Connexion

Wranglers
GP: 47 | W: 23 | L: 23 | OTL: 1 | P: 47
GF: 158 | GA: 140 | PP%: 25.00% | PK%: 77.86%
DG: Guy Brisson | Morale : 49 | Moyenne d’équipe : 63
Prochains matchs #796 vs Barracuda
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Centre de jeu
Wranglers
23-23-1, 47pts
2
FINAL
1 Barracuda
20-25-6, 46pts
Team Stats
W2SéquenceW1
13-12-0Fiche domicile13-9-2
10-11-1Fiche domicile7-16-4
6-4-0Derniers 10 matchs2-7-1
3.36Buts par match 3.20
2.98Buts contre par match 3.65
25.00%Pourcentage en avantage numérique24.09%
77.86%Pourcentage en désavantage numérique70.34%
Firebirds
30-18-1, 61pts
2
FINAL
3 Wranglers
23-23-1, 47pts
Team Stats
L1SéquenceW2
17-6-1Fiche domicile13-12-0
13-12-0Fiche domicile10-11-1
6-4-0Derniers 10 matchs6-4-0
3.51Buts par match 3.36
3.14Buts contre par match 2.98
25.63%Pourcentage en avantage numérique25.00%
80.14%Pourcentage en désavantage numérique77.86%
Wranglers
23-23-1, 47pts
2023-12-10
Barracuda
20-25-6, 46pts
Statistiques d’équipe
W2SéquenceW1
13-12-0Fiche domicile13-9-2
10-11-1Fiche visiteur7-16-4
6-4-010 derniers matchs2-7-1
3.36Buts par match 3.20
2.98Buts contre par match 3.20
25.00%Pourcentage en avantage numérique24.09%
77.86%Pourcentage en désavantage numérique70.34%
Condors
15-29-5, 35pts
2023-12-11
Wranglers
23-23-1, 47pts
Statistiques d’équipe
L1SéquenceW2
10-13-2Fiche domicile13-12-0
5-16-3Fiche visiteur10-11-1
1-9-010 derniers matchs6-4-0
2.94Buts par match 3.36
3.82Buts contre par match 3.36
15.79%Pourcentage en avantage numérique25.00%
75.00%Pourcentage en désavantage numérique77.86%
Wranglers
23-23-1, 47pts
2023-12-14
Canucks
33-12-4, 70pts
Statistiques d’équipe
W2SéquenceW8
13-12-0Fiche domicile18-5-1
10-11-1Fiche visiteur15-7-3
6-4-010 derniers matchs8-2-0
3.36Buts par match 3.82
2.98Buts contre par match 3.82
25.00%Pourcentage en avantage numérique23.53%
77.86%Pourcentage en désavantage numérique82.07%
Meneurs d'équipe
Buts
Jeffrey Viel
17
Passes
Jeffrey Viel
31
Points
Jeffrey Viel
48
Plus/Moins
Joel Kellman
12
Victoires
Antoine Bibeau
18
Pourcentage d’arrêts
Antoine Bibeau
0.918

Statistiques d’équipe
Buts pour
158
3.36 GFG
Tirs pour
1376
29.28 Avg
Pourcentage en avantage numérique
25.0%
36 GF
Début de zone offensive
40.1%
Buts contre
140
2.98 GAA
Tirs contre
1405
29.89 Avg
Pourcentage en désavantage numérique
77.9%%
29 GA
Début de la zone défensive
40.4%
Informations de l'équipe

Directeur généralGuy Brisson
EntraîneurBrent Sutter
DivisionDivision Nord-Ouest
ConférenceConference 2
CapitaineAustin Strand
Assistant #1Otto Makinen
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,182
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure20
Limite contact 47 / 55
Espoirs26


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
1Ryan DzingelX100.0062458771717570706467686966687250516503111,200,000$
2Joel KellmanX100.0066458872677486686971687265614953586402911,000,000$
3Andrej NestrasilX100.0060419769747471707169677265605247616403211,400,000$
4Otto Makinen (A)X100.006345907268727272716869716448476039630252750,000$
5Jeffrey VielX100.007845597471717672626769736853466458630262900,000$
6Kristian ReichelX100.006745857269727270676768766348466064630252900,000$
7Kristopher FoucaultX100.007155836872717569616767686545454662620322800,000$
8Fredrik ForsbergX100.006051877670706867636362696054506358620262800,000$
9Brandon McmillanX100.006245916969717367716564676258494256620332800,000$
10Sergey AndronovX100.006143967073717069656666706445454224620342800,000$
11Eetu TuulolaX100.007256687073687169646869656047466053620252750,000$
12Tanner FritzX100.006245977070706969636668716650465026620322800,000$
13Markus NutivaaraX100.0061429370727487734574717061765351616602923,500,000$
14Samuel MorinX100.0072518472737161754564657454554759486502811,200,000$
15Austin Strand (C)X100.006946837275737272456762745651466651640261900,000$
16Jake WalmanX100.0067458072687374724571716960554757496402721,100,000$
