Rocket

GP: 82 | W: 25 | L: 51 | OTL: 6 | P: 56
GF: 223 | GA: 310 | PP%: 16.77% | PK%: 78.45%
DG: Simon Deschamps | Morale : 50 | Moyenne d'Équipe : 45
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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
1Paul CareyXXX100.00623586726955485146465662484541050560
2Landon FerraroXXX100.00504395675349364535385254484439050500
3Ryan Lomberg (R)X100.00595053675747354235483560483532050490
4Andrew Crescenzi (R)X100.00533573707348353556353560483532050480
5Chase Balisy (R)XX100.00513595765451353541353566483532050480
6Brian Hart (R)X100.00414545457139394145414145433230050440
7Fredrik Karlstrom (R)X100.00434343435443434343434343433230050440
8Zach O'Brien (R)X100.00414545456739394145414145433230050440
9Auguste Impose (R)X100.00434545455442424345434345443230050440
10Brandon Duhaime (R)XX100.00404040407040404040404040403230050420
11Max Gaede (R)X100.00394343436437373943393943413230050420
12Andrew Yogan (R)XX100.00364040407135353640363640383230050400
13Scott MayfieldX100.00664372627861464735504372484136050580
14Taylor FedunX100.00523584646657364135493267484440050540
15Julian MelchioriX100.00553584597257353435373171473734050530
16Brian LashoffX100.00503595607344353135303268484741050520
17Kurtis MacDermid (R)X100.00695659608048404135394355483532050520
18Keegan Kanzig (R)X100.00394343438737373943393943413230050440
Rayé
1Mike Winther (R)X100.00414545455139394145414145433230050430
2Julien Pelletier (R)X100.00364040405335353640363640383230050390
3Markus Soberg (R)XX100.00333737375933333337333337353230050370
4Alexander Peters (R)X100.00394343436937373943393943413230050430
5Guillaume Gelinas (R)X100.00414545455739394145414145433230050430
6Andrew O'Brien (R)XX100.00364040406635353640363640383230050410
7Michael Downing (R)X100.00364040406235353640363640383230050400
8Eric Roy (R)X100.00333737375633333337333337353230050380
MOYENNE D'ÉQUIPE100.0046415651654338394139395043353205046
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
1Joni Ortio100.0044458269454344454259584036050490
2Jeff Glass100.0041458678404646394565453532050490
Rayé
1Fredrik Pettersson-Wentzel (R)100.0035373561343333333333333230050370
2Olivier Roy (R)100.0035373565343333333333333230050370
MOYENNE D'ÉQUIPE100.003941606838393938384842353205043
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Johnston68726876786171CAN611500,000$


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
1Brett ConnollyMontrealLW/RW473736733145591762595318814.29%11101921.701012225715910161328350.18%27100011.4358001573
2Andrew CrescenziRocket (Mon)C82212849-14300651932004713110.50%16141717.28412165123711211103057.61%140600100.6913000323
3Brian LashoffRocket (Mon)D8212364814604810194386812.77%122139717.04448281190000121210.00%100000.6900000202
4Taylor FedunRocket (Mon)D71153348-313606110989385916.85%125160722.648917552030110237010.00%000000.6000000222
5Julian MelchioriRocket (Mon)D82143347-3628047112117357811.97%132174421.287815612190113265000.00%200000.5400000011
6Landon FerraroRocket (Mon)C/LW/RW78192645-1695381261705513511.18%20161720.74110114721402292841143.12%109000000.5627010205
7Chase BalisyRocket (Mon)C/RW82103444-88028124161661286.21%22142217.35110112924511281820150.22%22900000.6204000111
8Paul CareyRocket (Mon)C/LW/RW33212243143156987121449617.36%1970521.376410219200011213248.27%86800101.2224001513
9Auguste ImposeRocket (Mon)C82162339-9683079127127408612.60%13112813.7622410421011444048.29%99400000.6900105151
10Ryan LombergRocket (Mon)LW82182139-3210152061331633811311.04%17151018.424101437244101102511045.78%16600000.5236001240
11Kurtis MacDermidRocket (Mon)D8092837-2713620250509330589.68%77156119.524812401970114207100.00%000000.4700202031
12Scott MayfieldRocket (Mon)D53926351367151184966283913.64%69114621.645914311470003140000.00%000000.6100020215
