Connexion

Monsters
GP: 24 | W: 17 | L: 7 | OTL: 0 | P: 34
GF: 94 | GA: 77 | PP%: 30.36% | PK%: 78.31%
DG: Benoit Toupin | Morale : 50 | Moyenne d’équipe : 57
Prochains matchs #404 vs Manchots
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Centre de jeu
Monsters
17-7-0, 34pts
2
FINAL
5 Oceanics
14-7-2, 30pts
Team Stats
W1StreakW2
12-4-0Home Record7-5-0
5-3-0Away Record7-2-2
7-3-0Last 10 Games6-3-1
3.92Buts par match 4.09
3.21Buts contre par match 3.65
30.36%Pourcentage en avantage numérique26.39%
78.31%Pourcentage en désavantage numérique80.68%
Cougars
14-7-3, 31pts
6
FINAL
7 Monsters
17-7-0, 34pts
Team Stats
SOL2StreakW1
8-5-1Home Record12-4-0
6-2-2Away Record5-3-0
6-2-2Last 10 Games7-3-0
4.54Buts par match 3.92
3.79Buts contre par match 3.21
22.08%Pourcentage en avantage numérique30.36%
74.63%Pourcentage en désavantage numérique78.31%
Monsters
17-7-0, 34pts
2022-12-06
Manchots
11-13-1, 23pts
Statistiques d’équipe
W1SéquenceW1
12-4-0Fiche domicile5-6-0
5-3-0Fiche visiteur6-7-1
7-3-010 derniers matchs3-7-0
3.92Buts par match 3.08
3.21Buts contre par match 3.08
30.36%Pourcentage en avantage numérique25.00%
78.31%Pourcentage en désavantage numérique78.26%
Crunch
13-9-3, 29pts
2022-12-07
Monsters
17-7-0, 34pts
Statistiques d’équipe
L2SéquenceW1
8-6-1Fiche domicile12-4-0
5-3-2Fiche visiteur5-3-0
5-4-110 derniers matchs7-3-0
3.16Buts par match 3.92
3.32Buts contre par match 3.92
14.49%Pourcentage en avantage numérique30.36%
74.39%Pourcentage en désavantage numérique78.31%
Heat
11-12-2, 24pts
2022-12-09
Monsters
17-7-0, 34pts
Statistiques d’équipe
W1SéquenceW1
6-7-2Fiche domicile12-4-0
5-5-0Fiche visiteur5-3-0
6-4-010 derniers matchs7-3-0
3.60Buts par match 3.92
3.76Buts contre par match 3.92
19.70%Pourcentage en avantage numérique30.36%
72.92%Pourcentage en désavantage numérique78.31%
Meneurs d'équipe
Buts
Brandon Pirri
18
Passes
Benoit-Olivier Groulx
20
Points
Brandon Pirri
28
Plus/Moins
Benoit-Olivier Groulx
12
Victoires
Mads Sogaard
17
Pourcentage d’arrêts
Jakub Skarek
1

Statistiques d’équipe
Buts pour
94
3.92 GFG
Tirs pour
924
38.50 Avg
Pourcentage en avantage numérique
30.4%
17 GF
Début de zone offensive
40.7%
Buts contre
77
3.21 GAA
Tirs contre
849
35.38 Avg
Pourcentage en désavantage numérique
78.3%%
18 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
Assistance2,855
Billets de saison300


Informations de la formation

Équipe Pro26
Équipe Mineure19
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$
13Ronald AttardX100.00814584717770436925505478254545050630224883,750$
14Matt KierstedX100.00754393716764665725495078254545050620231858,750$
15Kurtis MacDermidX100.00839959699046695525444867256060050610272650,000$
16Nils Lundkvist (R)X100.00674299766664586425504866254646050600213925,000$
17Connor MackeyX100.00687258717267705525544259404444050580253925,000$
18Jake Christiansen (R)X100.00764499667254625425395464254444050570222925,000$
Rayé
1Brandon Coe (R)X100.00757488627455574849484362434444050520193650,000$
2Chase PriskieX100.00736885656861635725504962474444050570252675,000$
3Keaton MiddletonX100.00819159619155584725384063384444050560231650,000$
4Adam Ginning (R)X100.00585870617758833825333566385052050560213825,000$
5Wyatte Wylie (R)X100.00757088637059624825394161394444050550213820,833$
6Drew Helleson (R)X100.00787391697338374525363961374444050530204925,000$
MOYENNE D’ÉQUIPE100.0074648467725660554249516440494905057
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
1Brandon PirriMonsters (Clb)C/LW/RW2418102811404732112217216.07%542217.6125711420001382253.57%5600001.3311000235
