Connexion

Monarchs
GP: 81 | W: 39 | L: 36 | OTL: 6 | P: 84
GF: 151 | GA: 179 | PP%: 15.74% | PK%: 86.96%
DG: Antoine Pelletier | Morale : 50 | Moyenne d’équipe : 55
Prochains matchs #1312 vs Baby Hawks
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Centre de jeu
Admirals
38-33-10, 86pts
0
FINAL
1 Monarchs
39-36-6, 84pts
Team Stats
SOL1SéquenceW4
18-20-3Fiche domicile20-18-2
20-13-7Fiche domicile19-18-4
3-5-2Derniers 10 matchs7-2-1
1.98Buts par match 1.86
2.15Buts contre par match 2.21
13.24%Pourcentage en avantage numérique15.74%
84.96%Pourcentage en désavantage numérique86.96%
Minnesota
34-44-3, 71pts
1
FINAL
2 Monarchs
39-36-6, 84pts
Team Stats
OTL1SéquenceW4
21-18-1Fiche domicile20-18-2
13-26-2Fiche domicile19-18-4
3-6-1Derniers 10 matchs7-2-1
2.46Buts par match 1.86
2.70Buts contre par match 2.21
11.11%Pourcentage en avantage numérique15.74%
80.95%Pourcentage en désavantage numérique86.96%
Baby Hawks
54-19-7, 115pts
2024-04-18
Monarchs
39-36-6, 84pts
Statistiques d’équipe
L1SéquenceW4
30-8-3Fiche domicile20-18-2
24-11-4Fiche visiteur19-18-4
7-3-010 derniers matchs7-2-1
2.66Buts par match 1.86
1.81Buts contre par match 1.86
20.75%Pourcentage en avantage numérique15.74%
86.67%Pourcentage en désavantage numérique86.96%
Meneurs d'équipe
Buts
Graeme Clarke
30
Passes
Tyler Kleven
42
Points
Tyler Kleven
56
Plus/Moins
Graeme Clarke
5
Victoires
Zachary Sawchenko
39
Pourcentage d’arrêts
Hugo Alnefelt
0.898

Statistiques d’équipe
Buts pour
151
1.86 GFG
Tirs pour
1404
17.33 Avg
Pourcentage en avantage numérique
15.7%
34 GF
Début de zone offensive
37.5%
Buts contre
179
2.21 GAA
Tirs contre
1629
20.11 Avg
Pourcentage en désavantage numérique
87.0%%
30 GA
Début de la zone défensive
40.9%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance1,935
Billets de saison300


