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

Wranglers
GP: 12 | W: 8 | L: 4 | OTL: 0 | P: 16
GF: 37 | GA: 32 | PP%: 20.93% | PK%: 82.22%
DG: Stephane Blanchette | Morale : 70 | Moyenne d’équipe : 66
Prochains matchs #198 vs Silver Knight

Centre de jeu
Wranglers
8-4-0, 16pts
3
2 Barracuda
11-0-1, 23pts
Team Stats
L1SéquenceW2
5-1-0Fiche domicile5-0-1
3-3-0Fiche domicile6-0-0
6-4-0Derniers 10 matchs9-0-1
3.08Buts par match 3.17
2.67Buts contre par match 1.50
20.93%Pourcentage en avantage numérique3.85%
82.22%Pourcentage en désavantage numérique90.91%
Barracuda
11-0-1, 23pts
3
2 Wranglers
8-4-0, 16pts
Team Stats
W2SéquenceL1
5-0-1Fiche domicile5-1-0
6-0-0Fiche domicile3-3-0
9-0-1Derniers 10 matchs6-4-0
3.17Buts par match 3.08
1.50Buts contre par match 2.67
3.85%Pourcentage en avantage numérique20.93%
90.91%Pourcentage en désavantage numérique82.22%
Silver Knight
5-4-3, 13pts
Jour 28
Wranglers
8-4-0, 16pts
Statistiques d’équipe
L1SéquenceL1
4-1-1Fiche domicile5-1-0
1-3-2Fiche visiteur3-3-0
4-4-210 derniers matchs6-4-0
3.00Buts par match 3.08
2.58Buts contre par match 3.08
19.57%Pourcentage en avantage numérique20.93%
86.79%Pourcentage en désavantage numérique82.22%
Wranglers
8-4-0, 16pts
Jour 30
Stars
5-6-1, 11pts
Statistiques d’équipe
L1SéquenceW2
5-1-0Fiche domicile4-1-0
3-3-0Fiche visiteur1-5-1
6-4-010 derniers matchs5-5-0
3.08Buts par match 2.58
2.67Buts contre par match 2.58
20.93%Pourcentage en avantage numérique21.95%
82.22%Pourcentage en désavantage numérique78.85%
Wranglers
8-4-0, 16pts
Jour 32
Silver Knight
5-4-3, 13pts
Statistiques d’équipe
L1SéquenceL1
5-1-0Fiche domicile4-1-1
3-3-0Fiche visiteur1-3-2
6-4-010 derniers matchs4-4-2
3.08Buts par match 3.00
2.67Buts contre par match 3.00
20.93%Pourcentage en avantage numérique19.57%
82.22%Pourcentage en désavantage numérique86.79%
Meneurs d'équipe
Buts
Kole Lind
6
Passes
Kole Lind
7
Points
Kole Lind
13
Plus/Moins
Justin Hryckowian
7
Victoires
Eetu Makiniemi
8
Pourcentage d’arrêts
Eetu Makiniemi
0.898

Statistiques d’équipe
Buts pour
37
3.08 GFG
Tirs pour
326
27.17 Avg
Pourcentage en avantage numérique
20.9%
9 GF
Début de zone offensive
41.2%
Buts contre
32
2.67 GAA
Tirs contre
299
24.92 Avg
Pourcentage en désavantage numérique
82.2%%
8 GA
Début de la zone défensive
39.5%
Informations de l'équipe

Directeur généralStephane Blanchette
EntraîneurKirk Muller
DivisionPacific
ConférenceConference Ouest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,478
Billets de saison300


