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Gorillas
GP: 4 | W: 3 | L: 1 | OTL: 0 | P: 6
GF: 20 | GA: 18 | PP%: 33.33% | PK%: 63.16%
DG: Patrick | Morale : 99 | Moyenne d’équipe : N/A
Prochains matchs #75 vs Americans

Centre de jeu
Blood Miners
0-3-0, 0pts
3
FINAL
4 Gorillas
3-1-0, 6pts
Team Stats
L3SéquenceW2
0-1-0Fiche domicile2-0-0
0-2-0Fiche domicile1-1-0
0-3-0Derniers 10 matchs3-1-0
2.33Buts par match 5.00
5.00Buts contre par match 4.50
18.18%Pourcentage en avantage numérique33.33%
66.67%Pourcentage en désavantage numérique63.16%
Gorillas
3-1-0, 6pts
5
FINAL
4 White Wolves
1-2-1, 3pts
Team Stats
W2SéquenceL2
2-0-0Fiche domicile0-1-1
1-1-0Fiche domicile1-1-0
3-1-0Derniers 10 matchs1-2-1
5.00Buts par match 4.75
4.50Buts contre par match 5.00
33.33%Pourcentage en avantage numérique33.33%
63.16%Pourcentage en désavantage numérique66.67%
Americans
2-1-0, 4pts
Jour 10
Gorillas
3-1-0, 6pts
Statistiques d’équipe
W1SéquenceW2
1-1-0Fiche domicile2-0-0
1-0-0Fiche visiteur1-1-0
2-1-010 derniers matchs3-1-0
4.67Buts par match 5.00
3.67Buts contre par match 5.00
41.67%Pourcentage en avantage numérique33.33%
76.47%Pourcentage en désavantage numérique63.16%
Gorillas
3-1-0, 6pts
Jour 12
White Wolves
1-2-1, 3pts
Statistiques d’équipe
W2SéquenceL2
2-0-0Fiche domicile0-1-1
1-1-0Fiche visiteur1-1-0
3-1-010 derniers matchs1-2-1
5.00Buts par match 4.75
4.50Buts contre par match 4.75
33.33%Pourcentage en avantage numérique33.33%
63.16%Pourcentage en désavantage numérique66.67%
Gorillas
3-1-0, 6pts
Jour 14
Bills
2-1-0, 4pts
Statistiques d’équipe
W2SéquenceW2
2-0-0Fiche domicile1-0-0
1-1-0Fiche visiteur1-1-0
3-1-010 derniers matchs2-1-0
5.00Buts par match 5.67
4.50Buts contre par match 5.67
33.33%Pourcentage en avantage numérique30.00%
63.16%Pourcentage en désavantage numérique41.67%
Meneurs d'équipe
Buts
Vladimir Tarasenko
4
Passes
Adam Gaudette
5
Points
Adam Gaudette
7
Plus/Moins
Jimmy Snuggerud
3
Victoires
Niklas Kokko
2
Pourcentage d’arrêts
Niklas Kokko
0.884

Statistiques d’équipe
Buts pour
20
5.00 GFG
Tirs pour
161
40.25 Avg
Pourcentage en avantage numérique
33.3%
7 GF
Début de zone offensive
39.1%
Buts contre
18
4.50 GAA
Tirs contre
156
39.00 Avg
Pourcentage en désavantage numérique
63.2%%
7 GA
Début de la zone défensive
33.7%
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 Mineure21
Limite contact 49 / 65
Espoirs13


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
1Adam GaudetteXX100.0068509480717794736865736765606709800281650,000$
2Aidan DudasX100.0060606060607070606060606060556109800241650,000$
3Vladimir TarasenkoXX100.00675095818281947561716968656868098003314,750,000$
4Adam TambelliniXXX100.0060606060607070606060606060596709800301650,000$
5Adam MascherinXX100.0060606060607070606060606060596309200261787,500$
6Justin SourdifXX100.00605082716976846461646465655155098002221,023,750$
7Sasha PastujovXX100.00606060606070706060606060604355095002121,312,500$
8Otto KivenmakiXXX100.0060606060607070606060606060495509800241735,000$
9Felix Unger SorumXX100.00606060606070706060606060604055098011921,250,000$
10Jimmy Snuggerud (R)X100.00606060606070706060606060604655098002031,500,000$
11Connor Kurth (R)XXX100.0060606060607070606060606060465509900212750,000$
12Trevor Connelly (R)X100.00606060606070706060606060604255098001831,500,000$
13Helge GransX100.00605089687881936425656370655057095002221,378,125$
14Anttoni HonkaX100.00606060606070706060606060605155095002411,023,750$
