Manitoba Moose

GP: 4 | W: 1 | L: 3 | OTL: 0 | P: 2
GF: 5 | GA: 11 | PP%: 15.00% | PK%: 88.89%
DG: Lucas Giguere | Morale : 97 | Moyenne d'Équipe : 66
Prochain matchs #58 vs HERSEY Bears
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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
1Byron Froese0X100.006453836378858662726061646277795694700
2Justin Bailey0X100.006746886389788062596061646269647197690
3Daniel Carr0X100.006242886573807763616464626577695694690
4Hudson Fasching0X100.006946816084878958555759615869655797680
5Greg McKegg0X100.007343876473728063776162666375685697680
6Brandon Pirri0XX100.005943856673767164616365626677695897680
7Matt Read0X100.005743896268787361565960635984745298670
8Reid Boucher0X100.005843896569737563596264616573675297670
9Kristian Vesalainen0X100.006545906285757663566159646261638297670
10Jesper Boqvist (R)0X100.006539876670797364726163676663647697670
11Austin Czarnik0XX100.005641886563777664626363596575684897660
12Vladislav Kamenev0XX100.006139886379746864736259576567647298650
13Jansen Harkins0X100.005946886374757362686159606365627298650
14Danick Martel0X100.005543846266717360545958615871665997640
15Connor Brickley0XXX100.005853686475545764505958525953516198590
16Alexandre Grenier0X100.006089616689505066505757505750505397590
17Quinton Howden0XX100.005437806873454558405054635562546398570
18Seth Helgeson0X100.007572715590889256305451584578685597680
19Adam Boqvist (R)0X100.006339887069767268306661595261628997670
20Ryan Lindgren0X100.006948786573797263306256665063657397660
21Frank Corrado0X100.006345895875787756305452554573675897640
22Juuso Valimaki (R)0X100.006135756683656266305653666451508497620
Rayé
MOYENNE D'ÉQUIPE100.00624783647673736253605961596864649766
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
1J-F Berube100.00718987737069717069717077835197670
2Philippe Desrosiers100.00717573767069717069717069736897650
Rayé
MOYENNE D'ÉQUIPE100.0071828075706971706971707378609766
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dean Evason71727473787858CAN561100,000$


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
1Adam BoqvistManitoba Moose (WPG)D4112-3602311169.09%39523.90101515000013100.00%000000.4200000100
2Hudson FaschingManitoba Moose (WPG)RW4112-22012172714.29%17418.75011215000012000.00%000000.5300000000
3Justin BaileyManitoba Moose (WPG)RW40220204109390.00%08521.400115150000180040.00%500000.4700000000
4Brandon PirriManitoba Moose (WPG)C/LW4022-20021184100.00%06115.35022115000000060.34%5800000.6500000000
5Daniel CarrManitoba Moose (WPG)LW4202020571551013.33%18020.061017150001130156.52%2300000.5000000001
6Greg McKeggManitoba Moose (WPG)C4011-2100866790.00%05112.8500027000000053.23%6200000.3900000000
7Byron FroeseManitoba Moose (WPG)C4011-10081411230.00%29323.330111150001190050.70%14200000.2100000000
8Reid BoucherManitoba Moose (WPG)LW4101-2001311269.09%04912.4410128000000066.67%300000.4000000000
9Seth HelgesonManitoba Moose (WPG)D4011-1601928030.00%610726.79000415000016000.00%000000.1900000000
10Austin CzarnikManitoba Moose (WPG)C/RW4000-100134140.00%04310.9700000000000050.00%400000.0000000000
11Danick MartelManitoba Moose (WPG)LW4000-320134150.00%0287.110000000000000.00%000000.0000000000
12Alexandre GrenierManitoba Moose (WPG)RW4000-420221120.00%0328.18000000000000100.00%100000.0000000000
13Frank CorradoManitoba Moose (WPG)D4000-200303000.00%28020.0400017000013000.00%000000.0000000000
