Crunch

GP: 47 | W: 27 | L: 15 | OTL: 5 | P: 59
GF: 142 | GA: 115 | PP%: 16.73% | PK%: 87.54%
DG: Stéphane Lacasse | Morale : 58 | Moyenne d'Équipe : 58
Prochain matchs #765 vs Senators
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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
1Reid BoucherXX100.00715573827871777350636566557472168670
2Austin CzarnikX99.00635580807070737064636462557272170650
3Byron FroeseX99.00795565757767696974656469556476118650
4Freddie HamiltonX100.00605566707770666360616061557268167620
5Kevin PorterX100.00665566727066696050606060556464170610
6Matt PuempelX100.00605566727972606150606058555454171600
7Tyler GraovacX100.00765563757873606150606060555050119600
8Francis Perron (R)X100.00615566606360755750565756557574170580
9Chase De LeoX100.00615562626360725550555555557273170570
10Henrik SamuelssonX100.00595574627975545550555555555050170560
11Borna RendulicX100.00565555555859595550555555557075167550
12Nathan Bastian (R)XX99.00565555555555555550555555555050155530
13Spencer Watson (R)XX100.00565555555555555550555555555050118520
14Duncan SiemensX100.00735560798071676925616170555353169660
15Jeff SchultzX100.00595559615959795925595959558381170600
16Mat BodieX100.00625566615865696025606056555353171570
17Nate GueninX100.00555555605555655525555555556566170550
18Kevin CzuczmanX100.00555555605555695525555555555353119540
19Nick EbertX100.00555555605555645525555555555353164540
Rayé
1Colin GreeningX100.00555555555555555550555555557271153540
2Michael ZalewskiX100.00565555555555555550555555555050120520
3Ryan MaloneX100.00565555555555555550555555555050120520
4Sam HenleyX100.00565555555555555550555555555050120520
5Paul PostmaX100.0069557470776958692561606655646419630
6Lukas Bengtsson (R)X100.00555556605656575625565656555353159540
7Brandon Crawley (R)X100.00555555605555565525555555555555120530
MOYENNE D'ÉQUIPE99.8861556264646263594358585855606115058
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
1Ondrej Pavelec100.0070727176707069656969558078118690
2Adin Hill100.0060686380656565636763556062159640
Rayé
1Jamie Phillips100.0060696664666665636763556062153630
MOYENNE D'ÉQUIPE100.006370677367676664686555676714365
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
1Reid BoucherCrunch (Tam)LW/RW4714314593209110614743999.52%12101121.513111426181202182181150.64%54300010.8901000145
2Austin CzarnikCrunch (Tam)C4717264391603195132367612.88%1397720.80710174221302242436059.07%90400000.8801000321
3Matt PuempelCrunch (Tam)LW47152439112355168137377010.95%383917.8651015292190000303053.57%5600000.9300001054
4Freddie HamiltonCrunch (Tam)C4712213315575651061173210010.26%592119.6138112817711231482157.39%79800000.7201010232
5Duncan SiemensCrunch (Tam)D341017273595804561215016.39%5165019.136915421271014148300.00%000000.8300001330
6Mat BodieCrunch (Tam)D475182319695553049132510.20%3894020.00178342100110206100.00%000000.4900001120
7Jeff SchultzCrunch (Tam)D4791221104810672747152519.15%3896820.60718312050110222200.00%000000.4300110205
8Kevin PorterCrunch (Tam)C4789170460527673296510.96%856412.000111170001242148.33%48000000.6000000102
9Francis PerronCrunch (Tam)LW474711-142045375617377.14%869514.7901142300001050045.54%10100000.3200000001
10Nathan BastianCrunch (Tam)C/RW3746102301039183663111.11%448613.15112145000001034.78%2300000.4100011001
11Nate GueninCrunch (Tam)D47281085606517207910.00%3163713.560113400000133000.00%000000.3100000020
12Borna RendulicCrunch (Tam)RW474610115010733039122910.26%376116.1921319193000000055.10%4900000.2600001110
13Byron FroeseCrunch (Tam)C9426122029283542411.43%220122.3310112330000360160.58%20800000.6011000001
14Chase De LeoCrunch (Tam)C471451401724133117.69%42365.030000160001310049.68%15500000.4200000000
15Colin GreeningCrunch (Tam)LW2932530068112527.27%21304.5000000000011066.67%1200000.7700000100
16Nick EbertCrunch (Tam)D45055430049175490.00%2247010.4600001000047000.00%000000.2100000000
