hellpepitosKingspatriots

 

 


Royaux

GP: 84 | W: 37 | L: 43 | OTL: 4 | P: 78
GF: 240 | GA: 257 | PP%: 17.91% | PK%: 77.13%
DG: Eric Plourde | Morale : 50 | Moyenne d'Équipe : 66
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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
1Pavel Zacha0X100.00632366367473727180798274754945050730
2Kevin Fiala0XX100.0043762295273787635828356825433020720
3Luke Kunin0X100.00733058375672746962798071713757050710
4Derek Grant0XX100.00793067438252766982788170695652050700
5Christian Fischer0X100.00782465357462807134778155654241050690
6Zach Sanford0X100.00673065397656657162808250653644050690
7Logan Shaw0X100.00783070477755806361767866706054050680
8Michael Rasmussen (R)0X100.00782754378356726842788155713247050680
9Henrik Borgstrom0X100.00382277365856857071787751663337050670
10Valentin Zykov0X100.00632875397748786533768053664645050660
11Jakob Forsbacka Karlsson0X100.00441978455054816162768152673939050650
12Daniel Carr0X100.00552774486053776233727955654748050640
13Alan Quine0X100.00662465556648706139707854715245050630
14Michael McLeod (R)0X100.00702965605556815948687657673759050630
15Alexander Nylander0XX100.00291974505556785934677665674037050620
16Jacob Larsson0X100.00571866486262787831807356664439050690
17Haydn Fleury0X100.00702671497351757830797342664757050680
18Christian Folin0X100.00873060487657757979817454634747012680
19Julius Honka0X100.00532363464549778031807441664842050670
20Mitch Reinke0X100.00262283574548846731966856683245050660
21Cale Makar (R)0X100.00412183484763827131747254682739050660
22Jeremy Lauzon (R)0X100.00473380596756816931737060673755050650
23Dante Fabbro (R)0X100.00432183595143826931727149683243050620
24Trevor Carrick0X100.00344176607035836731726854685068050620
Rayé
1Seth Griffith0X100.00362375605148775731667461735547050610
2Owen Tippett0X100.00312283627251825731647166683438050600
3Alex Formenton0X100.00412469643551785832657366683040050590
4Nicolas Kerdiles0X100.00313283686918755631646967683946050510
5Gabriel Carlsson0X100.00401974596440776830727051674137050610
MOYENNE D'ÉQUIPE100.0054257149635378674375765768424604865
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
1Pheonix Copley100.0086898786869290899080784868050820
2Maxime Lagace100.0082898277818882849053625359050780
Rayé
MOYENNE D'ÉQUIPE100.008489858284908687906770516405080
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Yeo87928481728350CAN462450,000$


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'ÉquipePOSGP 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
1Pavel ZachaRoyaux (KLA)C84415091571513423731512922313.02%101166919.88141832822880115735267.06%17005024211.0926000475
2Christian FischerRoyaux (KLA)RW84205272552019982243881348.23%34152318.1472027672930000182139.78%934230020.9522000442
3Luke KuninRoyaux (KLA)C84313162-95801961702768114511.23%68147517.571011217426811241374355.29%8324141000.8428000443
4Zach SanfordRoyaux (KLA)LW84243660050013367290811838.28%31145517.33512175016400081256268.49%73769000.8201000425
5Henrik BorgstromRoyaux (KLA)C84142640-214051100202601306.93%29135516.142794321300021153155.59%9392912000.5925000024
6Kevin FialaRoyaux (KLA)LW/RW3011294013240202011439719.65%958219.403710241080000323063.16%38156001.3703000021
7Markus NutivaaraKingsD75132538-8280756113760649.49%94167022.27459271120005275120.00%04832000.4600000034
8Michael RasmussenRoyaux (KLA)RW841818360680168104180518010.00%50134215.981121157022212911051.43%705018000.5412000131
9Jacob LarssonRoyaux (KLA)D8482634-44605911111340527.08%102177921.19549372440224202000.00%02544000.3800000101
10Valentin ZykovRoyaux (KLA)LW83131730-9140897016550867.88%30111413.4325716114000011050.00%46389000.5400000210
11Xavier OuelletKingsD5752126-432090449830595.10%39106718.743584122800001100.00%02116000.4900000012