14Ryan LindgrenManitoba Moose (WPG)D4000-540927050.00%39624.18000314000012000.00%000000.0000000000
15TJ BrennanWINNIPEG JetsD1000-120213320.00%12424.080001600005000.00%000000.0000000000
16Juuso ValimakiManitoba Moose (WPG)D4000-200252050.00%56516.500001000006000.00%000000.0000000000
17Kristian VesalainenManitoba Moose (WPG)LW4000-100223420.00%15112.9400000000030066.67%300000.0000000000
18Jesper BoqvistManitoba Moose (WPG)C4000-300359540.00%14010.1700000000000042.42%3300000.0000000000
Stats d'équipe Total ou en Moyenne695914-35380868012241924.10%26116316.873583515400021351152.69%33400000.2400000101
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
1J-F BerubeManitoba Moose (WPG)41300.8952.7623900111050000.000040001
Stats d'équipe Total ou en Moyenne41300.8952.7623900111050000.000040001


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 BoqvistManitoba Moose (WPG)D202000-08-15Yes81 Kg180 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$
Alexandre GrenierManitoba Moose (WPG)RW281991-09-05No91 Kg196 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Austin CzarnikManitoba Moose (WPG)C/RW271992-12-12No77 Kg175 CMNoNoNo2Pro & Farm1,250,000$1,192,660$1,250,000$1,192,660$0$0$No1,250,000$Lien
Brandon PirriManitoba Moose (WPG)C/LW291991-04-10No82 Kg185 CMNoNoNo1Pro & Farm775,000$739,449$775,000$739,449$0$0$NoLien
Byron FroeseManitoba Moose (WPG)C291991-03-12No92 Kg185 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Connor BrickleyManitoba Moose (WPG)C/LW/RW281992-02-25No92 Kg183 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Danick MartelManitoba Moose (WPG)LW251994-12-12No84 Kg175 CMNoNoNo3Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$Lien
Daniel CarrManitoba Moose (WPG)LW281991-11-01No88 Kg183 CMNoNoNo3Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$Lien
Frank CorradoManitoba Moose (WPG)D271993-03-26No93 Kg183 CMNoNoNo2Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$Lien
Greg McKeggManitoba Moose (WPG)C281992-06-17No87 Kg183 CMNoNoNo3Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$Lien
Hudson FaschingManitoba Moose (WPG)RW251995-07-28No93 Kg191 CMNoNoNo5Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$750,000$Lien
J-F BerubeManitoba Moose (WPG)G291991-07-13No80 Kg185 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Jansen HarkinsManitoba Moose (WPG)C231997-05-23No83 Kg185 CMNoNoNo2Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$Lien
Jesper BoqvistManitoba Moose (WPG)C211998-10-30Yes82 Kg183 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$
Justin BaileyManitoba Moose (WPG)RW251995-07-01No97 Kg193 CMNoNoNo2Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$Lien
Juuso ValimakiManitoba Moose (WPG)D211998-10-06Yes96 Kg188 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Kristian VesalainenManitoba Moose (WPG)LW211999-06-01No94 Kg191 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Matt ReadManitoba Moose (WPG)RW341986-06-14No85 Kg178 CMNoNoNo3Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$Lien
Philippe DesrosiersManitoba Moose (WPG)G251995-08-16No89 Kg185 CMNoNoNo2Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$Lien
Quinton HowdenManitoba Moose (WPG)C/LW281992-01-21No86 Kg188 CMNoNoNo4Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$
