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Moose

GP: 81 | W: 14 | L: 66 | OTL: 1 | P: 29
GF: 256 | GA: 587 | PP%: 21.52% | PK%: 56.60%
DG: | Morale : 50 | Moyenne d'Équipe : 61
Prochain matchs #1259 vs Roadrunners
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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
1Brad MaloneX100.00753886578475655668575565537870028620
2Hudson FaschingX100.00693692598492895863565562586664047620
3Luke JohnsonX100.00643787636880686273615966586965050620
4Paul CareyX100.00653688597780695855565957547871050610
5Ross ColtonX100.00643787587693905760565558526563050600
6Ryan OlsenX100.00593983587593915759565658576965050600
7Carter BancksX100.00533885546993915356535152487879050590
8Joe MorrowX100.00785080657476546330716264567367050650
9Andrej SekeraX100.00573692637476596230665461538273050620
10Chris SummersX100.00683982568291875430555257457971050600
11Reece WillcoxX100.00713690568792895530565158456965050600
12William BorgenX100.00683690588389725730545359456563050600
13Philip SamuelssonX100.00643690547993905230535154457568050590
14Jesse GrahamX100.00543886566690845530565152486965050580
Rayé
1Mario KempeX100.00793888607170675972565864597971039620
2Nolan VeseyX100.00613886547476705357545053526764050570
3Joonas LyytinenX100.00563691536577715230535154466764050570
MOYENNE D'ÉQUIPE100.0065388758768477574757545851726804860
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
1Tom McCollum100.0074757384737274737274737884050660
2Adam Wilcox100.0072737172717072717072717377050630
Rayé
MOYENNE D'ÉQUIPE100.007374727872717372717372768105065
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Chris SummersMoose (WIN)D81355691-107711544719334611824110.12%347193623.9011617134157000054200.00%000010.9400003455
2Luke JohnsonMoose (WIN)C81464490-744201492284641283429.91%76107713.3000000000002163.56%147100031.6700112544
3Philip SamuelssonMoose (WIN)D81344377-775402811472747619312.41%247153618.9715116101106000045000.00%000001.0000000234
4Carter BancksMoose (WIN)RW81442367-661951932345181443468.49%78133916.5401103000001147.19%8900031.0000010414
Stats d'équipe Total ou en Moyenne324159166325-257188401070802160246611229.93%748588918.18268342352670000995262.63%156000071.1000125151317
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
Stats d'équipe Total ou en Moyenne0.0000.0000.000


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 Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Cap 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 WilcoxMoose (WIN)G251992-11-26No189 Lbs6 ft0NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Andrej SekeraMoose (WIN)D321986-06-08No200 Lbs6 ft0NoNoNo3Pro & Farm5,500,000$0$0$No5,500,000$5,500,000$Lien / Lien NHL
Brad MaloneMoose (WIN)C291989-05-20No217 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Carter BancksMoose (WIN)RW291989-08-09No181 Lbs5 ft11NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Chris SummersMoose (WIN)D301988-02-05No207 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Hudson FaschingMoose (WIN)RW231995-07-28No204 Lbs6 ft3NoNoNo1Pro & Farm874,125$0$0$NoLien / Lien NHL
Jesse GrahamMoose (WIN)D241994-05-13No170 Lbs5 ft11NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Joe MorrowMoose (WIN)D251992-12-09No196 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$0$0$NoLien / Lien NHL
Joonas LyytinenMoose (WIN)D231995-04-04No154 Lbs6 ft0NoNoNo1Pro & Farm900,000$0$0$NoLien / Lien NHL
Luke JohnsonMoose (WIN)C241994-09-19No179 Lbs5 ft11NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Mario KempeMoose (WIN)RW301988-09-19No185 Lbs6 ft0NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Nolan VeseyMoose (WIN)C231995-03-28No198 Lbs6 ft0NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Paul CareyMoose (WIN)C301988-09-24No200 Lbs6 ft1NoNoNo3Pro & Farm700,000$0$0$No700,000$700,000$Lien / Lien NHL
Philip SamuelssonMoose (WIN)D271991-07-26No194 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Reece WillcoxMoose (WIN)D241994-03-20No205 Lbs6 ft4NoNoNo2Pro & Farm675,000$0$0$No675,000$Lien / Lien NHL
Ross ColtonMoose (WIN)C221996-09-11No209 Lbs6 ft0NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Ryan OlsenMoose (WIN)C241994-03-25No187 Lbs6 ft1NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Tom McCollumMoose (WIN)G281989-12-07No220 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
William BorgenMoose (WIN)D211996-12-19No196 Lbs6 ft3NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1925.95194 Lbs6 ft11.471,013,112$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
130122
2Carter Bancks30122
3Luke Johnson25122
415122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Summers30122
2Philip Samuelsson30122
325122
4Chris Summers15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
2Carter Bancks40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Summers60122
2Philip Samuelsson40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Summers60122
2Philip Samuelsson40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Chris Summers60122
240122Philip Samuelsson40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris Summers60122
2Philip Samuelsson40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris Summers
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris Summers
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Luke Johnson, , Luke Johnson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , Philip Samuelsson, Philip Samuelsson
Tirs de Pénalité
, , , ,
Gardien
#1 : , #2 :


