Moose

GP: 76 | W: 21 | L: 51 | OTL: 4 | P: 46
GF: 172 | GA: 342 | PP%: 14.04% | PK%: 78.57%
DG: Luc Forget | Morale : 23 | Moyenne d'Équipe : 58
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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
1Filip Chlapik (R)X99.00685555756657576771636262557274179620
2Vinni Lettieri (R)XX99.00765581706566746561646161555050182610
3Corban KnightX99.00805567627770696050596060557571181610
4Zach SanfordX100.00605574747465646050606159555050189600
5Ryan OlsenX100.00605569616866695599555559557374181590
6Garrett MitchellX100.00565558617264695550555556557450181570
7Graham BlackX100.00655567617263655550555556556950183570
8Justin Kirkland (R)X100.00655567647064695550555555555050143560
9Troy BourkeX100.00605566676360745550555556555050181560
10Antoine LaganiereX100.00565555555859595550555555557072181550
11Travis MorinX100.00565555555555555550555555555050143530
12Yannick WeberX100.00795582838071587325636374558179181700
13Dalton ProutX100.00655560779374716425606063557873181670
14T.J. BrennanX100.00605565647965796025606058555353160600
15Chris ButlerX100.00555556605656765625565656557071181570
16Morgan Ellis (A)X100.00585555605555685525555555555353182550
17John RamageX100.00565556605656695625565656555353181550
18Jarred TinordiX100.00555555605555585525555555555353181540
19Mac BennettX100.00565555605555585525555555555353181540
Rayé
1Jeff HogganX100.00565555555557565550555555555757120530
2Trent Frederic (R)X100.00565555555555555550555555555050120520
MOYENNE D'ÉQUIPE99.8662556264666165584457575855615917158
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
1Matiss Kivlenieks (R)100.0053749372475550584949555055180560
Rayé
1Matej Machovsky (R)98.0057475974605760646060555055176580
MOYENNE D'ÉQUIPE99.005561767354565561555555505517857
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bryan Trottier57476162787363CAN5951,000,000$


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
1Zach SanfordMoose (Wpg)LW773013431762205877149339020.13%9131117.03129214629120252145056.10%12300010.6611112334
2Justin KirklandMoose (Wpg)LW76201333-267751581221955615010.26%59101313.33101931000012153.03%6600000.6501001111
3T.J. BrennanMoose (Wpg)D38621276615903242173014.29%5665417.22448251040112131200.00%000000.8301001231
4Yannick WeberMoose (Wpg)D25816249540394669266311.59%3654621.876915541030111131210.00%000000.8800000320
5Dalton ProutMoose (Wpg)D2551621936036305718378.77%1955622.2641014371040221139100.00%000000.7500000013
6Filip ChlapikMoose (Wpg)C25910196260497348154118.75%657422.9724698220261182065.02%58600000.6602000230
7Chris ButlerMoose (Wpg)D25613191344035183251718.75%1646018.4243721930220118210.00%000000.8300000114
8Troy BourkeMoose (Wpg)LW254151964019285511347.27%344017.6209910910000200147.62%2100000.8600000111
9Vinni LettieriMoose (Wpg)C/RW25710175255374357195312.28%751720.6911213970112830154.33%12700000.6622100202
10Garrett MitchellMoose (Wpg)RW256111758013214473413.64%341816.7637101294000002070.00%2000000.8100000102
11Corban KnightMoose (Wpg)C2551116952068356117398.20%659223.70246128300031190051.65%39500000.5402000130
12Graham BlackMoose (Wpg)C2535841751217256712.00%01536.1200000000002056.20%12100001.0500100101
13Ryan OlsenMoose (Wpg)C253584220850335299.09%438815.56000010111981072.83%36800000.4100000001
14Lee StempniakWinnipeg JetsLW/RW83470160142827123411.11%421526.921126370000382048.89%9000000.6500000001
15Morgan EllisMoose (Wpg)D25145-5195381482512.50%1831512.6200000000055000.00%000000.3200100000
16Mac BennettMoose (Wpg)D25134212015873514.29%51656.630000000000000.00%000000.4800000000
17Antoine LaganiereMoose (Wpg)C25123-3140201814477.14%225710.290113350001250156.85%14600000.2300000000
18Jarred TinordiMoose (Wpg)D25033210022216290.00%112108.4400003000131000.00%000000.2800000000
19John RamageMoose (Wpg)D25033-7220311910080.00%928611.460003800018000.00%000000.2100000000
20Travis MorinMoose (Wpg)C5000000033010.00%0142.81000140000000100.00%500000.0000000000
Stats d'équipe Total ou en Moyenne579118178296565814576270394225869312.53%273909315.7040621022611268481224133923660.44%206800010.6539414181821
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
1Matej MachovskyMoose (Wpg)2417420.9062.19142301525550200.5717240401
2Matiss KivlenieksMoose (Wpg)21100.8683.3091005380000.0000125000
Stats d'équipe Total ou en Moyenne2618520.9042.26151501575930200.57172525401


