Wild

GP: 26 | W: 14 | L: 11 | OTL: 1 | P: 29
GF: 92 | GA: 83 | PP%: 16.25% | PK%: 80.52%
DG: Kevin Bourassa | Morale : 53 | Moyenne d'Équipe : 60
Prochain matchs #399 vs Rampage
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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 SP
1Mike RibeiroX100.00605576757975826350606065559180154650
2Nicholas BaptisteXX100.00655576777572856850616564556059165640
3Steve BernierX100.00845560667975706250606060557273163620
4Andreas JohnssonX100.00605567766662696250596060556571157610
5Nikita ScherbakX100.00645576766762696650626360555050161610
6Lucas WallmarkX100.00665573766662696450606161555050163600
7Phil VaroneX100.00685576776762716050606060555050161600
8Christoph BertschyX100.00655565556762715550555555557272153560
9Brendan RanfordX100.00565555555758585550555555557274151550
10Peter Mueller (R)X100.00555555555555555550555555556666150540
11Gustav ForslingX100.00735592806478708225696579557676153710
12Joakim RyanX100.00735598686380708525666378557373166690
13Zach RedmondX100.00625561737575586225606061556161166620
14Brenden KichtonX100.00555559605959685925595959555353160570
15Darren DietzX100.00595555605555675525555555555353160550
16Rinat ValievX100.00555555605555665525555555555353139540
17Ben MarshallX100.00555556605656595625565656555353147540
18Maxime Lajoie (R)X100.00555555605555665525555555555555159540
19Ludwig BystromX100.00565555605555665525555555555353158540
Rayé
1Adam Brooks (R)X100.00565555555859605550555555555050134530
2Mackenzie MacEachern (R)X100.00565555555555555550555555555050130520
3Stepan Falkovsky (R)X100.00555555605555535525555555555555163540
MOYENNE D'ÉQUIPE100.0062556565636366613958586055616015559
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 SP
1Anders Nilsson100.0073716076867684797686557470161750
2Parker Milner100.0062635770696966656866556465157640
Rayé
1Kent Simpson100.0057796965666667676264556063131630
MOYENNE D'ÉQUIPE100.006471627074707270697255666615067
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Kirk Muller61807162807071CAN5032,675,000$


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'ÉquipePOS GP 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
1Joakim RyanWild (Min)D261224366460654488326713.64%5260723.3710616691350001105300.00%000001.1800000422
2Nicholas BaptisteWild (Min)C/RW2619153403557189146429413.01%555721.43279391240001382155.88%6800011.2200001353
3Andreas JohnssonWild (Min)LW26101323840113574196013.51%543916.8926826104000040043.75%3200001.0500000112
4Phil VaroneWild (Min)C2691322840123150155318.00%143316.6825717104000002153.53%53800001.0100000202
5Zach RedmondWild (Min)D2651318443553235517319.09%4950219.3222438109000092000.00%000010.7200001100
6Dominic MooreMinnesota WildC12411151014017314713318.51%429324.471349680001531073.01%28900001.0200000100
7Steve BernierWild (Min)RW2631215846089314817406.25%647318.21022121070000341072.41%2900000.6300000011
8Lucas WallmarkWild (Min)C266612426028466120399.84%129111.20000110000000049.45%27500000.8200000120
9Nikita ScherbakWild (Min)RW2611112410029315312491.89%430711.83011226000000055.56%1800000.7800000100
10Gemel SmithMinnesota WildC/LW/RW106612380322138102515.79%623923.952249630000372165.00%2000001.0000000111
11Victor MeteMinnesota WildD1154918011183472014.71%621519.575162955000033100.00%000000.8400000012
12Darren DietzWild (Min)D26437-1300307161325.00%102479.500000000000100.00%000000.5700000001
13Brenden KichtonWild (Min)D26156-13201613106610.00%142509.620000000001000.00%000000.4800000000
14Maxime LajoieWild (Min)D2632542402010111227.27%51335.130000000000000.00%000000.7500000000
15Gustav ForslingWild (Min)D30330003092110.00%66923.27022315000010000.00%000000.8600000000
16Adam BrooksWild (Min)C31010001220150.00%03712.4000000000060065.52%2900000.5400000100
17Stepan FalkovskyWild (Min)D25011000011300.00%0180.740001900000000.00%000001.0800000000
18Ludwig BystromWild (Min)D2601146016710130.00%81335.140000000000000.00%000000.1500000000
19Rinat ValievWild (Min)D3000000000000.00%020.930000000002000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne37989143232623361050444075321853511.82%182525313.86263763255937000341913357.78%129800020.8800002161314
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
1Parker MilnerWild (Min)1611500.9101.9496002313450210.0000160000
Stats d'équipe Total ou en Moyenne1611500.9101.9496002313450210.0000160000


