Crunch

GP: 76 | W: 44 | L: 25 | OTL: 7 | P: 95
GF: 219 | GA: 172 | PP%: 14.25% | PK%: 87.62%
DG: Stéphane Lacasse | Morale : 66 | Moyenne d'Équipe : 58
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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 BoucherXX99.00715573827871777350636566557472180670
2Austin CzarnikX99.00635580807070737064636462557272181650
3Byron FroeseX99.00795565757767696974656469556476131650
4Freddie HamiltonX99.00605566707770666360616061557268180620
5Kevin PorterX99.00665566727066696050606060556464181610
6Matt PuempelX100.00605566727972606150606058555454182600
7Tyler GraovacX100.00765563757873606150606060555050135600
8Francis Perron (R)X100.00615566606360755750565756557574181580
9Chase De LeoX100.00615562626360725550555555557273181570
10Henrik SamuelssonX100.00595574627975545550555555555050162560
11Borna RendulicX100.00565555555859595550555555557075154550
12Spencer Watson (R)XX100.00565555555555555550555555555050135530
13Duncan SiemensX100.00735560798071676925616170555353183660
14Paul PostmaX100.00695574707769586925616066556464126630
15Jeff SchultzX100.00595559615959795925595959558381181600
16Mat BodieX100.00625566615865696025606056555353180570
17Nate GueninX100.00555555605555655525555555556566181560
18Kevin CzuczmanX100.00555555605555695525555555555353134540
19Lukas Bengtsson (R)X100.00555556605656575625565656555353137540
20Nick EbertX100.00555555605555645525555555555353179540
Rayé
1Colin GreeningX100.00555555555555555550555555557271157540
2Nathan Bastian (R)XX100.00565555555555555550555555555050155530
3Michael ZalewskiX100.00565555555555555550555555555050120520
4Ryan MaloneX100.00565555555555555550555555555050120520
5Sam HenleyX100.00565555555555555550555555555050120520
6Brandon Crawley (R)X100.00555555605555565525555555555555120530
MOYENNE D'ÉQUIPE99.8161556264646263594358585855606115758
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 Pavelec100.0070727176707069656969558078130690
2Adin Hill100.0060686380656565636763556062175640
Rayé
1Jamie Phillips100.0060696664666665636763556062124620
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/RW7423426521580145161243761569.47%23164022.174141844297213263471150.26%76000010.7913000366
2Austin CzarnikCrunch (Tam)C7628366421240561522095713913.40%18158320.83812206335813493869059.07%152200000.8103000441
3Matt PuempelCrunch (Tam)LW7626376326295681021975511513.20%7135317.8181624443540000385154.46%10100000.9300001284
4Freddie HamiltonCrunch (Tam)C7618274523755103173188501529.57%13154920.3849133725411242573157.89%124200000.5823010234
5Duncan SiemensCrunch (Tam)D6314314561161014480120519411.67%79132321.0081422822581125272410.00%000000.6800101533
6Mat BodieCrunch (Tam)D76631373111210103437026398.57%63152520.071910473360111337100.00%000000.4900002221
7Jeff SchultzCrunch (Tam)D761118291360101064274244014.86%70160221.099110463310110358200.00%000000.3600110215
8Kevin PorterCrunch (Tam)C76111425670107212711237979.82%991212.010115460001644151.80%69300000.5500002113
9Francis PerronCrunch (Tam)LW761110215655725811528849.57%12112514.8101198300001403046.02%11300000.3700001122
10Byron FroeseCrunch (Tam)C321192012480636381216013.58%449915.6140427990000732159.96%48200000.8013000122
11Nathan BastianCrunch (Tam)C/RW605131811551565326710487.46%783813.9724612134000002040.48%4200000.4300011011
12Nate GueninCrunch (Tam)D762161822980101373312226.06%47112914.8603391060000187000.00%000000.3200000030
13Nick EbertCrunch (Tam)D74214161062080351781711.76%4190112.18000060000102010.00%000000.3500000010
14Paul PostmaCrunch (Tam)D3631215530103018418467.32%2354615.19257331280000111000.00%000000.5500020012
15Borna RendulicCrunch (Tam)RW69581310561089405615438.93%394813.7422420216000000055.93%5900000.2700001110
16Chase De LeoCrunch (Tam)C76189-51202334246254.17%64225.550114420001560050.97%20600000.4300000000
17Spencer WatsonCrunch (Tam)LW/RW253364100151421101514.29%227911.1700007000120246.15%1300000.4300000002
18Tyler GraovacCrunch (Tam)C47246-63203740398365.13%43838.160112621011370056.42%17900000.3100000001
19Colin GreeningCrunch (Tam)LW4832544010101651318.75%22274.7400001000051060.87%2300000.4400000100
20Lukas BengtssonCrunch (Tam)D3722412401812132115.38%202897.8101127000026000.00%000000.2800000010
21Henrik SamuelssonCrunch (Tam)C68314-340922151920.00%12834.172023390002781062.14%10300000.2800000100
22Kevin CzuczmanCrunch (Tam)D471230535461425784.00%2749510.54000739000058000.00%000000.1200000001
23Paul MartinTampa Bay LightningD3000000000010.00%062.000000200000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne1367191340531217109795145513091776517126010.75%4811986514.5354941484963213681451294438955.89%553800010.53412259264038
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
1Ondrej PavelecCrunch (Tam)47231940.9012.2228062910410520510.72711470722
2Adin HillCrunch (Tam)3021630.9002.22173203646370200.00022947312
3Jamie PhillipsCrunch (Tam)20000.9621.0756001260000.0000029000
Stats d'équipe Total ou en Moyenne79442570.9012.21459421216917150710.6151376761034