13Brian HartRocket (Mon)RW82181129-163956764114276915.79%8117114.282138760000272054.55%7700000.5000100414
14Zach O'BrienRocket (Mon)RW82101222-18500734581265312.35%4123915.1124613186000050047.37%7600010.3600000200
15Fredrik KarlstromRocket (Mon)C8291221-14340717674194512.16%984410.3010142210111301047.52%78500000.5000000011
16Brandon DuhaimeRocket (Mon)LW/RW8241317-1742083215219457.69%7125415.3012331390001821143.75%6400000.2700000002
17Brian FlynnMontrealC/LW/RW104111572043231134112.90%321321.341344260005412068.46%27900001.4111000010
18Connor MurphyMontrealD2331215-10671577463811277.89%2350521.993472365000073010.00%000000.5900210011
19Max GaedeRocket (Mon)RW827714-15180522147102514.89%76277.6600014000000043.24%3700000.4500000111
20Keegan KanzigRocket (Mon)D822111351202015321246158.33%64130415.900114590001141100.00%000000.2000101010
21Andrew YoganRocket (Mon)C/LW68268-153404314267227.69%685912.64000050000230041.03%3900000.1900000001
22Alexander PetersRocket (Mon)D153258280321261650.00%1224516.37000115000011010.00%000000.4100000010
23Mike WintherRocket (Mon)C53145-5401518198105.26%32975.620334570001390046.02%17600000.3400000000
24Andrew O'BrienRocket (Mon)LW/D2000-340400000.00%23015.370000000002000.00%100000.0000000000
25Greg PaterynMontrealD1000-460142340.00%12323.230002500001000.00%000000.0000000000
26Guillaume GelinasRocket (Mon)D60001401845400.00%510317.2600003000010000.00%000000.0000000000
27Markus SobergRocket (Mon)LW/RW1000-100000000.00%088.200000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne1525264447711-2111057125179316652179666154112.12%7972500916.406611618253427906713552692301250.13%656100220.5714337411323437
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
1Joni OrtioRocket (Mon)82255060.8843.6946832128824760210.80826820323
2Jeff GlassRocket (Mon)110100.8703.9528900191460000.0000082000
Stats d'équipe Total ou en Moyenne93255160.8833.7049732130726220210.808268282323


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
Alexander PetersRocket (Mon)D211996-07-02Yes207 Lbs6 ft3NoNoNo2Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Andrew CrescenziRocket (Mon)C251992-07-29Yes207 Lbs6 ft5YesNoNo5Avec RestrictionPro & Farm450,000$45,000$0$NoLien
Andrew O'BrienRocket (Mon)LW/D241992-11-21Yes200 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm635,000$63,500$0$NoLien
Andrew YoganRocket (Mon)C/LW251991-12-04Yes203 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Auguste ImposeRocket (Mon)C201997-06-18Yes180 Lbs5 ft10NoNoNo3Contrat d'EntréePro & Farm825,000$82,500$0$NoLien
Brandon DuhaimeRocket (Mon)LW/RW201997-05-22Yes203 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Brian HartRocket (Mon)RW231993-11-25Yes203 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm635,000$63,500$0$NoLien
Brian LashoffRocket (Mon)D271990-07-16No219 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm775,000$77,500$0$NoLien
Chase BalisyRocket (Mon)C/RW251992-02-02Yes179 Lbs5 ft11YesNoNo6Avec RestrictionPro & Farm500,000$50,000$0$NoLien
Eric RoyRocket (Mon)D221994-10-24Yes180 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Fredrik KarlstromRocket (Mon)C191998-01-12Yes176 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Fredrik Pettersson-WentzelRocket (Mon)G261991-07-23Yes170 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Guillaume GelinasRocket (Mon)D241993-06-14Yes185 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm605,000$60,500$0$NoLien
Jeff GlassRocket (Mon)G311985-11-19No206 Lbs6 ft3YesNoNo4Sans RestrictionPro & Farm575,000$57,500$0$NoLien
Joni OrtioRocket (Mon)G261991-04-16No190 Lbs6 ft1NoNoNo5Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Julian MelchioriRocket (Mon)D251991-12-06No214 Lbs6 ft5NoNoNo6Avec RestrictionPro & Farm725,000$72,500$0$NoLien
