Manitoba Moose

GP: 7 | W: 5 | L: 2 | OTL: 0 | P: 10
GF: 45 | GA: 17 | PP%: 6.67% | PK%: 86.67%
DG: Lucas Giguere | Morale : 99 | Moyenne d'Équipe : 59
Prochain matchs #98 vs WILKIES-BARRIE 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 SP
1Austin Czarnik0XX100.005735756863776767726965616655513785650
2Brandon Pirri0XX100.005835717272426571686874577460535788640
3Justin Bailey0X100.006235676889535567506262526353516997620
4Matt Read0X100.005235666868555668526262536368552697610
5Hudson Fasching0X100.005889696984505069506262516251505892600
6Byron Froese0X100.005489627078505070706363526354514997600
7Connor Brickley0XXX100.005853686475545764505958525953516197590
8Alexandre Grenier0X100.006089616689505066505757505750505387590
9Kristian Vesalainen (R)0X100.005735726585545265505757525750508392590
10Jansen Harkins0X100.005089646774505067505959505950504497580
11Reid Boucher0X100.00503569706915070707070507055526097570
12Quinton Howden0XX100.005437806873454558405054635562546397570
13Roman Lyubimov (R)0XX100.005135806776454357334854645462526397570
14Jason Garrison0X100.005935756181735861305360726672572387640
15Juuso Valimaki (R)0X100.006135756683656266305653666451508488620
16TJ Brennan0X100.005789587081505070305045505552516297570
17Seth Helgeson0X100.006489425891465058304641505152514899540
18Frank Corrado0X100.005389695675505056304742505253514797530
19Ryan Lindgren (R)0X100.005335535875475258304541515150507396520
Rayé
1Danick Martel0X100.006135755664675456635757585751504292580
2Andrey Pedan0X100.006747585087586958304640605751516592570
MOYENNE D'ÉQUIPE100.00575567657852546447565655605551569459
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
1Philippe Desrosiers100.00746281767373747373736850624392640
2Jean-Francois Berube100.00515669696555586061575564555597550
Rayé
MOYENNE D'ÉQUIPE100.0063597573696466676765625759499560
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dean Evason68686868767662CAN562325,000$


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
1Byron FroeseManitoba Moose (WPG)C7791614404743132716.28%28612.3800000000001080.43%9200013.6900000110
2Matt ReadManitoba Moose (WPG)RW786141720425042916.00%07410.6900000000111080.00%500013.7400000121
3Connor BrickleyManitoba Moose (WPG)C/LW/RW711213920131169174215.94%610615.23101480000010100.00%1000022.4400000102
4TJ BrennanManitoba Moose (WPG)D72101291001861691212.50%812517.900113200017000.00%000001.9200000010
5Roman LyubimovManitoba Moose (WPG)C/LW725770003284247.14%1679.7000000000010085.71%1400002.0600000000
6Quinton HowdenManitoba Moose (WPG)C/LW724650014248138.33%0618.8200000000001040.00%500001.9400000001
7Jansen HarkinsManitoba Moose (WPG)C7336800673082310.00%0679.6400000000001075.00%8000001.7800000011
8Austin CzarnikManitoba Moose (WPG)C/RW305540046188220.00%16220.7200001011060079.45%7300001.6100000000
9Jason GarrisonManitoba Moose (WPG)D11458000051620.00%02323.900000000001000.00%000004.1800000100
10Kristian VesalainenManitoba Moose (WPG)LW414552011178125.88%04511.4000000000000066.67%300002.1900000000
11Hudson FaschingManitoba Moose (WPG)RW422430031166812.50%04912.470000000000000.00%100001.6000000000
12Reid BoucherManitoba Moose (WPG)LW71346002055620.00%0253.63000000000000100.00%300003.1500000000
13Brandon PirriManitoba Moose (WPG)C/LW2123300201514186.67%03517.78000000110200100.00%200001.6900000000