2Benoit-Olivier GroulxMonsters (Clb)C24820281240336810641897.55%1344618.6234717430113573149.58%58900001.2502000221
3Nils LundkvistMonsters (Clb)D246182460073553193111.32%3549320.562132841000161100.00%000000.9700000121
4Luke PhilpMonsters (Clb)C2471320712022497524479.33%331012.9300016000002056.99%36500011.2900000101
5Matt KierstedMonsters (Clb)D2441620140334632153512.50%3956423.533581044011066100.00%000000.7100000101
6Ronald AttardMonsters (Clb)D2071320-2220653748173314.58%3247123.563471941011051000.00%000000.8500000311
7Julien GauthierMonsters (Clb)RW2481018-540323271154211.27%546519.3914512412023370145.71%3500000.7722000020
8Cole FonstadMonsters (Clb)C/LW247714816023257118459.86%132613.59000000001281056.52%4600000.8600000100
9Connor MackeyMonsters (Clb)D24211131135577201271716.67%2040216.7900008000019000.00%000000.6500100100
10Sheldon DriesMonsters (Clb)C/LW244913-8004718521844.71%850821.191237410002741042.25%56100000.5123000100
11Chad YetmanMonsters (Clb)C/RW244610880231926142115.38%131313.0701107000061241.30%4600000.6400000012
12Kurtis MacDermidMonsters (Clb)D2437104521089133220189.38%2345919.140001038000145100.00%000000.4400001022
13Wayne SimmondsMonsters (Clb)LW/RW24459-912074377316345.48%146319.321128420003380153.08%13000000.3913000001
14Dominik BokkMonsters (Clb)LW/RW24178107537102811283.57%237915.80033442000010048.15%2700000.4200001000
15Jake ChristiansenMonsters (Clb)D24415810018112591616.00%2141117.1610114000031100.00%000000.2400000000
16Tim SoderlundMonsters (Clb)LW/RW22134200510228174.55%21948.8501124000050030.77%1300000.4100000000
17Matt FilipeMonsters (Clb)C/LW241343402728192205.26%41948.1100000000000050.00%21800000.4100000000
18Kasper BjorkqvistMonsters (Clb)LW/RW121232209417375.88%0937.7900001000000033.33%300000.6400000000
19Brandon CoeMonsters (Clb)RW101011005312548.33%1929.2600000000000066.67%600000.2200000000
20Chase PriskieMonsters (Clb)D4000240515100.00%48922.430002400008000.00%000000.00%00000000
Statistiques d’équipe totales ou en moyenne4289116125272200206355519242876609.85%220710416.601731481324582351557614749.07%209500010.71611102131315
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)2417700.9073.24142800778280000.81811240211
2Jakub SkarekMonsters (Clb)10001.0000.00%26000210000.00%0020000
Statistiques d’équipe totales ou en moyenne2517700.9093.1814550077849000112420211


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$564,474$0$0$No825,000$825,000$Lien
Benoit-Olivier GroulxMonsters (Clb)C212000-02-05Yes195 Lbs6 ft2NoNoNo3Pro & Farm822,500$562,763$0$0$No822,500$822,500$Lien
Brandon CoeMonsters (Clb)RW192001-12-01Yes190 Lbs6 ft4NoNoNo3Pro & Farm650,000$444,737$0$0$No650,000$650,000$Lien
Brandon Pirri (contrat à 1 volet)Monsters (Clb)C/LW/RW301991-04-10No186 Lbs6 ft0YesNoYes2Pro & Farm650,000$444,737$0$0$No650,000$Lien
Chad YetmanMonsters (Clb)C/RW212000-02-18Yes179 Lbs5 ft11NoNoNo3Pro & Farm560,000$383,158$0$0$No560,000$560,000$Lien
Chase PriskieMonsters (Clb)D251996-03-18No185 Lbs6 ft0NoNoYes2Pro & Farm675,000$461,842$0$0$No675,000$Lien
Cole FonstadMonsters (Clb)C/LW212000-04-24Yes165 Lbs5 ft10YesNoNo1Pro & Farm900,000$615,789$0$0$NoLien
Connor MackeyMonsters (Clb)D251996-09-12No190 Lbs6 ft2NoNoYes3Pro & Farm925,000$632,895$0$0$No925,000$925,000$Lien
Dominik BokkMonsters (Clb)LW/RW212000-02-03Yes181 Lbs6 ft2NoNoNo3Pro & Farm863,333$590,702$0$0$No863,333$863,333$Lien
Drew HellesonMonsters (Clb)D202001-03-26Yes190 Lbs6 ft3NoNoNo4Pro & Farm925,000$632,895$0$0$No925,000$925,000$925,000$Lien
