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Idaho Timberwolves
GP: 12 | W: 5 | L: 6 | OTL: 1 | P: 11
GF: 33 | GA: 40 | PP%: 22.73% | PK%: 76.92%
DG: Steeven Leblanc | Morale : 40 | Moyenne d’équipe : 61
Prochains matchs #205 vs San Jose Barracuda

Centre de jeu
Coachella Valley Firebirds
5-6-1, 11pts
4
2 Idaho Timberwolves
5-6-1, 11pts
Team Stats
W2SéquenceL2
3-3-0Fiche domicile4-2-0
2-3-1Fiche domicile1-4-1
4-5-1Derniers 10 matchs4-5-1
3.58Buts par match 2.75
4.00Buts contre par match 3.33
31.25%Pourcentage en avantage numérique22.73%
76.67%Pourcentage en désavantage numérique76.92%
Idaho Timberwolves
5-6-1, 11pts
1
5 Colorado Eagles
4-6-3, 11pts
Team Stats
L2SéquenceW1
4-2-0Fiche domicile3-2-1
1-4-1Fiche domicile1-4-2
4-5-1Derniers 10 matchs4-4-2
2.75Buts par match 3.08
3.33Buts contre par match 3.69
22.73%Pourcentage en avantage numérique16.13%
76.92%Pourcentage en désavantage numérique67.65%
San Jose Barracuda
5-6-1, 11pts
Jour 19
Idaho Timberwolves
5-6-1, 11pts
Statistiques d’équipe
L3SéquenceL2
3-2-1Fiche domicile4-2-0
2-4-0Fiche visiteur1-4-1
3-6-110 derniers matchs4-5-1
3.92Buts par match 2.75
4.08Buts contre par match 2.75
19.35%Pourcentage en avantage numérique22.73%
81.40%Pourcentage en désavantage numérique76.92%
Henderson Silver Knights
8-3-0, 16pts
Jour 21
Idaho Timberwolves
5-6-1, 11pts
Statistiques d’équipe
W2SéquenceL2
5-1-0Fiche domicile4-2-0
3-2-0Fiche visiteur1-4-1
8-2-010 derniers matchs4-5-1
3.27Buts par match 2.75
2.64Buts contre par match 2.75
4.55%Pourcentage en avantage numérique22.73%
71.43%Pourcentage en désavantage numérique76.92%
Idaho Timberwolves
5-6-1, 11pts
Jour 22
Calgary Wranglers
10-3-0, 20pts
Statistiques d’équipe
L2SéquenceOTW1
4-2-0Fiche domicile5-1-0
1-4-1Fiche visiteur5-2-0
4-5-110 derniers matchs8-2-0
2.75Buts par match 3.46
3.33Buts contre par match 3.46
22.73%Pourcentage en avantage numérique20.00%
76.92%Pourcentage en désavantage numérique86.21%
Meneurs d'équipe
Austin PoganskiButs
Austin Poganski
8
Caleb DesnoyersPasses
Caleb Desnoyers
10
Caleb DesnoyersPoints
Caleb Desnoyers
14
Ben McCartneyPlus/Moins
Ben McCartney
7
Nico DawsVictoires
Nico Daws
5
Nico DawsPourcentage d’arrêts
Nico Daws
0.898

Statistiques d’équipe
Buts pour
33
2.75 GFG
Tirs pour
359
29.92 Avg
Pourcentage en avantage numérique
22.7%
5 GF
Début de zone offensive
39.5%
Buts contre
40
3.33 GAA
Tirs contre
398
33.17 Avg
Pourcentage en désavantage numérique
76.9%%
6 GA
Début de la zone défensive
41.5%
Informations de l'équipe

Directeur généralSteeven Leblanc
DivisionPacific
ConférenceWest Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison0