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 Link
Antoine LaganiereMoose (Wpg)C261990-07-04No196 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Chris ButlerMoose (Wpg)D301986-10-27No196 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
Corban KnightMoose (Wpg)C261990-09-10No195 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Dalton ProutMoose (Wpg)D261990-03-13No222 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No
Filip ChlapikMoose (Wpg)C191997-06-03Yes196 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Garrett MitchellMoose (Wpg)RW251991-02-09No183 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Graham BlackMoose (Wpg)C241993-01-13No180 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jarred TinordiMoose (Wpg)D241992-02-20No225 Lbs6 ft6NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Jeff HogganMoose (Wpg)LW381978-02-01No193 Lbs5 ft11NoNoYes1Sans RestrictionPro & Farm500,000$0$0$No
John RamageMoose (Wpg)D251991-02-07No200 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Justin KirklandMoose (Wpg)LW201996-08-02Yes183 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Mac BennettMoose (Wpg)D251991-03-25No182 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Matej MachovskyMoose (Wpg)G231993-07-25Yes187 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Matiss KivlenieksMoose (Wpg)G201996-08-26Yes183 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Morgan EllisMoose (Wpg)D241992-04-29No204 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Ryan OlsenMoose (Wpg)C221994-03-24No187 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
T.J. BrennanMoose (Wpg)D271989-04-02No216 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Travis MorinMoose (Wpg)C331984-01-08No190 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Trent FredericMoose (Wpg)C181998-02-11Yes216 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Troy BourkeMoose (Wpg)LW221994-03-29No170 Lbs5 ft10NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
Vinni LettieriMoose (Wpg)C/RW211995-02-06Yes181 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Yannick WeberMoose (Wpg)D281988-09-22No200 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
Zach SanfordMoose (Wpg)LW221994-11-09No192 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2324.70195 Lbs6 ft12.35439,130$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Zach SanfordFilip ChlapikVinni Lettieri40122
2Troy BourkeCorban KnightGarrett Mitchell30122
3Justin KirklandRyan OlsenFilip Chlapik20122
4Corban KnightGraham BlackVinni Lettieri10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Yannick WeberDalton Prout40122
2T.J. BrennanChris Butler30122
3John RamageMorgan Ellis20122
4Jarred TinordiMac Bennett10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Zach SanfordFilip ChlapikVinni Lettieri60122
2Troy BourkeCorban KnightGarrett Mitchell40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Yannick WeberDalton Prout60122
2T.J. BrennanChris Butler40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Filip ChlapikCorban Knight60122
2Vinni LettieriZach Sanford40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Yannick WeberDalton Prout60122
2T.J. BrennanChris Butler40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Filip Chlapik60122Yannick WeberDalton Prout60122
2Corban Knight40122T.J. BrennanChris Butler40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Filip ChlapikCorban Knight60122
2Vinni LettieriZach Sanford40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Yannick WeberDalton Prout60122
2T.J. BrennanChris Butler40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Zach SanfordFilip ChlapikVinni LettieriYannick WeberDalton Prout
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Zach SanfordFilip ChlapikVinni LettieriYannick WeberDalton Prout
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Antoine Laganiere, , Ryan OlsenAntoine Laganiere, Ryan Olsen
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
John Ramage, Morgan Ellis, Jarred TinordiJohn RamageMorgan Ellis, Jarred Tinordi
Tirs de Pénalité
Filip Chlapik, Corban Knight, Vinni Lettieri, Zach Sanford, Ryan Olsen
Gardien
#1 : , #2 : Matiss Kivlenieks


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
1Admirals807010001041-3140301000416-1240400000625-1920.125101828006446568149609630572322951017510551611.76%29968.97%1827195142.39%1011256239.46%417111737.33%14169672329557842366
2Condors422000001416-22200000085320200000611-540.5001426400064465681376096305723214336388820420.00%18288.89%0827195142.39%1011256239.46%417111737.33%14169672329557842366
3Eagles41300000818-1020200000010-102110000088020.2508162400644656853609630572321425364611400.00%26965.38%0827195142.39%1011256239.46%417111737.33%14169672329557842366
4Griffins807001001838-20404000001122-1140300100716-910.06318355300644656819460963057232295757315425312.00%27581.48%0827195142.39%1011256239.46%417111737.33%14169672329557842366
5Gulls412010001117-62100100074320200000413-940.500112031006446568776096305723212241444525624.00%20480.00%0827195142.39%1011256239.46%417111737.33%14169672329557842366
6Heat422000001118-72200000084420200000314-1140.5001120310064465681036096305723214640568716318.75%23578.26%0827195142.39%1011256239.46%417111737.33%14169672329557842366
7IceHogs42101000131122200000081720101000510-560.7501322350164465681186096305723211339487417317.65%23386.96%2827195142.39%1011256239.46%417111737.33%14169672329557842366
8Marlies4210100016115201010009902200000072560.7501631470064465681946096305723213436261061516.67%12466.67%1827195142.39%1011256239.46%417111737.33%14169672329557842366
9Rampage815001012038-18403000011022-12412001001016-640.250204060006446568199609630572323521008916131412.90%37975.68%1827195142.39%1011256239.46%417111737.33%14169672329557842366
10Rocket41200001713-62020000017-62100000166030.37571219006446568886096305723213142739923313.04%30486.67%0827195142.39%1011256239.46%417111737.33%14169672329557842366
11Senators40300010611-52020000038-52010001033020.2506814006446568796096305723211328416428310.71%18383.33%0827195142.39%1011256239.46%417111737.33%14169672329557842366
12Stars826000001536-2141300000719-1241300000817-940.250152540006446568215609630572322991139117043613.95%391269.23%0827195142.39%1011256239.46%417111737.33%14169672329557842366
Total76155105212172342-170388250400187165-78387260121185177-92460.303172313485016446568183260963057232284685388614313565014.04%3788178.57%6827195142.39%1011256239.46%417111737.33%14169672329557842366
14Wild403010001024-1420101000710-320200000314-1120.250101626006446568726096305723219163546117211.76%25580.00%0827195142.39%1011256239.46%417111737.33%14169672329557842366
15Wolves817000001350-3740400000428-2441300000922-1320.125132437006446568154609630572323708611415631619.35%51786.27%1827195142.39%1011256239.46%417111737.33%14169672329557842366
_Since Last GM Reset76155105212172342-170388250400187165-78387260121185177-92460.303172313485016446568183260963057232284685388614313565014.04%3788178.57%6827195142.39%1011256239.46%417111737.33%14169672329557842366
_Vs Conference815010101728-11412010001012-240300010716-960.37517284500644656815660963057232235698510953916.98%38781.58%0827195142.39%1011256239.46%417111737.33%14169672329557842366

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7646W117231348518322846853886143101
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7615515212172342
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
38825400187165
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
38726121185177
Derniers 10 Matchs
WLOTWOTL SOWSOL
720100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3565014.04%3788178.57%6
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
609630572326446568
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
827195142.39%1011256239.46%417111737.33%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
14169672329557842366


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 - 2018-09-076Moose2Wild7LSommaire du Match
5 - 2018-09-0925Moose1Wild7LSommaire du Match
10 - 2018-09-1438Senators4Moose2LSommaire du Match
11 - 2018-09-1549Senators4Moose1LSommaire du Match
17 - 2018-09-2177Rampage7Moose2LSommaire du Match
19 - 2018-09-2397Rampage6Moose5LXXSommaire du Match
25 - 2018-09-29122Moose2Admirals7LSommaire du Match
26 - 2018-09-30135Moose4IceHogs3WXSommaire du Match
28 - 2018-10-02136Moose2Admirals5LSommaire du Match
31 - 2018-10-05148Wolves8Moose1LSommaire du Match
32 - 2018-10-06158Wolves7Moose0LSommaire du Match
37 - 2018-10-11180Griffins3Moose2LSommaire du Match
39 - 2018-10-13197Griffins7Moose2LSommaire du Match
42 - 2018-10-16211Moose1Rampage7LSommaire du Match
43 - 2018-10-17220Moose0Stars7LSommaire du Match
46 - 2018-10-20241Moose2Griffins4LSommaire du Match
47 - 2018-10-21251Moose1Wolves7LSommaire du Match
52 - 2018-10-26271Wild4Moose5WXSommaire du Match
53 - 2018-10-27277Wild6Moose2LSommaire du Match
57 - 2018-10-31306Moose3Gulls7LSommaire du Match
59 - 2018-11-02316Moose1Gulls6LSommaire du Match
60 - 2018-11-03331Moose1Condors4LSommaire du Match
64 - 2018-11-07347Moose5Condors7LSommaire du Match
66 - 2018-11-09361Moose1Heat7LSommaire du Match
67 - 2018-11-10373Moose2Heat7LSommaire du Match
73 - 2018-11-16397Marlies4Moose5WXSommaire du Match
74 - 2018-11-17405Marlies5Moose4LSommaire du Match
80 - 2018-11-23442Griffins6Moose3LSommaire du Match
81 - 2018-11-24451Griffins6Moose4LSommaire du Match
89 - 2018-12-02500Eagles5Moose0LSommaire du Match
90 - 2018-12-03506Eagles5Moose0LSommaire du Match
92 - 2018-12-05515Moose2Rampage3LXSommaire du Match
94 - 2018-12-07526Moose1Stars4LSommaire du Match
95 - 2018-12-08541Moose2Stars5LSommaire du Match
100 - 2018-12-13560Rocket4Moose0LSommaire du Match
102 - 2018-12-15578Rocket3Moose1LSommaire du Match
104 - 2018-12-17592Admirals6Moose1LSommaire du Match
106 - 2018-12-19600Admirals4Moose1LSommaire du Match
109 - 2018-12-22617Rampage4Moose3LSommaire du Match
110 - 2018-12-23633Rampage5Moose0LSommaire du Match
113 - 2018-12-26648Moose2Griffins4LSommaire du Match
115 - 2018-12-28663Moose1IceHogs7LSommaire du Match
116 - 2018-12-29668Moose1Admirals6LSommaire du Match
122 - 2019-01-04690Moose1Admirals7LSommaire du Match
123 - 2019-01-05707Moose0Wolves7LSommaire du Match
127 - 2019-01-09717Moose2Griffins6LSommaire du Match
130 - 2019-01-12742Stars9Moose3LSommaire du Match
131 - 2019-01-13750Stars3Moose0LSommaire du Match
134 - 2019-01-16766Wolves6Moose3LSommaire du Match
136 - 2019-01-18776Wolves7Moose0LSommaire du Match
138 - 2019-01-20795Admirals5Moose0LSommaire du Match
139 - 2019-01-21806Admirals1Moose2WXSommaire du Match
141 - 2019-01-23808Moose3Marlies1WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25825Moose3Rocket2WSommaire du Match
144 - 2019-01-26828Moose3Rocket4LXXSommaire du Match
148 - 2019-01-30850Moose4Marlies1WSommaire du Match
150 - 2019-02-01860Moose2Senators1WXXSommaire du Match
151 - 2019-02-02872Moose1Senators2LSommaire du Match
158 - 2019-02-09911IceHogs0Moose4WSommaire du Match
159 - 2019-02-10924IceHogs1Moose4WSommaire du Match
162 - 2019-02-13940Stars5Moose1LSommaire du Match
164 - 2019-02-15951Stars2Moose3WSommaire du Match
166 - 2019-02-17967Gulls2Moose3WXSommaire du Match
168 - 2019-02-19975Gulls2Moose4WSommaire du Match
171 - 2019-02-22991Moose5Eagles6LSommaire du Match
172 - 2019-02-231005Moose3Eagles2WSommaire du Match
176 - 2019-02-271024Moose5Stars1WSommaire du Match
178 - 2019-03-011035Moose3Rampage1WSommaire du Match
179 - 2019-03-021050Moose4Rampage5LSommaire du Match
182 - 2019-03-051061Condors3Moose4WSommaire du Match
183 - 2019-03-061068Condors2Moose4WSommaire du Match
186 - 2019-03-091084Heat2Moose5WSommaire du Match
187 - 2019-03-101099Heat2Moose3WSommaire du Match
192 - 2019-03-151118Moose1Griffins2LXSommaire du Match
193 - 2019-03-161137Moose2Wolves4LSommaire du Match
194 - 2019-03-171148Moose6Wolves4WSommaire du Match



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
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,101,126$ 101,000$ 50,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 101,185$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 5,675$ 0$




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
1376155105212172342-170388250400187165-78387260121185177-9246172313485016446568183260963057232284685388614313565014.04%3788178.57%6827195142.39%1011256239.46%417111737.33%14169672329557842366
Total Saison Régulière76155105212172342-170388250400187165-78387260121185177-9246172313485016446568183260963057232284685388614313565014.04%3788178.57%6827195142.39%1011256239.46%417111737.33%14169672329557842366