Crunch

GP: 3 | W: 3 | L: 0 | OTL: 0 | P: 6
GF: 11 | GA: 2 | PP%: 31.25% | PK%: 95.00%
DG: Stéphane Lacasse | Morale : 54 | Moyenne d'Équipe : N/A
Prochain matchs #75 vs Devils
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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
1Austin CzarnikX100.0063558080707073706463646255727215500
2Chase De LeoX100.0061556262636072555055555555727315500
3Francis Perron (R)X100.0061556660636075575056575655757415500
4Freddie HamiltonX100.0060556670777066636061606155726815500
5Nathan Bastian (R)XX100.0056555555555555555055555555505015300
6Matt PuempelX100.0060556672797260615060605855545415500
7Kevin PorterX100.0066556672706669605060606055646415500
8Reid BoucherXX100.0071557382787177735063656655747215500
9Colin GreeningX100.0055555555555555555055555555727115500
10Borna RendulicX100.0056555555585959555055555555707515500
11Henrik SamuelssonX100.0059557462797554555055555555505015500
12Nikolay KuleminXX100.0077558180796864665061616755848215500
13Jeff SchultzX100.0059555961595979592559595955838115800
14Ryan GravesX100.0055555660565677562556565655535315500
15Duncan SiemensX100.0073556079807167692561617055535315500
16Jason GarrisonX100.0064556578907584652562606455747715500
17Lukas Bengtsson (R)X100.0055555660565657562556565655535315500
18Nate GueninX100.0055555560555565552555555555656615500
19Mat BodieX100.0062556661586569602560605655535315600
20Nick EbertX100.0055555560555564552555555555535315500
Rayé
1Michael ZalewskiX100.0056555555555555555055555555505014700
2Ryan MaloneX100.0056555555555555555055555555505014700
3Spencer Watson (R)XX100.0056555555555555555055555555505014700
4Tyler GraovacX100.0076556375787360615060606055505014700
5Sam HenleyX100.0056555555555555555055555555505014700
6Kevin CzuczmanX100.0055555560555569552555555555535314700
7Brandon Crawley (R)X100.0055555560555556552555555555555514700
MOYENNE D'ÉQUIPE100.006055626465626559425858585561611530
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
1Adin Hill100.006068638065656563676355606215500
2Jamie Phillips100.006069666466666563676355606215500
Rayé
MOYENNE D'ÉQUIPE100.00606965726666656367635560621550
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Steve Spott60486266636461CAN475100,000$


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'ÉquipePOS 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
1Matt PuempelCrunch (Tam)LW3066100125440.00%05117.16044111000020075.00%400002.3300000001
2Freddie HamiltonCrunch (Tam)C33141202363850.00%25919.722132110000102070.00%4000001.3500000010
3Duncan SiemensCrunch (Tam)D322416012472428.57%86421.66123511000014100.00%000001.2300000200
4Kevin PorterCrunch (Tam)C32133603573428.57%03812.8600000000000055.56%2700001.5600000001
5Francis PerronCrunch (Tam)LW3022340310000.00%04715.6900000000080045.45%1100000.8500000000
6Jason GarrisonCrunch (Tam)D31121002441425.00%26822.86112311000017000.00%000000.5800000001
7Reid BoucherCrunch (Tam)LW/RW302224091014190.00%07123.68011190005170064.29%4200000.5600000010
8Mat BodieCrunch (Tam)D3022375123010.00%05217.56011211000013000.00%000000.7600001000
9Austin CzarnikCrunch (Tam)C3011120498360.00%16220.720001100000170063.41%4100000.3200000000
10Jeff SchultzCrunch (Tam)D3011375510020.00%35117.29000010000014000.00%000000.3900100000
11Nathan BastianCrunch (Tam)C/RW2011255302100.00%02311.570000000000000.00%100000.8600001000
12Nate GueninCrunch (Tam)D310114011100100.00%13511.920000000003000.00%000000.5600000000
13Borna RendulicCrunch (Tam)RW31011604030033.33%04816.19101310000000050.00%400000.4100000000
14Nikolay KuleminCrunch (Tam)LW/RW31011206174214.29%04515.080002110000100050.00%1000000.4400000000
15Chase De LeoCrunch (Tam)C3000000131120.00%1227.5900000000010060.71%2800000.0000000000
16Ryan GravesCrunch (Tam)D3000100010000.00%23411.390000000002000.00%000000.0000000000
17Lukas BengtssonCrunch (Tam)D3000020201110.00%2279.300000000004000.00%000000.0000000000
18Colin GreeningCrunch (Tam)LW3000000102010.00%0217.1300000000000050.00%200000.0000000000
19Henrik SamuelssonCrunch (Tam)C3000000010000.00%082.9200003000000080.00%500000.0000000000
20Nick EbertCrunch (Tam)D3000000100100.00%0237.970000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne59112031255715614871254815.49%2285914.56510152011500051393061.86%21500000.7200102223
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
1Adin HillCrunch (Tam)33000.9690.67180022640000.000030110
Stats d'équipe Total ou en Moyenne33000.9690.67180022640000.000030110


