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Gorillas
GP: 65 | W: 26 | L: 31 | OTL: 8 | P: 60
GF: 208 | GA: 246 | PP%: 25.00% | PK%: 71.08%
DG: Patrick | Morale : 79 | Moyenne d’équipe : N/A
Prochains matchs #1000 vs Blossom Bytes

Centre de jeu
Gorillas
26-31-8, 60pts
3
FINAL
4 Redhawks
30-26-5, 65pts
Team Stats
OTL1SéquenceL1
14-13-4Fiche domicile16-12-3
12-18-4Fiche domicile14-14-2
6-3-1Derniers 10 matchs4-5-1
3.20Buts par match 3.90
3.78Buts contre par match 3.84
25.00%Pourcentage en avantage numérique25.74%
71.08%Pourcentage en désavantage numérique70.83%
Octopus
32-24-2, 66pts
5
FINAL
4 Gorillas
26-31-8, 60pts
Team Stats
W3SéquenceOTL1
21-10-1Fiche domicile14-13-4
11-14-1Fiche domicile12-18-4
7-3-0Derniers 10 matchs6-3-1
4.22Buts par match 3.20
3.86Buts contre par match 3.78
31.25%Pourcentage en avantage numérique25.00%
71.31%Pourcentage en désavantage numérique71.08%
Gorillas
26-31-8, 60pts
Jour 140
Blossom Bytes
43-14-4, 90pts
Statistiques d’équipe
OTL1SéquenceW3
14-13-4Fiche domicile21-8-2
12-18-4Fiche visiteur22-6-2
6-3-110 derniers matchs8-1-1
3.20Buts par match 4.54
3.78Buts contre par match 4.54
25.00%Pourcentage en avantage numérique30.15%
71.08%Pourcentage en désavantage numérique73.55%
Gorillas
26-31-8, 60pts
Jour 142
Bulldogs
33-27-4, 70pts
Statistiques d’équipe
OTL1SéquenceL2
14-13-4Fiche domicile15-16-0
12-18-4Fiche visiteur18-11-4
6-3-110 derniers matchs3-6-1
3.20Buts par match 3.38
3.78Buts contre par match 3.38
25.00%Pourcentage en avantage numérique33.94%
71.08%Pourcentage en désavantage numérique72.51%
Americans
30-27-6, 66pts
Jour 143
Gorillas
26-31-8, 60pts
Statistiques d’équipe
W3SéquenceOTL1
15-11-5Fiche domicile14-13-4
15-16-1Fiche visiteur12-18-4
8-2-010 derniers matchs6-3-1
3.46Buts par match 3.20
3.83Buts contre par match 3.20
32.96%Pourcentage en avantage numérique25.00%
69.10%Pourcentage en désavantage numérique71.08%
Meneurs d'équipe
Buts
Adam Gaudette
38
Passes
Adam Gaudette
38
Points
Adam Gaudette
76
Plus/Moins
Adam Gaudette
10
Victoires
Adam Huska
12
Pourcentage d’arrêts
Tomas Suchanek
0.9

Statistiques d’équipe
Buts pour
208
3.20 GFG
Tirs pour
1783
27.43 Avg
Pourcentage en avantage numérique
25.0%
70 GF
Début de zone offensive
36.5%
Buts contre
246
3.78 GAA
Tirs contre
2067
31.80 Avg
Pourcentage en désavantage numérique
71.1%%
83 GA
Début de la zone défensive
37.8%
Informations de l'équipe

Directeur généralPatrick
EntraîneurKarl Taylor
DivisionCentral Division
ConférenceWestern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité8,000
Assistance8,000
Billets de saison800