Informations de la formation

Équipe Pro21
Équipe Mineure20
Limite contact 41 / 50
Espoirs11


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
1Connor Zary (R)X100.00614962706262616560636060655050050610211925,000$
2Graeme Clarke (R)XX100.00604470716062616643636160665050050610211850,833$
3Joseph BlandisiX100.00584562696168676358625760635751050610281650,000$
4Owen Sillinger (R)X100.00555362665765666353625754625250050590253825,000$
5Nick Henry (R)X100.00706983656943434649434259424444050520231783,935$
6Topi Ronni (R)X100.0045454545454545454545454545454501450183825,000$
7Hunter Haight (R)X100.0045454545454545454545454545454501450183897,500$
8Ilya Fedotov (R)X100.0045454545454545454545454545454501450193925,000$
9Jack Harvey (R)X100.0037373737373737373737373737373701380193620,000$
10Stiven Sardarian (R)X100.001111111111111110150193700,000$
11Jordan SpenceX100.00564372736170636840665767665150050640213820,000$
12Tyler Kleven (R)X100.00574071698078606540626062655150050640203916,667$
13Dennis CholowskiX100.00614568686564646440645268625350050630241850,000$
14Ryker Evans (R)X100.00654161696262626540655768635050050630203897,500$
15Brandon Scanlin (R)X100.00685365647163626040555367595250050620233925,000$
16Frederic AllardX100.00604466706263626040535366615350050610241600,000$
Rayé
1Mitchell StephensX100.00604370716770676664636162665650050630251900,000$
2Gage QuinneyX100.00584469696266666543636159655550050620271715,000$
MOYENNE D’ÉQUIPE100.0053445959565654554453505554474503654
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 SPÂgeContratSalaire moyen
1Zachary Sawchenko (R)100.0072666664686769656869615651050620271560,000$
2Hugo Alnefelt (R)100.0070616165676870686966585050050610213850,833$
Rayé
1Calle Clang (R)100.0062575766615959576059535050050550203878,333$
MOYENNE D’ÉQUIPE100.006861616565656663666557525005059
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
1Tyler KlevenMonarchs (LA )D81144256470016614614553909.66%75184822.8271017921930110165230%000000.6101000665
2Graeme ClarkeMonarchs (LA )C/RW813023535260155207308742399.74%17174821.583710441830003717147.93%29000000.61190001172
3Dennis CholowskiMonarchs (LA )D8183139-2260018912610629647.55%84152118.794812721640000147210%000000.5100000055
4Connor ZaryMonarchs (LA )C76171532-43751051681564510710.90%9114715.100337450000423059.59%112600000.5628000514
5Ryker EvansMonarchs (LA )D81101727-656012710636122627.78%61121715.03516174700001051233.33%300000.4400000125
6Joseph BlandisiMonarchs (LA )C3612820-7220448782234714.63%368619.063585580000143055.51%54400000.5823000230
7Brandon ScanlinMonarchs (LA )D8111920-1344099771914145.26%3990611.190113210000381050.00%200000.4400000022
8Jordan SpenceMonarchs (LA )D3521416-318047573514265.71%2578122.341341860000069000%000000.4101000202
9Nick HenryMonarchs (LA )RW819615-214401149511630757.76%11134316.591123600000343054.95%9100000.2201000042
10Owen SillingerMonarchs (LA )C818715-1100537773135410.96%96998.641343480000341149.34%53100000.4312000122
11Ilya FedotovMonarchs (LA )LW816612-12300853749133612.24%6140117.300000610000632145.65%9200000.1700000203
12Frederic AllardMonarchs (LA )D8111011-122207067279223.70%28108913.45000012000045000%000000.2000000020
13Topi RonniMonarchs (LA )C81358-1112041252432512.50%388210.90000090001190146.27%6700000.1800000000
14Andreas EnglundLA KingsD5055-1201986140%712124.35022312000013000%000000.8200000000
15Hunter HaightMonarchs (LA )C81145-182605913256224.00%5111913.8100003000000037.70%6100000.0900000100
16Mitchell StephensMonarchs (LA )C5134-140310132107.69%29619.351123120000140053.72%12100000.8311000010
17Gage QuinneyMonarchs (LA )LW5202-1407694622.22%011122.371013100000140112.50%800000.3601000100
18Stiven SardarianMonarchs (LA )RW28000-800500000%038613.8000001200000000%180000000000000
19Jack HarveyMonarchs (LA )C28000-9402942040%141014.6700002000000047.37%190000000000000
Statistiques d’équipe totales ou en moyenne1109125215340-141491514171316123134587110.15%3851752215.8027457227310220114898251153.72%297300000.39727000323532
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
1Zachary SawchenkoMonarchs (LA )81393660.8932.13475901016915790310.81332810766
2Hugo AlnefeltMonarchs (LA )60000.8982.011490054900000081000
Statistiques d’équipe totales ou en moyenne87393660.8932.1349090101741628031328181766


