Connexion

Monarchs
GP: 82 | W: 36 | L: 38 | OTL: 8 | P: 80
GF: 277 | GA: 297 | PP%: 20.08% | PK%: 77.65%
DG: Antoine Pelletier | Morale : 50 | Moyenne d’équipe : 53
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Centre de jeu
Monarchs
36-38-8, 80pts
3
FINAL
8 Admirals
46-30-6, 98pts
Team Stats
L3StreakL1
20-17-4Home Record22-15-4
16-21-4Away Record24-15-2
6-4-0Last 10 Games5-4-1
3.38Goals Per Game3.54
3.62Goals Against Per Game3.16
20.08%Power Play Percentage20.94%
77.65%Penalty Kill Percentage82.68%
Stars
43-36-3, 89pts
7
FINAL
6 Monarchs
36-38-8, 80pts
Team Stats
W1StreakL3
28-11-2Home Record20-17-4
15-25-1Away Record16-21-4
6-4-0Last 10 Games6-4-0
3.48Goals Per Game3.38
3.39Goals Against Per Game3.62
25.62%Power Play Percentage20.08%
74.35%Penalty Kill Percentage77.65%
Meneurs d'équipe
Buts
Joseph Blandisi
31
Passes
Joseph Blandisi
38
Points
Joseph Blandisi
69
Plus/Moins
Joseph Blandisi
0
Victoires
Carter Hart
16
Pourcentage d’arrêts
Carter Hart
0.927

Statistiques d’équipe
Buts pour
277
3.38 GFG
Tirs pour
2942
35.88 Avg
Pourcentage en avantage numérique
20.1%
53 GF
Début de zone offensive
39.2%
Buts contre
297
3.62 GAA
Tirs contre
3339
40.72 Avg
Pourcentage en désavantage numérique
77.7%
59 GA
Début de la zone défensive
42.4%
Information d’équipe

Directeur généralAntoine Pelletier
DivisionAtlantique
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,910
Billets de saison300


Information formation

Équipe Pro21
Équipe Mineure19
Limite contact 40 / 50
Espoirs11


Historique d'équipe

Saison actuelle36-38-8 (80PTS)
Historique36-38-7 (0.444%)
Apparitions séries éliminatoires
Historique séries éliminatoires (W-L)-


