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Monarchs
GP: 1 | W: 0 | L: 0 | OTL: 1 | P: 1
GF: 1 | GA: 2 | PP%: 25.00% | PK%: 100.00%
DG: Patrick Poulin | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #21 vs Soldiers
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Centre de jeu
Admirals
1-0-0, 2pts
2
FINAL
1 Monarchs
0-0-1, 1pts
Team Stats
W1StreakSOL1
0-0-0Home Record0-0-1
1-0-0Away Record0-0-0
1-0-0Last 10 Games0-0-1
2.00Buts par match 1.00
1.00Buts contre par match 2.00
0.00%Pourcentage en avantage numérique25.00%
75.00%Pourcentage en désavantage numérique100.00%
Monarchs
0-0-1, 1pts
2022-10-14
Soldiers
2-0-0, 4pts
Statistiques d’équipe
SOL1SéquenceW2
0-0-1Fiche domicile0-0-0
0-0-0Fiche visiteur2-0-0
0-0-110 derniers matchs2-0-0
1.00Buts par match 3.00
2.00Buts contre par match 3.00
25.00%Pourcentage en avantage numérique13.33%
100.00%Pourcentage en désavantage numérique81.82%
Condors
0-1-0, 0pts
2022-10-16
Monarchs
0-0-1, 1pts
Statistiques d’équipe
L1SéquenceSOL1
0-1-0Fiche domicile0-0-1
0-0-0Fiche visiteur0-0-0
0-1-010 derniers matchs0-0-1
2.00Buts par match 1.00
4.00Buts contre par match 1.00
50.00%Pourcentage en avantage numérique25.00%
85.71%Pourcentage en désavantage numérique100.00%
Moose
0-0-1, 1pts
2022-10-17
Monarchs
0-0-1, 1pts
Statistiques d’équipe
OTL1SéquenceSOL1
0-0-1Fiche domicile0-0-1
0-0-0Fiche visiteur0-0-0
0-0-110 derniers matchs0-0-1
2.00Buts par match 1.00
3.00Buts contre par match 1.00
25.00%Pourcentage en avantage numérique25.00%
85.71%Pourcentage en désavantage numérique100.00%
Meneurs d'équipe
Buts
Timothy Liljegren
1
Passes
Brad Richardson
1
Points
Brad Richardson
1
Plus/Moins
Timothy Liljegren
0
Victoires
Felix Sandstrom
0
Pourcentage d’arrêts
Felix Sandstrom
0.952

Statistiques d’équipe
Buts pour
1
1.00 GFG
Tirs pour
22
22.00 Avg
Pourcentage en avantage numérique
25.0%
1 GF
Début de zone offensive
43.8%
Buts contre
2
2.00 GAA
Tirs contre
21
21.00 Avg
Pourcentage en désavantage numérique
100.0%
0 GA
Début de la zone défensive
39.1%
Informations de l'équipe

Directeur généralPatrick Poulin
EntraîneurLuke Richardson
DivisionDivision 5
ConférenceConference 2
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,722
Billets de saison300


Informations de la formation

Équipe Pro25
Équipe Mineure18
Limite contact 43 / 60
Espoirs22


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
1Alex Iafallo0X100.006742968568799383407073803769697750002822,425,000$
2Brad Richardson15X100.007857777770575954785959702582866350003721,000,000$
3Daniel Sprong0X100.00694395847363786625607260756566695000254750,000$
4Samuel Fagemo (R)0XX100.00736982706972756250546763644444655000224910,833$
5Matias Maccelli (R)0X100.00654194676167626925675668254646645000214925,000$
6Filip Hallander (R)0XX100.00777288697258595771515964564444615000224913,333$
7Nicholas Merkley0X100.00754399796862766956676076254747685000251750,000$
8Kevin Labanc0X100.007843908167656475256266677566666950002611,000,000$
9Pat Maroon0X100.008599567489639471456566632576836850003411,000,000$
10Ryan Poehling0XX100.006943967473627269766270682555557050002311,491,667$
11Alexander Nylander (R)0XX100.00787194737156556250566366604444655000242874,125$
12Jake Leschyshyn0X100.00764393726959835368605774254747645000231927,500$
13Dmitri Samorukov (R)0X100.00747376657355565125464161394444535000234863,333$
14Reilly Walsh (R)0X100.00756892676873785625524663444444585000233925,000$
15Isaak Phillips (R)0X100.00757379647369735325415162484444575000202925,000$
16Timothy Liljegren0X100.007944927870706763256449762553536450002331,263,333$
17Martin Fehervary0X100.00974789787280775825495082255555655000221894,167$
18Pierre-Olivier Joseph0X100.007370797270737857254951624845456050002311,075,833$
Rayé
1Michael Pezzetta0XX93.209699587078506561526159602549496350002411,000,000$
2Gianni Fairbrother (R)0X100.00647051617043424925424055384444485000214903,333$
3Brennan Menell (R)0X100.00676475706446464925434057384444515000254750,000$
MOYENNE D’ÉQUIPE99.6776618373716369614156576740535363500
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
1Adam Scheel (R)100.00504455785250515552523044445150002311,000,000$
2Felix Sandstrom (R)100.0050455675525251565453304444525000254750,000$
Rayé
1Jack LaFontaine (R)100.00464050824648515351513044444950002431,000,000$
2David Hrenak (R)100.0044405075454445494545454444455000241925,000$
MOYENNE D’ÉQUIPE100.004842537849495053515034444449500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Luke Richardson75787472737482CAN533500,000$


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Brad RichardsonMonarchs (LAK)C1011-100011000.00%01515.7701112000000015.771400001.2700000000
2Daniel SprongMonarchs (LAK)RW1011-100012200.00%01717.600111200001000.00%000001.1400000000
3Timothy LiljegrenMonarchs (LAK)D11010000020050.00%22525.731012300002000.00%000000.7800000000
4Alex IafalloMonarchs (LAK)LW1000000055010.00%02121.8300013000030021.83700000.00%01000000
5Samuel FagemoMonarchs (LAK)LW/RW1000000000000.00%01010.6200000000000010.62100000.00%00000000
6Matias MaccelliMonarchs (LAK)LW1000000010010.00%01414.030000000001000.00%000000.00%00000000
7Dmitri SamorukovMonarchs (LAK)D1000000010000.00%11515.450000000000000.00%000000.00%00000000
8Filip HallanderMonarchs (LAK)C/LW1000020000000.00%000.270000000000000.27100000.00%00000000
9Nicholas MerkleyMonarchs (LAK)RW1000020202020.00%01313.270000000000000.00%000000.00%00000000
10Reilly WalshMonarchs (LAK)D1000-100001100.00%02222.180000300002000.00%000000.00%00000000
11Isaak PhillipsMonarchs (LAK)D1000020010000.00%01515.400000000000000.00%000000.00%00000000
12Michael PezzettaMonarchs (LAK)C/LW1000000320000.00%099.900000000000009.901000000.00%00000000
13Kevin LabancMonarchs (LAK)RW1000000531020.00%02020.0300013000010020.03200000.00%01000000
14Pat MaroonMonarchs (LAK)LW1000-100312140.00%02121.0500002000020021.05500000.00%01000000
15Ryan PoehlingMonarchs (LAK)C/LW1000000023020.00%01616.9000013000000016.901400000.00%00000000
16Martin FehervaryMonarchs (LAK)D1000000502000.00%42525.400000300002000.00%000000.00%00000000
17Pierre-Olivier JosephMonarchs (LAK)D1000-100210000.00%02020.820000300002000.00%000000.00%00000000
18Alexander NylanderMonarchs (LAK)LW/RW1000000010000.00%01010.170000000000000.00%100000.00%00000000
19Jake LeschyshynMonarchs (LAK)C1000000011020.00%01212.5800000000000012.581400000.00%00000000
Statistiques d’équipe totales ou en moyenne19123-5602021224144.55%730916.261237320000210056.52%6900000.1903000000
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
1Felix SandstromMonarchs (LAK)10010.9520.9265001210000.667310000
Statistiques d’équipe totales ou en moyenne10010.9520.926500121000310000