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Admirals404000001332-1920200000412-820200000920-1100.0001322350011381603175114410701079242597391282150.00%110.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
2Americans20200000519-141010000039-610100000210-800.000581300113816036111441070107924123296266116.67%3166.67%0990263337.60%936278233.64%587157237.34%162311712324529924417
3Barracuda30300000223-211010000016-520200000117-1600.00023500113816037611441070107924200471065500.00%6266.67%0990263337.60%936278233.64%587157237.34%162311712324529924417
4Bears20200000516-111010000038-51010000028-600.000581300113816037711441070107924124344363133.33%2150.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
5Bruins2020000009-91010000006-61010000003-300.0000000011381603351144107010792410831634600.00%3166.67%0990263337.60%936278233.64%587157237.34%162311712324529924417
6Checkers20200000513-81010000028-61010000035-200.000571200113816039211441070107924113361428500.00%7357.14%0990263337.60%936278233.64%587157237.34%162311712324529924417
7Comets32100000191452110000012931100000075240.66719315000113816031971144107010792416840101124125.00%5180.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
8Condors311000102019111000000844201000101215-340.667203252001138160325311441070107924151496904375.00%30100.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
9Crunch20200000216-141010000017-61010000019-800.00023500113816035811441070107924132461739200.00%6266.67%0990263337.60%936278233.64%587157237.34%162311712324529924417
10Devils2110000012120110000006511010000067-120.500122032001138160312811441070107924101264614250.00%220.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
11Eagles40400000936-2720200000316-1320200000620-1400.000917260011381603120114410701079242548112698112.50%5340.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
12Griffins20200000412-81010000028-61010000024-200.000471100113816037111441070107924125326547228.57%3166.67%0990263337.60%936278233.64%587157237.34%162311712324529924417
13Gulls30300000925-161010000039-620200000616-1000.0009172600113816038011441070107924170601156500.00%330.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
14Heat32000010191271100000084421000010118361.000192645001138160323911441070107924122414853133.33%20100.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
15IceHogs505000001044-3430300000623-1720200000421-1700.000101727001138160314111441070107924345851010410330.00%6266.67%0990263337.60%936278233.64%587157237.34%162311712324529924417
16Marlies20200000421-1710100000310-710100000111-1000.000461000113816035511441070107924145411052200.00%5420.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
17Monsters20200000519-1410100000310-71010000029-700.0005914001138160346114410701079241113711424125.00%3233.33%0990263337.60%936278233.64%587157237.34%162311712324529924417
18Penguins211000001213-1110000006511010000068-220.50012223400113816039311441070107924112342463266.67%110.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
19Phantoms20200000511-61010000026-41010000035-200.000591400113816038511441070107924161458614125.00%40100.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
20Rampage40400000831-2320200000315-1220200000516-1100.0008162400113816031471144107010792424555288011545.45%8450.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
21Reign30300000719-1220200000510-51010000029-700.000713200011381603691144107010792414742670600.00%2150.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
22Roadrunners20200000317-1420200000317-140000000000000.00035800113816035011441070107924134266444125.00%3166.67%0990263337.60%936278233.64%587157237.34%162311712324529924417
23Rocket20200000217-1510100000210-81010000007-700.0002460011381603621144107010792412739457500.00%2150.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
24Senators2110000012120110000008441010000048-420.500121931001138160314011441070107924942258433100.00%000.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
25Sound Tigers20200000714-71010000046-21010000038-500.0007132000113816035911441070107924100434439222.22%2150.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
26Stars54100000382992200000018126321000002017380.800386210010113816033461144107010792428577171425240.00%6266.67%0990263337.60%936278233.64%587157237.34%162311712324529924417
27Thunderbirds20200000717-1010100000110-91010000067-100.000781500113816038511441070107924119350524125.00%000.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
Total81126600120256587-3314183200100128283-1554043400020128304-176290.17925642367910113816033311114410701079244795135225819211583421.52%1064656.60%0990263337.60%936278233.64%587157237.34%162311712324529924417
29Wild40300100628-2220100100512-720200000116-1510.125610160011381603125114410701079242396410721100.00%5340.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
30Wolf Pack20200000415-111010000027-51010000028-600.0004590011381603601144107010792412733839700.00%3233.33%0990263337.60%936278233.64%587157237.34%162311712324529924417
31Wolves30300000222-2020200000115-141010000017-600.00024600113816038611441070107924154491050600.00%5180.00%0990263337.60%936278233.64%587157237.34%162311712324529924417
_Since Last GM Reset81126600120256587-3314183200100128283-1554043400020128304-176290.17925642367910113816033311114410701079244795135225819211583421.52%1064656.60%0990263337.60%936278233.64%587157237.34%162311712324529924417
_Vs Conference5074000120155368-213254200010073173-100253200002082195-113190.190155260415101138160320241144107010792429418181561151912021.98%612657.38%0990263337.60%936278233.64%587157237.34%162311712324529924417
_Vs Division230230010081151-7012012001004174-3311011000004077-3710.02281131212001138160310501144107010792412463546357237616.22%29968.97%0990263337.60%936278233.64%587157237.34%162311712324529924417

