Connexion

Wranglers
GP: 19 | W: 13 | L: 0 | OTL: 6 | P: 32
GF: 90 | GA: 68 | PP%: 28.92% | PK%: 80.65%
DG: Darren Mongrain | Morale : 50 | Moyenne d’équipe : 68
Prochain matchs #310 vs Firebirds
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Centre de jeu
Eagles
11-8-1, 23pts
7
FINAL
6 Wranglers
13-0-6, 32pts
Team Stats
L1StreakW1
5-4-0Home Record6-0-3
6-4-1Away Record7-0-3
6-3-1Last 10 Games6-0-4
3.85Buts par match 4.74
3.95Buts contre par match 3.58
18.42%Pourcentage en avantage numérique28.92%
73.91%Pourcentage en désavantage numérique80.65%
Wranglers
13-0-6, 32pts
5
FINAL
2 Texas Stars
11-7-1, 23pts
Team Stats
W1StreakL1
6-0-3Home Record6-3-1
7-0-3Away Record5-4-0
6-0-4Last 10 Games6-4-0
4.74Buts par match 3.37
3.58Buts contre par match 3.42
28.92%Pourcentage en avantage numérique26.83%
80.65%Pourcentage en désavantage numérique75.00%
Wranglers
13-0-6, 32pts
2022-11-29
Firebirds
8-11-0, 16pts
Statistiques d’équipe
W1SéquenceL3
6-0-3Fiche domicile4-5-0
7-0-3Fiche visiteur4-6-0
6-0-410 derniers matchs5-5-0
4.74Buts par match 2.95
3.58Buts contre par match 3.11
28.92%Pourcentage en avantage numérique15.49%
80.65%Pourcentage en désavantage numérique81.82%
Silver Knights
7-9-3, 17pts
2022-12-01
Wranglers
13-0-6, 32pts
Statistiques d’équipe
L3SéquenceW1
3-4-2Fiche domicile6-0-3
4-5-1Fiche visiteur7-0-3
4-4-210 derniers matchs6-0-4
3.74Buts par match 4.74
4.42Buts contre par match 3.58
24.29%Pourcentage en avantage numérique28.92%
67.03%Pourcentage en désavantage numérique80.65%
Condors
9-8-1, 19pts
2022-12-03
Wranglers
13-0-6, 32pts
Statistiques d’équipe
L1SéquenceW1
5-4-1Fiche domicile6-0-3
4-4-0Fiche visiteur7-0-3
4-6-010 derniers matchs6-0-4
3.06Buts par match 4.74
2.61Buts contre par match 3.58
19.44%Pourcentage en avantage numérique28.92%
84.21%Pourcentage en désavantage numérique80.65%
Meneurs d'équipe
Victoires
Joel Hofer
9
Pourcentage d’arrêts
Maxime Lagace
0.939

Statistiques d’équipe
Buts pour
90
4.74 GFG
Tirs pour
763
40.16 Avg
Pourcentage en avantage numérique
28.9%
24 GF
Début de zone offensive
42.7%
Buts contre
68
3.58 GAA
Tirs contre
663
34.89 Avg
Pourcentage en désavantage numérique
80.6%
12 GA
Début de la zone défensive
37.7%
Information d’équipe

Directeur généralDarren Mongrain
EntraîneurMitch Love
DivisionPACIFIQUE
ConférenceOUEST
CapitaineNathan Gerbe
Assistant #1Anthony Bitetto
Assistant #2Jonny Brodzinski


Informations de l’aréna

Capacité3,000
Assistance1,669
Billets de saison300


Information formation

Équipe Pro32
Équipe Mineure20
Limite contact 52 / 55
Espoirs35


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
1Dillon Dube0XX100.006634837170828568706772636864650507102442,686,000$
2Cody Glass0X100.007240886785879065786763647263680507102311,713,333$
3Jonny Brodzinski (A)0X100.006738816680857964756567686469730507102911,228,000$
4Maxim Mamin0X100.00733991678279756670656765686769050710272925,000$
5Nathan Gerbe (C)0XXX100.00793680676179806669676359658478050700351975,000$
6Brett Ritchie0X100.008778756190768062596163586271690507002911,034,000$
7Wade Allison0X100.007838826281857264616366586365670506902511,137,500$
8Jakob Pelletier0X100.00623680696385846858676661686263050690213863,333$
9Justin Danforth0X100.00663586676481826571636866636970050690291875,000$
10John Hayden0X100.007981625988768158675759665468700506802711,112,000$
11Fredrik Karlstrom0X100.00683892638276886672655861596466050680241795,000$
12Matthew Phillips0X100.005734936660898465736362566564660506602421,154,000$
13Nikolai Knyzhov0X100.00813878658480776430675869506566050710243862,000$
14Steven Kampfer0X100.00773594647278736230706173528273050710341950,000$
15Braden Schneider0X100.007139866781839066306559645363650507002131,325,000$
16Anthony Bitetto (A)0X99.69723977618179766230666163537274050690321900,000$
17Ben Thomas0X100.00563595647580756230615663506965050660261750,000$
18Tobias Geisser0X100.00783791568578935630555358456365050660231837,778$
Rayé
1Cole Schneider0X100.006638936280859363556465596472770507003211,031,000$
2Eetu Tuulola0X100.00767178578576875659555861576466050660242831,000$
3Walker Duehr0X100.006939855982798258615958605765670506602521,000,000$
4Joseph Gambardella0X100.00613886597074875866595756586971050640281750,000$
5Emilio Pettersen0X100.00573791586676865761585954586264050630221925,000$
6Maxim Cajkovic0X100.00603694556975655458555653556163050610212925,000$
7Dmitry Zavgorodniy0X100.00563692576466675651545352596264050590221780,000$
8Alexander Peters0X100.00714365569068635930585461456668050650261750,000$
9Philip Kemp0X100.007134895384617852305352564563650506202321,021,000$
MOYENNE D’ÉQUIPE99.9669428562777880625562616158676805067
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
1Joel Hofer100.0074757485737274737274736267050750225910,833$
2Arvid Soderblom100.00727776797170727170727163690507302341,500,000$
Rayé
1Maxime Lagace100.00757476787473757473757470830507602911,235,000$
2Dylan Ferguson100.0073676875727173727173726471050730241907,000$
3Jet Greaves100.00717475727069717069717061650507102141,300,000$
MOYENNE D’ÉQUIPE100.007373747872717372717372647105074
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mitch Love70717465575488CAN3750$


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
1Dillon DubeWranglers (CAL)C/LW19151732920253192295916.30%335718.8074112764000004131.71%4100011.7903000212
2Steven KampferWranglers (CAL)D1981826-1100263650153016.00%3943422.883692164000047210.00%000101.2000000410
3Jakob PelletierWranglers (CAL)LW1971421520113570206110.00%331416.530331864000001138.10%2100001.3401000201
4Matthew PhillipsWranglers (CAL)C17881670062137132221.62%424014.15325845000040038.46%15600001.3300000030
5Anthony BitettoWranglers (CAL)D1641115614053162382517.39%1931919.972571252000233100.00%000000.9400000101
6Cody GlassWranglers (CAL)C1878159135315850163714.00%631117.300116190000150054.38%43400000.9622010021
7Maxim MaminWranglers (CAL)C167815600223246123315.22%322514.111232110002150055.17%23200001.3301000201
8Nathan GerbeWranglers (CAL)C/LW/RW1921214-51003748507374.00%334718.311781263000050051.93%49300000.8000000011
9Ben ThomasWranglers (CAL)D19212140206143512295.71%1637319.682352064000015000.00%000000.7500000002
10Braden SchneiderWranglers (CAL)D193101378023293810317.89%2442222.243252566011048000.00%000000.6200000100
11Wade AllisonWranglers (CAL)RW192111306033224117384.88%233217.491671467000000047.83%2300000.7800000010
12Jonny BrodzinskiWranglers (CAL)C19651150014447217438.33%634318.060005150004503050.38%13300000.6402000011
13Justin DanforthWranglers (CAL)RW73696208922112313.64%111917.12000000111140038.46%1300001.5000000020
14John HaydenWranglers (CAL)C19257-21002518257148.00%321411.26000010000440037.50%2400000.6500000010
15Fredrik KarlstromWranglers (CAL)C194371004262862614.29%220010.57000051011370249.44%26700000.7000000000
16Brett RitchieWranglers (CAL)RW19347-49558133616218.33%126814.111341045000071065.38%2600000.5200100011
17Nikolai KnyzhovWranglers (CAL)D1933681805420264711.54%2037319.6400037000140110.00%000000.3200000200
18Tobias GeisserWranglers (CAL)D192356260407105220.00%1332517.1500000000021000.00%000000.3100000000
19Eetu TuulolaWranglers (CAL)RW122133201110135915.38%11018.48000000000170053.85%1300000.5900000000
20Philip KempWranglers (CAL)D3011140711000.00%34816.040000000000000.00%000000.4200000000
21Emilio PettersenWranglers (CAL)LW7000100015130.00%0466.7000000000000075.00%400000.0000000000
Statistiques d’équipe totales ou en moyenne34390160250681381049449177023155011.69%172572116.682444681836581231142013650.64%188000110.8729110141411
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
1Joel HoferWranglers (CAL)139040.9123.0678500404560000.4449127011
2Arvid SoderblomWranglers (CAL)63020.8684.3032100231740000.0000612001
3Maxime LagaceWranglers (CAL)11000.9392.0060002330000.000010000
Statistiques d’équipe totales ou en moyenne2013060.9023.34116700656630000.44491919012


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 Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire restantSalaire moyenPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Alexander PetersWranglers (CAL)D261996-07-02No220 Lbs6 ft4NoNoNo1Pro & Farm750,000$576,612$750,000$0$0$NoLien
Anthony BitettoWranglers (CAL)D321990-07-15No210 Lbs6 ft1NoNoNo1Pro & Farm900,000$691,935$900,000$0$0$NoLien
Arvid SoderblomWranglers (CAL)G231999-08-19No180 Lbs6 ft3NoNoNo4Pro & Farm1,500,000$1,153,225$1,500,000$0$0$No1,500,000$1,500,000$1,500,000$Lien
Ben ThomasWranglers (CAL)D261996-05-28No187 Lbs6 ft1NoNoNo1Pro & Farm750,000$576,612$750,000$0$0$NoLien
Braden SchneiderWranglers (CAL)D212001-09-20No202 Lbs6 ft2NoNoNo3Pro & Farm1,325,000$1,018,682$700,000$0$0$No1,325,000$1,325,000$Lien
Brett RitchieWranglers (CAL)RW291993-07-01No220 Lbs6 ft4NoNoNo1Pro & Farm1,034,000$794,956$525,000$0$0$NoLien
Cody GlassWranglers (CAL)C231999-04-01No206 Lbs6 ft3NoNoNo1Pro & Farm1,713,333$1,317,239$863,335$0$0$NoLien
Cole SchneiderWranglers (CAL)LW321990-08-26No199 Lbs6 ft2NoNoNo1Pro & Farm1,031,000$792,650$800,000$0$0$NoLien
Dillon DubeWranglers (CAL)C/LW241998-07-20No187 Lbs5 ft11NoNoNo4Pro & Farm2,686,000$2,065,043$650,000$0$0$No2,686,000$2,686,000$2,686,000$Lien
Dmitry ZavgorodniyWranglers (CAL)RW222000-08-11No173 Lbs5 ft9NoNoNo1Pro & Farm780,000$599,677$780,000$0$0$NoLien
Dylan FergusonWranglers (CAL)G241998-09-20No189 Lbs6 ft1NoNoNo1Pro & Farm907,000$697,317$750,000$0$0$NoLien
Eetu TuulolaWranglers (CAL)RW241998-03-17No224 Lbs6 ft2NoNoNo2Pro & Farm831,000$638,887$650,000$0$0$No831,000$Lien
Emilio PettersenWranglers (CAL)LW222000-04-03No170 Lbs5 ft11NoNoNo1Pro & Farm925,000$711,155$925,000$0$0$NoLien
Fredrik KarlstromWranglers (CAL)C241998-01-12No195 Lbs6 ft3NoNoNo1Pro & Farm795,000$611,209$700,000$0$0$NoLien
Jakob PelletierWranglers (CAL)LW212001-03-07No160 Lbs5 ft9NoNoNo3Pro & Farm863,333$663,745$700,000$0$0$No863,333$863,333$Lien
Jet GreavesWranglers (CAL)G212001-03-30No170 Lbs6 ft0NoNoNo4Pro & Farm1,300,000$999,462$1,300,000$0$0$No1,300,000$1,300,000$1,300,000$Lien
Joel HoferWranglers (CAL)G222000-07-30No179 Lbs6 ft5NoNoNo5Pro & Farm910,833$700,264$910,833$0$0$No1,648,000$1,648,000$1,648,000$1,648,000$Lien
John HaydenWranglers (CAL)C271995-02-14No223 Lbs6 ft3NoNoNo1Pro & Farm1,112,000$854,924$1,125,000$0$0$NoLien
Jonny BrodzinskiWranglers (CAL)C291993-06-19No211 Lbs6 ft1NoNoNo1Pro & Farm1,228,000$944,107$700,000$0$0$NoLien
Joseph GambardellaWranglers (CAL)C281993-12-01No196 Lbs5 ft10NoNoNo1Pro & Farm750,000$576,612$750,000$0$0$NoLien
Justin DanforthWranglers (CAL)RW291993-03-15No180 Lbs5 ft9NoNoNo1Pro & Farm875,000$672,715$875,000$0$0$NoLien
Matthew PhillipsWranglers (CAL)C241998-04-06No140 Lbs5 ft7NoNoNo2Pro & Farm1,154,000$887,215$1,019,333$0$0$No1,154,000$Lien
Maxim CajkovicWranglers (CAL)RW212001-01-03No185 Lbs5 ft11NoNoNo2Pro & Farm925,000$711,155$700,000$0$0$No925,000$Lien
Maxim MaminWranglers (CAL)C271995-01-13No206 Lbs6 ft2NoNoNo2Pro & Farm925,000$711,155$700,000$0$0$No925,000$Lien
Maxime LagaceWranglers (CAL)G291993-01-12No190 Lbs6 ft2NoNoNo1Pro & Farm1,235,000$949,489$600,000$0$0$NoLien
Nathan GerbeWranglers (CAL)C/LW/RW351987-07-24No176 Lbs5 ft4NoNoNo1Pro & Farm975,000$749,596$975,000$0$0$NoLien
Nikolai KnyzhovWranglers (CAL)D241998-03-20No218 Lbs6 ft2NoNoNo3Pro & Farm862,000$662,720$796,667$0$0$No862,000$862,000$Lien
Philip KempWranglers (CAL)D231999-02-12No202 Lbs6 ft3NoNoNo2Pro & Farm1,021,000$784,962$600,000$0$0$No1,021,000$Lien
Steven KampferWranglers (CAL)D341988-09-24No198 Lbs5 ft11NoNoNo1Pro & Farm950,000$730,376$950,000$0$0$NoLien
Tobias GeisserWranglers (CAL)D231999-02-13No201 Lbs6 ft4NoNoNo1Pro & Farm837,778$644,098$700,000$0$0$NoLien
Wade AllisonWranglers (CAL)RW251997-10-14No205 Lbs6 ft2NoNoNo1Pro & Farm1,137,500$874,529$1,137,500$0$0$NoLien
Walker DuehrWranglers (CAL)RW251997-11-23No210 Lbs6 ft2NoNoNo2Pro & Farm1,000,000$768,817$1,000,000$0$0$No1,000,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3225.59194 Lbs6 ft11.781,062,149$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dillon DubeCody GlassWade Allison30122
2Jonny BrodzinskiNathan GerbeJustin Danforth27122
3Jakob PelletierMaxim MaminMatthew Phillips27122
4John HaydenFredrik KarlstromBrett Ritchie16122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nikolai KnyzhovBraden Schneider34122
2Tobias GeisserSteven Kampfer34122
3Anthony BitettoBen Thomas32122
4Steven KampferNikolai Knyzhov0122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dillon DubeNathan GerbeWade Allison50014
2Jakob PelletierMaxim MaminMatthew Phillips50014
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Anthony BitettoSteven Kampfer50014
2Ben ThomasBraden Schneider50014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jonny BrodzinskiJohn Hayden50041
2Fredrik KarlstromJustin Danforth50041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nikolai KnyzhovSteven Kampfer50041
2Braden SchneiderBen Thomas50041
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1John Hayden50050Steven KampferNikolai Knyzhov50050
2Fredrik Karlstrom50050Ben ThomasBraden Schneider50050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Dillon DubeJustin Danforth50113
2Nathan GerbeJonny Brodzinski50113
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nikolai KnyzhovSteven Kampfer50122
2Ben ThomasBraden Schneider50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dillon DubeCody GlassJustin DanforthNikolai KnyzhovSteven Kampfer
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
John HaydenFredrik KarlstromJonny BrodzinskiNikolai KnyzhovSteven Kampfer
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Cody Glass, Justin Danforth, Brett RitchieBrett Ritchie, John HaydenFredrik Karlstrom
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ben Thomas, Tobias Geisser, Braden SchneiderBen ThomasTobias Geisser, Braden Schneider
Tirs de pénalité
Dillon Dube, Maxim Mamin, Jakob Pelletier, Nathan Gerbe, Jonny Brodzinski
Gardien
#1 : Joel Hofer, #2 : Arvid Soderblom
Lignes d’attaque personnalisées en prolongation
Dillon Dube, Cody Glass, Jonny Brodzinski, Justin Danforth, Nathan Gerbe, Wade Allison, Wade Allison, Matthew Phillips, Jakob Pelletier, Brett Ritchie, Maxim Mamin
Lignes de défense personnalisées en prolongation
Steven Kampfer, Nikolai Knyzhov, Braden Schneider, Tobias Geisser, Ben Thomas


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
1Barracuda220000001165110000004131100000075241.0001117280039282147228021524730642210607342.86%5260.00%039978151.09%36269052.46%18836052.22%481335438142247127
2Canucks21001000743110000004221000100032141.00071219003928214702802152473066101250600.00%6266.67%039978151.09%36269052.46%18836052.22%481335438142247127
3Condors21000001761110000004221000000134-130.750713200039282147928021524730652312458112.50%6183.33%039978151.09%36269052.46%18836052.22%481335438142247127
4Eagles1000010067-11000010067-10000000000010.5006111700392821449280215247304310221400.00%110.00%039978151.09%36269052.46%18836052.22%481335438142247127
5Firebirds22000000954110000004221100000053241.000916250039282148628021524730661220506116.67%10190.00%039978151.09%36269052.46%18836052.22%481335438142247127
6Gulls20000101911-21000000156-11000010045-120.500915240039282148328021524730752412478450.00%6266.67%039978151.09%36269052.46%18836052.22%481335438142247127
7Reign21000100761110000003121000010045-130.7507132000392821486280215247306612175610330.00%5180.00%039978151.09%36269052.46%18836052.22%481335438142247127
8Silver Knights5300100129218210000011284320010001713490.900295382003928214201280215247301774839124291034.48%17288.24%039978151.09%36269052.46%18836052.22%481335438142247127
9Texas Stars11000000523000000000001100000052321.000510150039282143728021524730411014295240.00%60100.00%139978151.09%36269052.46%18836052.22%481335438142247127
Total19110023039068229600010242291310500220148399320.8429016025000392821476328021524730663171138482832428.92%621280.65%139978151.09%36269052.46%18836052.22%481335438142247127
_Since Last GM Reset19110023039068229600010242291310500220148399320.8429016025000392821476328021524730663171138482832428.92%621280.65%139978151.09%36269052.46%18836052.22%481335438142247127
_Vs Conference19110023039068229600010242291310500220148399320.8429016025000392821476328021524730663171138482832428.92%621280.65%139978151.09%36269052.46%18836052.22%481335438142247127
_Vs Division1710002203795920860000023622149400220143376290.8537913921800392821467728021524730579151122432742229.73%551180.00%039978151.09%36269052.46%18836052.22%481335438142247127