Reid BoucherManitoba Moose (WPG)LW261993-09-08No89 Kg178 CMNoNoNo3Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$Lien
Ryan LindgrenManitoba Moose (WPG)D221998-02-11No87 Kg183 CMNoNoNo1Pro & Farm750,000$715,596$750,000$715,596$0$0$NoLien
Seth HelgesonManitoba Moose (WPG)D291990-10-08No100 Kg193 CMNoNoNo2Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$Lien
Vladislav KamenevManitoba Moose (WPG)C/LW241996-08-12No88 Kg188 CMNoNoNo5Pro & Farm750,000$715,596$750,000$715,596$0$0$No750,000$750,000$750,000$750,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2425.9288 Kg185 CM2.38771,875$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Daniel CarrByron FroeseJustin Bailey31122
2Reid BoucherBrandon PirriHudson Fasching26122
3Kristian VesalainenGreg McKeggAustin Czarnik23122
4Danick MartelJesper BoqvistAlexandre Grenier20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Seth HelgesonAdam Boqvist31122
2Ryan LindgrenFrank Corrado26122
3Juuso ValimakiSeth Helgeson23122
4Adam BoqvistRyan Lindgren20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Daniel CarrByron FroeseJustin Bailey55122
2Reid BoucherBrandon PirriHudson Fasching45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Seth HelgesonAdam Boqvist55122
2Ryan LindgrenFrank Corrado45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Byron FroeseJustin Bailey55122
2Daniel CarrHudson Fasching45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Seth HelgesonAdam Boqvist55122
2Ryan LindgrenFrank Corrado45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Byron Froese55122Seth HelgesonAdam Boqvist55122
2Justin Bailey45122Ryan LindgrenFrank Corrado45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Byron FroeseJustin Bailey55122
2Daniel CarrHudson Fasching45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Seth HelgesonAdam Boqvist55122
2Ryan LindgrenFrank Corrado45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Daniel CarrByron FroeseJustin BaileySeth HelgesonAdam Boqvist
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Daniel CarrByron FroeseJustin BaileySeth HelgesonAdam Boqvist
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Greg McKegg, Jesper Boqvist, Kristian VesalainenGreg McKegg, Jesper BoqvistKristian Vesalainen
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Juuso Valimaki, Frank Corrado, Seth HelgesonJuuso ValimakiFrank Corrado, Seth Helgeson
Tirs de Pénalité
Byron Froese, Justin Bailey, Daniel Carr, Hudson Fasching, Brandon Pirri
Gardien
#1 : J-F Berube, #2 : Philippe Desrosiers
Lignes d'Attaque Perso. en Prol.
Byron Froese, Justin Bailey, Daniel Carr, Hudson Fasching, Brandon Pirri, Greg McKegg, Greg McKegg, Jesper Boqvist, Reid Boucher, Kristian Vesalainen, Austin Czarnik
Lignes de Défense Perso. en Prol.
Seth Helgeson, Adam Boqvist, Ryan Lindgren, Frank Corrado, Juuso Valimaki


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
1Binghampton Devils1010000025-3000000000001010000025-300.00024600320037394538034814269111.11%6183.33%08615455.84%5611847.46%346254.84%1047185295025
2HERSEY Bears1010000003-31010000003-30000000000000.000000003200303945380235820400.00%40100.00%08615455.84%5611847.46%346254.84%1047185295025
3STOCKTON Flames1010000001-11010000001-10000000000000.0000000032002539453802481014200.00%50100.00%08615455.84%5611847.46%346254.84%1047185295025
