Connexion

Monsters
GP: 81 | W: 49 | L: 27 | OTL: 5 | P: 103
GF: 182 | GA: 146 | PP%: 17.15% | PK%: 85.34%
DG: Benoit Toupin | Morale : 50 | Moyenne d’équipe : 61
Prochains matchs #1296 vs Caroline
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Centre de jeu
Monsters
49-27-5, 103pts
3
FINAL
2 Cabaret Lady Mary Ann
30-38-13, 73pts
Team Stats
W8SéquenceL5
23-15-2Fiche domicile14-19-7
26-12-3Fiche domicile16-19-6
9-1-0Derniers 10 matchs2-8-0
2.25Buts par match 2.00
1.80Buts contre par match 2.41
17.15%Pourcentage en avantage numérique13.27%
85.34%Pourcentage en désavantage numérique81.60%
Monsters
49-27-5, 103pts
1
FINAL
0 Chill
37-37-8, 82pts
Team Stats
W8SéquenceSOL1
23-15-2Fiche domicile20-18-3
26-12-3Fiche domicile17-19-5
9-1-0Derniers 10 matchs3-6-1
2.25Buts par match 2.17
1.80Buts contre par match 2.28
17.15%Pourcentage en avantage numérique18.39%
85.34%Pourcentage en désavantage numérique85.50%
Caroline
50-19-12, 112pts
2024-04-16
Monsters
49-27-5, 103pts
Statistiques d’équipe
W2SéquenceW8
27-6-8Fiche domicile23-15-2
23-13-4Fiche visiteur26-12-3
5-3-210 derniers matchs9-1-0
2.37Buts par match 2.25
1.86Buts contre par match 2.25
14.62%Pourcentage en avantage numérique17.15%
88.27%Pourcentage en désavantage numérique85.34%
Meneurs d'équipe
Buts
Laurent Dauphin
23
Passes
Gustav Lindstrom
36
Points
Connor Mackey
55
Plus/Moins
Laurent Dauphin
23
Victoires
Mads Sogaard
49
Pourcentage d’arrêts
Mads Sogaard
0.901

Statistiques d’équipe
Buts pour
182
2.25 GFG
Tirs pour
1514
18.69 Avg
Pourcentage en avantage numérique
17.2%
41 GF
Début de zone offensive
39.5%
Buts contre
146
1.80 GAA
Tirs contre
1417
17.49 Avg
Pourcentage en désavantage numérique
85.3%%
39 GA
Début de la zone défensive
39.1%
Informations de l'équipe

Directeur généralBenoit Toupin
DivisionNord-Est
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,897
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure20
Limite contact 47 / 50
Espoirs19