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap 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 Link
Adin HillCrunch (Tam)G201996-05-11No198 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Austin CzarnikCrunch (Tam)C241992-12-12No160 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Borna RendulicCrunch (Tam)RW241992-03-24No200 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Brandon CrawleyCrunch (Tam)D191997-02-02Yes205 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Chase De LeoCrunch (Tam)C211995-10-25No178 Lbs5 ft9NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$No500,000$
Colin GreeningCrunch (Tam)LW301986-03-09No210 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Duncan SiemensCrunch (Tam)D231993-09-07No205 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Francis PerronCrunch (Tam)LW201996-04-18Yes166 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Freddie HamiltonCrunch (Tam)C251992-01-01No195 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Henrik SamuelssonCrunch (Tam)C221994-02-07No210 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm900,000$0$0$No
Jamie PhillipsCrunch (Tam)G231993-03-24No170 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Jason GarrisonCrunch (Tam)D321984-11-13No222 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm2,500,000$0$0$No
Jeff SchultzCrunch (Tam)D301986-02-25No230 Lbs6 ft6NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Kevin CzuczmanCrunch (Tam)D261991-01-09No209 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Kevin PorterCrunch (Tam)C301986-03-12No194 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Lukas BengtssonCrunch (Tam)D221994-04-13Yes172 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Mat BodieCrunch (Tam)D261990-06-03No175 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Matt PuempelCrunch (Tam)LW231993-01-23No205 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Michael ZalewskiCrunch (Tam)LW241992-08-18No205 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Nate GueninCrunch (Tam)D341982-12-09No207 Lbs6 ft3NoNoNo2Sans RestrictionPro & Farm450,000$0$0$No450,000$
Nathan BastianCrunch (Tam)C/RW191997-12-06Yes205 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Nick EbertCrunch (Tam)D221994-05-10No203 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm500,000$0$0$No
Nikolay KuleminCrunch (Tam)LW/RW301986-07-13No225 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm2,500,000$0$0$No2,500,000$
Reid BoucherCrunch (Tam)LW/RW231993-09-07No190 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Ryan GravesCrunch (Tam)D211995-05-21No220 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm865,000$0$0$No
Ryan MaloneCrunch (Tam)LW371979-11-30No225 Lbs6 ft4NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Sam HenleyCrunch (Tam)LW231993-07-24No209 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Spencer WatsonCrunch (Tam)LW/RW201996-04-26Yes170 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Tyler GraovacCrunch (Tam)C231993-04-26No200 Lbs6 ft5NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2924.69199 Lbs6 ft21.90559,138$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Reid BoucherAustin CzarnikNikolay Kulemin40122
2Matt PuempelFreddie HamiltonBorna Rendulic30122
3Francis PerronKevin PorterNathan Bastian20122
4Colin GreeningChase De LeoReid Boucher10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jason GarrisonDuncan Siemens40122
2Jeff SchultzMat Bodie30122
3Ryan GravesNate Guenin20122
4Lukas BengtssonNick Ebert10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Reid BoucherAustin CzarnikNikolay Kulemin60122
2Matt PuempelFreddie HamiltonBorna Rendulic40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jason GarrisonDuncan Siemens60122
2Jeff SchultzMat Bodie40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Reid BoucherAustin Czarnik60122
2Nikolay KuleminFreddie Hamilton40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jason GarrisonDuncan Siemens60122
2Jeff SchultzMat Bodie40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Reid Boucher60122Jason GarrisonDuncan Siemens60122
2Austin Czarnik40122Jeff SchultzMat Bodie40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Reid BoucherAustin Czarnik60122
2Nikolay KuleminFreddie Hamilton40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jason GarrisonDuncan Siemens60122
2Jeff SchultzMat Bodie40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Reid BoucherAustin CzarnikNikolay KuleminJason GarrisonDuncan Siemens
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Reid BoucherAustin CzarnikNikolay KuleminJason GarrisonDuncan Siemens
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Henrik Samuelsson, Kevin Porter, Francis PerronHenrik Samuelsson, Kevin PorterFrancis Perron
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Ryan Graves, Nate Guenin, Lukas BengtssonRyan GravesNate Guenin, Lukas Bengtsson
Tirs de Pénalité
Reid Boucher, Austin Czarnik, Nikolay Kulemin, Freddie Hamilton, Matt Puempel
Gardien
#1 : Adin Hill, #2 : Jamie Phillips


