Chill

GP: 82 | W: 42 | L: 36 | OTL: 4 | P: 88
GF: 266 | GA: 276 | PP%: 16.18% | PK%: 80.25%
DG: Yvon Bergeron | Morale : 50 | Moyenne d'Équipe : 43
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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
1Drake CaggiulaXXX100.00694383785763635635506264483936050590
2Filip ChlapikX100.00533589666753374958504861483532050530
3Michael LattaXX100.00576666677148444482424563434337050520
4Joel VerminXX100.00493588756352354145483369473734050510
5A.J. Greer (R)X100.00594360627156374435523561483734050500
6Justin Auger (R)X100.00503595608449353535353557483532050470
7Tobias LindbergXX100.00453577627550313335343270463532050470
8T.J. Tynan (R)X100.00463594754645333335333356473230050450
9Adam GaudetteX100.00453595635154353544353556483532050450
10Samuel Kurker (R)X100.00414545457039394145414145433230050440
11Keegan Kolesar (R)X100.00414343437840404143414143423230050440
12Cody GoloubefX100.00555078646559434335463967474642050550
13Joshua Mahura (R)X100.00434343435843434343434343433230050440
14Luke Green (R)X100.00434343436143434343434343433230050440
15Markus Niemelainen (R)X100.00434343436743434343434343433230050440
16Matthew Cairns (R)X100.00434343436843434343434343433230050440
17Chris Martenet (R)X100.00384040407237373840383840393230050420
Rayé
1Thomas Novak (R)X100.00414343435540404143414143423230050420
2Yan Pavel Laplante (R)X100.00394343435437373943393943413230050410
3Filip Ahl (R)XX100.00384040408037373840383840393230050410
4Todd Burgess (R)XX100.00404040405540404040404040403230050410
5Dmitry Sokolov (R)XX100.00373737377237373737373737373230050400
6Nikita Korostelev (R)X100.00353737376935353537353537363230050390
7Nolan Stevens (R)X100.00373737375837373737373737373230050390
8Pavel Jenys (R)X100.00333737376633333337333337353230050380
9Adam Marsh (R)X100.00353737374535353537353537363230050380
10Blaine Byron (R)X100.00333737374633333337333337353230050370
11Brian Pinho (R)XX100.00333737375233333337333337353230050370
12Grant Besse (R)X100.00333737375233333337333337353230050370
13Henri Ikonen (R)X100.00333737375733333337333337353230050370
14Victor Crus Rydberg (R)X100.00333737376133333337333337353230050370
15Tom Nilsson (R)X100.00364040405335353640363640383230050400
16Jordan Sambrook (R)X100.00353737373735353537353537363230050370
MOYENNE D'ÉQUIPE100.0042405348624238394139384741343105043
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
1Thomas McCollum100.0048454277473939453956553532050460
2Pheonix Copley100.0027456274304343334362603734050450
Rayé
1Kent Simpson100.0040454274393737383737363532050420
2Kristian Oldham (R)100.0036373670363535353535353230050390
MOYENNE D'ÉQUIPE100.003843467438393938394847353205043
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Filip ChlapikChill (Nas)C7931508113140651752436317712.76%27158220.03109195923922461813257.28%162700011.0237000665
2Joel VerminChill (Nas)LW/RW82273663-12220691592124013512.74%26147017.945914452470001922048.51%10100000.8604000413
3Cody GoloubefChill (Nas)D821644600420121101127429612.60%114179521.9061218762420221200330.00%000000.6700000234
4Michael LattaChill (Nas)C/RW74232750176201431271954613611.79%20129117.4666124221702241057164.94%57900000.7736211167
5A.J. GreerChill (Nas)LW8218325077820201116199391409.05%34127415.54257141320002542141.33%15000000.7812004533
6Drake CaggiulaChill (Nas)C/LW/RW2719193861557885116428216.38%1758821.793101314772025663241.15%64400211.2902001514
7Justin AugerChill (Nas)RW82151934-22356469100388115.00%24122614.96257111410000300250.62%8100000.5503000011
8T.J. TynanChill (Nas)C82112031-614039152103338110.68%13121414.8122491250001443138.09%122600000.5111000122
9Tobias LindbergChill (Nas)LW/RW5612162801203474110306210.91%2092316.48235141080000353252.54%5900000.6100000112
10Adam GaudetteChill (Nas)C78131326-9401811192236314.13%14100912.94000030000292046.24%81100000.5211000012
11Neal PionkNashvilleD24322251220026364113327.32%3550621.1128102377000135000.00%000000.9900000110
12Joshua MahuraChill (Nas)D824913-9840130183071413.33%52131816.0801158300011170144.44%2700000.2001000020
13Luke GreenChill (Nas)D8221113-8800881618111911.11%41142217.35123716100001110050.00%200000.1800000001
14Matthew CairnsChill (Nas)D8221113346010920237118.70%65133816.3202229300001000038.46%1300000.1900000010
15Keegan KolesarChill (Nas)RW82426-12355711634113611.76%67469.10011138000030048.94%4700100.1600010001
16Markus NiemelainenChill (Nas)D23134-521536263516.67%1544519.38011463000049000.00%000000.1800001000
17Samuel KurkerChill (Nas)RW23011-11159212390.00%31386.00011319000090042.86%3500000.1400001000
