Connexion

Moose
GP: 80 | W: 37 | L: 29 | OTL: 14 | P: 88
GF: 342 | GA: 352 | PP%: 22.89% | PK%: 73.72%
DG: Pascal Verret | Morale : 30 | Moyenne d’équipe : 64
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Centre de jeu
Wolfpack
43-33-4, 90pts
4
FINAL
2 Moose
37-29-14, 88pts
Team Stats
OTL1StreakL2
24-15-1Home Record20-14-6
19-18-3Away Record17-15-8
6-2-2Last 10 Games4-4-2
4.39Buts par match 4.28
4.01Buts contre par match 4.40
23.26%Pourcentage en avantage numérique22.89%
75.85%Pourcentage en désavantage numérique73.72%
Rampage
39-34-7, 85pts
6
FINAL
2 Moose
37-29-14, 88pts
Team Stats
W1StreakL2
20-16-4Home Record20-14-6
19-18-3Away Record17-15-8
5-5-0Last 10 Games4-4-2
3.75Buts par match 4.28
3.90Buts contre par match 4.40
21.31%Pourcentage en avantage numérique22.89%
79.44%Pourcentage en désavantage numérique73.72%
Meneurs d'équipe
Buts
Miro Aaltonen
56
Passes
Miro Aaltonen
85
Points
Miro Aaltonen
141
Plus/Moins
Nikolay Goldobin
14
Victoires
Elvis Merzlikins
30
Pourcentage d’arrêts
Elvis Merzlikins
0.886

Statistiques d’équipe
Buts pour
342
4.28 GFG
Tirs pour
2631
32.89 Avg
Pourcentage en avantage numérique
22.9%
76 GF
Début de zone offensive
36.3%
Buts contre
352
4.40 GAA
Tirs contre
2677
33.46 Avg
Pourcentage en désavantage numérique
73.7%
82 GA
Début de la zone défensive
35.8%
Informations de l'équipe

Directeur généralPascal Verret
EntraîneurAdams Oates
DivisionThayer-Tutt
ConférenceRobert-Lebel
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,791
Billets de saison300


Informations de la formation

Équipe Pro32
Équipe Mineure18
Limite contact 50 / 250
Espoirs0


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
1Miro Aaltonen (R)X100.0069298187747566797177736276535043507202311,250,000$
2Brendan Lemieux (R)X100.007745707478617576617673685852436539700204900,000$
3Frank Vatrano (R)X100.008845697774667876627565696550486044700221500,000$
4Justin Bailey (R)X100.007034836477726871757084556649435750690211900,000$
5Nathan Walker (R)X100.006831707569766676707370617346485546680222750,000$
6Roope Hintz (R)X100.007546747469627166647372647046446949680201500,000$
7Sam Reinhart (R)X100.006535767165707274798173545645436745680204990,000$
8Dominik Kahun (R)X100.005530806757757371848167535849446132660211500,000$
9Nikolay Goldobin (R)X100.006137807366675478616867657742426131660202750,000$
10Chase De Leo (R)X100.006230796761666963667871475843436334640202750,000$
11Mathieu Joseph (R)X100.007037646972567171536371636142426553640191500,000$
12Michael McLeod (R)X100.004537698053574580566167587140407220620182500,000$
13Troy Stetcher (R)X100.006532758871567682428857735255465539710221500,000$
14Mirco Mueller (R)X100.006922816971737369537260805350445430700211700,000$
15Ludwig Bystrom (R)X100.006923767668667275467155755553444536690221600,000$
16Tony DeAngelo (R)X100.005837788064647675398854745157435950690202800,000$
17Vladislav Gavrikov (R)X100.006745826368706567557360735853465839680211500,000$
18Erik Cernak (R)X100.007435666377795549326758714343427050650191500,000$
Rayé
1Rem Pitlick (R)X100.005529657959685177696056557042427333620192500,000$
2Julien Gauthier (R)X100.006028755372585863576772465943416319600192500,000$
3Carl Grundstrom (R)X100.006552815762676159605760596341438022600192500,000$
4Mitchell Stephens (R)X100.004725886864776246696256594441416719580191500,000$
5Nathan Bastian (R)X100.004738715559695964776257475741435920580192500,000$
6Max Jones (R)X100.006539656367507158456456524340406919570182500,000$
7David Kase (R)X100.006030585653556356595762426141415520550191500,000$
8Tim Gettinger (R)X100.005427634758565359495660296340406820520182500,000$
9Matthew Benning (R)X100.006522786664696362466757695146465020640221400,000$
10Jesse Graham (R)X100.005440707764576666466857694644444419630221450,000$
11Josh Mahura (R)X100.004934736952535673236550593640406719580182500,000$
MOYENNE D’ÉQUIPE100.00633474696665656858706360584643613364
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
1Elvis Merzlikins100.00628362737672708883726452465543730212900,000$
2Filip Gustavsson (R)100.00586269574673745046735840408248580182500,000$
Rayé
1Joey Daccord100.00646564454872725150655143426220580202550,000$
MOYENNE D’ÉQUIPE100.0061706558577272636070584543663763
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Adams Oates53568572375954CAN522950,000$


