Connexion

Crunch
GP: 49 | W: 31 | L: 16 | OTL: 2 | P: 64
GF: 170 | GA: 137 | PP%: 23.60% | PK%: 84.25%
DG: Guillaume Cazes | Morale : 67 | Moyenne d’équipe : 63
Prochains matchs #788 vs SenatorsF
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Centre de jeu
Crunch
31-16-2, 64pts
3
FINAL
4 Wolves
20-25-5, 45pts
Team Stats
W1SéquenceL1
16-7-1Fiche domicile11-13-1
15-9-1Fiche domicile9-12-4
6-3-1Derniers 10 matchs4-4-2
3.47Buts par match 2.46
2.80Buts contre par match 3.10
23.60%Pourcentage en avantage numérique20.81%
84.25%Pourcentage en désavantage numérique80.61%
Checkers
27-14-7, 61pts
1
FINAL
5 Crunch
31-16-2, 64pts
Team Stats
W1SéquenceW1
16-6-2Fiche domicile16-7-1
11-8-5Fiche domicile15-9-1
4-5-1Derniers 10 matchs6-3-1
3.94Buts par match 3.47
3.17Buts contre par match 2.80
26.62%Pourcentage en avantage numérique23.60%
80.53%Pourcentage en désavantage numérique84.25%
SenatorsF
24-20-4, 52pts
2023-12-09
Crunch
31-16-2, 64pts
Statistiques d’équipe
L1SéquenceW1
12-10-3Fiche domicile16-7-1
12-10-1Fiche visiteur15-9-1
7-1-210 derniers matchs6-3-1
2.92Buts par match 3.47
2.85Buts contre par match 3.47
20.83%Pourcentage en avantage numérique23.60%
81.41%Pourcentage en désavantage numérique84.25%
Crunch
31-16-2, 64pts
2023-12-12
SenatorsF
24-20-4, 52pts
Statistiques d’équipe
W1SéquenceL1
16-7-1Fiche domicile12-10-3
15-9-1Fiche visiteur12-10-1
6-3-110 derniers matchs7-1-2
3.47Buts par match 2.92
2.80Buts contre par match 2.92
23.60%Pourcentage en avantage numérique20.83%
84.25%Pourcentage en désavantage numérique81.41%
Wolf Pack
23-26-2, 48pts
2023-12-13
Crunch
31-16-2, 64pts
Statistiques d’équipe
L1SéquenceW1
12-11-1Fiche domicile16-7-1
11-15-1Fiche visiteur15-9-1
6-4-010 derniers matchs6-3-1
2.98Buts par match 3.47
3.25Buts contre par match 3.47
17.65%Pourcentage en avantage numérique23.60%
85.37%Pourcentage en désavantage numérique84.25%
Meneurs d'équipe
Buts
Marcus Kruger
18
Passes
Trevor Carrick
36
Points
Trevor Carrick
44
Plus/Moins
Trevor Carrick
16
Victoires
Dustin Tokarski
21
Pourcentage d’arrêts
Linden Rowat
0.944

Statistiques d’équipe
Buts pour
170
3.47 GFG
Tirs pour
1486
30.33 Avg
Pourcentage en avantage numérique
23.6%
38 GF
Début de zone offensive
42.6%
Buts contre
137
2.80 GAA
Tirs contre
1435
29.29 Avg
Pourcentage en désavantage numérique
84.3%%
20 GA
Début de la zone défensive
38.2%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,528
Billets de saison300