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 restantSalaire moyenSalaire 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 10Link
Adam ScheelMonarchs (LAK)G231999-05-01Yes192 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$972,603$1,000,000$972,603$0$0$NoLien
Alex IafalloMonarchs (LAK)LW281993-12-20No188 Lbs6 ft0NoNoNo2Pro & Farm2,425,000$2,358,562$2,425,000$2,358,562$0$0$No2,425,000$Lien
Alexander NylanderMonarchs (LAK)LW/RW241998-03-02Yes192 Lbs6 ft1NoNoNo2Pro & Farm874,125$850,176$874,125$850,176$0$0$No874,125$Lien
Brad RichardsonMonarchs (LAK)C371985-02-03No190 Lbs6 ft0NoNoNo2Pro & Farm1,000,000$972,603$1,000,000$972,603$0$0$No1,000,000$Lien
Brennan MenellMonarchs (LAK)D251997-05-24Yes177 Lbs5 ft11NoNoNo4Pro & Farm750,000$729,452$750,000$729,452$0$0$No750,000$750,000$750,000$Lien
Daniel SprongMonarchs (LAK)RW251997-03-17No200 Lbs6 ft0NoNoNo4Pro & Farm750,000$729,452$750,000$729,452$0$0$No750,000$750,000$750,000$Lien
David HrenakMonarchs (LAK)G241998-05-05Yes190 Lbs6 ft2NoNoNo1Pro & Farm925,000$899,658$925,000$899,658$0$0$No
Dmitri SamorukovMonarchs (LAK)D231999-06-16Yes198 Lbs6 ft2NoNoNo4Pro & Farm863,333$839,680$863,333$839,680$0$0$No863,333$863,333$863,333$
Felix SandstromMonarchs (LAK)G251997-01-12Yes191 Lbs6 ft2NoNoNo4Pro & Farm750,000$729,452$750,000$729,452$0$0$No750,000$750,000$750,000$Lien
Filip HallanderMonarchs (LAK)C/LW222000-06-29Yes196 Lbs6 ft1NoNoNo4Pro & Farm913,333$888,310$913,333$888,310$0$0$No913,333$913,333$913,333$
Gianni FairbrotherMonarchs (LAK)D212000-09-30Yes190 Lbs6 ft0NoNoNo4Pro & Farm903,333$878,584$903,333$878,584$0$0$No903,333$903,333$903,333$
Isaak PhillipsMonarchs (LAK)D202001-09-28Yes194 Lbs6 ft3NoNoNo2Pro & Farm925,000$899,658$925,000$899,658$0$0$No925,000$Lien
Jack LaFontaineMonarchs (LAK)G241998-01-06Yes209 Lbs6 ft3NoNoNo3Pro & Farm1,000,000$972,603$1,000,000$972,603$0$0$No1,000,000$1,000,000$
Jake LeschyshynMonarchs (LAK)C231999-03-10No190 Lbs5 ft11NoNoNo1Pro & Farm927,500$902,089$927,500$902,089$0$0$NoLien
Kevin LabancMonarchs (LAK)RW261995-12-12No185 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$972,603$1,000,000$972,603$0$0$NoLien
Martin FehervaryMonarchs (LAK)D221999-10-06No194 Lbs6 ft2NoNoNo1Pro & Farm894,167$869,669$894,167$869,669$0$0$NoLien
Matias MaccelliMonarchs (LAK)LW212000-10-14Yes165 Lbs5 ft11NoNoNo4Pro & Farm925,000$899,658$925,000$899,658$0$0$No925,000$925,000$925,000$
Michael Pezzetta (sur la masse salariale)Monarchs (LAK)C/LW241998-03-13No205 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$972,603$1,000,000$972,603$0$0$YesLien
Nicholas MerkleyMonarchs (LAK)RW251997-05-23No194 Lbs5 ft10NoNoNo1Pro & Farm750,000$729,452$750,000$729,452$0$0$NoLien
Pat MaroonMonarchs (LAK)LW341988-04-23No238 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$972,603$1,000,000$972,603$0$0$NoLien
Pierre-Olivier JosephMonarchs (LAK)D231999-07-01No185 Lbs6 ft2NoNoNo1Pro & Farm1,075,833$1,046,358$1,075,833$1,046,358$0$0$NoLien
Reilly WalshMonarchs (LAK)D231999-04-21Yes185 Lbs6 ft0NoNoNo3Pro & Farm925,000$899,658$925,000$899,658$0$0$No925,000$925,000$Lien
Ryan PoehlingMonarchs (LAK)C/LW231999-01-03No197 Lbs6 ft2NoNoNo1Pro & Farm1,491,667$1,450,799$1,491,667$1,450,799$0$0$NoLien
Samuel FagemoMonarchs (LAK)LW/RW222000-03-14Yes190 Lbs5 ft11NoNoNo4Pro & Farm910,833$885,879$910,833$885,879$0$0$No910,833$910,833$910,833$Lien
Timothy LiljegrenMonarchs (LAK)D231999-04-30No192 Lbs6 ft0NoNoNo3Pro & Farm1,263,333$1,228,721$1,263,333$1,228,721$0$0$No1,263,333$1,263,333$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2524.40193 Lbs6 ft12.361,009,698$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Alex IafalloRyan PoehlingKevin Labanc35122
2Pat MaroonBrad RichardsonDaniel Sprong30122
3Matias MaccelliJake LeschyshynNicholas Merkley25122
4Alexander NylanderFilip HallanderSamuel Fagemo10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Martin FehervaryTimothy Liljegren35122
2Pierre-Olivier JosephReilly Walsh30122
3Isaak PhillipsDmitri Samorukov25122
4Martin FehervaryTimothy Liljegren10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Alex IafalloRyan PoehlingKevin Labanc60122
2Pat MaroonBrad RichardsonDaniel Sprong40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Martin FehervaryTimothy Liljegren60122
2Pierre-Olivier JosephReilly Walsh40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Alex IafalloPat Maroon60122
2Kevin LabancDaniel Sprong40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Martin FehervaryTimothy Liljegren60122
2Pierre-Olivier JosephReilly Walsh40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Alex Iafallo60122Martin FehervaryTimothy Liljegren60122
2Pat Maroon40122Pierre-Olivier JosephReilly Walsh40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Alex IafalloPat Maroon60122
2Kevin LabancDaniel Sprong40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Martin FehervaryTimothy Liljegren60122
2Pierre-Olivier JosephReilly Walsh40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Alex IafalloRyan PoehlingKevin LabancMartin FehervaryTimothy Liljegren
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Alex IafalloRyan PoehlingKevin LabancMartin FehervaryTimothy Liljegren
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nicholas Merkley, Matias Maccelli, Jake LeschyshynNicholas Merkley, Matias MaccelliJake Leschyshyn
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Isaak Phillips, Dmitri Samorukov, Pierre-Olivier JosephIsaak PhillipsDmitri Samorukov, Pierre-Olivier Joseph
Tirs de pénalité
Alex Iafallo, Pat Maroon, Kevin Labanc, Daniel Sprong, Nicholas Merkley
Gardien
#1 : Felix Sandstrom, #2 : Adam Scheel
Lignes d’attaque personnalisées en prolongation
Alex Iafallo, Pat Maroon, Kevin Labanc, Daniel Sprong, Nicholas Merkley, Ryan Poehling, Ryan Poehling, Brad Richardson, Matias Maccelli, Jake Leschyshyn, Alexander Nylander
Lignes de défense personnalisées en prolongation
Martin Fehervary, Timothy Liljegren, Pierre-Olivier Joseph, Reilly Walsh, Isaak Phillips