Informations de la formation

Équipe Pro27
Équipe Mineure20
Limite contact 47 / 250
Espoirs24


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
1Caleb Desnoyers (R)X100.0056357372627570736875655868636590406601831,075,000$
2Cameron HebigX100.006038836369858464676362616468703640640291850,000$
3Austin PoganskiX100.006839826077768559636158606269744940630301750,000$
4Sammy WalkerX100.005936876566798563666056575966684740620271750,000$
5Andrew AgozzinoX100.007234856768666066585050595873752340610351750,000$
6Ben McCartneyX100.006242656071808159626059575864664840610251775,000$
7Sam LipkinX100.007040835779717256545555585662644940600231851,667$
8Jack RickettsX100.006738885876737156525557595467693740600261750,000$
9Michal Kunc (R)X100.006337935972737657545658555966684240600251750,000$
10Julian LutzX100.006537925874676856595753555461637440590221923,333$
11Noel Nordh (R)X100.007138955680648255505453575261636640590212935,000$
12Cole BeaudoinX100.005537645860646258645853585358607040580203941,667$
13Nick DeSimoneX100.0064369565798570643072595551717327406503121,000,000$
14Scott PerunovichX100.006233916965866568307360575368706140650281850,000$
15Kevin ConnautonX100.007244665681748255305754584775773340620361750,000$
16Artem DudaX100.006637945975737258306054564561637640610221950,000$
17Montana OnyebuchiX100.007561505684678155305453574565674240610261850,000$
18Terrell GoldsmithX100.005835605360605851305350584156583040560212936,111$
Rayé
1Miko MatikkaX100.007238955481656453555250565162646740580221870,000$
2Ryan McGregorX100.005735955668717554645755535666684740580271750,000$
3Vadim MorozX100.0048366058546058565360525051565830405602221,013,750$
4Jake LivingstoneX100.007541805784678456305554584666684240620271850,000$
5Robbie RussoX100.006439816173718657306353564772743840620331750,000$
6Lleyton MooreX100.005536945664636853305554514663654440570241750,000$
MOYENNE D’ÉQUIPE100.00643881607271735848595557536567494061
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
1Jaxson Stauber100.00756460787473757473757466775840670271775,000$
2Nico Daws100.007666628775747675747675667561406702521,100,000$
Rayé
1Matt Villalta100.00756160817473757473757466775640670271850,000$
MOYENNE D’ÉQUIPE100.0075646182747375747375746676584067
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Caleb DesnoyersIdaho Timberwolves (UTA)C12410145201455518477.84%128023.361017200002211048.52%37100001.0001000100
2Austin PoganskiIdaho Timberwolves (UTA)RW12841262016183651822.22%326522.08022120000080040.91%2200100.9101000111
3Scott PerunovichIdaho Timberwolves (UTA)D12371004024212191814.29%2029624.67123921000020000%000000.6800000021
4Ben McCartneyIdaho Timberwolves (UTA)LW121897203617306273.33%125821.58011320000010026.67%1500000.7000000000
5Cameron HebigIdaho Timberwolves (UTA)C12448-520103539133610.26%423219.392024180000260154.90%25500000.6901000011
6Nick DeSimoneIdaho Timberwolves (UTA)D121670100232513487.69%2429224.34112521000016100%000000.4800000000
7Artem DudaIdaho Timberwolves (UTA)D12066-30014139320%1318915.770000000004000%000000.6300000000
8Sammy WalkerIdaho Timberwolves (UTA)C12246-340632253128.00%018015.00000000000110047.39%21100000.6700000012
9Kevin ConnautonIdaho Timberwolves (UTA)D12235-2001510114918.18%1724620.51011317000020100%000000.4100000010
10Michal KuncIdaho Timberwolves (UTA)LW12314-3007142521912.00%016513.8200000000001050.00%800000.4800000010
11Andrew AgozzinoIdaho Timberwolves (UTA)LW12303-50017213713218.11%320617.21000217000041170.00%1000000.2900000100
12Montana OnyebuchiIdaho Timberwolves (UTA)D12033-3160381063190%2123619.70000216000015000%000000.2500000000
13Sam LipkinIdaho Timberwolves (UTA)LW12033-9402215217280%024420.39011217000000047.83%2300000.2500000000
14Terrell GoldsmithIdaho Timberwolves (UTA)D12101-34026762516.67%918515.420000000008000%000000.1100000000
15Jack RickettsIdaho Timberwolves (UTA)C12101-79516122410184.17%221217.7000000000000035.44%7900000.0900010000
16Julian LutzIdaho Timberwolves (UTA)LW12000100102000%0131.1600010000000050.00%40000000000000
17Cole BeaudoinIdaho Timberwolves (UTA)C12000100011100%0121.02000000000100050.00%60000000000000
18Noel NordhIdaho Timberwolves (UTA)LW12000-300342270%0524.3900010000000050.00%40000000000000
Statistiques d’équipe totales ou en moyenne216335992-26595288310359952949.19%118357016.5358134019400021715248.61%100800100.5203010375
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
1Nico DawsIdaho Timberwolves (UTA)125610.8983.4366500383730000.6673120200
2Jaxson StauberIdaho Timberwolves (UTA)30000.9601.02592012500000012000
Statistiques d’équipe totales ou en moyenne155610.9023.23725203939800031212200


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
Andrew AgozzinoIdaho Timberwolves (UTA)LW351991-01-03CANNo187 Lbs5 ft10NoNoAssign ManuallyNoNo12026-07-06FalseFalseFarm Only750,000$0$0$No---------------------------Lien / Lien NHL
Artem DudaIdaho Timberwolves (UTA)D222004-04-08RUSNo187 Lbs6 ft1NoNoAssign ManuallyNoNo12026-04-04FalseFalsePro & Farm950,000$0$0$No---------------------------Lien / Lien NHL
Austin PoganskiIdaho Timberwolves (UTA)RW301996-02-16USANo198 Lbs6 ft1NoNoAssign ManuallyNoNo12026-07-06FalseFalseFarm Only750,000$0$0$No---------------------------Lien / Lien NHL
Ben McCartneyIdaho Timberwolves (UTA)LW252001-07-13CANNo182 Lbs6 ft0NoNoAssign ManuallyNoNo12026-04-04FalseFalsePro & Farm775,000$0$0$No---------------------------Lien / Lien NHL
Caleb DesnoyersIdaho Timberwolves (UTA)C182007-11-04CANYes178 Lbs6 ft2NoNoDraftNoNo32026-07-06FalseFalsePro & Farm1,075,000$0$0$No1,075,000$1,075,000$-------1,075,000$1,075,000$-------NoNo-------Lien / Lien NHL
Cameron HebigIdaho Timberwolves (UTA)C291997-01-21CANNo184 Lbs5 ft11NoNoAssign ManuallyNoNo12026-07-02FalseFalsePro & Farm850,000$0$0$No---------------------------Lien / Lien NHL
Cole BeaudoinIdaho Timberwolves (UTA)C202006-04-24CANNo209 Lbs6 ft2NoNoDraftNoNo32026-07-23FalseFalsePro & Farm941,667$0$0$No941,667$941,667$-------941,667$941,667$-------NoNo-------Lien / Lien NHL
Jack RickettsIdaho Timberwolves (UTA)C261999-09-08CANNo194 Lbs6 ft1NoNoAssign ManuallyNoNo12026-07-06FalseFalseFarm Only750,000$0$0$No---------------------------Lien / Lien NHL
Jake LivingstoneIdaho Timberwolves (UTA)D271999-04-16CANNo205 Lbs6 ft3NoNoAssign ManuallyNoNo12026-07-01FalseFalsePro & Farm850,000$0$0$No---------------------------Lien / Lien NHL
Jaxson StauberIdaho Timberwolves (UTA)G271999-04-27USANo174 Lbs6 ft3NoNoAssign ManuallyNoNo12026-04-04FalseFalsePro & Farm775,000$0$0$No---------------------------Lien / Lien NHL
Julian LutzIdaho Timberwolves (UTA)LW222004-02-29DEUNo185 Lbs6 ft1NoNoAssign ManuallyNoNo12026-04-04FalseFalsePro & Farm923,333$0$0$No---------------------------Lien / Lien NHL
Kevin ConnautonIdaho Timberwolves (UTA)D361990-02-23CANNo205 Lbs6 ft2NoNoAssign ManuallyNoNo12026-07-06FalseFalseFarm Only750,000$0$0$No---------------------------Lien / Lien NHL
Lleyton MooreIdaho Timberwolves (UTA)D242002-02-27CANNo178 Lbs5 ft8NoNoAssign ManuallyNoNo12026-07-06FalseFalseFarm Only750,000$0$0$No---------------------------Lien / Lien NHL
Matt VillaltaIdaho Timberwolves (UTA)G271999-06-03CANNo190 Lbs6 ft3NoNoAssign ManuallyNoNo12026-07-04FalseFalsePro & Farm850,000$0$0$No---------------------------Lien / Lien NHL
Michal KuncIdaho Timberwolves (UTA)LW252000-10-31CZEYes187 Lbs6 ft0NoNoDraftNoNo12026-07-06FalseFalseFarm Only750,000$0$0$No---------------------------Lien / Lien NHL
Miko MatikkaIdaho Timberwolves (UTA)RW222003-10-26FINNo187 Lbs6 ft3NoNoAssign ManuallyNoNo12026-04-04FalseFalsePro & Farm870,000$0$0$No---------------------------Lien / Lien NHL
Montana OnyebuchiIdaho Timberwolves (UTA)D262000-03-08CANNo201 Lbs6 ft3NoNoAssign ManuallyNoNo12026-07-02FalseFalsePro & Farm850,000$0$0$No---------------------------Lien / Lien NHL
Nick DeSimoneIdaho Timberwolves (UTA)D311994-11-21USANo194 Lbs6 ft2NoNoAssign ManuallyNoNo22026-06-29FalseFalsePro & Farm1,000,000$0$0$No1,000,000$--------1,000,000$--------No--------Lien / Lien NHL
Nico DawsIdaho Timberwolves (UTA)G252000-12-22CANNo205 Lbs6 ft4NoNoTrade2026-07-08NoNo22026-07-01FalseFalsePro & Farm1,100,000$0$0$No1,100,000$--------1,100,000$--------No--------Lien / Lien NHL
Noel NordhIdaho Timberwolves (UTA)LW212005-01-25SWEYes196 Lbs6 ft2NoNoDraftNoNo22026-05-25FalseFalsePro & Farm935,000$0$0$No935,000$--------935,000$--------No--------Lien / Lien NHL
Robbie RussoIdaho Timberwolves (UTA)D331993-02-15USANo191 Lbs6 ft0NoNoAssign ManuallyNoNo12026-07-06FalseFalseFarm Only750,000$0$0$No---------------------------Lien / Lien NHL
Ryan McGregorIdaho Timberwolves (UTA)C271999-01-29CANNo168 Lbs6 ft0NoNoAssign ManuallyNoNo12026-07-06FalseFalseFarm Only750,000$0$0$No---------------------------Lien / Lien NHL
Sam LipkinIdaho Timberwolves (UTA)LW232003-01-03USANo192 Lbs6 ft2NoNoAssign ManuallyNoNo12026-04-04FalseFalsePro & Farm851,667$0$0$No---------------------------Lien / Lien NHL
Sammy WalkerIdaho Timberwolves (UTA)C271999-06-07USANo180 Lbs5 ft10NoNoAssign ManuallyNoNo12026-07-06FalseFalseFarm Only750,000$0$0$No---------------------------Lien / Lien NHL
Scott PerunovichIdaho Timberwolves (UTA)D281998-08-18USANo175 Lbs5 ft10NoNoAssign ManuallyNoNo12026-07-01FalseFalsePro & Farm850,000$0$0$No---------------------------Lien / Lien NHL
Terrell GoldsmithIdaho Timberwolves (UTA)D212005-05-13CANNo223 Lbs6 ft4NoNoDraftNoNo22026-07-23FalseFalsePro & Farm936,111$0$0$No936,111$--------936,111$--------No--------Lien / Lien NHL
Vadim MorozIdaho Timberwolves (UTA)RW222003-11-20NANo185 Lbs6 ft2NoNoDraftNoNo22026-07-23FalseFalsePro & Farm1,013,750$0$0$No1,013,750$--------1,013,750$--------No--------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2725.89190 Lbs6 ft11.33857,279$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ben McCartneyCaleb DesnoyersAustin Poganski40122
2Andrew AgozzinoCameron HebigSam Lipkin30122
3Michal KuncSammy WalkerJack Ricketts20122
4Sam LipkinJack RickettsNoel Nordh10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nick DeSimoneScott Perunovich40122
2Kevin ConnautonMontana Onyebuchi30122
3Artem DudaTerrell Goldsmith20122
4Nick DeSimoneScott Perunovich10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ben McCartneyCaleb DesnoyersAustin Poganski60122
2Andrew AgozzinoCameron HebigSam Lipkin40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nick DeSimoneScott Perunovich60122
2Kevin ConnautonMontana Onyebuchi40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Caleb DesnoyersCameron Hebig60122
2Austin PoganskiSammy Walker40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nick DeSimoneScott Perunovich60122
2Kevin ConnautonMontana Onyebuchi40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Caleb Desnoyers60122Nick DeSimoneScott Perunovich60122
2Cameron Hebig40122Kevin ConnautonMontana Onyebuchi40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Caleb DesnoyersCameron Hebig60122
2Austin PoganskiSammy Walker40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nick DeSimoneScott Perunovich60122
2Kevin ConnautonMontana Onyebuchi40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ben McCartneyCaleb DesnoyersAustin PoganskiNick DeSimoneScott Perunovich
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ben McCartneyCaleb DesnoyersAustin PoganskiNick DeSimoneScott Perunovich
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Julian Lutz, Noel Nordh, Cole BeaudoinJulian Lutz, Noel NordhCole Beaudoin
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Artem Duda, Terrell Goldsmith, Kevin ConnautonArtem DudaTerrell Goldsmith, Kevin Connauton
Tirs de pénalité
Caleb Desnoyers, Cameron Hebig, Austin Poganski, Sammy Walker, Ben McCartney
Gardien
#1 : Nico Daws, #2 : Jaxson Stauber


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
1Abbotsford Canucks21100000550110000003211010000023-120.5005914001958147117129108862191033400.00%5340.00%020939353.18%19241346.49%8918947.09%2781912898815880
2Bakersfield Condors1010000056-1000000000001010000056-100.000591400195813311712910884920641100.00%3233.33%020939353.18%19241346.49%8918947.09%2781912898815880
3Calgary Wranglers11000000312110000003120000000000021.00035800195813111712910884011417000%10100.00%020939353.18%19241346.49%8918947.09%2781912898815880
4Coachella Valley Firebirds1010000024-21010000024-20000000000000.000246001958132117129108841112203133.33%10100.00%020939353.18%19241346.49%8918947.09%2781912898815880
5Colorado Eagles2010100036-3100010002111010000015-420.500358001958152117129108855241055200.00%50100.00%020939353.18%19241346.49%8918947.09%2781912898815880
6Henderson Silver Knights1000000134-1000000000001000000134-110.50035800195814011712910883564205360.00%10100.00%020939353.18%19241346.49%8918947.09%2781912898815880
7Ontario Reign11000000523110000005230000000000021.000510150019581371171291088305623100.00%30100.00%020939353.18%19241346.49%8918947.09%2781912898815880
8Orlando Lizards2110000047-31010000015-41100000032120.5004610001958154117129108852154572150.00%20100.00%020939353.18%19241346.49%8918947.09%2781912898815880
9San Jose Barracuda1010000035-2000000000001010000035-200.00036900195813311712910883471522400.00%5180.00%020939353.18%19241346.49%8918947.09%2781912898815880
Total1246010013340-76320100016151614000011725-8110.458335992001958135911712910883981186128822522.73%26676.92%020939353.18%19241346.49%8918947.09%2781912898815880
_Since Last GM Reset1246010013340-76320100016151614000011725-8110.458335992001958135911712910883981186128822522.73%26676.92%020939353.18%19241346.49%8918947.09%2781912898815880
_Vs Conference1246010013340-76320100016151614000011725-8110.458335992001958135911712910883981186128822522.73%26676.92%020939353.18%19241346.49%8918947.09%2781912898815880
_Vs Division646010011820-233201000108231400001812-4110.91718345200195811891171291088202483711817423.53%15473.33%020939353.18%19241346.49%8918947.09%2781912898815880

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1211L23359923593981186128800
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
124610013340
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
63210001615
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
61400011725
Derniers 10 matchs
WLOTWOTL SOWSOL
450001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
22522.73%26676.92%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
117129108819581
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
20939353.18%19241346.49%8918947.09%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2781912898815880


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
112Idaho Timberwolves3San Jose Barracuda5LSommaire du match
221Colorado Eagles1Idaho Timberwolves2WXSommaire du match
337Idaho Timberwolves3Henderson Silver Knights4LXXSommaire du match
549Calgary Wranglers1Idaho Timberwolves3WSommaire du match
666Idaho Timberwolves5Bakersfield Condors6LSommaire du match
782Ontario Reign2Idaho Timberwolves5WSommaire du match
9106Idaho Timberwolves2Abbotsford Canucks3LSommaire du match
10118Abbotsford Canucks2Idaho Timberwolves3WSommaire du match
12138Orlando Lizards5Idaho Timberwolves1LSommaire du match
13148Idaho Timberwolves3Orlando Lizards2WSommaire du match
15168Coachella Valley Firebirds4Idaho Timberwolves2LSommaire du match
17188Idaho Timberwolves1Colorado Eagles5LSommaire du match
19205San Jose Barracuda-Idaho Timberwolves-
21228Henderson Silver Knights-Idaho Timberwolves-
22233Idaho Timberwolves-Calgary Wranglers-
24258Idaho Timberwolves-Coachella Valley Firebirds-
25265Idaho Timberwolves-Ontario Reign-
27279Bakersfield Condors-Idaho Timberwolves-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
3 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
0$ 2,314,653$ 2,314,653$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 12 0$ 0$




Idaho Timberwolves 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

Idaho Timberwolves 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

Idaho Timberwolves 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

Idaho Timberwolves 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

Idaho Timberwolves 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