14Juuso ValimakiManitoba Moose (WPG)D2033300005150.00%14422.320000000012000.00%000001.3400000000
15Justin BaileyManitoba Moose (WPG)RW41012202014377.14%1348.52000000000100100.00%200000.5900000000
16Frank CorradoManitoba Moose (WPG)D70111020412250.00%17510.760000000000000.00%000000.2700000000
17Seth HelgesonManitoba Moose (WPG)D21015002021350.00%03919.510000010112000.00%000000.5100000000
18Ryan LindgrenManitoba Moose (WPG)D60113201144140.00%26811.420000000008000.00%000000.2900000000
19Alexandre GrenierManitoba Moose (WPG)RW1000200107220.00%01616.87000000001100100.00%300000.0000000000
Stats d'équipe Total ou en Moyenne924364107123260785337011526811.62%23111112.081127111235395079.18%29300041.9300000455
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
1Philippe DesrosiersManitoba Moose (WPG)75200.9202.2038203141760100.000070100
2Jean-Francois BerubeManitoba Moose (WPG)10000.9294.8737003420000.000007000
Stats d'équipe Total ou en Moyenne85200.9222.4342003172180100.000077100


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
Alexandre GrenierManitoba Moose (WPG)RW271991-09-05No91 Kg196 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$Lien
Andrey PedanManitoba Moose (WPG)D261993-07-03No97 Kg196 CMNoNoNo0Pro & Farm0$0$NoLien
Austin CzarnikManitoba Moose (WPG)C/RW261992-12-12No77 Kg175 CMNoNoNo3Pro & Farm1,250,000$1,137,387$1,250,000$1,137,387$0$0$No1,250,000$1,250,000$Lien
Brandon PirriManitoba Moose (WPG)C/LW281991-04-10No85 Kg183 CMNoNoNo2Pro & Farm775,000$705,180$775,000$705,180$0$0$No775,000$Lien
Byron FroeseManitoba Moose (WPG)C281991-03-12No92 Kg185 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$Lien
Connor BrickleyManitoba Moose (WPG)C/LW/RW271992-02-25No92 Kg183 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$Lien
Danick MartelManitoba Moose (WPG)LW241994-12-12No80 Kg173 CMNoNoNo0Pro & Farm0$0$NoLien
Frank CorradoManitoba Moose (WPG)D261993-03-26No93 Kg183 CMNoNoNo3Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$Lien
Hudson FaschingManitoba Moose (WPG)RW241995-07-28No93 Kg191 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
Jansen HarkinsManitoba Moose (WPG)C221997-05-23No83 Kg185 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
Jason GarrisonManitoba Moose (WPG)D341984-11-13No99 Kg185 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
Jean-Francois BerubeManitoba Moose (WPG)G281991-07-13No80 Kg185 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$
Justin BaileyManitoba Moose (WPG)RW241995-07-01No97 Kg193 CMNoNoNo3Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$Lien
Juuso ValimakiManitoba Moose (WPG)D201998-10-06Yes96 Kg188 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$Lien
Kristian VesalainenManitoba Moose (WPG)LW201999-06-01Yes94 Kg191 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$Lien
Matt ReadManitoba Moose (WPG)RW331986-06-14No85 Kg178 CMNoNoNo4Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$750,000$Lien
Philippe DesrosiersManitoba Moose (WPG)G241995-08-16No89 Kg185 CMNoNoNo3Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$Lien
Quinton HowdenManitoba Moose (WPG)C/LW271992-01-21No86 Kg188 CMNoNoNo5Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$750,000$750,000$