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
LigueDomicileVisiteur
# 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
1Americans11000000202000000000001100000020221.00024601641022281825025914207114.29%70100.00%0549159.34%588766.67%213756.76%835962213418
2Bears11000000422000000000001100000042221.0004812006410172818250211110157342.86%5180.00%0549159.34%588766.67%213756.76%835962213418
3Checkers11000000505110000005050000000000021.000581301641032281825018233262150.00%80100.00%0549159.34%588766.67%213756.76%835962213418
Total330000001129110000005052200000062461.0001120310264107128182506422576116531.25%20195.00%0549159.34%588766.67%213756.76%835962213418
_Since Last GM Reset330000001129110000005052200000062461.0001120310264107128182506422576116531.25%20195.00%0549159.34%588766.67%213756.76%835962213418
_Vs Conference11000000422000000000001100000042221.0004812006410172818250211110157342.86%5180.00%0549159.34%588766.67%213756.76%835962213418
_Vs Division21000000927100000005051100000042220.50091625016410492818250391343419444.44%13192.31%0549159.34%588766.67%213756.76%835962213418

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
36W3112031716422576102
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
3300000112
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
110000050
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
220000062
Derniers 10 Matchs
WLOTWOTL SOWSOL
300000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
16531.25%20195.00%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
28182506410
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
549159.34%588766.67%213756.76%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
835962213418