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1932W19016025076366317113848200
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
1911023039068
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
96001024229
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
105022014839
Derniers 10 matchs
WLOTWOTL SOWSOL
600301
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
832428.92%621280.65%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
280215247303928214
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
39978151.09%36269052.46%18836052.22%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
481335438142247127


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
1 - 2022-10-168Silver Knights5Wranglers4BLXXSommaire du match
4 - 2022-10-1932Wranglers6Silver Knights4AWSommaire du match
5 - 2022-10-2041Wranglers3Condors4ALXXSommaire du match
8 - 2022-10-2356Firebirds2Wranglers4BWSommaire du match
10 - 2022-10-2568Wranglers5Firebirds3AWSommaire du match
11 - 2022-10-2684Reign1Wranglers3BWSommaire du match
13 - 2022-10-2891Wranglers4Silver Knights3AWSommaire du match
16 - 2022-10-31112Wranglers7Barracuda5AWSommaire du match
19 - 2022-11-03122Silver Knights3Wranglers8BWSommaire du match
21 - 2022-11-05141Wranglers4Reign5ALXSommaire du match
23 - 2022-11-07153Barracuda1Wranglers4BWSommaire du match
24 - 2022-11-08162Wranglers3Canucks2AWXSommaire du match
28 - 2022-11-12188Canucks2Wranglers4BWSommaire du match
29 - 2022-11-13197Wranglers4Gulls5ALXSommaire du match
33 - 2022-11-17221Condors2Wranglers4BWSommaire du match
36 - 2022-11-20240Wranglers7Silver Knights6AWXSommaire du match
37 - 2022-11-21251Gulls6Wranglers5BLXXSommaire du match
39 - 2022-11-23272Eagles7Wranglers6BLXSommaire du match
43 - 2022-11-27296Wranglers5Texas Stars2AWSommaire du match
45 - 2022-11-29310Wranglers-Firebirds-
47 - 2022-12-01317Silver Knights-Wranglers-
49 - 2022-12-03337Condors-Wranglers-
50 - 2022-12-04345Wranglers-Silver Knights-
52 - 2022-12-06366W-B/Scranton Penguins-Wranglers-
58 - 2022-12-12395Wranglers-Moose-
59 - 2022-12-13402Phantoms-Wranglers-
62 - 2022-12-16429Firebirds-Wranglers-
64 - 2022-12-18446Wranglers-Bears-
65 - 2022-12-19455Wranglers-Roadrunners-
67 - 2022-12-21471Wolf Pack-Wranglers-
73 - 2022-12-27493Binghamton Senateurs-Wranglers-
76 - 2022-12-30519Iowa Wild-Wranglers-
78 - 2023-01-01530Wranglers-Thunderbirds-
80 - 2023-01-03541Wranglers-Canucks-
83 - 2023-01-06556Checkers-Wranglers-
85 - 2023-01-08574Wranglers-Canucks-
87 - 2023-01-10589Silver Knights-Wranglers-
89 - 2023-01-12605Wranglers-Eagles-
91 - 2023-01-14618Wranglers-Crunch-
92 - 2023-01-15630Condors-Wranglers-
94 - 2023-01-17651Phantoms-Wranglers-
96 - 2023-01-19665Wranglers-islanders-
98 - 2023-01-21673Wranglers-Condors-
100 - 2023-01-23689Wranglers-Silver Knights-
101 - 2023-01-24696Firebirds-Wranglers-
103 - 2023-01-26719Wranglers-Roadrunners-
104 - 2023-01-27730Thunderbirds-Wranglers-
106 - 2023-01-29750Wranglers-Americans-
108 - 2023-01-31764Admirals-Wranglers-
111 - 2023-02-03787Reign-Wranglers-
114 - 2023-02-06804Wranglers-Condors-
115 - 2023-02-07818Providence Bruins-Wranglers-
120 - 2023-02-12844Wranglers-Monsters-
121 - 2023-02-13854Barracuda-Wranglers-
126 - 2023-02-18884Texas Stars-Wranglers-
128 - 2023-02-20900Wranglers-Firebirds-
129 - 2023-02-21908Wranglers-Barracuda-
130 - 2023-02-22918Reign-Wranglers-
132 - 2023-02-24943Wranglers-Admirals-
134 - 2023-02-26951Canucks-Wranglers-
136 - 2023-02-28960Wranglers-Rockets-
138 - 2023-03-02978Firebirds-Wranglers-
139 - 2023-03-03990Wranglers-Rockets-
144 - 2023-03-081007Barracuda-Wranglers-
146 - 2023-03-101029Wranglers-Barracuda-
147 - 2023-03-111040Wranglers-Griffins-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-03-131048Roadrunners-Wranglers-
151 - 2023-03-151072Wranglers-IceHogs-
152 - 2023-03-161083Canucks-Wranglers-
154 - 2023-03-181092Wranglers-Marlies-
157 - 2023-03-211104Wranglers-Iowa Wild-
158 - 2023-03-221120IceHogs-Wranglers-
163 - 2023-03-271146Wranglers-Reign-
164 - 2023-03-281154Wolves-Wranglers-
166 - 2023-03-301178Moose-Wranglers-
170 - 2023-04-031202Wranglers-Reign-
171 - 2023-04-041207Gulls-Wranglers-
175 - 2023-04-081235Comets-Wranglers-
178 - 2023-04-111254Wranglers-Gulls-
180 - 2023-04-131271Gulls-Wranglers-
181 - 2023-04-141285Wranglers-Gulls-
183 - 2023-04-161297Comets-Wranglers-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4030
Assistance11,1803,838
Assistance PCT62.11%42.64%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
32 1669 - 55.62% 93,098$837,886$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 3,398,877$ 2,678,267$ 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
2,979,150$ 143 18,274$ 2,613,182$




Wranglers Leaders statistiques (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 (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