Veuillez faire pivoter votre appareil en mode paysage pour une meilleure expérience.
Connexion

Monsters
GP: 12 | W: 2 | L: 9 | OTL: 1 | P: 5
GF: 28 | GA: 42 | PP%: 16.67% | PK%: 84.48%
DG: Alain Desnoyers | Morale : 70 | Moyenne d’équipe : 64
Prochains matchs #201 vs Comets

Centre de jeu
Wolf Pack
6-4-2, 14pts
4
3 Monsters
2-9-1, 5pts
Team Stats
L1SéquenceL3
4-1-0Fiche domicile1-4-1
2-3-2Fiche domicile1-5-0
5-3-2Derniers 10 matchs2-7-1
3.33Buts par match 2.33
2.75Buts contre par match 3.50
23.19%Pourcentage en avantage numérique16.67%
78.72%Pourcentage en désavantage numérique84.48%
Monsters
2-9-1, 5pts
1
3 Senators
8-3-1, 17pts
Team Stats
L3SéquenceW1
1-4-1Fiche domicile4-1-1
1-5-0Fiche domicile4-2-0
2-7-1Derniers 10 matchs7-2-1
2.33Buts par match 3.00
3.50Buts contre par match 2.75
16.67%Pourcentage en avantage numérique20.93%
84.48%Pourcentage en désavantage numérique84.00%
Comets
2-9-1, 5pts
Jour 29
Monsters
2-9-1, 5pts
Statistiques d’équipe
L2SéquenceL3
1-5-0Fiche domicile1-4-1
1-4-1Fiche visiteur1-5-0
1-8-110 derniers matchs2-7-1
2.17Buts par match 2.33
3.50Buts contre par match 2.33
23.91%Pourcentage en avantage numérique16.67%
76.56%Pourcentage en désavantage numérique84.48%
Thunderbirds
7-5-0, 14pts
Jour 33
Monsters
2-9-1, 5pts
Statistiques d’équipe
W1SéquenceL3
4-2-0Fiche domicile1-4-1
3-3-0Fiche visiteur1-5-0
6-4-010 derniers matchs2-7-1
3.17Buts par match 2.33
3.08Buts contre par match 2.33
18.00%Pourcentage en avantage numérique16.67%
87.50%Pourcentage en désavantage numérique84.48%
Firebird
5-6-0, 10pts
Jour 37
Monsters
2-9-1, 5pts
Statistiques d’équipe
L3SéquenceL3
3-3-0Fiche domicile1-4-1
2-3-0Fiche visiteur1-5-0
4-6-010 derniers matchs2-7-1
2.82Buts par match 2.33
2.82Buts contre par match 2.33
24.00%Pourcentage en avantage numérique16.67%
78.38%Pourcentage en désavantage numérique84.48%
Meneurs d'équipe
Buts
Jonny Brodzinski
4
Passes
Jonny Brodzinski
7
Points
Jonny Brodzinski
11
Plus/Moins
Josh Jacobs
5
Victoires
Al Desnoyers
2
Pourcentage d’arrêts
Al Desnoyers
0.888

Statistiques d’équipe
Buts pour
28
2.33 GFG
Tirs pour
272
22.67 Avg
Pourcentage en avantage numérique
16.7%
6 GF
Début de zone offensive
34.7%
Buts contre
42
3.50 GAA
Tirs contre
356
29.67 Avg
Pourcentage en désavantage numérique
84.5%%
9 GA
Début de la zone défensive
45.6%
Informations de l'équipe

Directeur généralAlain Desnoyers
EntraîneurJared Bednar
DivisionNorth
ConférenceConference Est
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,497
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure20
Limite Contrat47 / 99
Espoirs40


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
1Mason Appleton0XXX97.0072389572787179644771697825747567706903022,151,000$
2Logan Morrison0XX99.008374927072817067796465815766665970680241900,000$
3Ben Meyers0XX99.0078738266737881688163676763565765706602722,150,000$
4Matt Luff0XX99.0036189965775476685965716262787839706502921,215,000$
5Riley Thompson (R)0XX99.006848676469677363457262705655587370640242900,000$
6Ryan Schmelzer0XX100.0067388166748187597060595763768169706403321,449,000$
7Karson Kuhlman0XX100.0038149965745175634267736155686850706303123,195,075$
8Kai Uchacz0XX100.007876796278717259715858645659596670610232900,000$
9Dalton Smith0XX100.0061498160797775545053525559938646706003411,112,000$
10Carson Golder0XX100.007972936374606854495750645164635270590233975,000$
11Jon Martin0XX100.0071386856827678515652505753777927705903121,001,000$
12Tyler Spezia0XX100.0048288868716572555351565558938618705903311,054,000$
13Spencer Stastney0X99.0053369768728381682570738165646472706902622,057,000$
14Tucker Poolman0X99.0079488260817767632565577438787647706803322,150,000$
15Philip Kemp0X100.0079788160797480573061586560727045706502732,199,999$
16Topias Vilen0X100.007873896575678157256351635661616770640232900,000$
17Austin Strand41X100.0052189959816685463046436146807946706102921,192,000$
18Josh Jacobs0X100.007773906079618046254544605061614570590302975,000$
Rayé
1Jonny Brodzinski0XXX100.0050647658785566788672817965787822706903323,195,075$
2Justin Vaive0X100.005133716480307950565051575982821370570371866,000$
3Jett Jones0X100.007571995881517056634646655064635070570243615,000$
4Viliam Kmec (R)0X100.006743796568818458456553735164667270660222900,000$
5Blake Hillman0X100.004317996674699044304342564685834870600302975,000$
6Lleyton Moore0X100.006355886669586748304747635063615870590241975,000$
MOYENNE D’ÉQUIPE99.63644986647667775849595765547171517063
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
1Al Desnoyers099.0068717184737979797872726363927074N2211900,000$
2Ryan Fanti0100.006873687871727473727271707941707202741,875,000$
Rayé
1Vinnie Purpura0100.0069696895687070706969686362687070N0272850,000$
MOYENNE D’ÉQUIPE99.6768716986717474747371706568677072
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jared Bednar74819084868163CAN542500,000$


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
1Jonny BrodzinskiMonsters (CBJ)C/LW/RW947112003192892214.29%218620.761344180000331160.40%10100001.1800000021
2Kevin StenlundBlue JacketsC/RW9459260151116101825.00%217719.750003190002241070.37%2700001.0100000100
3Ben MeyersMonsters (CBJ)C/LW12437-8120151325122016.00%221017.550222310001160057.69%2600000.6600000000
4Viliam KmecMonsters (CBJ)D9167-3160231163316.67%1120022.25022423000123000%000000.7000000001
5Mason AppletonMonsters (CBJ)C/LW/RW9246-1001636253208.00%420122.380114200002430041.20%28400000.6000000100
6Spencer StastneyMonsters (CBJ)D12145-840321188125.56%1929224.34101733000146000%000000.3400000000
7Karson KuhlmanMonsters (CBJ)C/RW123251000161841916.67%214512.1200010000000043.75%4800000.6900000000
8Dalton SmithMonsters (CBJ)LW/RW121341406411219.09%015012.5400010000030045.45%1100000.5300000010
9Logan MorrisonMonsters (CBJ)C/RW12224-1140223020102410.00%623019.212025320000380053.19%18800000.3500000000
10Kai UchaczMonsters (CBJ)C/RW12134180231612698.33%012610.51000000000190051.11%9000000.6300000001
11Matt LuffMonsters (CBJ)LW/RW12044-7001101710130%319816.57011232000070050.00%1200000.4000000000
12Riley ThompsonMonsters (CBJ)C/LW12224-3602219292166.90%116113.42000212000000032.73%16500000.5000000000
13Tucker PoolmanMonsters (CBJ)D6112-518015351420.00%813522.56112416000016000%000000.3000000000
14Philip KempMonsters (CBJ)D12112-810030213257.69%1624320.26101828000040000%000000.1600000000
15Ryan SchmelzerMonsters (CBJ)C/RW6112-3006571714.29%110217.13011017000000040.00%1000000.3900000010
16Topias VilenMonsters (CBJ)D12011-8100897440%1421918.26000422000138000%000000.0900000000
17Josh JacobsMonsters (CBJ)D1201151601841020%716513.7800000000021000%000000.1200000000
18Austin StrandMonsters (CBJ)D12011300121110%716113.470000100003000%000000.1200000000
19Lleyton MooreMonsters (CBJ)D3000000000000%010.430000000000000%00000000000000
20Carson GolderMonsters (CBJ)LW/RW12000-300277470%1826.9000000000000033.33%30000000000000
21Blake HillmanMonsters (CBJ)D3000100000000%1206.710000000000000%00000000000000
22Jon MartinMonsters (CBJ)C/RW12000-200466130%0806.7200000000000045.45%220000000000000
23Tyler SpeziaMonsters (CBJ)C/LW3000-100000100%051.990000100000000%10000000000000
Statistiques d’équipe totales ou en moyenne225285179-5511402332442729421010.29%107349915.55611175131600083792146.46%98800000.4500000243
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
1Al DesnoyersMonsters (CBJ)112810.8883.36660603732900200110001
2Ryan FantiMonsters (CBJ)10100.8803.00600032500000111000
Statistiques d’équipe totales ou en moyenne122910.8873.33720604035400201211001


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer UFA Rappel d'urgence Type Salaire actuel Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 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
Al DesnoyersMonsters (CBJ)G212005-06-30CANNo227 Lbs6 ft5YesNoFree AgentNoNo12024-11-30FalseFalsePro & Farm900,000$0$0$No---------------------------
Austin StrandMonsters (CBJ)D291997-02-17CANNo228 Lbs6 ft4NoNoFree AgentNoNo22025-05-25FalseFalsePro & Farm1,192,000$0$0$No1,192,000$--------1,192,000$--------No--------
Ben MeyersMonsters (CBJ)C/LW271998-11-15USANo203 Lbs5 ft11NoNoFree AgentNoNo22024-07-15FalseFalsePro & Farm2,150,000$0$0$No2,150,000$--------2,150,000$--------No--------
Blake HillmanMonsters (CBJ)D301996-01-26USANo199 Lbs6 ft1NoNoFree AgentNoNo22024-07-30FalseFalsePro & Farm975,000$0$0$No975,000$--------975,000$--------No--------
Carson GolderMonsters (CBJ)LW/RW232002-10-29CANNo200 Lbs6 ft0NoNoFree AgentNoNo32024-07-30FalseFalsePro & Farm975,000$0$0$No975,000$975,000$-------975,000$975,000$-------NoNo-------
Dalton SmithMonsters (CBJ)LW/RW341992-06-30CANNo217 Lbs6 ft2NoNoFree AgentNoNo12025-05-25FalseFalsePro & Farm1,112,000$0$0$No---------------------------
Jett JonesMonsters (CBJ)C242002-08-27CANNo228 Lbs6 ft3NoNoFree AgentNoNo32025-02-12FalseFalsePro & Farm615,000$0$0$No615,000$615,000$-------615,000$615,000$-------NoNo-------
Jon MartinMonsters (CBJ)C/RW311995-08-23CANNo235 Lbs6 ft2NoNoFree AgentNoNo22025-05-25FalseFalsePro & Farm1,001,000$0$0$No1,001,000$--------1,001,000$--------No--------
Jonny BrodzinskiMonsters (CBJ)C/LW/RW331993-06-19USANo218 Lbs6 ft0NoNoTrade2025-10-29NoNo22024-07-10FalseFalsePro & Farm3,195,075$0$0$No3,195,075$--------3,195,075$--------No--------
Josh JacobsMonsters (CBJ)D301996-02-15USANo220 Lbs6 ft2NoNoFree AgentNoNo22024-07-30FalseFalsePro & Farm975,000$0$0$No975,000$--------975,000$--------No--------
Justin VaiveMonsters (CBJ)LW371989-07-08USANo217 Lbs6 ft6NoNoFree AgentNoNo12025-05-25FalseFalsePro & Farm866,000$0$0$No---------------------------
Kai UchaczMonsters (CBJ)C/RW232003-06-24CANNo211 Lbs6 ft2NoNoFree AgentNoNo22025-05-25FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Karson KuhlmanMonsters (CBJ)C/RW311995-09-26USANo197 Lbs5 ft11NoNoTrade2024-12-03NoNo22024-07-15FalseFalsePro & Farm3,195,075$0$0$No3,195,075$--------3,195,075$--------No--------
Lleyton MooreMonsters (CBJ)D242002-02-27CANNo184 Lbs5 ft8NoNoFree AgentNoNo12024-07-18FalseFalsePro & Farm975,000$0$0$No---------------------------
Logan MorrisonMonsters (CBJ)C/RW242002-07-09CANNo182 Lbs6 ft0NoNoTrade2025-05-25NoNo1FalseFalsePro & Farm900,000$0$0$No---------------------------
Mason AppletonMonsters (CBJ)C/LW/RW301996-01-15USANo215 Lbs6 ft2NoNoTrade2025-02-15NoNo22025-05-25FalseFalsePro & Farm2,151,000$0$0$No2,151,000$--------2,151,000$--------No--------
Matt LuffMonsters (CBJ)LW/RW291997-05-05CANNo206 Lbs6 ft3NoNoTrade2024-12-09NoNo2FalseFalsePro & Farm1,215,000$0$0$No1,215,000$--------1,215,000$--------No--------
Philip KempMonsters (CBJ)D271999-02-12USANo218 Lbs6 ft3NoNoTrade2024-12-03NoNo32024-07-11FalseFalsePro & Farm2,199,999$0$0$No2,199,999$2,199,999$-------2,199,999$2,199,999$-------NoNo-------
Riley ThompsonMonsters (CBJ)C/LW242002-08-17CANYes216 Lbs6 ft4NoNoFree AgentNoNo22026-06-22FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Ryan FantiMonsters (CBJ)G271999-10-03CANNo199 Lbs6 ft3NoNoFree AgentNoNo42025-09-01FalseFalsePro & Farm1,875,000$0$0$No1,875,000$1,875,000$1,875,000$------1,875,000$1,875,000$1,875,000$------NoNoNo------
Ryan SchmelzerMonsters (CBJ)C/RW331993-07-28USANo190 Lbs6 ft2NoNoN/ANoNo22026-05-31FalseFalsePro & Farm1,449,000$0$0$No1,449,000$--------1,449,000$--------No--------
Spencer StastneyMonsters (CBJ)D262000-01-04USANo186 Lbs6 ft0NoNoTrade2024-12-18NoNo22025-05-25FalseFalsePro & Farm2,057,000$0$0$No2,057,000$--------2,057,000$--------No--------
Topias VilenMonsters (CBJ)D232003-04-01FINNo197 Lbs6 ft1NoNoFree AgentNoNo22025-05-25FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Tucker PoolmanMonsters (CBJ)D331993-06-08USANo226 Lbs6 ft4NoNoFree AgentNoNo22025-08-22FalseFalsePro & Farm2,150,000$0$0$No2,150,000$--------2,150,000$--------No--------
Tyler SpeziaMonsters (CBJ)C/LW331993-06-07USANo183 Lbs5 ft10NoNoFree AgentNoNo12025-05-25FalseFalsePro & Farm1,054,000$0$0$No---------------------------
Viliam KmecMonsters (CBJ)D222004-01-02SVKYes220 Lbs6 ft3NoNoFree AgentNoNo22026-06-05FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Vinnie PurpuraMonsters (CBJ)G271998-10-29USANo225 Lbs6 ft6YesNoFree AgentNoNo22026-08-30FalseFalsePro & Farm850,000$0$0$No850,000$--------850,000$--------Yes--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2727.96209 Lbs6 ft21.961,393,598$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ben MeyersMason AppletonLogan Morrison40122
2Matt LuffRiley ThompsonRyan Schmelzer30122
3Dalton SmithKarson KuhlmanKai Uchacz20122
4Carson GolderJon MartinMason Appleton10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Spencer StastneyTucker Poolman40122
2Philip KempTopias Vilen30122
3Austin StrandJosh Jacobs20122
4Spencer StastneyTucker Poolman10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ben MeyersMason AppletonLogan Morrison60122
2Matt LuffRiley ThompsonRyan Schmelzer40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Spencer StastneyTucker Poolman60122
2Philip KempTopias Vilen40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Mason AppletonLogan Morrison60122
2Ben MeyersMatt Luff40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Spencer StastneyTucker Poolman60122
2Philip KempTopias Vilen40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Mason Appleton60122Spencer StastneyTucker Poolman60122
2Logan Morrison40122Philip KempTopias Vilen40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Mason AppletonLogan Morrison60122
2Ben MeyersMatt Luff40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Spencer StastneyTucker Poolman60122
2Philip KempTopias Vilen40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ben MeyersMason AppletonLogan MorrisonSpencer StastneyTucker Poolman
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ben MeyersMason AppletonLogan MorrisonSpencer StastneyTucker Poolman
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Tyler Spezia, Karson Kuhlman, Kai UchaczTyler Spezia, Karson KuhlmanKai Uchacz
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Austin Strand, Josh Jacobs, Philip KempAustin StrandJosh Jacobs, Philip Kemp
Tirs de pénalité
Mason Appleton, Logan Morrison, Ben Meyers, Matt Luff, Riley Thompson
Gardien
#1 : Al Desnoyers, #2 : Ryan Fanti