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
1Miro AaltonenMoose (Win)C805685141322010713334411418816.28%33168621.092226486628222491299249.82%22727324031.675140001164
2Troy StetcherMoose (Win)D762281103-854011413722887949.65%95187224.63122234512780332120510.00%05564001.10000002112
3Brendan LemieuxMoose (Win)LW67353772-7980147762476510314.17%35137920.607101734188123111581243.18%1324430021.0413000415
4Iiro PakarinenJetsRW59343771-148014469189699817.99%30117619.931010202717531491142255.51%2364813001.2115000245
5Frank VatranoMoose (Win)RW612735620580165851804611015.00%35115118.88612182418501151032043.14%1024320001.0804000214
6Sam ReinhartMoose (Win)RW76283260-27360109602187012812.84%31128816.9591221391890001282257.27%1104117010.9300000211
7Roope HintzMoose (Win)LW65213455-3715131951605010013.13%35120818.5978151818400001032144.99%4893818000.9103001124
8Nathan WalkerMoose (Win)RW662727541138098661654310016.36%22113717.234711231591012954248.96%963218020.9515000333
9Nikolay GoldobinMoose (Win)LW70242145141006655150398116.00%14102614.6704491202133803136.36%1102516000.8807000412
10Tony DeAngeloMoose (Win)D7873845-173758514314662734.79%108189424.2841418262820111144110.00%05065000.4800000012
11Justin BaileyMoose (Win)LW751430441140110701104610212.73%29125916.8003371370112820052.56%782416000.7024000322
12Dominik KahunMoose (Win)C77221941-2020079103153678514.38%21127016.50448132020000321355.54%9921611000.6500000051
13Michael McLeodMoose (Win)C70201939-34004564132418915.15%3080311.48011160111731048.13%4282217000.9736000102
14Ludwig BystromMoose (Win)D8032831-255510214110639492.83%110174421.81145102240224247000.00%02157000.3600000001
15Mathieu JosephMoose (Win)RW76171229-23809958102365216.67%2788811.6901111610171091342.86%212119100.6501000011
16Chase De LeoMoose (Win)C68111728940433689275112.36%66649.77000021013752048.59%284168000.8400000210
17Rem PitlickMoose (Win)LW671111224180593890305712.22%86659.93000026000020141.43%701711000.6613000021
18Vladislav GavrikovMoose (Win)D80021211214068998028310.00%102165420.6801142260110192000.00%01743000.2501000000
19Erik CernakMoose (Win)D802171995601021025820213.45%77136517.070001560000188100.00%0543000.2800000100
20Mirco MuellerMoose (Win)D6451419-91601011196735227.46%101133920.930111431013161200.00%0837000.2800000220
21Matthew BenningMoose (Win)D301910280153421894.76%2638712.920000100008000.00%019000.5200000000
22Carl GrundstromMoose (Win)RW57167-32037192911193.45%104397.7200000000070080.00%517000.3200000000
23Mitchell StephensMoose (Win)C61235002442225.00%3508.4101104000040063.33%3000001.1900000001
24Jordan MartinookJetsLW5011-920948250.00%17615.30000030001160038.46%1331000.2600000000
25Julien GauthierMoose (Win)RW8011200343220.00%0769.58000000000000100.00%201000.2600000000
26Jesse GrahamMoose (Win)D1000100000000.00%055.550000000000000.00%001000.0000000000
27Josh MahuraMoose (Win)D3000000110000.00%2289.330000000000000.00%000000.0000000000
28Max JonesMoose (Win)LW8000-240431110.00%2648.110000000000000.00%010000.0000000000
Statistiques d’équipe totales ou en moyenne15533896341023-40763152045181830801040167212.63%9932660617.13861412273552999121628642282392150.05%5470622566180.771456001404441
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
1Elvis MerzlikinsMoose (Win)653021110.8863.693726202292008988210.500246414323
2Filip GustavssonMoose (Win)41151450.8744.112132601461158636330.524213442000
Statistiques d’équipe totales ou en moyenne1064535160.8823.8458598037531661624540.511459856323