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8129L1256423679331147951352258192110
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8112660120256587
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
418320100128283
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
404340020128304
Derniers 10 Matchs
WLOTWOTL SOWSOL
360010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1583421.52%1064656.60%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
1144107010792411381603
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
990263337.60%936278233.64%587157237.34%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
162311712324529924417


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
2 - 2019-10-036Moose2Wolf Pack8LSommaire du Match
3 - 2019-10-0414Moose6Devils7LSommaire du Match
5 - 2019-10-0633Moose3Sound Tigers8LSommaire du Match
7 - 2019-10-0838Moose6Penguins8LSommaire du Match
9 - 2019-10-1053Wild4Moose3LXSommaire du Match
11 - 2019-10-1264Moose3IceHogs10LSommaire du Match
12 - 2019-10-1375Penguins5Moose6WSommaire du Match
14 - 2019-10-1587Roadrunners10Moose2LSommaire du Match
16 - 2019-10-17102Sound Tigers6Moose4LSommaire du Match
19 - 2019-10-20127Condors4Moose8WSommaire du Match
21 - 2019-10-22140Reign6Moose3LSommaire du Match
25 - 2019-10-26169Heat4Moose8WSommaire du Match
28 - 2019-10-29187Moose3Gulls9LSommaire du Match
31 - 2019-11-01203Moose1Barracuda11LSommaire du Match
32 - 2019-11-02215Moose1Wolves7LSommaire du Match
35 - 2019-11-05229Devils5Moose6WSommaire du Match
38 - 2019-11-08250Comets6Moose4LSommaire du Match
40 - 2019-11-10264Stars6Moose10WSommaire du Match
42 - 2019-11-12276Eagles7Moose2LSommaire du Match
44 - 2019-11-14288Moose6Thunderbirds7LSommaire du Match
46 - 2019-11-16302Moose1Crunch9LSommaire du Match
49 - 2019-11-19325Moose3Admirals11LSommaire du Match
51 - 2019-11-21342Moose4Stars6LSommaire du Match
53 - 2019-11-23352Monsters10Moose3LSommaire du Match
57 - 2019-11-27389Moose0Barracuda6LSommaire du Match
59 - 2019-11-29392Moose3Gulls7LSommaire du Match
60 - 2019-11-30414Moose2Reign9LSommaire du Match
63 - 2019-12-03431Stars6Moose8WSommaire du Match
65 - 2019-12-05445Moose7Stars6WSommaire du Match
68 - 2019-12-08463Gulls9Moose3LSommaire du Match
70 - 2019-12-10477Griffins8Moose2LSommaire du Match
72 - 2019-12-12491Moose2Griffins4LSommaire du Match
75 - 2019-12-15515Phantoms6Moose2LSommaire du Match
77 - 2019-12-17530Checkers8Moose2LSommaire du Match
79 - 2019-12-19543IceHogs8Moose2LSommaire du Match
81 - 2019-12-21554Moose1Wild8LSommaire du Match
83 - 2019-12-23577Rocket10Moose2LSommaire du Match
87 - 2019-12-27588Rampage8Moose2LSommaire du Match
89 - 2019-12-29602Moose2Rampage8LSommaire du Match
91 - 2019-12-31621Moose2Eagles11LSommaire du Match
93 - 2020-01-02633Marlies10Moose3LSommaire du Match
95 - 2020-01-04643Moose0Wild8LSommaire du Match
97 - 2020-01-06660Moose0Rocket7LSommaire du Match
99 - 2020-01-08675Moose1Marlies11LSommaire du Match
100 - 2020-01-09678Moose0Bruins3LSommaire du Match
103 - 2020-01-12703Admirals6Moose2LSommaire du Match
105 - 2020-01-14721Comets3Moose8WSommaire du Match
108 - 2020-01-17742Crunch7Moose1LSommaire du Match
110 - 2020-01-19757Moose1IceHogs11LSommaire du Match
112 - 2020-01-21764Moose3Checkers5LSommaire du Match
113 - 2020-01-22766Moose2Monsters9LSommaire du Match
122 - 2020-01-31789Bruins6Moose0LSommaire du Match
123 - 2020-02-01795Rampage7Moose1LSommaire du Match
126 - 2020-02-04822Admirals6Moose2LSommaire du Match
128 - 2020-02-06834Moose3Rampage8LSommaire du Match
130 - 2020-02-08843Senators4Moose8WSommaire du Match
131 - 2020-02-09858IceHogs9Moose2LSommaire du Match
133 - 2020-02-11872Wolf Pack7Moose2LSommaire du Match
136 - 2020-02-14891Barracuda6Moose1LSommaire du Match
138 - 2020-02-16914IceHogs6Moose2LSommaire du Match
140 - 2020-02-18926Reign4Moose2LSommaire du Match
142 - 2020-02-20937Moose4Senators8LSommaire du Match
144 - 2020-02-22949Moose3Phantoms5LSommaire du Match
145 - 2020-02-23961Moose2Americans10LSommaire du Match
147 - 2020-02-25973Moose2Bears8LSommaire du Match
149 - 2020-02-27992Bears8Moose3LSommaire du Match
151 - 2020-02-291009Moose7Condors6WXXSommaire du Match
154 - 2020-03-031024Americans9Moose3LSommaire du Match
157 - 2020-03-061045Wolves9Moose0LSommaire du Match
160 - 2020-03-091067Roadrunners7Moose1LSommaire du Match
162 - 2020-03-111080Moose5Condors9LSommaire du Match
165 - 2020-03-141108Moose5Heat4WXXSommaire du Match
166 - 2020-03-151117Moose7Comets5WSommaire du Match
168 - 2020-03-171128Thunderbirds10Moose1LSommaire du Match
171 - 2020-03-201148Wild8Moose2LSommaire du Match
173 - 2020-03-221168Moose9Stars5WSommaire du Match
175 - 2020-03-241183Moose6Admirals9LSommaire du Match
178 - 2020-03-271201Eagles9Moose1LSommaire du Match
180 - 2020-03-291218Wolves6Moose1LSommaire du Match
182 - 2020-03-311236Moose6Heat4WSommaire du Match
184 - 2020-04-021251Moose4Eagles9LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
186 - 2020-04-041259Moose-Roadrunners-



