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Connexion

Monsters
GP: 82 | W: 49 | L: 24 | OTL: 9 | P: 107
GF: 287 | GA: 258 | PP%: 19.75% | PK%: 80.38%
DG: Benoit Toupin | Morale : 50 | Moyenne d’équipe : 57
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Centre de jeu
Monsters
49-24-9, 107pts
3
FINAL
4 Phantoms
33-46-3, 69pts
Team Stats
W1StreakL1
24-13-4Home Record17-21-3
25-11-5Away Record16-25-0
4-2-4Last 10 Games5-5-0
3.50Buts par match 3.01
3.15Buts contre par match 4.01
19.75%Pourcentage en avantage numérique14.29%
80.38%Pourcentage en désavantage numérique77.35%
Manchots
43-32-7, 93pts
2
FINAL
7 Monsters
49-24-9, 107pts
Team Stats
L1StreakW1
23-14-4Home Record24-13-4
20-18-3Away Record25-11-5
6-4-0Last 10 Games4-2-4
3.10Buts par match 3.50
2.98Buts contre par match 3.15
19.29%Pourcentage en avantage numérique19.75%
82.53%Pourcentage en désavantage numérique80.38%
Meneurs d'équipe
Buts
Benoit-Olivier Groulx
38
Passes
Nils Lundkvist
52
Points
Benoit-Olivier Groulx
83
Plus/Moins
Benoit-Olivier Groulx
31
Victoires
Mads Sogaard
49
Pourcentage d’arrêts
Jakub Skarek
0.962

Statistiques d’équipe
Buts pour
287
3.50 GFG
Tirs pour
3209
39.13 Avg
Pourcentage en avantage numérique
19.7%
47 GF
Début de zone offensive
42.0%
Buts contre
258
3.15 GAA
Tirs contre
2875
35.06 Avg
Pourcentage en désavantage numérique
80.4%%
52 GA
Début de la zone défensive
39.0%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,859
Billets de saison300


Informations de la formation

Équipe Pro25
Équipe Mineure20
Limite contact 45 / 50
Espoirs16


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 SimmondsXX100.00869464727354815644625860618487050620334750,000$
2Sheldon DriesXX100.00714299746456696842597165255050050610273700,000$
3Brandon PirriXXX100.00636861676853516579526966686768050600302650,000$
4Benoit-Olivier Groulx (R)X100.00764496677359765860605777254545050600213822,500$
5Julien GauthierX100.00854694778456656034585761255757050600232990,900$
6Luke PhilpX100.00736591636564656278586263594444050590251600,000$
7Cole Fonstad (R)XX100.00706093706050495771525860554444050550211900,000$
8Dominik Bokk (R)XX100.00766991676952535150504762454444050540213863,333$
9Kasper BjorkqvistXX100.00767284647258605150435462514444050540243800,000$
10Tim SoderlundXX100.00726498645853495254514563414444050530232825,834$
11Matt FilipeXX100.00737275607256585164475060484444050530231600,000$
12Chad Yetman (R)XX100.00726492646445444961474659444444050510213560,000$
13Matt KierstedX100.00754393716764665725495078254545050620231858,750$
14Kurtis MacDermidX100.00839959699046695525444867256060050610272650,000$
15Nils Lundkvist (R)X100.00674299766664586425504866254646050600213925,000$
16Connor MackeyX100.00687258717267705525544259404444050580253925,000$
17Jake Christiansen (R)X100.00764499667254625425395464254444050570222925,000$
18Adam Ginning (R)X100.00585870617758833825333566385052050560213825,000$
Rayé
1Brandon Coe (R)X100.00757488627455574849484362434444050520193650,000$
2Chase PriskieX100.00736885656861635725504962474444050570252675,000$
3Keaton MiddletonX100.00819159619155584725384063384444050560231650,000$
4Wyatte Wylie (R)X100.00757088637059624825394161394444050550213820,833$
5Drew Helleson (R)X100.00787391697338374525363961374444050530204925,000$
MOYENNE D’ÉQUIPE100.0074658467715661544349516440494905057
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)100.0054425386585452585655304444050560202925,000$
2Jakub Skarek (R)100.0048445581494950545050304444050520213764,167$
Rayé
MOYENNE D’ÉQUIPE100.005143548454525156535330444405054
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
1Benoit-Olivier GroulxMonsters (Clb)C8238458331200942253861132409.84%34154618.861192063193213152259550.90%216100001.0728000944
2Brandon PirriMonsters (Clb)C/LW/RW823740772936014412235710727110.36%18145617.77713205919203371405356.65%23300011.0611000668
