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Connexion

Moose
GP: 24 | W: 12 | L: 9 | OTL: 3 | P: 27
GF: 103 | GA: 89 | PP%: 28.00% | PK%: 76.12%
DG: Dylan Nadeau | Morale : 50 | Moyenne d’équipe : 60
Prochains matchs #394 vs Checkers
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Centre de jeu
Devils
4-17-2, 10pts
3
FINAL
4 Moose
12-9-3, 27pts
Team Stats
L1StreakSOL1
2-9-2Home Record9-2-2
2-8-0Away Record3-7-1
3-7-0Last 10 Games4-4-2
3.00Goals Per Game4.29
4.43Goals Against Per Game3.71
15.38%Power Play Percentage28.00%
61.54%Penalty Kill Percentage76.12%
Marlies
10-15-1, 21pts
5
FINAL
4 Moose
12-9-3, 27pts
Team Stats
SOW1StreakSOL1
7-6-1Home Record9-2-2
3-9-0Away Record3-7-1
6-4-0Last 10 Games4-4-2
3.04Goals Per Game4.29
3.58Goals Against Per Game3.71
15.87%Power Play Percentage28.00%
65.45%Penalty Kill Percentage76.12%
Checkers
13-8-2, 28pts
2021-12-07
Moose
12-9-3, 27pts
Statistiques d’équipe
L2SéquenceSOL1
6-4-0Fiche domicile9-2-2
7-4-2Fiche visiteur3-7-1
4-5-110 derniers matchs4-4-2
3.52Buts par match 4.29
3.30Buts contre par match 3.71
11.86%Pourcentage en avantage numérique28.00%
81.36%Pourcentage en désavantage numérique76.12%
Moose
12-9-3, 27pts
2021-12-09
Palm Springs
13-10-1, 27pts
Statistiques d’équipe
SOL1SéquenceL1
9-2-2Fiche domicile5-6-1
3-7-1Fiche visiteur8-4-0
4-4-210 derniers matchs5-5-0
4.29Buts par match 4.38
3.71Buts contre par match 4.00
28.00%Pourcentage en avantage numérique20.75%
76.12%Pourcentage en désavantage numérique77.78%
Moose
12-9-3, 27pts
2021-12-10
Comets
5-20-0, 10pts
Statistiques d’équipe
SOL1SéquenceL13
9-2-2Fiche domicile4-7-0
3-7-1Fiche visiteur1-13-0
4-4-210 derniers matchs0-10-0
4.29Buts par match 4.20
3.71Buts contre par match 7.56
28.00%Pourcentage en avantage numérique21.74%
76.12%Pourcentage en désavantage numérique53.33%
Meneurs d'équipe
Brendan GaunceButs
Brendan Gaunce
11
Matt BartkowskiPasses
Matt Bartkowski
12
Brendan GauncePoints
Brendan Gaunce
21
Alex LimogesPlus/Moins
Alex Limoges
6
Garret SparksVictoires
Garret Sparks
12
Tom McCollumPourcentage d’arrêts
Tom McCollum
0.914

Statistiques d’équipe
Buts pour
103
4.29 GFG
Tirs pour
1030
42.92 Avg
Pourcentage en avantage numérique
28.0%
14 GF
Début de zone offensive
40.2%
Buts contre
89
3.71 GAA
Tirs contre
873
36.38 Avg
Pourcentage en désavantage numérique
76.1%
16 GA
Début de la zone défensive
40.0%
Informations de l'équipe

Directeur généralDylan Nadeau
DivisionCentrale
ConférenceOuest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro20
Équipe Mineure20
Limite contact 40 / 250
Espoirs10


Historique d'équipe

Saison actuelle12-9-3 (27PTS)
Historique142-347-18 (0.280%)
Apparitions en séries éliminatoires 0
Historique en séries éliminatoires (W-L)-
Coupe Stanley0


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
1Hudson FaschingX100.00593595628472736163626162617166050630251737,500$
2Mario KempeXXX100.00624383637180756569665856678273050630321700,000$
3Martin KautXX100.006439866578807564586263576563620506302121,319,167$
4Paul CareyXXX100.00503595647782786163606261638279050630321700,000$
5Nick BaptisteX100.00693986607884795861596257637169050620251787,500$
6Nick MoutreyX100.00797382568880855451535559547169050610251925,000$
7Ryan OlsenX100.00665471587588935663545753587367050600261701,667$
8Damien Riat (R)X100.00613987577179845658555453566764050590232925,000$
9Samuel KurkerX100.00723593538163675255545156527367050580261700,000$
10Jack Badini (R)X100.00663593537569745254515053526563050570222815,000$
11William BorgenX100.00833987588487805730585464476965050620231925,000$
12Reece WillcoxX100.00783691588781865730565259467367050610261675,000$
13Reece ScarlettX100.00624284597183885830575556477568050600271700,000$
14Markus Phillips (R)X100.00664285567577825530575458476362050590212801,667$
15Joe MorrowX100.00655669577478735830565354467769050590271700,000$
Rayé
1Matt DonovanX100.00693770617888935830645459467971050620301675,000$
MOYENNE D’ÉQUIPE100.0067428559787980584858565754726805061
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 SPÂgeContratSalaire
1Garret Sparks100.0071858384706971706971707581050620271750,000$
2Tom McCollum100.0068716984676668676668678086050600301650,000$
Rayé
1Adam Wilcox100.0066868472656466656466657783050590271650,000$
2Filip Larsson100.00617169796059616059616065690505702221,100,000$
MOYENNE D’ÉQUIPE100.006778768066656766656766748005060
Nom de l’entraîneur 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
1Paul CareyMoose (WIN)C/LW/RW241513281820537110358313.64%745318.8824618420000251060.00%4000011.2401000111
2Mario KempeMoose (WIN)C/LW/RW2472027174030619824697.14%746219.2714511540112351059.11%49400001.1702000103
3Martin KautMoose (WIN)LW/RW24121123300215712933859.30%1449220.5310116390002584045.00%4000000.9300000011
4Brendan GaunceJetsC211110213220626197195511.34%739618.870225250001381160.95%58900011.0601000201
5Hudson FaschingMoose (WIN)RW2411920-50093993207311.83%135014.592359270000150150.00%4600101.1400000102
6Matt DonovanMoose (WIN)D20020202606024278200.00%2849224.62055736000149000.00%000000.8100000210
7Reece WillcoxMoose (WIN)D243141761405921499256.12%2949020.460331436000240000.00%000000.6900000101
8Nick MoutreyMoose (WIN)LW24791614120642254122712.96%635114.661015261011171065.38%2600000.9100000010
9Reece ScarlettMoose (WIN)D24412166100302238112110.53%3550220.943141036000152010.00%000000.6400000000
10Matt BartkowskiJetsD92121402031020141210.00%1521924.36044518000121000.00%000001.2800000010
11Markus PhillipsMoose (WIN)D243111491003114218614.29%1835814.9200000000015100.00%000000.7800000101
12Riley StillmanJetsD1131013210031303313189.09%2326724.300111419000015000.00%000000.9700000012
13William BorgenMoose (WIN)D154913316056252781314.81%2637925.32213927011133000.00%000000.6800000112
14Joe MorrowMoose (WIN)D243101392004113166818.75%3434214.280000000002000.00%000000.7600000020
15Brad MaloneJetsC/LW206612-28050317824557.69%329714.852136120002100061.03%21300000.8100000010
16Ryan OlsenMoose (WIN)C24551024013203882613.16%21677.0000000000001053.68%19000001.1900000010
17Alex LimogesJetsC5426600082191819.05%29519.0100000000000042.86%700001.2600000010
18Damien RiatMoose (WIN)RW2415644012264815382.08%436115.07000190000131054.24%5900000.3300000000
19Nick BaptisteMoose (WIN)RW24246-62014364818364.17%127511.4900000000000053.13%22400000.4400000000
20Samuel KurkerMoose (WIN)RW18325040681521120.00%11367.6000000000001041.38%2900000.7300000100
Statistiques d’équipe totales ou en moyenne407106194300911500597565106029669910.00%263689316.941429431304141231444612357.79%195700120.8704000111214
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
1Garret SparksMoose (WIN)2412730.8993.48127520747320110.4005240120
2Tom McCollumMoose (WIN)40200.9144.1117500121400000.0000024000
Statistiques d’équipe totales ou en moyenne2812930.9013.56145020868720110.40052424120