Informations de la formation

Équipe Pro28
Équipe Mineure18
Limite contact 46 / 55
Espoirs19


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 Dauphin (A)X100.0075497275707376717168677459605056686502811,100,000$
2Mackenzie Entwistle (R) (C)X100.007245907270728670616967736160457078640243900,000$
3Tomas JurcoX100.0059409173727375696970606958785747796403011,100,000$
4Alexander KhokhlachevX97.0063457969696973707073706968585452786403021,200,000$
5Par LindholmX98.0062469471687476706668697469594850776403221,300,000$
6James SheppardX100.0067568669736867686364646862676034796303531,000,000$
7Antoine Morand (R) (A)X100.006244947268707066706865686045456079620243750,000$
8Joey HishonX100.00644573746869636778666066625753457961X0321900,000$
9Jonathan MatsumotoX100.0062469068696966676465646762474529226003731,000,000$
10Adam MascherinX100.006145807269687064646465606047456020600252750,000$
11Simon BenoitX100.0080548675737681724567657462564668596602521,700,000$
12Trevor CarrickX99.0077646673717374734572737060555154796502921,300,000$
13Brandon GormleyX100.0059458569707277684566647350685745756403111,000,000$
14Klas DahlbeckX100.0062439368747079694568657064614850796403221,250,000$
15Tommy Miller (R)X100.006544857269707066456664725645456042620243750,000$
16Thomas SchemitschX100.006546887073696863456663685447456054620271750,000$
Rayé
1Stefan NoesenX96.0059419069746878726666736967655449786503021,200,000$
2Marcus KrugerX95.1956429971717270706769677065726642666503311,500,000$
3Mikkel BoedkerX98.0055409867717582686167656863807942796503311,250,000$
4Dominik UherX100.006545766873656662686263666153524767600302700,000$
5Graham BlackX100.005739857171645663695658666254544619590302700,000$
6Kasper Kotkansalo (R)X100.006544857271707065456664725645456076620253750,000$
7Nick WolffX100.007465687275696864456562675545456020610271750,000$
8Luke GreenX100.006849917068686858456361685745456020600252750,000$
9Jeremy RoyX100.006649897068696059456562665745456020600261750,000$
MOYENNE D’ÉQUIPE99.32654785717170726758666569605751526063
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
1Andrey Makarov100.00706868767481858181817753544869640301900,000$
Rayé
1Dustin Tokarski96.007879777679768480818479595842716503431,500,000$
2Linden Rowat100.00747170757578838180817345514234630342900,000$
MOYENNE D’ÉQUIPE98.6774737276767884818182765254445864
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Michel Therrien74788399999943CAN615100,000$


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
1Trevor CarrickCrunch (TB )D498364416515934576356010.53%62115923.67291132129101386400%000000.7600000224
2Marcus KrugerCrunch (TB )C441821397602885110198316.36%877817.7076132912201141002053.40%108800001.0001000223
3Alexander KhokhlachevCrunch (TB )C491722392403785111237115.32%784817.3158131512411221092152.16%113300000.9211000232
4Stefan NoesenCrunch (TB )RW491717349804628127347813.39%579416.2234731133000073152.00%5000100.8613000321
5Par LindholmCrunch (TB )LW49122234218101341119318510.08%585017.362792812411251083256.16%7300000.8001011144
6Tomas JurcoCrunch (TB )LW491121327205354107297910.28%1189918.3667132013300021132063.49%6300000.7102000042
7Laurent DauphinCrunch (TB )RW45131730-11808348110238311.82%963914.2226823105000002147.29%12900000.9401000132
8Brandon GormleyCrunch (TB )D49722293375424167243610.45%54107521.9425729127000198200%000000.5400000210
9Klas DahlbeckCrunch (TB )D49915242220533265232813.85%5196919.79358351250110109100%000000.5000000101
10Mackenzie EntwistleCrunch (TB )RW491492351804044111309412.61%1071814.672024230000112144.29%7000000.6401000412
11Kasper KotkansaloCrunch (TB )D4751621-4220534247142410.64%6390319.222241063000178000%000000.4700000012
12Simon BenoitCrunch (TB )D33218201015540264910324.08%3670021.221342268000057000%000000.5700001110
13Antoine MorandCrunch (TB )C4991019-260355781237011.11%865313.3400000000002047.32%71000000.5800000210
14Joey HishonCrunch (TB )C4951217610040647214456.94%457911.8300021000021056.33%68700000.5900000001
15James SheppardCrunch (TB )LW4971017-114077298222548.54%865713.4200000000011048.84%4300000.5200000012
16Tommy MillerCrunch (TB )D342111301204318249188.33%3857516.9301125000019100%000000.4500000111
17Mikkel BoedkerCrunch (TB )RW495813-18011277228536.94%668013.89022111000001052.86%7000000.3813000100
18Thomas SchemitschCrunch (TB )D333912114027152011815.00%2452916.041012400005000%000000.4500000001
19Dominik UherCrunch (TB )LW464375255311136143911.11%252911.5100003000020056.00%2500000.2600010011
20Graham BlackCrunch (TB )RW4000000000000%000.110000000000000%00000000000000
21Jonathan MatsumotoCrunch (TB )C5000000000000%010.240000000000000%00000000000000
22Adam MascherinCrunch (TB )LW3000000000000%000.220000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne88216829946766310308457921486416104011.31%4111454616.49386510328513083471891229652.31%414100100.64313022232829
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 )3221710.9042.83177901848770300.66763016320
2Andrey MakarovCrunch (TB )2210910.9062.67114702515400001.00071926310
3Linden RowatCrunch (TB )10000.9442.0030001180000007000
Statistiques d’équipe totales ou en moyenne55311620.9052.762958031361435030134949630