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
TotalDomicile Visiteur
# 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 RI
1Americans11000000312110000003120000000000021.000369007417029107798332661215300.00%5180.00%014634242.69%21944948.78%9419448.45%2581683079315574
2Comets1010000004-4000000000001010000004-400.00000000741702510779833228615400.00%30100.00%014634242.69%21944948.78%9419448.45%2581683079315574
3Crunch20200000710-31010000034-11010000046-200.0007121900741703610779833822134375240.00%17288.24%014634242.69%21944948.78%9419448.45%2581683079315574
4Griffins11000000413000000000001100000041321.00047110074170251077983333108163133.33%40100.00%014634242.69%21944948.78%9419448.45%2581683079315574
5Marlies2020000037-41010000024-21010000013-200.00036910741704110779833612020465120.00%10370.00%014634242.69%21944948.78%9419448.45%2581683079315574
6Rockets2020000059-41010000035-21010000024-200.000581310741704310779833591814393133.33%7185.71%014634242.69%21944948.78%9419448.45%2581683079315574
7Senators2010010036-31000010023-11010000013-210.2503690074170511077983345131647800.00%7185.71%014634242.69%21944948.78%9419448.45%2581683079315574
8Wolf Pack1010000034-11010000034-10000000000000.00036900741702210779833281110185120.00%5180.00%014634242.69%21944948.78%9419448.45%2581683079315574
Total1229001002842-14614001001621-5615000001221-950.20828517920741702721077983335610712023336616.67%58984.48%014634242.69%21944948.78%9419448.45%2581683079315574
_Since Last GM Reset1229001002842-14614001001621-5615000001221-950.20828517920741702721077983335610712023336616.67%58984.48%014634242.69%21944948.78%9419448.45%2581683079315574
_Vs Conference1229001002842-14614001001621-5615000001221-950.20828517920741702721077983335610712023336616.67%58984.48%014634242.69%21944948.78%9419448.45%2581683079315574