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 Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Adam WilcoxMoose (WIN)G271992-11-26No189 Lbs6 ft0NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Damien RiatMoose (WIN)RW231997-02-26Yes180 Lbs6 ft0NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien NHL
Filip LarssonMoose (WIN)G221998-08-17No194 Lbs6 ft2NoNoNo2Pro & Farm1,100,000$0$0$No1,100,000$Lien / Lien NHL
Garret SparksMoose (WIN)G271993-06-28No201 Lbs6 ft3NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Hudson FaschingMoose (WIN)RW251995-07-28No204 Lbs6 ft3NoNoNo1Pro & Farm737,500$0$0$NoLien / Lien NHL
Jack BadiniMoose (WIN)LW221998-01-19Yes203 Lbs6 ft0NoNoNo2Pro & Farm815,000$0$0$No815,000$Lien NHL
Joe MorrowMoose (WIN)D271992-12-09No196 Lbs6 ft0NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Mario KempeMoose (WIN)C/LW/RW321988-09-19No185 Lbs6 ft0NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Markus PhillipsMoose (WIN)D211999-03-21Yes202 Lbs6 ft0NoNoNo2Pro & Farm801,667$0$0$No801,667$Lien NHL
Martin KautMoose (WIN)LW/RW211999-10-02No190 Lbs6 ft2NoNoNo2Pro & Farm1,319,167$0$0$No1,319,167$Lien / Lien NHL
Matt DonovanMoose (WIN)D301990-05-09No205 Lbs6 ft1NoNoNo1Pro & Farm675,000$0$0$NoLien / Lien NHL
Nick BaptisteMoose (WIN)RW251995-08-04No203 Lbs6 ft1NoNoNo1Pro & Farm787,500$0$0$NoLien / Lien NHL
Nick MoutreyMoose (WIN)LW251995-06-24No222 Lbs6 ft3NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Paul CareyMoose (WIN)C/LW/RW321988-09-24No196 Lbs6 ft1NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Reece ScarlettMoose (WIN)D271993-03-31No168 Lbs6 ft1NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Reece WillcoxMoose (WIN)D261994-03-20No205 Lbs6 ft4NoNoNo1Pro & Farm675,000$0$0$NoLien / Lien NHL
Ryan OlsenMoose (WIN)C261994-03-25No187 Lbs6 ft1NoNoNo1Pro & Farm701,667$0$0$NoLien / Lien NHL
Samuel KurkerMoose (WIN)RW261994-04-08No202 Lbs6 ft2NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Tom McCollumMoose (WIN)G301989-12-07No220 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
William BorgenMoose (WIN)D231996-12-19No205 Lbs6 ft3NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2025.85198 Lbs6 ft11.25796,875$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Martin KautDamien Riat40122
2Nick MoutreyMario KempePaul Carey30122
3Nick BaptisteHudson Fasching20122
4Samuel KurkerRyan Olsen10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1William Borgen40122
2Reece WillcoxReece Scarlett30122
3Markus PhillipsJoe Morrow20122
4William Borgen10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Martin KautMario Kempe60122
2Nick MoutreyMario KempePaul Carey40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1William Borgen60122
2Reece WillcoxReece Scarlett40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Martin Kaut60122
2Mario KempeNick Moutrey40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1William Borgen60122
2Reece WillcoxReece Scarlett40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
160122William Borgen60122
2Mario Kempe40122Reece WillcoxReece Scarlett40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Martin Kaut60122
2Mario KempeNick Moutrey40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1William Borgen60122
2Reece WillcoxReece Scarlett40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Martin KautMario KempeWilliam Borgen
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Martin KautMario KempeWilliam Borgen
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Hudson Fasching, Nick Baptiste, Nick MoutreyHudson Fasching, Nick BaptisteHudson Fasching
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Reece Scarlett, Markus Phillips, Joe MorrowReece ScarlettReece Scarlett, Markus Phillips
Tirs de pénalité
, Mario Kempe, Paul Carey, Martin Kaut, Hudson Fasching
Gardien
#1 : Garret Sparks, #2 : Tom McCollum


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
TotalDomicileVisiteur
# 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
1Admirals11000000936110000009360000000000021.000917260053311906533835433310287226200.00%110.00%049186356.89%44685951.92%23242354.85%605436550161295149
2Barracuda312000001017-71100000053220200000514-920.333101828005331190104338354333101242818646233.33%8450.00%049186356.89%44685951.92%23242354.85%605436550161295149
3Comets11000000743000000000001100000074321.00071421005331190433383543331035962211100.00%3233.33%149186356.89%44685951.92%23242354.85%605436550161295149
4Condors21000100651110000005321000010012-130.7506101600533119090338354333107019628400.00%2150.00%049186356.89%44685951.92%23242354.85%605436550161295149
5Devils11000000431110000004310000000000021.0004711005331190353383543331051146292150.00%30100.00%049186356.89%44685951.92%23242354.85%605436550161295149
6Gulls31200000151411100000071620200000813-520.33315274200533119015533835433310994118608450.00%8362.50%049186356.89%44685951.92%23242354.85%605436550161295149
7Heat1010000024-2000000000001010000024-200.00022400533119056338354333104111828400.00%4250.00%049186356.89%44685951.92%23242354.85%605436550161295149
8IceHogs11000000523110000005230000000000021.00059140053311904333835433310338225300.00%10100.00%049186356.89%44685951.92%23242354.85%605436550161295149
9Marlies1000000145-11000000145-10000000000010.5004610005331190423383543331051184372150.00%10100.00%049186356.89%44685951.92%23242354.85%605436550161295149
10Monsters1010000035-2000000000001010000035-200.00036910533119038338354333104876295120.00%30100.00%049186356.89%44685951.92%23242354.85%605436550161295149
11Penguins1010000027-51010000027-50000000000000.000246005331190263383543331033612232150.00%6183.33%049186356.89%44685951.92%23242354.85%605436550161295149
12Rampage11000000514110000005140000000000021.0005101500533119025338354333102311102211100.00%50100.00%049186356.89%44685951.92%23242354.85%605436550161295149
13Reign21100000330110000003121010000002-220.500358005331190543383543331061211247400.00%60100.00%049186356.89%44685951.92%23242354.85%605436550161295149
14Roadrunners1010000025-31010000025-30000000000000.00023500533119039338354333104711628200.00%3166.67%049186356.89%44685951.92%23242354.85%605436550161295149
15Sound Tigers1000000112-11000000112-10000000000010.50012300533119027338354333103278182150.00%40100.00%049186356.89%44685951.92%23242354.85%605436550161295149
16Stars11000000743110000007430000000000021.0007121900533119056338354333103510827100.00%40100.00%049186356.89%44685951.92%23242354.85%605436550161295149
17Wild220000001851300000000000220000001851341.000183351005331190132338354333106212105411100.00%5180.00%049186356.89%44685951.92%23242354.85%605436550161295149
Total241290010210389141392000025940191137001004449-5270.563103185288105331190103033835433310873240142567501428.00%671676.12%149186356.89%44685951.92%23242354.85%605436550161295149
_Since Last GM Reset241290010210389141392000025940191137001004449-5270.563103185288105331190103033835433310873240142567501428.00%671676.12%149186356.89%44685951.92%23242354.85%605436550161295149
_Vs Conference1910800100856817981000004823251027001003745-8210.553851522371053311908573383543331067118610643841921.95%501374.00%049186356.89%44685951.92%23242354.85%605436550161295149
_Vs Division1251000004347-44300000020812821000002339-16100.4174376119005331190502338354333104301296824927725.93%311261.29%149186356.89%44685951.92%23242354.85%605436550161295149

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2427SOL1103185288103087324014256710
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
24129010210389
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
139200025940
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
113701004449
Derniers 10 matchs
WLOTWOTL SOWSOL
440101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
501428.00%671676.12%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
338354333105331190
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
49186356.89%44685951.92%23242354.85%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
605436550161295149


Derniers matchs 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 - 2021-10-137Moose5Gulls7ALSommaire du match
5 - 2021-10-1632Moose1Barracuda5ALSommaire du match
8 - 2021-10-1948Moose8Wild2AWSommaire du match
10 - 2021-10-2159Gulls1Moose7BWSommaire du match
12 - 2021-10-2375Admirals3Moose9BWSommaire du match
15 - 2021-10-2695Moose3Gulls6ALSommaire du match
17 - 2021-10-28109Moose0Reign2ALSommaire du match
19 - 2021-10-30122Moose4Barracuda9ALSommaire du match
22 - 2021-11-02139Stars4Moose7BWSommaire du match
25 - 2021-11-05157IceHogs2Moose5BWSommaire du match
26 - 2021-11-06170Sound Tigers2Moose1BLXXSommaire du match
29 - 2021-11-09187Rampage1Moose5BWSommaire du match
31 - 2021-11-11202Barracuda3Moose5BWSommaire du match
33 - 2021-11-13218Reign1Moose3BWSommaire du match
36 - 2021-11-16240Condors3Moose5BWSommaire du match
38 - 2021-11-18255Moose1Condors2ALXSommaire du match
39 - 2021-11-19259Moose7Comets4AWSommaire du match
42 - 2021-11-22284Penguins7Moose2BLSommaire du match
44 - 2021-11-24295Moose3Monsters5ALSommaire du match
46 - 2021-11-26307Moose10Wild3AWSommaire du match
47 - 2021-11-27325Moose2Heat4ALSommaire du match
49 - 2021-11-29335Roadrunners5Moose2BLSommaire du match
53 - 2021-12-03363Devils3Moose4BWSommaire du match
55 - 2021-12-05379Marlies5Moose4BLXXSommaire du match
57 - 2021-12-07394Checkers-Moose-
59 - 2021-12-09409Moose-Palm Springs-
60 - 2021-12-10417Moose-Comets-
64 - 2021-12-14445Americans-Moose-
67 - 2021-12-17468Bears-Moose-
69 - 2021-12-19482Rampage-Moose-
71 - 2021-12-21498Moose-Admirals-
72 - 2021-12-22506Moose-Stars-
77 - 2021-12-27531Wild-Moose-
79 - 2021-12-29547IceHogs-Moose-
81 - 2021-12-31565Moose-Heat-
83 - 2022-01-02580Moose-Wolves-
85 - 2022-01-04592Moose-Roadrunners-
87 - 2022-01-06606Moose-Eagles-
89 - 2022-01-08620Palm Springs-Moose-
91 - 2022-01-10633Wild-Moose-
94 - 2022-01-13653Moose-Griffins-
96 - 2022-01-15674Senators-Moose-
97 - 2022-01-16681Condors-Moose-
99 - 2022-01-18695Moose-Bears-
101 - 2022-01-20708Moose-Admirals-
103 - 2022-01-22722Moose-Bruins-
104 - 2022-01-23732Moose-Penguins-
106 - 2022-01-25749Thunderbirds-Moose-
108 - 2022-01-27765Comets-Moose-
110 - 2022-01-29775Moose-Rampage-
113 - 2022-02-01800Moose-Phantoms-
135 - 2022-02-23813Moose-Stars-
137 - 2022-02-25826Moose-Eagles-
139 - 2022-02-27842Moose-Roadrunners-
141 - 2022-03-01856Rocket-Moose-
144 - 2022-03-04878Stars-Moose-
146 - 2022-03-06895Wolf Pack-Moose-
148 - 2022-03-08910Crunch-Moose-
150 - 2022-03-10921Moose-Devils-
151 - 2022-03-11930Moose-Sound Tigers-
153 - 2022-03-13947Moose-Rampage-
155 - 2022-03-15958Wolves-Moose-
158 - 2022-03-18979Bruins-Moose-
160 - 2022-03-20997Moose-IceHogs-
162 - 2022-03-221010Wolves-Moose-
165 - 2022-03-251030Monsters-Moose-
167 - 2022-03-271053Roadrunners-Moose-
170 - 2022-03-301068Moose-Americans-
171 - 2022-03-311075Moose-Marlies-
173 - 2022-04-021096Reign-Moose-
177 - 2022-04-061124Griffins-Moose-
179 - 2022-04-081141Eagles-Moose-
181 - 2022-04-101160Moose-Senators-
182 - 2022-04-111162Moose-Rocket-
184 - 2022-04-131179Palm Springs-Moose-
186 - 2022-04-151194Moose-Thunderbirds-
187 - 2022-04-161203Moose-Crunch-
190 - 2022-04-191223Moose-Wolf Pack-
192 - 2022-04-211237Moose-Checkers-
195 - 2022-04-241267Eagles-Moose-
198 - 2022-04-271286Phantoms-Moose-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
200 - 2022-04-291308Heat-Moose-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
28 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
470,839$ 1,593,751$ 294,417$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 470,839$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 146 7,929$ 1,157,634$




TotalDomicileVisiteur
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
482116300062185442-2574182700042102207-105413360002083235-15236185332517110775844224707627357224238122497316734595712.42%38511270.91%0817237034.47%960317930.20%404134729.99%14039072594639962411
582175701412241388-1474192601311119184-654183100101122204-8244241402643210101657325610878841826307683745519702205123.18%2096767.94%11115259542.97%822222936.88%600139942.89%196314051989545996494
682333501535314318-441161800322158169-11411717012131561497843145578711201361037133710108310901173351296246621832314419.05%2014975.62%31390295347.07%1329304743.62%633139545.38%1937137720195711009499
78287100102197513-3164163300101106250-144412380000191263-17219197324521100736460266708649188804397139239122141702615.29%1816663.54%0987268936.71%943280833.58%536147436.36%166711622295553968445
882126700120257596-3394183200100128283-1554143500020129313-184292574256821001138260332801152107510834870138026019381603421.25%1064656.60%0993265537.40%952283633.57%590159536.99%163711812359536934421
982314501032297387-9041162300011149183-3441152201021148204-56722975298262401248980323901095106510633926113139318671724425.58%1664374.10%21511291751.80%1474314446.88%666147345.21%178612682160560998476
10241290010210389141392000025940191137001004449-527103185288105331190103033835433310873240142567501428.00%671676.12%149186356.89%44685951.92%23242354.85%605436550161295149
Total Saison régulière5161243470312151515942733-113925972161018898211316-49525752186024767731417-644311159427544348985365548038818443338618860575757248927166308012412146227018.47%131539969.66%773041704242.86%69261810238.26%3661910640.20%11002773813969356861652899