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 )LW251998-06-06No205 Lbs5 ft10NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------Lien
Alexander KhokhlachevCrunch (TB )C301993-09-09No181 Lbs5 ft10NoNoN/ANoNo2Pro & Farm1,200,000$0$0$No1,200,000$--------No--------Lien
Andrey MakarovCrunch (TB )G301993-04-20No193 Lbs6 ft1NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Antoine MorandCrunch (TB )C241999-02-18Yes184 Lbs5 ft11NoNoN/ANoNo3Pro & Farm750,000$0$0$No750,000$750,000$-------NoNo-------
Brandon GormleyCrunch (TB )D311992-02-18No196 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,000,000$0$0$No------------------Lien
Dominik UherCrunch (TB )LW301992-12-31No202 Lbs6 ft0NoNoN/ANoNo2Pro & Farm700,000$0$0$No700,000$--------No--------Lien
Dustin TokarskiCrunch (TB )G341989-09-16 18:01:24No198 Lbs6 ft0NoNoN/ANoNo3Pro & Farm1,500,000$0$0$No1,500,000$1,500,000$-------NoNo-------Lien
Graham BlackCrunch (TB )RW301993-01-13No185 Lbs6 ft0NoNoN/ANoNo2Pro & Farm700,000$0$0$No700,000$--------No--------Lien
James SheppardCrunch (TB )LW351988-04-25No215 Lbs6 ft1NoNoN/ANoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------NoNo-------Lien
Jeremy RoyCrunch (TB )D261997-05-14No187 Lbs6 ft0NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Joey HishonCrunch (TB )C321991-10-20No170 Lbs5 ft10NoYesN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Jonathan MatsumotoCrunch (TB )C371986-10-13No185 Lbs5 ft10NoNoN/ANoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------NoNo-------Lien
Kasper KotkansaloCrunch (TB )D251998-11-16Yes205 Lbs6 ft2NoNoN/ANoNo3Pro & Farm750,000$0$0$No750,000$750,000$-------NoNo-------
Klas DahlbeckCrunch (TB )D321991-07-06No207 Lbs6 ft3NoNoN/ANoNo2Pro & Farm1,250,000$0$0$No1,250,000$--------No--------Lien
Laurent DauphinCrunch (TB )RW281995-03-27No180 Lbs6 ft1NoNoN/ANoNo1Pro & Farm1,100,000$0$0$No------------------Lien
Linden RowatCrunch (TB )G341989-06-27No177 Lbs6 ft1NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Luke GreenCrunch (TB )D251998-01-12No187 Lbs6 ft0NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------Lien
Mackenzie EntwistleCrunch (TB )RW241999-07-14Yes184 Lbs6 ft3NoNoN/ANoNo3Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------Lien
Marcus KrugerCrunch (TB )C331990-05-27No190 Lbs6 ft0NoNoN/ANoNo1Pro & Farm1,500,000$0$0$No------------------Lien
Mikkel BoedkerCrunch (TB )RW331989-12-16No207 Lbs5 ft11NoNoN/ANoNo1Pro & Farm1,250,000$0$0$No------------------Lien
Nick WolffCrunch (TB )D271996-07-21No229 Lbs6 ft6NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Par LindholmCrunch (TB )LW321991-10-05No182 Lbs5 ft11NoNoN/ANoNo2Pro & Farm1,300,000$0$0$No1,300,000$--------No--------Lien
Simon BenoitCrunch (TB )D251998-09-19No181 Lbs6 ft3NoNoN/ANoNo2Pro & Farm1,700,000$0$0$No1,700,000$--------No--------Lien
Stefan NoesenCrunch (TB )RW301993-02-12No205 Lbs6 ft1NoNoN/ANoNo2Pro & Farm1,200,000$0$0$No1,200,000$--------No--------Lien
Thomas SchemitschCrunch (TB )D271996-10-26No201 Lbs6 ft5NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Tomas JurcoCrunch (TB )LW301992-12-28No188 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,100,000$0$0$No------------------Lien
Tommy MillerCrunch (TB )D241999-03-06Yes181 Lbs6 ft2NoNoN/ANoNo3Pro & Farm750,000$0$0$No750,000$750,000$-------NoNo-------
Trevor CarrickCrunch (TB )D291994-07-04No196 Lbs6 ft2NoNoN/ANoNo2Pro & Farm1,300,000$0$0$No1,300,000$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2829.36193 Lbs6 ft11.891,014,286$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tomas JurcoLaurent Dauphin25122
2Par LindholmAlexander KhokhlachevMackenzie Entwistle25122
3James SheppardAntoine Morand25122
4Joey Hishon25122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Simon BenoitTrevor Carrick25122
2Brandon GormleyKlas Dahlbeck25122
3Thomas SchemitschTommy Miller25122
4Brandon GormleyTrevor Carrick25122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tomas Jurco50122
2Par LindholmAlexander KhokhlachevLaurent Dauphin50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Simon BenoitTrevor Carrick50122
2Brandon GormleyKlas Dahlbeck50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Tomas Jurco50122
2Alexander KhokhlachevPar Lindholm50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tommy MillerTrevor Carrick50122
2Brandon GormleyKlas Dahlbeck50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Tomas Jurco50122Simon BenoitTrevor Carrick50122
2Alexander Khokhlachev50122Brandon GormleyKlas Dahlbeck50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Tomas Jurco50122
2Alexander KhokhlachevPar Lindholm50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Thomas SchemitschTrevor Carrick50122
2Brandon GormleyKlas Dahlbeck50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tomas JurcoKlas DahlbeckTrevor Carrick
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tomas JurcoKlas DahlbeckTrevor Carrick
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, Tomas Jurco, Par LindholmPar Lindholm, Tomas JurcoTomas Jurco
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Klas Dahlbeck, Brandon Gormley, Trevor CarrickKlas DahlbeckKlas Dahlbeck, Trevor Carrick
Tirs de pénalité
, Tomas Jurco, , Par Lindholm, Alexander Khokhlachev
Gardien
#1 : , #2 : Andrey Makarov