12Derek GrantRoyaux (KLA)C/LW65101424-4180916514147797.09%416149.45011414000021162.11%952421000.7800000020
13Michael McLeodRoyaux (KLA)C8451722-33006510510837574.63%3795411.3701118303233040046.07%7885422000.4600000101
14Logan ShawRoyaux (KLA)RW8141216-9300728711939903.36%4681310.0500000000002052.50%403619000.3901000011
15Cale MakarRoyaux (KLA)D84411151740231127726325.19%127201824.03134192610003261100.00%0542000.1501000010
16Julius HonkaRoyaux (KLA)D7741115052074306933365.80%33153619.96224121670004172100.00%03516000.2000000001
17Haydn FleuryRoyaux (KLA)D841910-2128084336325261.59%39136816.290224570002125000.00%01516000.1500000100
18Owen TippettRoyaux (KLA)RW413710-1007536423324.69%2851812.651341597000000056.25%162811000.3900000001
19Daniel CarrRoyaux (KLA)LW17246-14012192915206.90%723814.0000000000001057.14%7107000.5000000000
20Alexander NylanderRoyaux (KLA)LW/RW71246210010425121283.92%145197.320115260001281040.00%5069000.2300000100
21Seth GriffithRoyaux (KLA)LW27224-24011233917195.13%1128910.7300000000000045.45%11193000.2800000000
22Jakob Forsbacka KarlssonRoyaux (KLA)C171230405122312184.35%21186.9500000000000049.25%6763000.5100000000
23Gabriel CarlssonRoyaux (KLA)D9022000094220.00%213214.740000000008000.00%001000.3000000000
24Christian FolinRoyaux (KLA)D70220801675340.00%412618.0400000000020000.00%031000.3200000000
25Alex FormentonRoyaux (KLA)LW44011100112315690.00%51363.11000240000360038.46%2632000.1500000000
26Jeremy LauzonRoyaux (KLA)D7011000353330.00%1210915.5701101600000000.00%001000.1800000000
27Dante FabbroRoyaux (KLA)D11000040284510.00%516114.6700002700002000.00%004000.0000000000
Stats d'équipe Total ou en Moyenne1559236430666-346535170016992947102316838.01%10002469415.846010916953427774610822238341257.58%4891679419230.54929000233332
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
1Pheonix CopleyRoyaux (KLA)55262330.9192.643188011401728952400.741275232754
2Maxime LagaceRoyaux (KLA)34112010.8903.611893011141041508001.00033252210
Stats d'équipe Total ou en Moyenne89374340.9083.0050820225427691460400.767308484964


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 Type Salaire Actuel Salaire RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Alan QuineRoyaux (KLA)C261993-02-25No203 Lbs183 CMNoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Alex FormentonRoyaux (KLA)LW201999-09-13No165 Lbs188 CMNoNoNo1Pro & Farm925,000$0$0$NoLien
Alexander NylanderRoyaux (KLA)LW/RW211998-03-02No192 Lbs185 CMNoNoNo3Pro & Farm1,713,333$0$0$No1,713,333$1,713,333$Lien
Cale MakarRoyaux (KLA)D201998-10-30Yes187 Lbs180 CMNoNoNo2Pro & Farm2,854,166$0$0$No2,854,166$Lien
Christian FischerRoyaux (KLA)RW221997-04-15No214 Lbs188 CMNoNoNo2Pro & Farm1,075,833$0$0$No1,075,833$Lien
Christian FolinRoyaux (KLA)D281991-02-09No204 Lbs191 CMNoNoNo1Pro & Farm2,500,000$0$0$NoLien / Lien NHL
Daniel CarrRoyaux (KLA)LW271991-11-01No193 Lbs183 CMNoNoNo1Pro & Farm725,000$0$0$NoLien / Lien NHL
Dante FabbroRoyaux (KLA)D211998-06-20Yes189 Lbs183 CMNoNoNo2Pro & Farm1,491,666$0$0$No1,491,666$Lien
Derek GrantRoyaux (KLA)C/LW291990-04-20No215 Lbs191 CMNoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Gabriel CarlssonRoyaux (KLA)D221997-01-02No192 Lbs196 CMNoNoNo2Pro & Farm894,166$0$0$No894,166$Lien / Lien NHL
Haydn FleuryRoyaux (KLA)D231996-07-08No208 Lbs191 CMNoNoNo1Pro & Farm1,713,333$0$0$NoLien
Henrik BorgstromRoyaux (KLA)C221997-08-06No190 Lbs191 CMNoNoNo1Pro & Farm1,491,666$0$0$NoLien
Jacob LarssonRoyaux (KLA)D221997-04-29No197 Lbs188 CMNoNoNo2Pro & Farm894,166$0$0$No894,166$Lien
Jakob Forsbacka KarlssonRoyaux (KLA)C221996-10-31No184 Lbs185 CMNoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Jeremy LauzonRoyaux (KLA)D221997-04-28Yes204 Lbs185 CMNoNoNo2Pro & Farm871,666$0$0$No871,666$Lien