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
1Wayne SimmondsXX100.00797057727476846840656265689080050680343750,000$
2Laurent DauphinX100.00664376737582786877626267687969050680273888,888$
3Loui ErikssonXX100.0055419573735961595362527624868605065N0381750,000$
4Luke PhilpX100.00614870725967676544636367675550050630262900,000$
5Benoit-Olivier Groulx (R)X100.00564962646562626458605951625150050590222822,500$
6Cole Fonstad (R)X100.00554071675863646242605953625150050590223700,000$
7Matt Rempe (R)X100.00666457606960605940545559585050050580203820,000$
8Brandon Coe (R)X100.00574070616461615941575453585050050570202650,000$
9Chad Yetman (R)X100.00584068636159585440545354575150050560222560,000$
10Dominik Bokk (R)XX100.00716989666948494849464361434444050540222863,333$
11Kasper BjorkqvistXX100.00717282637253554849405061494444050540252800,000$
12Tim SoderlundXX100.00686496635849454953474162394444050530241825,834$
13Gustav LindstromX100.00654775747984757040696266696454050690231775,833$
14Connor MackeyX100.00687356747779686840646270685852050670262925,000$
15Jake Christiansen (R)X100.00614477737679666840646166675650050660231925,000$
16Matt KierstedX100.00574770747276656640626066675852050650242930,000$
17Ronald AttardX100.00654768717470636740626269675250050650233883,750$
18Chase PriskieX100.00564469716167666440586063655550050620261675,000$
Rayé
1Adam Ginning (R)X100.00674462686562626240605667625150050620222825,000$
2Vincent Iorio (R)X100.00664071686457576240625467625050050620193845,000$
3Lukas Cormier (R)X100.00564065696160616540626062655050050610203793,333$
4Wyatte Wylie (R)X100.00604871696463626140555461615150050600222820,833$
5Drew Helleson (R)X100.00584861646561606040565455605050050580213925,000$
6Daniil Chayka (R)X100.00584071626457575940545454595050050570193847,500$
MOYENNE D’ÉQUIPE100.0063507168676563614458566259565305061
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
1Mads Sogaard (R)100.0076717182747473757474735651050680211925,000$
2Jakub Skarek (R)100.0069636768686870676968575150050620222764,167$
Rayé
1Ken Appleby (R)100.006258547161575653575958575105055N0272750,000$
MOYENNE D’ÉQUIPE100.006964647468666665676763555105062
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
1Connor MackeyMonsters (Clb)D81203555118810189100124406716.13%60186022.9713518742150000199320%000000.5901011656
2Gustav LindstromMonsters (Clb)D81123648121807110298446512.24%49191823.6851318612170000230310%000100.5011000334
3Laurent DauphinMonsters (Clb)C8123224523200622181965112811.73%13183822.691783020801152594165.97%195400210.49616000462
4Wayne SimmondsMonsters (Clb)LW/RW7720234317801019575165538812.12%12157020.3958132919600032254148.70%11500000.55516002543
5Luke PhilpMonsters (Clb)C812220421380971771904811811.58%14147818.2668143419700031144148.38%126700100.5737000682
6Ronald AttardMonsters (Clb)D8172936126951446749153614.29%29131516.241231022000119200%000000.5501001122
7Jake ChristiansenMonsters (Clb)D819263534601158488206210.23%60172321.28581359194011020012100.00%100000.4111000324
8Matt KierstedMonsters (Clb)D81525304615117937738596.49%69168520.80246431831011184300%000000.3611000112
9Cole FonstadMonsters (Clb)LW8171724518059608527798.24%5141917.53189231970000904158.23%7900000.3413000114
10Chase PriskieMonsters (Clb)D817162312480665432122221.88%52133216.4500004000082010%000000.3511000202
11Loui ErikssonMonsters (Clb)LW/RW515172214002677627626.58%797819.19033151220001831060.68%11700000.4549000014
12Brandon CoeMonsters (Clb)RW817132012200693352142713.46%4128715.892798201000004145.71%7000000.3111000121
13Benoit-Olivier GroulxMonsters (Clb)C817121948075998225808.54%3112513.900112240000351257.27%88000000.3401000102
14Matt RempeMonsters (Clb)C8165112355754340153415.00%37018.65000213000051145.22%54400000.3101010200
15Chad YetmanMonsters (Clb)RW816282220633658152910.34%2118914.690002780001622043.59%7800000.1301000210
16Dominik BokkMonsters (Clb)LW/RW814485435644236113011.11%6102712.6900002000030150.00%4800000.1601001011
17Kasper BjorkqvistMonsters (Clb)LW/RW81336-122067383612258.33%591411.290000120000221052.24%6700000.1301000002
18Tim SoderlundMonsters (Clb)LW/RW81134-155253329783.45%46918.5300002000080062.50%4000000.1200010000
19Lukas CormierMonsters (Clb)D4000100100110%2256.470000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne142817130847913864145155614211513475102011.30%3992408316.8741741153922098123151828381556.58%526000410.402463035383741
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
1Mads SogaardMonsters (Clb)81492750.9011.70486741613813910400.73865810854
2Jakub SkarekMonsters (Clb)30000.8852.77650032600000081000
Statistiques d’équipe totales ou en moyenne84492750.9001.7249324161411417040658181854