3Nils LundkvistMonsters (Clb)D81105262252755313513851977.25%110164420.302911551420223192100.00%000000.7500000143
4Sheldon DriesMonsters (Clb)C/LW8227305724018218348812987.76%24174821.3227947197022122378042.48%202200010.65310000333
5Matt KierstedMonsters (Clb)D82124557-718087139174651376.90%143192523.496814812110112214310.00%000000.5900000312
6Julien GauthierMonsters (Clb)RW822135565220102111255601658.24%15161219.66471149200404131150241.38%11600000.6923000122
7Luke PhilpMonsters (Clb)C8222345610240761622197015810.05%7101912.43123316000023257.86%118900011.1000000422
8Ronald AttardColumbusD51163551-632016011216456959.76%94122023.936713741331123120000.00%000100.8400000634
9Wayne SimmondsMonsters (Clb)LW/RW822129501580294122219501379.59%12154018.78156321990003385150.58%25900000.65410000325
10Cole FonstadMonsters (Clb)C/LW82172643132607791203671478.37%10110013.430113400021101156.34%14200000.7800000210
11Connor MackeyMonsters (Clb)D8282937158351976777355410.39%62142717.413471673000167010.00%000000.5200100220
12Dominik BokkMonsters (Clb)LW/RW8282533262410944112728976.30%12128415.67191025192000041149.41%8500000.5100002102
13Kurtis MacDermidMonsters (Clb)D82524291012525333488556585.88%97166420.30011281800001163100.00%000000.3500301052
14Chad YetmanMonsters (Clb)C/RW801214264240615895305912.63%498312.290223190000273244.25%11300000.5300000023
15Kasper BjorkqvistMonsters (Clb)LW/RW7071118-426063439123557.69%56399.1400002000001044.19%4300000.5600000000
16Tim SoderlundMonsters (Clb)LW/RW8071017-134025608225728.54%157279.102135110000271038.10%4200000.4700000011
17Jake ChristiansenMonsters (Clb)D82891724240934778285710.26%105150718.3911211680110129200.00%000000.2300000002
18Matt FilipeMonsters (Clb)C/LW82459-12271578837823555.13%136958.4800000000000148.93%79700000.2600012010
19Adam GinningMonsters (Clb)D271895802013162126.25%3544316.4400014000014000.00%000000.4100000000
20Brandon CoeMonsters (Clb)RW101011005312548.33%1929.2600000000000066.67%600000.2200000000
21Chase PriskieMonsters (Clb)D4000240515100.00%48922.430002400008000.00%000000.00%00000000
22Wyatte WylieMonsters (Clb)D1000100310000.00%31717.200000000000000.00%000000.00%00000000
Statistiques d’équipe totales ou en moyenne14702825067881626166020821902320997622688.79%8232438916.594786133557204971118621843442049.38%720800130.651232415413943
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)82492490.9123.0449356025028470220.63633820674
2Jakub SkarekMonsters (Clb)20000.9621.1154001260000.00%0076000
Statistiques d’équipe totales ou en moyenne84492490.9133.024989602512873022338276674


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 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 GinningMonsters (Clb)D212000-01-13Yes206 Lbs6 ft4NoNoNo3Pro & Farm825,000$0$0$No825,000$825,000$Lien
Benoit-Olivier GroulxMonsters (Clb)C212000-02-05Yes195 Lbs6 ft2NoNoNo3Pro & Farm822,500$0$0$No822,500$822,500$Lien
Brandon CoeMonsters (Clb)RW192001-12-01Yes190 Lbs6 ft4NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Lien
Brandon Pirri (contrat à 1 volet)Monsters (Clb)C/LW/RW301991-04-10No186 Lbs6 ft0YesNoYes2Pro & Farm650,000$0$0$No650,000$Lien
Chad YetmanMonsters (Clb)C/RW212000-02-18Yes179 Lbs5 ft11NoNoNo3Pro & Farm560,000$0$0$No560,000$560,000$Lien
Chase PriskieMonsters (Clb)D251996-03-18No185 Lbs6 ft0NoNoYes2Pro & Farm675,000$0$0$No675,000$Lien
Cole FonstadMonsters (Clb)C/LW212000-04-24Yes165 Lbs5 ft10YesNoNo1Pro & Farm900,000$0$0$NoLien
Connor MackeyMonsters (Clb)D251996-09-12No190 Lbs6 ft2NoNoYes3Pro & Farm925,000$0$0$No925,000$925,000$Lien
Dominik BokkMonsters (Clb)LW/RW212000-02-03Yes181 Lbs6 ft2NoNoNo3Pro & Farm863,333$0$0$No863,333$863,333$Lien
Drew HellesonMonsters (Clb)D202001-03-26Yes190 Lbs6 ft3NoNoNo4Pro & Farm925,000$0$0$No925,000$925,000$925,000$Lien
Jake ChristiansenMonsters (Clb)D221999-09-12Yes195 Lbs6 ft1NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Jakub SkarekMonsters (Clb)G211999-11-10Yes202 Lbs6 ft3NoNoNo3Pro & Farm764,167$0$0$No764,167$764,167$Lien