18Chris MartenetChill (Nas)D23011-71402522250.00%434915.19000118000034000.00%000000.0600000000
Stats d'équipe Total ou en Moyenne1145201336537-2961165132612811663453118412.09%5301864216.28417711833020944610221304281549.13%540200320.58927228262935
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
1Thomas McCollumChill (Nas)62292530.8753.5733122019715760510.743356030100
2Pheonix CopleyChill (Nas)51100.9172.332320091080000.0000123000
Stats d'équipe Total ou en Moyenne67302630.8783.4935452020616840510.743356153100


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
A.J. GreerChill (Nas)LW201996-12-14Yes204 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm725,000$72,500$0$NoLien
Adam GaudetteChill (Nas)C211996-10-03No170 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Adam MarshChill (Nas)LW201997-08-22Yes160 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Blaine ByronChill (Nas)C221995-02-21Yes163 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Brian PinhoChill (Nas)C/RW221995-05-11Yes173 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Chris MartenetChill (Nas)D211996-09-25Yes212 Lbs6 ft7NoNoNo3Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Cody GoloubefChill (Nas)D271989-11-30No200 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm900,000$90,000$0$NoLien
Dmitry SokolovChill (Nas)LW/RW191998-04-14Yes208 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Drake CaggiulaChill (Nas)C/LW/RW231994-06-20No185 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm925,000$925,000$0$NoLien
Filip AhlChill (Nas)LW/RW201997-06-12Yes225 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Filip ChlapikChill (Nas)C201997-06-03No196 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm825,000$82,500$0$NoLien
Grant BesseChill (Nas)RW231994-07-14Yes177 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Henri IkonenChill (Nas)LW231994-04-17Yes184 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm625,000$62,500$0$NoLien
Joel VerminChill (Nas)LW/RW251992-02-05No192 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm635,000$63,500$0$NoLien
Jordan SambrookChill (Nas)D191998-04-11Yes193 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Joshua MahuraChill (Nas)D191998-05-05Yes185 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Justin AugerChill (Nas)RW231994-05-14Yes232 Lbs6 ft6NoNoNo2Avec RestrictionPro & Farm625,000$62,500$0$NoLien
Keegan KolesarChill (Nas)RW201997-04-08Yes223 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Kent SimpsonChill (Nas)G251992-03-26No198 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm550,000$55,000$0$NoLien
Kristian OldhamChill (Nas)G201997-06-25Yes190 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Luke GreenChill (Nas)D191998-01-12Yes190 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm690,000$69,000$0$NoLien
Markus NiemelainenChill (Nas)D191998-06-08Yes200 Lbs6 ft5NoNoNo4Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Matthew CairnsChill (Nas)D191998-04-27Yes205 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Michael LattaChill (Nas)C/RW261991-05-25No207 Lbs6 ft0YesNoNo2Avec RestrictionPro & Farm570,000$57,000$0$NoLien
Nikita KorostelevChill (Nas)RW201997-02-08Yes201 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Nolan StevensChill (Nas)C211996-07-22Yes183 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm842,500$84,250$0$NoLien
Pavel JenysChill (Nas)C211996-04-22Yes192 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm655,000$65,500$0$NoLien
Pheonix CopleyChill (Nas)G251992-01-18No196 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm767,000$76,700$0$NoLien
Samuel KurkerChill (Nas)RW231994-04-08Yes201 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm825,000$82,500$0$NoLien
T.J. TynanChill (Nas)C251992-02-25Yes165 Lbs5 ft8NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Thomas McCollumChill (Nas)G271989-12-07No205 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm450,000$45,000$0$NoLien
Thomas NovakChill (Nas)C201997-04-28Yes179 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Tobias LindbergChill (Nas)LW/RW221995-07-22No217 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm660,000$66,000$0$NoLien
Todd BurgessChill (Nas)C/RW211996-04-03Yes178 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Tom NilssonChill (Nas)D241993-08-19Yes176 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm825,000$82,500$0$NoLien