Julius HonkaRoyaux (KLA)D231995-12-03No180 Lbs180 CMNoNoNo2Pro & Farm1,363,333$0$0$No1,363,333$Lien
Kevin FialaRoyaux (KLA)LW/RW231996-07-22No193 Lbs178 CMNoNoNo1Pro & Farm1,425,000$0$0$NoLien / Lien NHL
Logan ShawRoyaux (KLA)RW261992-10-05No208 Lbs191 CMNoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Luke KuninRoyaux (KLA)C211997-12-04No195 Lbs183 CMNoNoNo1Pro & Farm1,425,000$0$0$NoLien
Maxime LagaceRoyaux (KLA)G261993-01-12No190 Lbs188 CMNoNoNo1Pro & Farm650,000$0$0$NoLien
Michael McLeodRoyaux (KLA)C211998-02-03Yes188 Lbs188 CMNoNoNo2Pro & Farm1,363,333$0$0$No1,363,333$Lien
Michael RasmussenRoyaux (KLA)RW201999-04-17Yes221 Lbs198 CMNoNoNo2Pro & Farm1,710,833$0$0$No1,710,833$Lien
Mitch ReinkeRoyaux (KLA)D231996-02-04No181 Lbs180 CMNoNoNo1Pro & Farm925,000$0$0$NoLien
Nicolas KerdilesRoyaux (KLA)LW251994-01-11No200 Lbs188 CMNoNoNo2Pro & Farm650,000$0$0$No650,000$Lien / Lien NHL
Owen TippettRoyaux (KLA)RW201999-02-16No216 Lbs185 CMNoNoNo1Pro & Farm1,658,333$0$0$NoLien
Pavel ZachaRoyaux (KLA)C221997-04-06No210 Lbs191 CMNoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Pheonix CopleyRoyaux (KLA)G271992-01-18No200 Lbs193 CMNoNoNo1Pro & Farm650,000$0$0$NoLien
Seth GriffithRoyaux (KLA)LW261993-01-04No190 Lbs175 CMNoNoNo2Pro & Farm650,000$0$0$No650,000$Lien / Lien NHL
Trevor CarrickRoyaux (KLA)D251994-07-04No196 Lbs188 CMNoNoNo1Pro & Farm670,000$0$0$NoLien
Valentin ZykovRoyaux (KLA)LW241995-05-15No220 Lbs183 CMNoNoNo2Pro & Farm675,000$0$0$No675,000$Lien
Zach SanfordRoyaux (KLA)LW241994-11-09No207 Lbs193 CMNoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3123.32198 Lbs188 CM1.521,151,317$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kevin FialaPavel ZachaChristian Fischer40122
2Zach SanfordLuke KuninAlexander Nylander30122
3Valentin ZykovHenrik BorgstromLogan Shaw20122
4Derek GrantMichael McLeodMichael Rasmussen10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Haydn FleuryCale Makar40122
2Jacob LarssonChristian Folin30122
3Jeremy LauzonDante Fabbro20122
4Haydn FleuryCale Makar10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kevin FialaPavel ZachaChristian Fischer60122
2Alexander NylanderHenrik BorgstromLuke Kunin40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Cale MakarDante Fabbro60122
2Jacob LarssonJeremy Lauzon40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Michael McLeodMichael Rasmussen60122
2Luke KuninZach Sanford40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Haydn FleuryCale Makar60122
2Jacob LarssonChristian Folin40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Michael McLeod60122Haydn FleuryCale Makar60122
2Michael Rasmussen40122Jacob LarssonChristian Folin40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Pavel ZachaKevin Fiala60122
2Luke KuninAlexander Nylander40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Haydn FleuryCale Makar60122
2Jacob LarssonChristian Folin40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kevin FialaPavel ZachaChristian FischerHaydn FleuryCale Makar
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Zach SanfordMichael McLeodMichael RasmussenJacob LarssonChristian Folin
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Rasmussen, Christian Fischer, Kevin FialaLuke Kunin, Kevin FialaPavel Zacha
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Christian Folin, Cale Makar, Jacob LarssonDante FabbroHaydn Fleury, Jacob Larsson
Tirs de Pénalité
Kevin Fiala, Luke Kunin, Henrik Borgstrom, Pavel Zacha, Cale Makar
Gardien
#1 : Pheonix Copley, #2 : Maxime Lagace


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
1Barracuda51300001181802010000148-4312000001410430.3001833510093706615193104094290059152523211424312.50%16381.25%01169193460.44%1012184754.79%606105157.66%1962128118816701245623
2Benchwarmers52102000171163200100011562010100066080.800172946009370661515010409429005918456429225728.00%21195.24%01169193460.44%1012184754.79%606105157.66%1962128118816701245623
3Caribou52300000171702110000087131200000910-140.400173047009370661517010409429005916553528820315.00%261157.69%01169193460.44%1012184754.79%606105157.66%1962128118816701245623
4Casse-Tete724000012123-232100000963403000011217-550.3572135560093706615246104094290059264925414620420.00%27388.89%01169193460.44%1012184754.79%606105157.66%1962128118816701245623
5Chevalier716000001324-112110000045-150500000919-1020.1431326390093706615225104094290059237918013820315.00%40977.50%01169193460.44%1012184754.79%606105157.66%1962128118816701245623
6Diabotins7510001019910430000101331032100000660120.857193251019370661526410409429005914757181631616.25%90100.00%01169193460.44%1012184754.79%606105157.66%1962128118816701245623
7Hooligans1024011112840-12512011001418-4512000111422-8100.50028507800937066153771040942900594041397815327414.81%391269.23%01169193460.44%1012184754.79%606105157.66%1962128118816701245623
8Hybrides5220100012111320010008442020000047-360.600122032009370661514710409429005917277429517211.76%21195.24%01169193460.44%1012184754.79%606105157.66%1962128118816701245623
9Jardiniers623010002222042101000171342020000059-460.5002241630093706615194104094290059198596313836822.22%25772.00%11169193460.44%1012184754.79%606105157.66%1962128118816701245623
10Leftovers642000002416843100000181172110000065180.6672444680093706615228104094290059183734411743716.28%21576.19%01169193460.44%1012184754.79%606105157.66%1962128118816701245623
11Pirates5120002011110201000104403110001077060.600111425009370661520210409429005916155281001516.67%14471.43%11169193460.44%1012184754.79%606105157.66%1962128118816701245623
12Requins523000001313021100000330312000001010040.4001324370193706615151104094290059167644412025624.00%22577.27%01169193460.44%1012184754.79%606105157.66%1962128118816701245623
Total84264306153240257-1742181405131129109204282901022111148-37780.46424042066002937066152912104094290059276998667117103356017.91%3287577.13%41169193460.44%1012184754.79%606105157.66%1962128118816701245623
14Vagabond605010001323-1030201000913-430300000410-620.1671324370093706615185104094290059197585411623626.09%27677.78%11169193460.44%1012184754.79%606105157.66%1962128118816701245623
15Werewolves504000101219-73020001079-220200000510-520.2001218300093706615180104094290059138604013024520.83%20860.00%11169193460.44%1012184754.79%606105157.66%1962128118816701245623
_Since Last GM Reset84264306153240257-1742181405131129109204282901022111148-37780.46424042066002937066152912104094290059276998667117103356017.91%3287577.13%41169193460.44%1012184754.79%606105157.66%1962128118816701245623
_Vs Conference348220101293112-191566010114039119216000015373-20220.324931622550093706615116110409429005911284253007111252016.00%1503576.67%11169193460.44%1012184754.79%606105157.66%1962128118816701245623
_Vs Division26511010008490-6144201000504371219000003447-13120.2318415023400937066158911040942900599513072354711082220.37%1113172.07%11169193460.44%1012184754.79%606105157.66%1962128118816701245623

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8478W224042066029122769986671171002
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8426436153240257
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4218145131129109
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
428291022111148
Derniers 10 Matchs
WLOTWOTL SOWSOL
450001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3356017.91%3287577.13%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
10409429005993706615
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
1169193460.44%1012184754.79%606105157.66%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1962128118816701245623


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 - 2019-10-078Hooligans3Royaux4WXSommaire du Match
3 - 2019-10-0814Royaux1Caribou3LSommaire du Match
6 - 2019-10-1122Diabotins0Royaux3WSommaire du Match
7 - 2019-10-1228Royaux3Vagabond5LSommaire du Match
9 - 2019-10-1435Royaux3Pirates1WSommaire du Match
11 - 2019-10-1643Benchwarmers1Royaux3WSommaire du Match
14 - 2019-10-1952Jardiniers2Royaux4WSommaire du Match
15 - 2019-10-2059Royaux1Casse-Tete3LSommaire du Match
17 - 2019-10-2268Hooligans1Royaux2WSommaire du Match
19 - 2019-10-2474Royaux2Hooligans3LXXSommaire du Match
20 - 2019-10-2579Royaux2Chevalier4LSommaire du Match
22 - 2019-10-2786Diabotins1Royaux2WSommaire du Match
24 - 2019-10-2994Royaux2Chevalier4LSommaire du Match
26 - 2019-10-31102Leftovers2Royaux5WSommaire du Match
28 - 2019-11-02110Leftovers3Royaux5WSommaire du Match
30 - 2019-11-04117Royaux3Leftovers4LSommaire du Match
32 - 2019-11-06125Hooligans5Royaux1LSommaire du Match
34 - 2019-11-08134Royaux2Barracuda3LSommaire du Match
35 - 2019-11-09140Hooligans3Royaux2LSommaire du Match
36 - 2019-11-10146Royaux5Benchwarmers4WXSommaire du Match
39 - 2019-11-13155Requins3Royaux1LSommaire du Match
41 - 2019-11-15161Royaux6Hooligans4WSommaire du Match
42 - 2019-11-16168Royaux3Pirates2WXXSommaire du Match
44 - 2019-11-18176Chevalier4Royaux1LSommaire du Match
45 - 2019-11-19183Barracuda6Royaux3LSommaire du Match
47 - 2019-11-21191Royaux2Requins3LSommaire du Match
49 - 2019-11-23199Royaux2Barracuda4LSommaire du Match
51 - 2019-11-25205Royaux1Hybrides3LSommaire du Match
52 - 2019-11-26210Benchwarmers3Royaux4WXSommaire du Match
55 - 2019-11-29218Werewolves3Royaux1LSommaire du Match
57 - 2019-12-01229Royaux3Diabotins2WSommaire du Match
59 - 2019-12-03235Caribou3Royaux6WSommaire du Match
61 - 2019-12-05244Leftovers3Royaux1LSommaire du Match
62 - 2019-12-06252Royaux1Pirates4LSommaire du Match
64 - 2019-12-08257Royaux1Chevalier4LSommaire du Match
65 - 2019-12-09265Werewolves4Royaux3LSommaire du Match
68 - 2019-12-12275Royaux5Casse-Tete6LSommaire du Match
69 - 2019-12-13279Diabotins1Royaux6WSommaire du Match
71 - 2019-12-15288Royaux1Casse-Tete2LSommaire du Match
72 - 2019-12-16293Royaux2Diabotins1WSommaire du Match
74 - 2019-12-18300Pirates1Royaux2WXXSommaire du Match
76 - 2019-12-20308Casse-Tete2Royaux3WSommaire du Match
77 - 2019-12-21314Royaux1Jardiniers3LSommaire du Match
80 - 2019-12-24321Royaux0Vagabond2LSommaire du Match
82 - 2019-12-26330Chevalier1Royaux3WSommaire du Match
84 - 2019-12-28337Royaux1Benchwarmers2LSommaire du Match
86 - 2019-12-30344Casse-Tete3Royaux2LSommaire du Match
88 - 2020-01-01352Royaux3Leftovers1WSommaire du Match
89 - 2020-01-02356Royaux4Caribou2WSommaire du Match
90 - 2020-01-03362Hybrides1Royaux3WSommaire du Match
92 - 2020-01-05373Royaux1Vagabond3LSommaire du Match
93 - 2020-01-06376Hybrides2Royaux3WXSommaire du Match
96 - 2020-01-09385Royaux1Requins4LSommaire du Match
97 - 2020-01-10390Benchwarmers1Royaux4WSommaire du Match
99 - 2020-01-12399Royaux1Hooligans4LSommaire du Match
101 - 2020-01-14404Jardiniers6Royaux4LSommaire du Match
102 - 2020-01-15407Royaux2Werewolves4LSommaire du Match
104 - 2020-01-17418Barracuda2Royaux1LXXSommaire du Match
106 - 2020-01-19425Royaux4Hooligans3WXXSommaire du Match
108 - 2020-01-21433Royaux7Requins3WSommaire du Match
109 - 2020-01-22438Hybrides1Royaux2WSommaire du Match
113 - 2020-01-26449Vagabond7Royaux3LSommaire du Match
115 - 2020-01-28460Royaux3Werewolves6LSommaire du Match
116 - 2020-01-29464Jardiniers4Royaux5WXSommaire du Match
118 - 2020-01-31469Royaux4Caribou5LSommaire du Match
120 - 2020-02-02479Requins0Royaux2WSommaire du Match
121 - 2020-02-03483Royaux1Hooligans8LSommaire du Match
122 - 2020-02-04491Royaux3Hybrides4LSommaire du Match
124 - 2020-02-06496Casse-Tete1Royaux4WSommaire du Match
129 - 2020-02-11509Royaux4Jardiniers6LSommaire du Match
130 - 2020-02-12514Leftovers3Royaux7WSommaire du Match
132 - 2020-02-14524Caribou4Royaux2LSommaire du Match
135 - 2020-02-17533Royaux10Barracuda3WSommaire du Match
137 - 2020-02-19540Hooligans6Royaux5LXSommaire du Match
139 - 2020-02-21548Royaux1Diabotins3LSommaire du Match
141 - 2020-02-23555Diabotins1Royaux2WXXSommaire du Match
144 - 2020-02-26568Pirates3Royaux2LSommaire du Match
145 - 2020-02-27575Royaux5Casse-Tete6LXXSommaire du Match
147 - 2020-02-29582Jardiniers1Royaux4WSommaire du Match
149 - 2020-03-02589Royaux1Chevalier3LSommaire du Match
151 - 2020-03-04597Vagabond3Royaux2LSommaire du Match
153 - 2020-03-06604Royaux3Chevalier4LSommaire du Match
157 - 2020-03-10614Vagabond3Royaux4WXSommaire du Match
160 - 2020-03-13623Werewolves2Royaux3WXXSommaire 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
4,069,784$ 7,101,583$ 4,967,166$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
43,568$ 4,069,784$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 43,568$ 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
Saison Régulière
20168425520040338931079421324003022241457942122800101165165050389596985111331271290259786286487082941105745913473303610.91%1694672.78%1509175029.09%461173126.63%391124831.33%1749118621936371120523
2017843032066462662343242151404414139115244215180223212711986026644170702898384112429811784783832635948101615872615019.16%4608082.61%11738158746.50%898197545.47%454107642.19%1785112820747081255592
201784402501396310340-304226900142180172842141601254130168-388031053684616981049813260484988783192231077067315172885418.75%3214885.05%14940168055.95%966163659.05%650124252.33%2021132417996911300648
201882432400546491283208412611002112671381294117130033522414579864917431234201921701256332412351143938502960102837411503438725.36%1784873.03%1933200046.65%711164143.33%612131946.40%1937134518696131171582
201882432404245465289176412710000312401241164116140421422516560864658311296021901581091032211166105197556263393487718143388525.15%4168380.05%241110191957.84%1022176357.97%788130660.34%2023132416996551250644
201984264306153240257-1742181405131129109204282901022111148-377824042066002937066152912104094290059276998667117103356017.91%3287577.13%41169193460.44%1012184754.79%606105157.66%1962128118816701245623
Total Saison Régulière5002072000172126292161171344825012582091112111179803376250821180810141898291072440216135675728413795712611551708759635671529734816248572340709125189537219.63%187238079.70%5553991087049.67%50701059347.86%3501724248.34%11479759011518397673433614
Séries
20161046000002527-25230000014122523000001115-482545700071152291816810438351126102228371232.43%42685.71%07320236.14%7524131.12%3911833.05%2121202859817785
201740400000714-72020000047-32020000037-407111800043011736453601344863611417.14%24866.67%0278830.68%5010249.02%174240.48%855498345626
2017158700000292817430000013112844000001617-11629558410156534181571161133242716412025765710.77%60886.67%116229554.92%18131657.28%10417858.43%358224349136252126
2018734000002523233000000169740400000914-5625315600117703131289671182451084212431825.81%201050.00%07620137.81%4415927.67%3311528.70%182131158539946
20181156000003539-45230000019181633000001621-510355792102067241615112612910399148138268581322.41%641871.88%314329348.81%13826152.87%6714845.27%25815526010118189
Total Séries47202700000121131-10221111000006657925916000005574-194012119932020533427715555534514539815565944659382054120.00%2105076.19%4481107944.58%488107945.23%26060143.26%10976851152423767374