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
1Gage QuinneyXX100.00777287627260596880597168675151050620253715,000$
2Mitchell StephensX100.00626947656961596980736160584849050600231700,000$
3Stefan MatteauX100.00844585647657616034505778255555050590262600,000$
4Connor Zary (R)X100.00716586586557566480616363604444050580193925,000$
5Liam O'BrienXX100.00884628677746645525705567254646050580261750,000$
6Nick HenryX100.00807691666959555855476467554444050570213783,935$
7Steven LorentzXXX100.00754493617856815877615655254848050570243728,333$
8Graeme Clarke (R)X100.00716488606454536250576262594444050560193850,833$
9Giovanni FioreXX100.007574895471565253493855655650500505302431,300,000$
10Dalton SmithX100.00667644637655584550384655444444050500281560,000$
11Ben JohnsonXX100.00334343435931313343333343383230050370262660,000$
12Derrick PouliotX100.00737177777163665725514566436263050620262975,000$
13Dennis CholowskiX100.00614191777368717125504859255656050610221925,000$
14Andreas EnglundX100.00839082737458705125434264615757050600243900,000$
15Frederic AllardX100.00706679616665675825554562435151050580221742,500$
16Viktor LoovX100.00423590586933252835282771433532050460271690,000$
17Dmitry SinitsynX100.00303737376627273037303037323230050350262565,000$
Rayé
MOYENNE D’ÉQUIPE100.0067607362705356544750516145474705055
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
1Zach Sawchenko (R)100.0057516370615854625857334844050570
2Wouter Peeters (R)100.0038434278383737373737353230050410
Rayé
1Jack Lafontaine (R)100.0038434274383737373737353230050410
2Eamon McAdam100.0036434069353333333333323230050380
MOYENNE D’ÉQUIPE100.004245477343414042414134363405044
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’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 HenryMonarchs (LA )RW82443882-15763016913937210526211.83%33152118.561341777211000007150.75%13400211.0800114495
2Stefan MatteauMonarchs (LA )LW824036761931517316234510328811.59%46154518.8428105619701141043234.17%12000000.9839100586
3Joseph BlandisiLA KingsC/LW5931386901801291342779517611.19%23128321.75511164914620261661055.58%46600001.0826000353
4Mitchell StephensMonarchs (LA )C68263864103410961992355915611.06%9123318.144812321561012643361.54%171100001.0418101342
5Derrick PouliotMonarchs (LA )D63133851-5951522373129386710.08%121143522.798816601680003134100.00%000000.7100012027
6Dennis CholowskiMonarchs (LA )D8294150-820054114179591355.03%159194823.7631417852270111211110.00%000100.5100000113
7Graeme ClarkeMonarchs (LA )RW82232548-24019892297216510.04%27111413.5912310250005655353.77%10600000.8600000024
8Frederic AllardMonarchs (LA )D827394657551508711238966.25%116168320.5351015642020001176000.00%000000.5500000132
9Andreas EnglundMonarchs (LA )D82112738-1772527594110366110.00%143173521.176511542000000179110.00%300000.4401311132
10Liam O'BrienMonarchs (LA )C/LW82102838-10720300130178641545.62%40118614.4714522760002520029.97%107100000.6423000211
11Steven LorentzMonarchs (LA )C/LW/RW7982836151404774175511224.57%11135817.20145351890000243065.66%9900000.5311000002
12Connor ZaryMonarchs (LA )C71161834-523548150187471248.56%1675910.6910110180000160157.74%88500100.9000001011
13Giovanni FioreMonarchs (LA )LW/RW8291928-12195815414648906.16%50115314.070331056000014125.81%6200000.4900010002
14Dalton SmithMonarchs (LA )LW4078153295763962174311.29%744311.090002200001201050.00%2800000.6800100112
15Viktor LoovMonarchs (LA )D8251015-2416049576426517.81%124132216.1311211590001580050.00%200000.2300000001
16Gage QuinneyMonarchs (LA )C/LW9381148019394412376.82%520522.861127110220220060.85%25800001.0700000110
17Ben JohnsonMonarchs (LA )C/LW76246-16408341871411.11%16188.14000070000290035.77%41100000.1900000000
18Dmitry SinitsynMonarchs (LA )D44123524060752120.00%2366015.01000018000040000.00%000000.0900000000
Statistiques d’équipe totales ou en moyenne1247265445710-3763910519761675286787920429.24%9542121217.0152831355841996347261368301350.60%535600410.67928749224143
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
1Carter HartLA Kings2616820.9273.101588208211210110.73315260520
2Anton ForsbergLA Kings2112720.9222.76119721557040000.75082132501
3Zach SawchenkoMonarchs (LA )207920.9063.89100200656890000.75041928022
Statistiques d’équipe totales ou en moyenne67352460.9203.2037884120225140110.7412766601043


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 restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Andreas EnglundMonarchs (LA )D241996-01-21No189 Lbs6 ft3NoNoNo3Pro & Farm900,000$90,000$0$No900,000$900,000$Lien
Ben JohnsonMonarchs (LA )C/LW261994-06-07No188 Lbs5 ft11NoNoNo2Pro & Farm660,000$66,000$0$No660,000$Lien
Connor ZaryMonarchs (LA )C192001-09-25Yes179 Lbs6 ft0NoNoNo3Pro & Farm925,000$92,500$0$No925,000$925,000$Lien
Dalton SmithMonarchs (LA )LW281992-06-30No206 Lbs6 ft2YesNoNo1Pro & Farm560,000$56,000$0$NoLien
Dennis CholowskiMonarchs (LA )D221998-02-15No197 Lbs6 ft2NoNoNo1Pro & Farm925,000$92,500$0$NoLien
Derrick PouliotMonarchs (LA )D261994-01-16No196 Lbs6 ft0NoNoNo2Pro & Farm975,000$97,500$0$No975,000$Lien
Dmitry SinitsynMonarchs (LA )D261994-06-17No200 Lbs6 ft2NoNoNo2Pro & Farm565,000$56,500$0$No565,000$Lien
Eamon McAdamMonarchs (LA )G261994-09-24No188 Lbs6 ft2NoNoNo2Pro & Farm700,000$70,000$0$No700,000$Lien
Frederic AllardMonarchs (LA )D221997-12-27No179 Lbs6 ft1NoNoNo1Pro & Farm742,500$74,250$0$NoLien
Gage QuinneyMonarchs (LA )C/LW251995-07-29No200 Lbs5 ft11NoNoNo3Pro & Farm715,000$71,500$0$No715,000$715,000$Lien
Giovanni FioreMonarchs (LA )LW/RW241996-08-13No194 Lbs6 ft1NoNoNo3Pro & Farm1,200,000$130,000$0$No1,200,000$1,100,000$Lien
Graeme ClarkeMonarchs (LA )RW192001-04-24Yes174 Lbs6 ft0NoNoNo3Pro & Farm850,833$85,083$0$No850,833$850,833$Lien
Jack LafontaineMonarchs (LA )G221998-01-06Yes197 Lbs6 ft3NoNoNo1Pro & Farm700,000$70,000$0$NoLien
Liam O'BrienMonarchs (LA )C/LW261994-07-29No213 Lbs6 ft1NoNoNo1Pro & Farm750,000$75,000$0$NoLien
Mitchell StephensMonarchs (LA )C231997-02-05No190 Lbs5 ft11NoNoNo1Pro & Farm700,000$70,000$0$NoLien
Nick HenryMonarchs (LA )RW211999-07-04No192 Lbs5 ft11NoNoNo3Pro & Farm783,935$78,394$0$No783,935$783,935$Lien
Stefan MatteauMonarchs (LA )LW261994-02-23No208 Lbs6 ft2NoNoNo2Pro & Farm600,000$60,000$0$No600,000$Lien
Steven LorentzMonarchs (LA )C/LW/RW241996-04-13No206 Lbs6 ft4NoNoNo3Pro & Farm728,333$72,833$0$No728,333$728,333$Lien
Viktor LoovMonarchs (LA )D271992-11-16No212 Lbs6 ft1NoNoNo1Pro & Farm690,000$69,000$0$NoLien
Wouter PeetersMonarchs (LA )G221998-07-31Yes205 Lbs6 ft4NoNoNo1Pro & Farm700,000$70,000$0$NoLien
Zach SawchenkoMonarchs (LA )G221997-12-30Yes185 Lbs6 ft1NoNoNo3Pro & Farm560,000$56,000$0$No560,000$560,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2123.81195 Lbs6 ft12.00758,600$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Stefan MatteauMitchell StephensSteven Lorentz40122
2Giovanni FioreLiam O'BrienNick Henry30122
3Dalton SmithConnor ZaryGraeme Clarke20122
4Mitchell StephensBen JohnsonStefan Matteau10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Derrick PouliotDennis Cholowski40122
2Andreas EnglundFrederic Allard30122
3Viktor LoovDmitry Sinitsyn20122
4Derrick PouliotDennis Cholowski10122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Stefan MatteauMitchell StephensSteven Lorentz60122
2Giovanni FioreLiam O'BrienNick Henry40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Derrick PouliotDennis Cholowski60122
2Andreas EnglundFrederic Allard40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Mitchell StephensStefan Matteau60122
2Liam O'BrienConnor Zary40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Derrick PouliotDennis Cholowski60122
2Andreas EnglundFrederic Allard40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Mitchell Stephens60122Derrick PouliotDennis Cholowski60122
2Stefan Matteau40122Andreas EnglundFrederic Allard40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Mitchell StephensStefan Matteau60122
2Liam O'BrienConnor Zary40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Derrick PouliotDennis Cholowski60122
2Andreas EnglundFrederic Allard40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Stefan MatteauMitchell StephensSteven LorentzDerrick PouliotDennis Cholowski
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Stefan MatteauMitchell StephensSteven LorentzDerrick PouliotDennis Cholowski
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Graeme Clarke, Dalton Smith, Ben JohnsonGraeme Clarke, Dalton SmithBen Johnson
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Viktor Loov, Dmitry Sinitsyn, Andreas EnglundViktor LoovDmitry Sinitsyn, Andreas Englund
Tirs de pénalité
Mitchell Stephens, Stefan Matteau, Liam O'Brien, Connor Zary, Steven Lorentz
Gardien
#1 : , #2 :