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
1Admirals1010000034-11010000034-10000000000000.0003470068504853851448147232195818200.00%40100.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
2Americans11000000743110000007430000000000021.0007142100685048532514481472323186153266.67%30100.00%1906176651.30%827158252.28%43379354.60%11928181131361639322
3Barracuda11000000404000000000001100000040421.0004812016850485305144814723230649200.00%20100.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
4Bears11000000303110000003030000000000021.0003690168504852451448147232221002311100.00%000%0906176651.30%827158252.28%43379354.60%11928181131361639322
5BruinsF22000000624110000004131100000021141.000610160068504856651448147232561582912216.67%4175.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
6Checkers431000001385211000006602200000072560.750132437006850485955144814723213136307811436.36%15286.67%0906176651.30%827158252.28%43379354.60%11928181131361639322
7Comets43100000910-13210000068-21100000032160.750915240068504851065144814723212228318710110.00%14192.86%0906176651.30%827158252.28%43379354.60%11928181131361639322
8Condors11000000615110000006150000000000021.0006101600685048528514481472323096134250.00%30100.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
9Firebirds1010000027-5000000000001010000027-500.0002350068504853451448147232441110194125.00%4175.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
10Griffins1010000023-11010000023-10000000000000.0002460068504854151448147232277820300.00%4175.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
11Gulls10001000321000000000001000100032121.00035800685048544514481472323182283133.33%10100.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
12Icehogs11000000202110000002020000000000021.00024601685048524514481472322812617300.00%20100.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
13Islanders3210000013121110000006512110000077040.667132437006850485875144814723297251250500.00%6183.33%0906176651.30%827158252.28%43379354.60%11928181131361639322
14Marlies4220000016124211000009542110000077040.5001626420068504851225144814723210938315913323.08%12283.33%1906176651.30%827158252.28%43379354.60%11928181131361639322
15Monsters11000000211110000002110000000000021.00024600685048534514481472321856163133.33%30100.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
16Moose2020000068-2000000000002020000068-200.0006101600685048556514481472325320293612433.33%6266.67%0906176651.30%827158252.28%43379354.60%11928181131361639322
17PenguinsF1010000045-1000000000001010000045-100.000471100685048540514481472322870196116.67%000%0906176651.30%827158252.28%43379354.60%11928181131361639322
18Phantoms20100010101001010000034-11000001076120.500101828006850485765144814723265141436400.00%20100.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
19Reign11000000321000000000001100000032121.00036900685048514514481472323054152150.00%2150.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
20Rocket431000001587220000009452110000064260.7501527420068504851535144814723210437335619631.58%10280.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
21SenatorsF1000010012-11000010012-10000000000010.5001230068504853051448147232298617300.00%20100.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
22Silver Knights11000000523000000000001100000052321.0005914006850485315144814723230118163133.33%4250.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
23StarsF21100000880211000008800000000000020.50081422006850485705144814723261158346116.67%4250.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
24Thunderbirds11000000523000000000001100000052321.000581300685048526514481472322684135120.00%20100.00%1906176651.30%827158252.28%43379354.60%11928181131361639322
25Wolf Pack20100010770000000000002010001077020.50071017006850485595144814723263174389222.22%20100.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
26Wolves411010011114-3210010007522010000149-550.625112031006850485995144814723212034247511218.18%12283.33%0906176651.30%827158252.28%43379354.60%11928181131361639322
27Wranglers11000000431000000000001100000043121.000471100685048527514481472323112892150.00%40100.00%0906176651.30%827158252.28%43379354.60%11928181131361639322
Total492716021211701373324157011008461232512901021867610640.65317029946903685048514865144814723214354113108451613823.60%1272084.25%3906176651.30%827158252.28%43379354.60%11928181131361639322
_Since Last GM Reset492716021211701373324157011008461232512901021867610640.65317029946903685048514865144814723214354113108451613823.60%1272084.25%3906176651.30%827158252.28%43379354.60%11928181131361639322
_Vs Conference361813011211231091417114011006144171979000216265-3440.61112321633901685048510795144814723210743082386371232923.58%921484.78%2906176651.30%827158252.28%43379354.60%11928181131361639322