Jake ChristiansenMonsters (Clb)D221999-09-12Yes195 Lbs6 ft1NoNoNo2Pro & Farm925,000$632,895$0$0$No925,000$Lien
Jakub SkarekMonsters (Clb)G211999-11-10Yes202 Lbs6 ft3NoNoNo3Pro & Farm764,167$522,851$0$0$No764,167$764,167$Lien
Julien GauthierMonsters (Clb)RW231997-10-15No227 Lbs6 ft4NoNoNo2Pro & Farm990,900$677,984$0$0$No990,900$Lien
Kasper BjorkqvistMonsters (Clb)LW/RW241997-07-10No198 Lbs6 ft1NoNoYes3Pro & Farm800,000$547,368$0$0$No800,000$800,000$Lien
Keaton MiddletonMonsters (Clb)D231998-02-10No240 Lbs6 ft6NoNoNo1Pro & Farm650,000$444,737$0$0$NoLien
Kurtis MacDermid (contrat à 1 volet)Monsters (Clb)D271994-03-25No233 Lbs6 ft5NoNoYes2Pro & Farm650,000$444,737$0$0$No650,000$Lien
Luke PhilpMonsters (Clb)C251995-11-06No181 Lbs5 ft10NoNoYes1Pro & Farm600,000$410,526$0$0$NoLien
Mads SogaardMonsters (Clb)G202000-12-13Yes201 Lbs6 ft7NoNoNo2Pro & Farm925,000$632,895$0$0$No925,000$Lien
Matt FilipeMonsters (Clb)C/LW231997-12-31No193 Lbs6 ft2NoNoNo1Pro & Farm600,000$410,526$0$0$NoLien
Matt KierstedMonsters (Clb)D231998-04-14No181 Lbs6 ft0NoNoNo1Pro & Farm858,750$587,566$0$0$NoLien
Nils LundkvistMonsters (Clb)D212000-07-27Yes187 Lbs5 ft10NoNoNo3Pro & Farm925,000$632,895$0$0$No925,000$925,000$Lien
Ronald AttardMonsters (Clb)D221999-03-20No207 Lbs6 ft3NoNoNo4Pro & Farm883,750$604,671$0$0$No883,750$883,750$883,750$Lien
Sheldon Dries (contrat à 1 volet)Monsters (Clb)C/LW271994-04-23No180 Lbs5 ft9NoNoYes3Pro & Farm700,000$478,947$0$0$No700,000$700,000$Lien
Tim SoderlundMonsters (Clb)LW/RW231998-01-23No163 Lbs5 ft9NoNoNo2Pro & Farm825,834$565,044$0$0$No825,834$Lien
Wayne Simmonds (contrat à 1 volet)Monsters (Clb)LW/RW331988-08-26No185 Lbs6 ft2YesNoYes4Pro & Farm750,000$513,158$0$0$No750,000$750,000$750,000$Lien
Wyatte WylieMonsters (Clb)D211999-11-02Yes190 Lbs6 ft0NoNoNo3Pro & Farm820,833$561,623$0$0$No820,833$820,833$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2623.15193 Lbs6 ft12.46787,118$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Wayne SimmondsSheldon DriesJulien Gauthier40014
2Brandon PirriBenoit-Olivier GroulxDominik Bokk30014
3Cole FonstadLuke PhilpChad Yetman20023
4Tim SoderlundMatt FilipeKasper Bjorkqvist10032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ronald AttardMatt Kiersted40014
2Kurtis MacDermidNils Lundkvist30023
3Connor MackeyJake Christiansen20023
4Ronald AttardMatt 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
1Ronald AttardMatt Kiersted60014
2Kurtis MacDermidNils Lundkvist40014
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
1Ronald AttardMatt Kiersted60122
2Kurtis MacDermidNils Lundkvist40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Benoit-Olivier Groulx60122Ronald AttardMatt Kiersted60122
2Sheldon Dries40122Kurtis MacDermidNils Lundkvist40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Wayne SimmondsSheldon Dries60122
2Benoit-Olivier GroulxJulien Gauthier40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ronald AttardMatt Kiersted60122
2Kurtis MacDermidNils Lundkvist40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Wayne SimmondsSheldon DriesJulien GauthierRonald AttardMatt Kiersted
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Brandon PirriBenoit-Olivier GroulxJulien GauthierRonald AttardMatt Kiersted
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Chad Yetman, Luke Philp, Cole FonstadChad Yetman, Luke PhilpCole Fonstad
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Connor Mackey, Jake Christiansen, Kurtis MacDermidConnor MackeyJake Christiansen, 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
