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Connexion

Monarchs
GP: 11 | W: 5 | L: 6 | OTL: 0 | P: 10
GF: 42 | GA: 60 | PP%: 10.53% | PK%: 66.67%
DG: Thomas Belair-Ferland | Morale : 50 | Moyenne d’équipe : 57
Prochains matchs #177 vs Cougars

Centre de jeu
Monarchs
5-6-0, 10pts
4
FINAL
3 Baby Hawks
8-1-1, 17pts
Team Stats
L1SéquenceW1
1-2-0Fiche domicile5-1-0
4-4-0Fiche domicile3-0-1
5-5-0Derniers 10 matchs8-1-1
3.82Buts par match 4.80
5.45Buts contre par match 3.00
10.53%Pourcentage en avantage numérique23.81%
66.67%Pourcentage en désavantage numérique80.95%
Monarchs
5-6-0, 10pts
5
FINAL
10 Sags
7-3-0, 14pts
Team Stats
L1SéquenceW2
1-2-0Fiche domicile4-1-0
4-4-0Fiche domicile3-2-0
5-5-0Derniers 10 matchs7-3-0
3.82Buts par match 5.30
5.45Buts contre par match 4.40
10.53%Pourcentage en avantage numérique33.33%
66.67%Pourcentage en désavantage numérique65.22%
Cougars
2-5-3, 7pts
2025-10-30
Monarchs
5-6-0, 10pts
Statistiques d’équipe
OTL2SéquenceL1
1-3-2Fiche domicile1-2-0
1-2-1Fiche visiteur4-4-0
2-5-310 derniers matchs5-5-0
4.80Buts par match 3.82
6.10Buts contre par match 3.82
36.11%Pourcentage en avantage numérique10.53%
84.21%Pourcentage en désavantage numérique66.67%
Spiders
7-1-2, 16pts
2025-11-01
Monarchs
5-6-0, 10pts
Statistiques d’équipe
W4SéquenceL1
4-0-1Fiche domicile1-2-0
3-1-1Fiche visiteur4-4-0
7-1-210 derniers matchs5-5-0
5.60Buts par match 3.82
4.50Buts contre par match 3.82
15.79%Pourcentage en avantage numérique10.53%
72.22%Pourcentage en désavantage numérique66.67%
Oceanics
5-4-1, 11pts
2025-11-04
Monarchs
5-6-0, 10pts
Statistiques d’équipe
W2SéquenceL1
3-2-1Fiche domicile1-2-0
2-2-0Fiche visiteur4-4-0
5-4-110 derniers matchs5-5-0
5.70Buts par match 3.82
4.80Buts contre par match 3.82
39.02%Pourcentage en avantage numérique10.53%
69.23%Pourcentage en désavantage numérique66.67%
Meneurs d'équipe

Statistiques d’équipe
Buts pour
42
3.82 GFG
Tirs pour
242
22.00 Avg
Pourcentage en avantage numérique
10.5%
4 GF
Début de zone offensive
30.1%
Buts contre
60
5.45 GAA
Tirs contre
270
24.55 Avg
Pourcentage en désavantage numérique
66.7%%
10 GA
Début de la zone défensive
29.8%
Informations de l'équipe

Directeur généralThomas Belair-Ferland
DivisionAtlantique
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,891
Billets de saison300


Informations de la formation

Équipe Pro25
Équipe Mineure23
Limite contact 48 / 50
Espoirs15


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
1Oliver Wahlstrom (R)X100.006959727484827869476464676973630506802411,000,000$
2Jakub LaukoXXX100.008269717580807670496665707059500506802421,300,000$
3Ivan Ivan (R)X100.00584177717374636653626260665150050630222845,000$
4Luke Toporowski (R)X100.00594467666165636343605758625250050590231560,000$
5Hunter Haight (R)X100.00554265626161606242586054615050050580201897,500$
6Justin Gill (R)XXX100.00554166596260585740545453575050050550213620,000$
7Topi Ronni (R)X100.00394543434538383943383843414545050420201825,000$
8Ilya Fedotov (R)X100.00394543434538383943383843414545050420211925,000$
9Stiven Sardarian (R)X100.00333534343532323334323234343535050350211700,000$
10Jack Harvey (R)X100.00333735353731313335313135353737050350211620,000$
11Ryker Evans (R)X100.00714277797984737440736674735550050710221897,500$
12Tyler Kleven (R)X100.00745176728578727040646374695650050690221916,667$
13Nolan Allan (R)X100.00684177717576676640636070665250050660212825,000$
14Elias Petterssen (D) (R)X100.00634072697275626440616162655150050630203838,333$
15Topias Vilen (R)X100.00634271656563616240635367605050050610212836,667$
16Ben Roger (R)X100.00434343434343434343434343434343050440213825,000$
Rayé
1Chris TierneyX100.006244817377737766776359686684740506703021,425,000$
2Owen SillingerX100.00544568665768666245625654625550050590271825,000$
3Nick Henry (R)XHO6269796369373740473736573844440504802500$
4Robert HäggX100.006044666667737064406057676278550506402921,000,000$
5Brandon Scanlin (R)X100.00634468637067666340535962625450050610251925,000$
MOYENNE D’ÉQUIPE100.0057466462646259574455535857535005057
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
1Calle Clang (R)100.0069626466676669656767585150050610221878,333$
2Hugo Alnefelt100.0068616065656570646563555146050590231850,833$
Rayé
1Zach SawchenkoHO726464626666686467685955500506002600$
2Kyle Keyser (R)HO645856636058605458595153460505402500$
MOYENNE D’ÉQUIPE100.006861616465646762646456534805059
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
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