Julien PelletierRocket (Mon)LW211996-06-28Yes177 Lbs5 ft11NoNoNo2Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Keegan KanzigRocket (Mon)D221995-02-26Yes241 Lbs6 ft7NoNoNo2Avec RestrictionPro & Farm667,000$66,700$0$NoLien
Kurtis MacDermidRocket (Mon)D231994-03-25Yes233 Lbs6 ft5YesNoNo6Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Landon FerraroRocket (Mon)C/LW/RW261991-08-08No176 Lbs6 ft0YesNoNo6Avec RestrictionPro & Farm450,000$45,000$0$NoLien
Markus SobergRocket (Mon)LW/RW221995-04-22Yes187 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Max GaedeRocket (Mon)RW251992-03-27Yes190 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Michael DowningRocket (Mon)D221995-05-19Yes192 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Mike WintherRocket (Mon)C231994-07-09Yes172 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm825,000$82,500$0$NoLien
Olivier RoyRocket (Mon)G261991-07-12Yes180 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Paul CareyRocket (Mon)C/LW/RW291988-09-24No200 Lbs6 ft1YesNoNo6Sans RestrictionPro & Farm875,000$875,000$0$NoLien
Ryan LombergRocket (Mon)LW221994-12-09Yes187 Lbs5 ft9YesNoNo6Avec RestrictionPro & Farm600,000$60,000$0$NoLien
Scott MayfieldRocket (Mon)D241992-10-14No227 Lbs6 ft4NoNoNo4Avec RestrictionPro & Farm1,200,000$120,000$0$NoLien
Taylor FedunRocket (Mon)D291988-06-04No201 Lbs6 ft1YesNoNo6Sans RestrictionPro & Farm450,000$45,000$0$NoLien
Zach O'BrienRocket (Mon)RW251992-06-29Yes197 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm825,000$82,500$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3024.07196 Lbs6 ft23.50657,233$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Landon FerraroPaul CareyChase Balisy40122
2Ryan LombergAndrew CrescenziZach O'Brien30122
3Brandon DuhaimeFredrik KarlstromBrian Hart20122
4Andrew YoganAuguste ImposeMax Gaede10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Taylor Fedun40122
2Julian MelchioriKurtis MacDermid30122
3Brian LashoffKeegan Kanzig20122
4Taylor Fedun10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Landon FerraroPaul CareyChase Balisy60122
2Ryan LombergAndrew CrescenziZach O'Brien40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Taylor Fedun60122
2Julian MelchioriKurtis MacDermid40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Paul CareyLandon Ferraro60122
2Ryan LombergChase Balisy40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Taylor Fedun60122
2Julian MelchioriKurtis MacDermid40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Paul Carey60122Taylor Fedun60122
2Landon Ferraro40122Julian MelchioriKurtis MacDermid40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Paul CareyLandon Ferraro60122
2Ryan LombergChase Balisy40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Taylor Fedun60122
2Julian MelchioriKurtis MacDermid40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Landon FerraroPaul CareyChase BalisyTaylor Fedun
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Landon FerraroPaul CareyChase BalisyTaylor Fedun
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Fredrik Karlstrom, Auguste Impose, Brian HartFredrik Karlstrom, Auguste ImposeBrian Hart
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brian Lashoff, Keegan Kanzig, Julian MelchioriBrian LashoffKeegan Kanzig, Julian Melchiori
Tirs de Pénalité
Paul Carey, Landon Ferraro, Ryan Lomberg, Chase Balisy, Andrew Crescenzi
Gardien
#1 : Joni Ortio, #2 : Jeff Glass


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
1Admirals2020000049-51010000015-41010000034-100.000461000826764133660860164348591328357114.29%14192.86%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
2Baby Hawks20001010862100000103211000100054141.0008132100826764134160860164348591120347228.57%10370.00%11066209450.91%1279264548.36%651137747.28%1857121420056551117549