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
1,997,327$ 1,924,912$ 1,924,912$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,997,327$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 3 10,294$ 30,882$




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
282432304345307239684126901221165112534117140312414212715863075368431311010485142944947103394054228068784414433908922.82%3185582.70%81606293454.74%1304250152.14%739135254.66%2079145618536071050532
382126001342236411-1754182901111121208-874143100231115203-88242363555913010173571030201061984952443728100271515033695615.18%2869267.83%01269286444.31%1122260443.09%619142643.41%180913022205584945434
482116300062185442-2574182700042102207-105413360002083235-1522218533251711775844102247762735722514238122497316734595712.42%38511270.91%0817237034.47%960317930.20%404134729.99%14039072594639962411
582175701412241388-1474192601311119184-654183100101122204-82342414026432110165734256187884182624307683745519702205123.18%2096767.94%11115259542.97%822222936.88%600139942.89%196314051989545996494
682333501535314318-441161800322158169-114117170121315614976631455787112136103716337110831090117350351296246621832314419.05%2014975.62%31390295347.07%1329304743.62%633139545.38%1937137720195711009499
78287100102197513-3164163300101106250-144412380000191263-172161973245211073646002667864918880124397139239122141702615.29%1816663.54%0987268936.71%943280833.58%536147436.36%166711622295553968445
881126600120256587-3314183200100128283-1554043400020128304-1762925642367910113816033311114410701079244795135225819211583421.52%1064656.60%0990263337.60%936278233.64%587157237.34%162311712324529924417
Total Saison Régulière5731363750717201817362898-11622878117403111088991413-5142865520104610108371485-6482771736292946651077115484504720121673966716572259260267456410212907199735717.88%168648771.12%1281741903842.94%74161915038.73%4118996541.32%12485878315282403168563236
Séries
2514000001120-92020000029-731200000911-2211213200623015452465601595460882328.70%22863.64%08615954.09%7114947.65%397750.65%11077127356230
Total Séries514000001120-92020000029-731200000911-2211213200623015452465601595460882328.70%22863.64%08615954.09%7114947.65%397750.65%11077127356230