Version obsolète du STHS! Veuillez mettre à jour votre version!
Connexion

Monsters
GP: 18 | W: 7 | L: 10 | OTL: 1 | P: 15
GF: 78 | GA: 71 | PP%: 13.33% | PK%: 74.14%
DG: Tyler Bell | Morale : 50 | Moyenne d’équipe : 58
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Centre de jeu
Thunderbirds
2-16-0, 4pts
0
FINAL
12 Monsters
7-10-1, 15pts
Team Stats
L6StreakL1
2-7-0Home Record4-5-0
0-9-0Away Record3-5-1
2-8-0Last 10 Games2-7-1
1.78Buts par match 4.33
7.28Buts contre par match 3.94
9.62%Pourcentage en avantage numérique13.33%
76.00%Pourcentage en désavantage numérique74.14%
Monsters
7-10-1, 15pts
6
FINAL
9 Penguins
4-13-1, 9pts
Team Stats
L1StreakW3
4-5-0Home Record3-5-1
3-5-1Away Record1-8-0
2-7-1Last 10 Games4-6-0
4.33Buts par match 3.33
3.94Buts contre par match 5.72
13.33%Pourcentage en avantage numérique18.46%
74.14%Pourcentage en désavantage numérique75.00%
Meneurs d'équipe
Buts
Samuel Walker
14
Passes
Lukas Reichel
22
Points
Lukas Reichel
35
Plus/Moins
Lukas Reichel
28
Victoires
Dylan Garand
6
Pourcentage d’arrêts
Dylan Garand
0.89

Statistiques d’équipe
Buts pour
78
4.33 GFG
Tirs pour
546
30.33 Avg
Pourcentage en avantage numérique
13.3%
8 GF
Début de zone offensive
35.1%
Buts contre
71
3.94 GAA
Tirs contre
565
31.39 Avg
Pourcentage en désavantage numérique
74.1%%
15 GA
Début de la zone défensive
39.9%
Informations de l'équipe

Directeur généralTyler Bell
EntraîneurKen Hitchcock
DivisionNorth
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison1,200


Informations de la formation

Équipe Pro23
Équipe Mineure20
Limite contact 43 / 50
Espoirs50


Historique d'équipe

Saison actuelle7-10-1 (15PTS)
Historique48-17-7 (0.667%)
Apparitions en séries éliminatoires 1
Historique en séries éliminatoires (W-L)1-4
Coupe Stanley0


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
1Lukas ReichelXX100.0063419378626792755063586625565666506502211,337,500$
2Zachary SanfordX100.0071439277785777665366556725676964506403011,000,000$
3Raphael LavoieXX100.0074757368757882648057686465444467506302411,500,000$
4Marat Khusnutdinov (R)X100.007543886864645266696557762545456550620223925,000$
5Mackie Samoskevich (R)X100.007367876667707165506364646144446650620213925,000$
6Samuel WalkerXX100.007366896666808562506158635545456450620252855,000$
7Jack Finley (R)X100.008282836382737662785960685744446550620222797,500$
8Cedric PareX100.007880746680676961765958655544446350610251750,000$
9John Farinacci (R)X100.007669915969687160755857645444446250590233925,000$
10William LockwoodX100.008691826965516064455455692547476150590261842,500$
11Aidan McDonoughX100.008175956375626554504757655444446150580243925,000$
12Jared Davidson (R)X100.007067776367585955694660605744445950560223775,000$
13Mark FriedmanX100.007974757369595861254347682555565850620282800,000$
14Adam WilsbyX100.007467896567758250253946614444445650590242842,500$
15Cole McWard (R)X100.008075906875616548254041633944445350590232925,000$
16Santtu KinnunenX100.006860886560778450254341583944445450580252855,000$
17Seth Barton (R)X100.007470846770495145253441593944445150550251832,500$
Rayé
1Kale HowarthXX100.007978816578545746584344624244445250540271750,000$
2Brendan WarrenXX100.007270776370565850634054605144445650540271750,000$
3Danila Klimovich (R)X100.007675776475596348504446614444445350540211925,000$
4Luka Burzan (R)XX100.007767996467414049614547624544445450530241750,000$
5Lukas SvejkovskyX100.006860876060535549614548574644445350520222859,167$
MOYENNE D’ÉQUIPE100.00756885667063675753515364444646595059
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
1Dustin Tokarski100.00495265744748505448483044445050520351800,000$
Rayé
MOYENNE D’ÉQUIPE100.0049526574474850544848304444505052
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ken Hitchcock94647263999782CAN65110$


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
1Lukas ReichelMonsters (CLB)C/LW181322352820133570225318.57%1334719.291127280223500061.34%11900032.0200000302
2Samuel WalkerMonsters (CLB)LW/RW181414281820151773224419.18%722412.4900000000002050.00%1000012.4900000203
3Raphael LavoieMonsters (CLB)C/RW1813152825200422085236415.29%629616.451127280000231064.10%3900011.8900000223
4William LockwoodMonsters (CLB)RW1812142619275412970234717.14%1422212.3800000000000033.33%600022.3300001210
5Kent JohnsonBlue JacketsC/LW1381523170093546203317.39%423418.040227222023420054.77%24100001.9600000032
6Santtu KinnunenMonsters (CLB)D1819109601910104810.00%1526314.640114500004100.00%000000.7600000000
7Adam WilsbyMonsters (CLB)D1834792204081361423.08%926214.561013500003000.00%000000.5300000010
8Cedric PareMonsters (CLB)C182021404350340.00%1160.9300000000001070.59%1700002.3900000000
Statistiques d’équipe totales ou en moyenne139669315912683518315737212026617.74%69186713.44358289022461245057.64%43200071.70000019710
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
1Dylan GarandBlue Jackets136700.8903.2171000383440000.00%01313110
Statistiques d’équipe totales ou en moyenne136700.8903.21710003834400001313110


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 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 WilsbyMonsters (CLB)D242000-07-08No183 Lbs6 ft0NoNoNo2Pro & Farm842,500$842,500$0$0$No842,500$Lien
Aidan McDonoughMonsters (CLB)LW241999-11-06No201 Lbs6 ft2NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$Lien
Brendan WarrenMonsters (CLB)C/LW271997-05-07No192 Lbs6 ft0NoNoNo1Pro & Farm750,000$750,000$0$0$NoLien
Cedric PareMonsters (CLB)C251999-01-24No212 Lbs6 ft4NoNoNo1Pro & Farm750,000$750,000$0$0$NoLien
Cole McWardMonsters (CLB)D232001-06-09Yes205 Lbs6 ft1NoNoNo2Pro & Farm925,000$925,000$0$0$No925,000$Lien
Danila KlimovichMonsters (CLB)RW212003-01-09Yes202 Lbs6 ft2NoNoNo1Pro & Farm925,000$925,000$0$0$NoLien
Dustin TokarskiMonsters (CLB)G351989-09-15No205 Lbs6 ft0NoNoNo1Pro & Farm800,000$800,000$0$0$NoLien / Lien NHL
Jack FinleyMonsters (CLB)C222002-02-09Yes213 Lbs6 ft6NoNoNo2Pro & Farm797,500$797,500$0$0$No797,500$Lien
Jared DavidsonMonsters (CLB)C222002-07-07Yes184 Lbs6 ft0NoNoNo3Pro & Farm775,000$775,000$0$0$No775,000$775,000$Lien
John FarinacciMonsters (CLB)C232001-02-14Yes190 Lbs5 ft11NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$Lien
Kale HowarthMonsters (CLB)C/LW271997-06-10No201 Lbs6 ft5NoNoNo1Pro & Farm750,000$750,000$0$0$NoLien
Luka BurzanMonsters (CLB)C/RW242000-01-07Yes183 Lbs6 ft0NoNoNo1Pro & Farm750,000$750,000$0$0$NoLien
Lukas ReichelMonsters (CLB)C/LW222002-05-17No169 Lbs6 ft0NoNoNo1Pro & Farm1,337,500$1,337,500$0$0$NoLien
Lukas SvejkovskyMonsters (CLB)C222001-11-28No165 Lbs5 ft10NoNoNo2Pro & Farm859,167$859,167$0$0$No859,167$Lien
Mackie SamoskevichMonsters (CLB)RW212002-11-15Yes189 Lbs5 ft11NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$Lien
Marat KhusnutdinovMonsters (CLB)C222002-07-17Yes176 Lbs5 ft11NoNoNo3Pro & Farm925,000$925,000$0$0$No925,000$925,000$Lien
Mark FriedmanMonsters (CLB)D281995-12-25No185 Lbs5 ft11NoNoNo2Pro & Farm800,000$800,000$0$0$No800,000$Lien / Lien NHL
Raphael LavoieMonsters (CLB)C/RW242000-09-25No196 Lbs6 ft4NoNoNo1Pro & Farm1,500,000$1,500,000$0$0$NoLien
Samuel WalkerMonsters (CLB)LW/RW251999-07-06No180 Lbs5 ft11NoNoNo2Pro & Farm855,000$855,000$0$0$No855,000$Lien
Santtu KinnunenMonsters (CLB)D251999-03-25No154 Lbs6 ft2NoNoNo2Pro & Farm855,000$855,000$0$0$No855,000$Lien
Seth BartonMonsters (CLB)D251999-08-18Yes185 Lbs6 ft2NoNoNo1Pro & Farm832,500$832,500$0$0$NoLien
William LockwoodMonsters (CLB)RW261998-06-20No172 Lbs5 ft11NoNoNo1Pro & Farm842,500$842,500$0$0$NoLien
Zachary SanfordMonsters (CLB)RW301994-09-11No207 Lbs6 ft4NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2324.65189 Lbs6 ft11.74897,681$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Lukas ReichelRaphael Lavoie40122
230122
3Samuel WalkerWilliam Lockwood20122
4Cedric PareLukas Reichel10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
140122
2Santtu KinnunenAdam Wilsby30122
320122
410122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Lukas ReichelRaphael Lavoie60122
240122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Santtu KinnunenAdam Wilsby40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Lukas Reichel60122
2Raphael Lavoie40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Santtu KinnunenAdam Wilsby40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Lukas Reichel6012260122
240122Santtu KinnunenAdam Wilsby40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Lukas Reichel60122
2Raphael Lavoie40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
160122
2Santtu KinnunenAdam Wilsby40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Lukas ReichelRaphael Lavoie
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Lukas ReichelRaphael Lavoie
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, Samuel Walker, , Samuel Walker
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
, Santtu Kinnunen, Adam WilsbySanttu Kinnunen, Adam Wilsby
Tirs de pénalité
Lukas Reichel, , Raphael Lavoie, ,
Gardien
#1 : , #2 :
Lignes d’attaque personnalisées en prolongation
Lukas Reichel, , Raphael Lavoie, , , , , Samuel Walker, , , William Lockwood
Lignes de défense personnalisées en prolongation
, , Santtu Kinnunen, Adam Wilsby,


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
1Bears21100000510-51010000017-61100000043120.5005712003226200461931471941285322751800.00%4175.00%018841545.30%17747237.50%12429641.89%43032546111219391
2Bruins20200000610-41010000045-11010000025-300.000610160032262005519314719412612210304125.00%4175.00%018841545.30%17747237.50%12429641.89%43032546111219391
3Checkers2020000036-31010000012-11010000024-200.000358003226200311931471941269152338800.00%8187.50%018841545.30%17747237.50%12429641.89%43032546111219391
4Islanders220000001721511000000131121100000041341.0001731480032262001071931471941241158623266.67%30100.00%018841545.30%17747237.50%12429641.89%43032546111219391
5Penguins2110000012120110000006331010000069-320.50012223400322620073193147194125614102911327.27%5340.00%018841545.30%17747237.50%12429641.89%43032546111219391
6Phantoms211000001376110000009181010000046-220.5001321340032262005619314719412822024315240.00%12283.33%218841545.30%17747237.50%12429641.89%43032546111219391
7Senators1000010056-1000000000001000010056-110.5005611003226200531931471941244171031000.00%5260.00%018841545.30%17747237.50%12429641.89%43032546111219391
8Thunderbirds110000001201211000000120120000000000021.0001219310132262007119314719412186428200.00%20100.00%018841545.30%17747237.50%12429641.89%43032546111219391
9Wolf Pack2110000036-31010000015-41100000021120.5003470032262002419314719412481516221100.00%7271.43%018841545.30%17747237.50%12429641.89%43032546111219391
10Wolves20200000212-101010000018-71010000014-300.00022400322620030193147194126191626800.00%8362.50%018841545.30%17747237.50%12429641.89%43032546111219391
Total18710001007871794500000483216935001003039-9150.417781272050132262005461931471941256516514834860813.33%581574.14%218841545.30%17747237.50%12429641.89%43032546111219391
_Since Last GM Reset18710001007871794500000483216935001003039-9150.417781272050132262005461931471941256516514834860813.33%581574.14%218841545.30%17747237.50%12429641.89%43032546111219391
_Vs Conference17610001006671-58350000036324935001003039-9130.382661081740032262004751931471941254715914432058813.79%561573.21%218841545.30%17747237.50%12429641.89%43032546111219391
_Vs Division500001001422-82000000057-230000100915-610.100142135003226200139193147194121745443991218.33%17476.47%018841545.30%17747237.50%12429641.89%43032546111219391

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1815L17812720554656516514834801
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
1871001007871
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
94500004832
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
93501003039
Derniers 10 matchs
WLOTWOTL SOWSOL
270100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
60813.33%581574.14%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
193147194123226200
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
18841545.30%17747237.50%12429641.89%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
43032546111219391


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 - 2024-09-239Islanders1Monsters13BWSommaire du match
3 - 2024-09-2529Monsters2Checkers4ALSommaire du match
4 - 2024-09-2636Phantoms1Monsters9BWSommaire du match
6 - 2024-09-2864Monsters4Bears3AWSommaire du match
7 - 2024-09-2976Bruins5Monsters4BLSommaire du match
9 - 2024-10-0197Monsters4Islanders1AWSommaire du match
10 - 2024-10-02109Penguins3Monsters6BWSommaire du match
11 - 2024-10-03128Monsters4Phantoms6ALSommaire du match
12 - 2024-10-04145Wolves8Monsters1BLSommaire du match
13 - 2024-10-05156Monsters1Wolves4ALSommaire du match
14 - 2024-10-06174Checkers2Monsters1BLSommaire du match
16 - 2024-10-08193Wolf Pack5Monsters1BLSommaire du match
18 - 2024-10-10217Monsters2Wolf Pack1AWSommaire du match
19 - 2024-10-11229Bears7Monsters1BLSommaire du match
20 - 2024-10-12244Monsters5Senators6ALXSommaire du match
22 - 2024-10-14254Monsters2Bruins5ALSommaire du match
23 - 2024-10-15266Thunderbirds0Monsters12BWSommaire du match
24 - 2024-10-16279Monsters6Penguins9ALSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets1000
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,064,667$ 2,044,667$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 1 0$ 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
1Jacob Lucchini72447311751328614531314.06%41136318.931522379200016140.9131.7211
2Samuel Walker72446310752425210827615.94%20130718.16722296900017356.5811.6401
3Jake Neighbours724459103506413111427615.94%21141919.7112102262000010351.2421.4513
4Raphael Lavoie705148996010215217625020.40%10147121.0114122638202183266.8851.3503
5Zac Dalpe7237549138458717923215.95%50152021.11914235710167367.1401.2013

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
1Dustin Tokarski72471770.8742.5541660817714020600.50010
2Dylan Garand71000.9142.31182007810000.00%0

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
Saison régulière
2023724217055123281861423623702211162847836191003301166102641033285708980813193989214465770976425148343278912053757219.20%3315483.69%11342206065.15%1033174759.13%706115461.18%198414941565457801417
Total Saison régulière724217055123281861423623702211162847836191003301166102641033285708980813193989214465770976425148343278912053757219.20%3315483.69%11342206065.15%1033174759.13%706115461.18%198414941565457801417
Séries éliminatoires
2021514000001426-122020000068-231200000818-10214233700553188292829217343529520525.00%251060.00%0308634.88%5214436.11%317740.26%9365155355625
Total Séries éliminatoires514000001426-122020000068-231200000818-10214233700553188292829217343529520525.00%251060.00%0308634.88%5214436.11%317740.26%9365155355625

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
1Brent Pedersen5448-221392020.00%18416.871344000010100.0001.9000
2Greg McKegg425712315450.00%37218.16213200000157.5801.9300
3Mason Geertsen5257-210138728.57%118416.8912330000000.00%01.6600
4T.J. Tynan51230017911.11%210320.73011100010048.6800.5800
5Phillip Di Giuseppe512308816425.00%29920.00101100010033.3300.6000

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
1Jeff Glass51310.8624.7425300201450100.00%0