3Bears301011001216-420001100101001010000026-430.50012203200826764136360860164348974141588337.50%18572.22%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
4Bruins40301000713-62010100046-22020000037-420.25071118008267641360608601643481073966851000.00%23673.91%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
5Cabaret Lady Mary Ann412000101417-32110000078-12010001079-240.50014253900826764131176086016434814339678616425.00%19384.21%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
6Caroline303000001015-520200000811-31010000024-200.000101929008267641380608601643481023137889333.33%16662.50%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
7Chiefs20200000314-111010000035-21010000009-900.0003580082676413386086016434854201838400.00%9277.78%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
8Chill2020000027-51010000014-31010000013-200.00024610826764132960860164348671931325240.00%12466.67%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
9Comets220000001174110000006511100000052341.0001118290082676413536086016434852722318225.00%10370.00%21066209450.91%1279264548.36%651137747.28%1857121420056551117549
10Cougars404000001117-62020000069-32020000058-300.00011203100826764131166086016434812537348824416.67%17476.47%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
11Crunch42100100171342100010074321100000109150.6251730470182676413129608601643488130505323417.39%13376.92%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
12Heat2020000028-61010000024-21010000004-400.0002460082676413426086016434873216658800.00%15473.33%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
13Jayhawks20100010330100000102111010000012-120.50033600826764132760860164348521318446116.67%90100.00%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
14Las Vegas2020000057-21010000045-11010000012-100.000510150082676413496086016434853983612216.67%4250.00%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
15Manchots30200100711-42010010046-21010000035-210.1677132000826764138160860164348772647529222.22%160100.00%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
16Marlies413000001327-1421100000911-220200000416-1220.2501323360082676413946086016434814641369816425.00%18761.11%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
17Minnesota2010010025-31010000002-21000010023-110.2502460082676413336086016434861171227600.00%6183.33%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
18Monarchs20200000511-61010000026-41010000035-200.00059140082676413666086016434894241438600.00%7271.43%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
19Monsters31200000810-2110000003212020000058-320.333813210082676413536086016434896312871800.00%14378.57%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
20Monsters2020000016-51010000002-21010000014-300.00012300826764133360860164348651824341317.69%11372.73%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
21Oceanics2020000048-41010000014-31010000034-100.000471100826764133460860164348951916417228.57%8275.00%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
22Oil Kings22000000633110000002111100000042241.0006121800826764133360860164348471338355120.00%11190.91%11066209450.91%1279264548.36%651137747.28%1857121420056551117549
23Phantoms30201000911-2201010006601010000035-220.3339162500826764136360860164348773540591300.00%20670.00%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
24Senators41300000710-32020000014-32110000066020.250712190082676413776086016434811221568414214.29%27485.19%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
25Sharks2110000057-2110000005321010000004-420.500581300826764134360860164348120441846200.00%80100.00%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
26Sound Tigers3200001014951100000043121000010106461.000142337008267641383608601643487826247018422.22%11372.73%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
