch1Islanders2ALSommaire du match
71 - 2024-11-12498Islanders3Crunch4BWXSommaire du match
73 - 2024-11-14520Crunch2Eagles4ALSommaire du match
75 - 2024-11-16531Silver Knights3Crunch4BWXSommaire du match
77 - 2024-11-18547Crunch3Barracuda2AWSommaire du match
79 - 2024-11-20561Crunch5Roadrunners7ALSommaire du match
80 - 2024-11-21570Wolves-Crunch-
83 - 2024-11-24589Crunch-Monsters-
84 - 2024-11-25603Rocket-Crunch-
87 - 2024-11-28625Crunch-Firebirds-
88 - 2024-11-29633Rocket-Crunch-
91 - 2024-12-02657Crunch-Checkers-
93 - 2024-12-04667Eagles-Crunch-
96 - 2024-12-07690BruinsF-Crunch-
99 - 2024-12-10712Crunch-SenatorsF-
101 - 2024-12-12725Marlies-Crunch-
102 - 2024-12-13738Crunch-Bears-
105 - 2024-12-16753Crunch-Phantoms-
107 - 2024-12-18765Marlies-Crunch-
109 - 2024-12-20780Crunch-Firebirds-
110 - 2024-12-21792Icehogs-Crunch-
113 - 2024-12-24812Crunch-Wolf Pack-
115 - 2024-12-26823Americans-Crunch-
117 - 2024-12-28842Crunch-StarsF-
119 - 2024-12-30854Wolf Pack-Crunch-
121 - 2025-01-01870Crunch-Wolves-
123 - 2025-01-03885Crunch-Admirals-
124 - 2025-01-04893Firebirds-Crunch-
127 - 2025-01-07917Crunch-Comets-
128 - 2025-01-08925PenguinsF-Crunch-
132 - 2025-01-12952Wranglers-Crunch-
134 - 2025-01-14971Crunch-Phantoms-
136 - 2025-01-16983Moose-Crunch-
139 - 2025-01-191007Comets-Crunch-
141 - 2025-01-211028Checkers-Crunch-
144 - 2025-01-241047Crunch-Marlies-
147 - 2025-01-271070Checkers-Crunch-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2025-01-291082Crunch-Rocket-
151 - 2025-01-311100Americans-Crunch-
153 - 2025-02-021112Crunch-BruinsF-
156 - 2025-02-051133Moose-Crunch-
159 - 2025-02-081151Crunch-Americans-
161 - 2025-02-101163Crunch-PenguinsF-
162 - 2025-02-111172SenatorsF-Crunch-
166 - 2025-02-151198Phantoms-Crunch-
170 - 2025-02-191224Bears-Crunch-
172 - 2025-02-211236Crunch-Rocket-
176 - 2025-02-251256Phantoms-Crunch-
178 - 2025-02-271274Crunch-Americans-
179 - 2025-02-281279Crunch-BruinsF-
182 - 2025-03-031296Firebirds-Crunch-
184 - 2025-03-051311Crunch-PenguinsF-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance26,48916,056
Assistance PCT77.91%94.45%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
24 2503 - 83.42% 102,368$1,740,253$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,066,681$ 2,535,000$ 2,535,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,023,975$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
2,456,828$ 106 14,243$ 1,509,758$




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
1Par Lindholm112324375-33151983259.85%18194217.34515206511264549.49%00.7714
2Trevor Carrick10416577341512001011669.64%134230422.1661622671013510%00.6300
3Laurent Dauphin100363571-95022311031311.50%24157615.761212246400013248.12%00.9015
4Alexander Khokhlachev8127437011299612720313.30%16143717.75515202411274150.29%00.9713
5Stefan Noesen11730356542093703099.71%16186015.90510155600025247.21%10.7028

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 Tokarski77382860.8983.1241884221821370410.60923
2Andrey Makarov31131010.9092.59155102677390001.00010
3Linden Rowat2591030.8933.17138460736810120.5006

Crunch 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
Saison régulière
158238310323527424826412015022111341221241181601024140126149527449376704102818510247982879782266242067954914152546023.62%2253982.67%31428288349.53%1366269650.67%691133551.76%1979135419196051072539
1636141702201116119-317840220165531219613000005166-15351162053213042413121088354365366611403402546221372719.71%1092676.15%3556123744.95%563123445.62%28961247.22%829566870269467232
Total Saison régulière11852480543639036723582819044121991752460242901024191192-1130390698108834144122116123567118211621188723560101980320373918722.25%3346580.54%61984412048.16%1929393049.08%980194750.33%2808192027908741539772
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