Victor Crus RydbergChill (Nas)C221995-03-21Yes190 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Yan Pavel LaplanteChill (Nas)C221995-04-23Yes178 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3721.84193 Lbs6 ft12.68653,905$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Joel VerminDrake CaggiulaMichael Latta40122
2A.J. GreerFilip ChlapikTobias Lindberg30122
3Adam GaudetteT.J. TynanJustin Auger20122
4Drake CaggiulaAdam GaudetteKeegan Kolesar10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Cody GoloubefJoshua Mahura40122
2Matthew CairnsMarkus Niemelainen30122
3Luke GreenChris Martenet20122
4Cody GoloubefJoshua Mahura10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Joel VerminDrake CaggiulaMichael Latta60122
2A.J. GreerFilip ChlapikTobias Lindberg40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Cody GoloubefJoshua Mahura60122
2Matthew CairnsMarkus Niemelainen40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Drake CaggiulaFilip Chlapik60122
2Michael LattaJoel Vermin40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Cody GoloubefJoshua Mahura60122
2Matthew CairnsMarkus Niemelainen40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Drake Caggiula60122Cody GoloubefJoshua Mahura60122
2Filip Chlapik40122Matthew CairnsMarkus Niemelainen40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Drake CaggiulaFilip Chlapik60122
2Michael LattaJoel Vermin40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Cody GoloubefJoshua Mahura60122
2Matthew CairnsMarkus Niemelainen40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Joel VerminDrake CaggiulaMichael LattaCody GoloubefJoshua Mahura
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Joel VerminDrake CaggiulaMichael LattaCody GoloubefJoshua Mahura
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Samuel Kurker, Justin Auger, T.J. TynanSamuel Kurker, Justin AugerT.J. Tynan
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Luke Green, Chris Martenet, Matthew CairnsLuke GreenChris Martenet, Matthew Cairns
Tirs de Pénalité
Drake Caggiula, Filip Chlapik, Michael Latta, Joel Vermin, A.J. Greer
Gardien
#1 : Thomas McCollum, #2 : Pheonix Copley


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
1Admirals30300000514-91010000025-32020000039-600.00056110011178701355715716753658930335410110.00%14471.43%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
2Baby Hawks402000111214-22020000057-22000001177030.375121830001117870131007157167536511333388715320.00%19289.47%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
3Bears20200000311-81010000027-51010000014-300.000347001117870135671571675365642026471218.33%13469.23%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
4Bruins21000001770110000003211000000145-130.75071118001117870134671571675365561326405240.00%13284.62%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
5Cabaret Lady Mary Ann22000000853110000004311100000042241.00081220001117870139871571675365508304413215.38%4175.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
6Caroline22000000844110000004311100000041341.00081523001117870137071571675365621510499333.33%5180.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
7Chiefs51400000916-72020000047-33120000059-420.2009152400111787013102715716753651354145981317.69%20670.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
8Comets3110100013103211000008621000100054140.6671320330011178701383715716753656518247010110.00%12375.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
9Cougars2110000078-11010000026-41100000052320.50071219001117870134471571675365762118365120.00%9188.89%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
10Crunch21001000954110000004131000100054141.000914230011178701362715716753654722123511218.18%6266.67%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
11Heat330000001468110000006152200000085361.0001424380011178701398715716753655919264520420.00%120100.00%11128235447.92%1192244148.83%683134250.89%1985134818896251091549
12Jayhawks30300000617-1120200000511-61010000016-500.000691500111787013657157167536594182737400.00%11372.73%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
13Las Vegas311000011113-21000000123-121100000910-130.50011182900111787013857157167536510136285911218.18%13284.62%11128235447.92%1192244148.83%683134250.89%1985134818896251091549
14Manchots211000006601010000035-21100000031220.500691500111787013357157167536534910429222.22%5180.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
15Marlies2110000034-11010000013-21100000021120.50035800111787013317157167536556192444700.00%70100.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