4Syracruse Crunch11000000321000000000001100000032121.0003580032003039453802456265240.00%3166.67%08615455.84%5611847.46%346254.84%1047185295025
Total41300000511-62020000004-42110000057-220.2505914003200122394538010526388620315.00%18288.89%08615455.84%5611847.46%346254.84%1047185295025
_Since Last GM Reset41300000511-62020000004-42110000057-220.2505914003200122394538010526388620315.00%18288.89%08615455.84%5611847.46%346254.84%1047185295025
_Vs Conference3120000058-31010000001-12110000057-220.33359140032009239453808221306616318.75%14285.71%08615455.84%5611847.46%346254.84%1047185295025
_Vs Division2010000028-61000000003-31010000025-300.000246003200673945380571322461317.69%10190.00%08615455.84%5611847.46%346254.84%1047185295025

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
42L1591412210526388600
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4130000511
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
202000004
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
211000057
Derniers 10 Matchs
WLOTWOTL SOWSOL
130000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
20315.00%18288.89%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
39453803200
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
8615455.84%5611847.46%346254.84%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1047185295025


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 - 2020-08-027Manitoba Moose2Binghampton Devils5LSommaire du Match
2 - 2020-08-0321STOCKTON Flames1Manitoba Moose0LSommaire du Match
4 - 2020-08-0530Manitoba Moose3Syracruse Crunch2WSommaire du Match
5 - 2020-08-0645HERSEY Bears3Manitoba Moose0LSommaire du Match
6 - 2020-08-0758HERSEY Bears-Manitoba Moose-
7 - 2020-08-0870Manitoba Moose-Syracruse Crunch-
9 - 2020-08-1088MONT-LAURIER Sommet-Manitoba Moose-
10 - 2020-08-1196Manitoba Moose-COLORADO Eagles-
11 - 2020-08-12106Manitoba Moose-BELLEVILLE Senators-
12 - 2020-08-13114Manitoba Moose-BROOKLYN Wolfpack-
13 - 2020-08-14127HOLLYWOOD Oscar-Manitoba Moose-
15 - 2020-08-16144Manitoba Moose-ROCKFORD IceHogs-
16 - 2020-08-17152CHICAGO Wolves-Manitoba Moose-
18 - 2020-08-19171Manitoba Moose-BRIDGEPORT Sound Tigers-
19 - 2020-08-20180Marlies de Toronto-Manitoba Moose-
20 - 2020-08-21196LEHIGH VALLEY Phantoms-Manitoba Moose-
22 - 2020-08-23210Manitoba Moose-MILWAUKEE Admirals-
23 - 2020-08-24220Manitoba Moose-STOCKTON Flames-
24 - 2020-08-25230BRIDGEPORT Sound Tigers-Manitoba Moose-
25 - 2020-08-26251CHICAGO Wolves-Manitoba Moose-
26 - 2020-08-27260Manitoba Moose-CHICAGO Wolves-
27 - 2020-08-28275Manitoba Moose-IOWA Wild-
29 - 2020-08-30284Binghampton Devils-Manitoba Moose-
31 - 2020-09-01302ROCKFORD IceHogs-Manitoba Moose-
32 - 2020-09-02310Manitoba Moose-MONT-LAURIER Sommet-
33 - 2020-09-03318Manitoba Moose-Binghampton Devils-
34 - 2020-09-04332Marlies de Toronto-Manitoba Moose-
36 - 2020-09-06353STOCKTON Flames-Manitoba Moose-
37 - 2020-09-07366Manitoba Moose-LAVAL Rockets-
39 - 2020-09-09378Manitoba Moose-LEHIGH VALLEY Phantoms-
40 - 2020-09-10386Manitoba Moose-HERSEY Bears-
41 - 2020-09-11397COLORADO Eagles-Manitoba Moose-
42 - 2020-09-12413LAVAL Rockets-Manitoba Moose-
44 - 2020-09-14428PV Sharapovas-Manitoba Moose-
45 - 2020-09-15439Manitoba Moose-VICTORIAVILLE Tigres-
46 - 2020-09-16448Manitoba Moose-TUSCON Roadrunners-
48 - 2020-09-18460Manitoba Moose-HOLLYWOOD Oscar-
49 - 2020-09-19473BROOKLYN Wolfpack-Manitoba Moose-
50 - 2020-09-20487Manitoba Moose-IOWA Wild-
