Manitoba Moose

GP: 25 | W: 11 | L: 10 | OTL: 4 | P: 26
GF: 85 | GA: 82 | PP%: 25.58% | PK%: 71.58%
DG: Andrew Shaughnessy | Morale : 42 | Moyenne d'Équipe : N/A
Prochain matchs #375 vs Wilkes-Barre/Scranton Penguins
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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 SPÂgeContratSalaire Moyen
1Gabriel Dumont (C)XX100.00814374757879737377747373708389703700301750,000$
2Kay Schweri (R)XX100.005825858369777478677373647259627046002411,000,000$
3Noah Rod (R)XXX100.008240757978808078747879707666657049002411,000,000$
4Adam BrooksX100.007335808372797780727977667364657049002421,200,000$
5Simon Stransky (R)XX100.00663084787279767471737266696262704000232750,000$
6Colin Blackwell (A)X100.008143757875828176757676667382857039002711,000,000$
7Linden VeyXX99.006735807776767679717778657683857049002911,750,000$
8Alexander AvtsinX100.007435817778807677637675657784807049002931,850,000$
9Jérôme Verrier (R)XX99.008543777881828077757877687269707049002611,000,000$
10Daniel Lafontaine (R)X100.007138798175787575737674667066687029002511,000,000$
11Alexandre GrenierX100.00864874708579807261747467737878704600292800,000$
12Brent Pedersen (R)X100.008946747686828277667677697270707039002511,000,000$
13Taylor BeckXX100.008040807284818275657878647780807039002911,250,000$
14Filip Zadina (A)XX99.00763778837779768663787968825857704900211950,000$
15Mark AltX99.00864574767976747350756182627174704900292800,000$
16Jerome Gauthier-LeducX99.00764573797576767550776178686667704900282800,000$
17Frederic St-DenisX100.00603781697470697150735778577990704100342800,000$
18Jordan SchmaltzX99.008243757880787778507760856371717040002721,500,000$
19Kevin Lidström (R)X99.007538827775787671517459805566687049002611,000,000$
Rayé
1Maxime MacenauerX100.00694574727475717477727264728481704000312800,000$
2Joel ChouinardX100.00633572737474737350725677607578703800302800,000$
3Peter StoykewychX100.008642747883807776517760805776807035002811,000,000$
MOYENNE D'ÉQUIPE99.6876397777777876766476707169727470430
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
1Olof Lindbom (R)97.0081808182848183818080796262704400
2Louis Domingue100.0086818486908887898786877680705100
Rayé
1Jean-François Bérubé100.0085818383878588868585866569704500
MOYENNE D'ÉQUIPE99.008481838487858685848484687070470
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ted Nolan90908585858470CAN6321,500,000$


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
1Filip ZadinaManitoba Moose (WPG)LW/RW25111223460284788226012.50%652220.91461015701122922042.17%23000000.8803000301
2Kevin LidströmManitoba Moose (WPG)D25616220100272347152312.77%3451720.715492458000057000.00%000000.8500000110
3Jordan SchmaltzManitoba Moose (WPG)D2341519916052332642415.38%3649221.433581448011060000.00%000000.7700000131
4Jerome Gauthier-LeducManitoba Moose (WPG)D2531417414026313117229.68%2950720.281122155000066100.00%000000.6700000021
5Noah RodManitoba Moose (WPG)C/LW/RW2561016-610028266617439.09%744917.9718911711014351051.22%8200000.7102000110
6Adam BrooksManitoba Moose (WPG)C2579168120123355253812.73%034913.99123222000001143.50%44600000.9200000011
7Jérôme VerrierManitoba Moose (WPG)C/RW2551116-910041345815388.62%749119.643696690001681055.66%31800100.6502000102
8Mark AltManitoba Moose (WPG)D2511415136056272911173.45%3756522.621341363000064000.00%000000.5300000100
9Brent PedersenManitoba Moose (WPG)LW2559141140512248173810.42%634713.9113411630000140043.90%4100000.8111000010
10Colin BlackwellManitoba Moose (WPG)C258513-112026445793414.04%235614.251015410001320052.64%41600000.7300000011
11Alexander AvtsinManitoba Moose (WPG)RW25671314091848133012.50%132312.94101543000000057.14%2100010.8000000101
12Gabriel DumontManitoba Moose (WPG)C/RW247411-1120182740112917.50%932313.4700000000032050.00%16200010.6800000101
13Simon StranskyManitoba Moose (WPG)C/LW1963950042127111322.22%022511.8900000000020253.75%8000000.8000000010
14Alexandre GrenierManitoba Moose (WPG)RW2344898039132682315.38%225210.96000000000330033.33%1800000.6300000000
15Linden VeyManitoba Moose (WPG)C/RW25167912031252811323.57%844717.91000219000001046.48%14200000.3100000101
16Daniel LafontaineManitoba Moose (WPG)C18167200319175135.88%01488.2701114000011046.54%15900000.9400000000
17Frederic St-DenisManitoba Moose (WPG)D23055-1401214121100.00%1931513.7000023011024000.00%000000.3200000000
18Peter StoykewychManitoba Moose (WPG)D1605541604022164120.00%3536722.95022840011043000.00%000000.2700000002
19Maxime MacenauerManitoba Moose (WPG)C1220210016142914.29%0988.2100004000000051.02%9800000.4100000000
20Kay SchweriManitoba Moose (WPG)LW/RW231010001761516.67%0883.83000010000210046.67%1500000.2300000000
21Joel ChouinardManitoba Moose (WPG)D90111808108160.00%914115.760002600001000.00%000000.1400000000
22Taylor BeckManitoba Moose (WPG)LW/RW23000-18019183111280.00%430213.16000110000060047.83%2300000.0001000000
Stats d'équipe Total ou en Moyenne4888415624040212053252077823154710.80%251763415.65224163143700246863110348.73%225100120.6319000111112
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
1Olof LindbomManitoba Moose (WPG)136520.8943.1175301393680001.00031312100
2Louis DomingueManitoba Moose (WPG)63120.9063.2736700202120000.6673613000
3Jean-François BérubéManitoba Moose (WPG)103510.9073.1357540303220000.333399010
Stats d'équipe Total ou en Moyenne29121150.9013.15169641899020000.66792834110


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 MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Adam BrooksManitoba Moose (WPG)C241995-01-22 08:50:21No176 Lbs5 ft11NoNoNo2Pro & Farm1,200,000$880,851$1,200,000$880,851$0$0$No1,200,000$
Alexander AvtsinManitoba Moose (WPG)RW291990-01-22 14:08:32No188 Lbs6 ft3NoNoNo3Pro & Farm1,850,000$1,357,978$1,850,000$1,357,978$0$0$No1,850,000$1,850,000$
Alexandre GrenierManitoba Moose (WPG)RW291990-01-22 03:10:39No200 Lbs6 ft5NoNoNo2Pro & Farm800,000$587,234$800,000$587,234$0$0$No800,000$
Brent PedersenManitoba Moose (WPG)LW251994-01-22 17:06:05Yes212 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$734,042$1,000,000$734,042$0$0$No
Colin BlackwellManitoba Moose (WPG)C271992-01-22 07:09:40No175 Lbs5 ft10NoNoNo1Pro & Farm1,000,000$734,042$1,000,000$734,042$0$0$No
Daniel LafontaineManitoba Moose (WPG)C251994-01-22 05:33:58Yes181 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$734,042$1,000,000$734,042$0$0$No
Filip ZadinaManitoba Moose (WPG)LW/RW211998-01-22 06:21:02No196 Lbs6 ft0NoNoNo1Pro & Farm950,000$697,340$950,000$697,340$0$0$No
Frederic St-DenisManitoba Moose (WPG)D341985-01-22 04:50:56No190 Lbs5 ft11NoNoNo2Pro & Farm800,000$587,234$800,000$587,234$0$0$No800,000$
Gabriel DumontManitoba Moose (WPG)C/RW301989-01-22 06:41:52No181 Lbs5 ft11NoNoNo1Pro & Farm750,000$550,531$750,000$550,531$0$0$No
Jean-François BérubéManitoba Moose (WPG)G291990-01-22 07:13:22No176 Lbs6 ft1NoNoNo2Pro & Farm800,000$587,234$800,000$587,234$0$0$No800,000$
Jerome Gauthier-LeducManitoba Moose (WPG)D281991-01-22 07:30:29No194 Lbs6 ft1NoNoNo2Pro & Farm800,000$587,234$800,000$587,234$0$0$No800,000$
Joel ChouinardManitoba Moose (WPG)D301989-01-22 12:30:22No190 Lbs6 ft1NoNoNo2Pro & Farm800,000$587,234$800,000$587,234$0$0$No800,000$
Jordan SchmaltzManitoba Moose (WPG)D271992-01-22 02:42:58No190 Lbs6 ft2NoNoNo2Pro & Farm1,500,000$1,101,063$1,500,000$1,101,063$0$0$No1,500,000$