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 Recrue Poids Taille Non-échange Disponible pour échange Ballotage forcé Waiver Possible Contrat Type Salaire actuel Salaire moyen 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 10Lien
Brandon ScanlinMonarchs (LA )D231999-06-02Yes214 Lbs6 ft4NoNoNoNo3Pro & Farm925,000$14,453$0$0$No925,000$925,000$Lien
Calle ClangMonarchs (LA )G202002-05-20Yes194 Lbs6 ft2NoNoNoNo3Pro & Farm878,333$13,724$0$0$No878,333$878,333$
Connor ZaryMonarchs (LA )C212001-09-25Yes179 Lbs6 ft0NoNoNoNo1Pro & Farm925,000$14,453$0$0$NoLien
Dennis CholowskiMonarchs (LA )D241998-02-15No196 Lbs6 ft2NoNoYesYes1Pro & Farm850,000$13,281$0$0$NoLien
Frederic Allard (contrat à 1 volet)Monarchs (LA )D241997-12-27No179 Lbs6 ft1NoNoYesYes1Pro & Farm600,000$9,375$0$0$NoLien
Gage Quinney (contrat à 1 volet)Monarchs (LA )LW271995-07-29No194 Lbs6 ft0NoNoYesYes1Pro & Farm715,000$11,172$0$0$NoLien
Graeme ClarkeMonarchs (LA )C/RW212001-04-24Yes174 Lbs6 ft0NoNoNoNo1Pro & Farm850,833$13,294$0$0$NoLien
Hugo AlnefeltMonarchs (LA )G212001-06-04Yes176 Lbs6 ft2NoNoNoNo3Pro & Farm850,833$13,294$0$0$No850,833$850,833$Lien
Hunter HaightMonarchs (LA )C182004-04-04 16:15:01Yes180 Lbs5 ft11NoNoNoNo3Pro & Farm897,500$14,023$0$0$No897,500$897,500$
Ilya FedotovMonarchs (LA )LW192003-03-19 16:15:40Yes182 Lbs6 ft1NoNoNoNo3Pro & Farm925,000$14,453$0$0$No925,000$925,000$
Jack HarveyMonarchs (LA )C192003-03-30 16:16:13Yes175 Lbs5 ft10NoNoNoNo3Pro & Farm620,000$9,688$0$0$No620,000$620,000$
Jordan SpenceMonarchs (LA )D212001-02-24No163 Lbs5 ft10NoNoNoNo3Pro & Farm820,000$12,812$0$0$No820,000$820,000$Lien
Joseph Blandisi (contrat à 1 volet)Monarchs (LA )C281994-07-18No183 Lbs6 ft0NoNoYesYes1Pro & Farm650,000$10,156$0$0$NoLien
Mitchell StephensMonarchs (LA )C251997-02-05No190 Lbs5 ft11NoNoYesYes1Pro & Farm900,000$14,062$0$0$NoLien
Nick HenryMonarchs (LA )RW231999-07-04Yes190 Lbs5 ft11NoNoNoNo1Pro & Farm783,935$12,249$0$0$NoLien
Owen SillingerMonarchs (LA )C251997-09-23Yes170 Lbs5 ft10NoNoYesYes3Pro & Farm825,000$12,891$0$0$No825,000$825,000$Lien
Ryker EvansMonarchs (LA )D202001-12-13Yes190 Lbs5 ft11NoNoNoNo3Pro & Farm897,500$14,023$0$0$No897,500$897,500$
Stiven SardarianMonarchs (LA )RW192003-02-07 16:14:14Yes156 Lbs6 ft1NoNoNoNo3Pro & Farm700,000$10,938$0$0$No700,000$700,000$
Topi RonniMonarchs (LA )C182004-05-05 16:13:26Yes179 Lbs6 ft2NoNoNoNo3Pro & Farm825,000$12,891$0$0$No825,000$825,000$
Tyler KlevenMonarchs (LA )D202002-01-10Yes200 Lbs6 ft4NoNoNoNo3Pro & Farm916,667$14,323$0$0$No916,667$916,667$
Zachary SawchenkoMonarchs (LA )G271995-05-28Yes187 Lbs6 ft2NoNoYesYes1Pro & Farm560,000$8,750$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2122.05183 Lbs6 ft12.14805,505$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ilya FedotovConnor ZaryGraeme Clarke40122
2Hunter HaightJoseph BlandisiNick Henry30122
3Jack HarveyOwen SillingerStiven Sardarian20122
4Ilya FedotovOwen SillingerGraeme Clarke10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan SpenceTyler Kleven40122
2Dennis CholowskiRyker Evans30122
3Brandon ScanlinFrederic Allard20122
4Jordan SpenceTyler Kleven10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ilya FedotovConnor ZaryGraeme Clarke60122
2Owen SillingerJoseph BlandisiNick Henry40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan SpenceTyler Kleven60122
2Dennis CholowskiRyker Evans40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Graeme ClarkeIlya Fedotov60122
2Connor ZaryOwen Sillinger40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan SpenceTyler Kleven60122
2Dennis CholowskiRyker Evans40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Graeme Clarke60122Jordan SpenceTyler Kleven60122
2Connor Zary40122Dennis CholowskiRyker Evans40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Graeme ClarkeIlya Fedotov60122
2Connor ZaryJoseph Blandisi40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan SpenceTyler Kleven60122
2Dennis CholowskiRyker Evans40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ilya FedotovConnor ZaryGraeme ClarkeJordan SpenceTyler Kleven
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ilya FedotovConnor ZaryGraeme ClarkeJordan SpenceTyler Kleven
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nick Henry, Ilya Fedotov, Topi RonniNick Henry, Ilya FedotovNick Henry
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ryker Evans, Brandon Scanlin, Frederic AllardRyker EvansRyker Evans, Brandon Scanlin
Tirs de pénalité
Graeme Clarke, Connor Zary, Joseph Blandisi, Owen Sillinger, Nick Henry
Gardien
#1 : Zachary Sawchenko, #2 : Hugo Alnefelt