51 - 2020-09-21493LEHIGH VALLEY Phantoms-Manitoba Moose-
53 - 2020-09-23514BELLEVILLE Senators-Manitoba Moose-
55 - 2020-09-25531Manitoba Moose-COLORADO Eagles-
56 - 2020-09-26536HOLLYWOOD Oscar-Manitoba Moose-
57 - 2020-09-27550Manitoba Moose-Binghampton Devils-
58 - 2020-09-28567Manitoba Moose-ROCKFORD IceHogs-
59 - 2020-09-29573LAVAL Rockets-Manitoba Moose-
60 - 2020-09-30590IOWA Wild-Manitoba Moose-
61 - 2020-10-01604Manitoba Moose-BELLEVILLE Senators-
63 - 2020-10-03616Marlies de Toronto-Manitoba Moose-
64 - 2020-10-04627Manitoba Moose-PROVIDENCE Bruins-
65 - 2020-10-05640Quebec Nordiques-Manitoba Moose-
67 - 2020-10-07662Manitoba Moose-SAN DIEGO Gulls-
68 - 2020-10-08672PROVIDENCE Bruins-Manitoba Moose-
69 - 2020-10-09682Manitoba Moose-SAN DIEGO Gulls-
70 - 2020-10-10695PROVIDENCE Bruins-Manitoba Moose-
72 - 2020-10-12711Manitoba Moose-UTICA Comets-
73 - 2020-10-13722Syracruse Crunch-Manitoba Moose-
75 - 2020-10-15738Manitoba Moose-Marlies de Toronto-
76 - 2020-10-16747Manitoba Moose-Syracruse Crunch-
77 - 2020-10-17754TUSCON Roadrunners-Manitoba Moose-
79 - 2020-10-19775MILWAUKEE Admirals-Manitoba Moose-
80 - 2020-10-20793HOLLYWOOD Oscar-Manitoba Moose-
82 - 2020-10-22805Manitoba Moose-BROOKLYN Wolfpack-
83 - 2020-10-23818Quebec Nordiques-Manitoba Moose-
84 - 2020-10-24827Manitoba Moose-PV Sharapovas-
85 - 2020-10-25837Manitoba Moose-WILKIES-BARRIE Penguins-
86 - 2020-10-26852WILKIES-BARRIE Penguins-Manitoba Moose-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
88 - 2020-10-28864Manitoba Moose-WILKIES-BARRIE Penguins-
89 - 2020-10-29878UTICA Comets-Manitoba Moose-
90 - 2020-10-30887Manitoba Moose-Quebec Nordiques-
91 - 2020-10-31905VICTORIAVILLE Tigres-Manitoba Moose-
94 - 2020-11-03927MONT-LAURIER Sommet-Manitoba Moose-
95 - 2020-11-04944HERSEY Bears-Manitoba Moose-
96 - 2020-11-05953Manitoba Moose-BRIDGEPORT Sound Tigers-
98 - 2020-11-07974Manitoba Moose-TUSCON Roadrunners-
99 - 2020-11-08978Manitoba Moose-VICTORIAVILLE Tigres-
100 - 2020-11-09984MILWAUKEE Admirals-Manitoba Moose-
103 - 2020-11-121008SAN DIEGO Gulls-Manitoba Moose-
105 - 2020-11-141022UTICA Comets-Manitoba Moose-
108 - 2020-11-171039Manitoba Moose-PV Sharapovas-



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
86,581$ 1,852,500$ 1,852,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 85,663$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 104 16,995$ 1,767,480$




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
Saison Régulière
338239280543339121317841181305311187102854121150012220411193783916441035115209967810395812961328130453258674952615482143114.49%2354182.55%41324255351.86%890258334.46%595128046.48%229718091816462857448
3441300000511-62020000004-42110000057-225914003200122394538010526388620315.00%18288.89%08615455.84%5611847.46%346254.84%1047185295025
Total Saison Régulière8640310543339622417243181505311187106814322160012220911891803966531049115212987810408013351373134253269177556416342343414.53%2534383.00%41410270752.09%946270135.02%629134246.87%240118801902491908473
Séries
33734000001920-13120000069-34220000013112619325100124302629285778307794614418633.33%18383.33%110428636.36%7827628.26%3010030.00%160117190448038
Total Séries734000001920-13120000069-34220000013112619325100124302629285778307794614418633.33%18383.33%110428636.36%7827628.26%3010030.00%160117190448038