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
TotalDomicileVisiteur
# 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
1Admirals504000011527-122010000168-230300000919-1010.100152843009510076121439051018100551226624314520630.00%19573.68%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
2Baby Hawks3110000168-21010000002-22100000166030.500611170095100761210390510181005511144523951400.00%8450.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
3Bears2010001035-21010000014-31000001021120.5003360095100761255905101810055181208546116.67%40100.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
4Bruins20100010660100000102111010000045-120.50069150095100761247905101810055165361645500.00%5180.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
5Cabaret Lady Mary Ann220000001165110000006421100000052341.0001120310095100761288905101810055171296638112.50%30100.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
6Caroline22000000633110000004221100000021141.00061117009510076126690510181005516824934100.00%20100.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
7Chiefs3110000169-31010000015-42100000154130.50069150095100761283905101810055110229266417423.53%13284.62%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
8Chill3110010089-12010010058-31100000031230.500814220095100761293905101810055112234197810110.00%6350.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
9Comets413000001214-2211000008802020000046-220.2501223350095100761214190510181005511434329849333.33%11281.82%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
10Cougars20100001711-41000000156-11010000025-310.2507101700951007612579051018100551943812508225.00%6183.33%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
11Crunch2020000057-21010000023-11010000034-100.000591400951007612107905101810055158914618112.50%7185.71%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
12Heat412010001417-32100100086220200000611-540.50014243810951007612143905101810055115049341139333.33%17476.47%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
13Jayhawks43100000171522110000078-122000000107360.750172744009510076121749051018100551146382911414535.71%12375.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
14Las Vegas4210001016106210000107432110000096360.75016264200951007612156905101810055120040211041119.09%8275.00%11372287947.66%1359311443.64%616134445.83%1882127620206151080531
15Manchots20100010910-1100000105411010000046-220.5009132200951007612829051018100551952617505120.00%6433.33%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
16Marlies2110000067-11010000035-21100000032120.5006111700951007612639051018100551701820588225.00%9188.89%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
17Minnesota32100000141222200000011831010000034-140.66714264000951007612143905101810055111224127410110.00%6266.67%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
18Monsters2110000079-2110000006421010000015-420.5007121900951007612749051018100551102201042500.00%50100.00%11372287947.66%1359311443.64%616134445.83%1882127620206151080531
19Monsters321000009902110000057-21100000042240.6679142300951007612919051018100551964022601119.09%6183.33%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
20Oceanics312000001011-1110000006242020000049-520.3331014240095100761211790510181005511583621846233.33%70100.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
21Oil Kings4220000012111211000007612110000055040.50012213300951007612141905101810055114142348911218.18%16475.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
22Phantoms200000119901000000156-11000001043130.7509152400951007612759051018100551923045468337.50%13376.92%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
23Rocket2110000057-2110000003211010000025-320.500591400951007612479051018100551953320569444.44%10460.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
24Senators22000000835110000002021100000063341.0008142201951007612849051018100551851832509222.22%11190.91%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
25Sharks412001001113-2211000005502010010068-230.3751119300095100761210490510181005511684227918112.50%11190.91%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
26Sound Tigers2010000169-31010000035-21000000134-110.2506111700951007612689051018100551104312046500.00%10370.00%11372287947.66%1359311443.64%616134445.83%1882127620206151080531
27Spiders2110000089-11010000057-21100000032120.50081523009510076129790510181005518124205713215.38%10370.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
28Stars312000001314-121100000101001010000034-120.3331321340095100761210790510181005511274740626233.33%12375.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
29Thunder211000009631010000034-11100000062420.50091524009510076121019051018100551812412462150.00%60100.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
30Wolf Pack20200000911-21010000056-11010000045-100.0009172600951007612929051018100551922824438112.50%5180.00%01372287947.66%1359311443.64%616134445.83%1882127620206151080531
Total82303801256277297-2041161701133146150-441142100123131147-16800.4882774717481195100761229429051018100551333997966520582645320.08%2645977.65%31372287947.66%1359311443.64%616134445.83%1882127620206151080531
_Since Last GM Reset82303801256277297-2041161701133146150-441142100123131147-16800.4882774717481195100761229429051018100551333997966520582645320.08%2645977.65%31372287947.66%1359311443.64%616134445.83%1882127620206151080531
_Vs Conference3791900243124144-201849001226269-719510001216275-13310.419124210334019510076121295905101810055116224493349351182319.49%1272679.53%21372287947.66%1359311443.64%616134445.83%1882127620206151080531
_Vs Division1647002105753482300110262518240010031283120.3755797154019510076125949051018100551619205132429571322.81%57984.21%01372287947.66%1359311443.64%616134445.83%1882127620206151080531