1Bruins11000000413110000004130000000000021.00048120030313062332428231019226817000.00%40100.00%043285250.70%39381848.04%20342547.76%602415534170318162
2Cabaret Lady Mary Ann11000000633110000006330000000000021.000611170030313065832428231019287625100.00%3233.33%143285250.70%39381848.04%20342547.76%602415534170318162
3Caroline11000000523000000000001100000052321.00051015003031306533242823101944131040000.00%50100.00%043285250.70%39381848.04%20342547.76%602415534170318162
4Chiefs11000000633000000000001100000063321.00061016003031306533242823101933764411100.00%30100.00%043285250.70%39381848.04%20342547.76%602415534170318162
5Chill22000000844110000003211100000052341.000814220030313068632428231019631421447114.29%8187.50%143285250.70%39381848.04%20342547.76%602415534170318162
6Comets11000000312110000003120000000000021.00036900303130639324282310192979264250.00%20100.00%043285250.70%39381848.04%20342547.76%602415534170318162
7Cougars2100001012932100001012930000000000041.0001219310030313066732428231019702022636350.00%10460.00%043285250.70%39381848.04%20342547.76%602415534170318162
8Jayhawks1010000003-31010000003-30000000000000.00000000303130633324282310193191229300.00%5260.00%043285250.70%39381848.04%20342547.76%602415534170318162
9Las Vegas10000010541100000105410000000000021.0005712003031306413242823101949811206233.33%3166.67%043285250.70%39381848.04%20342547.76%602415534170318162
10Manchots11000000413110000004130000000000021.00047110030313063832428231019238823000.00%40100.00%043285250.70%39381848.04%20342547.76%602415534170318162
11Monsters2010001056-11010000024-21000001032120.50056110030313066632428231019652212557228.57%6183.33%043285250.70%39381848.04%20342547.76%602415534170318162
12Oceanics1010000025-3000000000001010000025-300.00023500303130643324282310193817238600.00%10100.00%043285250.70%39381848.04%20342547.76%602415534170318162
13Phantoms22000000945220000009450000000000041.0009152400303130666324282310197613844000.00%40100.00%043285250.70%39381848.04%20342547.76%602415534170318162
14Rocket20200000711-420200000711-40000000000000.000713200030313068132428231019661510417342.86%5180.00%043285250.70%39381848.04%20342547.76%602415534170318162
15Sound Tigers21100000710-3110000007521010000005-520.50071421003031306823242823101998242260200.00%11554.55%043285250.70%39381848.04%20342547.76%602415534170318162
16Spiders1010000024-2000000000001010000024-200.00023500303130626324282310193811102311100.00%5180.00%043285250.70%39381848.04%20342547.76%602415534170318162
17Thunder11000000532110000005320000000000021.0005914003031306343242823101928116223266.67%30100.00%043285250.70%39381848.04%20342547.76%602415534170318162
18Wolf Pack11000000431000000000001100000043121.000461000303130635324282310194881721200.00%10100.00%043285250.70%39381848.04%20342547.76%602415534170318162
Total241470003094771716104000206751168430001027261340.7089416125500303130692432428231019849220200635561730.36%831878.31%243285250.70%39381848.04%20342547.76%602415534170318162
_Since Last GM Reset241470003094771716104000206751168430001027261340.7089416125500303130692432428231019849220200635561730.36%831878.31%243285250.70%39381848.04%20342547.76%602415534170318162
_Vs Conference12930000045351077000000321616523000001319-6180.75045791240030313064333242823101943411210229221419.05%41782.93%143285250.70%39381848.04%20342547.76%602415534170318162
_Vs Division842000003124743000000201010412000001114-380.5003155860030313063003242823101932777752115120.00%30680.00%043285250.70%39381848.04%20342547.76%602415534170318162

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2434W19416125592484922020063500
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
2414700309477
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
1610400206751
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
84300102726
Derniers 10 matchs
WLOTWOTL SOWSOL
730000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
561730.36%831878.31%2
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
324282310193031306
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
43285250.70%39381848.04%20342547.76%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
602415534170318162


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 - 2022-12-06404Monsters-Manchots-
62 - 2022-12-07412Crunch-Monsters-
64 - 2022-12-09424Heat-Monsters-
66 - 2022-12-11443Monarchs-Monsters-
68 - 2022-12-13455Monsters-Cabaret Lady Mary Ann-
70 - 2022-12-15470Monsters-Thunder-
72 - 2022-12-17484Monsters-Bruins-
74 - 2022-12-19502Stars-Monsters-
75 - 2022-12-20510Monsters-Phantoms-
78 - 2022-12-23540Monsters-Baby Hawks-
82 - 2022-12-27547Crunch-Monsters-
84 - 2022-12-29567Monsters-Sound Tigers-
86 - 2022-12-31584Baby Hawks-Monsters-
89 - 2023-01-03601Monsters-Senators-
91 - 2023-01-05617Bears-Monsters-
93 - 2023-01-07629Caroline-Monsters-
94 - 2023-01-08639Monsters-Bears-
96 - 2023-01-10648Monsters-Thunder-
98 - 2023-01-12662Caroline-Monsters-
100 - 2023-01-14679Monsters-Cougars-
102 - 2023-01-16701Wolf Pack-Monsters-
105 - 2023-01-19717Admirals-Monsters-
107 - 2023-01-21736Sharks-Monsters-
109 - 2023-01-23754Monsters-Heat-
111 - 2023-01-25768Monsters-Oil Kings-
113 - 2023-01-27787Monsters-Comets-
114 - 2023-01-28797Monsters-Seattle-
117 - 2023-01-31804Bears-Monsters-
127 - 2023-02-10829Marlies-Monsters-
128 - 2023-02-11840Monsters-Marlies-
131 - 2023-02-14857Spiders-Monsters-
133 - 2023-02-16872Oceanics-Monsters-
135 - 2023-02-18887Monsters-Stars-
136 - 2023-02-19901Monsters-Jayhawks-
140 - 2023-02-23924Minnesota-Monsters-
142 - 2023-02-25936Oil Kings-Monsters-
143 - 2023-02-26948Monsters-Minnesota-
145 - 2023-02-28958Monsters-Crunch-
148 - 2023-03-03984Seattle-Monsters-
149 - 2023-03-04996Monsters-Senators-
152 - 2023-03-071013Monsters-Manchots-
156 - 2023-03-111045Chiefs-Monsters-
159 - 2023-03-141074Monsters-Sharks-
161 - 2023-03-161089Monsters-Monarchs-
162 - 2023-03-171094Monsters-Admirals-
164 - 2023-03-191110Monsters-Las Vegas-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
166 - 2023-03-211121Monsters-Bears-
169 - 2023-03-241147Sound Tigers-Monsters-
170 - 2023-03-251159Monsters-Rocket-
173 - 2023-03-281176Monsters-Wolf Pack-
175 - 2023-03-301189Monsters-Bruins-
177 - 2023-04-011208Cabaret Lady Mary Ann-Monsters-
178 - 2023-04-021220Senators-Monsters-
180 - 2023-04-041230Monsters-Marlies-
182 - 2023-04-061243Monsters-Spiders-
184 - 2023-04-081264Wolf Pack-Monsters-
187 - 2023-04-111287Monsters-Phantoms-
189 - 2023-04-131303Manchots-Monsters-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance30,29415,384
Assistance PCT94.67%96.15%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
25 2855 - 95.16% 80,691$1,291,050$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
550,062$ 1,771,506$ 1,771,506$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,324$ 550,062$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
2,017,266$ 130 9,324$ 1,212,120$




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