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Ben RogerMonarchs (LA )D212002-11-02CANYes201 Lbs5 ft4NoNoProspectNoNo32025-07-10FalseFalsePro & Farm825,000$0$0$No825,000$825,000$-------825,000$825,000$-------NoNo-------Lien
Brandon ScanlinMonarchs (LA )D251999-06-02CANYes214 Lbs6 ft4NoNoN/AYesYes1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien
Calle ClangMonarchs (LA )G222002-05-20SWEYes194 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm878,333$0$0$No---------------------------Lien
Chris Tierney (contrat à 1 volet)Monarchs (LA )C301994-07-01CANNo191 Lbs6 ft1NoNoN/AYesYes2FalseFalsePro & Farm1,425,000$505,000$447,435$No1,425,000$--------1,425,000$--------No--------Lien
Elias Petterssen (D)Monarchs (LA )D202004-02-16SWEYes185 Lbs6 ft2NoNoProspectNoNo32025-07-10FalseFalsePro & Farm838,333$0$0$No838,333$838,333$-------838,333$838,333$-------NoNo-------Lien
Hugo AlnefeltMonarchs (LA )G232001-06-04SWENo189 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm850,833$0$0$No---------------------------Lien
Hunter HaightMonarchs (LA )C202004-04-04CANYes181 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm897,500$0$0$No---------------------------Lien
Ilya FedotovMonarchs (LA )LW212003-03-19RUSYes182 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm925,000$0$0$No---------------------------Lien
Ivan IvanMonarchs (LA )C222002-08-20CZEYes190 Lbs6 ft0NoNoTrade2025-07-18NoNo22024-06-25FalseFalsePro & Farm845,000$0$0$No845,000$--------845,000$--------No--------Lien
Jack HarveyMonarchs (LA )C212003-03-30MNYes175 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm620,000$0$0$No---------------------------Lien
Jakub Lauko (contrat à 1 volet)Monarchs (LA )C/LW/RW242000-03-28CZENo193 Lbs6 ft1NoNoFree Agent2025-07-18NoYes22025-08-28FalseFalsePro & Farm1,300,000$380,000$336,684$No1,300,000$--------1,300,000$--------No--------Lien
Justin GillMonarchs (LA )C/LW/RW212003-01-27CANYes190 Lbs6 ft1NoNoDraftNoNo32025-07-10FalseFalsePro & Farm620,000$0$0$No620,000$620,000$-------620,000$620,000$-------NoNo-------Lien
Kyle KeyserMonarchs (LA )G251999-03-08USAYes186 Lbs6 ft2NoNoTrade2025-03-06YesYes0FalseFalsePro & Farm0$0$No---------------------------Lien
Luke ToporowskiMonarchs (LA )LW232001-04-12USAYes183 Lbs5 ft11NoNoTrade2025-07-18NoNo1FalseFalsePro & Farm560,000$0$0$No---------------------------Lien
Nick Henry (contrat à 1 volet)Monarchs (LA )RW251999-07-04MANYes190 Lbs5 ft11NoNoFree AgentYesYes02024-09-11FalseFalsePro & Farm0$0$No---------------------------Lien
Nolan AllanMonarchs (LA )D212003-04-28CANYes195 Lbs6 ft2NoNoProspectNoNo22024-06-25FalseFalsePro & Farm825,000$0$0$No825,000$--------825,000$--------No--------Lien
Oliver WahlstromMonarchs (LA )RW242000-06-13USAYes205 Lbs6 ft2NoNoTrade2025-07-18NoYes12024-09-11FalseFalsePro & Farm1,000,000$0$0$No---------------------------Lien
Owen SillingerMonarchs (LA )C271997-09-23CANNo170 Lbs5 ft10NoNoN/AYesYes1FalseFalsePro & Farm825,000$0$0$No---------------------------Lien
Robert Hägg (contrat à 1 volet)Monarchs (LA )D291995-02-08SWENo205 Lbs6 ft2NoNoN/AYesYes2FalseFalsePro & Farm1,000,000$80,000$70,881$No1,000,000$--------1,000,000$--------No--------Lien
Ryker EvansMonarchs (LA )D222001-12-13CANYes195 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm897,500$0$0$No---------------------------Lien
Stiven SardarianMonarchs (LA )RW212003-02-07RUSYes156 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Topi RonniMonarchs (LA )C202004-05-05FINYes179 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm825,000$0$0$No---------------------------Lien