17Brock BeukeboomX100.005842946775727470456766726248465046630311900,000$
18Andrew WelinskiX100.006044956974707169456767686550455346630302900,000$
Rayé
1Kirill Marchenko (R)X100.006545897271828472616676747450457042650233900,000$
2Cody AlmondX100.007153876974697668666665686351454242620341800,000$
3Tye McGinnX100.006045977073696769626366696454474623620332800,000$
4Oliver KylingtonX100.006346897470737167456863696061476626640261750,000$
5Joseph CecconiX100.006946857072736963456465665649466020620261750,000$
6Joni TuulolaX100.006548887071716958456460685749465719610271750,000$
MOYENNE D’ÉQUIPE100.00654687717172736958676770635448554563
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
1Antoine Bibeau100.007076758076818180817982595955676502911,300,000$
2Jason Missiaen100.007273738377767777787474656546596403311,400,000$
Rayé
1Harri Sateri100.007880787879748177788176495442366303311,000,000$
MOYENNE D’ÉQUIPE100.0073767580777780787978775859485464
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Brent Sutter79846468999946CAN605100,000$


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
1Jeffrey VielWranglers (Cal)LW47173148933511239119338714.29%673615.684131723116000011142.22%4500011.3000010624
2Kirill MarchenkoWranglers (Cal)RW4116213762012401203611013.33%668216.654711261020000261044.19%8600001.0800000140
3Samuel MorinWranglers (Cal)D477263310455684546143515.22%4991019.382241547011089000%000000.7200001013
4Kristian ReichelWranglers (Cal)LW4512213312140523912132999.92%569515.4616727115000000041.07%5600000.9500000011
5Joel KellmanWranglers (Cal)C47171532121954165106327316.04%873915.7254926121000065052.27%88000000.8700010214
6Markus NutivaaraWranglers (Cal)D476253138020447329308.22%3295920.4236933116000036010%000000.6500000101
7Ryan DzingelWranglers (Cal)RW44131225860323786206315.12%672416.47134151140001234054.76%8400000.6911000221
8Jake WalmanWranglers (Cal)D41517222340412837112313.51%3979019.282461037000159100%000000.5600000220
9Andrej NestrasilWranglers (Cal)C477152210006797429619.46%877516.4902223700041090053.36%101200000.5700000003
10Austin StrandWranglers (Cal)D4761521-216069486523389.23%60100121.30235271190000104010%000000.4200000011
11Otto MakinenWranglers (Cal)C4412719-5100356388225913.64%464914.765271886101194049.00%74700000.5900000121
12Andrew WelinskiWranglers (Cal)D3541519-51802419419219.76%3867119.184261040011056100%000000.5700000010
13Kristopher FoucaultWranglers (Cal)LW4710717-53715303176206613.16%457912.3300003000090150.00%3800000.5900102210
14Brock BeukeboomWranglers (Cal)D3121214916028243410305.88%4965121.021341365000065010%000000.4300000010
15Eetu TuulolaWranglers (Cal)RW4741014-10442058267717415.19%757912.32022010000000052.17%6900000.4800031001
16Oliver KylingtonWranglers (Cal)D3221113518044202213159.09%4060518.912461252000028010%000000.4300000000
17Cody AlmondWranglers (Cal)C357512060254351163113.73%546213.22000000003684044.18%55000000.5200000120
18Fredrik ForsbergWranglers (Cal)RW42538-44032326512457.69%658814.01000140003791034.69%4900000.2700000000
19Brandon McmillanWranglers (Cal)LW402681802321369395.56%957314.34000000000730046.51%4300000.2800000001
20Tanner FritzWranglers (Cal)RW143031005122191514.29%320314.52000410000080127.78%1800000.3001000000
21Tye McGinnWranglers (Cal)LW9022220328440%29710.8100000000070016.67%600000.4100000000
22Sergey AndronovWranglers (Cal)C15011-70001592130%116110.77000130000210042.79%20100000.1200000000
23Joni TuulolaWranglers (Cal)D2000000131000%14321.780001500004000%00000000000000
Statistiques d’équipe totales ou en moyenne8461572774345234050761775137640299811.41%3881388316.4136639926412101231389022749.41%388400010.6312154182121
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
1Antoine BibeauWranglers (Cal)2718800.9182.60154601678180111.00032621401
2Jason MissiaenWranglers (Cal)1631110.8743.359132051406000001520000
3Harri SateriWranglers (Cal)62400.8833.5235800211800000066000