15Kyle MastersX100.0060606060607070606060606060405509800211825,000$
16Shai BuiumX100.00606060606070706060606060604055095012121,500,000$
17Ryan UfkoX100.0062509470678293622564616865405509801212825,000$
18Otto SalinX100.0060606060607070606060606060405509901202825,000$
Rayé
1Carson LatimerXX100.0060606060607070606060606060405509500211825,000$
2Luke TuchXX100.00606060606070706060606060604055095012211,250,000$
3Lenni HameenahoXX100.00606060606070706060606060604055095012021,500,000$
4Tyler Thorpe (R)X100.0060606060607070606060606060465509500193750,000$
5Tom HedbergX100.0060606060607070606060606060554409500251787,500$
6Arttu Karki (R)X100.0060606060607070606060606060445509500203975,000$
MOYENNE D’ÉQUIPE100.006158666363727562586161626148570970
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
1Kirill Gerasimyuk (R)100.006070706060606060606060405509800212750,000$
Rayé
1Adam Huska100.006070706060606060606060586709700271650,000$
2Niklas Kokko88.446070706060606060606060405508900201975,000$
3Tomas Suchanek94.816070706060606060606060405508800211750,000$
MOYENNE D’ÉQUIPE95.50607070606060606060606045580930
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/RW425730049254148.00%08320.962247150001140142.86%751001.6700000110
2Adam MascherinGorillas (CBS)LW/RW42461311593123816.67%37017.55022114101391028.57%1431001.7100021010
3Otto KivenmakiGorillas (CBS)C/LW/RW414507569125128.33%27318.361013150001100039.18%9702001.3600001000
4Vladimir TarasenkoGorillas (CBS)LW/RW440400032181422.22%04110.34000000001200100.00%142011.9300000101
5Helge GransGorillas (CBS)D404411010347330%58922.43022116000013000%016000.8900011000
6Kyle MastersGorillas (CBS)D41340552545725.00%79323.30112216000013100%014000.8600001000
7Felix Unger SorumGorillas (CBS)LW/RW431402063104730.00%16516.28101215000000050.00%401001.2300000100
8Otto SalinGorillas (CBS)D4044-11810216310%68421.1602201401108000%025000.9500200000
9Justin SourdifGorillas (CBS)LW/RW4213-30034111418.18%05112.7800001000000166.67%321001.1700000000
10Jimmy SnuggerudGorillas (CBS)RW43033405293233.33%26315.92202415000001033.33%622000.9400000000
11Adam TambelliniGorillas (CBS)C/LW/RW41123191571092511.11%17518.820113150001100045.71%10501000.5300003000
12Shai BuiumGorillas (CBS)D402221210325110%56516.430000000005000%014000.6100011000
13Aidan DudasGorillas (CBS)C4011000352120%14310.8200000000030040.91%2211000.4600000000
14Anttoni HonkaGorillas (CBS)D4011022106911120%68521.43000114000010000%011000.2300011000
15Ryan UfkoGorillas (CBS)D4011200138230%26115.260000000001000%023000.3300000000
16Trevor ConnellyGorillas (CBS)LW4101-1552220350.00%04310.8400000000000050.00%201000.4600001000
17Sasha PastujovGorillas (CBS)LW/RW400001610447110%0389.6000010000000060.00%52100000011000
18Connor KurthGorillas (CBS)C/LW/RW4000-11210853140%04310.8500000000000048.39%311000000101000
Statistiques d’équipe totales ou en moyenne7220325291631057782161418312.42%41117216.28710172515511271053243.10%2972837010.89003612321
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
1Niklas KokkoGorillas (CBS)42100.8844.62208001613881100040010
2Kirill GerasimyukGorillas (CBS)11000.9094.0015001116000002000
3Tomas SuchanekGorillas (CBS)10000.8573.751600173000002000
Statistiques d’équipe totales ou en moyenne63100.8854.5024000181569010044010


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$625,798$65,000$62,580$No---------------------------