17Lukas BengtssonCrunch (Tam)D3122412401812132115.38%202859.2001127000025000.00%000000.2800000010
18Paul PostmaCrunch (Tam)D11044-521516816190.00%920518.680221252000033000.00%000000.3900010000
19Henrik SamuelssonCrunch (Tam)C47213-140916111718.18%11954.151012380001381067.11%7600000.3100000100
20Kevin CzuczmanCrunch (Tam)D1801132001487000.00%61649.13000219000021000.00%000000.1200000000
21Spencer WatsonCrunch (Tam)LW/RW5011120223110.00%0377.41000010000100100.00%200000.5400000000
22Tyler GraovacCrunch (Tam)C18011020101071120.00%0804.4700007000000050.00%3200000.2500000000
Stats d'équipe Total ou en Moyenne80111620832410465755884788103528769511.21%2801145914.313764101290183345932171923454.96%343900010.5714145162322
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)2920630.8982.27169303646300200.00022918312
2Ondrej PavelecCrunch (Tam)187920.8922.65108722484450000.3333180200
3Jamie PhillipsCrunch (Tam)20000.9621.0756001260000.0000029000
Stats d'équipe Total ou en Moyenne49271550.8972.3928372511311010200.20054747512


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 Link
Adin HillCrunch (Tam)G201996-05-11No198 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Austin CzarnikCrunch (Tam)C241992-12-12No160 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
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$0$No
Byron FroeseCrunch (Tam)C251991-03-12No190 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Chase De LeoCrunch (Tam)C211995-10-25No178 Lbs5 ft9NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$No
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$0$No
Freddie HamiltonCrunch (Tam)C251992-01-01No195 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
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$0$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$0$No
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$0$No
Nathan BastianCrunch (Tam)C/RW191997-12-06Yes205 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Nick EbertCrunch (Tam)D221994-05-10No203 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm500,000$0$0$No
Ondrej PavelecCrunch (Tam)G291987-08-30No218 Lbs6 ft3NoNoNo2Sans RestrictionPro & Farm500,000$0$0$No
Paul PostmaCrunch (Tam)D271989-02-21No195 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm400,000$0$0$No
Reid BoucherCrunch (Tam)LW/RW231993-09-07No190 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm300,000$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$0$No
Spencer WatsonCrunch (Tam)LW/RW201996-04-26Yes170 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Tyler GraovacCrunch (Tam)C231993-04-26No200 Lbs6 ft5NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2924.62197 Lbs6 ft12.00398,276$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt PuempelByron FroeseBorna Rendulic40122
2Francis PerronAustin CzarnikNathan Bastian30122
3Spencer WatsonFreddie HamiltonByron Froese20122
4Austin CzarnikKevin PorterFreddie Hamilton10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Duncan SiemensJeff Schultz40122
2Mat BodieNate Guenin30122
3Kevin CzuczmanNick Ebert20122
4Duncan SiemensJeff Schultz10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt PuempelByron FroeseBorna Rendulic60122
2Francis PerronAustin CzarnikNathan Bastian40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Duncan SiemensJeff Schultz60122
2Mat BodieNate Guenin40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Byron FroeseAustin Czarnik60122
2Freddie HamiltonKevin Porter40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Duncan SiemensJeff Schultz60122
2Mat BodieNate Guenin40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Byron Froese60122Duncan SiemensJeff Schultz60122
2Austin Czarnik40122Mat BodieNate Guenin40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Byron FroeseAustin Czarnik60122
2Freddie HamiltonKevin Porter40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Duncan SiemensJeff Schultz60122