Julien GauthierMonsters (Clb)RW231997-10-15No227 Lbs6 ft4NoNoNo2Pro & Farm990,900$0$0$No990,900$Lien
Kasper BjorkqvistMonsters (Clb)LW/RW241997-07-10No198 Lbs6 ft1NoNoYes3Pro & Farm800,000$0$0$No800,000$800,000$Lien
Keaton MiddletonMonsters (Clb)D231998-02-10No240 Lbs6 ft6NoNoNo1Pro & Farm650,000$0$0$NoLien
Kurtis MacDermid (contrat à 1 volet)Monsters (Clb)D271994-03-25No233 Lbs6 ft5NoNoYes2Pro & Farm650,000$0$0$No650,000$Lien
Luke PhilpMonsters (Clb)C251995-11-06No181 Lbs5 ft10NoNoYes1Pro & Farm600,000$0$0$NoLien
Mads SogaardMonsters (Clb)G202000-12-13Yes201 Lbs6 ft7NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Matt FilipeMonsters (Clb)C/LW231997-12-31No193 Lbs6 ft2NoNoNo1Pro & Farm600,000$0$0$NoLien
Matt KierstedMonsters (Clb)D231998-04-14No181 Lbs6 ft0NoNoNo1Pro & Farm858,750$0$0$NoLien
Nils LundkvistMonsters (Clb)D212000-07-27Yes187 Lbs5 ft10NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien
Sheldon Dries (contrat à 1 volet)Monsters (Clb)C/LW271994-04-23No180 Lbs5 ft9NoNoYes3Pro & Farm700,000$0$0$No700,000$700,000$Lien
Tim SoderlundMonsters (Clb)LW/RW231998-01-23No163 Lbs5 ft9NoNoNo2Pro & Farm825,834$0$0$No825,834$Lien
Wayne Simmonds (contrat à 1 volet)Monsters (Clb)LW/RW331988-08-26No185 Lbs6 ft2YesNoYes4Pro & Farm750,000$0$0$No750,000$750,000$750,000$Lien
Wyatte WylieMonsters (Clb)D211999-11-02Yes190 Lbs6 ft0NoNoNo3Pro & Farm820,833$0$0$No820,833$820,833$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2523.20193 Lbs6 ft12.40783,253$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Wayne SimmondsSheldon DriesJulien Gauthier40014
2Brandon PirriBenoit-Olivier GroulxDominik Bokk30014
3Cole FonstadLuke PhilpKasper Bjorkqvist20023
4Tim SoderlundMatt FilipeChad Yetman10032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kurtis MacDermidMatt Kiersted40014
2Jake ChristiansenNils Lundkvist30023
3Connor MackeyAdam Ginning20023
4Kurtis MacDermidMatt Kiersted10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Wayne SimmondsSheldon DriesJulien Gauthier60050
2Brandon PirriBenoit-Olivier GroulxDominik Bokk40005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kurtis MacDermidMatt Kiersted60014
2Jake ChristiansenConnor Mackey40014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Benoit-Olivier GroulxSheldon Dries60122
2Brandon PirriJulien Gauthier40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kurtis MacDermidMatt Kiersted60122
2Jake ChristiansenNils Lundkvist40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Benoit-Olivier Groulx60122Kurtis MacDermidMatt Kiersted60122
2Sheldon Dries40122Jake ChristiansenNils Lundkvist40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Wayne SimmondsSheldon Dries60122
2Benoit-Olivier GroulxJulien Gauthier40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kurtis MacDermidMatt Kiersted60122
2Jake ChristiansenNils Lundkvist40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Wayne SimmondsSheldon DriesJulien GauthierKurtis MacDermidMatt Kiersted
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Brandon PirriBenoit-Olivier GroulxJulien GauthierKurtis MacDermidMatt Kiersted
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Brandon Pirri, Luke Philp, Cole FonstadCole Fonstad, Luke PhilpCole Fonstad
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Connor Mackey, Jake Christiansen, Kurtis MacDermidConnor MackeyNils Lundkvist, Kurtis MacDermid
Tirs de pénalité
Wayne Simmonds, Sheldon Dries, Benoit-Olivier Groulx, Julien Gauthier, Brandon Pirri
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
1Admirals211000004401010000013-21100000031220.500471100109927716731039103210937750148385120.00%4175.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
2Baby Hawks20101000710-3100010004311010000037-420.5007132000109927716801039103210937770292566500.00%10370.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
3Bears42100010161062010001078-12200000092760.750162642101099277161551039103210937713636301011815.56%14192.86%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
4Bruins310010011293110000004132000100188050.8331223350010992771611210391032109377762420728225.00%9277.78%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
5Cabaret Lady Mary Ann3300000015782200000012661100000031261.000152843001099277161831039103210937798271896300.00%9366.67%21531302550.61%1363281248.47%665137148.50%2022138218766051092557
6Caroline321000001174211000006511100000052340.6671120310010992771699103910321093771273637884250.00%13376.92%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
7Chiefs211000009721010000034-11100000063320.50091524001099277168610391032109377651516605360.00%8362.50%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
8Chill22000000844110000003211100000052341.00081422001099277168610391032109377631421447114.29%8187.50%11531302550.61%1363281248.47%665137148.50%2022138218766051092557
9Comets2110000056-1110000003121010000025-320.50051015001099277167210391032109377722111515240.00%30100.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
10Cougars32000010161062100001012931100000041361.00016274300109927716117103910321093771043128988450.00%13469.23%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
11Crunch311010001082211000006511000100043140.66710182800109927716158103910321093778027217312325.00%7271.43%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
12Heat210001008711000010034-11100000053230.750813210010992771684103910321093778028849400.00%40100.00%11531302550.61%1363281248.47%665137148.50%2022138218766051092557
13Jayhawks2110000046-21010000003-31100000043120.5004812001099277165710391032109377641725507228.57%9366.67%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
14Las Vegas21000010972100000105411100000043141.000914230010992771693103910321093778017214210220.00%8275.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
15Manchots422000001413122000000113820200000310-740.50014253900109927716116103910321093771283934934125.00%17194.12%11531302550.61%1363281248.47%665137148.50%2022138218766051092557
16Marlies3200000113112110000005322100000188050.833132538001099277161201039103210937710027147315320.00%7185.71%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
17Minnesota21100000550110000003121010000024-220.500581300109927716761039103210937785282349200.00%9277.78%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
18Monarchs21001000972100010005411100000043141.00091726001099277168810391032109377692617505120.00%60100.00%11531302550.61%1363281248.47%665137148.50%2022138218766051092557
19Monsters2010001056-11010000024-21000001032120.5005611001099277166610391032109377652212557228.57%6183.33%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
20Oceanics2020000027-51010000002-21010000025-300.00023510109927716781039103210937773204591200.00%2150.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
21Oil Kings2110000067-11010000024-21100000043120.5006111700109927716871039103210937786221841500.00%8187.50%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
22Phantoms4300000117107220000009452100000186270.87517304700109927716148103910321093771482818847114.29%80100.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
23Rocket312000001114-320200000711-41100000043120.333112031001099277161231039103210937710626236110440.00%9277.78%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
24Seattle211000006601010000012-11100000054120.5006101600109927716921039103210937781231050300.00%5180.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
25Senators321000008711010000035-22200000052340.667814220010992771687103910321093771092912819111.11%6183.33%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