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 restantPlafond 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
Brendan LemieuxMoose (Win)LW201996-01-01Yes215 Lbs6 ft1NoNoNo4Pro & Farm900,000$0$0$No1,200,000$2,000,000$2,800,000$
Carl GrundstromMoose (Win)RW191997-01-01Yes194 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Chase De LeoMoose (Win)C201996-01-01Yes179 Lbs5 ft9NoNoNo2Pro & Farm750,000$0$0$No750,000$
David KaseMoose (Win)RW191997-01-01Yes169 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Dominik KahunMoose (Win)C211995-01-01Yes175 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Elvis MerzlikinsMoose (Win)G211995-01-01No183 Lbs6 ft2NoNoNo2Pro & Farm900,000$0$0$No1,200,000$
Erik CernakMoose (Win)D191997-01-01Yes233 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Filip GustavssonMoose (Win)G181998-01-01Yes183 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$
Frank VatranoMoose (Win)RW221994-01-01Yes197 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Jesse GrahamMoose (Win)D221994-01-01Yes170 Lbs5 ft11NoNoNo1Pro & Farm450,000$0$0$No
Joey DaccordMoose (Win)G201996-01-01No197 Lbs6 ft2NoNoNo2Pro & Farm550,000$0$0$No600,000$
Josh MahuraMoose (Win)D181998-01-01Yes185 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Julien GauthierMoose (Win)RW191997-01-01Yes227 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$
Justin BaileyMoose (Win)LW211995-01-01Yes185 Lbs6 ft0NoNoNo1Pro & Farm900,000$0$0$No
Ludwig BystromMoose (Win)D221994-01-01Yes169 Lbs6 ft0NoNoNo1Pro & Farm600,000$0$0$No
Mathieu JosephMoose (Win)RW191997-01-01Yes190 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$No
Matthew BenningMoose (Win)D221994-01-01Yes180 Lbs6 ft0NoNoNo1Pro & Farm400,000$0$0$No
Max JonesMoose (Win)LW181998-01-01Yes220 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Michael McLeodMoose (Win)C181998-01-01Yes187 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$
Mirco MuellerMoose (Win)D211995-01-01Yes185 Lbs6 ft4NoNoNo1Pro & Farm700,000$0$0$No
Miro AaltonenMoose (Win)C231993-01-01Yes185 Lbs5 ft10NoNoNo1Pro & Farm1,250,000$0$0$No
Mitchell StephensMoose (Win)C191997-01-01Yes193 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Nathan BastianMoose (Win)RW191997-01-01Yes205 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$
Nathan WalkerMoose (Win)RW221994-01-01Yes186 Lbs5 ft9NoNoNo2Pro & Farm750,000$0$0$No850,000$
Nikolay GoldobinMoose (Win)LW201996-01-01Yes196 Lbs5 ft11NoNoNo2Pro & Farm750,000$0$0$No850,000$
Rem PitlickMoose (Win)LW191997-01-01Yes196 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
Roope HintzMoose (Win)LW201996-01-01Yes220 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Sam ReinhartMoose (Win)RW201996-01-01Yes192 Lbs6 ft1NoNoNo4Pro & Farm990,000$0$0$No990,000$1,600,000$2,500,000$
Tim GettingerMoose (Win)LW181998-01-01Yes220 Lbs6 ft6NoNoNo2Pro & Farm500,000$0$0$No500,000$
Tony DeAngeloMoose (Win)D201996-01-01Yes180 Lbs5 ft11NoNoNo2Pro & Farm800,000$0$0$No950,000$
Troy StetcherMoose (Win)D221994-01-01Yes186 Lbs5 ft10NoNoNo1Pro & Farm500,000$0$0$No
Vladislav GavrikovMoose (Win)D211995-01-01Yes213 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3220.06194 Lbs6 ft11.66615,313$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Brendan LemieuxMiro AaltonenSam Reinhart40122
2Justin BaileyDominik KahunFrank Vatrano30122
3Roope HintzMichael McLeodNathan Walker20122
4Nikolay GoldobinChase De LeoMathieu Joseph10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Troy StetcherMirco Mueller40122
2Vladislav GavrikovTony DeAngelo30122
3Ludwig BystromErik Cernak20122
4Tony DeAngeloErik Cernak10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Brendan LemieuxMiro AaltonenSam Reinhart60122
2Roope HintzDominik KahunFrank Vatrano40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Troy StetcherTony DeAngelo60122
2Vladislav GavrikovLudwig Bystrom40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Michael McLeodMathieu Joseph60122
2Miro AaltonenFrank Vatrano40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mirco MuellerLudwig Bystrom60122
2Vladislav GavrikovErik Cernak40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Frank Vatrano60122Mirco MuellerLudwig Bystrom60122
2Miro Aaltonen40122Vladislav GavrikovErik Cernak40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Miro AaltonenSam Reinhart60122
2Dominik KahunFrank Vatrano40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Troy StetcherLudwig Bystrom60122
2Vladislav GavrikovTony DeAngelo40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Brendan LemieuxMiro AaltonenSam ReinhartTroy StetcherTony DeAngelo
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nathan WalkerMiro AaltonenMathieu JosephMirco MuellerLudwig Bystrom
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Justin Bailey, Sam Reinhart, Roope HintzNathan Walker, Justin BaileyNathan Walker
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Mirco Mueller, Erik Cernak, Vladislav GavrikovVladislav GavrikovLudwig Bystrom, Vladislav Gavrikov
Tirs de pénalité
Nathan Walker, Miro Aaltonen, Nikolay Goldobin, Frank Vatrano, Roope Hintz
Gardien
#1 : Elvis Merzlikins, #2 : Filip Gustavsson