Derniers Match 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
4 - 2018-09-0811Crunch4Bears2WSommaire du Match
8 - 2018-09-1230Crunch2Americans0WSommaire du Match
11 - 2018-09-1546Checkers0Crunch5WSommaire du Match
17 - 2018-09-2175Crunch-Devils-
18 - 2018-09-2285Comets-Crunch-
24 - 2018-09-28107Crunch-Marlies-
25 - 2018-09-29119Checkers-Crunch-
31 - 2018-10-05140Senators-Crunch-
32 - 2018-10-06157Senators-Crunch-
38 - 2018-10-12187Crunch-Americans-
40 - 2018-10-14209Bears-Crunch-
43 - 2018-10-17217Devils-Crunch-
45 - 2018-10-19224Crunch-Comets-
46 - 2018-10-20239Rocket-Crunch-
50 - 2018-10-24260Crunch-Devils-
52 - 2018-10-26265Devils-Crunch-
53 - 2018-10-27283Crunch-Thunderbirds-
59 - 2018-11-02308Crunch-Monsters-
60 - 2018-11-03318Crunch-Monsters-
66 - 2018-11-09350Devils-Crunch-
67 - 2018-11-10366Americans-Crunch-
71 - 2018-11-14384Crunch-Marlies-
73 - 2018-11-16396Crunch-Rocket-
74 - 2018-11-17401Crunch-Rocket-
78 - 2018-11-21429Crunch-Thunderbirds-
80 - 2018-11-23439Crunch-Phantoms-
81 - 2018-11-24457Penguins-Crunch-
85 - 2018-11-28468Crunch-Devils-
87 - 2018-11-30476Comets-Crunch-
88 - 2018-12-01489Thunderbirds-Crunch-
92 - 2018-12-05511Crunch-Comets-
94 - 2018-12-07518Sound Tigers-Crunch-
95 - 2018-12-08535Marlies-Crunch-
99 - 2018-12-12554Crunch-Devils-
101 - 2018-12-14563Monsters-Crunch-
102 - 2018-12-15577Crunch-Comets-
106 - 2018-12-19596Crunch-Comets-
108 - 2018-12-21605Senators-Crunch-
109 - 2018-12-22626Crunch-Devils-
111 - 2018-12-24636Devils-Crunch-
115 - 2018-12-28655Thunderbirds-Crunch-
116 - 2018-12-29673Americans-Crunch-
122 - 2019-01-04685Comets-Crunch-
123 - 2019-01-05702Monsters-Crunch-
127 - 2019-01-09719Crunch-Americans-
129 - 2019-01-11726Crunch-Wolf Pack-
131 - 2019-01-13752Crunch-Bruins-
134 - 2019-01-16765Crunch-Senators-
136 - 2019-01-18774Crunch-Americans-
137 - 2019-01-19782Americans-Crunch-
139 - 2019-01-21805Crunch-Marlies-
141 - 2019-01-23809Rocket-Crunch-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25817Marlies-Crunch-
144 - 2019-01-26832Marlies-Crunch-
150 - 2019-02-01856Phantoms-Crunch-
151 - 2019-02-02871Americans-Crunch-
152 - 2019-02-03884Crunch-Americans-
155 - 2019-02-06890Crunch-Comets-
157 - 2019-02-08897Comets-Crunch-
158 - 2019-02-09915Crunch-Penguins-
162 - 2019-02-13939Crunch-Rocket-
164 - 2019-02-15943Wolf Pack-Crunch-
165 - 2019-02-16958Devils-Crunch-
168 - 2019-02-19973Crunch-Checkers-
169 - 2019-02-20978Crunch-Checkers-
172 - 2019-02-23997Comets-Crunch-
173 - 2019-02-241013Crunch-Sound Tigers-
176 - 2019-02-271019Crunch-Senators-
178 - 2019-03-011027Bruins-Crunch-
179 - 2019-03-021043Comets-Crunch-
183 - 2019-03-061064Crunch-Senators-
185 - 2019-03-081077Crunch-Americans-
186 - 2019-03-091089Americans-Crunch-
192 - 2019-03-151117Rocket-Crunch-
193 - 2019-03-161130Americans-Crunch-
194 - 2019-03-171147Crunch-Comets-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
37 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
17,563$ 162,150$ 134,783$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 10,868$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 181 1,351$ 244,531$




LigueDomicileVisiteur
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
13330000001129110000005052200000062461120310264107128182506422576116531.25%20195.00%0549159.34%588766.67%213756.76%835962213418
Total Saison Régulière330000001129110000005052200000062461120310264107128182506422576116531.25%20195.00%0549159.34%588766.67%213756.76%835962213418
Séries
1251400000515-102110000055030300000010-10251015011130812626281145358913016212.50%38781.58%07513256.82%9217054.12%356553.85%10063138376329
1251400000515-102110000055030300000010-10251015011130812626281145358913016212.50%38781.58%07513256.82%9217054.12%356553.85%10063138376329
Total Séries1028000001030-20422000001010060600000020-20410203002226016252525622907017826032412.50%761481.58%015026456.82%18434054.12%7013053.85%2011272777412658