Informations de la formation

Équipe Pro28
Équipe Mineure20
Limite Contrat48 / 99
Espoirs43


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
1Justin Hryckowian0XX100.0071428669728289668268657164666742706802531,556,000$
2Nathan Smith0X97.0092479266747967747965726262747559706802832,100,000$
3Matthew Seminoff (R)0XX100.005832687060777668556968666962687870660222900,000$
4Lleyton Roed (R)0XX100.005830716960757765577062686664687570650242900,000$
5Zack Ostapchuk0XX100.008053756589768763766059665663657570650232900,000$
6Noah Philp0XX100.0075757666766973657566686465706757706502811,225,000$
7Bennett Schimek (R)0XXX100.005832736961687369457663695955587870650232900,000$
8Julien Gauthier0XX100.0073289958837281595862616461767550706402931,399,000$
9Trey Fix-Wolansky0X100.0056189962716667605567706766747439706402711,286,000$
10Grant Porter0XXX100.005630736758687367457662685857587570640241900,000$
11Wyatt Bongiovanni0XX100.00634270656375776365646466647068807064N02731,150,000$
12David Gustafsson0X100.0044269965777077638063615762727257706302611,195,000$
13Cole Reinhardt0X100.0087835460777384594862606363676355706302641,245,000$
14Samuel Poulin0XX100.0088877159798691536453546359707273706202521,203,000$
15Zach Whitecloud0X100.0078398959808988572964537054797532706802931,998,000$
16Reilly Walsh0X100.0072659566748385673068576051637552706602731,595,000$
17Declan Carlile0X100.0083797668746273603066627062706846706602621,525,000$
18Luke Prokop0X100.008884936593656652255451695263636570650241900,000$
19John Parker-Jones0XX100.0099984959855967525356566458656541706302621,174,000$
20Zach Bookman0X100.005632736258677359457055705257597470620241835,000$
Rayé
1Kole Lind0XX97.0052199770737572716176676567737266706802811,665,000$
2Stephane Blanchette0XX100.00565174698163705557555561606363777060N2252575,000$
3Joe Carroll0XX100.0069688067755977565051556457656266706002531,101,000$
4Wyatt Kaiser0X100.0064348270718868673080546756686667706702431,781,000$
5Brandon Chabrier0X100.00573770605865736045715167525558707061N0243650,000$
MOYENNE D’ÉQUIPE99.76694979657372766254656066606667627064
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
1Jack Lafontaine0100.006768728073838281837676747472707602832,130,000$
2Eetu Makiniemi099.006969707672838584837473758153707602731,950,000$
3Carl Lindbom (R)0100.00747172657673737677707162637370710232900,000$
Rayé
MOYENNE D’ÉQUIPE99.6770697174748080808173737073667074
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Kirk Muller82896384999919CAN602900,000$


