Kings

GP: 82 | W: 51 | L: 27 | OTL: 4 | P: 106
GF: 250 | GA: 209 | PP%: 21.43% | PK%: 81.90%
DG: Guillaume Laplante | Morale : 92 | Moyenne d'Équipe : 70
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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
1Markus Granlund (R)X100.006235777173839081898587807382746781760
2Sam Bennett (R)X100.007551657675818185698885775971579381750
3Valeri NichushkinX100.004631997679777981608385807277738377750
4Nick Schmaltz (R)X100.005438888469879586808180705577567981740
5Pierre-Luc Dubois (R)X100.007235677785889576858076757057578970730
6Anthony Mantha (R)X100.006744757694889578617583647679577881730
7Ondrej Kase (R)X100.006748747672778384527883755456574880720
8Alex Tuch (R)X100.007035807691868775687572745671578271710
9Dylan Strome (R)X100.005735777783859176837671747054568981710
10Andreas Johnsson (R)X100.006535707467828673627172736653514781680
11Dominik Kahun (R)X100.005735767167819570677067696553514381660
12Adam Gaudette (R)X100.006235736771718366736363656052515431620
13Ivan Provorov (R)X100.007639937175959874307585855675618581750
14Brett Pesce (R)X100.006435816985868669307265896762546481720
15Erik Gustafsson (R)X100.007035797874919277308270745665575381720
16Brandon Montour (R)X100.006935747073919580307678725871526880710
17Josh Morrissey (R)X100.006635847373917272307765836959588381710
18Neal Pionk (R)X100.007747796872888668307164776654514381690
Rayé
1Rudolfs Balcers (R)X100.005535736967636869506766675951505620620
2Victor Olofsson (R)X100.005135716969535369506666675550554819610
3Filip Zadina (R)X100.005135716973545469526262635150509020590
4Devon Toews (R)X100.005835776976718568306662645652515820630
5Juuso Valimaki (R)X100.006135756683656266306060656151508420610
6Philippe Myers (R)X100.006735636891586068305959605551504420610
7Caleb Jones (R)X100.005535726976585869305957595751506020590
MOYENNE D'ÉQUIPE100.00633777727778817452737172626155686168
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
1Philipp Grubauer (R)100.00918187769094969594908360765081850
2Jonas Hiller100.00708476797397999999809199996181850
Rayé
MOYENNE D'ÉQUIPE100.0081838278829698979785878088568185
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Michel Therrien85998288999689CAN5631,000,000$


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
1Nick SchmaltzKings (LA )C82403878-21001162002707916514.81%24142117.33211940502710223608455.65%1362569021.10380005710
2Sam BennettKings (LA )LW822849771111620194167296981709.46%41163319.921218305026110162406262.14%1036424110.9419202831
3Markus GranlundKings (LA )C82304272155351422982279714413.22%33168720.581316294027201182722356.48%21073627110.8503001325
4Valeri NichushkinKings (LA )RW84254166-120941822308916910.87%39165919.76617233127111251982342.20%4364935100.80311000534
5Ondrej Kase Kings (LA )LW82312960498201851242257011813.78%24136116.6010112133274000044138.37%863819010.8801013613
6Alex TuchKings (LA )RW792037570180169139206631219.71%42152019.251120314429111271050353.85%1304216000.7514000431
7Dylan StromeKings (LA )C822136572260135214232671049.05%22144717.66189152480112627150.70%12194229000.7911000173
8Pierre-Luc DuboisKings (LA )LW80163450-17915215200188671478.51%33143317.922572119020251114051.22%7794320000.7026012161
9Anthony Mantha Kings (LA )RW821432461420171109210501096.67%22135116.486152138269000012332.35%683916000.6823000125
10Ivan ProvorovKings (LA )D8082432155514217811644446.90%113186223.284711122670115233200.00%03741000.3411001054
11Erik Gustafsson Kings (LA )D824252913601391329639404.17%93165720.2125717274000177110.00%03348000.3500000001
12Brandon MontourKings (LA )D8481725134401531589938448.08%102166319.81257231630113171200.00%03642000.3000000112
13Andreas JohnssonKings (LA )RW82121224335510875131401009.16%2683510.180111112025681134.21%382512000.5700001111
14Josh MorrisseyKings (LA )D8211617111751271307227351.39%86153418.720000180224255000.00%02751000.2201010010
15Dominik KahunKings (LA )LW78124166240465484355614.29%126588.45101370000512138.79%16598000.4900000130
16Brett PesceKings (LA )D82281053515991526624233.03%109159419.44000070004294000.00%01050100.1300021102
17Neal PionkKings (LA )D82077-34351611195725210.00%69138216.850110500000110000.00%0942000.1000010001
18Adam GaudetteKings (LA )C3022441001916166912.50%72387.96000030000120053.26%9222000.3400000000
19Rudolfs BalcersKings (LA )LW16011-340856570.00%01348.38000030000140040.00%511000.1500000000
20Devon ToewsKings (LA )D6000220541120.00%48614.360000000001000.00%013000.0000000000
21Victor OlofssonKings (LA )RW5000020222110.00%1306.130000000000000.00%002000.0000000000
Stats d'équipe Total ou en Moyenne1444274454728837019524302658283096516299.68%9022519517.4591148239378315871017582348432352.59%6590599497450.5814482611384544
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
1Jonas HillerKings (LA )49301430.9302.312861201101567628400.688164735883
2Philipp GrubauerKings (LA )36211310.9152.71210120951113463300.846133547423
Stats d'équipe Total ou en Moyenne85512740.9242.4849624020526801091700.75929828212106


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
Adam GaudetteKings (LA )C231996-10-03 05:10:31Yes170 Lbs6 ft1NoNoNo3Pro & Farm916,666$0$0$No916,666$916,666$
Alex TuchKings (LA )RW231996-05-10 10:00:42Yes222 Lbs6 ft4NoNoNo1Pro & Farm925,000$0$0$No
Andreas JohnssonKings (LA )RW251994-11-21 05:30:22Yes181 Lbs5 ft10NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$
Anthony Mantha Kings (LA )RW251994-09-16 17:04:44Yes225 Lbs6 ft5NoNoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$
Brandon MontourKings (LA )D261994-04-11 10:52:49Yes193 Lbs6 ft0NoNoNo1Pro & Farm925,000$0$0$No
Brett PesceKings (LA )D251994-11-15 17:11:13Yes206 Lbs6 ft3NoNoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$
Caleb JonesKings (LA )D221997-06-06 08:53:26Yes194 Lbs6 ft1NoNoNo3Pro & Farm790,000$0$0$No790,000$790,000$
Devon ToewsKings (LA )D261994-02-21 07:36:08Yes191 Lbs6 ft1NoNoNo3Pro & Farm700,000$0$0$No700,000$700,000$
Dominik KahunKings (LA )LW241995-07-02 07:23:49Yes175 Lbs5 ft11NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$
Dylan StromeKings (LA )C231997-03-07 13:29:38Yes200 Lbs6 ft3NoNoNo1Pro & Farm863,333$0$0$No
Erik Gustafsson Kings (LA )D281992-03-14 17:52:07Yes197 Lbs6 ft0NoNoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$
Filip ZadinaKings (LA )LW201999-11-27 04:55:45Yes195 Lbs6 ft0NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$
Ivan ProvorovKings (LA )D231997-01-13 09:36:50Yes203 Lbs6 ft1NoNoNo1Pro & Farm894,167$0$0$No
Jonas HillerKings (LA )G381982-02-12 17:11:14No205 Lbs6 ft2NoNoNo2Pro & Farm2,950,000$0$0$No2,950,000$
Josh MorrisseyKings (LA )D251995-03-28 16:21:22Yes195 Lbs6 ft0NoNoNo3Pro & Farm1,500,000$0$0$No1,500,000$1,500,000$
Juuso ValimakiKings (LA )D211998-10-06 05:14:16Yes212 Lbs6 ft2NoNoNo3Pro & Farm894,166$0$0$No894,166$894,166$
Markus GranlundKings (LA )C271993-04-16 11:11:13Yes180 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$0$0$No
Neal PionkKings (LA )D241995-07-29 10:28:15Yes186 Lbs6 ft0NoNoNo2Pro & Farm1,775,000$0$0$No1,775,000$
Nick SchmaltzKings (LA )C241996-02-23 04:12:54Yes177 Lbs6 ft0NoNoNo1Pro & Farm925,000$0$0$No
Ondrej Kase Kings (LA )LW241995-11-08 04:05:45Yes186 Lbs5 ft11NoNoNo1Pro & Farm670,000$0$0$No
Philipp GrubauerKings (LA )G281991-11-25 23:11:14Yes191 Lbs6 ft1NoNoNo1Pro & Farm2,000,000$0$0$No
Philippe MyersKings (LA )D231997-01-25 08:14:37Yes210 Lbs6 ft5NoNoNo3Pro & Farm678,333$0$0$No678,333$678,333$
Pierre-Luc DuboisKings (LA )LW211998-06-24 03:05:03Yes207 Lbs6 ft3NoNoNo2Pro & Farm3,394,170$0$0$No3,394,170$
Rudolfs BalcersKings (LA )LW231997-04-08 04:53:30Yes175 Lbs5 ft11NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$
Sam BennettKings (LA )LW231996-06-20 05:11:13Yes195 Lbs6 ft1NoNoNo3Pro & Farm2,500,000$0$0$No2,500,000$2,500,000$
Valeri NichushkinKings (LA )RW251995-03-04 23:11:13No214 Lbs6 ft6NoNoNo1Pro & Farm1,100,000$0$0$No
Victor OlofssonKings (LA )RW241995-07-18 08:34:24Yes181 Lbs5 ft11NoNoNo3Pro & Farm767,500$0$0$No767,500$767,500$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2724.56195 Lbs6 ft12.221,328,457$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Sam BennettMarkus GranlundAnthony Mantha 33131
2Ondrej Kase Nick SchmaltzValeri Nichushkin33131
3Pierre-Luc DuboisDylan StromeAlex Tuch32131
4Dominik KahunAdam GaudetteAndreas Johnsson2131
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ivan ProvorovBrandon Montour37131
2Erik Gustafsson Josh Morrissey37131
3Brett PesceNeal Pionk26131
4Ivan ProvorovBrett Pesce0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Sam BennettMarkus GranlundValeri Nichushkin50122
2Ondrej Kase Nick SchmaltzAlex Tuch50122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ivan ProvorovDylan Strome50122
2Erik Gustafsson Anthony Mantha 50122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Markus GranlundSam Bennett60122
2Dylan StromeValeri Nichushkin40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Josh MorrisseyBrett Pesce60122
2Neal PionkIvan Provorov40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Markus Granlund60122Josh MorrisseyBrett Pesce60122
2Sam Bennett40122Ivan ProvorovNeal Pionk40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Markus GranlundSam Bennett60122
2Nick SchmaltzPierre-Luc Dubois40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ivan ProvorovBrett Pesce60122
2Erik Gustafsson Brandon Montour40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Sam BennettMarkus GranlundOndrej Kase Ivan ProvorovBrett Pesce
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Sam BennettMarkus GranlundOndrej Kase Ivan ProvorovBrett Pesce
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dylan Strome, Valeri Nichushkin, Alex TuchDylan Strome, Anthony Mantha Pierre-Luc Dubois
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brandon Montour, Josh Morrissey, Neal PionkBrandon MontourNeal Pionk, Brandon Montour
Tirs de Pénalité
Valeri Nichushkin, Sam Bennett, Nick Schmaltz, Anthony Mantha , Ondrej Kase
Gardien
#1 : Jonas Hiller, #2 : Philipp Grubauer


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
1Avalanche4210100013103201010007702200000063360.75013223500757689131338888858504112550241181200.00%12375.00%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
2Blackhawks42101000181442100100011922110000075260.750183048007576891313288888585041138471810516318.75%9366.67%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
3Blues42200000910-12110000035-22110000065140.50091524007576891312288888585041126483012119210.53%10280.00%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
4Bruins21000010633100000103211100000031241.000681400757689136288888585041752311564250.00%3166.67%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
5Canadiens21100000862110000005231010000034-120.5008142200757689137088888585041802812583266.67%6266.67%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
6Canucks6220101017152311010008623110001099080.667172744007576891319988888585041179559919740512.50%32778.13%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
7Capitals3010100168-21010000024-22000100144030.50061218007576891399888885850411054218769111.11%9188.89%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
8Devils22000000642110000003211100000032141.0006111700757689136888888585041672110495120.00%50100.00%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
9Ducks64100010261115311000109543300000017611100.8332641670075768913193888885850411845493185411536.59%39684.62%11125216352.01%1258224955.94%574110052.18%1813104917507531402707
10Flames6330000021201321000001082312000001112-160.500213354007576891318588888585041193539417333927.27%40587.50%11125216352.01%1258224955.94%574110052.18%1813104917507531402707
11Flyers21000001440110000002111000000123-130.75047110075768913688888858504170124557114.29%20100.00%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
12Islanders210000016601000000123-11100000043130.750612180075768913618888858504180184644125.00%30100.00%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
13Maple Leafs21001000532100010003211100000021141.000571200757689137088888585041732412685120.00%6183.33%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
14Oilers65100000221210321000001064330000001266100.833223557007576891319388888585041181497119336925.00%28582.14%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
15Penguins201000106601010000023-11000001043120.500671300757689136688888585041721512514125.00%6183.33%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
16Predators54100000211293210000012752200000095480.800213354007576891315888888585041168593814127829.63%19384.21%11125216352.01%1258224955.94%574110052.18%1813104917507531402707
17Rangers20000011550100000103211000000123-130.7505712007576891374888885850416629455600.00%220.00%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
18Red Wings32100000810-22110000058-31100000032140.66781321007576891393888885850411092526809222.22%8362.50%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
19Sabres22000000954110000005231100000043141.0009152400757689137288888585041712012494125.00%6183.33%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
20Senateurs3120000057-21010000014-32110000043120.33356110075768913908888858504110932208211327.27%10460.00%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
21Sharks633000001415-1321000009903120000056-160.500142438007576891317488888585041177589016136616.67%40782.50%11125216352.01%1258224955.94%574110052.18%1813104917507531402707
22Stars41300000912-3211000006602020000036-320.2509152400757689131308888858504111944309719421.05%15193.33%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
Total8241270505425020941411914040311251071841221301023125102231060.6462504066560075768913263388888585041268084376423473647821.43%3265981.90%41125216352.01%1258224955.94%574110052.18%1813104917507531402707
24Wild41300000611-5211000004402020000027-520.2506121800757689131218888858504111337321131417.14%16193.75%01125216352.01%1258224955.94%574110052.18%1813104917507531402707
_Since Last GM Reset8241270505425020941411914040311251071841221301023125102231060.6462504066560075768913263388888585041268084376423473647821.43%3265981.90%41125216352.01%1258224955.94%574110052.18%1813104917507531402707
_Vs Conference55292103020176142342814100301089721727151100010877017680.6181762874630075768913174088888585041170355461916042936221.16%2604383.46%41125216352.01%1258224955.94%574110052.18%1813104917507531402707
_Vs Division301710010201007327158501010463412159500010543915400.6671001602600075768913944888885850419142694479091864423.66%1793083.24%31125216352.01%1258224955.94%574110052.18%1813104917507531402707

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
82106L225040665626332680843764234700
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8241275054250209
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4119144031125107
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4122131023125102
Derniers 10 Matchs
WLOTWOTL SOWSOL
640000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3647821.43%3265981.90%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
8888858504175768913
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
1125216352.01%1258224955.94%574110052.18%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1813104917507531402707


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 - 2019-10-061Kings3Sharks1WR5Sommaire du Match
3 - 2019-10-0816Sharks2Kings3WSommaire du Match
6 - 2019-10-1129Kings2Oilers1WSommaire du Match
8 - 2019-10-1344Oilers1Kings7WSommaire du Match
10 - 2019-10-1554Flames3Kings5WSommaire du Match
12 - 2019-10-1765Kings6Flames1WSommaire du Match
15 - 2019-10-2080Kings3Canucks2WSommaire du Match
17 - 2019-10-2290Predators2Kings8WSommaire du Match
20 - 2019-10-25107Ducks1Kings6WSommaire du Match
22 - 2019-10-27115Kings5Ducks1WSommaire du Match
24 - 2019-10-29131Canucks2Kings3WXSommaire du Match
26 - 2019-10-31141Kings6Ducks2WSommaire du Match
28 - 2019-11-02152Ducks2Kings0LSommaire du Match
32 - 2019-11-06172Stars4Kings2LSommaire du Match
34 - 2019-11-08178Kings3Avalanche2WSommaire du Match
36 - 2019-11-10189Kings2Capitals3LXXSommaire du Match
37 - 2019-11-11199Kings1Wild4LSommaire du Match
39 - 2019-11-13210Ducks2Kings3WXXSommaire du Match
42 - 2019-11-16225Kings4Islanders3WSommaire du Match
44 - 2019-11-18234Penguins3Kings2LSommaire du Match
47 - 2019-11-21250Avalanche4Kings5WXSommaire du Match
49 - 2019-11-23263Kings3Devils2WSommaire du Match
51 - 2019-11-25271Canadiens2Kings5WSommaire du Match
54 - 2019-11-28290Kings2Stars3LSommaire du Match
56 - 2019-11-30299Islanders3Kings2LXXSommaire du Match
60 - 2019-12-04316Kings4Oilers1WSommaire du Match
62 - 2019-12-06324Maple Leafs2Kings3WXSommaire du Match
65 - 2019-12-09342Kings2Flames6LSommaire du Match
66 - 2019-12-10347Blackhawks5Kings6WXSommaire du Match
69 - 2019-12-13363Avalanche3Kings2LSommaire du Match
71 - 2019-12-15373Kings6Ducks3WSommaire du Match
74 - 2019-12-18389Capitals4Kings2LSommaire du Match
76 - 2019-12-20403Kings1Sharks3LR5Sommaire du Match
78 - 2019-12-22413Kings3Avalanche1WSommaire du Match
79 - 2019-12-23420Senateurs4Kings1LSommaire du Match
82 - 2019-12-26434Kings3Bruins1WSommaire du Match
84 - 2019-12-28443Blackhawks4Kings5WSommaire du Match
86 - 2019-12-30453Kings2Blackhawks3LSommaire du Match
87 - 2019-12-31464Rangers2Kings3WXXSommaire du Match
90 - 2020-01-03476Kings3Flames5LSommaire du Match
93 - 2020-01-06489Sabres2Kings5WSommaire du Match
95 - 2020-01-08501Kings1Sharks2LR5Sommaire du Match
98 - 2020-01-11516Devils2Kings3WSommaire du Match
100 - 2020-01-13528Kings2Rangers3LXXSommaire du Match
102 - 2020-01-15537Kings6Oilers4WSommaire du Match
103 - 2020-01-16544Stars2Kings4WSommaire du Match
106 - 2020-01-19561Kings2Flyers3LXXSommaire du Match
107 - 2020-01-20568Bruins2Kings3WXXSommaire du Match
110 - 2020-01-23584Canucks1Kings3WSommaire du Match
111 - 2020-01-24592Kings3Red Wings2WSommaire du Match
114 - 2020-01-27604Kings5Blues2WSommaire du Match
116 - 2020-01-29614Flyers1Kings2WSommaire du Match
118 - 2020-01-31625Kings2Maple Leafs1WSommaire du Match
121 - 2020-02-03638Blues4Kings1LSommaire du Match
123 - 2020-02-05650Kings5Predators4WSommaire du Match
126 - 2020-02-08663Sharks3Kings5WR5Sommaire du Match
129 - 2020-02-11681Red Wings6Kings1LSommaire du Match
131 - 2020-02-13695Kings3Canucks5LSommaire du Match
133 - 2020-02-15705Kings5Blackhawks2WSommaire du Match
134 - 2020-02-16710Blues1Kings2WSommaire du Match
137 - 2020-02-19726Kings4Sabres3WSommaire du Match
138 - 2020-02-20734Canucks3Kings2LSommaire du Match
141 - 2020-02-23749Kings1Blues3LSommaire du Match
143 - 2020-02-25757Sharks4Kings1LR5Sommaire du Match
146 - 2020-02-28774Kings4Penguins3WXXSommaire du Match
147 - 2020-02-29782Kings3Canadiens4LSommaire du Match
148 - 2020-03-01787Predators4Kings1LSommaire du Match
151 - 2020-03-04804Red Wings2Kings4WSommaire du Match
154 - 2020-03-07819Kings1Stars3LSommaire du Match
155 - 2020-03-08822Kings4Predators1WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
157 - 2020-03-10834Flames4Kings1LSommaire du Match
160 - 2020-03-13850Kings2Capitals1WXSommaire du Match
162 - 2020-03-15857Wild2Kings3WSommaire du Match
165 - 2020-03-18877Wild2Kings1LSommaire du Match
166 - 2020-03-19882Kings3Senateurs1WSommaire du Match
171 - 2020-03-24902Predators1Kings3WSommaire du Match
174 - 2020-03-27917Oilers1Kings2WSommaire du Match
177 - 2020-03-30933Kings1Wild3LSommaire du Match
178 - 2020-03-31936Kings3Canucks2WXXSommaire du Match
181 - 2020-04-03949Flames1Kings4WSommaire du Match
185 - 2020-04-07968Kings1Senateurs2LSommaire du Match
188 - 2020-04-10979Oilers4Kings1LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets5535
Assistance75,87638,242
Assistance PCT92.53%93.27%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2783 - 92.78% 141,137$5,786,634$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
5,019,980$ 3,586,834$ 1,819,334$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
18,878$ 3,746,280$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 24,141$ 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
13782730031611226244-1839131502036114117-339141501135112127-155422637259860578080162628934816847108261087747619762806824.29%2345178.21%41041204750.85%955195348.90%545112848.32%1772105916676921332674
148241270505425020941411914040311251071841221301023125102231062504066560075768913263388888585041268084376423473647821.43%3265981.90%41125216352.01%1258224955.94%574110052.18%1813104917507531402707
Total Saison Régulière16068570811115476453238032290606723922415803628021582372298160476778125460132156169295261182217011697149529017201240432364414622.67%56011080.36%82166421051.45%2213420252.67%1119222850.22%358521093418144627351382