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
1Admirals403000101627-11302000101219-71010000048-420.250162440009011713014127847895868701544940757228.57%20575.00%0900177650.68%869175149.63%699136951.06%173797016877481454733
2Barracuda621000033334-1311000011314-1310000022020070.583335386009011713014208847895868702208360148311135.48%301066.67%1900177650.68%869175149.63%699136951.06%173797016877481454733
3Bears220000001073110000006421100000043141.0001016260090117130146484789586870782418514375.00%9366.67%0900177650.68%869175149.63%699136951.06%173797016877481454733
4Comets20001001101001000000156-11000100054130.7501014240090117130146384789586870732910359333.33%50100.00%0900177650.68%869175149.63%699136951.06%173797016877481454733
5Condors633000002022-2321000001110131200000912-360.50020345400901171301419484789586870197856012930413.33%30873.33%1900177650.68%869175149.63%699136951.06%173797016877481454733
6Crunch210000011091110000005321000000156-130.75010192900901171301478847895868704317184710330.00%9277.78%0900177650.68%869175149.63%699136951.06%173797016877481454733
7Devils2110000078-1110000003121010000047-320.50071118009011713014698478958687052178426233.33%40100.00%0900177650.68%869175149.63%699136951.06%173797016877481454733
8Eagles30100002611-51000000134-12010000137-420.333610160090117130149984789586870953112841417.14%6266.67%0900177650.68%869175149.63%699136951.06%173797016877481454733
9Griffins632010002122-1311010001011-1321000001111080.66721345500901171301417984789586870183455613929413.79%21576.19%2900177650.68%869175149.63%699136951.06%173797016877481454733
10Heat431000001697220000009272110000077060.7501627430090117130141258478958687012246309316425.00%15380.00%0900177650.68%869175149.63%699136951.06%173797016877481454733
11Icehogs311001001314-11000010056-12110000088030.5001322350090117130141058478958687012140166711436.36%8450.00%1900177650.68%869175149.63%699136951.06%173797016877481454733
12Little Stars412000011721-4311000011517-21010000024-230.3751729460090117130141238478958687014355228612433.33%12466.67%1900177650.68%869175149.63%699136951.06%173797016877481454733
13Marlies31100001151501010000046-221000001119230.500152338109011713014998478958687011919208114642.86%10460.00%0900177650.68%869175149.63%699136951.06%173797016877481454733
14Monsters32000001171342200000014951000000134-150.83317324900901171301498847895868701063834559111.11%17288.24%0900177650.68%869175149.63%699136951.06%173797016877481454733
15Penguins2110000078-11010000036-31100000042220.500713200090117130147384789586870501416509222.22%8362.50%0900177650.68%869175149.63%699136951.06%173797016877481454733
16Phantoms312000001014-41100000064220200000410-620.3331014240090117130148384789586870118281878800.00%9188.89%0900177650.68%869175149.63%699136951.06%173797016877481454733
17Punishers2010010069-31000010034-11010000035-210.250610161090117130146184789586870752920468112.50%10190.00%1900177650.68%869175149.63%699136951.06%173797016877481454733
18Rampage20200000614-81010000026-41010000048-400.000611170090117130146684789586870631718418225.00%9633.33%0900177650.68%869175149.63%699136951.06%173797016877481454733
19Reign312000001316-31010000067-12110000079-220.33313213400901171301498847895868709832267513323.08%13469.23%0900177650.68%869175149.63%699136951.06%173797016877481454733
20Rocket623001001920-131200000119231100100811-350.41719294810901171301420284789586870189604611731412.90%23578.26%0900177650.68%869175149.63%699136951.06%173797016877481454733
21Senators32000010191272200000012661000001076161.00019345300901171301493847895868709231226610550.00%11281.82%0900177650.68%869175149.63%699136951.06%173797016877481454733
22Sound Tigers220000001468110000009271100000054141.00014233700901171301481847895868705612143313430.77%7185.71%0900177650.68%869175149.63%699136951.06%173797016877481454733
23Thunderbirds210000101486110000008351000001065141.0001422360090117130147784789586870732212431119.09%6183.33%2900177650.68%869175149.63%699136951.06%173797016877481454733
24Wolfpack2110000067-11010000024-21100000043120.50061016009011713014658478958687062271854500.00%9277.78%0900177650.68%869175149.63%699136951.06%173797016877481454733
25Wolves31100001171611010000067-121000001119230.500172643009011713014101847895868709528226114214.29%11463.64%1900177650.68%869175149.63%699136951.06%173797016877481454733
Total803229023311342352-10401814012141831701340141501127159182-23880.550342561903309011713014263184789586870267787863617963327622.89%3128273.72%10900177650.68%869175149.63%699136951.06%173797016877481454733
_Since Last GM Reset803229023311342352-10401814012141831701340141501127159182-23880.550342561903309011713014263184789586870267787863617963327622.89%3128273.72%10900177650.68%869175149.63%699136951.06%173797016877481454733
_Vs Conference50211901225212218-6251290111111310310259100011499115-16550.550212347559209011713014161184789586870171955642811232094822.97%2075374.40%5900177650.68%869175149.63%699136951.06%173797016877481454733
_Vs Division24109011039398-5125501001454411254001024854-6260.54293150243109011713014783847895868707892732225331212319.01%1042873.08%4900177650.68%869175149.63%699136951.06%173797016877481454733