Adam HuskaGorillas (CBS)G271997-05-12SVKNo198 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm650,000$625,798$65,000$62,580$No---------------------------
Adam MascherinGorillas (CBS)LW/RW261998-06-06CANNo205 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm787,500$758,178$78,750$75,818$No---------------------------
Adam TambelliniGorillas (CBS)C/LW/RW301994-11-01CANNo194 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm650,000$625,798$65,000$62,580$No---------------------------
Aidan DudasGorillas (CBS)C242000-06-15CANNo185 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm650,000$625,798$65,000$62,580$No---------------------------
Anttoni HonkaGorillas (CBS)D242000-10-05FINNo179 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm1,023,750$985,632$102,375$98,563$No---------------------------
Arttu KarkiGorillas (CBS)D202004-12-08FINYes181 Lbs6 ft0NoNoProspectNoNo32025-08-20FalseFalsePro & Farm975,000$938,697$97,500$93,870$No975,000$975,000$-------975,000$975,000$-------NoNo-------
Carson LatimerGorillas (CBS)LW/RW212003-01-10CANNo185 Lbs7 ft3NoNoN/ANoNo1FalseFalsePro & Farm825,000$794,282$82,500$79,428$No---------------------------
Connor KurthGorillas (CBS)C/LW/RW212003-07-30USAYes212 Lbs5 ft10NoNoProspectNoNo22025-08-20FalseFalsePro & Farm750,000$722,074$75,000$72,207$No750,000$--------750,000$--------No--------
Felix Unger SorumGorillas (CBS)LW/RW192005-09-14SWENo172 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm1,250,000$1,203,457$125,000$120,346$No1,250,000$--------1,250,000$--------No--------
Helge GransGorillas (CBS)D222002-05-10SWENo205 Lbs6 ft4NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,378,125$1,326,812$137,812$132,681$No1,378,125$--------1,378,125$--------No--------
Jimmy SnuggerudGorillas (CBS)RW202004-06-01USAYes187 Lbs6 ft0NoNoProspectNoNo32025-08-20FalseFalsePro & Farm1,500,000$1,444,149$150,000$144,415$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$985,632$102,375$98,563$No1,023,750$--------1,023,750$--------No--------
Kirill GerasimyukGorillas (CBS)G212003-08-22RUSYes179 Lbs6 ft0NoNoProspectNoNo22025-08-20FalseFalsePro & Farm750,000$722,074$75,000$72,207$No750,000$--------750,000$--------No--------
Kyle MastersGorillas (CBS)D212003-04-09CANNo183 Lbs6 ft8NoNoN/ANoNo1FalseFalsePro & Farm825,000$794,282$82,500$79,428$No---------------------------
Lenni HameenahoGorillas (CBS)LW/RW202004-11-07FINNo185 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm1,500,000$1,444,149$150,000$144,415$No1,500,000$--------1,500,000$--------No--------
Luke TuchGorillas (CBS)LW/RW222002-03-07USANo203 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$1,203,457$125,000$120,346$No---------------------------
Niklas Kokko (sur la masse salariale)Gorillas (CBS)G202004-03-14FINNo192 Lbs7 ft2NoNoN/ANoNo1FalseFalsePro & Farm975,000$938,697$97,500$93,870$No---------------------------
Otto KivenmakiGorillas (CBS)C/LW/RW242000-03-24FINNo172 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm735,000$707,633$73,500$70,763$No---------------------------
Otto SalinGorillas (CBS)D202004-03-07FINNo192 Lbs5 ft11NoNoProspectNoNo22024-08-30FalseFalsePro & Farm825,000$794,282$82,500$79,428$No825,000$--------825,000$--------No--------
Ryan UfkoGorillas (CBS)D212003-05-07USANo174 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm825,000$794,282$82,500$79,428$No825,000$--------825,000$--------No--------