16Minnesota41100020171252100001010552010001077060.750172744001117870131237157167536515442388313215.38%18288.89%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
17Monarchs32100000972211000005411100000043140.667915240011178701379715716753657828185411436.36%90100.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
18Monsters21001000752110000002111000100054141.000711180011178701359715716753654019123710110.00%6183.33%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
19Monsters403000101019-920200000411-72010001068-220.2501016260011178701391715716753651514732761800.00%15566.67%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
20Oceanics403000011521-620100001811-320200000710-310.125152338001117870131037157167536514444247516425.00%12558.33%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
21Oil Kings32100000963211000005411100000042240.667915240011178701371715716753655823294910110.00%80100.00%11128235447.92%1192244148.83%683134250.89%1985134818896251091549
22Phantoms22000000963110000005321100000043141.000914230011178701349715716753655416163610220.00%8275.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
23Rocket22000000725110000003121100000041341.00071219001117870136771571675365295173812433.33%5260.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
24Senators2110000010911010000057-21100000052320.500101828101117870135271571675365752012357228.57%6350.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
25Sharks321000001115-41100000054121100000611-540.667111829001117870131017157167536511444246320210.00%120100.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
26Sound Tigers22000000734110000005321100000020241.000713200111178701372715716753653412133311218.18%40100.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
27Spiders2110000057-21010000006-61100000051420.500581300111787013637157167536566222734500.00%10370.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
28Stars52300000131123210000012752020000014-340.400132134001117870131487157167536511432398730310.00%17382.35%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
29Thunder2020000059-41010000035-21010000024-200.0005914001117870133571571675365481320388225.00%10460.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549
Total82353603044266276-1041172100012133146-13411815030321331303880.53726643069612111787013221171571675365232270572215713405516.18%3146280.25%41128235447.92%1192244148.83%683134250.89%1985134818896251091549
31Wolf Pack220000001147110000006421100000050541.000111829011117870136871571675365621624465120.00%110100.00%11128235447.92%1192244148.83%683134250.89%1985134818896251091549
_Since Last GM Reset82353603044266276-1041172100012133146-13411815030321331303880.53726643069612111787013221171571675365232270572215713405516.18%3146280.25%41128235447.92%1192244148.83%683134250.89%1985134818896251091549
_Vs Conference35161601002113128-151779000015570-1518970100158580360.514113182295121117870139047157167536510143253096781462617.81%1402979.29%11128235447.92%1192244148.83%683134250.89%1985134818896251091549
_Vs Division16660000256497833000012528-383300001312110140.43856931491011178701343571571675365437121159310681522.06%601575.00%01128235447.92%1192244148.83%683134250.89%1985134818896251091549

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8288L126643069622112322705722157112
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8235363044266276
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4117210012133146
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4118153032133130
Derniers 10 Matchs
WLOTWOTL SOWSOL
460000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3405516.18%3146280.25%4
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
71571675365111787013
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
1128235447.92%1192244148.83%683134250.89%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1985134818896251091549


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
2 - 2018-10-046Chill5Wolf Pack0WSommaire du Match
4 - 2018-10-0622Chill2Sound Tigers0WSommaire du Match
7 - 2018-10-0939Heat1Chill6WSommaire du Match
9 - 2018-10-1155Oceanics6Chill4LSommaire du Match
11 - 2018-10-1366Sound Tigers3Chill5WSommaire du Match
13 - 2018-10-1577Minnesota1Chill5WSommaire du Match
17 - 2018-10-19101Chill3Heat2WSommaire du Match
18 - 2018-10-20113Chill4Oil Kings2WSommaire du Match
21 - 2018-10-23126Sharks4Chill5WSommaire du Match
23 - 2018-10-25136Chill5Spiders1WSommaire du Match
25 - 2018-10-27150Oil Kings2Chill5WSommaire du Match
28 - 2018-10-30173Las Vegas3Chill2LXXSommaire du Match
30 - 2018-11-01185Chill2Thunder4LSommaire du Match