Statistiques d’équipe totales ou en moyenne49232310.9012.96281821139140401134747401


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 Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Type Salaire actuel Plafond salarial Non Activé 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 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
Andrej NestrasilWranglers (Cal)C321991-02-22No211 Lbs6 ft2NoNoN/ANoNo1Pro & Farm1,400,000$0$0$No------------------Lien
Andrew WelinskiWranglers (Cal)D301993-04-27No212 Lbs6 ft2NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Antoine BibeauWranglers (Cal)G291994-05-01No213 Lbs6 ft3NoNoN/ANoNo1Pro & Farm1,300,000$0$0$No------------------Lien
Austin StrandWranglers (Cal)D261997-04-17No216 Lbs6 ft4NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Brandon McmillanWranglers (Cal)LW331990-03-22No189 Lbs5 ft10NoNoN/ANoNo2Pro & Farm800,000$0$0$No800,000$--------No--------Lien
Brock BeukeboomWranglers (Cal)D311992-04-01No220 Lbs6 ft2NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Cody AlmondWranglers (Cal)C341989-07-24No217 Lbs6 ft2NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Eetu TuulolaWranglers (Cal)RW251998-03-17No225 Lbs6 ft2NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------Lien
Fredrik ForsbergWranglers (Cal)RW261996-12-12No185 Lbs5 ft11NoNoN/ANoNo2Pro & Farm800,000$0$0$No800,000$--------No--------Lien
Harri SateriWranglers (Cal)G331989-12-29No205 Lbs6 ft1NoNoN/ANoNo1Pro & Farm1,000,000$0$0$No------------------Lien
Jake WalmanWranglers (Cal)D271996-02-20No170 Lbs6 ft1NoNoN/ANoNo2Pro & Farm1,100,000$0$0$No1,100,000$--------No--------Lien
Jason MissiaenWranglers (Cal)G331990-04-25No206 Lbs6 ft8NoNoN/ANoNo1Pro & Farm1,400,000$0$0$No------------------Lien
Jeffrey VielWranglers (Cal)LW261997-01-28No195 Lbs6 ft0NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Joel KellmanWranglers (Cal)C291994-05-25No190 Lbs6 ft0NoNoN/ANoNo1Pro & Farm1,000,000$0$0$No------------------Lien
Joni TuulolaWranglers (Cal)D271996-01-01No198 Lbs6 ft3NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Joseph CecconiWranglers (Cal)D261997-03-23No209 Lbs6 ft3NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Kirill MarchenkoWranglers (Cal)RW232000-07-21Yes197 Lbs6 ft3NoNoN/ANoNo3Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------Lien
Kristian ReichelWranglers (Cal)LW251998-06-11No188 Lbs6 ft2NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Kristopher FoucaultWranglers (Cal)LW321990-12-12No202 Lbs6 ft0NoNoN/ANoNo2Pro & Farm800,000$0$0$No800,000$--------No--------Lien
Markus NutivaaraWranglers (Cal)D291994-06-06No191 Lbs6 ft1NoNoN/ANoNo2Pro & Farm3,500,000$0$0$No3,500,000$--------No--------Lien
Oliver KylingtonWranglers (Cal)D261997-05-19No181 Lbs6 ft0NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Otto MakinenWranglers (Cal)C251998-05-21 08:33:17No178 Lbs6 ft1NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------Lien
Ryan DzingelWranglers (Cal)RW311992-03-09No190 Lbs6 ft0NoNoN/ANoNo1Pro & Farm1,200,000$0$0$No------------------Lien
Samuel MorinWranglers (Cal)D281995-07-12No202 Lbs6 ft6NoNoN/ANoNo1Pro & Farm1,200,000$0$0$No------------------Lien
Sergey AndronovWranglers (Cal)C341989-07-19No207 Lbs6 ft2NoNoN/ANoNo2Pro & Farm800,000$0$0$No800,000$--------No--------Lien
Tanner FritzWranglers (Cal)RW321991-08-20No192 Lbs5 ft11NoNoN/ANoNo2Pro & Farm800,000$0$0$No800,000$--------No--------Lien
Tye McGinnWranglers (Cal)LW331990-07-29No205 Lbs6 ft3NoNoN/ANoNo2Pro & Farm800,000$0$0$No800,000$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2729.07200 Lbs6 ft21.561,031,481$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jeffrey VielAndrej NestrasilTanner Fritz26122
2Kristian ReichelJoel KellmanRyan Dzingel25122
3Brandon McmillanOtto MakinenFredrik Forsberg25122
4Kristopher FoucaultSergey AndronovEetu Tuulola24122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Markus NutivaaraSamuel Morin33122