Reid BoucherManitoba Moose (WPG)LW251993-09-08No89 Kg178 CMNoNoNo1Pro & Farm750,000$682,432$750,000$682,432$0$0$NoLien
Roman LyubimovManitoba Moose (WPG)C/LW271992-01-06Yes94 Kg188 CMNoNoNo1Pro & Farm950,000$864,414$950,000$864,414$0$0$No
Ryan LindgrenManitoba Moose (WPG)D211998-02-11Yes91 Kg183 CMNoNoNo2Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$Lien
Seth HelgesonManitoba Moose (WPG)D281990-10-08No100 Kg193 CMNoNoNo3Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$Lien
TJ BrennanManitoba Moose (WPG)D301989-04-03No98 Kg185 CMNoNoNo4Pro & Farm750,000$682,432$750,000$682,432$0$0$No750,000$750,000$750,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2326.0490 Kg185 CM2.13716,304$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Justin Bailey34122
2Kristian VesalainenConnor BrickleyHudson Fasching27122
3Reid BoucherByron FroeseMatt Read22122
4Quinton HowdenJansen HarkinsRoman Lyubimov17122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1TJ Brennan46122
2Seth HelgesonRyan Lindgren32122
3Frank Corrado22122
4TJ Brennan0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kristian VesalainenHudson Fasching60122
2Connor BrickleyJustin Bailey40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1TJ Brennan60122
2TJ BrennanRyan Lindgren40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Roman LyubimovMatt Read55122
2Justin Bailey45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan Lindgren55122
2TJ BrennanSeth Helgeson45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
155122Ryan Lindgren55122
245122TJ BrennanSeth Helgeson45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
155122
2Justin BaileyHudson Fasching45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan Lindgren55122
2TJ BrennanSeth Helgeson45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Connor BrickleyTJ Brennan
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Hudson FaschingConnor BrickleyJustin BaileyRyan Lindgren
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Roman Lyubimov, Reid Boucher, Matt ReadRoman Lyubimov, Reid BoucherMatt Read
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Ryan Lindgren, TJ BrennanFrank Corrado, TJ Brennan
Tirs de Pénalité
, , Hudson Fasching, Kristian Vesalainen, Matt Read
Gardien
#1 : Philippe Desrosiers, #2 : Jean-Francois Berube
Lignes d'Attaque Perso. en Prol.
, , Connor Brickley, Hudson Fasching, Justin Bailey, Matt Read, Matt Read, Byron Froese, Reid Boucher, Jansen Harkins, Kristian Vesalainen
Lignes de Défense Perso. en Prol.
, Ryan Lindgren, TJ Brennan, Seth Helgeson, Frank Corrado


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
1HOLLYWOOD Oscar330000003012911000000909220000002112061.0003050800225173028112915513803410646000.00%30100.00%114019173.30%8621040.95%7411763.25%220183133306536
2IOWA Wild20200000314-110000000000020200000314-1100.0003580025173022129155138013327162210110.00%8275.00%014019173.30%8621040.95%7411763.25%220183133306536
3MONT-LAURIER Sommet11000000202110000002020000000000021.00023501251730231291551380333818500.00%40100.00%014019173.30%8621040.95%7411763.25%220183133306536
4Marlies de Toronto1100000010281100000010280000000000021.00010162600251730961291551380184025000.00%000.00%014019173.30%8621040.95%7411763.25%220183133306536
Total7520000045172833000000212194220000024159100.714457411903251730422129155138021844301111516.67%15286.67%114019173.30%8621040.95%7411763.25%220183133306536
_Since Last GM Reset7520000045172833000000212194220000024159100.714457411903251730422129155138021844301111516.67%15286.67%114019173.30%8621040.95%7411763.25%220183133306536
_Vs Conference642000003515202200000011011422000002415980.6673558930325173032612915513802004030861516.67%15286.67%114019173.30%8621040.95%7411763.25%220183133306536

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
710W24574119422218443011103
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
75200004517
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3300000212
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
42200002415
Derniers 10 Matchs
WLOTWOTL SOWSOL
520000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1516.67%15286.67%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
1291551380251730
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
14019173.30%8621040.95%7411763.25%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
220183133306536


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 - 2020-01-158Manitoba Moose10HOLLYWOOD Oscar0WSommaire du Match
2 - 2020-01-1621Marlies de Toronto2Manitoba Moose10WSommaire du Match
3 - 2020-01-1733MONT-LAURIER Sommet0Manitoba Moose2WSommaire du Match
4 - 2020-01-1842Manitoba Moose2IOWA Wild8LSommaire du Match
5 - 2020-01-1960Manitoba Moose1IOWA Wild6LSommaire du Match
7 - 2020-01-2166HOLLYWOOD Oscar0Manitoba Moose9WSommaire du Match
9 - 2020-01-2381Manitoba Moose11HOLLYWOOD Oscar1WSommaire du Match
11 - 2020-01-2598Manitoba Moose-WILKIES-BARRIE Penguins-
13 - 2020-01-27108BELLEVILLE Senators-Manitoba Moose-
15 - 2020-01-29121CORNWALL Aces-Manitoba Moose-
17 - 2020-01-31137Binghampton Devils-Manitoba Moose-
19 - 2020-02-02151Manitoba Moose-STOCKTON Flames-
21 - 2020-02-04160ROCKFORD IceHogs-Manitoba Moose-
22 - 2020-02-05174Manitoba Moose-PV Sharapovas-
24 - 2020-02-07191Manitoba Moose-IOWA Wild-
25 - 2020-02-08203MONT-LAURIER Sommet-Manitoba Moose-
26 - 2020-02-09216BROOKLYN Wolfpack-Manitoba Moose-
28 - 2020-02-11239HOLLYWOOD Oscar-Manitoba Moose-
29 - 2020-02-12249Manitoba Moose-TUSCON Roadrunners-
31 - 2020-02-14261PROVIDENCE Bruins-Manitoba Moose-
32 - 2020-02-15279Manitoba Moose-TUSCON Roadrunners-
33 - 2020-02-16288Manitoba Moose-LEHIGH VALLEY Phantoms-
34 - 2020-02-17295Manitoba Moose-SAN DIEGO Gulls-
35 - 2020-02-18306BRIDGEPORT Sound Tigers-Manitoba Moose-
37 - 2020-02-20320ROCKFORD IceHogs-Manitoba Moose-
38 - 2020-02-21339Manitoba Moose-MONT-LAURIER Sommet-
39 - 2020-02-22350Manitoba Moose-HERSEY Bears-
40 - 2020-02-23358Manitoba Moose-BROOKLYN Wolfpack-
41 - 2020-02-24364CORNWALL Aces-Manitoba Moose-
43 - 2020-02-26384COLORADO Eagles-Manitoba Moose-
44 - 2020-02-27400SAN DIEGO Gulls-Manitoba Moose-
45 - 2020-02-28412Manitoba Moose-PROVIDENCE Bruins-
46 - 2020-02-29427CHICAGO Wolves-Manitoba Moose-
48 - 2020-03-02444Manitoba Moose-PV Sharapovas-
49 - 2020-03-03453UTICA Comets-Manitoba Moose-
50 - 2020-03-04470Manitoba Moose-CORNWALL Aces-
52 - 2020-03-06477LEHIGH VALLEY Phantoms-Manitoba Moose-
53 - 2020-03-07495Manitoba Moose-IOWA Wild-
54 - 2020-03-08503IOWA Wild-Manitoba Moose-
56 - 2020-03-10522STOCKTON Flames-Manitoba Moose-