Sasha PastujovGorillas (CBS)LW/RW212003-07-15USANo187 Lbs6 ft1NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,312,500$1,263,630$131,250$126,363$No1,312,500$--------1,312,500$--------No--------
Shai BuiumGorillas (CBS)D212003-03-26USANo220 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm1,500,000$1,444,149$150,000$144,415$No1,500,000$--------1,500,000$--------No--------
Tom HedbergGorillas (CBS)D251999-08-10SWENo179 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm787,500$758,178$78,750$75,818$No---------------------------
Tomas Suchanek (sur la masse salariale)Gorillas (CBS)G212003-04-30CZENo181 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm750,000$722,074$65,000$62,580$No---------------------------
Trevor ConnellyGorillas (CBS)LW182006-02-28USAYes165 Lbs5 ft11NoNoDraftNoNo32025-08-20FalseFalsePro & Farm1,500,000$1,444,149$150,000$144,415$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$722,074$75,000$72,207$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Vladimir TarasenkoGorillas (CBS)LW/RW331991-12-13RUSNo219 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm4,750,000$4,573,138$475,000$457,314$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
1Adam GaudetteAdam TambelliniJimmy Snuggerud28122
2Adam MascherinOtto KivenmakiFelix Unger Sorum28122
3Justin SourdifConnor KurthTrevor Connelly25122
4Sasha PastujovAidan DudasVladimir Tarasenko19122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Otto SalinHelge Grans35122
2Anttoni HonkaKyle Masters33122
3Shai BuiumRyan Ufko32122
4Otto SalinHelge Grans0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Adam GaudetteAdam TambelliniJimmy Snuggerud50122
2Adam MascherinOtto KivenmakiFelix Unger Sorum50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Otto SalinHelge Grans50122
2Anttoni HonkaKyle Masters50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Adam TambelliniAdam Gaudette50122
2Otto KivenmakiAdam Mascherin50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Otto SalinHelge Grans50122
2Anttoni HonkaKyle Masters50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Adam Tambellini50122Otto SalinHelge Grans50122
2Otto Kivenmaki50122Anttoni HonkaKyle Masters50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Adam TambelliniAdam Gaudette50122
2Otto KivenmakiAdam Mascherin50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Otto SalinHelge Grans50122
2Anttoni HonkaKyle Masters50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Adam GaudetteAdam TambelliniJimmy SnuggerudOtto SalinHelge Grans
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Adam GaudetteAdam TambelliniFelix Unger SorumOtto SalinHelge Grans
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Adam Mascherin, Justin Sourdif, Sasha PastujovAdam Mascherin, Justin SourdifAdam Mascherin
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Kyle Masters, Shai Buium, Ryan UfkoKyle MastersKyle Masters, Shai Buium
Tirs de pénalité
Adam Tambellini, Otto Kivenmaki, Connor Kurth, Adam Gaudette, Adam Mascherin
Gardien
#1 : , #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
1Bills11000000752110000007520000000000021.00071421002126038308843039574155240.00%7271.43%05111643.97%4110041.00%368144.44%834482387437
2Blood Miners11000000431110000004310000000000021.0004480021260373088430441237216116.67%6266.67%15111643.97%4110041.00%368144.44%834482387437
3Roadrunners1010000046-2000000000001010000046-200.00046100021260523088430331320255360.00%5340.00%05111643.97%4110041.00%368144.44%834482387437
4White Wolves11000000541000000000001100000054121.00058130021260343088430401132165120.00%10100.00%05111643.97%4110041.00%368144.44%834482387437
Total431000002018222000000118321100000910-160.75020325200212601613088430156411637721733.33%19763.16%15111643.97%4110041.00%368144.44%834482387437
_Since Last GM Reset431000002018222000000118321100000910-160.75020325200212601613088430156411637721733.33%19763.16%15111643.97%4110041.00%368144.44%834482387437
_Vs Conference431000002018222000000118321100000910-160.75020325200212601613088430156411637721733.33%19763.16%15111643.97%4110041.00%368144.44%834482387437
_Vs Division33100000131301200000043121100000910-161.0001318310021260123308843011736896216531.25%12558.33%15111643.97%4110041.00%368144.44%834482387437

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
46W2203252161156411637700
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
43100002018
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2200000118
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2110000910
Derniers 10 matchs
WLOTWOTL SOWSOL
310000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
21733.33%19763.16%1
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
308843021260
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
5111643.97%4110041.00%368144.44%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
834482387437


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
1075Americans-Gorillas-
1290Gorillas-White Wolves-
14103Gorillas-Bills-
16115Griffins-Gorillas-
19138Bulldogs-Gorillas-
20148Gorillas-Crunch-
23172Griffins-Gorillas-
26189Gorillas-White Wolves-
28202Bills-Gorillas-
30215Gorillas-Reign-
32228Gorillas-Rocket-
34241Saints-Gorillas-
36254Gorillas-Crunch-
38268Gorillas-Octopus-
40281Senators-Gorillas-
43302Gorillas-Silver Knights-
45311Admirals-Gorillas-
47328Gorillas-Senators-
49342Wolf Pack-Gorillas-
51359Gorillas-Eagles-
53375Rocket-Gorillas-
55393Gorillas-Roadrunners-
57406Gorillas-Norsemen-
58415Mountaineers-Gorillas-
61437Redhawks-Gorillas-
62446Gorillas-Grisards-
65460Gorillas-Eagles-
67474Reign-Gorillas-
69490Gorillas-Bills-
72507Eagles-Gorillas-
74524Gorillas-Phantoms-
76534Gorillas-Mountaineers-
77543Bills-Gorillas-
80560Gorillas-Rocket-
82574Whalers-Gorillas-
84591Gorillas-Reign-
86605Bills-Gorillas-
88618Gorillas-Blood Miners-
90630Gorillas-Mountaineers-
91640Americans-Gorillas-
94665Gorillas-White Wolves-
95672Blood Miners-Gorillas-
98696Gorillas-Saints-
100704Griffins-Gorillas-
102724Gorillas-Silver Knights-
104736Griffins-Gorillas-
106748Gorillas-Griffins-
109768Bulldogs-Gorillas-
112796Octopus-Gorillas-
115815Gorillas-Griffins-
117830White Wolves-Gorillas-
119846Gorillas-Wolves-
121862Blood Miners-Gorillas-
124880Gorillas-Bulldogs-
125893Roadrunners-Gorillas-
127907Gorillas-Blood Miners-
129926Bears-Gorillas-
132942Gorillas-Roadrunners-
134958Rams-Gorillas-
136971Gorillas-Redhawks-
138986Octopus-Gorillas-
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
Assistance5,00011,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
39 8000 - 100.00% 136,200$272,400$8000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
136,205$ 2,942,312$ 2,942,312$ 600,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
18,842$ 136,043$ 26 2

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
5,311,800$ 181 18,842$ 3,410,402$




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