Informations de la formation

Équipe Pro28
Équipe Mineure19
Limite contact 47 / 65
Espoirs14


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
1Aidan DudasX100.0060606060607070606060606060556107900241650,000$
2Vladimir TarasenkoXX100.00675095818281947561716968656868078003314,750,000$
3Adam TambelliniXXX100.0060606060607070606060606060596706100301650,000$
4Adam MascherinXX100.0060606060607070606060606060596304500261787,500$
5Justin SourdifXX100.00605082716976846461646465655155071002221,023,750$
6Sasha PastujovXX100.00606060606070706060606060604355068002121,312,500$
7Otto KivenmakiXXX100.0060606060607070606060606060495506300241735,000$
8Lenni HameenahoXX100.00606060606070706060606060604055069012021,500,000$
9Felix Unger SorumXX100.00606060606070706060606060604055072011921,250,000$
10Jimmy Snuggerud (R)X100.00606060606070706060606060604655046002031,500,000$
11Tyler Thorpe (R)X100.0060606060607070606060606060465507900193750,000$
12Tom HedbergX100.0060606060607070606060606060554405400251787,500$
13Anttoni HonkaX100.00606060606070706060606060605155067002411,023,750$
14Kyle MastersX100.0060606060607070606060606060405505400211825,000$
15Shai BuiumX100.00606060606070706060606060604055070012121,500,000$
16Ryan UfkoX100.0062509470678293622564616865405506401212825,000$
17Otto SalinX100.0060606060607070606060606060405507301202825,000$
Rayé
1Adam GaudetteXX96.9268509480717794736865736765606706800281650,000$
2Carson LatimerXX100.0060606060607070606060606060405503700211825,000$
3Luke TuchXX100.00606060606070706060606060604055068012211,250,000$
4Connor Kurth (R)XXX100.0060606060607070606060606060465507500212750,000$
5Trevor Connelly (R)X100.00606060606070706060606060604255036001831,500,000$
6Helge GransX36.15605089687881936425656370655057044002221,378,125$
7Arttu Karki (R)X100.0060606060607070606060606060445506400203975,000$
MOYENNE D’ÉQUIPE97.176158666363727562586161626148570630
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
1Adam Huska99.006070706060606060606060586703900271650,000$
2Kirill Gerasimyuk (R)100.006070706060606060606060405504300212750,000$
Rayé
1Niklas Kokko100.006070706060606060606060405506900201975,000$
2Tomas Suchanek93.836070706060606060606060405504800211750,000$
MOYENNE D’ÉQUIPE98.00607070606060606060606045580500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Karl Taylor6565656563681CAN541600,000$