Jérôme VerrierManitoba Moose (WPG)C/RW261993-01-22 05:29:47Yes185 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$734,042$1,000,000$734,042$0$0$No
Kay SchweriManitoba Moose (WPG)LW/RW241995-01-22 07:34:36Yes176 Lbs5 ft10NoNoNo1Pro & Farm1,000,000$734,042$1,000,000$734,042$0$0$No
Kevin LidströmManitoba Moose (WPG)D261993-01-22 05:32:11Yes176 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$734,042$1,000,000$734,042$0$0$No
Linden VeyManitoba Moose (WPG)C/RW291990-01-22 10:57:52No200 Lbs6 ft0NoNoNo1Pro & Farm1,750,000$1,284,574$1,750,000$1,284,574$0$0$No
Louis DomingueManitoba Moose (WPG)G281991-01-22 12:50:32No200 Lbs6 ft3NoNoNo2Pro & Farm800,000$587,234$800,000$587,234$0$0$No800,000$
Mark AltManitoba Moose (WPG)D291990-01-22 07:50:37No201 Lbs6 ft4NoNoNo2Pro & Farm800,000$587,234$800,000$587,234$0$0$No800,000$
Maxime MacenauerManitoba Moose (WPG)C311988-01-22 13:51:04No203 Lbs6 ft0NoNoNo2Pro & Farm800,000$587,234$800,000$587,234$0$0$No800,000$
Noah RodManitoba Moose (WPG)C/LW/RW241995-01-22 07:41:23Yes192 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$734,042$1,000,000$734,042$0$0$No
Olof LindbomManitoba Moose (WPG)G201999-01-22 08:13:50Yes183 Lbs6 ft2NoNoNo2Pro & Farm700,000$513,829$700,000$513,829$0$0$No700,000$
Peter StoykewychManitoba Moose (WPG)D281991-01-22 06:51:50No200 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$734,042$1,000,000$734,042$0$0$No
Simon StranskyManitoba Moose (WPG)C/LW231996-01-22 23:39:50Yes183 Lbs5 ft11NoNoNo2Pro & Farm750,000$550,531$750,000$550,531$0$0$No750,000$
Taylor BeckManitoba Moose (WPG)LW/RW291990-01-22 02:41:20No205 Lbs6 ft2NoNoNo1Pro & Farm1,250,000$917,553$1,250,000$917,553$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2527.00190 Lbs6 ft11.561,004,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Filip ZadinaJérôme VerrierNoah Rod25023
2Brent PedersenColin BlackwellAlexander Avtsin25122
3Taylor BeckAdam BrooksGabriel Dumont25122
4Simon StranskyLinden VeyAlexandre Grenier25122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Frederic St-DenisJordan Schmaltz25122
2Mark AltJerome Gauthier-Leduc25122
3Kevin LidströmLinden Vey25122
4Mark AltJordan Schmaltz25122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Filip ZadinaJérôme VerrierNoah Rod60122
2Brent PedersenColin BlackwellAlexander Avtsin40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Kevin LidströmJordan Schmaltz60122
2Mark AltJerome Gauthier-Leduc40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Filip ZadinaJérôme Verrier60122
2Noah RodColin Blackwell40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Kevin LidströmJordan Schmaltz60122
2Mark AltJerome Gauthier-Leduc40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Filip Zadina60122Frederic St-DenisJordan Schmaltz60122
2Jérôme Verrier40122Mark AltJerome Gauthier-Leduc40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Filip ZadinaJérôme Verrier60122
2Noah RodColin Blackwell40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Kevin LidströmJordan Schmaltz60122
2Mark AltJerome Gauthier-Leduc40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Filip ZadinaJérôme VerrierNoah RodMark AltJordan Schmaltz
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Filip ZadinaJérôme VerrierNoah RodMark AltJordan Schmaltz
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Daniel Lafontaine, Filip Zadina, Kay SchweriDaniel Lafontaine, Jérôme VerrierKay Schweri
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Kevin Lidström, Mark Alt, Jerome Gauthier-LeducKevin LidströmMark Alt, Jerome Gauthier-Leduc
Tirs de Pénalité
Filip Zadina, Jérôme Verrier, Noah Rod, Colin Blackwell, Brent Pedersen
Gardien
#1 : Olof Lindbom, #2 : Louis Domingue
Lignes d'Attaque Perso. en Prol.
Filip Zadina, Jérôme Verrier, Noah Rod, Colin Blackwell, Brent Pedersen, Alexander Avtsin, Alexander Avtsin, Taylor Beck, Adam Brooks, Gabriel Dumont, Linden Vey
Lignes de Défense Perso. en Prol.
Frederic St-Denis, Jordan Schmaltz, Mark Alt, Jerome Gauthier-Leduc, Kevin Lidström


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
1Adirondack Phantoms2020000046-2000000000002020000046-200.00048120032322014826826521517501010258337.50%5260.00%041584549.11%43790148.50%20740950.61%581397615184320158
2Albany Devils1010000023-1000000000001010000023-100.00024600323220128268265215173746194125.00%3166.67%041584549.11%43790148.50%20740950.61%581397615184320158
3Binghamton Senators11000000752110000007520000000000021.000714210032322013626826521517329419400.00%20100.00%041584549.11%43790148.50%20740950.61%581397615184320158
4Bridgeport Sound Tigers11000000422110000004220000000000021.0004711003232201292682652151723614155120.00%7271.43%041584549.11%43790148.50%20740950.61%581397615184320158
5CCCP Red Army1010000034-1000000000001010000034-100.000358003232201322682652151730161221200.00%5260.00%041584549.11%43790148.50%20740950.61%581397615184320158
6Charlotte Checkers310001011082210000016331000010045-140.66710172701323220193268265215179830168010220.00%8275.00%041584549.11%43790148.50%20740950.61%581397615184320158
7Chicago Wolves1010000024-21010000024-20000000000000.000235003232201312682652151727612224125.00%6350.00%041584549.11%43790148.50%20740950.61%581397615184320158
8Chicoutimi Saguenéens1000010034-11000010034-10000000000010.50036900323220134268265215173376234250.00%30100.00%041584549.11%43790148.50%20740950.61%581397615184320158
9Connecticut Whale22000000963000000000002200000096341.00091726003232201572682652151782182441500.00%12191.67%141584549.11%43790148.50%20740950.61%581397615184320158
10Gatineau Olympiques11000000541110000005410000000000021.0005813003232201222682652151732138162150.00%40100.00%041584549.11%43790148.50%20740950.61%581397615184320158
11Las Vegas Gamblers1000000167-1000000000001000000167-110.50061117003232201302682652151747108225240.00%4250.00%041584549.11%43790148.50%20740950.61%581397615184320158
12Laval Chiefs11000000624110000006240000000000021.00069150032322013826826521517381010184250.00%4175.00%041584549.11%43790148.50%20740950.61%581397615184320158
13Providence Bruins10000010321000000000001000001032121.0003470032322012626826521517291412213133.33%4175.00%041584549.11%43790148.50%20740950.61%581397615184320158
14Roberval Dwarfs11000000413000000000001100000041321.000481200323220125268265215172582214125.00%110.00%041584549.11%43790148.50%20740950.61%581397615184320158
15Rochester Americans21100000761211000007610000000000020.500713200032322017426826521517662724457342.86%10280.00%041584549.11%43790148.50%20740950.61%581397615184320158
16Rouyn-Noranda Huskies30300000310-70000000000030300000310-700.000369003232201932682652151796292870700.00%10370.00%041584549.11%43790148.50%20740950.61%581397615184320158
Total2510100021285823116300101443681447001114146-5260.5208515323801323220175726826521517814239212513862225.58%952771.58%241584549.11%43790148.50%20740950.61%581397615184320158
17Trois-Rivières Draveurs11000000321000000000001100000032121.00036900323220129268265215173488184125.00%3166.67%141584549.11%43790148.50%20740950.61%581397615184320158
18Wilkes-Barre/Scranton Penguins1010000046-21010000046-20000000000000.0004711003232201322682652151735148174125.00%4325.00%041584549.11%43790148.50%20740950.61%581397615184320158
_Since Last GM Reset2510100021285823116300101443681447001114146-5260.5208515323801323220175726826521517814239212513862225.58%952771.58%241584549.11%43790148.50%20740950.61%581397615184320158
_Vs Conference18860021163558842001013126510440011032293210.5836311617901323220154326826521517574171146365641625.00%671873.13%241584549.11%43790148.50%20740950.61%581397615184320158

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2526OTL28515323875781423921251301
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
25101002128582
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
116301014436
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
144701114146
Derniers 10 Matchs
WLOTWOTL SOWSOL
520201
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
862225.58%952771.58%2
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
268265215173232201
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
41584549.11%43790148.50%20740950.61%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
581397615184320158


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
1 - 2020-10-284Manitoba Moose1Rouyn-Noranda Huskies4LSommaire du Match
3 - 2020-10-3015Manitoba Moose4Roberval Dwarfs1WSommaire du Match
5 - 2020-11-0130Bridgeport Sound Tigers2Manitoba Moose4WSommaire du Match
6 - 2020-11-0241Manitoba Moose3Providence Bruins2WXXSommaire du Match
8 - 2020-11-0460Gatineau Olympiques4Manitoba Moose5WSommaire du Match
11 - 2020-11-0784Wilkes-Barre/Scranton Penguins6Manitoba Moose4LSommaire du Match
13 - 2020-11-09101Manitoba Moose4Connecticut Whale3WSommaire du Match
14 - 2020-11-10108Manitoba Moose0Rouyn-Noranda Huskies2LSommaire du Match
17 - 2020-11-13131Rochester Americans3Manitoba Moose2LSommaire du Match
19 - 2020-11-15147Manitoba Moose2Adirondack Phantoms3LSommaire du Match
21 - 2020-11-17156Manitoba Moose3Trois-Rivières Draveurs2WSommaire du Match
22 - 2020-11-18165Chicago Wolves4Manitoba Moose2LSommaire du Match
24 - 2020-11-20183Manitoba Moose3CCCP Red Army4LSommaire du Match
26 - 2020-11-22197Charlotte Checkers3Manitoba Moose2LXXSommaire du Match
30 - 2020-11-26220Manitoba Moose2Rouyn-Noranda Huskies4LSommaire du Match
31 - 2020-11-27229Binghamton Senators5Manitoba Moose7WSommaire du Match
34 - 2020-11-30250Manitoba Moose2Albany Devils3LSommaire du Match
35 - 2020-12-01260Rochester Americans3Manitoba Moose5WSommaire du Match
37 - 2020-12-03276Manitoba Moose6Las Vegas Gamblers7LXXSommaire du Match
40 - 2020-12-06293Laval Chiefs2Manitoba Moose6WSommaire du Match
42 - 2020-12-08314Manitoba Moose5Connecticut Whale3WSommaire du Match
44 - 2020-12-10328Charlotte Checkers0Manitoba Moose4WSommaire du Match
46 - 2020-12-12340Manitoba Moose2Adirondack Phantoms3LSommaire du Match
48 - 2020-12-14349Manitoba Moose4Charlotte Checkers5LXSommaire du Match
50 - 2020-12-16363Chicoutimi Saguenéens4Manitoba Moose3LXSommaire du Match
52 - 2020-12-18375Manitoba Moose-Wilkes-Barre/Scranton Penguins-
54 - 2020-12-20392Manitoba Moose-Providence Bruins-
55 - 2020-12-21399Mercer Island Hafgufa-Manitoba Moose-
58 - 2020-12-24426The Nuuk Vikings-Manitoba Moose-
60 - 2020-12-26442Manitoba Moose-Adirondack Phantoms-
62 - 2020-12-28450Manitoba Moose-CCCP Red Army-
64 - 2020-12-30462San Antonio Rampage-Manitoba Moose-
67 - 2021-01-02486Manitoba Moose-Providence Bruins-
68 - 2021-01-03495Rockford IceHogs-Manitoba Moose-
71 - 2021-01-06519Manitoba Moose-Charlotte Checkers-
72 - 2021-01-07528Joliette Sportif-Manitoba Moose-
77 - 2021-01-12557Manitoba Moose-Binghamton Senators-
78 - 2021-01-13565Adirondack Phantoms-Manitoba Moose-
80 - 2021-01-15589Trois-Rivières Draveurs-Manitoba Moose-
83 - 2021-01-18604Manitoba Moose-Rochester Americans-
86 - 2021-01-21626Rochester Americans-Manitoba Moose-
88 - 2021-01-23636Manitoba Moose-Rouyn-Noranda Huskies-
90 - 2021-01-25654Manitoba Moose-Grand Rapids Griffins-
91 - 2021-01-26662San Antonio Rampage-Manitoba Moose-
94 - 2021-01-29684Manitoba Moose-Laval Chiefs-
95 - 2021-01-30693Milwaukee Admirals-Manitoba Moose-
98 - 2021-02-02716Manitoba Moose-Bridgeport Sound Tigers-
99 - 2021-02-03726Lake Erie Monsters-Manitoba Moose-
102 - 2021-02-06749Manitoba Moose-The Nuuk Vikings-
103 - 2021-02-07759Albany Devils-Manitoba Moose-
107 - 2021-02-11785Manitoba Moose-Norfolk Admirals-
108 - 2021-02-12792Gatineau Olympiques-Manitoba Moose-
112 - 2021-02-16822Rouyn-Noranda Huskies-Manitoba Moose-
115 - 2021-02-19840Manitoba Moose-San Antonio Rampage-
117 - 2021-02-21855CCCP Red Army-Manitoba Moose-
119 - 2021-02-23867Manitoba Moose-Trois-Rivières Draveurs-
122 - 2021-02-26888Connecticut Whale-Manitoba Moose-
125 - 2021-03-01910Manitoba Moose-San Antonio Rampage-
126 - 2021-03-02922Houston Aeros-Manitoba Moose-
129 - 2021-03-05949Manitoba Moose-Chicoutimi Saguenéens-
130 - 2021-03-06955Providence Bruins-Manitoba Moose-
132 - 2021-03-08974Manitoba Moose-Roberval Dwarfs-
134 - 2021-03-10987CCCP Red Army-Manitoba Moose-
139 - 2021-03-151016Manitoba Moose-Albany Devils-
140 - 2021-03-161022Roberval Dwarfs-Manitoba Moose-
144 - 2021-03-201052Chicago Wolves-Manitoba Moose-
147 - 2021-03-231079Bridgeport Sound Tigers-Manitoba Moose-
149 - 2021-03-251086Manitoba Moose-Roberval Dwarfs-
151 - 2021-03-271102Manitoba Moose-Peoria Rivermen-
153 - 2021-03-291114Henderson Silver Knights-Manitoba Moose-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
157 - 2021-04-021143Bridgeport Sound Tigers-Manitoba Moose-
158 - 2021-04-031151Manitoba Moose-Norfolk Admirals-
163 - 2021-04-081184Wilkes-Barre/Scranton Penguins-Manitoba Moose-
166 - 2021-04-111202Manitoba Moose-Springfield Falcons-
168 - 2021-04-131217Binghamton Senators-Manitoba Moose-
169 - 2021-04-141227Manitoba Moose-Chicoutimi Saguenéens-
172 - 2021-04-171246Wilkes-Barre/Scranton Penguins-Manitoba Moose-
178 - 2021-04-231274Norfolk Admirals-Manitoba Moose-
179 - 2021-04-241286Manitoba Moose-Oklahoma City Barons-
185 - 2021-04-301306Norfolk Admirals-Manitoba Moose-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets181
Assistance21,99910,995
Assistance PCT100.00%99.95%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
29 2999 - 99.98% 36,998$406,977$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,016,841$ 2,510,000$ 2,510,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
13,351$ 615,992$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
1,072,939$ 138 21,330$ 2,943,540$




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