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8088L234256190326312677878636179630
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
80322923311342352
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4018141214183170
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4014151127159182
Derniers 10 matchs
WLOTWOTL SOWSOL
440002
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3327622.89%3128273.72%10
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
847895868709011713014
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
900177650.68%869175149.63%699136951.06%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
173797016877481454733


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
1 - 2021-11-301Moose3Rocket4ALXR1Sommaire du match
3 - 2021-12-0212Moose5Condors3AWR1Sommaire du match
5 - 2021-12-0420Moose6Barracuda7ALXXSommaire du match
7 - 2021-12-0626Rocket4Moose2BLR1Sommaire du match
10 - 2021-12-0948Admirals6Moose3BLSommaire du match
14 - 2021-12-1368Barracuda5Moose3BLR1Sommaire du match
17 - 2021-12-1683Moose5Griffins3AWR1Sommaire du match
20 - 2021-12-1995Condors4Moose5BWSommaire du match
21 - 2021-12-20104Moose6Marlies3AWSommaire du match
25 - 2021-12-24120Griffins2Moose4BWR1Sommaire du match
27 - 2021-12-26131Moose2Condors4ALSommaire du match
29 - 2021-12-28143Moose3Rocket2AWR1Sommaire du match
30 - 2021-12-29152Little Stars5Moose2BLSommaire du match
32 - 2021-12-31162Moose2Griffins5ALR1Sommaire du match
34 - 2022-01-02173Moose2Phantoms4ALSommaire du match
36 - 2022-01-04181Barracuda4Moose6BWR1Sommaire du match
38 - 2022-01-06192Moose8Barracuda9ALXXSommaire du match
40 - 2022-01-08205Moose4Heat2AWSommaire du match
41 - 2022-01-09212Admirals4Moose5BWXXSommaire du match
44 - 2022-01-12232Crunch3Moose5BWSommaire du match
46 - 2022-01-14243Moose3Monsters4ALXXSommaire du match
48 - 2022-01-16254Moose4Wolfpack3AWSommaire du match
49 - 2022-01-17260Thunderbirds3Moose8BWSommaire du match
53 - 2022-01-21279Moose6Thunderbirds5AWXXSommaire du match
54 - 2022-01-22286Sound Tigers2Moose9BWSommaire du match
58 - 2022-01-26304Moose3Heat5ALSommaire du match
60 - 2022-01-28312Senators3Moose8BWSommaire du match
62 - 2022-01-30330Moose3Reign6ALSommaire du match
63 - 2022-01-31337Penguins6Moose3BLSommaire du match
66 - 2022-02-03348Moose5Crunch6ALXXSommaire du match
68 - 2022-02-05362Barracuda5Moose4BLXXR1Sommaire du match
70 - 2022-02-07371Moose2Rocket5ALSommaire du match
72 - 2022-02-09383Moose5Sound Tigers4AWSommaire du match
73 - 2022-02-10390Monsters4Moose6BWSommaire du match
78 - 2022-02-15414Devils1Moose3BWSommaire du match
82 - 2022-02-19434Moose3Punishers5ALSommaire du match
84 - 2022-02-21441Wolves7Moose6BLSommaire du match
87 - 2022-02-24457Moose5Wolves6ALXXSommaire du match
89 - 2022-02-26466Admirals9Moose4BLSommaire du match
91 - 2022-02-28476Moose4Admirals8ALSommaire du match
93 - 2022-03-02492Condors3Moose5BWR1Sommaire du match