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
1Adam GaudetteGorillas (CBS)LW/RW60383876103735751012959313212.88%41135222.5513162941175101101545446.02%1767633021.1200106773
2Justin SourdifGorillas (CBS)LW/RW62253661-15603083922136213811.74%36128420.72613192113701161293349.06%2654318000.9501303273
3Vladimir TarasenkoGorillas (CBS)LW/RW57292958-1443076992147013713.55%37121721.36106162914410191332050.57%5245226010.9513213546
4Adam TambelliniGorillas (CBS)C/LW/RW61132538-1222712510196108386212.04%34116219.06710172918000091121047.19%7481617000.65154714012
5Aidan DudasGorillas (CBS)C5812203218840998876244415.79%2194316.272810101050003630049.28%6211416000.6801224114
6Felix Unger SorumGorillas (CBS)LW/RW50151631-24915634876274719.74%1673614.746915181070002572240.74%54158000.8412111302
7Adam MascherinGorillas (CBS)LW/RW51141630-1512480646878235717.95%2683616.414711201111014353146.50%2431213000.7201475221
8Otto KivenmakiGorillas (CBS)C/LW/RW4991625-77155746575275312.00%2280216.374711131090003740146.79%5601413000.6201236103
9Helge GransGorillas (CBS)D53222240604042726524233.08%87122123.052911151560003152000%21641000.3900341001
10Ryan UfkoGorillas (CBS)D63121227323031756831321.47%89130620.7415671340114152100%01641000.3400312000
11Jimmy SnuggerudGorillas (CBS)RW321161717345393054153920.37%743413.5841513680001231044.00%5089000.7802324121
12Otto SalinGorillas (CBS)D552131531589048394116204.88%53101518.460331107011070000%0932000.3011549000
13Tyler ThorpeGorillas (CBS)RW52961596220524341154221.95%456810.9300000000000048.31%207410000.5300112120
14Kyle MastersGorillas (CBS)D3411314-2714529463020133.33%2866919.70123855000074100%0716000.4200333000
15Sasha PastujovGorillas (CBS)LW/RW514610-24593556496022356.67%861212.002247490000120051.68%14986000.3300142000
16Anttoni HonkaGorillas (CBS)D462810-231065032495214203.85%4487118.94235782000476000%0729000.2300217000
17Shai BuiumGorillas (CBS)D552810-181568059625412173.70%61108719.7824691060111119000%01429000.1800664010
18Arttu KarkiGorillas (CBS)D42189-287553033301593.33%4779018.8301166700016200100.00%11230000.2300128100
19Tom HedbergGorillas (CBS)D45178-15883050413910122.56%4688719.71167710700009201100.00%2516000.1800132001
20Trevor ConnellyGorillas (CBS)LW284481594541143251512.50%534312.2600013000002071.43%1415000.4700153020
21Lenni HameenahoGorillas (CBS)LW/RW413475462024132361613.04%32927.14213317000002062.96%8123000.4800031100
22Connor KurthGorillas (CBS)C/LW/RW49437-3352525252262318.18%42685.4710114000040146.91%8141000.5200203010
23Luke TuchGorillas (CBS)LW/RW45235-511524171841711.11%62435.4000002000001055.00%2034000.4100001010
24Carson LatimerGorillas (CBS)LW/RW31213-82420211519101610.53%42558.2500005000000050.00%827000.2300211000
Statistiques d’équipe totales ou en moyenne1170206329535-11518271045123812801783589101911.55%7291920516.42701131832662042347601602241348.55%3806360423030.56417536195253127
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
1Adam HuskaGorillas (CBS)37121740.8813.47198700115966554310.6005361111
2Tomas SuchanekGorillas (CBS)166610.9003.397250141412232100.50021111100
3Kirill GerasimyukGorillas (CBS)205430.8813.868400054455252100.57171240011
4Niklas KokkoGorillas (CBS)93400.8674.9137900312331311000613010
Statistiques d’équipe totales ou en moyenne82263180.8833.683932012412066116961146565232