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8280L327747174829423339979665205811
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8230381256277297
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4116171133146150
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4114210123131147
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
2645320.08%2645977.65%3
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
9051018100551951007612
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
1372287947.66%1359311443.64%616134445.83%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1882127620206151080531


Derniers matchs 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 - 2021-10-1530Monarchs3Oil Kings1WSommaire du match
7 - 2021-10-1842Monarchs2Heat4LSommaire du match
8 - 2021-10-1946Monarchs2Comets3LSommaire du match
11 - 2021-10-2263Chill4Monarchs3LXSommaire du match
12 - 2021-10-2376Las Vegas2Monarchs3WXXSommaire du match
14 - 2021-10-2591Caroline2Monarchs4WSommaire du match
16 - 2021-10-27106Crunch3Monarchs2LSommaire du match
18 - 2021-10-29122Heat3Monarchs4WSommaire du match
21 - 2021-11-01140Monarchs1Oceanics4LSommaire du match
23 - 2021-11-03149Monarchs1Chiefs2LXXSommaire du match
25 - 2021-11-05167Monarchs3Minnesota4LSommaire du match
26 - 2021-11-06172Monarchs2Baby Hawks3LXXSommaire du match
29 - 2021-11-09193Comets5Monarchs2LSommaire du match
32 - 2021-11-12217Baby Hawks2Monarchs0LSommaire du match
35 - 2021-11-15228Monarchs3Marlies2WSommaire du match
37 - 2021-11-17242Monarchs6Senators3WSommaire du match
39 - 2021-11-19255Monarchs2Rocket5LSommaire du match
42 - 2021-11-22279Minnesota3Monarchs4WSommaire du match
44 - 2021-11-24293Cougars6Monarchs5LXXSommaire du match
46 - 2021-11-26312Las Vegas2Monarchs4WSommaire du match
48 - 2021-11-28317Monarchs6Jayhawks5WSommaire du match
51 - 2021-12-01345Oil Kings5Monarchs4LSommaire du match
53 - 2021-12-03350Jayhawks5Monarchs3LSommaire du match
55 - 2021-12-05373Sharks2Monarchs4WSommaire du match
57 - 2021-12-07388Sound Tigers5Monarchs3LSommaire du match
59 - 2021-12-09393Monarchs3Sharks4LXSommaire du match
60 - 2021-12-10414Oceanics2Monarchs6WSommaire du match
62 - 2021-12-12423Monarchs1Admirals3LSommaire du match
64 - 2021-12-14437Bears4Monarchs1LSommaire du match
66 - 2021-12-16450Monarchs2Oil Kings4LSommaire du match
67 - 2021-12-17462Monarchs4Heat7LSommaire du match
70 - 2021-12-20483Wolf Pack6Monarchs5LSommaire du match
72 - 2021-12-22497Monarchs5Admirals8LSommaire du match
74 - 2021-12-24511Monarchs4Manchots6LSommaire du match
75 - 2021-12-25517Monarchs2Cougars5LSommaire du match
77 - 2021-12-27524Monarchs4Bruins5LSommaire du match
79 - 2021-12-29541Monarchs1Monsters5LSommaire du match
81 - 2021-12-31552Monarchs3Crunch4LSommaire du match
83 - 2022-01-02581Chiefs5Monarchs1LSommaire du match
87 - 2022-01-06592Monarchs3Sharks4LSommaire du match