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4964W11702994691486143541131084503
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4927162121170137
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2415711008461
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2512910218676
Derniers 10 matchs
WLOTWOTL SOWSOL
431011
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1613823.60%1272084.25%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
514481472326850485
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
906176651.30%827158252.28%43379354.60%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
11928181131361639322


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
3 - 2023-08-2718Comets1Crunch2BWSommaire du match
4 - 2023-08-2824Crunch4PenguinsF5ALSommaire du match
7 - 2023-08-3147Wolves3Crunch4BWSommaire du match
9 - 2023-09-0265Crunch5Islanders3AWSommaire du match
10 - 2023-09-0378Rocket2Crunch5BWSommaire du match
13 - 2023-09-0698Crunch5Marlies4AWSommaire du match
15 - 2023-09-08111Islanders5Crunch6BWSommaire du match
17 - 2023-09-10125Crunch1Wolves5ALSommaire du match
19 - 2023-09-12141Crunch4Moose5ALSommaire du match
20 - 2023-09-13148Crunch2Firebirds7ALSommaire du match
22 - 2023-09-15163BruinsF1Crunch4BWSommaire du match
24 - 2023-09-17183Bears0Crunch3BWSommaire du match
27 - 2023-09-20207Comets5Crunch1BLSommaire du match
29 - 2023-09-22216Crunch3Comets2AWSommaire du match
31 - 2023-09-24226Crunch5Checkers1AWSommaire du match
33 - 2023-09-26241StarsF6Crunch5BLSommaire du match
35 - 2023-09-28255Crunch0Rocket1ALSommaire du match
37 - 2023-09-30274Crunch5Wolf Pack4AWXXSommaire du match
39 - 2023-10-02284Rocket2Crunch4BWSommaire du match
42 - 2023-10-05306Crunch2BruinsF1AWSommaire du match
43 - 2023-10-06316StarsF2Crunch3BWSommaire du match
46 - 2023-10-09340Condors1Crunch6BWSommaire du match
48 - 2023-10-11357Crunch5Silver Knights2AWSommaire du match
50 - 2023-10-13370Americans4Crunch7BWSommaire du match
53 - 2023-10-16389Crunch3Gulls2AWXSommaire du match
55 - 2023-10-18405Griffins3Crunch2BLSommaire du match
57 - 2023-10-20424Crunch2Marlies3ALSommaire du match
58 - 2023-10-21435Icehogs0Crunch2BWSommaire du match
61 - 2023-10-24453Crunch3Reign2AWSommaire du match
63 - 2023-10-26466Marlies2Crunch7BWSommaire du match
67 - 2023-10-30491Crunch4Wranglers3AWSommaire du match
69 - 2023-11-01502Checkers5Crunch1BLSommaire du match
72 - 2023-11-04523Crunch2Checkers1AWSommaire du match
73 - 2023-11-05531Admirals4Crunch3BLSommaire du match
76 - 2023-11-08550Crunch2Moose3ALSommaire du match
78 - 2023-11-10564Comets2Crunch3BWSommaire du match
80 - 2023-11-12576Crunch2Islanders4ALSommaire du match
82 - 2023-11-14595SenatorsF2Crunch1BLXSommaire du match
84 - 2023-11-16613Crunch5Thunderbirds2AWSommaire du match
86 - 2023-11-18626Marlies3Crunch2BLSommaire du match
88 - 2023-11-20643Crunch4Barracuda0AWSommaire du match
90 - 2023-11-22660Wolves2Crunch3BWXSommaire du match
93 - 2023-11-25682Monsters1Crunch2BWSommaire du match
95 - 2023-11-27699Crunch2Wolf Pack3ALSommaire du match
97 - 2023-11-29714Phantoms4Crunch3BLSommaire du match
99 - 2023-12-01727Crunch6Rocket3AWSommaire du match
101 - 2023-12-03744Crunch7Phantoms6AWXXSommaire du match
102 - 2023-12-04753Crunch3Wolves4ALXXSommaire du match
104 - 2023-12-06764Checkers1Crunch5BWSommaire du match
107 - 2023-12-09788SenatorsF-Crunch-
110 - 2023-12-12808Crunch-SenatorsF-
111 - 2023-12-13819Wolf Pack-Crunch-
113 - 2023-12-15837Crunch-Comets-
115 - 2023-12-17850Roadrunners-Crunch-
119 - 2023-12-21876Eagles-Crunch-
121 - 2023-12-23886Crunch-Bears-
123 - 2023-12-25907Crunch-Americans-
124 - 2023-12-26916Wolf Pack-Crunch-
127 - 2023-12-29933Crunch-SenatorsF-
128 - 2023-12-30947Crunch-BruinsF-
130 - 2024-01-01956Phantoms-Crunch-
133 - 2024-01-04975BruinsF-Crunch-
136 - 2024-01-071002Americans-Crunch-
137 - 2024-01-081012Crunch-Americans-
141 - 2024-01-121035Crunch-Iowa Wild-
142 - 2024-01-131043Islanders-Crunch-
144 - 2024-01-151063Crunch-Bears-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
146 - 2024-01-171077PenguinsF-Crunch-
149 - 2024-01-201095Firebirds-Crunch-
151 - 2024-01-221106Crunch-Firebirds-
154 - 2024-01-251128Crunch-Iowa Wild-
156 - 2024-01-271138Crunch-Firebirds-
157 - 2024-01-281148PenguinsF-Crunch-
160 - 2024-01-311169Crunch-Canucks-
161 - 2024-02-011179Bears-Crunch-
163 - 2024-02-031192Crunch-Phantoms-
165 - 2024-02-051204Islanders-Crunch-
169 - 2024-02-091233Firebirds-Crunch-
170 - 2024-02-101238Crunch-PenguinsF-
175 - 2024-02-151267Crunch-PenguinsF-
177 - 2024-02-171277Moose-Crunch-
180 - 2024-02-201300Moose-Crunch-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance37,50523,166
Assistance PCT78.14%96.53%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
17 2528 - 84.27% 100,302$2,407,241$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,647,234$ 2,840,000$ 2,840,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,588,957$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,705,129$ 76 16,154$ 1,227,704$




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

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

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

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

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