27Spiders30101001712-51000100032120100001410-630.500713200082676413716086016434811640465213323.08%16381.25%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
28Stars21100000541110000003121010000023-120.50058130082676413496086016434850112640800.00%13284.62%11066209450.91%1279264548.36%651137747.28%1857121420056551117549
29Thunder403000011116-52010000146-220200000710-310.1251119300082676413986086016434812735287822418.18%12283.33%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
Total82155105452223310-874192204321113141-284162901131110169-59560.3412233846071182676413187660860164348262376198316633165316.77%3998678.45%51066209450.91%1279264548.36%651137747.28%1857121420056551117549
31Wolf Pack3110001010821010000023-12100001085340.667101424008267641385608601643481383024729222.22%12191.67%01066209450.91%1279264548.36%651137747.28%1857121420056551117549
_Since Last GM Reset82155105452223310-874192204321113141-284162901131110169-59560.3412233846071182676413187660860164348262376198316633165316.77%3998678.45%51066209450.91%1279264548.36%651137747.28%1857121420056551117549
_Vs Conference358210123098125-2718510001205360-717311011104565-20260.3719817327101826764138406086016434810172774406921492416.11%1633777.30%51066209450.91%1279264548.36%651137747.28%1857121420056551117549
_Vs Division1454001002550-25731001001120-9723000001430-16110.39325436810826764132576086016434845111514724650714.00%691775.36%21066209450.91%1279264548.36%651137747.28%1857121420056551117549

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8256W122338460718762623761983166311
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8215515452223310
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
419224321113141
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
416291131110169
Derniers 10 Matchs
WLOTWOTL SOWSOL
360100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3165316.77%3998678.45%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
6086016434882676413
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
1066209450.91%1279264548.36%651137747.28%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1857121420056551117549


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
1 - 2018-10-031Rocket0Marlies8LSommaire du Match
4 - 2018-10-0623Rocket3Manchots5LSommaire du Match
9 - 2018-10-1151Monarchs6Rocket2LSommaire du Match
11 - 2018-10-1362Manchots4Rocket3LXSommaire du Match
13 - 2018-10-1575Cougars5Rocket3LSommaire du Match
15 - 2018-10-1786Chiefs5Rocket3LSommaire du Match
18 - 2018-10-20107Rocket3Senators2WSommaire du Match
21 - 2018-10-23124Heat4Rocket2LSommaire du Match
23 - 2018-10-25135Rocket7Crunch5WSommaire du Match
25 - 2018-10-27152Rocket3Bruins5LSommaire du Match
28 - 2018-10-30171Stars1Rocket3WSommaire du Match
30 - 2018-11-01182Bears5Rocket6WXSommaire du Match
32 - 2018-11-03196Thunder3Rocket2LXXSommaire du Match
34 - 2018-11-05211Rocket5Sound Tigers4WXXSommaire du Match
35 - 2018-11-06216Rocket5Wolf Pack4WXXSommaire du Match
37 - 2018-11-08230Crunch0Rocket4WSommaire du Match
39 - 2018-11-10246Las Vegas5Rocket4LSommaire du Match
42 - 2018-11-13270Rocket4Oil Kings2WSommaire du Match
44 - 2018-11-15283Rocket0Heat4LSommaire du Match
46 - 2018-11-17295Rocket5Comets2WSommaire du Match
48 - 2018-11-19311Bears5Rocket4LXSommaire du Match
50 - 2018-11-21319Rocket2Spiders3LXXSommaire du Match
52 - 2018-11-23335Rocket3Crunch4LSommaire du Match
53 - 2018-11-24350Bruins4Rocket1LSommaire du Match
56 - 2018-11-27369Caroline6Rocket4LSommaire du Match
60 - 2018-12-01399Wolf Pack3Rocket2LSommaire du Match
61 - 2018-12-02410Sharks3Rocket5WSommaire du Match
63 - 2018-12-04421Senators2Rocket0LSommaire du Match
65 - 2018-12-06433Rocket3Senators4LSommaire du Match