Topias VilenMonarchs (LA )D212003-04-01FINYes194 Lbs6 ft1NoNoProspectNoNo22024-06-25FalseFalsePro & Farm836,667$0$0$No836,667$--------836,667$--------No--------Lien
Tyler KlevenMonarchs (LA )D222002-01-10USAYes221 Lbs6 ft5NoNoN/ANoNo1FalseFalsePro & Farm916,667$0$0$No---------------------------Lien
Zach SawchenkoMonarchs (LA )G261997-12-30CANNo185 Lbs6 ft1NoNoFree AgentYesYes02024-09-11FalseFalsePro & Farm0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2523.04190 Lbs6 ft11.36773,433$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
140122
230122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
140122
230122
320122
410122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
160122
240122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
240122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
160122
240122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
240122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
16012260122
24012240122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
240122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, , ,
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
, , ,
Tirs de pénalité
, , , ,
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
1Baby Hawks11000000431000000000001100000043121.00047110011131712166749932912217400.00%110.00%05916735.33%6416538.79%9222241.44%25416422410018283
2Caroline11000000541110000005410000000000021.00059140011131711766749931676146350.00%30100.00%05916735.33%6416538.79%9222241.44%25416422410018283
3Chiefs1010000067-1000000000001010000067-100.000612180011131712766749933112412300.00%2150.00%05916735.33%6416538.79%9222241.44%25416422410018283
4Jayhawks1010000024-2000000000001010000024-200.000246001113171196674993184416400.00%20100.00%05916735.33%6416538.79%9222241.44%25416422410018283
5Las Vegas11000000431000000000001100000043121.0004812001113171286674993128815300.00%4175.00%05916735.33%6416538.79%9222241.44%25416422410018283
6Manchots1010000058-31010000058-30000000000000.000510150011131712766749933281411400.00%7357.14%05916735.33%6416538.79%9222241.44%25416422410018283
7Minnesota11000000321000000000001100000032121.00035800111317196674993204010000%000%05916735.33%6416538.79%9222241.44%25416422410018283
8Monsters1010000045-11010000045-10000000000000.00048120011131713066749932668113133.33%4250.00%05916735.33%6416538.79%9222241.44%25416422410018283
9Oceanics10001000321000000000001000100032121.000358001113171266674993259416500.00%20100.00%05916735.33%6416538.79%9222241.44%25416422410018283
10Sags10100000510-50000000000010100000510-500.000591400111317127667499327118314300.00%4175.00%05916735.33%6416538.79%9222241.44%25416422410018283
11Stars10100000112-110000000000010100000112-1100.0001230011131711166749933487217300.00%110.00%05916735.33%6416538.79%9222241.44%25416422410018283
Total1146010004260-18312000001417-3834010002843-15100.455427912100111317124266749932708920515338410.53%301066.67%05916735.33%6416538.79%9222241.44%25416422410018283
_Since Last GM Reset1146010004260-18312000001417-3834010002843-15100.455427912100111317124266749932708920515338410.53%301066.67%05916735.33%6416538.79%9222241.44%25416422410018283
_Vs Conference302010001320-71010000058-320101000812-420.3331324370011131718066749938428101411200.00%13469.23%05916735.33%6416538.79%9222241.44%25416422410018283