2Brock BeukeboomAndrew Welinski33122
3Austin StrandJake Walman33122
4Markus NutivaaraSamuel Morin1122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jeffrey VielOtto MakinenTanner Fritz50014
2Kristian ReichelJoel KellmanRyan Dzingel50014
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Markus NutivaaraAustin Strand50014
2Andrew WelinskiBrock Beukeboom50014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Andrej NestrasilFredrik Forsberg50041
2Sergey AndronovBrandon Mcmillan50041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake WalmanSamuel Morin50140
2Brock BeukeboomAustin Strand50140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Andrej Nestrasil50050Markus NutivaaraSamuel Morin50140
2Otto Makinen50050Brock BeukeboomAustin Strand50140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Sergey AndronovRyan Dzingel50122
2Andrej NestrasilJoel Kellman50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Markus NutivaaraSamuel Morin50122
2Brock BeukeboomAustin Strand50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Kristian ReichelOtto MakinenTanner FritzMarkus NutivaaraBrock Beukeboom
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jeffrey VielAndrej NestrasilRyan DzingelSamuel MorinAustin Strand
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Fredrik Forsberg, Brandon Mcmillan, Sergey AndronovEetu Tuulola, Sergey AndronovTanner Fritz
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Brock Beukeboom, Jake Walman, Andrew WelinskiJake WalmanJake Walman, Andrew Welinski
Tirs de pénalité
Tanner Fritz, Ryan Dzingel, Andrej Nestrasil, Joel Kellman, Otto Makinen
Gardien
#1 : Antoine Bibeau, #2 : Jason Missiaen


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
1Admirals440000002191222000000114722000000105581.000213859006150461152475442458310429266421838.10%12191.67%0780155750.10%766156848.85%37375949.14%11027501106352617305
2Americans11000000422110000004220000000000021.000481200615046134475442458322102174375.00%10100.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
3Barracuda321000001073211000008621100000021140.667101929006150461994754424583752522476233.33%10190.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
4Bears11000000716000000000001100000071621.0007121900615046136475442458336141512200.00%5180.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
5BruinsF10000010541100000105410000000000021.00057120061504612847544245834538182150.00%40100.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
6Canucks1010000012-11010000012-10000000000000.000123006150461224754424583262618400.00%30100.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
7Checkers1010000034-11010000034-10000000000000.00036900615046116475442458332911162150.00%3233.33%0780155750.10%766156848.85%37375949.14%11027501106352617305
8Condors1010000035-2000000000001010000035-200.000347006150461334754424583309219200.00%10100.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
9Crunch1010000034-11010000034-10000000000000.000358006150461314754424583277415400.00%2150.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
10Eagles21100000761211000007610000000000020.50071219006150461404754424583731016304125.00%8275.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
11Firebirds11000000321110000003210000000000021.00035800615046131475442458320124165240.00%20100.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
12Griffins413000001214-21100000031230300000913-420.250122234006150461129475442458312427196111218.18%7271.43%0780155750.10%766156848.85%37375949.14%11027501106352617305
13Gulls41300000912-3211000005502020000047-320.25091423106150461100475442458314743387813430.77%13469.23%0780155750.10%766156848.85%37375949.14%11027501106352617305
14Icehogs3120000046-21010000004-42110000042220.3334812016150461814754424583812522439111.11%11463.64%0780155750.10%766156848.85%37375949.14%11027501106352617305
15Iowa Wild1010000035-21010000035-20000000000000.000347006150461254754424583297420200.00%2150.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
16Marlies1010000035-2000000000001010000035-200.0003690061504613447544245831514612300.00%3233.33%0780155750.10%766156848.85%37375949.14%11027501106352617305
17Monsters320001001192220000008531000010034-150.8331121320061504619047544245839428144613215.38%60100.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
18Moose22000000853110000004311100000042241.00081321006150461524754424583761622345120.00%11281.82%1780155750.10%766156848.85%37375949.14%11027501106352617305
19Phantoms2200000011650000000000022000000116541.000112031006150461614754424583521911366116.67%3233.33%0780155750.10%766156848.85%37375949.14%11027501106352617305
20Roadrunners2110000011651010000034-11100000082620.500111930006150461714754424583601914399333.33%7185.71%0780155750.10%766156848.85%37375949.14%11027501106352617305
21Rocket11000000211110000002110000000000021.0002350061504612247544245831679165240.00%20100.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
22StarsF2020000036-32020000036-30000000000000.000358006150461534754424583791344272150.00%7271.43%0780155750.10%766156848.85%37375949.14%11027501106352617305
23Thunderbirds30300000712-51010000012-120200000610-400.00071320006150461864754424583852315398112.50%40100.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
24Wolf Pack11000000431000000000001100000043121.0004711006150461274754424583369224100.00%10100.00%0780155750.10%766156848.85%37375949.14%11027501106352617305
25Wolves1010000034-1000000000001010000034-100.000347006150461234754424583218614100.00%3166.67%0780155750.10%766156848.85%37375949.14%11027501106352617305
Total4722230011015814018251212000107770722101100100817011470.5001582774351161504611376475442458314053883427611443625.00%1312977.86%1780155750.10%766156848.85%37375949.14%11027501106352617305
_Since Last GM Reset4722230011015814018251212000107770722101100100817011470.5001582774351161504611376475442458314053883427611443625.00%1312977.86%1780155750.10%766156848.85%37375949.14%11027501106352617305
_Vs Conference3313190010010299318810000005350315590010049490270.409102181283116150461981475442458310072602425311042524.04%911880.22%0780155750.10%766156848.85%37375949.14%11027501106352617305
_Vs Division1014000002628-2613000001715240100000913-420.1002644701061504612854754424583298917217830826.67%29582.76%0780155750.10%766156848.85%37375949.14%11027501106352617305

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4747W21582774351376140538834276111
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4722230110158140
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
25121200107770
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
22101101008170
Derniers 10 matchs
WLOTWOTL SOWSOL
540010
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1443625.00%1312977.86%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
47544245836150461
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
780155750.10%766156848.85%37375949.14%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
11027501106352617305


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 - 2023-08-253Wranglers4Griffins5ALSommaire du match
2 - 2023-08-2617Wranglers3Condors5ALSommaire du match
5 - 2023-08-2929StarsF2Wranglers1BLSommaire du match
7 - 2023-08-3149Monsters2Wranglers4BWSommaire du match
9 - 2023-09-0266Wranglers3Icehogs0AWSommaire du match
11 - 2023-09-0481Wranglers3Monsters4ALXSommaire du match
13 - 2023-09-0694Barracuda3Wranglers6BWSommaire du match
15 - 2023-09-08114Wranglers1Gulls2ALSommaire du match
16 - 2023-09-09122Wranglers4Admirals2AWSommaire du match
18 - 2023-09-11131Admirals3Wranglers5BWSommaire du match
21 - 2023-09-14159Gulls3Wranglers1BLSommaire du match
24 - 2023-09-17178Thunderbirds2Wranglers1BLSommaire du match