88 - 2022-01-07599Monarchs2Comets3LSommaire du match
91 - 2022-01-10622Phantoms6Monarchs5LXXSommaire du match
95 - 2022-01-14652Chill4Monarchs2LSommaire du match
97 - 2022-01-16662Monsters4Monarchs6WSommaire du match
99 - 2022-01-18677Stars3Monarchs4WSommaire du match
100 - 2022-01-19686Monarchs6Las Vegas2WSommaire du match
102 - 2022-01-21697Monarchs2Caroline1WSommaire du match
105 - 2022-01-24716Monarchs6Thunder2WSommaire du match
107 - 2022-01-26729Monarchs5Cabaret Lady Mary Ann2WSommaire du match
109 - 2022-01-28750Monarchs4Phantoms3WXXSommaire du match
120 - 2022-02-08779Thunder4Monarchs3LSommaire du match
121 - 2022-02-09784Monarchs4Jayhawks2WSommaire du match
123 - 2022-02-11804Admirals5Monarchs4LXXSommaire du match
126 - 2022-02-14817Monarchs2Bears1WXXSommaire du match
128 - 2022-02-16831Monarchs3Sound Tigers4LXXSommaire du match
130 - 2022-02-18849Monarchs3Spiders2WSommaire du match
131 - 2022-02-19857Monarchs4Wolf Pack5LSommaire du match
134 - 2022-02-22878Heat3Monarchs4WXSommaire du match
137 - 2022-02-25902Monarchs4Monsters2WSommaire du match
140 - 2022-02-28926Monarchs3Oceanics5LSommaire du match
142 - 2022-03-02940Cabaret Lady Mary Ann4Monarchs6WSommaire du match
144 - 2022-03-04958Monsters6Monarchs2LSommaire du match
145 - 2022-03-05966Oil Kings1Monarchs3WSommaire du match
148 - 2022-03-08983Manchots4Monarchs5WXXSommaire du match
151 - 2022-03-111000Spiders7Monarchs5LSommaire du match
152 - 2022-03-121016Monarchs3Las Vegas4LSommaire du match
156 - 2022-03-161041Marlies5Monarchs3LSommaire du match
158 - 2022-03-181052Minnesota5Monarchs7WSommaire du match
160 - 2022-03-201069Monsters1Monarchs3WSommaire du match
162 - 2022-03-221082Senators0Monarchs2WSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
165 - 2022-03-251099Admirals3Monarchs2LSommaire du match
168 - 2022-03-281131Rocket2Monarchs3WSommaire du match
170 - 2022-03-301144Bruins1Monarchs2WXXSommaire du match
172 - 2022-04-011161Comets3Monarchs6WSommaire du match
173 - 2022-04-021169Jayhawks3Monarchs4WSommaire du match
175 - 2022-04-041184Monarchs3Stars4LSommaire du match
177 - 2022-04-061197Monarchs3Chill1WSommaire du match
178 - 2022-04-071200Monarchs4Chiefs2WSommaire du match
180 - 2022-04-091217Monarchs4Baby Hawks3WSommaire du match
182 - 2022-04-111238Sharks3Monarchs1LSommaire du match
185 - 2022-04-141256Monarchs3Admirals8LSommaire du match
186 - 2022-04-151270Stars7Monarchs6LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5020
Assistance50,71127,585
Assistance PCT61.84%67.28%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 1910 - 63.66% 75,299$3,087,250$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,737,088$ 1,593,060$ 1,603,060$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,573$ 1,747,161$ 21 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 8,519$ 0$




TotalDomicileVisiteur
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