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1110L142791212422708920515300
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
114610004260
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
31200001417
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
83410002843
Derniers 10 matchs
WLOTWOTL SOWSOL
550000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
38410.53%301066.67%0
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
66749931113171
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
5916735.33%6416538.79%9222241.44%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
25416422410018283


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
1 - 2025-10-073Monsters5Monarchs4LSommaire du match
2 - 2025-10-087Monarchs4Las Vegas3WSommaire du match
5 - 2025-10-1122Monarchs3Oceanics2WXSommaire du match
7 - 2025-10-1347Monarchs3Minnesota2WSommaire du match
10 - 2025-10-1671Manchots8Monarchs5LSommaire du match
12 - 2025-10-1886Caroline4Monarchs5WSommaire du match
15 - 2025-10-21104Monarchs6Chiefs7LSommaire du match
17 - 2025-10-23119Monarchs1Stars12LSommaire du match
19 - 2025-10-25137Monarchs2Jayhawks4LSommaire du match
20 - 2025-10-26144Monarchs4Baby Hawks3WSommaire du match
22 - 2025-10-28165Monarchs5Sags10LSommaire du match
24 - 2025-10-30177Cougars-Monarchs-
26 - 2025-11-01191Spiders-Monarchs-
29 - 2025-11-04212Oceanics-Monarchs-
31 - 2025-11-06226Cabaret Lady Mary Ann-Monarchs-
34 - 2025-11-09245Monarchs-Manchots-
36 - 2025-11-11257Monarchs-Rocket-
38 - 2025-11-13269Monarchs-Marlies-
40 - 2025-11-15286Monarchs-Senators-
42 - 2025-11-17304Monarchs-Bears-
45 - 2025-11-20330Monarchs-Sags-
46 - 2025-11-21334Bruins-Monarchs-
49 - 2025-11-24359Senators-Monarchs-
53 - 2025-11-28384Monarchs-Admirals-
54 - 2025-11-29401Comets-Monarchs-
57 - 2025-12-02420Bears-Monarchs-
59 - 2025-12-04435Baby Hawks-Monarchs-
61 - 2025-12-06449Baby Hawks-Monarchs-
63 - 2025-12-08462Monarchs-Roadrunners-
65 - 2025-12-10479Monarchs-Firebirds-
68 - 2025-12-13507Heat-Monarchs-
70 - 2025-12-15518Monarchs-Stars-
72 - 2025-12-17529Monarchs-Cabaret Lady Mary Ann-
73 - 2025-12-18538Monarchs-Thunder-
77 - 2025-12-22574Monsters-Monarchs-
78 - 2025-12-23587Firebirds-Monarchs-
82 - 2025-12-27597Admirals-Monarchs-
84 - 2025-12-29611Monarchs-Monsters-
87 - 2026-01-01639Thunder-Monarchs-
89 - 2026-01-03655Minnesota-Monarchs-
91 - 2026-01-05666Minnesota-Monarchs-
93 - 2026-01-07681Sags-Monarchs-
95 - 2026-01-09695Monarchs-Oceanics-
96 - 2026-01-10709Monarchs-Oil Kings-
98 - 2026-01-12724Stars-Monarchs-
100 - 2026-01-14738Las Vegas-Monarchs-
102 - 2026-01-16753Admirals-Monarchs-
103 - 2026-01-17766Monarchs-Admirals-
106 - 2026-01-20787Wolf Pack-Monarchs-
110 - 2026-01-24816Monarchs-Chiefs-
112 - 2026-01-26828Monarchs-Monsters-
113 - 2026-01-27833Monarchs-Cougars-
115 - 2026-01-29844Monarchs-Crunch-
117 - 2026-01-31859Monarchs-Phantoms-
118 - 2026-02-01874Monarchs-Caroline-
121 - 2026-02-04902Firebirds-Monarchs-
122 - 2026-02-05909Monarchs-Las Vegas-
142 - 2026-02-25916Las Vegas-Monarchs-
143 - 2026-02-26929Oil Kings-Monarchs-
145 - 2026-02-28944Heat-Monarchs-
147 - 2026-03-02958Monsters-Monarchs-
150 - 2026-03-05982Sound Tigers-Monarchs-
152 - 2026-03-07997Rocket-Monarchs-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
155 - 2026-03-101012Monarchs-Bruins-
158 - 2026-03-131041Monarchs-Sound Tigers-
159 - 2026-03-141050Monarchs-Spiders-
161 - 2026-03-161065Monarchs-Wolf Pack-
164 - 2026-03-191093Phantoms-Monarchs-
166 - 2026-03-211102Crunch-Monarchs-
167 - 2026-03-221118Monarchs-Roadrunners-
169 - 2026-03-241133Monarchs-Heat-
171 - 2026-03-261149Monarchs-Comets-
173 - 2026-03-281164Roadrunners-Monarchs-
177 - 2026-04-011189Chiefs-Monarchs-
178 - 2026-04-021204Jayhawks-Monarchs-
180 - 2026-04-041217Marlies-Monarchs-
182 - 2026-04-061232Jayhawks-Monarchs-
185 - 2026-04-091260Comets-Monarchs-
187 - 2026-04-111264Oil Kings-Monarchs-
189 - 2026-04-131291Monarchs-Firebirds-
190 - 2026-04-141300Monarchs-Comets-
192 - 2026-04-161310Monarchs-Heat-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5020
Assistance3,7481,925
Assistance PCT62.47%64.17%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 1891 - 63.03% 90,360$271,080$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
177,439$ 1,561,083$ 1,561,083$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,089$ 177,439$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
3,433,680$ 171 8,089$ 1,383,219$




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