57 - 2020-03-11531Manitoba Moose-BELLEVILLE Senators-
59 - 2020-03-13539Manitoba Moose-Syracruse Crunch-
60 - 2020-03-14556Manitoba Moose-Marlies de Toronto-
61 - 2020-03-15566MILWAUKEE Admirals-Manitoba Moose-
62 - 2020-03-16582PV Sharapovas-Manitoba Moose-
63 - 2020-03-17598Manitoba Moose-CHICAGO Wolves-
64 - 2020-03-18606Manitoba Moose-VICTORIAVILLE Tigres-
65 - 2020-03-19615IOWA Wild-Manitoba Moose-
67 - 2020-03-21631PV Sharapovas-Manitoba Moose-
68 - 2020-03-22642Manitoba Moose-CORNWALL Aces-
69 - 2020-03-23660Manitoba Moose-LEHIGH VALLEY Phantoms-
70 - 2020-03-24666WILKIES-BARRIE Penguins-Manitoba Moose-
71 - 2020-03-25684Manitoba Moose-BELLEVILLE Senators-
72 - 2020-03-26693VICTORIAVILLE Tigres-Manitoba Moose-
73 - 2020-03-27704Manitoba Moose-WILKIES-BARRIE Penguins-
75 - 2020-03-29719HERSEY Bears-Manitoba Moose-
76 - 2020-03-30739Binghampton Devils-Manitoba Moose-
77 - 2020-03-31751Manitoba Moose-HOLLYWOOD Oscar-
78 - 2020-04-01761BELLEVILLE Senators-Manitoba Moose-
80 - 2020-04-03775Manitoba Moose-ROCKFORD IceHogs-
81 - 2020-04-04787LEHIGH VALLEY Phantoms-Manitoba Moose-
82 - 2020-04-05800Manitoba Moose-VICTORIAVILLE Tigres-
83 - 2020-04-06813Manitoba Moose-COLORADO Eagles-
84 - 2020-04-07824VICTORIAVILLE Tigres-Manitoba Moose-
85 - 2020-04-08829Manitoba Moose-MILWAUKEE Admirals-
86 - 2020-04-09847Manitoba Moose-STOCKTON Flames-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
88 - 2020-04-11858Marlies de Toronto-Manitoba Moose-
89 - 2020-04-12874WILKIES-BARRIE Penguins-Manitoba Moose-
91 - 2020-04-14889Manitoba Moose-MONT-LAURIER Sommet-
92 - 2020-04-15903TUSCON Roadrunners-Manitoba Moose-
93 - 2020-04-16918LAVAL Rockets-Manitoba Moose-
94 - 2020-04-17931Manitoba Moose-Binghampton Devils-
95 - 2020-04-18945Manitoba Moose-Syracruse Crunch-
96 - 2020-04-19953STOCKTON Flames-Manitoba Moose-
97 - 2020-04-20962Manitoba Moose-UTICA Comets-
99 - 2020-04-22981Syracruse Crunch-Manitoba Moose-
100 - 2020-04-23997Syracruse Crunch-Manitoba Moose-
102 - 2020-04-251009Manitoba Moose-LAVAL Rockets-
105 - 2020-04-281027Marlies de Toronto-Manitoba Moose-
106 - 2020-04-291033Manitoba Moose-Binghampton Devils-
108 - 2020-05-011047MONT-LAURIER Sommet-Manitoba Moose-
109 - 2020-05-021060Manitoba Moose-BRIDGEPORT Sound Tigers-



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
38 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
157,273$ 1,647,500$ 1,647,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 127,993$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 101 17,770$ 1,794,770$




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
33752000004517283300000021219422000002415910457411903251730422129155138021844301111516.67%15286.67%114019173.30%8621040.95%7411763.25%220183133306536
Total Saison Régulière752000004517283300000021219422000002415910457411903251730422129155138021844301111516.67%15286.67%114019173.30%8621040.95%7411763.25%220183133306536
Séries
32201280000048480106400000282531064000002023-324488413201181316158318019518820599203203338811316.05%871286.21%037366056.52%38971154.71%15029251.37%471325520151249124
Total Séries201280000048480106400000282531064000002023-324488413201181316158318019518820599203203338811316.05%871286.21%037366056.52%38971154.71%15029251.37%471325520151249124