26Sharks211000001082110000006241010000046-220.500101727001099277166810391032109377721318616233.33%8275.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
27Sound Tigers411001011318-52100010010912010000139-640.50013253800109927716166103910321093771755045110900.00%20670.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
28Spiders30200001715-81000000134-120200000411-710.1677132000109927716104103910321093771062722879222.22%11463.64%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
29Stars2010010013-21000010012-11010000001-110.250123001099277166510391032109377652914477114.29%70100.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
30Thunder320000101275110000005322100001074361.00012213300109927716113103910321093778325147312325.00%70100.00%01531302550.61%1363281248.47%665137148.50%2022138218766051092557
31Wolf Pack4300010014122220000006422100010088070.875142337001099277161571039103210937715953358015320.00%10190.00%11531302550.61%1363281248.47%665137148.50%2022138218766051092557
Total824024044552872582941191302331148125234121110212413913361070.65228750679320109927716320910391032109377287582362220822384719.75%2655280.38%71531302550.61%1363281248.47%665137148.50%2022138218766051092557
_Since Last GM Reset824024044552872582941191302331148125234121110212413913361070.65228750679320109927716320910391032109377287582362220822384719.75%2655280.38%71531302550.61%1363281248.47%665137148.50%2022138218766051092557
_Vs Conference4523110222515914217201240111178572125117011148185-4610.67815928344220109927716167110391032109377154742531211061412215.60%1372283.94%41531302550.61%1363281248.47%665137148.50%2022138218766051092557
_Vs Division267300203928571350001015237151323001024048-8190.365921622541010992771694510391032109377979269221643661015.15%931682.80%21531302550.61%1363281248.47%665137148.50%2022138218766051092557

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
82107W128750679332092875823622208220
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8240244455287258
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4119132331148125
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4121112124139133
Derniers 10 matchs
WLOTWOTL SOWSOL
420103
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2384719.75%2655280.38%7
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
10391032109377109927716
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
1531302550.61%1363281248.47%665137148.50%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2022138218766051092557


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
6 - 2022-10-126Monsters5Caroline2AWSommaire du match
8 - 2022-10-1421Thunder3Monsters5BWSommaire du match
9 - 2022-10-1533Monsters6Chiefs3AWSommaire du match
12 - 2022-10-1850Comets1Monsters3BWSommaire du match
14 - 2022-10-2063Chill2Monsters3BWSommaire du match
16 - 2022-10-2282Manchots1Monsters4BWSommaire du match
17 - 2022-10-2389Monsters4Wolf Pack3AWSommaire du match
19 - 2022-10-2598Jayhawks3Monsters0BLSommaire du match
22 - 2022-10-28122Bruins1Monsters4BWSommaire du match
24 - 2022-10-30139Monsters2Spiders4ALSommaire du match
29 - 2022-11-04174Monsters3Monsters2AWXXSommaire du match
30 - 2022-11-05176Monsters4Monsters2BLSommaire du match
35 - 2022-11-10214Phantoms1Monsters4BWSommaire du match
37 - 2022-11-12231Monsters0Sound Tigers5ALSommaire du match
40 - 2022-11-15250Phantoms3Monsters5BWSommaire du match
42 - 2022-11-17263Rocket6Monsters4BLSommaire du match
44 - 2022-11-19280Cougars3Monsters5BWSommaire du match
45 - 2022-11-20289Cabaret Lady Mary Ann3Monsters6BWSommaire du match
48 - 2022-11-23307Rocket5Monsters3BLSommaire du match
50 - 2022-11-25326Sound Tigers5Monsters7BWSommaire du match
51 - 2022-11-26338Monsters5Chill2AWSommaire du match
53 - 2022-11-28349Las Vegas4Monsters5BWXXSommaire du match
57 - 2022-12-02378Monsters2Oceanics5ALSommaire du match
59 - 2022-12-04394Cougars6Monsters7BWXXSommaire du match
61 - 2022-12-06404Monsters2Manchots5ALSommaire du match
62 - 2022-12-07412Crunch2Monsters4BWSommaire du match
64 - 2022-12-09424Heat4Monsters3BLXSommaire du match
66 - 2022-12-11443Monarchs4Monsters5BWXSommaire du match
68 - 2022-12-13455Monsters3Cabaret Lady Mary Ann1AWSommaire du match
70 - 2022-12-15470Monsters5Thunder3AWSommaire du match
72 - 2022-12-17484Monsters4Bruins3AWXSommaire du match
74 - 2022-12-19502Stars2Monsters1BLXSommaire du match
75 - 2022-12-20510Monsters5Phantoms2AWSommaire du match
78 - 2022-12-23540Monsters3Baby Hawks7ALSommaire du match
82 - 2022-12-27547Crunch3Monsters2BLSommaire du match
84 - 2022-12-29567Monsters3Sound Tigers4ALXXSommaire du match
86 - 2022-12-31584Baby Hawks3Monsters4BWXSommaire du match
89 - 2023-01-03601Monsters2Senators1AWSommaire du match
91 - 2023-01-05617Bears6Monsters4BLSommaire du match
93 - 2023-01-07629Caroline2Monsters4BWSommaire du match
94 - 2023-01-08639Monsters4Bears1AWSommaire du match
96 - 2023-01-10648Monsters2Thunder1AWXXSommaire du match
98 - 2023-01-12662Caroline3Monsters2BLSommaire du match
100 - 2023-01-14679Monsters4Cougars1AWSommaire du match
102 - 2023-01-16701Wolf Pack2Monsters3BWSommaire du match
105 - 2023-01-19717Admirals3Monsters1BLSommaire du match
107 - 2023-01-21736Sharks2Monsters6BWSommaire du match
109 - 2023-01-23754Monsters5Heat3AWSommaire du match
111 - 2023-01-25768Monsters4Oil Kings3AWSommaire du match
113 - 2023-01-27787Monsters2Comets5ALSommaire du match
114 - 2023-01-28797Monsters5Seattle4AWSommaire du match
117 - 2023-01-31804Bears2Monsters3BWXXSommaire du match
127 - 2023-02-10829Marlies3Monsters5BWSommaire du match
128 - 2023-02-11840Monsters4Marlies3AWSommaire du match
131 - 2023-02-14857Spiders4Monsters3BLXXSommaire du match
133 - 2023-02-16872Oceanics2Monsters0BLSommaire du match
135 - 2023-02-18887Monsters0Stars1ALSommaire du match
136 - 2023-02-19901Monsters4Jayhawks3AWSommaire du match
140 - 2023-02-23924Minnesota1Monsters3BWSommaire du match
142 - 2023-02-25936Oil Kings4Monsters2BLSommaire du match
143 - 2023-02-26948Monsters2Minnesota4ALSommaire du match
145 - 2023-02-28958Monsters4Crunch3AWXSommaire du match
148 - 2023-03-03984Seattle2Monsters1BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-03-04996Monsters3Senators1AWSommaire du match
152 - 2023-03-071013Monsters1Manchots5ALSommaire du match
156 - 2023-03-111045Chiefs4Monsters3BLSommaire du match
159 - 2023-03-141074Monsters4Sharks6ALSommaire du match
161 - 2023-03-161089Monsters4Monarchs3AWSommaire du match
162 - 2023-03-171094Monsters3Admirals1AWSommaire du match
164 - 2023-03-191110Monsters4Las Vegas3AWSommaire du match
166 - 2023-03-211121Monsters5Bears1AWSommaire du match
169 - 2023-03-241147Sound Tigers4Monsters3BLXSommaire du match
170 - 2023-03-251159Monsters4Rocket3AWSommaire du match
173 - 2023-03-281176Monsters4Wolf Pack5ALXSommaire du match
175 - 2023-03-301189Monsters4Bruins5ALXXSommaire du match
177 - 2023-04-011208Cabaret Lady Mary Ann3Monsters6BWSommaire du match
178 - 2023-04-021220Senators5Monsters3BLSommaire du match
180 - 2023-04-041230Monsters4Marlies5ALXXSommaire du match
182 - 2023-04-061243Monsters2Spiders7ALSommaire du match
184 - 2023-04-081264Wolf Pack2Monsters3BWSommaire du match
187 - 2023-04-111287Monsters3Phantoms4ALXXSommaire du match
189 - 2023-04-131303Manchots2Monsters7BWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance78,23739,002
Assistance PCT95.41%95.13%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2859 - 95.32% 81,057$3,323,325$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,740,595$ 1,683,131$ 1,683,131$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,859$ 1,740,595$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 8,859$ 0$




Monsters 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

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 (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