68 - 2018-12-09457Rocket5Baby Hawks4WXSommaire du Match
70 - 2018-12-11472Rocket2Minnesota3LXSommaire du Match
72 - 2018-12-13481Caroline5Rocket4LSommaire du Match
74 - 2018-12-15496Senators2Rocket1LSommaire du Match
76 - 2018-12-17514Bruins2Rocket3WXSommaire du Match
78 - 2018-12-19529Rocket1Monsters4LSommaire du Match
79 - 2018-12-20538Rocket1Jayhawks2LSommaire du Match
81 - 2018-12-22548Rocket1Las Vegas2LSommaire du Match
87 - 2018-12-28580Rocket5Cabaret Lady Mary Ann4WXXSommaire du Match
88 - 2018-12-29590Rocket4Thunder6LSommaire du Match
90 - 2018-12-31608Rocket2Stars3LSommaire du Match
93 - 2019-01-03626Comets5Rocket6WSommaire du Match
95 - 2019-01-05640Chill4Rocket1LSommaire du Match
97 - 2019-01-07654Minnesota2Rocket0LSommaire du Match
98 - 2019-01-08662Rocket4Cougars6LSommaire du Match
100 - 2019-01-10677Rocket0Chiefs9LSommaire du Match
102 - 2019-01-12691Monsters2Rocket0LSommaire du Match
104 - 2019-01-14705Rocket0Bruins2LSommaire du Match
105 - 2019-01-15714Cabaret Lady Mary Ann5Rocket3LSommaire du Match
108 - 2019-01-18734Rocket2Monsters4LSommaire du Match
109 - 2019-01-19745Phantoms3Rocket4WXSommaire du Match
113 - 2019-01-23766Jayhawks1Rocket2WXXSommaire du Match
123 - 2019-02-02790Spiders2Rocket3WXSommaire du Match
124 - 2019-02-03803Oil Kings1Rocket2WSommaire du Match
126 - 2019-02-05815Admirals5Rocket1LSommaire du Match
128 - 2019-02-07828Oceanics4Rocket1LSommaire du Match
130 - 2019-02-09847Marlies8Rocket5LSommaire du Match
135 - 2019-02-14881Rocket1Chill3LSommaire du Match
137 - 2019-02-16897Rocket3Thunder4LSommaire du Match
138 - 2019-02-17908Rocket2Cabaret Lady Mary Ann5LSommaire du Match
140 - 2019-02-19920Monsters2Rocket3WSommaire du Match
142 - 2019-02-21934Phantoms3Rocket2LSommaire du Match
144 - 2019-02-23952Rocket4Marlies8LSommaire du Match
146 - 2019-02-25963Rocket2Spiders7LSommaire du Match
147 - 2019-02-26974Rocket1Cougars2LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2019-03-01994Rocket3Wolf Pack1WSommaire du Match
151 - 2019-03-021003Manchots2Rocket1LSommaire du Match
154 - 2019-03-051028Rocket3Monarchs5LSommaire du Match
156 - 2019-03-071043Rocket0Sharks4LSommaire du Match
157 - 2019-03-081047Rocket3Admirals4LSommaire du Match
161 - 2019-03-121075Cougars4Rocket3LSommaire du Match
163 - 2019-03-141084Rocket5Sound Tigers2WSommaire du Match
165 - 2019-03-161104Baby Hawks2Rocket3WXXSommaire du Match
168 - 2019-03-191125Rocket3Phantoms5LSommaire du Match
170 - 2019-03-211139Sound Tigers3Rocket4WSommaire du Match
172 - 2019-03-231156Crunch4Rocket3LXSommaire du Match
173 - 2019-03-241166Rocket2Caroline4LSommaire du Match
175 - 2019-03-261180Cabaret Lady Mary Ann3Rocket4WSommaire du Match
177 - 2019-03-281191Rocket3Monsters4LSommaire du Match
179 - 2019-03-301204Rocket3Oceanics4LSommaire du Match
182 - 2019-04-021232Thunder3Rocket2LSommaire du Match
184 - 2019-04-041246Rocket2Bears6LSommaire du Match
186 - 2019-04-061259Marlies3Rocket4WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance60,53330,733
Assistance PCT73.82%74.96%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2226 - 74.20% 62,918$2,579,650$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,891,995$ 2,759,200$ 2,756,075$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
14,755$ 2,891,995$ 30 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 14,755$ 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
201882155105452223310-874192204321113141-284162901131110169-59562233846071182676413187660860164348262376198316633165316.77%3998678.45%51066209450.91%1279264548.36%651137747.28%1857121420056551117549
Total Saison Régulière82155105452223310-874192204321113141-284162901131110169-59562233846071182676413187660860164348262376198316633165316.77%3998678.45%51066209450.91%1279264548.36%651137747.28%1857121420056551117549