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
1Admirals42100010633201000103302200000030360.7506915035651351167423475486515615165910220.00%6183.33%0937196547.68%958214144.75%542113347.84%1897133220215731000492
2Baby Hawks2020000047-31010000024-21010000023-100.000481210565135112242347548651471514284125.00%7271.43%0937196547.68%958214144.75%542113347.84%1897133220215731000492
3Bears21000001431110000002021000000123-130.75048120156513511344234754865130171436200.00%70100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
4Bruins2010001024-2100000102111010000003-320.50021300565135112142347548651461814291000.00%6266.67%0937196547.68%958214144.75%542113347.84%1897133220215731000492
5Cabaret Lady Mary Ann2110000045-11010000003-31100000042220.500471100565135115042347548651381631358225.00%9277.78%1937196547.68%958214144.75%542113347.84%1897133220215731000492
6Caroline2010000147-31010000035-21000000112-110.250481200565135112242347548651431418307228.57%9277.78%0937196547.68%958214144.75%542113347.84%1897133220215731000492
7Chiefs3020001059-41010000023-12010001036-320.333561100565135114242347548651721920508112.50%10190.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
8Chill330000001055220000007431100000031261.00010172700565135115542347548651681526653133.33%12283.33%0937196547.68%958214144.75%542113347.84%1897133220215731000492
9Comets4120000169-32020000015-42100000154130.375611170056513511454234754865172151285600.00%6266.67%0937196547.68%958214144.75%542113347.84%1897133220215731000492
10Cougars21100000651110000003121010000034-120.5006121800565135115342347548651541416258112.50%8275.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
11Crunch2020000004-41010000002-21010000002-200.0000000056513511354234754865152141851300.00%90100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
12Heat4120100078-1210010005322020000025-340.5007132000565135115442347548651611528509222.22%12191.67%0937196547.68%958214144.75%542113347.84%1897133220215731000492
13Jayhawks3300000014311110000006152200000082661.00014193300565135118842347548651692016635120.00%80100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
14Las Vegas3020100036-3100010001012020000026-420.3333690156513511544234754865144201854700.00%8187.50%0937196547.68%958214144.75%542113347.84%1897133220215731000492
15Manchots2110000037-4110000002111010000016-520.500369005651351130423475486513878378112.50%40100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
16Marlies21000100440110000002111000010023-130.75047110056513511344234754865144710388112.50%40100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
17Minnesota31101000871201010003301100000054140.6678142200565135115642347548651631516606350.00%80100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
18Monsters22000000422110000001011100000032141.0004590156513511334234754865134712404250.00%60100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
19Monsters3030000027-52020000024-21010000003-300.00023500565135115642347548651571520481715.88%100100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
20Oceanics30200010713-61010000015-42010001068-220.333712190056513511524234754865176192469600.00%12283.33%0937196547.68%958214144.75%542113347.84%1897133220215731000492
21Oil Kings43100000844211000004402200000040460.75081321025651351179423475486515619169211218.18%6183.33%0937196547.68%958214144.75%542113347.84%1897133220215731000492
22Phantoms211000001101010000001-11100000010120.50012301565135113142347548651351014461218.33%5180.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
23Rocket211000005501010000024-21100000031220.500591400565135114242347548651401012425120.00%5180.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
24Sags44000000945220000004222200000052381.00091726005651351173423475486516626206511218.18%80100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
25Seattle30200001413-92010000139-61010000014-310.1674812005651351149423475486517220146210110.00%6266.67%0937196547.68%958214144.75%542113347.84%1897133220215731000492
26Senators211000004401010000002-21100000042220.50047110056513511234234754865143111639400.00%7185.71%0937196547.68%958214144.75%542113347.84%1897133220215731000492
27Sound Tigers21000010422110000001011000001032141.000459015651351136423475486512896298337.50%30100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
28Spiders2110000034-1110000002111010000013-220.5003580056513511324234754865134712394125.00%60100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
29Stars3020001049-5100000103212020000017-620.333461000565135113842347548651721522578225.00%11372.73%0937196547.68%958214144.75%542113347.84%1897133220215731000492
30Thunder2020000026-41010000002-21010000024-200.0002460056513511584234754865157161249000%50100.00%0937196547.68%958214144.75%542113347.84%1897133220215731000492
31Wolf Pack2010010049-51000010045-11010000004-410.25046100056513511404234754865162161655400.00%7185.71%0937196547.68%958214144.75%542113347.84%1897133220215731000492
Total81303603264151179-28401418031317181-10411618001338098-18840.51915125440511056513511140442347548651162945651115272163415.74%2303086.96%1937196547.68%958214144.75%542113347.84%1897133220215731000492
_Since Last GM Reset81303603264151179-28401418031317181-10411618001338098-18840.51915125440511056513511140442347548651162945651115272163415.74%2303086.96%1937196547.68%958214144.75%542113347.84%1897133220215731000492
_Vs Conference361811002416771-41810500120312831886001213643-7470.65367111178075651351161942347548651717200220695941414.89%981089.80%0937196547.68%958214144.75%542113347.84%1897133220215731000492
_Vs Division1683001202737-1085100010916-7832001101821-3210.65627477400565135113164234754865137410612930846510.87%53884.91%1937196547.68%958214144.75%542113347.84%1897133220215731000492