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
125L328517927235610712023320
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
122901002842
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
61401001621
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
61500001221
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
36616.67%58984.48%0
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
1077983374170
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
14634242.69%21944948.78%9419448.45%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2581683079315574


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
16Rockets5Monsters3LSommaire du match
321Monsters2Rockets4LSommaire du match
435Monsters4Crunch6LSommaire du match
753Crunch4Monsters3LSommaire du match
1071Americans1Monsters3WSommaire du match
1286Monsters1Marlies3LSommaire du match
1498Monsters0Comets4LSommaire du match
15108Monsters4Griffins1WSommaire du match
18125Senators3Monsters2LXSommaire du match
22147Marlies4Monsters2LSommaire du match
25174Wolf Pack4Monsters3LSommaire du match
27185Monsters1Senators3LSommaire du match
29201Comets-Monsters-
33228Thunderbirds-Monsters-
37258Firebird-Monsters-
40267Monsters-Canucks-
42283Monsters-Wolves-
43295Comets-Monsters-
46319Monsters-Wranglers-
48326Bears-Monsters-
51348Monsters-Bears-
52359IceHogs-Monsters-
55378Monsters-Checkers-
58389Moose-Monsters-
61412Monsters-Barracuda-
63424Monsters-Crunch-
64434Phantoms-Monsters-
67455Monsters-Gulls-
68464Bruins-Monsters-
71480Monsters-Wild-
73494Americans-Monsters-
75508Monsters-Wolf Pack-
78522Monsters-Silver Knight-
79536Senators-Monsters-
82555Monsters-Eagles-
83567Wranglers-Monsters-
85586Monsters-Bruins-
87597Stars-Monsters-
90619Monsters-Senators-
91631Eagles-Monsters-
94648Monsters-Firebird-
97662Crunch-Monsters-
99680Monsters-Griffins-
100691Reign-Monsters-
103715Monsters-IceHogs-
105725Monsters-Roadrunners-
106731Gulls-Monsters-
109755Wolves-Monsters-
111766Monsters-Rockets-
115787Canucks-Monsters-
117801Monsters-Admirals-
119812Monsters-Hammers-
120823Checkers-Monsters-
124849Monsters-Marlies-
125858Hammers-Monsters-
128884Condors-Monsters-
130900Monsters-Penguins-
132915Rockets-Monsters-
135930Monsters-Reign-
137941Monsters-Condors-
139954Wild-Monsters-
142973Monsters-Americans-
143986Penguins-Monsters-
1471009Marlies-Monsters-
1501035Monsters-Moose-
1511042Barracuda-Monsters-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1561070Griffins-Monsters-
1571074Monsters-Thunderbirds-
1611102Admirals-Monsters-
1631111Monsters-Comets-
1661132Roadrunners-Monsters-
1671137Monsters-Stars-
1721164Griffins-Monsters-
1741177Monsters-Phantoms-
1761191Monsters-Americans-
1841214Silver Knight-Monsters-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets10099
Assistance6,4462,538
Assistance PCT53.72%42.30%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
32 1497 - 49.91% 222,472$1,334,833$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,189,193$ 7,525,430$ 7,525,430$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,116,225$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
7,119,109$ 158 43,381$ 6,854,198$




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