99 - 2022-03-08517Moose4Penguins2AWSommaire du match
100 - 2022-03-09521Reign7Moose6BLSommaire du match
103 - 2022-03-12534Moose4Devils7ALSommaire du match
105 - 2022-03-14545Marlies6Moose4BLSommaire du match
107 - 2022-03-16560Moose3Icehogs2AWSommaire du match
110 - 2022-03-19570Comets6Moose5BLXXSommaire du match
112 - 2022-03-21582Moose5Icehogs6ALSommaire du match
114 - 2022-03-23590Moose4Bears3AWSommaire du match
115 - 2022-03-24596Eagles4Moose3BLXXSommaire du match
118 - 2022-03-27610Moose6Wolves3AWSommaire du match
121 - 2022-03-30624Rocket4Moose2BLR1Sommaire du match
125 - 2022-04-03644Moose4Griffins3AWR1Sommaire du match
126 - 2022-04-04650Bears4Moose6BWSommaire du match
129 - 2022-04-07672Moose2Little Stars4ALSommaire du match
130 - 2022-04-08676Condors3Moose1BLR1Sommaire du match
132 - 2022-04-10694Moose2Phantoms6ALSommaire du match
133 - 2022-04-11699Moose7Senators6AWXXSommaire du match
134 - 2022-04-12702Icehogs6Moose5BLXSommaire du match
138 - 2022-04-16726Moose4Rampage8ALSommaire du match
139 - 2022-04-17728Phantoms4Moose6BWSommaire du match
143 - 2022-04-21753Rocket1Moose7BWR1Sommaire du match
146 - 2022-04-24767Moose4Reign3AWSommaire du match
148 - 2022-04-26780Griffins5Moose1BLR1Sommaire du match
150 - 2022-04-28794Moose5Marlies6ALXXSommaire du match
153 - 2022-05-01806Griffins4Moose5BWXR1Sommaire du match
155 - 2022-05-03818Moose5Comets4AWXSommaire du match
157 - 2022-05-05832Monsters5Moose8BWSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
162 - 2022-05-10857Senators3Moose4BWSommaire du match
166 - 2022-05-14881Punishers4Moose3BLXSommaire du match
168 - 2022-05-16889Moose1Eagles4ALSommaire du match
172 - 2022-05-20908Heat1Moose6BWSommaire du match
174 - 2022-05-22916Moose6Barracuda4AWR1Sommaire du match
177 - 2022-05-25934Little Stars5Moose7BWSommaire du match
181 - 2022-05-29954Little Stars7Moose6BLXXSommaire du match
183 - 2022-05-31963Moose2Condors5ALR1Sommaire du match
184 - 2022-06-01969Moose2Eagles3ALXXSommaire du match
188 - 2022-06-05986Heat1Moose3BWSommaire du match
193 - 2022-06-101014Wolfpack4Moose2BLSommaire du match
198 - 2022-06-151034Rampage6Moose2BLSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance74,55237,077
Assistance PCT93.19%92.69%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2791 - 93.02% 83,094$3,323,752$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,902,679$ 1,969,000$ 1,540,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,845$ 1,931,429$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 14,595$ 0$




Moose Leaders statistiques (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Moose Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Moose Statistiques de l'Équipe de Carrière

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

Moose Leaders statistiques (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Moose Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA