Monarchs

GP: 82 | W: 47 | L: 28 | OTL: 7 | P: 101
GF: 339 | GA: 301 | PP%: 22.22% | PK%: 81.09%
DG: Benoit Plouffe | Morale : 50 | Moyenne d'Équipe : 52
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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 SPÂgeContratSalaire Moyen
1Kenny AgostinoX100.00786781677476816645626665675555050630271800,000$
2Gage Quinney (R)XX100.00787292627371766074586270625151050610244715,000$
3Steven Lorentz (R)X100.00797782617771736480596567624444050610234728,333$
4Joseph BlandisiXX100.00754977736657745456605870255858050600253700,000$
5Stefan MatteauX100.00828275648472745850535567575151050600253600,000$
6Eric FehrXX100.005243847073586952844757734772660505903441,100,000$
7Liam O'BrienX100.00757665677679845668535563534545050590252750,000$
8Mitchell StephensX100.00715091657061645880565772254747050590221825,000$
9Turner ElsonXX100.00716976656772845650505463514444050570271895,000$
10Giovanni FioreXX100.007974905571605656504058655850500505502341,300,000$
11Nick Henry (R)X100.00746985666969744950474660444444050540204783,935$
12Dennis CholowskiX100.00634194776477878025524863255555050640212925,000$
13Andreas EnglundX100.00889083747462765425454464635757050620234900,000$
14Frederic AllardX100.00746788616673795125453964385050050580212742,500$
15Niko Mikkola (R)X100.00757185687173794925434061384444050580254842,500$
16Jesper Lindgren (R)X100.00696189636156584925434058384444050530221650,000$
17Brandon GormleyX100.00483582586445343335313567444136050480273670,000$
Rayé
1Ben Johnson (R)XX100.00354343435933333543353543393230050380253660,000$
2Adam Helewka (R)X100.00344040406933333440343440373230050370241650,000$
3Matthew Mistele (R)X100.00323737376431313237323237343230050350231525,000$
4Viktor LoovX100.00443591596935272935292871443532050470262690,000$
5Dmitry Sinitsyn (R)X100.00313737376629293137313137333230050360253565,000$
MOYENNE D'ÉQUIPE100.0064587661695963504746476145464505054
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
1Anton Forsberg100.0059617678596052625957304848050590
2Zach Sawchenko (R)100.0057526565605852605756304444050560
Rayé
1Evan Fitzpatrick (R)100.0042454476424141414141393230050440
2Wouter Peeters (R)100.0040434278403939393939373230050430
3Jack Lafontaine (R)100.0040434274403939393939373230050420
4Eamon McAdam (R)100.0038434069373535353535343230050390
MOYENNE D'ÉQUIPE100.004648527346454346454535373505047
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Sheldon Keefe43506474545457CAN381500,000$


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
1Kenny AgostinoMonarchs (LA )LW714576121473801451975291353628.51%48157922.2511102196162347112126247.14%68100011.53380001098
2Steven LorentzMonarchs (LA )C714374117462751692424681103189.19%85157322.1610112180161426122166459.51%201300111.49080109127
3Eric FehrMonarchs (LA )C/RW713458923720101693601163019.44%43130818.431151665158000003062.26%10600021.4100000436
4Stefan MatteauMonarchs (LA )LW823636721849514717335410530610.17%51115714.120112111013303453.02%23200021.2411010452
5Joseph BlandisiMonarchs (LA )C/LW55284371-23751261713691032637.59%38104719.0591221791430003805040.26%7700001.3623001452
6Liam O'BrienMonarchs (LA )C822137581728085194283912127.42%4298712.04000470111214055.68%133800011.1700000115
7Mitchell StephensMonarchs (LA )C82213455224069186261631418.05%99112413.7200000000002159.92%49900010.9800000214
8Gage QuinneyMonarchs (LA )C/LW37222547-3140431432125316210.38%3571019.19781550950003612159.71%97300001.3235000321