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Adam BrooksWild (Min)C181998-05-06Yes176 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Anders NilssonWild (Min)G261990-03-19No227 Lbs6 ft5NoNoNo1Avec RestrictionPro & Farm2,500,000$0$0$No
Andreas JohnssonWild (Min)LW221994-11-20No181 Lbs5 ft10NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Ben MarshallWild (Min)D241992-08-30No161 Lbs5 ft9NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Brendan RanfordWild (Min)LW241992-05-02No190 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Brenden KichtonWild (Min)D241992-06-17No185 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Christoph BertschyWild (Min)C221994-04-05No189 Lbs5 ft10NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Darren DietzWild (Min)D231993-07-17No204 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Gustav ForslingWild (Min)D201996-06-12No183 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Joakim RyanWild (Min)D231993-06-17No185 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No500,000$
Kent SimpsonWild (Min)G241992-03-26No198 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Lucas WallmarkWild (Min)C211995-09-05No176 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Ludwig BystromWild (Min)D221994-07-20No174 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm500,000$0$0$No
Mackenzie MacEachernWild (Min)LW221994-03-09Yes190 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Maxime LajoieWild (Min)D191997-11-05Yes181 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Mike RibeiroWild (Min)C361980-02-09No177 Lbs6 ft0NoNoNo4Sans RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Nicholas BaptisteWild (Min)C/RW211995-08-04No203 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$No500,000$
Nikita ScherbakWild (Min)RW211995-12-30No175 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm900,000$0$0$No900,000$
Parker MilnerWild (Min)G261990-09-06No196 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Peter MuellerWild (Min)C281988-04-13Yes204 Lbs6 ft2NoNoNo4Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
Phil VaroneWild (Min)C261990-12-03No185 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Rinat ValievWild (Min)D211995-05-11No205 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$No500,000$
Stepan FalkovskyWild (Min)D201996-12-18Yes225 Lbs6 ft7NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Steve BernierWild (Min)RW311985-03-30No215 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Zach RedmondWild (Min)D281988-07-25No205 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2523.68192 Lbs6 ft12.48500,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nicholas Baptiste40122
2Andreas JohnssonPhil VaroneSteve Bernier30122
3Lucas WallmarkNikita Scherbak20122
4Nicholas Baptiste10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Joakim Ryan40122
2Zach Redmond30122
3Brenden KichtonDarren Dietz20122
4Maxime LajoieLudwig Bystrom10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nicholas Baptiste60122
2Andreas JohnssonPhil VaroneSteve Bernier40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Joakim Ryan60122
2Zach Redmond40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
2Nicholas BaptisteSteve Bernier40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Joakim Ryan60122
2Zach Redmond40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Joakim Ryan60122
240122Zach Redmond40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
2Nicholas BaptisteSteve Bernier40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Joakim Ryan60122
2Zach Redmond40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nicholas BaptisteJoakim Ryan
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nicholas BaptisteJoakim Ryan
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nikita Scherbak, Lucas Wallmark, Nikita Scherbak, Lucas Wallmark
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , Brenden Kichton, Brenden Kichton
Tirs de Pénalité
, , Nicholas Baptiste, Steve Bernier, Andreas Johnsson
Gardien
#1 : , #2 :


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
LigueDomicileVisiteur
# 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
1Admirals30201000710-32010100056-11010000024-220.333712190038233017324625127638328544916212.50%24387.50%041882550.67%29766544.66%20641649.52%695515572171292152
2Condors22000000918220000009180000000000041.00091524013823301542462512763422231389333.33%120100.00%041882550.67%29766544.66%20641649.52%695515572171292152
3Eagles41300000619-132110000045-120200000214-1220.250611170038233018524625127631264066753425.88%331069.70%041882550.67%29766544.66%20641649.52%695515572171292152
4Griffins3210000012662200000012571010000001-140.6671222340038233018124625127635612366814214.29%17288.24%041882550.67%29766544.66%20641649.52%695515572171292152
5IceHogs330000001596110000006422200000095461.0001526410038233019724625127637116366114535.71%17476.47%041882550.67%29766544.66%20641649.52%695515572171292152
6Moose43000100241014220000001431121000100107370.87524406400382330119124625127637218389025520.00%17288.24%041882550.67%29766544.66%20641649.52%695515572171292152
7Stars42200000131031100000031231200000109140.50013243701382330112924625127637333519636616.67%20385.00%041882550.67%29766544.66%20641649.52%695515572171292152
Total26131101100928391494010005840181247001003443-9290.5589216025212382330177624625127636112103465211602616.25%1543080.52%041882550.67%29766544.66%20641649.52%695515572171292152
9Wolves30300000618-1220200000515-101010000013-200.00061016103823301662462512763884134441218.33%14657.14%041882550.67%29766544.66%20641649.52%695515572171292152
_Since Last GM Reset26131101100928391494010005840181247001003443-9290.5589216025212382330177624625127636112103465211602616.25%1543080.52%041882550.67%29766544.66%20641649.52%695515572171292152
_Vs Conference221011010006873-5127401000443771037000002436-12220.5006812018812382330158524625127635391923084311352115.56%1372879.56%041882550.67%29766544.66%20641649.52%695515572171292152

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2629L19216025277661121034652112
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
26131111009283
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
149410005840
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
124701003443
Derniers 10 Matchs
WLOTWOTL SOWSOL
360100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1602616.25%1543080.52%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
24625127633823301
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
41882550.67%29766544.66%20641649.52%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
695515572171292152


Derniers Match 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
3 - 2018-09-076Moose2Wild7WSommaire du Match
5 - 2018-09-0925Moose1Wild7WSommaire du Match
10 - 2018-09-1439Stars1Wild3WSommaire du Match
17 - 2018-09-2178Wild5Stars0WSommaire du Match
18 - 2018-09-2291Wild1Stars3LSommaire du Match
24 - 2018-09-28114Eagles2Wild4WSommaire du Match
25 - 2018-09-29128Eagles3Wild0LSommaire du Match
31 - 2018-10-05142Wild0Griffins1LSommaire du Match
32 - 2018-10-06160Wild4IceHogs2WSommaire du Match
33 - 2018-10-07170IceHogs4Wild6WSommaire du Match
36 - 2018-10-10175Wild5IceHogs3WSommaire du Match
37 - 2018-10-11179Condors1Wild3WSommaire du Match
39 - 2018-10-13202Condors0Wild6WSommaire du Match
43 - 2018-10-17221Admirals3Wild4WXSommaire du Match
45 - 2018-10-19232Admirals3Wild1LSommaire du Match
46 - 2018-10-20246Wild1Wolves3LSommaire du Match
50 - 2018-10-24261Wild2Admirals4LSommaire du Match
52 - 2018-10-26271Wild4Moose5LXSommaire du Match
53 - 2018-10-27277Wild6Moose2WSommaire du Match
55 - 2018-10-29298Griffins3Wild7WSommaire du Match
59 - 2018-11-02315Wild0Eagles7LSommaire du Match
60 - 2018-11-03330Wild2Eagles7LSommaire du Match
64 - 2018-11-07346Wolves8Wild1LSommaire du Match
66 - 2018-11-09358Wolves7Wild4LSommaire du Match
67 - 2018-11-10372Griffins2Wild5WSommaire du Match
71 - 2018-11-14388Wild4Stars6LSommaire du Match
73 - 2018-11-16399Wild-Rampage-
75 - 2018-11-18418Wild-Rampage-
80 - 2018-11-23445Heat-Wild-
81 - 2018-11-24461Heat-Wild-
85 - 2018-11-28466IceHogs-Wild-
88 - 2018-12-01493Admirals-Wild-
90 - 2018-12-03505Wolves-Wild-
92 - 2018-12-05514Wild-Wolves-
94 - 2018-12-07527IceHogs-Wild-
96 - 2018-12-09550Wild-IceHogs-
99 - 2018-12-12556Wild-Rampage-
101 - 2018-12-14570Wild-Rampage-
102 - 2018-12-15583Wild-Stars-
104 - 2018-12-17593Gulls-Wild-
108 - 2018-12-21612Reign-Wild-
109 - 2018-12-22623Reign-Wild-
111 - 2018-12-24637IceHogs-Wild-
115 - 2018-12-28662Wild-Admirals-
116 - 2018-12-29676Wild-IceHogs-
122 - 2019-01-04694Wild-Condors-
123 - 2019-01-05710Wild-Gulls-
126 - 2019-01-08715Wild-Barracuda-
129 - 2019-01-11729Rampage-Wild-
130 - 2019-01-12743Rampage-Wild-
137 - 2019-01-19785Wild-IceHogs-
138 - 2019-01-20798Wild-Wolves-
140 - 2019-01-22807Stars-Wild-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
142 - 2019-01-24815Barracuda-Wild-
143 - 2019-01-25826Barracuda-Wild-
147 - 2019-01-29849Wild-Barracuda-
150 - 2019-02-01865Wild-Condors-
151 - 2019-02-02878Wild-Reign-
152 - 2019-02-03887Wild-Reign-
157 - 2019-02-08900Wild-Griffins-
158 - 2019-02-09918Wild-Wolves-
161 - 2019-02-12932Rampage-Wild-
164 - 2019-02-15952Rampage-Wild-
168 - 2019-02-19976Wild-Roadrunners-
169 - 2019-02-20983Wild-Roadrunners-
171 - 2019-02-22992Wild-Heat-
173 - 2019-02-241015Wild-Heat-
175 - 2019-02-261017Griffins-Wild-
178 - 2019-03-011034Stars-Wild-
179 - 2019-03-021046Stars-Wild-
182 - 2019-03-051062Roadrunners-Wild-
183 - 2019-03-061069Roadrunners-Wild-
186 - 2019-03-091091Wild-Admirals-
190 - 2019-03-131109Wild-Griffins-
192 - 2019-03-151123Wolves-Wild-
193 - 2019-03-161132IceHogs-Wild-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
24 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,040,820$ 125,000$ 96,130$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 48,020$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 14,433$ 1,760,826$




LigueDomicileVisiteur
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
1326131101100928391494010005840181247001003443-9299216025212382330177624625127636112103465211602616.25%1543080.52%041882550.67%29766544.66%20641649.52%695515572171292152
Total Saison Régulière26131101100928391494010005840181247001003443-9299216025212382330177624625127636112103465211602616.25%1543080.52%041882550.67%29766544.66%20641649.52%695515572171292152