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
1Kole LindWranglers (CAL)LW/RW11671330012239103415.38%125623.321126400000361047.25%9100001.0102000301
2Justin HryckowianWranglers (CAL)C/LW12371078015252773211.11%424520.450337350001250050.60%25100000.8112000001
3Matthew SeminoffWranglers (CAL)C/RW12358160820349298.82%124620.582138400000170040.00%2500000.6512000020
4Zach WhitecloudWranglers (CAL)D12167740129101610.00%1630225.19011442000138100%000000.4600000010
5Reilly WalshWranglers (CAL)D12167060810113119.09%1225621.34022432000032000%000000.5500000000
6Bennett SchimekWranglers (CAL)C/LW/RW12347-22081629121610.34%117814.87123517000031137.66%7700000.7811000010
7Noah PhilpWranglers (CAL)C/RW12246-280177314226.45%220016.71224833000001037.50%1600000.6000000001
8Trey Fix-WolanskyWranglers (CAL)RW12314-100162471212.50%01038.6100000000000137.50%800000.7700000000
9Zach BookmanWranglers (CAL)D12044-5000126020%919015.8601100011115000%000000.4200000000
10Nathan SmithWranglers (CAL)C7314-28026151971715.79%315722.521013221011271050.53%19000000.5102000001
11Grant PorterWranglers (CAL)C/LW/RW12044100410113130%0826.9100000000000031.43%3500000.9700000000
12Declan CarlileWranglers (CAL)D121341100311313267.69%1925921.61000633000230000%000000.3100000010
13Lleyton RoedWranglers (CAL)C/LW12123-1008112311214.35%316613.85011216000040043.75%1600000.3600000010
14Luke ProkopWranglers (CAL)D7213018025372428.57%1114520.79101318000016000%000000.4100000000
15David GustafssonWranglers (CAL)C121122000141325.00%0231.9800001000051061.11%1800001.6900000010
16Julien GauthierWranglers (CAL)LW/RW12112-1006511499.09%014612.20000000000110036.36%1100000.2700000000
17Cole ReinhardtWranglers (CAL)LW1211204012441025.00%0413.4400000000030066.67%300000.9700000000
18Wyatt KaiserWranglers (CAL)D5022400223120%211923.9901121900009000%000000.3300000001
19Zack OstapchukWranglers (CAL)C/LW12112-3602511921511.11%216713.99000016000050050.62%16200000.2400000100
20John Parker-JonesWranglers (CAL)RW/D12202-512046562233.33%817514.601012300002000%000000.2300000100
21Samuel PoulinWranglers (CAL)LW/RW12000000731020%0393.2900000000030050.00%40000000000000
22Wyatt BongiovanniWranglers (CAL)C/LW12000140354120%1494.1100000000000060.98%410000000000000
Statistiques d’équipe totales ou en moyenne24635619659602652153269026010.74%95355414.45915246037511262916248.31%94800000.5439000575
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
1Eetu MakiniemiWranglers (CAL)118300.8982.6067000292850000.8899110100
2Jack LafontaineWranglers (CAL)10100.7863.00600031400000111000
Statistiques d’équipe totales ou en moyenne128400.8932.63730003229900091211100


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
Bennett SchimekWranglers (CAL)C/LW/RW232003-04-15USAYes187 Lbs6 ft0NoNoFree AgentNoNo22026-06-18FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Brandon ChabrierWranglers (CAL)D242002-08-19USANo185 Lbs6 ft0YesNoFree AgentNoNo32026-08-23FalseFalsePro & Farm650,000$0$0$No650,000$650,000$-------650,000$650,000$-------YesYes-------
Carl LindbomWranglers (CAL)G232003-05-20SWEYes190 Lbs6 ft1NoNoFree AgentNoNo22026-06-05FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Cole ReinhardtWranglers (CAL)LW262000-02-01CANNo212 Lbs6 ft1NoNoFree AgentNoNo42025-09-01FalseFalsePro & Farm1,245,000$0$0$No1,245,000$1,245,000$1,245,000$------1,245,000$1,245,000$1,245,000$------NoNoNo------
David GustafssonWranglers (CAL)C262000-04-11SWENo205 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm1,195,000$0$0$No---------------------------
Declan CarlileWranglers (CAL)D262000-05-18USANo195 Lbs6 ft2NoNoN/ANoNo22025-05-25FalseFalsePro & Farm1,525,000$0$0$No1,525,000$--------1,525,000$--------No--------
Eetu MakiniemiWranglers (CAL)G271999-04-19FINNo190 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm1,950,000$0$0$No1,950,000$1,950,000$-------1,950,000$1,950,000$-------NoNo-------
Grant PorterWranglers (CAL)C/LW/RW242002-02-21USANo181 Lbs6 ft0NoNoFree AgentNoNo12026-07-04FalseFalsePro & Farm900,000$0$0$No---------------------------
Jack LafontaineWranglers (CAL)G281998-01-06CANNo212 Lbs6 ft3NoNoFree AgentNoNo32025-08-22FalseFalsePro & Farm2,130,000$0$0$No2,130,000$2,130,000$-------2,130,000$2,130,000$-------NoNo-------
Joe CarrollWranglers (CAL)LW/RW252001-02-01CANNo198 Lbs6 ft3NoNoFree AgentNoNo32026-05-31FalseFalsePro & Farm1,101,000$0$0$No1,101,000$1,101,000$-------1,101,000$1,101,000$-------NoNo-------
John Parker-JonesWranglers (CAL)RW/D262000-04-07CANNo234 Lbs6 ft7NoNoN/ANoNo22025-05-25FalseFalsePro & Farm1,174,000$0$0$No1,174,000$--------1,174,000$--------No--------
Julien GauthierWranglers (CAL)LW/RW291997-10-15CANNo232 Lbs6 ft4NoNoN/ANoNo32026-05-31FalseFalsePro & Farm1,399,000$0$0$No1,399,000$1,399,000$-------1,399,000$1,399,000$-------NoNo-------
Justin HryckowianWranglers (CAL)C/LW252001-02-23CANNo106 Lbs4 ft0NoNoFree AgentNoNo32026-05-31FalseFalsePro & Farm1,556,000$0$0$No1,556,000$1,556,000$-------1,556,000$1,556,000$-------NoNo-------
Kole LindWranglers (CAL)LW/RW281998-10-16CANNo185 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm1,665,000$0$0$No---------------------------
Lleyton RoedWranglers (CAL)C/LW242002-08-08USAYes179 Lbs6 ft0NoNoFree AgentNoNo22026-06-05FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Luke ProkopWranglers (CAL)D242002-05-06CANNo104 Lbs4 ft0NoNoFree AgentNoNo12025-05-25FalseFalsePro & Farm900,000$0$0$No---------------------------
Matthew SeminoffWranglers (CAL)C/RW222003-12-27CANYes187 Lbs5 ft11NoNoFree AgentNoNo22026-06-05FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Nathan SmithWranglers (CAL)C281998-10-18USANo195 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm2,100,000$0$0$No2,100,000$2,100,000$-------2,100,000$2,100,000$-------NoNo-------
Noah PhilpWranglers (CAL)C/RW281998-08-31CANNo200 Lbs6 ft3NoNoTrade2025-05-30NoNo12024-10-16FalseFalsePro & Farm1,225,000$0$0$No---------------------------
Reilly WalshWranglers (CAL)D271999-04-21USANo194 Lbs6 ft0NoNoN/ANoNo3FalseFalsePro & Farm1,595,000$0$0$No1,595,000$1,595,000$-------1,595,000$1,595,000$-------NoNo-------
Samuel PoulinWranglers (CAL)LW/RW252001-02-25CANNo224 Lbs6 ft2NoNoN/ANoNo22025-05-25FalseFalsePro & Farm1,203,000$0$0$No1,203,000$--------1,203,000$--------No--------
Stephane BlanchetteWranglers (CAL)C/LW252001-07-10CANNo219 Lbs6 ft7YesNoN/ANoNo2FalseFalsePro & Farm575,000$0$0$No575,000$--------575,000$--------Yes--------
Trey Fix-WolanskyWranglers (CAL)RW271999-05-26CANNo190 Lbs5 ft7NoNoN/ANoNo1FalseFalsePro & Farm1,286,000$0$0$No---------------------------
Wyatt BongiovanniWranglers (CAL)C/LW271999-07-24USANo100 Lbs4 ft0YesNoFree AgentNoNo32026-08-22FalseFalsePro & Farm1,150,000$0$0$No1,150,000$1,150,000$-------1,150,000$1,150,000$-------YesYes-------
Wyatt KaiserWranglers (CAL)D242002-07-31USANo181 Lbs6 ft0NoNoN/ANoNo32026-05-31FalseFalsePro & Farm1,781,000$0$0$No1,781,000$1,781,000$-------1,781,000$1,781,000$-------NoNo-------
Zach BookmanWranglers (CAL)D242002-03-29USANo185 Lbs5 ft11NoNoFree AgentNoNo12026-06-05FalseFalsePro & Farm835,000$0$0$No---------------------------
Zach WhitecloudWranglers (CAL)D291996-11-28CANNo225 Lbs6 ft2NoNoTrade2025-08-17NoNo32026-05-31FalseFalsePro & Farm1,998,000$0$0$No1,998,000$1,998,000$-------1,998,000$1,998,000$-------NoNo-------
Zack OstapchukWranglers (CAL)C/LW232003-05-29CANNo208 Lbs6 ft3NoNoTrade2026-08-01NoNo22025-05-27FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2825.61189 Lbs5 ft112.211,272,786$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Justin HryckowianNathan SmithMatthew Seminoff40122
2Zack OstapchukBennett SchimekNoah Philp30122
3Wyatt BongiovanniLleyton RoedGrant Porter20122
4Julien GauthierDavid GustafssonTrey Fix-Wolansky10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zach WhitecloudDeclan Carlile40122
2Reilly WalshLuke Prokop30122
3John Parker-JonesZach Bookman20122
4Zach WhitecloudDeclan Carlile10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Justin HryckowianNathan SmithMatthew Seminoff60122
2Zack OstapchukBennett SchimekNoah Philp40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zach WhitecloudDeclan Carlile60122
2Reilly WalshLuke Prokop40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Nathan SmithJustin Hryckowian60122
2Matthew SeminoffBennett Schimek40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zach WhitecloudDeclan Carlile60122
2Reilly WalshLuke Prokop40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Nathan Smith60122Zach WhitecloudDeclan Carlile60122
2Justin Hryckowian40122Reilly WalshLuke Prokop40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Nathan SmithJustin Hryckowian60122
2Matthew SeminoffBennett Schimek40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zach WhitecloudDeclan Carlile60122
2Reilly WalshLuke Prokop40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Justin HryckowianNathan SmithMatthew SeminoffZach WhitecloudDeclan Carlile
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Justin HryckowianNathan SmithMatthew SeminoffZach WhitecloudDeclan Carlile
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Cole Reinhardt, Samuel Poulin, Lleyton RoedCole Reinhardt, Samuel PoulinLleyton Roed
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
John Parker-Jones, Zach Bookman, Reilly WalshJohn Parker-JonesZach Bookman, Reilly Walsh
Tirs de pénalité
Nathan Smith, Justin Hryckowian, Matthew Seminoff, Bennett Schimek, Noah Philp
Gardien
#1 : Jack Lafontaine, #2 : Carl Lindbom, #3 : Eetu Makiniemi


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
TotalDomicile Visiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT RI
1Barracuda201000105501010000023-11000001032120.50057120013118649102981181736111855400.00%90100.00%118938449.22%18336949.59%8618047.78%2921982809215880
2Canucks20100010770100000104311010000034-120.500710170013118671102981181753181651500.00%8187.50%018938449.22%18336949.59%8618047.78%2921982809215880
3Condors21100000550110000004221010000013-220.500591400131186581029811817511510368112.50%3233.33%018938449.22%18336949.59%8618047.78%2921982809215880
4Eagles21001000862100010005411100000032141.00081523001311863910298118173918124811436.36%5180.00%018938449.22%18336949.59%8618047.78%2921982809215880
5Gulls21001000743100010004311100000031241.0007121900131186611029811817541922428337.50%11372.73%018938449.22%18336949.59%8618047.78%2921982809215880
6Reign1010000023-1000000000001010000023-100.0002460013118622102981181741111015300.00%50100.00%018938449.22%18336949.59%8618047.78%2921982809215880
7Silver Knight10001000321100010003210000000000021.000347001311862610298118172538184125.00%4175.00%018938449.22%18336949.59%8618047.78%2921982809215880
Total1234030203732561103010221756230001015150160.667376198001311863261029811817299959626543920.93%45882.22%118938449.22%18336949.59%8618047.78%2921982809215880
_Since Last GM Reset1234030203732561103010221756230001015150160.667376198001311863261029811817299959626543920.93%45882.22%118938449.22%18336949.59%8618047.78%2921982809215880
_Vs Conference1234030203732561103010221756230001015150160.667376198001311863261029811817299959626543920.93%45882.22%118938449.22%18336949.59%8618047.78%2921982809215880

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1216L1376198326299959626500
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
123430203732
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
61130102217
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
62300101515
Derniers 10 matchs
WLOTWOTL SOWSOL
242020
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
43920.93%45882.22%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
1029811817131186
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
18938449.22%18336949.59%8618047.78%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2921982809215880


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
18Wranglers3Eagles2WSommaire du match
319Silver Knight2Wranglers3WXSommaire du match
643Wranglers1Condors3LSommaire du match
858Condors2Wranglers4WSommaire du match
1175Wranglers3Canucks4LSommaire du match
1391Canucks3Wranglers4WXXSommaire du match
15103Wranglers2Reign3LSommaire du match
17121Eagles4Wranglers5WXSommaire du match
20130Wranglers3Gulls1WSommaire du match
22149Gulls3Wranglers4WXSommaire du match
23155Wranglers3Barracuda2WXXSommaire du match
26179Barracuda3Wranglers2LSommaire du match
28198Silver Knight-Wranglers-
30213Wranglers-Stars-
32223Wranglers-Silver Knight-
34239Wranglers-Rockets-
36249Wranglers-Condors-
37256Bruins-Wranglers-
41278Wranglers-Comets-
42286Bears-Wranglers-
45311Wranglers-IceHogs-
46319Monsters-Wranglers-
49336Wranglers-Admirals-
51349Senators-Wranglers-
53365Wranglers-Wolves-
55377Wranglers-Phantoms-
56384Thunderbirds-Wranglers-
61413Griffins-Wranglers-
63428Wranglers-Americans-
66446Wolf Pack-Wranglers-
68458Wranglers-Senators-
69472Wranglers-Moose-
71479Firebird-Wranglers-
74499Wranglers-Hammers-
75511Roadrunners-Wranglers-
79535Wranglers-Barracuda-
80543Crunch-Wranglers-
83567Wranglers-Monsters-
84575Barracuda-Wranglers-
87598Wranglers-Roadrunners-
89607Wranglers-Bears-
90616Phantoms-Wranglers-
93640Admirals-Wranglers-
96656Wranglers-Checkers-
98671Condors-Wranglers-
100687Wranglers-Bruins-
102703Wolves-Wranglers-
105724Wranglers-Thunderbirds-
106735Comets-Wranglers-
109752Wranglers-Canucks-
111767Eagles-Wranglers-
113782Wranglers-Silver Knight-
116796Wranglers-Wild-
117800Gulls-Wranglers-
120820Wranglers-Eagles-
121830Americans-Wranglers-
124857Wranglers-Penguins-
125862Canucks-Wranglers-
127881Wranglers-Marlies-
129894Moose-Wranglers-
132921Wranglers-Wolf Pack-
134927Checkers-Wranglers-
137944Wranglers-Firebird-
140960Hammers-Wranglers-
143988Stars-Wranglers-
145994Wranglers-Reign-
1461003Wranglers-Gulls-
1491024Reign-Wranglers-
1521044Wranglers-Crunch-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1541056Reign-Wranglers-
1591087Penguins-Wranglers-
1641117Wild-Wranglers-
1661131Wranglers-Griffins-
1691150Marlies-Wranglers-
1741183IceHogs-Wranglers-
1831212Rockets-Wranglers-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets10099
Assistance6,3512,519
Assistance PCT52.93%41.98%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
32 1478 - 49.28% 219,646$1,317,876$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,160,284$ 7,127,600$ 7,127,600$ 900,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,028,952$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
7,028,672$ 158 43,392$ 6,855,936$




Wranglers 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

Wranglers 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

Wranglers 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

Wranglers 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

Wranglers 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