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
Adam GinningMonsters (Clb)D222000-01-13Yes196 Lbs6 ft3NoNoNoNo2Pro & Farm825,000$12,891$0$0$No825,000$Lien
Benoit-Olivier GroulxMonsters (Clb)C222000-02-06Yes194 Lbs6 ft2NoNoNoNo2Pro & Farm822,500$12,852$0$0$No822,500$Lien
Brandon CoeMonsters (Clb)RW202001-12-01Yes187 Lbs6 ft4NoNoNoNo2Pro & Farm650,000$10,156$0$0$No650,000$Lien
Chad YetmanMonsters (Clb)RW222000-02-18Yes179 Lbs5 ft11NoNoNoNo2Pro & Farm560,000$8,750$0$0$No560,000$Lien
Chase PriskieMonsters (Clb)D261996-03-19No185 Lbs6 ft0NoNoYesYes1Pro & Farm675,000$10,547$0$0$NoLien
Cole FonstadMonsters (Clb)LW222000-04-24Yes170 Lbs5 ft10NoNoNoNo3Pro & Farm700,000$10,938$0$0$No700,000$700,000$Lien
Connor MackeyMonsters (Clb)D261996-09-12No197 Lbs6 ft2NoNoYesYes2Pro & Farm925,000$14,453$0$0$No925,000$Lien
Daniil ChaykaMonsters (Clb)D192002-10-22Yes187 Lbs6 ft3NoNoNoNo3Pro & Farm847,500$13,242$0$0$No847,500$847,500$
Dominik BokkMonsters (Clb)LW/RW222000-02-03Yes181 Lbs6 ft2NoNoNoNo2Pro & Farm863,333$13,490$0$0$No863,333$Lien
Drew HellesonMonsters (Clb)D212001-03-26Yes190 Lbs6 ft3NoNoNoNo3Pro & Farm925,000$14,453$0$0$No925,000$925,000$Lien
Gustav LindstromMonsters (Clb)D231998-10-20No186 Lbs6 ft2NoNoNoNo1Pro & Farm775,833$12,122$0$0$NoLien
Jake ChristiansenMonsters (Clb)D231999-09-12Yes193 Lbs6 ft0NoNoNoNo1Pro & Farm925,000$14,453$0$0$NoLien
Jakub SkarekMonsters (Clb)G221999-11-10Yes203 Lbs6 ft3NoNoNoNo2Pro & Farm764,167$11,940$0$0$No764,167$Lien
Kasper BjorkqvistMonsters (Clb)LW/RW251997-07-10No198 Lbs6 ft1NoNoYesYes2Pro & Farm800,000$12,500$0$0$No800,000$Lien
Ken Appleby (contrat à 1 volet)Monsters (Clb)G271995-04-10Yes216 Lbs6 ft5YesNoYesYes2Pro & Farm750,000$11,719$0$0$No750,000$Lien
Laurent Dauphin (contrat à 1 volet)Monsters (Clb)C271995-03-27No186 Lbs6 ft0NoNoYesYes3Pro & Farm888,888$13,889$0$0$No888,888$888,888$Lien
Loui Eriksson (contrat à 1 volet)Monsters (Clb)LW/RW381984-07-17No196 Lbs6 ft2YesNoYesYes1Pro & Farm750,000$11,719$0$0$NoLien
Lukas CormierMonsters (Clb)D202002-03-27Yes181 Lbs5 ft10NoNoNoNo3Pro & Farm793,333$12,396$0$0$No793,333$793,333$
Luke Philp (contrat à 1 volet)Monsters (Clb)C261995-11-06No181 Lbs5 ft10NoNoYesYes2Pro & Farm900,000$14,062$0$0$No900,000$Lien
Mads SogaardMonsters (Clb)G212000-12-13Yes196 Lbs6 ft7NoNoNoNo1Pro & Farm925,000$14,453$0$0$NoLien
Matt KierstedMonsters (Clb)D241998-04-14No181 Lbs6 ft0NoNoYesYes2Pro & Farm930,000$14,531$0$0$No930,000$Lien
Matt RempeMonsters (Clb)C202002-06-29Yes207 Lbs6 ft7NoNoNoNo3Pro & Farm820,000$12,812$0$0$No820,000$820,000$
Ronald AttardMonsters (Clb)D231999-03-20No207 Lbs6 ft3NoNoNoNo3Pro & Farm883,750$13,809$0$0$No883,750$883,750$Lien
Tim SoderlundMonsters (Clb)LW/RW241998-01-23No163 Lbs5 ft9NoNoYesYes1Pro & Farm825,834$12,904$0$0$NoLien
Vincent IorioMonsters (Clb)D192002-11-14Yes192 Lbs6 ft2NoNoNoNo3Pro & Farm845,000$13,203$0$0$No845,000$845,000$
Wayne Simmonds (contrat à 1 volet)Monsters (Clb)LW/RW341988-08-26No184 Lbs6 ft2NoNoYesYes3Pro & Farm750,000$11,719$0$0$No750,000$750,000$Lien
Wyatte WylieMonsters (Clb)D221999-11-02Yes190 Lbs6 ft0NoNoNoNo2Pro & Farm820,833$12,826$0$0$No820,833$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2723.70190 Lbs6 ft22.11812,629$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Wayne SimmondsLaurent DauphinLoui Eriksson40032
2Cole FonstadLuke PhilpBrandon Coe30041
3Dominik BokkBenoit-Olivier GroulxChad Yetman20041
4Kasper BjorkqvistMatt RempeTim Soderlund10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Gustav LindstromConnor Mackey40032
2Jake ChristiansenMatt Kiersted30032
3Ronald AttardChase Priskie20032
4Gustav LindstromConnor Mackey10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Wayne SimmondsLaurent DauphinLoui Eriksson60050
2Cole FonstadLuke PhilpBrandon Coe40050
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Gustav LindstromConnor Mackey60050
2Jake ChristiansenMatt Kiersted40050
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Laurent DauphinWayne Simmonds60050
2Loui ErikssonLuke Philp40050
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Gustav LindstromConnor Mackey60050
2Jake ChristiansenMatt Kiersted40050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Laurent Dauphin60050Gustav LindstromConnor Mackey60050
2Loui Eriksson40050Jake ChristiansenMatt Kiersted40050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Laurent DauphinWayne Simmonds60122
2Loui ErikssonLuke Philp40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Gustav LindstromConnor Mackey60122
2Jake ChristiansenMatt Kiersted40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Wayne SimmondsLaurent DauphinLoui ErikssonGustav LindstromConnor Mackey
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Wayne SimmondsLaurent DauphinLoui ErikssonGustav LindstromConnor Mackey
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Benoit-Olivier Groulx, Matt Rempe, Chad YetmanBenoit-Olivier Groulx, Matt RempeChad Yetman
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ronald Attard, Chase Priskie, Jake ChristiansenRonald AttardChase Priskie, Jake Christiansen
Tirs de pénalité
Laurent Dauphin, Wayne Simmonds, Loui Eriksson, Luke Philp, Cole Fonstad
Gardien
#1 : Mads Sogaard, #2 : Jakub Skarek


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
1Admirals2020000038-51010000023-11010000015-400.00036900585657243648252748088461014365120.00%7357.14%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
2Baby Hawks21000010523100000102111100000031241.000571200585657242748252748088441518313133.33%8187.50%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
3Bears3110001010731010000014-32100001093640.667101626005856572464482527480884911266710110.00%11190.91%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
4Bruins3110000156-1211000004401000000112-130.500581300585657246048252748088511718531218.33%9277.78%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
5Cabaret Lady Mary Ann32000010853100000103212200000053261.0008122000585657244848252748088531620427114.29%10190.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
6Caroline3110000145-11010000001-12100000144030.500471101585657244848252748088412324515240.00%10280.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
7Chiefs21100000330110000002021010000013-220.500347015856572426482527480883893139400.00%8187.50%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
8Chill22000000202110000001011100000010141.000246025856572431482527480882382739100.00%50100.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
9Comets2020000024-21010000012-11010000012-100.000246005856572434482527480883672139700.00%7185.71%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
10Cougars31200000810-21010000013-22110000077020.333815230058565724464825274808866132662900.00%12283.33%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
11Crunch3300000014410110000006332200000081761.000142438015856572474482527480885618167410550.00%7185.71%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
12Heat21000001770110000005411000000123-130.750713200058565724414825274808839910315120.00%3166.67%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
13Jayhawks22000000606110000003031100000030341.00061016025856572461482527480883714652400.00%30100.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
14Las Vegas2010001024-21010000003-31000001021120.5002240058565724334825274808837131842400.00%9188.89%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
15Manchots4120001057-22010001034-12110000023-140.5005712005856572465482527480887124417413215.38%21480.95%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
16Marlies3020001045-1201000103301010000012-120.333461000585657244548252748088562330609111.11%13192.31%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
17Minnesota22000000725110000004221100000030341.000712190158565724364825274808837612433266.67%60100.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
18Monarchs2020000024-21010000023-11010000001-100.000246005856572434482527480883311849600.00%4250.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
19Monsters2110000034-1110000002111010000013-220.50036900585657242948252748088346333810110.00%70100.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
20Oceanics2010001046-21010000014-31000001032120.50046100058565724474825274808829922429222.22%10190.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
21Oil Kings21000010624100000103211100000030341.0006915015856572450482527480883814233511327.27%9188.89%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
22Phantoms43100000642220000003122110000033060.7506915015856572465482527480886419366511218.18%16287.50%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
23Rocket320000101028100000103212200000070761.0001018280258565724764825274808842918739444.44%90100.00%11181207756.86%1134205855.10%661112558.76%2146152917685671024537
24Sags2010000135-21000000123-11010000012-110.250369005856572430482527480883558367114.29%4175.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
25Seattle2020000036-31010000023-11010000013-200.0003580058565724284825274808833615305120.00%40100.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
26Senators311000017522010000135-21100000040430.50071219015856572455482527480883612184517211.76%7357.14%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
27Sound Tigers32000010844210000105321100000031261.000812200058565724704825274808855914657114.29%50100.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
28Spiders440000001165220000006332200000053281.00011213200585657245348252748088731634709222.22%16287.50%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
29Stars22000000404110000002021100000020241.0004711025856572437482527480883610827700.00%40100.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
30Thunder3300000016792200000010551100000062461.00016304600585657248948252748088551212726350.00%6266.67%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
31Wolf Pack40300010412-82020000039-62010001013-220.250461001585657247648252748088742538741417.14%16381.25%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
Total813827000115182146364016150007288835412212000439463311030.63618230849001658565724151448252748088141739964515562394117.15%2663985.34%11181207756.86%1134205855.10%661112558.76%2146152917685671024537
_Since Last GM Reset813827000115182146364016150007288835412212000439463311030.63618230849001658565724151448252748088141739964515562394117.15%2663985.34%11181207756.86%1134205855.10%661112558.76%2146152917685671024537
_Vs Conference441817000639086424910000324954-520970003141329510.580901532430558565724820482527480887502113468471362014.71%1502782.00%01181207756.86%1134205855.10%661112558.76%2146152917685671024537
_Vs Division259400020484531252000102125-413420001027207220.4404878126035856572444148252748088427127213466691115.94%951485.26%01181207756.86%1134205855.10%661112558.76%2146152917685671024537

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
81103W8182308490151414173996451556016
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
81382700115182146
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
40161500728883
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
41221200439463
Derniers 10 matchs
WLOTWOTL SOWSOL
910000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2394117.15%2663985.34%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
4825274808858565724
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
1181207756.86%1134205855.10%661112558.76%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2146152917685671024537


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
3 - 2023-10-1211Phantoms1Monsters2BWSommaire du match
5 - 2023-10-1422Wolf Pack3Monsters2BLSommaire du match
7 - 2023-10-1635Cougars3Monsters1BLSommaire du match
11 - 2023-10-2063Heat4Monsters5BWSommaire du match
12 - 2023-10-2173Monsters3Minnesota0AWSommaire du match
15 - 2023-10-2484Admirals3Monsters2BLSommaire du match
17 - 2023-10-26103Monsters5Rocket0AWSommaire du match
19 - 2023-10-28121Sound Tigers1Monsters2BWXXSommaire du match
21 - 2023-10-30136Monsters2Stars0AWSommaire du match
24 - 2023-11-02146Thunder3Monsters5BWSommaire du match
26 - 2023-11-04166Monsters3Bears2AWXXSommaire du match
28 - 2023-11-06176Monsters2Cabaret Lady Mary Ann1AWSommaire du match
31 - 2023-11-09194Stars0Monsters2BWSommaire du match
33 - 2023-11-11210Monsters6Cougars4AWSommaire du match
34 - 2023-11-12225Monsters1Wolf Pack0AWXXSommaire du match
36 - 2023-11-14230Manchots3Monsters1BLSommaire du match
38 - 2023-11-16243Jayhawks0Monsters3BWSommaire du match
40 - 2023-11-18263Monsters6Bears1AWSommaire du match
41 - 2023-11-19268Monsters0Phantoms2ALSommaire du match
44 - 2023-11-22280Baby Hawks1Monsters2BWXXSommaire du match
46 - 2023-11-24297Monsters3Spiders2AWSommaire du match
48 - 2023-11-26318Monsters3Caroline4ALXXSommaire du match
49 - 2023-11-27321Bruins2Monsters1BLSommaire du match
51 - 2023-11-29337Rocket2Monsters3BWXXSommaire du match
53 - 2023-12-01354Senators2Monsters1BLXXSommaire du match
55 - 2023-12-03371Monsters1Bruins2ALXXSommaire du match
57 - 2023-12-05381Monarchs3Monsters2BLSommaire du match
59 - 2023-12-07397Monsters3Sound Tigers1AWSommaire du match
60 - 2023-12-08405Chiefs0Monsters2BWSommaire du match
62 - 2023-12-10420Cabaret Lady Mary Ann2Monsters3BWXXSommaire du match
66 - 2023-12-14449Monsters1Marlies2ALSommaire du match
68 - 2023-12-16464Spiders2Monsters4BWSommaire du match
71 - 2023-12-19485Monsters3Crunch1AWSommaire du match
73 - 2023-12-21499Bears4Monsters1BLSommaire du match
75 - 2023-12-23518Marlies2Monsters3BWXXSommaire du match
79 - 2023-12-27528Monsters2Spiders1AWSommaire du match
81 - 2023-12-29546Marlies1Monsters0BLSommaire du match
82 - 2023-12-30556Monsters5Crunch0AWSommaire du match
85 - 2024-01-02574Bruins2Monsters3BWSommaire du match
87 - 2024-01-04592Monsters3Phantoms1AWSommaire du match
89 - 2024-01-06610Minnesota2Monsters4BWSommaire du match
92 - 2024-01-09631Monsters3Oceanics2AWXXSommaire du match
96 - 2024-01-13659Seattle3Monsters2BLSommaire du match
98 - 2024-01-15673Comets2Monsters1BLSommaire du match
102 - 2024-01-19703Spiders1Monsters2BWSommaire du match
106 - 2024-01-23736Monsters3Oil Kings0AWSommaire du match
108 - 2024-01-25753Monsters2Heat3ALXXSommaire du match
110 - 2024-01-27771Monsters1Comets2ALSommaire du match
111 - 2024-01-28774Monsters1Seattle3ALSommaire du match
113 - 2024-01-30776Monsters1Chiefs3ALSommaire du match
124 - 2024-02-10812Thunder2Monsters5BWSommaire du match
127 - 2024-02-13826Monsters4Senators0AWSommaire du match
131 - 2024-02-17861Monsters1Sags2ALSommaire du match
134 - 2024-02-20883Monsters0Monarchs1ALSommaire du match
135 - 2024-02-21886Monsters1Admirals5ALSommaire du match
137 - 2024-02-23900Crunch3Monsters6BWSommaire du match
139 - 2024-02-25921Wolf Pack6Monsters1BLSommaire du match
142 - 2024-02-28939Monsters0Wolf Pack3ALSommaire du match
143 - 2024-02-29942Caroline1Monsters0BLSommaire du match
145 - 2024-03-02965Monsters3Baby Hawks1AWSommaire du match
147 - 2024-03-04975Las Vegas3Monsters0BLSommaire du match
148 - 2024-03-05983Monsters2Manchots1AWSommaire du match
150 - 2024-03-07995Oil Kings2Monsters3BWXXSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
152 - 2024-03-091010Chill0Monsters1BWSommaire du match
155 - 2024-03-121033Monsters2Rocket0AWSommaire du match
157 - 2024-03-141047Senators3Monsters2BLSommaire du match
159 - 2024-03-161066Sags3Monsters2BLXXSommaire du match
160 - 2024-03-171076Oceanics4Monsters1BLSommaire du match
162 - 2024-03-191083Monsters1Cougars3ALSommaire du match
165 - 2024-03-221111Monsters1Monsters3ALSommaire du match
166 - 2024-03-231123Monsters2Las Vegas1AWXXSommaire du match
169 - 2024-03-261145Monsters3Jayhawks0AWSommaire du match
171 - 2024-03-281154Monsters0Manchots2ALSommaire du match
173 - 2024-03-301172Manchots1Monsters2BWXXSommaire du match
175 - 2024-04-011181Monsters1Monsters2BWSommaire du match
178 - 2024-04-041203Sound Tigers2Monsters3BWSommaire du match
180 - 2024-04-061222Phantoms0Monsters1BWSommaire du match
181 - 2024-04-071230Monsters1Caroline0AWSommaire du match
183 - 2024-04-091245Monsters6Thunder2AWSommaire du match
185 - 2024-04-111256Monsters3Cabaret Lady Mary Ann2AWSommaire du match
187 - 2024-04-131278Monsters1Chill0AWSommaire du match
190 - 2024-04-161296Caroline-Monsters-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance77,32138,543
Assistance PCT96.65%96.36%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
1 2897 - 96.55% 98,531$3,941,256$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,762,236$ 1,790,207$ 1,790,207$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,324$ 1,762,236$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
98,531$ 3 9,324$ 27,972$




Monsters 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

Monsters 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

Monsters 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

Monsters 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

Monsters 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