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 Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond 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
Adam GaudetteGorillas (CBS)LW/RW281996-10-03USANo187 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm650,000$169,415$65,000$16,941$No---------------------------
Adam HuskaGorillas (CBS)G271997-05-12SVKNo198 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm650,000$169,415$65,000$16,941$No---------------------------
Adam MascherinGorillas (CBS)LW/RW261998-06-06CANNo205 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm787,500$205,253$78,750$20,525$No---------------------------
Adam TambelliniGorillas (CBS)C/LW/RW301994-11-01CANNo194 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm650,000$169,415$65,000$16,941$No---------------------------
Aidan DudasGorillas (CBS)C242000-06-15CANNo185 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm650,000$169,415$65,000$16,941$No---------------------------
Anttoni HonkaGorillas (CBS)D242000-10-05FINNo179 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm1,023,750$266,828$102,375$26,683$No---------------------------
Arttu KarkiGorillas (CBS)D202004-12-08FINYes181 Lbs6 ft0NoNoProspectNoNo32025-08-20FalseFalsePro & Farm975,000$254,122$97,500$25,412$No975,000$975,000$-------975,000$975,000$-------NoNo-------
Carson LatimerGorillas (CBS)LW/RW212003-01-10CANNo185 Lbs7 ft3NoNoN/ANoNo1FalseFalsePro & Farm825,000$215,027$82,500$21,503$No---------------------------
Connor KurthGorillas (CBS)C/LW/RW212003-07-30USAYes212 Lbs5 ft10NoNoProspectNoNo22025-08-20FalseFalsePro & Farm750,000$195,479$75,000$19,548$No750,000$--------750,000$--------No--------
Felix Unger SorumGorillas (CBS)LW/RW192005-09-14SWENo172 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm1,250,000$325,798$125,000$32,580$No1,250,000$--------1,250,000$--------No--------
Helge Grans (sur la masse salariale)Gorillas (CBS)D222002-05-10SWENo205 Lbs6 ft4NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,378,125$359,192$137,812$35,919$No1,378,125$--------1,378,125$--------No--------
Jimmy SnuggerudGorillas (CBS)RW202004-06-01USAYes187 Lbs6 ft0NoNoProspectNoNo32025-08-20FalseFalsePro & Farm1,500,000$390,957$150,000$39,096$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------
Justin SourdifGorillas (CBS)LW/RW222002-03-24CANNo181 Lbs5 ft11NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,023,750$266,828$102,375$26,683$No1,023,750$--------1,023,750$--------No--------
Kirill GerasimyukGorillas (CBS)G212003-08-22RUSYes179 Lbs6 ft0NoNoProspectNoNo22025-08-20FalseFalsePro & Farm750,000$195,479$75,000$19,548$No750,000$--------750,000$--------No--------
Kyle MastersGorillas (CBS)D212003-04-09CANNo183 Lbs6 ft8NoNoN/ANoNo1FalseFalsePro & Farm825,000$215,027$82,500$21,503$No---------------------------
Lenni HameenahoGorillas (CBS)LW/RW202004-11-07FINNo185 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm1,500,000$390,957$150,000$39,096$No1,500,000$--------1,500,000$--------No--------
Luke TuchGorillas (CBS)LW/RW222002-03-07USANo203 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$325,798$125,000$32,580$No---------------------------
Niklas KokkoGorillas (CBS)G202004-03-14FINNo192 Lbs7 ft2NoNoN/ANoNo1FalseFalsePro & Farm975,000$254,122$97,500$25,412$No---------------------------
Otto KivenmakiGorillas (CBS)C/LW/RW242000-03-24FINNo172 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm735,000$191,569$73,500$19,157$No---------------------------
Otto SalinGorillas (CBS)D202004-03-07FINNo192 Lbs5 ft11NoNoProspectNoNo22024-08-30FalseFalsePro & Farm825,000$215,027$82,500$21,503$No825,000$--------825,000$--------No--------
Ryan UfkoGorillas (CBS)D212003-05-07USANo174 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm825,000$215,027$82,500$21,503$No825,000$--------825,000$--------No--------
Sasha PastujovGorillas (CBS)LW/RW212003-07-15USANo187 Lbs6 ft1NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,312,500$342,088$131,250$34,209$No1,312,500$--------1,312,500$--------No--------
Shai BuiumGorillas (CBS)D212003-03-26USANo220 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm1,500,000$390,957$150,000$39,096$No1,500,000$--------1,500,000$--------No--------
Tom HedbergGorillas (CBS)D251999-08-10SWENo179 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm787,500$205,253$78,750$20,525$No---------------------------
Tomas Suchanek (sur la masse salariale)Gorillas (CBS)G212003-04-30CZENo181 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm750,000$195,479$65,000$16,941$No---------------------------
Trevor ConnellyGorillas (CBS)LW182006-02-28USAYes165 Lbs5 ft11NoNoDraftNoNo32025-08-20FalseFalsePro & Farm1,500,000$390,957$150,000$39,096$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------
Tyler ThorpeGorillas (CBS)RW192005-08-11CANYes220 Lbs6 ft3NoNoDraftNoNo32025-08-20FalseFalsePro & Farm750,000$195,479$75,000$19,548$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Vladimir TarasenkoGorillas (CBS)LW/RW331991-12-13RUSNo219 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm4,750,000$1,238,032$475,000$123,803$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2822.54190 Lbs6 ft21.641,112,433$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Vladimir TarasenkoOtto KivenmakiJimmy Snuggerud28122
2Adam TambelliniAidan DudasAdam Mascherin28122
3Sasha PastujovJustin SourdifTyler Thorpe25122
4Justin SourdifVladimir TarasenkoLenni Hameenaho19122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ryan Ufko40122
2Kyle MastersShai Buium35122
3Otto SalinAnttoni Honka25122
4Otto Salin0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Vladimir TarasenkoOtto KivenmakiJustin Sourdif50122
2Adam TambelliniAidan DudasAdam Mascherin50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Otto Salin50122
2Ryan UfkoShai Buium50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Vladimir TarasenkoJustin Sourdif50122
2Otto KivenmakiAidan Dudas50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Otto Salin50122
2Ryan UfkoShai Buium50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Vladimir Tarasenko50122Otto Salin50122
2Otto Kivenmaki50122Kyle MastersShai Buium50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Vladimir TarasenkoAdam Tambellini50122
2Otto KivenmakiAidan Dudas50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Otto Salin50122
2Ryan UfkoShai Buium50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Vladimir TarasenkoOtto KivenmakiJustin SourdifRyan Ufko
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Vladimir TarasenkoOtto KivenmakiJustin SourdifRyan Ufko
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Felix Unger Sorum, Vladimir Tarasenko, Sasha PastujovFelix Unger Sorum, Vladimir TarasenkoSasha Pastujov
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Otto Salin, Shai Buium, Otto Salin, Otto Salin
Tirs de pénalité
Vladimir Tarasenko, Sasha Pastujov, Otto Kivenmaki, Aidan Dudas, Adam Tambellini
Gardien
#1 : Adam Huska, #2 : Kirill Gerasimyuk


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
1Admirals1010000024-21010000024-20000000000000.000224005199563215376545812623121819400.00%4175.00%0662138847.69%695143748.36%49198150.05%124055812986731398710
2Americans21100000990211000009900000000000020.5009152400519956357537654581266412904711327.27%10370.00%0662138847.69%695143748.36%49198150.05%124055812986731398710
3Bears11000000523110000005230000000000021.00058130051995632753765458126291262611100.00%3233.33%0662138847.69%695143748.36%49198150.05%124055812986731398710
4Bills624000002129-8422000001616020200000513-840.333213556005199563163537654581262066633011531825.81%35974.29%0662138847.69%695143748.36%49198150.05%124055812986731398710
5Blood Miners522001001418-432000100121022020000028-650.50014183200519956314553765458126185751479723417.39%26869.23%1662138847.69%695143748.36%49198150.05%124055812986731398710
6Bulldogs32000001972210000016511100000032150.833913220051995637553765458126732996699444.44%14471.43%1662138847.69%695143748.36%49198150.05%124055812986731398710
7Crunch2010000136-3000000000002010000136-310.2503580051995634553765458126531417314250.00%6183.33%0662138847.69%695143748.36%49198150.05%124055812986731398710
8Eagles302000101213-11010000045-12010001088020.333121628005199563815376545812613454596111327.27%17664.71%0662138847.69%695143748.36%49198150.05%124055812986731398710
9Griffins633000001821-3422000001015-52110000086260.50018304800519956315753765458126162641589830723.33%19763.16%0662138847.69%695143748.36%49198150.05%124055812986731398710
10Grisards1010000025-3000000000001010000025-300.000235005199563245376545812626112118400.00%8187.50%0662138847.69%695143748.36%49198150.05%124055812986731398710
11Mountaineers31200000913-41010000038-52110000065120.3339152401519956373537654581267823514410440.00%13469.23%0662138847.69%695143748.36%49198150.05%124055812986731398710
12Norsemen11000000642000000000001100000064221.0006101600519956331537654581262912242322100.00%7271.43%0662138847.69%695143748.36%49198150.05%124055812986731398710
13Octopus301001101314-1200001109901010000045-130.500131932005199563975376545812613243965614321.43%13284.62%0662138847.69%695143748.36%49198150.05%124055812986731398710
14Phantoms11000000431000000000001100000043121.00047110051995633453765458126311820194125.00%5180.00%0662138847.69%695143748.36%49198150.05%124055812986731398710
15Rams1010000012-11010000012-10000000000000.00012300519956326537654581263161618600.00%3166.67%0662138847.69%695143748.36%49198150.05%124055812986731398710
16Redhawks20200000410-61010000016-51010000034-100.00047110051995636453765458126572227391218.33%6266.67%0662138847.69%695143748.36%49198150.05%124055812986731398710
17Reign302001001015-51010000024-220100100811-310.167101424005199563905376545812611934615214535.71%18761.11%0662138847.69%695143748.36%49198150.05%124055812986731398710
18Roadrunners421000011314-111000000321311000011012-250.6251321340051995631375376545812610841507616637.50%15660.00%0662138847.69%695143748.36%49198150.05%124055812986731398710
19Rocket321000009721010000024-22200000073440.66791524005199563805376545812682291357115426.67%15286.67%1662138847.69%695143748.36%49198150.05%124055812986731398710
20Saints21100000660110000004221010000024-220.500610160051995633053765458126562144386350.00%7185.71%0662138847.69%695143748.36%49198150.05%124055812986731398710
21Senators21000001871110000005321000000134-130.750814220051995635953765458126842333367114.29%4175.00%0662138847.69%695143748.36%49198150.05%124055812986731398710
22Silver Knights2020000036-3000000000002020000036-300.00035800519956353537654581265221333410110.00%9277.78%0662138847.69%695143748.36%49198150.05%124055812986731398710
23Whalers1000010012-11000010012-10000000000010.5001120051995636537654581261161412000%2150.00%0662138847.69%695143748.36%49198150.05%124055812986731398710
24White Wolves532000002022-211000000514422000001521-660.60020335300519956316253765458126190632019323417.39%18761.11%0662138847.69%695143748.36%49198150.05%124055812986731398710
25Wolf Pack1010000024-21010000024-20000000000000.0002461051995632353765458126331135218225.00%50100.00%0662138847.69%695143748.36%49198150.05%124055812986731398710
26Wolves11000000431000000000001100000043121.0004711005199563235376545812619745255120.00%5260.00%0662138847.69%695143748.36%49198150.05%124055812986731398710
Total65243100424208246-3831131300311102113-1134111800113106133-27600.4622083295371151995631783537654581262067729182712382807025.00%2878371.08%3662138847.69%695143748.36%49198150.05%124055812986731398710
_Since Last GM Reset65243100424208246-3831131300311102113-1134111800113106133-27600.4622083295371151995631783537654581262067729182712382807025.00%2878371.08%3662138847.69%695143748.36%49198150.05%124055812986731398710
_Vs Conference52182600323164201-3723109002117787-10298170011287114-27460.442164256420015199563145253765458126168759915059742285925.88%2316870.56%3662138847.69%695143748.36%49198150.05%124055812986731398710
_Vs Division221413001037682-699400101322751359000024455-11320.7277611318900519956365253765458126742286595438882326.14%1013466.34%2662138847.69%695143748.36%49198150.05%124055812986731398710

