Connexion

Monsters
GP: 51 | W: 32 | L: 19 | OTL: 0 | P: 64
GF: 182 | GA: 156 | PP%: 17.42% | PK%: 74.31%
DG: Jean Francois Langelier | Morale : 69 | Moyenne d’équipe : 63
Prochains matchs #797 vs Gulls
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Centre de jeu
Reign
18-25-5, 41pts
5
FINAL
3 Monsters
32-19-0, 64pts
Team Stats
OTL1SéquenceW1
10-12-3Fiche domicile16-8-0
8-13-2Fiche domicile16-11-0
7-2-1Derniers 10 matchs3-7-0
3.23Buts par match 3.57
4.10Buts contre par match 3.06
19.62%Pourcentage en avantage numérique17.42%
70.59%Pourcentage en désavantage numérique74.31%
Monsters
32-19-0, 64pts
5
FINAL
3 Firebirds
30-19-1, 61pts
Team Stats
W1SéquenceL2
16-8-0Fiche domicile17-7-1
16-11-0Fiche domicile13-12-0
3-7-0Derniers 10 matchs5-5-0
3.57Buts par match 3.50
3.06Buts contre par match 3.18
17.42%Pourcentage en avantage numérique25.47%
74.31%Pourcentage en désavantage numérique80.42%
Gulls
23-22-4, 50pts
2023-12-11
Monsters
32-19-0, 64pts
Statistiques d’équipe
W1SéquenceW1
16-6-3Fiche domicile16-8-0
7-16-1Fiche visiteur16-11-0
7-3-010 derniers matchs3-7-0
3.04Buts par match 3.57
3.49Buts contre par match 3.57
29.10%Pourcentage en avantage numérique17.42%
76.19%Pourcentage en désavantage numérique74.31%
Monsters
32-19-0, 64pts
2023-12-13
Griffins
38-10-2, 78pts
Statistiques d’équipe
W1SéquenceSOW1
16-8-0Fiche domicile20-3-2
16-11-0Fiche visiteur18-7-0
3-7-010 derniers matchs7-3-0
3.57Buts par match 4.06
3.06Buts contre par match 4.06
17.42%Pourcentage en avantage numérique21.09%
74.31%Pourcentage en désavantage numérique79.61%
Condors
15-29-5, 35pts
2023-12-15
Monsters
32-19-0, 64pts
Statistiques d’équipe
L1SéquenceW1
10-13-2Fiche domicile16-8-0
5-16-3Fiche visiteur16-11-0
1-9-010 derniers matchs3-7-0
2.94Buts par match 3.57
3.82Buts contre par match 3.57
15.79%Pourcentage en avantage numérique17.42%
75.00%Pourcentage en désavantage numérique74.31%
Meneurs d'équipe
Buts
Teemu Pulkkinen
18
Passes
Juuso Valimaki
43
Points
Juuso Valimaki
52
Plus/Moins
Alexis Binner
18
Victoires
Mason McDonald
20
Pourcentage d’arrêts
Jaroslav Janus
0.897

Statistiques d’équipe
Buts pour
182
3.57 GFG
Tirs pour
1585
31.08 Avg
Pourcentage en avantage numérique
17.4%
27 GF
Début de zone offensive
42.0%
Buts contre
156
3.06 GAA
Tirs contre
1423
27.90 Avg
Pourcentage en désavantage numérique
74.3%%
37 GA
Début de la zone défensive
38.2%
Informations de l'équipe

Directeur généralJean Francois Langelier
EntraîneurKen Hitchcock
DivisionDivision Centrale
ConférenceConference 2
CapitaineVictor Mete
Assistant #1Steven Lorentz
Assistant #2Juuso Valimaki


Informations de l’aréna

Capacité3,000
Assistance2,028
Billets de saison300


Informations de la formation

Équipe Pro30
Équipe Mineure18
Limite contact 48 / 55
Espoirs17


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
1Jack Mcbain (R)X100.007865877272769072717272746655457080660233900,000$
2Jacob PetersonX100.0061469275707885727570727070585070796602421,700,000$
3Joseph Veleno (R)X100.007245877271749072717172756660457079660233900,000$
4Vyacheslav LeshchenkoX100.0072458475677374726571716660605557796602811,300,000$
5Steven Lorentz (A)X100.0065459374737785717070696968625061796602721,700,000$
6Linden VeyX100.0064459071697279696269686666575050796403231,250,000$
7Teemu PulkkinenX100.0058449671696971706169696967544750796303131,100,000$
8David DesharnaisX100.005846936767686767726764676272772960630372900,000$
9Michal RepikX100.0060439570706774696467686766534738586303431,100,000$
10Seth GriffithX100.0061449270697275696468696967544753796303031,100,000$
11Andrew DesjardinsX100.0068618568716875687767656763685429796303731,100,000$
12Ondrej RomanX100.006145957169716969636566706445453870620341800,000$
13Juuso Valimaki (R) (A)X100.006650827271809074457667736160456079660253900,000$
14Victor Mete (C)X100.006346927667748471457461755669476068660252900,000$
15TJ BrennanX100.006946896673687070466767736554493880640341900,000$
16Lucas JohansenX100.0060459971707466704565657563454566726402631,500,000$
17Rushan RafikovX100.006643837170696966456862686058545671630281900,000$
18Alexis BinnerX100.0062468375756771694565656857565066786302531,000,000$
Rayé
1Jordan SchroederX100.005643976967717068646867676558504620630332900,000$
2Dan SextonX100.0060439671677371696568686966544929206303631,100,000$
3Matt FrattinX100.006957856972666668616765676357493420620351800,000$
4Petr VranaX100.005136957067686668666866676447452425610381700,000$
5Kelsey TessierX100.005442977166666867676565726245454228610331700,000$
6Danick PaquetteX100.0063498668737067666463626460454546196003331,000,000$
7Tyler CumaX100.0061458973716766694569647163515142206303321,250,000$
8Matt BartkowskiX100.0064509369716868684567627162645234206303521,250,000$
9Gage AusmusX100.006756776973706564456260695150495520610281700,000$
MOYENNE D’ÉQUIPE100.00634790717071746960686670635650495763
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
1Mason McDonald100.00808779817773827673717957566068630271750,000$
2Jaroslav Janus100.007678777677778179808078455042776303431,050,000$
Rayé
1Brent Moran100.00798670817665836868757745456025590272750,000$
MOYENNE D’ÉQUIPE100.0078847579777282747475784950545762
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ken Hitchcock72828163999915CAN735100,000$


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Juuso ValimakiMonsters (Clb)D519435217440725768244713.24%67116922.947411351300220107020%000000.8900000332
2Joseph VelenoMonsters (Clb)C511731481726077901705010510.00%24101519.913693112611221033150.79%113400010.9500000235
3Victor MeteMonsters (Clb)D46538431712032436421427.81%51103622.5326834117022098100%000000.8300000103
4Jacob PetersonMonsters (Clb)LW511324371660115214938878.72%1090617.7725722127000032054.69%6400000.8200000131
5Jack McbainMonsters (Clb)C51152136152758710816540989.09%11101319.882352512710121052150.37%133600000.7111100511
6Steven LorentzMonsters (Clb)LW511618346404454124377412.90%886817.0336924126000005049.21%6300000.7800000261
7Teemu PulkkinenMonsters (Clb)LW5118143214201645106388316.98%1277215.150001501111102140.74%5400000.8300000340
8Linden VeyMonsters (Clb)RW51141630111003232118306811.86%888817.4336922126000004147.69%6500100.6800000211
9Lucas JohansenMonsters (Clb)D5162430315520426925398.70%50104320.45167271180002107200%000000.5800001112
10Vyacheslav LeshchenkoMonsters (Clb)RW511612281418054241203611813.33%389517.5613415126000005253.33%6000000.6311000115
11Alexis BinnerMonsters (Clb)D5182028184915473265183612.31%4797319.0835827121000039010%000000.5800120023
12Seth GriffithMonsters (Clb)RW51913226140213177245611.69%765912.93000000000290140.35%5700000.6700000100
13Andrew DesjardinsMonsters (Clb)C511111228140548176183714.47%1173814.480000310131051158.60%94200100.6000000221
14TJ BrennanMonsters (Clb)D5141721-4535763636192611.11%5085916.850001500007200%000000.4900001300
15Rushan RafikovMonsters (Clb)D51415191726062372662415.38%4493518.35000412000094000%000000.4100000212
16Ondrej RomanMonsters (Clb)LW336612140121747142212.77%62617.9200000000001228.57%1400000.9200000011
17Michal RepikMonsters (Clb)RW3724606020143311226.06%22937.9300003000000040.00%2000000.4100000000
18David DesharnaisMonsters (Clb)C3041512012212541516.00%22397.9700000000000250.60%25100010.4200000100
19Kelsey TessierMonsters (Clb)C21325-5205152181614.29%11577.5100000000011050.29%17100000.6300000000
20Dan SextonMonsters (Clb)RW14112-40072107910.00%11077.6900000000000044.44%900000.3700000000
21Petr VranaMonsters (Clb)LW18000-40062115120%21427.9300000000030062.50%80000000000000
22Matt BartkowskiMonsters (Clb)D5000140535220%611322.69000211000012000%00000000000000
Statistiques d’équipe totales ou en moyenne918181331512165338307728381585475103811.42%4231509116.44275077270129136910931311552.00%424800220.6822222302928
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
1Mason McDonaldMonsters (Clb)38201500.8873.222068621119860101.00023714322
2Jaroslav JanusMonsters (Clb)1912400.8972.7010010145437010001437100
Statistiques d’équipe totales ou en moyenne57321900.8903.05306963156142302025151422


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 Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Type Salaire actuel Plafond salarial Non Activé 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 10Non-échange Année 2Non-échange Année 3Non-échange Année 4Non-échange Année 5Non-échange Année 6Non-échange Année 7Non-échange Année 8Non-échange Année 9Non-échange Année 10Lien
Alexis BinnerMonsters (Clb)D251998-12-03No212 Lbs6 ft3NoNoN/ANoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------NoNo-------Lien
Andrew DesjardinsMonsters (Clb)C371986-07-27No196 Lbs6 ft0NoNoN/ANoNo3Pro & Farm1,100,000$0$0$No1,100,000$1,100,000$-------NoNo-------Lien
Brent MoranMonsters (Clb)G271996-07-05No195 Lbs6 ft4NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------
Dan SextonMonsters (Clb)RW361987-04-29No156 Lbs5 ft10NoNoN/ANoNo3Pro & Farm1,100,000$0$0$No1,100,000$1,100,000$-------NoNo-------Lien
Danick PaquetteMonsters (Clb)C331990-07-17No217 Lbs6 ft0NoNoN/ANoNo3Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------NoNo-------Lien
David DesharnaisMonsters (Clb)C371986-09-14No180 Lbs5 ft7NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Gage AusmusMonsters (Clb)D281995-04-22No215 Lbs6 ft1NoNoN/ANoNo1Pro & Farm700,000$0$0$No------------------Lien
Jack McbainMonsters (Clb)C232000-01-06Yes201 Lbs6 ft3NoNoN/ANoNo3Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------Lien
Jacob PetersonMonsters (Clb)LW241999-07-19No170 Lbs6 ft1NoNoN/ANoNo2Pro & Farm1,700,000$0$0$No1,700,000$--------No--------Lien
Jaroslav JanusMonsters (Clb)G341989-09-21No191 Lbs6 ft0NoNoN/ANoNo3Pro & Farm1,050,000$0$0$No1,050,000$1,050,000$-------NoNo-------Lien
Jordan SchroederMonsters (Clb)LW331990-09-29No174 Lbs5 ft8NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Joseph VelenoMonsters (Clb)C232000-01-13Yes203 Lbs6 ft1NoNoN/ANoNo3Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------Lien
Juuso ValimakiMonsters (Clb)D251998-10-06Yes205 Lbs6 ft2NoNoN/ANoNo3Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------Lien
Kelsey TessierMonsters (Clb)C331990-01-16No178 Lbs5 ft8NoNoN/ANoNo1Pro & Farm700,000$0$0$No------------------Lien
Linden VeyMonsters (Clb)RW321991-07-17No194 Lbs5 ft8NoNoN/ANoNo3Pro & Farm1,250,000$0$0$No1,250,000$1,250,000$-------NoNo-------Lien
Lucas JohansenMonsters (Clb)D261997-11-16No176 Lbs6 ft2NoNoN/ANoNo3Pro & Farm1,500,000$0$0$No1,500,000$1,500,000$-------NoNo-------Lien
Mason McDonaldMonsters (Clb)G271996-04-23No200 Lbs6 ft4NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Matt BartkowskiMonsters (Clb)D351988-06-04No192 Lbs6 ft1NoNoN/ANoNo2Pro & Farm1,250,000$0$0$No1,250,000$--------No--------Lien
Matt FrattinMonsters (Clb)RW351988-01-03No205 Lbs6 ft0NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Michal RepikMonsters (Clb)RW341988-12-31No191 Lbs5 ft10NoNoN/ANoNo3Pro & Farm1,100,000$0$0$No1,100,000$1,100,000$-------NoNo-------Lien
Ondrej RomanMonsters (Clb)LW341989-02-08No182 Lbs5 ft11NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Petr VranaMonsters (Clb)LW381985-03-29No182 Lbs5 ft9NoNoN/ANoNo1Pro & Farm700,000$0$0$No------------------Lien
Rushan RafikovMonsters (Clb)D281995-05-15No185 Lbs6 ft1NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Seth GriffithMonsters (Clb)RW301993-01-04No190 Lbs5 ft9NoNoN/ANoNo3Pro & Farm1,100,000$0$0$No1,100,000$1,100,000$-------NoNo-------Lien
Steven LorentzMonsters (Clb)LW271996-04-13No192 Lbs6 ft3NoNoN/ANoNo2Pro & Farm1,700,000$0$0$No1,700,000$--------No--------Lien
TJ BrennanMonsters (Clb)D341989-04-03No213 Lbs6 ft1NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Teemu PulkkinenMonsters (Clb)LW311992-01-02No187 Lbs5 ft10NoNoN/ANoNo3Pro & Farm1,100,000$0$0$No1,100,000$1,100,000$-------NoNo-------Lien
Tyler CumaMonsters (Clb)D331990-01-19 00:01:24No187 Lbs6 ft2NoNoN/ANoNo2Pro & Farm1,250,000$0$0$No1,250,000$--------No--------Lien
Victor MeteMonsters (Clb)D251998-06-07No187 Lbs5 ft9NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Vyacheslav LeshchenkoMonsters (Clb)RW281995-04-24No160 Lbs6 ft0NoNoN/ANoNo1Pro & Farm1,300,000$0$0$No------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3030.50191 Lbs6 ft02.131,030,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jacob PetersonJack McbainVyacheslav Leshchenko31014
2Teemu PulkkinenJoseph VelenoLinden Vey31014
3Steven LorentzAndrew DesjardinsSeth Griffith24032
4Ondrej RomanDavid DesharnaisMichal Repik14032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiVictor Mete36023
2Lucas JohansenTJ Brennan32032
3Rushan RafikovAlexis Binner32032
4Juuso ValimakiVictor Mete0032
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jacob PetersonJack McbainVyacheslav Leshchenko50005
2Steven LorentzJoseph VelenoLinden Vey50005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiVictor Mete50005
2Lucas JohansenAlexis Binner50014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Andrew DesjardinsJoseph Veleno50050
2Jack McbainTeemu Pulkkinen50050
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiVictor Mete50050
2Lucas JohansenRushan Rafikov50050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Joseph Veleno50050Juuso ValimakiVictor Mete50050
2Jack Mcbain50050Lucas JohansenRushan Rafikov50050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jack McbainVyacheslav Leshchenko50014
2Joseph VelenoJacob Peterson50014
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiVictor Mete50023
2Lucas JohansenTJ Brennan50032
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jacob PetersonJack McbainJoseph VelenoJuuso ValimakiVictor Mete
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jacob PetersonJack McbainJoseph VelenoJuuso ValimakiVictor Mete
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Teemu Pulkkinen, Andrew Desjardins, Seth GriffithTeemu Pulkkinen, Andrew DesjardinsSeth Griffith
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Rushan Rafikov, Alexis Binner, Lucas JohansenRushan RafikovAlexis Binner, Lucas Johansen
Tirs de pénalité
Vyacheslav Leshchenko, Jack Mcbain, Jacob Peterson, Joseph Veleno, Steven Lorentz
Gardien
#1 : Jaroslav Janus, #2 : Mason McDonald


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
1Barracuda311010001192110000005232010100067-140.667112233005964528108511525536157220124416318.75%5180.00%0941178652.69%834162251.42%43484051.67%12468621159369668336
2BruinsF22000000954220000009540000000000041.000915240059645287551152553615441416268225.00%7185.71%0941178652.69%834162251.42%43484051.67%12468621159369668336
3Canucks413000001215-3211000007702020000058-320.2501220320059645281245115255361511529416712325.00%17664.71%1941178652.69%834162251.42%43484051.67%12468621159369668336
4Checkers10000010541100000105410000000000021.000571200596452839511525536153374132150.00%20100.00%0941178652.69%834162251.42%43484051.67%12468621159369668336
5Comets11000000413110000004130000000000021.000471100596452836511525536151540224250.00%000%0941178652.69%834162251.42%43484051.67%12468621159369668336
6Condors32001000161061100000053221001000117461.000163147005964528126511525536156321224816318.75%11372.73%0941178652.69%834162251.42%43484051.67%12468621159369668336
7Crunch1010000012-1000000000001010000012-100.00012300596452818511525536153414611300.00%3166.67%1941178652.69%834162251.42%43484051.67%12468621159369668336
8Eagles3120000078-13120000078-10000000000020.33371421005964528935115255361586352048400.00%9277.78%0941178652.69%834162251.42%43484051.67%12468621159369668336
9Firebirds11000000532000000000001100000053221.00059140059645282351152553615143711200.00%10100.00%0941178652.69%834162251.42%43484051.67%12468621159369668336
10Griffins10001000321000000000001000100032121.000358005964528315115255361517104155120.00%2150.00%0941178652.69%834162251.42%43484051.67%12468621159369668336
11Gulls31200000990110000006242020000037-420.3339162500596452890511525536158928264410110.00%7357.14%0941178652.69%834162251.42%43484051.67%12468621159369668336
12Icehogs422000001315-22110000089-12110000056-140.500132336005964528109511525536151334128547114.29%14657.14%1941178652.69%834162251.42%43484051.67%12468621159369668336
13Iowa Wild431000001394220000006152110000078-160.750132538015964528105511525536151163330629111.11%14285.71%0941178652.69%834162251.42%43484051.67%12468621159369668336
14Islanders10001000541100010005410000000000021.0005101500596452829511525536153013615200.00%3166.67%0941178652.69%834162251.42%43484051.67%12468621159369668336
15Marlies11000000523000000000001100000052321.000510150059645283051152553615232816300.00%40100.00%0941178652.69%834162251.42%43484051.67%12468621159369668336
16Reign4310000016972110000065122000000104660.750163147015964528107511525536151133217666116.67%6266.67%0941178652.69%834162251.42%43484051.67%12468621159369668336
17Roadrunners3200100011740000000000032001000117461.00011193000596452894511525536158524254713215.38%7185.71%0941178652.69%834162251.42%43484051.67%12468621159369668336
18Rocket11000000541000000000001100000054121.0005914005964528335115255361534102156233.33%000%0941178652.69%834162251.42%43484051.67%12468621159369668336
19SenatorsF11000000541110000005410000000000021.000591400596452834511525536152884213133.33%20100.00%0941178652.69%834162251.42%43484051.67%12468621159369668336
20Silver Knights1010000016-5000000000001010000016-500.0001120059645283151152553615325618300.00%3233.33%0941178652.69%834162251.42%43484051.67%12468621159369668336
21StarsF1010000023-11010000023-10000000000000.0002350059645282751152553615258418200.00%20100.00%0941178652.69%834162251.42%43484051.67%12468621159369668336
22Thunderbirds312000001214-220200000712-51100000052320.333122133005964528965115255361510929243012325.00%11372.73%0941178652.69%834162251.42%43484051.67%12468621159369668336
23Wolves11000000303000000000001100000030321.0003580159645283351152553615237418100.00%10100.00%0941178652.69%834162251.42%43484051.67%12468621159369668336
24Wranglers30201000911-2100010004312020000058-320.33391726005964528945115255361590262843600.00%13284.62%0941178652.69%834162251.42%43484051.67%12468621159369668336
Total512519060101821562624138020109173182712110400091838640.62718233151303596452815855115255361514234233447721552717.42%1443774.31%3941178652.69%834162251.42%43484051.67%12468621159369668336
_Since Last GM Reset512519060101821562624138020109173182712110400091838640.62718233151303596452815855115255361514234233447721552717.42%1443774.31%3941178652.69%834162251.42%43484051.67%12468621159369668336
_Vs Conference40171805000135127818980100063558228100400072720440.55013524838302596452812355115255361511453412876041211915.70%1213471.90%2941178652.69%834162251.42%43484051.67%12468621159369668336
_Vs Division183401000585621013000003033-3821010002823580.222581051630159645285245115255361555417013125947714.89%571475.44%1941178652.69%834162251.42%43484051.67%12468621159369668336

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
5164W11823315131585142342334477203
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
5125196010182156
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2413820109173
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
27121140009183
Derniers 10 matchs
WLOTWOTL SOWSOL
370000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1552717.42%1443774.31%3
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
511525536155964528
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
941178652.69%834162251.42%43484051.67%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
12468621159369668336


Derniers matchs joués
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe visiteuse Score Équipe locale Score ST OT SO RI Lien
1 - 2023-08-252Eagles4Monsters2BLSommaire du match
2 - 2023-08-2611Monsters5Thunderbirds2AWSommaire du match
5 - 2023-08-2936Monsters4Condors3AWXSommaire du match
7 - 2023-08-3149Monsters2Wranglers4ALSommaire du match
8 - 2023-09-0161Eagles2Monsters1BLSommaire du match
11 - 2023-09-0481Wranglers3Monsters4BWXSommaire du match
13 - 2023-09-06100Canucks2Monsters4BWSommaire du match
15 - 2023-09-08112Monsters1Icehogs4ALSommaire du match
17 - 2023-09-10129Monsters3Barracuda2AWXSommaire du match
18 - 2023-09-11134Monsters4Roadrunners3AWSommaire du match
21 - 2023-09-14158Iowa Wild0Monsters4BWSommaire du match
23 - 2023-09-16176Monsters1Silver Knights6ALSommaire du match
24 - 2023-09-17186Condors3Monsters5BWSommaire du match
27 - 2023-09-20201Monsters0Gulls2ALSommaire du match
30 - 2023-09-23223BruinsF3Monsters5BWSommaire du match
32 - 2023-09-25240Monsters3Iowa Wild6ALSommaire du match
34 - 2023-09-27250Reign0Monsters3BWSommaire du match
36 - 2023-09-29268Monsters3Wranglers4ALSommaire du match
38 - 2023-10-01283SenatorsF4Monsters5BWSommaire du match
41 - 2023-10-04302Monsters5Reign3AWSommaire du match
43 - 2023-10-06315Icehogs4Monsters5BWSommaire du match
45 - 2023-10-08331Monsters4Iowa Wild2AWSommaire du match
47 - 2023-10-10347Eagles2Monsters4BWSommaire du match
49 - 2023-10-12367Monsters5Marlies2AWSommaire du match
51 - 2023-10-14379Islanders4Monsters5BWXSommaire du match
53 - 2023-10-16393Monsters7Condors4AWSommaire du match
54 - 2023-10-17402Monsters4Icehogs2AWSommaire du match
56 - 2023-10-19414StarsF3Monsters2BLSommaire du match
59 - 2023-10-22441Checkers4Monsters5BWXXSommaire du match
62 - 2023-10-25462Monsters3Wolves0AWSommaire du match
64 - 2023-10-27475Thunderbirds7Monsters3BLSommaire du match
66 - 2023-10-29486Monsters5Reign1AWSommaire du match
68 - 2023-10-31500Monsters3Roadrunners2AWXSommaire du match
70 - 2023-11-02509Monsters3Griffins2AWXSommaire du match
71 - 2023-11-03515Comets1Monsters4BWSommaire du match
74 - 2023-11-06534Monsters4Canucks5ALSommaire du match
75 - 2023-11-07544Gulls2Monsters6BWSommaire du match
79 - 2023-11-11572Iowa Wild1Monsters2BWSommaire du match
81 - 2023-11-13589Monsters4Roadrunners2AWSommaire du match
82 - 2023-11-14599Monsters5Rocket4AWSommaire du match
84 - 2023-11-16610Canucks5Monsters3BLSommaire du match
87 - 2023-11-19636Barracuda2Monsters5BWSommaire du match
91 - 2023-11-23662Thunderbirds5Monsters4BLSommaire du match
93 - 2023-11-25682Monsters1Crunch2ALSommaire du match
94 - 2023-11-26692Monsters1Canucks3ALSommaire du match
96 - 2023-11-28704BruinsF2Monsters4BWSommaire du match
99 - 2023-12-01726Icehogs5Monsters3BLSommaire du match
101 - 2023-12-03739Monsters3Barracuda5ALSommaire du match
102 - 2023-12-04752Monsters3Gulls5ALSommaire du match
104 - 2023-12-06767Reign5Monsters3BLSommaire du match
107 - 2023-12-09789Monsters5Firebirds3AWSommaire du match
109 - 2023-12-11797Gulls-Monsters-
111 - 2023-12-13818Monsters-Griffins-
113 - 2023-12-15830Condors-Monsters-
115 - 2023-12-17853Wolf Pack-Monsters-
117 - 2023-12-19864Monsters-Silver Knights-
121 - 2023-12-23887Americans-Monsters-
123 - 2023-12-25908Monsters-Moose-
125 - 2023-12-27920Monsters-Bears-
126 - 2023-12-28926Wranglers-Monsters-
129 - 2023-12-31951Monsters-Admirals-
130 - 2024-01-01957Griffins-Monsters-
134 - 2024-01-05986PenguinsF-Monsters-
135 - 2024-01-06997Monsters-SenatorsF-
138 - 2024-01-091016Barracuda-Monsters-
141 - 2024-01-121037StarsF-Monsters-
144 - 2024-01-151059Monsters-StarsF-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
146 - 2024-01-171076Bears-Monsters-
149 - 2024-01-201091Monsters-StarsF-
150 - 2024-01-211102Monsters-Phantoms-
152 - 2024-01-231113Roadrunners-Monsters-
155 - 2024-01-261136Admirals-Monsters-
157 - 2024-01-281149Monsters-Eagles-
159 - 2024-01-301156Monsters-Thunderbirds-
161 - 2024-02-011176Monsters-Admirals-
162 - 2024-02-021182Admirals-Monsters-
164 - 2024-02-041202Monsters-Eagles-
166 - 2024-02-061213Griffins-Monsters-
167 - 2024-02-071218Monsters-Thunderbirds-
171 - 2024-02-111247Roadrunners-Monsters-
176 - 2024-02-161275Silver Knights-Monsters-
181 - 2024-02-211311Silver Knights-Monsters-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4020
Assistance32,94815,730
Assistance PCT68.64%65.54%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
17 2028 - 67.61% 98,631$2,367,154$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,772,504$ 3,090,000$ 3,090,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,713,730$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,676,734$ 75 17,527$ 1,314,525$




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