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8184W4151254405140416294565111527110
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8130363264151179
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
40141831317181
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
41161801338098
Derniers 10 matchs
WLOTWOTL SOWSOL
720001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2163415.74%2303086.96%1
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
4234754865156513511
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
937196547.68%958214144.75%542113347.84%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1897133220215731000492


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
2 - 2023-10-117Monsters2Monarchs1BLSommaire du match
5 - 2023-10-1432Caroline5Monarchs3BLSommaire du match
8 - 2023-10-1745Monarchs2Oceanics5ALSommaire du match
10 - 2023-10-1956Monarchs5Minnesota4AWSommaire du match
12 - 2023-10-2179Bruins1Monarchs2BWXXSommaire du match
15 - 2023-10-2497Jayhawks1Monarchs6BWSommaire du match
18 - 2023-10-27115Monarchs5Jayhawks1AWSommaire du match
19 - 2023-10-28125Las Vegas0Monarchs1BWXSommaire du match
22 - 2023-10-31139Monarchs2Marlies3ALXSommaire du match
24 - 2023-11-02149Monarchs4Senators2AWSommaire du match
26 - 2023-11-04164Monarchs1Phantoms0AWSommaire du match
30 - 2023-11-08192Monarchs0Las Vegas3ALSommaire du match
31 - 2023-11-09202Manchots1Monarchs2BWSommaire du match
33 - 2023-11-11221Phantoms1Monarchs0BLSommaire du match
38 - 2023-11-16249Cabaret Lady Mary Ann3Monarchs0BLSommaire du match
40 - 2023-11-18266Chiefs3Monarchs2BLSommaire du match
42 - 2023-11-20276Monarchs3Jayhawks1AWSommaire du match
46 - 2023-11-24299Monarchs1Admirals0AWSommaire du match
47 - 2023-11-25309Rocket4Monarchs2BLSommaire du match
51 - 2023-11-29339Bears0Monarchs2BWSommaire du match
55 - 2023-12-03373Monsters2Monarchs1BLSommaire du match
57 - 2023-12-05381Monarchs3Monsters2AWSommaire du match
59 - 2023-12-07394Monarchs3Rocket1AWSommaire du match
61 - 2023-12-09415Monarchs3Sound Tigers2AWXXSommaire du match
62 - 2023-12-10424Monarchs0Wolf Pack4ALSommaire du match
65 - 2023-12-13446Oceanics5Monarchs1BLSommaire du match
68 - 2023-12-16471Monarchs1Seattle4ALSommaire du match
71 - 2023-12-19494Monarchs3Sags1AWSommaire du match
72 - 2023-12-20497Seattle6Monarchs1BLSommaire du match
75 - 2023-12-23526Heat2Monarchs3BWSommaire du match
79 - 2023-12-27541Sags1Monarchs2BWSommaire du match
80 - 2023-12-28544Monarchs2Las Vegas3ALSommaire du match
82 - 2023-12-30563Oil Kings3Monarchs4BWSommaire du match
85 - 2024-01-02585Marlies1Monarchs2BWSommaire du match
87 - 2024-01-04600Cougars1Monarchs3BWSommaire du match
90 - 2024-01-07618Monarchs2Bears3ALXXSommaire du match
92 - 2024-01-09626Monarchs2Thunder4ALSommaire du match
94 - 2024-01-11641Monarchs4Cabaret Lady Mary Ann2AWSommaire du match
96 - 2024-01-13660Monarchs3Cougars4ALSommaire du match
98 - 2024-01-15675Monarchs1Caroline2ALXXSommaire du match
99 - 2024-01-16684Monarchs0Stars3ALSommaire du match
101 - 2024-01-18699Chill2Monarchs3BWSommaire du match