32 - 2018-11-03202Bruins2Chill3WSommaire du Match
36 - 2018-11-07225Chill2Monsters5LSommaire du Match
39 - 2018-11-10244Chill0Stars1LSommaire du Match
41 - 2018-11-12263Chill0Admirals4LSommaire du Match
42 - 2018-11-13272Chill5Sharks2WSommaire du Match
44 - 2018-11-15284Chill1Jayhawks6LSommaire du Match
46 - 2018-11-17300Monarchs1Chill4WSommaire du Match
48 - 2018-11-19314Thunder5Chill3LSommaire du Match
50 - 2018-11-21326Chiefs3Chill2LSommaire du Match
52 - 2018-11-23344Chill2Chiefs4LSommaire du Match
54 - 2018-11-25360Admirals5Chill2LSommaire du Match
56 - 2018-11-27371Monsters6Chill1LSommaire du Match
58 - 2018-11-29386Jayhawks6Chill2LSommaire du Match
60 - 2018-12-01405Baby Hawks2Chill1LSommaire du Match
62 - 2018-12-03414Crunch1Chill4WSommaire du Match
65 - 2018-12-06437Chill5Comets4WXSommaire du Match
67 - 2018-12-08453Chill5Heat3WSommaire du Match
70 - 2018-12-11471Senators7Chill5LSommaire du Match
72 - 2018-12-13483Comets5Chill4LSommaire du Match
74 - 2018-12-15502Spiders6Chill0LSommaire du Match
76 - 2018-12-17515Chill5Senators2WSommaire du Match
77 - 2018-12-18522Chill4Baby Hawks3WXXSommaire du Match
79 - 2018-12-20532Chill4Phantoms3WSommaire du Match
81 - 2018-12-22545Chill4Bruins5LXXSommaire du Match
86 - 2018-12-27573Stars2Chill6WSommaire du Match
88 - 2018-12-29593Wolf Pack4Chill6WSommaire du Match
90 - 2018-12-31599Chill1Bears4LSommaire du Match
91 - 2019-01-01613Phantoms3Chill5WSommaire du Match
94 - 2019-01-04630Chill5Cougars2WSommaire du Match
95 - 2019-01-05640Chill4Rocket1WSommaire du Match
97 - 2019-01-07652Chill2Marlies1WSommaire du Match
99 - 2019-01-09668Chill3Baby Hawks4LXXSommaire du Match
100 - 2019-01-10675Chill5Monsters4WXSommaire du Match
103 - 2019-01-13699Chill4Caroline1WSommaire du Match
105 - 2019-01-15716Bears7Chill2LSommaire du Match
107 - 2019-01-17730Oceanics5Chill4LXXSommaire du Match
109 - 2019-01-19747Cabaret Lady Mary Ann3Chill4WSommaire du Match
111 - 2019-01-21756Chill4Monsters3WXXSommaire du Match
113 - 2019-01-23768Chill5Las Vegas7LSommaire du Match
122 - 2019-02-01782Chill4Cabaret Lady Mary Ann2WSommaire du Match
123 - 2019-02-02798Stars3Chill2LSommaire du Match
126 - 2019-02-05817Jayhawks5Chill3LSommaire du Match
128 - 2019-02-07832Stars2Chill4WSommaire du Match
130 - 2019-02-09843Chill0Chiefs4LSommaire du Match
131 - 2019-02-10852Chiefs4Chill2LSommaire du Match
133 - 2019-02-12870Cougars6Chill2LSommaire du Match
135 - 2019-02-14881Rocket1Chill3WSommaire du Match
137 - 2019-02-16901Chill4Las Vegas3WSommaire du Match
140 - 2019-02-19923Chill1Stars3LSommaire du Match
142 - 2019-02-21936Monarchs3Chill1LSommaire du Match
144 - 2019-02-23951Monsters5Chill3LSommaire du Match
146 - 2019-02-25965Oil Kings2Chill0LSommaire du Match
147 - 2019-02-26975Chill3Chiefs1WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2019-03-01996Chill4Oceanics5LSommaire du Match
152 - 2019-03-031015Chill3Minnesota2WXXSommaire du Match
154 - 2019-03-051024Minnesota4Chill5WXXSommaire du Match
158 - 2019-03-091057Caroline3Chill4WSommaire du Match
161 - 2019-03-121079Chill3Admirals5LSommaire du Match
163 - 2019-03-141091Chill4Monarchs3WSommaire du Match
165 - 2019-03-161110Chill1Sharks9LSommaire du Match
168 - 2019-03-191128Marlies3Chill1LSommaire du Match
170 - 2019-03-211141Manchots5Chill3LSommaire du Match
172 - 2019-03-231154Chill3Oceanics5LSommaire du Match
174 - 2019-03-251174Chill4Minnesota5LSommaire du Match
178 - 2019-03-291198Chill3Manchots1WSommaire du Match
179 - 2019-03-301210Monsters1Chill2WSommaire du Match
182 - 2019-04-021229Chill5Crunch4WXSommaire du Match
184 - 2019-04-041249Comets1Chill4WSommaire du Match
186 - 2019-04-061266Baby Hawks5Chill4LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3818
Assistance61,50330,554
Assistance PCT75.00%74.52%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2245 - 74.84% 70,417$2,887,086$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,042,235$ 3,251,950$ 3,251,950$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
17,390$ 3,042,235$ 37 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 17,390$ 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
201882353603044266276-1041172100012133146-134118150303213313038826643069612111787013221171571675365232270572215713405516.18%3146280.25%41128235447.92%1192244148.83%683134250.89%1985134818896251091549
Total Saison Régulière82353603044266276-1041172100012133146-134118150303213313038826643069612111787013221171571675365232270572215713405516.18%3146280.25%41128235447.92%1192244148.83%683134250.89%1985134818896251091549