9Giovanni FioreMonarchs (LA )LW/RW7191019880394510632748.49%174326.0900000000000040.74%2700000.8800000002
10Nick HenryMonarchs (LA )RW71711188120304466236810.61%84296.0500000000001147.83%2300000.8400000010
11Turner ElsonMonarchs (LA )LW/RW2071017-1100322166134810.61%1133816.933361548000000138.46%2600001.0000000021
12Frederic AllardMonarchs (LA )D711910-1344074272810223.57%497039.910001200009100.00%000000.2800000000
13Andreas EnglundMonarchs (LA )D15369216035152271413.64%2027818.55044321011029100.00%000000.6500000001
14Dennis CholowskiMonarchs (LA )D9077520912168200.00%1322324.89011822011037000.00%000000.6300000002
15Derrick PouliotLA KingsD83141140267143921.43%1919023.81101518000027200.00%000000.4200000020
16Niko MikkolaMonarchs (LA )D9112-14011575314.29%1019421.59101419000032000.00%000000.2100000001
17Brandon GormleyMonarchs (LA )D1000-300403110.00%61616.530000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne8262814387191683291510541651316487823248.88%5941229614.894365108412873891733761361456.65%599500181.17925021374342
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
1Anton ForsbergMonarchs (LA )71442150.9193.25426860231286101140.69226710542
2Zach SawchenkoMonarchs (LA )11001.0000.0041000290000.0000071000
Stats d'équipe Total ou en Moyenne72452150.9203.22431060231289001140.692267171542


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 HelewkaMonarchs (LA )LW241995-07-21Yes200 Lbs6 ft2NoNoNo1Pro & Farm650,000$65,000$0$NoLien
Andreas EnglundMonarchs (LA )D231996-01-21No189 Lbs6 ft3NoNoNo4Pro & Farm900,000$90,000$0$No900,000$900,000$900,000$Lien
Anton ForsbergMonarchs (LA )G261992-11-26No192 Lbs6 ft3NoNoNo2Pro & Farm875,000$87,500$0$No875,000$Lien
Ben JohnsonMonarchs (LA )C/LW251994-06-07Yes188 Lbs5 ft11NoNoNo3Pro & Farm660,000$66,000$0$No660,000$660,000$Lien
Brandon GormleyMonarchs (LA )D271992-02-18No196 Lbs6 ft2NoNoNo3Pro & Farm670,000$67,000$0$No670,000$670,000$Lien
Dennis CholowskiMonarchs (LA )D211998-02-15No170 Lbs6 ft0NoNoNo2Pro & Farm925,000$92,500$0$No925,000$Lien
Dmitry SinitsynMonarchs (LA )D251994-06-17Yes200 Lbs6 ft2NoNoNo3Pro & Farm565,000$56,500$0$No565,000$565,000$Lien
Eamon McAdamMonarchs (LA )G251994-09-24Yes188 Lbs6 ft2NoNoNo3Pro & Farm700,000$70,000$0$No700,000$700,000$Lien
Eric FehrMonarchs (LA )C/RW341985-09-07No209 Lbs6 ft4NoNoNo4Pro & Farm1,100,000$110,000$0$No1,100,000$1,100,000$1,100,000$Lien
Evan FitzpatrickMonarchs (LA )G211998-01-28Yes202 Lbs6 ft3NoNoNo2Pro & Farm742,500$74,250$0$No742,500$Lien
Frederic AllardMonarchs (LA )D211997-12-27No179 Lbs6 ft1NoNoNo2Pro & Farm742,500$74,250$0$No742,500$Lien
Gage QuinneyMonarchs (LA )C/LW241995-07-29Yes201 Lbs6 ft0NoNoNo4Pro & Farm715,000$71,500$0$No715,000$715,000$715,000$
Giovanni FioreMonarchs (LA )LW/RW231996-08-13No194 Lbs6 ft1NoNoNo4Pro & Farm1,300,000$130,000$0$No1,200,000$1,200,000$1,100,000$Lien
Jack LafontaineMonarchs (LA )G211998-01-06Yes197 Lbs6 ft3NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Lien
Jesper LindgrenMonarchs (LA )D221997-05-19Yes161 Lbs6 ft0NoNoNo1Pro & Farm650,000$65,000$0$NoLien
Joseph BlandisiMonarchs (LA )C/LW251994-07-18No182 Lbs5 ft11NoNoNo3Pro & Farm700,000$70,000$0$No700,000$700,000$Lien
Kenny AgostinoMonarchs (LA )LW271992-04-30No200 Lbs6 ft1NoNoNo1Pro & Farm800,000$80,000$0$NoLien
Liam O'BrienMonarchs (LA )C251994-07-29No215 Lbs5 ft11NoNoNo2Pro & Farm750,000$75,000$0$No750,000$Lien
Matthew MisteleMonarchs (LA )LW231995-10-17Yes190 Lbs6 ft2NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Mitchell StephensMonarchs (LA )C221997-02-05No191 Lbs6 ft0NoNoNo1Pro & Farm825,000$82,500$0$NoLien
Nick HenryMonarchs (LA )RW201999-07-04Yes192 Lbs5 ft11NoNoNo4Pro & Farm783,935$78,394$0$No783,935$783,935$783,935$Lien
Niko MikkolaMonarchs (LA )D251994-04-26Yes184 Lbs6 ft4NoNoNo4Pro & Farm842,500$84,250$0$No842,500$842,500$842,500$
Stefan MatteauMonarchs (LA )LW251994-02-23No220 Lbs6 ft2NoNoNo3Pro & Farm600,000$60,000$0$No600,000$600,000$Lien
Steven LorentzMonarchs (LA )C231996-04-12Yes201 Lbs6 ft4NoNoNo4Pro & Farm728,333$72,833$0$No728,333$728,333$728,333$
Turner ElsonMonarchs (LA )LW/RW271992-09-12No184 Lbs6 ft0NoNoNo1Pro & Farm895,000$89,500$0$NoLien
Viktor LoovMonarchs (LA )D261992-11-16No212 Lbs6 ft1NoNoNo2Pro & Farm690,000$69,000$0$No690,000$Lien
Wouter PeetersMonarchs (LA )G211998-07-31Yes205 Lbs6 ft4NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Lien
Zach SawchenkoMonarchs (LA )G211997-12-30Yes179 Lbs6 ft0NoNoNo4Pro & Farm560,000$56,000$0$No560,000$560,000$560,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2824.00194 Lbs6 ft12.57760,527$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kenny AgostinoSteven LorentzEric Fehr40122
230122
3Stefan MatteauLiam O'Brien20122
4Giovanni FioreMitchell StephensNick Henry10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
3Frederic AllardMitchell Stephens20122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kenny AgostinoSteven LorentzEric Fehr60122
240122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kenny AgostinoSteven Lorentz60122
240122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Kenny Agostino6012260122
2Steven Lorentz4012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kenny AgostinoSteven Lorentz60122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kenny AgostinoSteven LorentzEric Fehr
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kenny AgostinoSteven LorentzEric Fehr
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Stefan Matteau, Liam O'Brien, Stefan Matteau, Liam O'Brien
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Frederic Allard, , Frederic Allard,
Tirs de Pénalité
Kenny Agostino, Steven Lorentz, , , Stefan Matteau
Gardien
#1 : Anton Forsberg, #2 : Zach Sawchenko


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
1Admirals503000021420-62020000068-230100002812-420.2001422360015499771424013461296130710925067351271616.25%150100.00%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
2Baby Hawks312000001011-1110000006422020000047-320.3331017271015499771412613461296130710911425166911327.27%70100.00%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
3Bears21100000811-3110000005411010000037-420.500814220015499771411113461296130710996341646700.00%8450.00%11742331952.49%1599325749.09%763141953.77%1867131520876001029492
4Bruins2020000069-31010000035-21010000034-100.00068140015499771488134612961307109902119494125.00%50100.00%11742331952.49%1599325749.09%763141953.77%1867131520876001029492
5Cabaret Lady Mary Ann220000001349110000008171100000053241.0001324370015499771420313461296130710981181261400.00%6183.33%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
6Caroline211000006511010000004-41100000061520.500691500154997714841346129613071098424631600.00%3166.67%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
7Chiefs31200000911-21010000034-12110000067-120.33391726001549977141381346129613071091344124669222.22%11190.91%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
8Chill311000101313020100010910-11100000043140.667132134101549977141181346129613071091563616695120.00%8187.50%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
9Comets42100001151502200000074320100001811-350.6251522371015499771417013461296130710915849328613215.38%15286.67%11742331952.49%1599325749.09%763141953.77%1867131520876001029492
10Cougars210001001082110000006331000010045-130.7501016260015499771499134612961307109802316488562.50%6266.67%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
11Crunch21100000710-31010000015-41100000065120.5007121900154997714911346129613071091404212444125.00%7185.71%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
12Heat431000002316721100000109122000000137660.7502341640015499771421913461296130710920755201147342.86%10190.00%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
13Jayhawks41101010181622010100078-121000010118360.75018335110154997714219134612961307109165463010120735.00%12466.67%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
14Las Vegas412000011315-2210000019722020000048-430.375132033101549977141991346129613071091614812721616.25%5180.00%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
15Manchots21100000963110000005141010000045-120.500914230015499771487134612961307109763012409111.11%6183.33%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
16Marlies200001108801000010045-11000001043130.75081321001549977147813461296130710976151049600.00%5260.00%21742331952.49%1599325749.09%763141953.77%1867131520876001029492
17Minnesota33000000181172200000011561100000076161.00018294700154997714224134612961307109169421459600.00%7271.43%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
18Monsters21000010954100000104311100000052341.0009122100154997714106134612961307109651912389333.33%6266.67%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
19Monsters3110001011101201000107701100000043140.6671117280015499771415013461296130710912435186814214.29%9277.78%21742331952.49%1599325749.09%763141953.77%1867131520876001029492
20Oceanics30300000519-141010000026-420200000313-1000.00058130015499771497134612961307109189492664800.00%13561.54%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
21Oil Kings412000011217-52110000087120100001410-630.3751221330015499771416913461296130710920561379211327.27%13284.62%11742331952.49%1599325749.09%763141953.77%1867131520876001029492
22Phantoms220000001073110000006421100000043141.0001019290015499771494134612961307109732417446233.33%60100.00%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
23Rocket21001000752100010005411100000021141.00071320001549977147713461296130710982341838400.00%8275.00%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
24Senators2020000047-31010000013-21010000034-100.00047110015499771474134612961307109852818552150.00%9366.67%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
25Sharks4300100018117210010009542200000096381.0001829470015499771416813461296130710915249249114321.43%11190.91%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
26Sound Tigers220000001257110000008351100000042241.0001223350015499771491134612961307109702054515360.00%10190.00%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
27Spiders201010007701010000023-11000100054120.500710170015499771411013461296130710994314453266.67%20100.00%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
28Stars33000000208122200000011651100000092761.0002034540015499771418413461296130710989349746233.33%2150.00%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
29Thunder22000000954110000005321100000042241.000915240015499771498134612961307109561514515360.00%7185.71%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
Total823828042553393013841191403131178143354119140112416115831010.6163395669055015499771440251346129613071093590103456718712435422.22%2384581.09%81742331952.49%1599325749.09%763141953.77%1867131520876001029492
30Wolf Pack2200000015691100000010281100000054141.00015264100154997714113134612961307109691914295240.00%6183.33%01742331952.49%1599325749.09%763141953.77%1867131520876001029492
_Since Last GM Reset823828042553393013841191403131178143354119140112416115831010.6163395669055015499771440251346129613071093590103456718712435422.22%2384581.09%81742331952.49%1599325749.09%763141953.77%1867131520876001029492
_Vs Conference3715140213214713981877011207965141987010126874-6430.58114724138810154997714167313461296130710915974572918481042322.12%1172281.20%41742331952.49%1599325749.09%763141953.77%1867131520876001029492
_Vs Division1646011206456881301110332948330001031274150.4696410817200154997714808134612961307109690196119395371129.73%531277.36%31742331952.49%1599325749.09%763141953.77%1867131520876001029492

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
82101W1339566905402535901034567187150
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8238284255339301
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4119143131178143
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4119141124161158
Derniers 10 Matchs
WLOTWOTL SOWSOL
630001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2435422.22%2384581.09%8
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
134612961307109154997714
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
1742331952.49%1599325749.09%763141953.77%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1867131520876001029492


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
4 - 2020-10-2530Monarchs1Oil Kings6LSommaire du Match
7 - 2020-10-2842Monarchs7Heat5WSommaire du Match
8 - 2020-10-2946Monarchs4Comets5LXXSommaire du Match
11 - 2020-11-0163Chill7Monarchs5LSommaire du Match
12 - 2020-11-0276Las Vegas5Monarchs4LXXSommaire du Match
14 - 2020-11-0491Caroline4Monarchs0LSommaire du Match
16 - 2020-11-06106Crunch5Monarchs1LSommaire du Match
18 - 2020-11-08122Heat7Monarchs5LSommaire du Match
21 - 2020-11-11140Monarchs1Oceanics8LSommaire du Match
23 - 2020-11-13149Monarchs3Chiefs5LSommaire du Match
25 - 2020-11-15167Monarchs7Minnesota6WSommaire du Match
26 - 2020-11-16172Monarchs2Baby Hawks4LSommaire du Match
29 - 2020-11-19193Comets2Monarchs3WSommaire du Match
32 - 2020-11-22217Baby Hawks4Monarchs6WSommaire du Match
35 - 2020-11-25228Monarchs4Marlies3WXXSommaire du Match
37 - 2020-11-27242Monarchs3Senators4LSommaire du Match
39 - 2020-11-29255Monarchs2Rocket1WSommaire du Match
42 - 2020-12-02279Minnesota3Monarchs5WSommaire du Match
44 - 2020-12-04293Cougars3Monarchs6WSommaire du Match
46 - 2020-12-06312Las Vegas2Monarchs5WSommaire du Match
48 - 2020-12-08317Monarchs4Jayhawks3WXXSommaire du Match
51 - 2020-12-11345Oil Kings4Monarchs7WSommaire du Match
53 - 2020-12-13350Jayhawks4Monarchs5WXSommaire du Match
55 - 2020-12-15373Sharks3Monarchs6WSommaire du Match
57 - 2020-12-17388Sound Tigers3Monarchs8WSommaire du Match
59 - 2020-12-19393Monarchs4Sharks3WSommaire du Match
60 - 2020-12-20414Oceanics6Monarchs2LSommaire du Match
62 - 2020-12-22423Monarchs1Admirals3LSommaire du Match
64 - 2020-12-24437Bears4Monarchs5WSommaire du Match
66 - 2020-12-26450Monarchs3Oil Kings4LXXSommaire du Match
67 - 2020-12-27462Monarchs6Heat2WSommaire du Match
70 - 2020-12-30483Wolf Pack2Monarchs10WSommaire du Match
72 - 2021-01-01497Monarchs2Admirals3LXXSommaire du Match
74 - 2021-01-03511Monarchs4Manchots5LSommaire du Match
75 - 2021-01-04517Monarchs4Cougars5LXSommaire du Match
77 - 2021-01-06524Monarchs3Bruins4LSommaire du Match
79 - 2021-01-08541Monarchs5Monsters2WSommaire du Match
81 - 2021-01-10552Monarchs6Crunch5WSommaire du Match
83 - 2021-01-12581Chiefs4Monarchs3LSommaire du Match
87 - 2021-01-16592Monarchs5Sharks3WSommaire du Match
88 - 2021-01-17599Monarchs4Comets6LSommaire du Match
91 - 2021-01-20622Phantoms4Monarchs6WSommaire du Match
95 - 2021-01-24652Chill3Monarchs4WXXSommaire du Match
97 - 2021-01-26662Monsters3Monarchs4WXXSommaire du Match
99 - 2021-01-28677Stars3Monarchs7WSommaire du Match
100 - 2021-01-29686Monarchs2Las Vegas4LSommaire du Match
102 - 2021-01-31697Monarchs6Caroline1WSommaire du Match
105 - 2021-02-03716Monarchs4Thunder2WSommaire du Match
107 - 2021-02-05729Monarchs5Cabaret Lady Mary Ann3WSommaire du Match
109 - 2021-02-07750Monarchs4Phantoms3WSommaire du Match
120 - 2021-02-18779Thunder3Monarchs5WSommaire du Match
121 - 2021-02-19784Monarchs7Jayhawks5WSommaire du Match
123 - 2021-02-21804Admirals4Monarchs3LSommaire du Match
126 - 2021-02-24817Monarchs3Bears7LSommaire du Match
128 - 2021-02-26831Monarchs4Sound Tigers2WSommaire du Match
130 - 2021-02-28849Monarchs5Spiders4WXSommaire du Match
131 - 2021-03-01857Monarchs5Wolf Pack4WSommaire du Match
134 - 2021-03-04878Heat2Monarchs5WSommaire du Match
137 - 2021-03-07902Monarchs4Monsters3WSommaire du Match
140 - 2021-03-10926Monarchs2Oceanics5LSommaire du Match
142 - 2021-03-12940Cabaret Lady Mary Ann1Monarchs8WSommaire du Match
144 - 2021-03-14958Monsters3Monarchs4WXXSommaire du Match
145 - 2021-03-15966Oil Kings3Monarchs1LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
148 - 2021-03-18983Manchots1Monarchs5WSommaire du Match
151 - 2021-03-211000Spiders3Monarchs2LSommaire du Match
152 - 2021-03-221016Monarchs2Las Vegas4LSommaire du Match
156 - 2021-03-261041Marlies5Monarchs4LXSommaire du Match
158 - 2021-03-281052Minnesota2Monarchs6WSommaire du Match
160 - 2021-03-301069Monsters4Monarchs3LSommaire du Match
162 - 2021-04-011082Senators3Monarchs1LSommaire du Match
165 - 2021-04-041099Admirals4Monarchs3LSommaire du Match
168 - 2021-04-071131Rocket4Monarchs5WXSommaire du Match
170 - 2021-04-091144Bruins5Monarchs3LSommaire du Match
172 - 2021-04-111161Comets2Monarchs4WSommaire du Match
173 - 2021-04-121169Jayhawks4Monarchs2LSommaire du Match
175 - 2021-04-141184Monarchs9Stars2WSommaire du Match
177 - 2021-04-161197Monarchs4Chill3WSommaire du Match
178 - 2021-04-171200Monarchs3Chiefs2WSommaire du Match
180 - 2021-04-191217Monarchs2Baby Hawks3LSommaire du Match
182 - 2021-04-211238Sharks2Monarchs3WXSommaire du Match
185 - 2021-04-241256Monarchs5Admirals6LXXSommaire du Match
186 - 2021-04-251270Stars3Monarchs4WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets5020
Assistance50,45127,398
Assistance PCT61.53%66.82%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 1899 - 63.29% 74,890$3,070,510$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,206,152$ 2,129,477$ 2,129,477$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
11,449$ 2,206,152$ 28 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 11,449$ 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