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
1Reid BoucherAustin CzarnikFreddie Hamilton40122
2Matt PuempelByron FroeseKevin Porter30122
3Francis PerronFreddie HamiltonSpencer Watson20122
4Byron FroeseKevin PorterReid Boucher10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Duncan SiemensPaul Postma40122
2Jeff SchultzMat Bodie30122
3Nate GueninNick Ebert20122
4Kevin CzuczmanDuncan Siemens10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Reid BoucherAustin CzarnikFreddie Hamilton60122
2Matt PuempelByron FroeseKevin Porter40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Duncan SiemensPaul Postma60122
2Jeff SchultzMat Bodie40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Reid BoucherAustin Czarnik60122
2Byron FroeseFreddie Hamilton40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Duncan SiemensPaul Postma60122
2Jeff SchultzMat Bodie40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Reid Boucher60122Duncan SiemensPaul Postma60122
2Austin Czarnik40122Jeff SchultzMat Bodie40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Reid BoucherAustin Czarnik60122
2Byron FroeseFreddie Hamilton40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Duncan SiemensPaul Postma60122
2Jeff SchultzMat Bodie40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Reid BoucherAustin CzarnikByron FroeseDuncan SiemensPaul Postma
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Reid BoucherAustin CzarnikByron FroeseDuncan SiemensPaul Postma
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Tyler Graovac, Chase De Leo, Kevin PorterTyler Graovac, Chase De LeoKevin Porter
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nate Guenin, Nick Ebert, Kevin CzuczmanNate GueninNick Ebert, Kevin Czuczman
Tirs de Pénalité
Reid Boucher, Austin Czarnik, Byron Froese, Freddie Hamilton, Kevin Porter
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
1Americans1283010003221116420000019154641010001367180.7503257890474796082595796916562926185169228791215.19%821087.80%01315230057.17%1227222855.07%613109256.14%199214051686539920480
2Bears21001000743100010003211100000042241.000714210074796083057969165629582534359333.33%16381.25%11315230057.17%1227222855.07%613109256.14%199214051686539920480
3Bruins20100010110100000101011010000001-120.5001010174796086257969165629431430461200.00%13192.31%01315230057.17%1227222855.07%613109256.14%199214051686539920480
4Checkers440000002161522000000112922000000104681.0002135560174796081565796916562974116910810220.00%25292.00%11315230057.17%1227222855.07%613109256.14%199214051686539920480
5Comets1263012003730763101100211476320010016160160.6673768105017479608287579691656292398821227778911.54%77889.61%11315230057.17%1227222855.07%613109256.14%199214051686539920480
6Devils1026001011535-2051300001515-10513001001020-1060.30015274200747960818357969165629282861982076369.52%731678.08%11315230057.17%1227222855.07%613109256.14%199214051686539920480
7Marlies660000002942533000000161153300000013310121.00029538203747960826857969165629120326213314535.71%29196.55%01315230057.17%1227222855.07%613109256.14%199214051686539920480
8Monsters412010001112-12020000047-32100100075240.500111930007479608715796916562911637668223313.04%33584.85%01315230057.17%1227222855.07%613109256.14%199214051686539920480
9Penguins2020000025-31010000023-11010000002-200.0002461074796084157969165629381130491119.09%15193.33%01315230057.17%1227222855.07%613109256.14%199214051686539920480
10Phantoms2110000035-21010000003-31100000032120.50035800747960837579691656295914524114214.29%19194.74%01315230057.17%1227222855.07%613109256.14%199214051686539920480
11Rocket64100100181173110010088033000000103790.75018325001747960813857969165629126477810932412.50%32390.63%01315230057.17%1227222855.07%613109256.14%199214051686539920480
12Senators604001101421-730200100811-330200010610-430.2501423370074796081315796916562911937771345159.80%35682.86%11315230057.17%1227222855.07%613109256.14%199214051686539920480
13Sound Tigers211000008711010000034-11100000053220.500811190074796085857969165629391022361218.33%11190.91%11315230057.17%1227222855.07%613109256.14%199214051686539920480
14Thunderbirds4400000018513220000009182200000094581.000183452017479608162579691656299121669327933.33%29196.55%11315230057.17%1227222855.07%613109256.14%199214051686539920480
Total7638250452221917247381615023111108723382210022111098524950.62521938660511274796081942579691656291716532120416284426314.25%5016287.62%71315230057.17%1227222855.07%613109256.14%199214051686539920480
16Wolf Pack2010000135-21010000001-11000000134-110.2503470074796085957969165629511439507114.29%12375.00%01315230057.17%1227222855.07%613109256.14%199214051686539920480
_Since Last GM Reset5727200242216112635291311012118566192814901211766016680.5961612824431107479608149257969165629125039987611963344814.37%3654487.95%31315230057.17%1227222855.07%613109256.14%199214051686539920480
_Vs Conference32618022226495-3116111011112646-201657011113849-11240.37564107171117479608672579691656298052485486802022210.89%2273783.70%41315230057.17%1227222855.07%613109256.14%199214051686539920480
_Vs Division2816011107079-91403011002837-91413000104242070.12570119189117479608635579691656297172085106081491912.75%2043284.31%41315230057.17%1227222855.07%613109256.14%199214051686539920480

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7695OTL12193866051942171653212041628112
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7638254522219172
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
381615231111087
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
382210221110985
Derniers 10 Matchs
WLOTWOTL SOWSOL
520120
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4426314.25%5016287.62%7
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
579691656297479608
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
1315230057.17%1227222855.07%613109256.14%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
199214051686539920480


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 - 2019-01-16765Crunch3Senators6LSommaire du Match
136 - 2019-01-18774Crunch1Americans2LSommaire du Match
137 - 2019-01-19782Americans3Crunch5WSommaire du Match
139 - 2019-01-21805Crunch2Marlies0WSommaire du Match
141 - 2019-01-23809Rocket5Crunch4LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25817Marlies0Crunch4WSommaire du Match
144 - 2019-01-26832Marlies0Crunch7WSommaire du Match
150 - 2019-02-01856Phantoms3Crunch0LSommaire du Match
151 - 2019-02-02871Americans4Crunch2LSommaire du Match
152 - 2019-02-03884Crunch2Americans1WXSommaire du Match
155 - 2019-02-06890Crunch1Comets2LSommaire du Match
157 - 2019-02-08897Comets4Crunch3LXSommaire du Match
158 - 2019-02-09915Crunch0Penguins2LSommaire du Match
162 - 2019-02-13939Crunch3Rocket0WSommaire du Match
164 - 2019-02-15943Wolf Pack1Crunch0LSommaire du Match
165 - 2019-02-16958Devils1Crunch2WSommaire du Match
168 - 2019-02-19973Crunch6Checkers1WSommaire du Match
169 - 2019-02-20978Crunch4Checkers3WSommaire du Match
172 - 2019-02-23997Comets4Crunch5WXSommaire du Match
173 - 2019-02-241013Crunch5Sound Tigers3WSommaire du Match
176 - 2019-02-271019Crunch2Senators1WXXSommaire du Match
178 - 2019-03-011027Bruins0Crunch1WXXSommaire du Match
179 - 2019-03-021043Comets0Crunch3WSommaire du Match
183 - 2019-03-061064Crunch1Senators3LSommaire du Match
185 - 2019-03-081077Crunch3Americans0WSommaire du Match
186 - 2019-03-091089Americans3Crunch1LSommaire du Match
192 - 2019-03-151117Rocket1Crunch3WSommaire du Match
193 - 2019-03-161130Americans1Crunch2WSommaire du Match
194 - 2019-03-171147Crunch2Comets3LXSommaire du Match



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
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
252,739$ 115,500$ 147,708$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 152,728$ 0 0

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




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
1376382504522219172473816150231111087233822100221110985249521938660511274796081942579691656291716532120416284426314.25%5016287.62%71315230057.17%1227222855.07%613109256.14%199214051686539920480
Total Saison Régulière76382504522219172473816150231111087233822100221110985249521938660511274796081942579691656291716532120416284426314.25%5016287.62%71315230057.17%1227222855.07%613109256.14%199214051686539920480
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