26 - 2023-09-19198Wranglers8Roadrunners2AWSommaire du match
27 - 2023-09-20205Wranglers3Thunderbirds5ALSommaire du match
30 - 2023-09-23220Griffins1Wranglers3BWSommaire du match
33 - 2023-09-26245Roadrunners4Wranglers3BLSommaire du match
36 - 2023-09-29268Monsters3Wranglers4BWSommaire du match
40 - 2023-10-03294Moose3Wranglers4BWSommaire du match
42 - 2023-10-05310Wranglers3Wolves4ALSommaire du match
44 - 2023-10-07323Wranglers3Gulls5ALSommaire du match
45 - 2023-10-08335Checkers4Wranglers3BLSommaire du match
48 - 2023-10-11356Wranglers7Bears1AWSommaire du match
50 - 2023-10-13368Barracuda3Wranglers2BLSommaire du match
53 - 2023-10-16391Admirals1Wranglers6BWSommaire du match
56 - 2023-10-19416Wranglers6Admirals3AWSommaire du match
58 - 2023-10-21427Eagles3Wranglers2BLSommaire du match
60 - 2023-10-23446Wranglers4Wolf Pack3AWSommaire du match
61 - 2023-10-24457Eagles3Wranglers5BWSommaire du match
64 - 2023-10-27472Wranglers2Griffins4ALSommaire du match
67 - 2023-10-30491Crunch4Wranglers3BLSommaire du match
70 - 2023-11-02514Gulls2Wranglers4BWSommaire du match
72 - 2023-11-04521Wranglers3Marlies5ALSommaire du match
75 - 2023-11-07545Wranglers7Phantoms3AWSommaire du match
76 - 2023-11-08553Canucks2Wranglers1BLSommaire du match
80 - 2023-11-12579Rocket1Wranglers2BWSommaire du match
82 - 2023-11-14600Wranglers3Griffins4ALSommaire du match
84 - 2023-11-16611StarsF4Wranglers2BLSommaire du match
86 - 2023-11-18634Wranglers1Icehogs2ALSommaire du match
87 - 2023-11-19640Wranglers3Thunderbirds5ALSommaire du match
89 - 2023-11-21650Icehogs4Wranglers0BLSommaire du match
92 - 2023-11-24673Americans2Wranglers4BWSommaire du match
94 - 2023-11-26686Wranglers4Moose2AWSommaire du match
95 - 2023-11-27702Wranglers4Phantoms3AWSommaire du match
97 - 2023-11-29713Iowa Wild5Wranglers3BLSommaire du match
100 - 2023-12-02737BruinsF4Wranglers5BWXXSommaire du match
104 - 2023-12-06765Wranglers2Barracuda1AWSommaire du match
105 - 2023-12-07772Firebirds2Wranglers3BWSommaire du match
108 - 2023-12-10796Wranglers-Barracuda-
109 - 2023-12-11803Condors-Wranglers-
112 - 2023-12-14821Wranglers-Canucks-
113 - 2023-12-15836Canucks-Wranglers-
116 - 2023-12-18856Wranglers-Eagles-
118 - 2023-12-20869Iowa Wild-Wranglers-
120 - 2023-12-22884Wranglers-Moose-
122 - 2023-12-24899Griffins-Wranglers-
123 - 2023-12-25911Wranglers-Eagles-
126 - 2023-12-28926Wranglers-Monsters-
127 - 2023-12-29934Wranglers-StarsF-
129 - 2023-12-31948Americans-Wranglers-
132 - 2024-01-03968Wranglers-Reign-
133 - 2024-01-04974StarsF-Wranglers-
136 - 2024-01-07999Condors-Wranglers-
139 - 2024-01-101025Wranglers-Silver Knights-
140 - 2024-01-111032Silver Knights-Wranglers-
144 - 2024-01-151058Icehogs-Wranglers-
145 - 2024-01-161067Wranglers-Iowa Wild-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2024-01-201090Wranglers-Silver Knights-
150 - 2024-01-211097Islanders-Wranglers-
153 - 2024-01-241119Wranglers-Condors-
154 - 2024-01-251127PenguinsF-Wranglers-
157 - 2024-01-281146Wranglers-Canucks-
158 - 2024-01-291155Wranglers-Iowa Wild-
159 - 2024-01-301157Wranglers-Roadrunners-
161 - 2024-02-011174Roadrunners-Wranglers-
162 - 2024-02-021188Wranglers-StarsF-
163 - 2024-02-031190Wranglers-Reign-
165 - 2024-02-051206Silver Knights-Wranglers-
167 - 2024-02-071220Wranglers-SenatorsF-
170 - 2024-02-101241Thunderbirds-Wranglers-
172 - 2024-02-121253Wranglers-Comets-
177 - 2024-02-171279Reign-Wranglers-
181 - 2024-02-211310Reign-Wranglers-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3618
Assistance37,06917,493
Assistance PCT74.14%69.97%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
16 2182 - 72.75% 95,663$2,391,569$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,647,818$ 2,785,000$ 2,785,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,589,560$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,530,604$ 76 15,852$ 1,204,752$




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