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6560OTL1208329537178320677291827123811
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6524310424208246
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3113130311102113
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3411180113106133
Derniers 10 matchs
WLOTWOTL SOWSOL
630100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2807025.00%2878371.08%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
537654581265199563
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
662138847.69%695143748.36%49198150.05%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
124055812986731398710


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
213Bills5Gorillas7WSommaire du match
427Gorillas4Roadrunners6LSommaire du match
644Blood Miners3Gorillas4WSommaire du match
752Gorillas5White Wolves4WSommaire du match
1075Americans6Gorillas7WSommaire du match
1290Gorillas2White Wolves9LSommaire du match
14103Gorillas1Bills6LSommaire du match
16115Griffins7Gorillas2LSommaire du match
19138Bulldogs1Gorillas3WSommaire du match
20148Gorillas0Crunch2LSommaire du match
23172Griffins1Gorillas2WSommaire du match
26189Gorillas4White Wolves5LSommaire du match
28202Bills5Gorillas2LSommaire du match
30215Gorillas5Reign6LXSommaire du match
32228Gorillas4Rocket2WSommaire du match
34241Saints2Gorillas4WSommaire du match
36254Gorillas3Crunch4LXXSommaire du match
38268Gorillas4Octopus5LSommaire du match
40281Senators3Gorillas5WSommaire du match
43302Gorillas1Silver Knights2LSommaire du match
45311Admirals4Gorillas2LSommaire du match
47328Gorillas3Senators4LXXSommaire du match
49342Wolf Pack4Gorillas2LSommaire du match
51359Gorillas4Eagles3WXXSommaire du match
53375Rocket4Gorillas2LSommaire du match
55393Gorillas1Roadrunners2LXXSommaire du match
57406Gorillas6Norsemen4WSommaire du match
58415Mountaineers8Gorillas3LSommaire du match
61437Redhawks6Gorillas1LSommaire du match
62446Gorillas2Grisards5LSommaire du match
65460Gorillas4Eagles5LSommaire du match
67474Reign4Gorillas2LSommaire du match
69490Gorillas4Bills7LSommaire du match
72507Eagles5Gorillas4LSommaire du match
74524Gorillas4Phantoms3WSommaire du match
76534Gorillas2Mountaineers0WSommaire du match
77543Bills4Gorillas3LSommaire du match
80560Gorillas3Rocket1WSommaire du match
82574Whalers2Gorillas1LXSommaire du match
84591Gorillas3Reign5LSommaire du match
86605Bills2Gorillas4WSommaire du match
88618Gorillas0Blood Miners4LSommaire du match
90630Gorillas4Mountaineers5LSommaire du match
91640Americans3Gorillas2LSommaire du match
94665Gorillas4White Wolves3WSommaire du match
95672Blood Miners5Gorillas4LXSommaire du match
98696Gorillas2Saints4LSommaire du match
100704Griffins2Gorillas4WSommaire du match
102724Gorillas2Silver Knights4LSommaire du match
104736Griffins5Gorillas2LSommaire du match
106748Gorillas4Griffins5LSommaire du match
109768Bulldogs4Gorillas3LXXSommaire du match
112796Octopus4Gorillas5WXXSommaire du match
115815Gorillas4Griffins1WSommaire du match
117830White Wolves1Gorillas5WSommaire du match
119846Gorillas4Wolves3WSommaire du match
121862Blood Miners2Gorillas4WSommaire du match
124880Gorillas3Bulldogs2WSommaire du match
125893Roadrunners2Gorillas3WSommaire du match
127907Gorillas2Blood Miners4LSommaire du match
129926Bears2Gorillas5WSommaire du match
132942Gorillas5Roadrunners4WSommaire du match
134958Rams2Gorillas1LSommaire du match
136971Gorillas3Redhawks4LSommaire du match
138986Octopus5Gorillas4LXSommaire du match
1401000Gorillas-Blossom Bytes-
1421013Gorillas-Bulldogs-
1431024Americans-Gorillas-
1451040Gorillas-Crunch-
1471055Crunch-Gorillas-
1491069Gorillas-Blossom Bytes-
1511086Bulldogs-Gorillas-
1541104Gorillas-Redhawks-
1561119Moose-Gorillas-
1601150Crunch-Gorillas-
1611154Gorillas-Gulls-
1641179Gorillas-Penguins-
1651184Roadrunners-Gorillas-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1691215Saints-Gorillas-
1751245Titans-Gorillas-
1801272Silver Knights-Gorillas-
1851304White Wolves-Gorillas-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité25005500
Prix des billets1912
Assistance77,500170,500
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
10 8000 - 100.00% 136,200$4,222,200$8000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,580,731$ 2,902,000$ 2,902,000$ 600,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
18,628$ 2,574,445$ 26 2

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,362,000$ 49 18,628$ 912,772$




Gorillas 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

Gorillas 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

Gorillas 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

Gorillas 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

Gorillas 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