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
1Admirals1000000112-11000000112-10000000000010.5001230010002299432176204125.00%30100.00%0162857.14%152560.00%81172.73%2718237147
Total1000000112-11000000112-10000000000010.5001230010002299432176204125.00%30100.00%0162857.14%152560.00%81172.73%2718237147
_Since Last GM Reset1000000112-11000000112-10000000000010.5001230010002299432176204125.00%30100.00%0162857.14%152560.00%81172.73%2718237147
_Vs Conference1000000112-11000000112-10000000000010.5001230010002299432176204125.00%30100.00%0162857.14%152560.00%81172.73%2718237147
_Vs Division1000000112-11000000112-10000000000010.5001230010002299432176204125.00%30100.00%0162857.14%152560.00%81172.73%2718237147

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
11SOL11232221762000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
100000112
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
100000112
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 matchs
WLOTWOTL SOWSOL
000001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
4125.00%30100.00%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
99431000
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
162857.14%152560.00%81172.73%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2718237147


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 - 2022-10-093Admirals2Monarchs1BLXXSommaire du match
6 - 2022-10-1421Monarchs-Soldiers-
8 - 2022-10-1633Condors-Monarchs-
9 - 2022-10-1748Moose-Monarchs-
11 - 2022-10-1956Monarchs-Moose-
12 - 2022-10-2060Monarchs-Senators-
14 - 2022-10-2275IceHogs-Monarchs-
16 - 2022-10-2490Monarchs-Sharks-
17 - 2022-10-2598Rocket-Monarchs-
19 - 2022-10-27108Monarchs-Flames-
20 - 2022-10-28117Monarchs-Sound Tigers-
23 - 2022-10-31129Rampage-Monarchs-
24 - 2022-11-01139Phantoms-Monarchs-
26 - 2022-11-03154Monarchs-Wolves-
28 - 2022-11-05161Sharks-Monarchs-
30 - 2022-11-07178Sound Tigers-Monarchs-
31 - 2022-11-08183Monarchs-Sharks-
34 - 2022-11-11196Monarchs-Sound Tigers-
36 - 2022-11-13207Penguins-Monarchs-
40 - 2022-11-17217Monarchs-Rampage-
42 - 2022-11-19226Monarchs-Moose-
43 - 2022-11-20236Rampage-Monarchs-
46 - 2022-11-23250Admirals-Monarchs-
47 - 2022-11-24260Monarchs-Rampage-
49 - 2022-11-26273Monarchs-Griffins-
50 - 2022-11-27278Condors-Monarchs-
52 - 2022-11-29294Monarchs-Moose-
53 - 2022-11-30303Sharks-Monarchs-
55 - 2022-12-02317Bruins-Monarchs-
56 - 2022-12-03323Monarchs-Senators-
59 - 2022-12-06337Monarchs-Sharks-
61 - 2022-12-08346Wolves-Monarchs-
62 - 2022-12-09359Monarchs-Sound Tigers-
65 - 2022-12-12368Wolf Pack-Monarchs-
67 - 2022-12-14382Soldiers-Monarchs-
68 - 2022-12-15395Monarchs-Flames-
70 - 2022-12-17405IceHogs-Monarchs-
72 - 2022-12-19415Monarchs-Soldiers-
74 - 2022-12-21426Monsters-Monarchs-
76 - 2022-12-23437Monarchs-Soldiers-
77 - 2022-12-24444Monarchs-Rocket-
79 - 2022-12-26454Monarchs-Griffins-
80 - 2022-12-27462Admirals-Monarchs-
82 - 2022-12-29476Rampage-Monarchs-
85 - 2023-01-01492Phantoms-Monarchs-
88 - 2023-01-04505Monarchs-Crunch-
90 - 2023-01-06512Monarchs-Condors-
91 - 2023-01-07521Griffins-Monarchs-
94 - 2023-01-10536IceHogs-Monarchs-
98 - 2023-01-14553Monarchs-Admirals-
99 - 2023-01-15560Senators-Monarchs-
102 - 2023-01-18573Monarchs-Admirals-
103 - 2023-01-19583Stars-Monarchs-
106 - 2023-01-22596Monarchs-Wolves-
108 - 2023-01-24604Sound Tigers-Monarchs-
110 - 2023-01-26619Monarchs-Penguins-
111 - 2023-01-27625Marlies-Monarchs-
114 - 2023-01-30642Moose-Monarchs-
117 - 2023-02-02653Monarchs-Senators-
118 - 2023-02-03664Condors-Monarchs-
121 - 2023-02-06672Monarchs-IceHogs-
122 - 2023-02-07679Monarchs-Flames-
125 - 2023-02-10691Wolves-Monarchs-
126 - 2023-02-11698Monarchs-Condors-
127 - 2023-02-12709Monarchs-Wolves-
129 - 2023-02-14718Condors-Monarchs-
132 - 2023-02-17732Monarchs-Senators-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
134 - 2023-02-19739Monarchs-Stars-
135 - 2023-02-20747Moose-Monarchs-
140 - 2023-02-25763Rocket-Monarchs-
143 - 2023-02-28778Rocket-Monarchs-
144 - 2023-03-01786Monarchs-Stars-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance1,834888
Assistance PCT91.70%88.80%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
35 2722 - 90.73% 85,261$85,261$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
80,116$ 2,424,244$ 2,424,244$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 66,416$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
2,984,135$ 142 20,029$ 2,844,118$




Monarchs Leaders statistiques (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 (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