2Mat BodieNate Guenin40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt PuempelByron FroeseBorna RendulicDuncan SiemensJeff Schultz
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt PuempelByron FroeseBorna RendulicDuncan SiemensJeff Schultz
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Tyler Graovac, Chase De Leo, Henrik SamuelssonTyler Graovac, Chase De LeoHenrik Samuelsson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Kevin Czuczman, Nick Ebert, Mat BodieKevin CzuczmanNick Ebert, Mat Bodie
Tirs de Pénalité
Byron Froese, Austin Czarnik, Freddie Hamilton, Kevin Porter, Matt Puempel
Gardien
#1 : Ondrej Pavelec, #2 : Adin Hill


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
1Americans5500000016792200000094533000000734101.00016294503535334311036041441715104296610435720.00%33293.94%0796144055.28%771141554.49%38368755.75%12178531052337571295
2Bears21001000743100010003211100000042241.000714210053533433036041441715582534359333.33%16381.25%1796144055.28%771141554.49%38368755.75%12178531052337571295
3Bruins1010000001-1000000000001010000001-100.00000000535334331360414417152161021500.00%5180.00%0796144055.28%771141554.49%38368755.75%12178531052337571295
4Checkers2200000011292200000011290000000000041.000111829015353343713604144171539245564125.00%130100.00%1796144055.28%771141554.49%38368755.75%12178531052337571295
5Comets75200000231763210000010644310000013112100.714234265005353343181360414417151344812215846613.04%48589.58%0796144055.28%771141554.49%38368755.75%12178531052337571295
6Devils916001011334-2140300001314-11513001001020-1040.22213233600535334315936041441715265841811915559.09%681577.94%1796144055.28%771141554.49%38368755.75%12178531052337571295
7Marlies33000000164121100000051422000000113861.000163046005353343127360414417155716408510440.00%18194.44%0796144055.28%771141554.49%38368755.75%12178531052337571295
8Monsters412010001112-12020000047-32100100075240.500111930005353343713604144171511637668223313.04%33584.85%0796144055.28%771141554.49%38368755.75%12178531052337571295
9Penguins1010000023-11010000023-10000000000000.000246005353343243604144171520714208112.50%7185.71%0796144055.28%771141554.49%38368755.75%12178531052337571295
10Phantoms11000000321000000000001100000032121.000358005353343213604144171518723254250.00%80100.00%0796144055.28%771141554.49%38368755.75%12178531052337571295
11Rocket320001008531000010012-12200000073450.8338142200535334372360414417156721416114214.29%16287.50%0796144055.28%771141554.49%38368755.75%12178531052337571295
12Senators30200100811-330200100811-30000000000010.167814220053533436836041441715601536752229.09%17288.24%1796144055.28%771141554.49%38368755.75%12178531052337571295
13Sound Tigers1010000034-11010000034-10000000000000.0003470053533433936041441715194619900.00%30100.00%0796144055.28%771141554.49%38368755.75%12178531052337571295
14Thunderbirds4400000018513220000009182200000094581.000183452015353343162360414417159121669327933.33%29196.55%1796144055.28%771141554.49%38368755.75%12178531052337571295
Total472515023021421152723910012016857112416501101745816590.628142254396055353343120136041441715110133176410572754616.73%3214087.54%5796144055.28%771141554.49%38368755.75%12178531052337571295
16Wolf Pack1000000134-1000000000001000000134-110.500347005353343353604144171532914324125.00%7271.43%0796144055.28%771141554.49%38368755.75%12178531052337571295
_Since Last GM Reset281410002028469151466001014336714840010141338320.57184150234035353343751360414417156351984366251673118.56%1852288.11%1796144055.28%771141554.49%38368755.75%12178531052337571295
_Vs Conference23413022025075-251209011012341-181144011012734-7160.3485087137005353343478360414417156091943845001391712.23%1642982.32%3796144055.28%771141554.49%38368755.75%12178531052337571295
_Vs Division2113011005365-121103011002632-61010000002733-650.1195391144015353343450360414417155671753834601161613.79%1552683.23%3796144055.28%771141554.49%38368755.75%12178531052337571295

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4759L114225439612011101331764105705
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4725152302142115
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2391012016857
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2416511017458
Derniers 10 Matchs
WLOTWOTL SOWSOL
350101
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2754616.73%3214087.54%5
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
360414417155353343
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
796144055.28%771141554.49%38368755.75%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12178531052337571295


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 - 2018-09-2175Crunch4Devils3WSommaire du Match
18 - 2018-09-2285Comets3Crunch5WSommaire du Match
24 - 2018-09-28107Crunch3Marlies2WSommaire du Match
25 - 2018-09-29119Checkers2Crunch6WSommaire du Match
31 - 2018-10-05140Senators4Crunch3LSommaire du Match
32 - 2018-10-06157Senators2Crunch1LSommaire du Match
38 - 2018-10-12187Crunch4Americans3WSommaire du Match
40 - 2018-10-14209Bears2Crunch3WXSommaire du Match
43 - 2018-10-17217Devils4Crunch0LSommaire du Match
45 - 2018-10-19224Crunch4Comets3WSommaire du Match
46 - 2018-10-20239Rocket2Crunch1LXSommaire du Match
50 - 2018-10-24260Crunch0Devils5LSommaire du Match
52 - 2018-10-26265Devils2Crunch1LSommaire du Match
53 - 2018-10-27283Crunch5Thunderbirds2WSommaire du Match
59 - 2018-11-02308Crunch4Monsters3WXSommaire du Match
60 - 2018-11-03318Crunch3Monsters2WSommaire du Match
66 - 2018-11-09350Devils3Crunch2LXXSommaire du Match
67 - 2018-11-10366Americans4Crunch5WSommaire du Match
71 - 2018-11-14384Crunch8Marlies1WSommaire du Match
73 - 2018-11-16396Crunch3Rocket1WSommaire du Match
74 - 2018-11-17401Crunch4Rocket2WSommaire du Match
78 - 2018-11-21429Crunch4Thunderbirds2WSommaire du Match
80 - 2018-11-23439Crunch3Phantoms2WSommaire du Match
81 - 2018-11-24457Penguins3Crunch2LSommaire du Match
85 - 2018-11-28468Crunch2Devils3LXSommaire du Match
87 - 2018-11-30476Comets1Crunch5WSommaire du Match
88 - 2018-12-01489Thunderbirds0Crunch4WSommaire du Match
92 - 2018-12-05511Crunch5Comets3WSommaire du Match
94 - 2018-12-07518Sound Tigers4Crunch3LSommaire du Match
95 - 2018-12-08535Marlies1Crunch5WSommaire du Match
99 - 2018-12-12554Crunch2Devils4LSommaire du Match
101 - 2018-12-14563Monsters3Crunch2LSommaire du Match
102 - 2018-12-15577Crunch3Comets2WSommaire du Match
106 - 2018-12-19596Crunch1Comets3LSommaire du Match
108 - 2018-12-21605Senators5Crunch4LXSommaire du Match
109 - 2018-12-22626Crunch2Devils5LSommaire du Match
111 - 2018-12-24636Devils5Crunch0LSommaire du Match
115 - 2018-12-28655Thunderbirds1Crunch5WSommaire du Match
116 - 2018-12-29673Americans0Crunch4WSommaire du Match
122 - 2019-01-04685Comets2Crunch0LSommaire du Match
123 - 2019-01-05702Monsters4Crunch2LSommaire du Match
127 - 2019-01-09719Crunch1Americans0WSommaire du Match
129 - 2019-01-11726Crunch3Wolf Pack4LXXSommaire du Match
131 - 2019-01-13752Crunch0Bruins1LSommaire du Match
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
15 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
177,650$ 115,500$ 147,708$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 110,124$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 63 1,111$ 69,993$




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
1347251502302142115272391001201685711241650110174581659142254396055353343120136041441715110133176410572754616.73%3214087.54%5796144055.28%771141554.49%38368755.75%12178531052337571295
Total Saison Régulière47251502302142115272391001201685711241650110174581659142254396055353343120136041441715110133176410572754616.73%3214087.54%5796144055.28%771141554.49%38368755.75%12178531052337571295
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