103 - 2024-01-20717Wolf Pack5Monarchs4BLXSommaire du match
105 - 2024-01-22729Sags1Monarchs2BWSommaire du match
107 - 2024-01-24745Crunch2Monarchs0BLSommaire du match
109 - 2024-01-26757Monarchs0Monsters3ALSommaire du match
111 - 2024-01-28773Monarchs3Chiefs2AWXXSommaire du match
114 - 2024-01-31779Monarchs3Chill1AWSommaire du match
124 - 2024-02-10816Oil Kings1Monarchs0BLSommaire du match
127 - 2024-02-13824Monarchs0Crunch2ALSommaire du match
129 - 2024-02-15839Monarchs1Spiders3ALSommaire du match
131 - 2024-02-17855Monarchs0Bruins3ALSommaire du match
132 - 2024-02-18865Monarchs1Manchots6ALSommaire du match
134 - 2024-02-20883Monsters0Monarchs1BWSommaire du match
136 - 2024-02-22899Chill2Monarchs4BWSommaire du match
138 - 2024-02-24915Admirals3Monarchs2BLSommaire du match
140 - 2024-02-26925Monarchs1Oil Kings0AWSommaire du match
141 - 2024-02-27935Monarchs0Heat2ALSommaire du match
143 - 2024-02-29951Monarchs2Comets3ALXXSommaire du match
146 - 2024-03-03970Spiders1Monarchs2BWSommaire du match
148 - 2024-03-05988Comets2Monarchs1BLSommaire du match
150 - 2024-03-071003Senators2Monarchs0BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
152 - 2024-03-091021Stars2Monarchs3BWXXSommaire du match
154 - 2024-03-111030Sound Tigers0Monarchs1BWSommaire du match
156 - 2024-03-131041Monarchs0Chiefs4ALSommaire du match
158 - 2024-03-151058Monarchs2Baby Hawks3ALSommaire du match
159 - 2024-03-161068Monarchs1Stars4ALSommaire du match
162 - 2024-03-191092Baby Hawks4Monarchs2BLSommaire du match
163 - 2024-03-201097Minnesota2Monarchs1BLSommaire du match
166 - 2024-03-231121Thunder2Monarchs0BLSommaire du match
168 - 2024-03-251135Monarchs3Comets1AWSommaire du match
171 - 2024-03-281160Monarchs3Oil Kings0AWSommaire du match
173 - 2024-03-301179Monarchs2Heat3ALSommaire du match
175 - 2024-04-011187Monarchs4Oceanics3AWXXSommaire du match
177 - 2024-04-031201Seattle3Monarchs2BLXXSommaire du match
178 - 2024-04-041210Monarchs2Sags1AWSommaire du match
180 - 2024-04-061226Comets3Monarchs0BLSommaire du match
183 - 2024-04-091249Monarchs2Admirals0AWSommaire du match
185 - 2024-04-111264Heat1Monarchs2BWXSommaire du match
187 - 2024-04-131281Admirals0Monarchs1BWXXSommaire du match
189 - 2024-04-151293Minnesota1Monarchs2BWXSommaire du match
192 - 2024-04-181312Baby Hawks-Monarchs-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5020
Assistance50,65926,754
Assistance PCT63.32%66.89%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
1 1935 - 64.51% 92,041$3,681,636$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,416,973$ 1,495,060$ 1,495,060$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
7,787$ 1,416,973$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
92,041$ 3 7,787$ 23,361$




Monarchs Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Monarchs Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Monarchs Statistiques de l'Équipe de Carrière

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

Monarchs Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Monarchs Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA