MILWAUKEE Admirals

GP: 69 | W: 52 | L: 14 | OTL: 3 | P: 107
GF: 378 | GA: 114 | PP%: 16.94% | PK%: 87.74%
DG: Louis Bourgault | Morale : 99 | Moyenne d'Équipe : 62
Prochain matchs #919 vs BROOKLYN Wolfpack
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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
1Dmitrij Jaskin0XX100.008335766684756865506662626462547191680
2Pontus Aberg0XX100.006435777072797469506968606955527391680
3William Carrier0X100.009941716583746764506166606555526791670
4Brendan Lemieux (R)0X100.007959486780737666616368616753517891670
5Beau Bennett0X100.006043736174668365307058605858547091650
6Markus Hannikainen (R)0X100.007235736477745763506364626454514291640
7Carter Verhaeghe0X100.005289657078505070706767576750504391610
8Mark Letestu0X100.005035697069505170706464526472572390610
9Tomas Hyka (R)0X100.005135736964585868566665576651504790610
10Sergey Tolchinsky0X100.004842746054536060506257605750504491570
11Dalton Smith0X100.005689485782505057505252505250506691550
12Dylan DeMelo0X100.007435756776839066306661776958534790700
13Christian Folin0X100.008841766384775863306155726459533691660
14Thomas Schemitsch (R)0X100.005889666786505067305757515750504491590
15Viktor Svedberg0X100.007847595099539055304536605351533791590
16John Ramage0X100.005089606672505066305247505750505188550
17Dylan Olsen0X100.005637796580454451303025695562586391520
Rayé
MOYENNE D'ÉQUIPE100.00665268657762636445605760625552539162
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
1Aaron Dell100.00817475758079818079807456693591690
2Thatcher Demko100.00747079857373747373736851637491650
3Charlie Lindgren100.00716573747070717070706651614261620
Rayé
1Samuel Montembeault (R)100.00676872816971706969666650594430610
MOYENNE D'ÉQUIPE100.0073697579737374737372695263496864
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Davis Payne70707070757574CAN493650,000$


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
1Pontus AbergMILWAUKEE Admirals (NSH)LW/RW6849611101071605313038210628512.83%13171425.2138113815513481907358.72%87200021.2813000876
2Brendan LemieuxMILWAUKEE Admirals (NSH)LW685152103105800232934159924412.29%17163224.003254213103351157063.51%37000051.26010001275
3Christian FolinMILWAUKEE Admirals (NSH)D68178198104895163571365210112.50%74163524.0521012391340331131200.00%000001.2000000248
4William CarrierMILWAUKEE Admirals (NSH)LW69414889105720143723119321513.18%18126518.34000315303111206066.98%10600021.4100000562
5Dylan DeMeloMILWAUKEE Admirals (NSH)D5318698791480114631593910111.32%48142826.953584211302221232033.33%300001.2200000575
6Dmitrij JaskinMILWAUKEE Admirals (NSH)LW/RW68364884884401881172827322312.77%17170925.1336917145213111663255.25%101900020.9813000457
7Carter VerhaegheMILWAUKEE Admirals (NSH)C683249816560111142757317711.64%9115516.9917818144101392161.37%128400021.4000000450
8Beau BennettMILWAUKEE Admirals (NSH)RW682457816518025492356015510.21%6116817.19651124149000007255.56%6300021.3900000241
9Tomas HykaMILWAUKEE Admirals (NSH)RW5630295958000612056214214.63%381914.6300002000004165.31%4900021.4400000521
10Mark LetestuMILWAUKEE Admirals (NSH)C66223153470010611974112411.17%293814.21459191421014263065.25%107900111.1300000032
11Markus HannikainenMILWAUKEE Admirals (NSH)LW68163046652403058166521309.64%1586212.680002711251215065.89%12900001.0700000111
12Sergey TolchinskyMILWAUKEE Admirals (NSH)LW691522374840519111197613.51%86018.712246390110230045.10%15300001.2300000103
13Dylan OlsenMILWAUKEE Admirals (NSH)D68525308410047266520497.69%43107415.81011529011064000.00%000000.5600000110
14Thomas SchemitschMILWAUKEE Admirals (NSH)D385152039275481447132010.64%1359515.682461247033071010.00%000000.6700010011
15Viktor SvedbergMILWAUKEE Admirals (NSH)D6951520834201103247173110.64%50128718.66101121290002151100.00%000000.3100000012
16John RamageMILWAUKEE Admirals (NSH)D2121517211402781671512.50%1731415.000110200009100.00%000001.0800000000
17Dalton SmithMILWAUKEE Admirals (NSH)LW692461540225239188.70%02063.00101219000050060.47%4300000.5800000001
Stats d'équipe Total ou en Moyenne1054370651102111904981012289793072835210612.04%3531840917.47315687281141091827521331501060.37%5170001181.1127010505445
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
1Aaron DellMILWAUKEE Admirals (NSH)68511430.9221.62406301711014020000.5717680412
2Thatcher DemkoMILWAUKEE Admirals (NSH)21000.9471.2894002380000.0000168000
Stats d'équipe Total ou en Moyenne70521430.9221.62415801711214400000.57176968412


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Aaron DellMILWAUKEE Admirals (NSH)G301989-05-04No93 Kg183 CMNoNoNo2Sans RestrictionPro & Farm750,000$0$0$NoLien
Beau BennettMILWAUKEE Admirals (NSH)RW271991-11-27No89 Kg188 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Brendan LemieuxMILWAUKEE Admirals (NSH)LW231996-03-15Yes98 Kg185 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Carter VerhaegheMILWAUKEE Admirals (NSH)C241995-08-14No86 Kg188 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Charlie LindgrenMILWAUKEE Admirals (NSH)G251993-12-18No83 Kg185 CMNoNoNo1Avec RestrictionPro & Farm750,000$0$0$NoLien
Christian FolinMILWAUKEE Admirals (NSH)D281991-02-09No93 Kg191 CMNoNoNo2Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Dalton SmithMILWAUKEE Admirals (NSH)LW271992-06-30No94 Kg188 CMNoNoNo1Avec RestrictionPro & Farm750,000$0$0$NoLien
Dmitrij JaskinMILWAUKEE Admirals (NSH)LW/RW261993-03-23No98 Kg188 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Dylan DeMeloMILWAUKEE Admirals (NSH)D261993-05-01No89 Kg185 CMNoNoNo1Avec RestrictionPro & Farm900,000$0$0$NoLien
Dylan OlsenMILWAUKEE Admirals (NSH)D281991-01-03No101 Kg188 CMNoNoNo1Sans RestrictionPro & Farm750,000$0$0$No
John RamageMILWAUKEE Admirals (NSH)D281991-02-07No86 Kg183 CMNoNoNo4Sans RestrictionPro & Farm750,000$0$0$NoLien
Mark LetestuMILWAUKEE Admirals (NSH)C341985-02-04No89 Kg178 CMNoNoNo2Sans RestrictionPro & Farm1,500,000$0$0$NoLien
Markus HannikainenMILWAUKEE Admirals (NSH)LW261993-03-26Yes91 Kg185 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Pontus AbergMILWAUKEE Admirals (NSH)LW/RW251993-09-23No89 Kg180 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Samuel Montembeault (Contrat à 1 Volet)MILWAUKEE Admirals (NSH)G221996-10-30Yes87 Kg191 CMNoNoNo1Avec RestrictionPro & Farm725,000$725,000$100,694$NoLien
Sergey TolchinskyMILWAUKEE Admirals (NSH)LW241995-02-03No77 Kg173 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Thatcher DemkoMILWAUKEE Admirals (NSH)G231995-12-08No87 Kg193 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Thomas SchemitschMILWAUKEE Admirals (NSH)D221996-10-26Yes91 Kg193 CMNoNoNo4Avec RestrictionPro & Farm750,000$0$0$NoLien
Tomas HykaMILWAUKEE Admirals (NSH)RW261993-03-23Yes73 Kg180 CMNoNoNo3Avec RestrictionPro & Farm750,000$0$0$NoLien
Viktor SvedbergMILWAUKEE Admirals (NSH)D281991-05-24No108 Kg203 CMNoNoNo1Sans RestrictionPro & Farm750,000$0$0$NoLien
William CarrierMILWAUKEE Admirals (NSH)LW241994-12-20No96 Kg188 CMNoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2126.0090 Kg185 CM2.19803,571$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Pontus AbergMark LetestuDmitrij Jaskin31122
2William CarrierCarter VerhaegheBeau Bennett26122
3Brendan LemieuxPontus AbergTomas Hyka23122
4Markus HannikainenDmitrij JaskinWilliam Carrier20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan DeMeloChristian Folin31122
2Viktor SvedbergThomas Schemitsch26122
3John RamageDylan Olsen23122
4Dylan DeMeloChristian Folin20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Pontus AbergMark LetestuDmitrij Jaskin55122
2William CarrierCarter VerhaegheBeau Bennett45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan DeMeloChristian Folin55122
2Viktor SvedbergThomas Schemitsch45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Pontus AbergDmitrij Jaskin55122
2William CarrierBrendan Lemieux45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan DeMeloChristian Folin55122
2Viktor SvedbergThomas Schemitsch45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Pontus Aberg55122Dylan DeMeloChristian Folin55122
2Dmitrij Jaskin45122Viktor SvedbergThomas Schemitsch45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Pontus AbergDmitrij Jaskin55122
2William CarrierBrendan Lemieux45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Dylan DeMeloChristian Folin55122
2Viktor SvedbergThomas Schemitsch45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Pontus AbergMark LetestuDmitrij JaskinDylan DeMeloChristian Folin
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Pontus AbergMark LetestuDmitrij JaskinDylan DeMeloChristian Folin
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Sergey Tolchinsky, Dalton Smith, Markus HannikainenSergey Tolchinsky, Dalton SmithMarkus Hannikainen
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
John Ramage, Dylan Olsen, Viktor SvedbergJohn RamageDylan Olsen, Viktor Svedberg
Tirs de Pénalité
Pontus Aberg, Dmitrij Jaskin, William Carrier, Brendan Lemieux, Beau Bennett
Gardien
#1 : Aaron Dell, #2 : Thatcher Demko, #3 : Charlie Lindgren
Lignes d'Attaque Perso. en Prol.
Pontus Aberg, Dmitrij Jaskin, William Carrier, Brendan Lemieux, Beau Bennett, Markus Hannikainen, Markus Hannikainen, Mark Letestu, Carter Verhaeghe, Tomas Hyka, Sergey Tolchinsky
Lignes de Défense Perso. en Prol.
Dylan DeMelo, Christian Folin, Viktor Svedberg, Thomas Schemitsch, John Ramage


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
1BELLEVILLE Senators2200000014311110000007251100000071641.000142741001681317641511014104611231838514302150.00%60100.00%01455234262.13%1006179456.08%690107963.95%217916991215392768434
2BRIDGEPORT Sound Tigers4120100078-1210010006422020000014-340.5007916001681317641041014104611231813323348617211.76%14192.86%01455234262.13%1006179456.08%690107963.95%217916991215392768434
3BROOKLYN Wolfpack220000002011900000000000220000002011941.0002031510116813176414710141046112318278639000.00%30100.00%11455234262.13%1006179456.08%690107963.95%217916991215392768434
4CHICAGO Wolves3300000031625220000002121911000000104661.0003156870116813176417910141046112318531820563133.33%10280.00%01455234262.13%1006179456.08%690107963.95%217916991215392768434
5CLEVELAND Monsters44000000451442200000022121220000002302381.000458613103168131764298101410461123184010147011100.00%70100.00%11455234262.13%1006179456.08%690107963.95%217916991215392768434
6COLORADO Eagles321000008712110000056-11100000031240.667814220016813176475101410461123187428226210110.00%10280.00%11455234262.13%1006179456.08%690107963.95%217916991215392768434
7CORNWALL Aces22000000231221100000010010110000001311241.00023436601168131764182101410461123181324303266.67%20100.00%01455234262.13%1006179456.08%690107963.95%217916991215392768434
8HERSEY Bears31100010651100000103212110000033040.6676101600168131764781014104611231877252438400.00%12191.67%01455234262.13%1006179456.08%690107963.95%217916991215392768434
9HOLLYWOOD Oscar22000000251241100000012111110000001301341.00025477201168131764178101410461123181111026100.00%50100.00%01455234262.13%1006179456.08%690107963.95%217916991215392768434
10IOWA Wild22000000936110000005141100000042241.000917260016813176410810141046112318519123510440.00%6266.67%01455234262.13%1006179456.08%690107963.95%217916991215392768434
11LAVAL Rockets421000011394220000009362010000146-250.6251323360016813176496101410461123181203839531915.26%11190.91%11455234262.13%1006179456.08%690107963.95%217916991215392768434
12LEHIGH VALLEY Phantoms220000001046110000003211100000072541.000101828001681317646210141046112318521616484125.00%5260.00%01455234262.13%1006179456.08%690107963.95%217916991215392768434
13MANITOBA Moose21100000761110000005321010000023-120.500713200016813176458101410461123184521183111218.18%8275.00%01455234262.13%1006179456.08%690107963.95%217916991215392768434
14MONT-LAURIER Sommet22000000835110000005141100000032141.00081523001681317647210141046112318501124439222.22%11190.91%01455234262.13%1006179456.08%690107963.95%217916991215392768434
15PROVIDENCE Bruins4310000016124220000009452110000078-160.750163248001681317641521014104611231810624367620315.00%16287.50%01455234262.13%1006179456.08%690107963.95%217916991215392768434
16PV Sharapovas211000003211010000012-11100000020220.5003580116813176453101410461123185782033600.00%9277.78%01455234262.13%1006179456.08%690107963.95%217916991215392768434
17ROCKFORD IceHogs11000000321110000003210000000000021.00035800168131764291014104611231832126212150.00%20100.00%01455234262.13%1006179456.08%690107963.95%217916991215392768434
18SAN DIEGO Gulls44000000240242200000013013220000001101181.000244367041681317642951014104611231819812997228.57%60100.00%11455234262.13%1006179456.08%690107963.95%217916991215392768434
19STOCKTON Flames2110000046-21010000025-31100000021120.500481200168131764531014104611231843883410110.00%3166.67%01455234262.13%1006179456.08%690107963.95%217916991215392768434
20SYRACUSE Crunch20101000550100010004311010000012-120.5005914001681317646310141046112318601820397228.57%9188.89%01455234262.13%1006179456.08%690107963.95%217916991215392768434
21TORONTO Marlies211000005411010000012-11100000042220.500581300168131764761014104611231858726382150.00%11190.91%01455234262.13%1006179456.08%690107963.95%217916991215392768434
22TUSCON Roadrunners44000000222202200000011110220000001111081.000224365021681317641531014104611231865241882900.00%80100.00%11455234262.13%1006179456.08%690107963.95%217916991215392768434
Total694914021123781142643525502111196571393424900001182571251070.7753786931071017168131764319410141046112318144038448312421833116.94%2122687.74%91455234262.13%1006179456.08%690107963.95%217916991215392768434
24UTICA Comets40300100513-82010010025-32020000038-510.125591400168131764125101410461123181343846762114.76%21480.95%01455234262.13%1006179456.08%690107963.95%217916991215392768434
25VICTORIAVILLE Tigres210000017701000000134-11100000043130.75071320001681317646710141046112318471612414125.00%6183.33%11455234262.13%1006179456.08%690107963.95%217916991215392768434
26WILKIES-BARRIE Penguins550000005835533000000341332200000024222101.000581091670316813176434010141046112318356225611100.00%110100.00%21455234262.13%1006179456.08%690107963.95%217916991215392768434
_Since Last GM Reset694914021123781142643525502111196571393424900001182571251070.7753786931071017168131764319410141046112318144038448312421833116.94%2122687.74%91455234262.13%1006179456.08%690107963.95%217916991215392768434
_Vs Conference402790111120066134201520111010430742012700001963660600.7502003615610111681317641731101410461123188802562777581131311.50%1201389.17%61455234262.13%1006179456.08%690107963.95%217916991215392768434
_Vs Division13134010016531348910100042182454300001231310291.11565118183011681317645161014104611231830210490246401025.00%42978.57%21455234262.13%1006179456.08%690107963.95%217916991215392768434

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
69107W173786931071319414403844831242017
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
6949142112378114
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
35255211119657
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
34249000118257
Derniers 10 Matchs
WLOTWOTL SOWSOL
1000000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1833116.94%2122687.74%9
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
10141046112318168131764
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
1455234262.13%1006179456.08%690107963.95%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
217916991215392768434


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
1 - 2019-07-303MILWAUKEE Admirals10BROOKLYN Wolfpack1WSommaire du Match
2 - 2019-07-3116MILWAUKEE Admirals10WILKIES-BARRIE Penguins0WSommaire du Match
3 - 2019-08-0129WILKIES-BARRIE Penguins1MILWAUKEE Admirals11WSommaire du Match
4 - 2019-08-0248UTICA Comets2MILWAUKEE Admirals0LSommaire du Match
6 - 2019-08-0457MILWAUKEE Admirals0BRIDGEPORT Sound Tigers2LSommaire du Match
7 - 2019-08-0572SAN DIEGO Gulls0MILWAUKEE Admirals7WSommaire du Match
9 - 2019-08-0782MILWAUKEE Admirals3LAVAL Rockets4LXXSommaire du Match
10 - 2019-08-08102CLEVELAND Monsters0MILWAUKEE Admirals11WSommaire du Match
11 - 2019-08-09115MILWAUKEE Admirals9TUSCON Roadrunners0WSommaire du Match
12 - 2019-08-10119WILKIES-BARRIE Penguins0MILWAUKEE Admirals11WSommaire du Match
14 - 2019-08-12138MILWAUKEE Admirals6SAN DIEGO Gulls0WSommaire du Match
15 - 2019-08-13145MILWAUKEE Admirals0UTICA Comets4LSommaire du Match
16 - 2019-08-14156CHICAGO Wolves0MILWAUKEE Admirals12WSommaire du Match
18 - 2019-08-16175TUSCON Roadrunners0MILWAUKEE Admirals8WSommaire du Match
20 - 2019-08-18192MILWAUKEE Admirals3HERSEY Bears1WSommaire du Match
21 - 2019-08-19204PROVIDENCE Bruins2MILWAUKEE Admirals6WSommaire du Match
22 - 2019-08-20213UTICA Comets3MILWAUKEE Admirals2LXSommaire du Match
24 - 2019-08-22225MILWAUKEE Admirals1LAVAL Rockets2LSommaire du Match
25 - 2019-08-23239MILWAUKEE Admirals13HOLLYWOOD Oscar0WSommaire du Match
26 - 2019-08-24254MILWAUKEE Admirals3UTICA Comets4LSommaire du Match
27 - 2019-08-25263CORNWALL Aces0MILWAUKEE Admirals10WSommaire du Match
28 - 2019-08-26274TORONTO Marlies2MILWAUKEE Admirals1LSommaire du Match
29 - 2019-08-27289HOLLYWOOD Oscar1MILWAUKEE Admirals12WSommaire du Match
30 - 2019-08-28308MILWAUKEE Admirals7LEHIGH VALLEY Phantoms2WSommaire du Match
31 - 2019-08-29317STOCKTON Flames5MILWAUKEE Admirals2LSommaire du Match
32 - 2019-08-30327MILWAUKEE Admirals12CLEVELAND Monsters0WSommaire du Match
34 - 2019-09-01346MANITOBA Moose3MILWAUKEE Admirals5WSommaire du Match
35 - 2019-09-02357MILWAUKEE Admirals1PROVIDENCE Bruins6LSommaire du Match
36 - 2019-09-03366MILWAUKEE Admirals3MONT-LAURIER Sommet2WSommaire du Match
37 - 2019-09-04384MILWAUKEE Admirals2MANITOBA Moose3LSommaire du Match
38 - 2019-09-05390VICTORIAVILLE Tigres4MILWAUKEE Admirals3LXXSommaire du Match
39 - 2019-09-06403MILWAUKEE Admirals4VICTORIAVILLE Tigres3WSommaire du Match
41 - 2019-09-08416CHICAGO Wolves2MILWAUKEE Admirals9WSommaire du Match
42 - 2019-09-09428MILWAUKEE Admirals5SAN DIEGO Gulls0WSommaire du Match
44 - 2019-09-11442COLORADO Eagles1MILWAUKEE Admirals2WSommaire du Match
46 - 2019-09-13460ROCKFORD IceHogs2MILWAUKEE Admirals3WSommaire du Match
47 - 2019-09-14471BELLEVILLE Senators2MILWAUKEE Admirals7WSommaire du Match
48 - 2019-09-15490MILWAUKEE Admirals13CORNWALL Aces1WSommaire du Match
49 - 2019-09-16503MILWAUKEE Admirals1BRIDGEPORT Sound Tigers2LSommaire du Match
50 - 2019-09-17505MILWAUKEE Admirals10CHICAGO Wolves4WSommaire du Match
51 - 2019-09-18519PV Sharapovas2MILWAUKEE Admirals1LSommaire du Match
53 - 2019-09-20535MONT-LAURIER Sommet1MILWAUKEE Admirals5WSommaire du Match
54 - 2019-09-21553MILWAUKEE Admirals2STOCKTON Flames1WSommaire du Match
56 - 2019-09-23566WILKIES-BARRIE Penguins0MILWAUKEE Admirals12WSommaire du Match
57 - 2019-09-24574MILWAUKEE Admirals2PV Sharapovas0WSommaire du Match
59 - 2019-09-26585SYRACUSE Crunch3MILWAUKEE Admirals4WXSommaire du Match
60 - 2019-09-27602MILWAUKEE Admirals1SYRACUSE Crunch2LSommaire du Match
62 - 2019-09-29615MILWAUKEE Admirals6PROVIDENCE Bruins2WSommaire du Match
64 - 2019-10-01624BRIDGEPORT Sound Tigers2MILWAUKEE Admirals3WXSommaire du Match
66 - 2019-10-03641LAVAL Rockets2MILWAUKEE Admirals5WSommaire du Match
67 - 2019-10-04653MILWAUKEE Admirals0HERSEY Bears2LSommaire du Match
68 - 2019-10-05668COLORADO Eagles5MILWAUKEE Admirals3LSommaire du Match
69 - 2019-10-06671MILWAUKEE Admirals2TUSCON Roadrunners1WSommaire du Match
71 - 2019-10-08686MILWAUKEE Admirals4IOWA Wild2WSommaire du Match
72 - 2019-10-09698SAN DIEGO Gulls0MILWAUKEE Admirals6WSommaire du Match
73 - 2019-10-10709MILWAUKEE Admirals7BELLEVILLE Senators1WSommaire du Match
75 - 2019-10-12724LEHIGH VALLEY Phantoms2MILWAUKEE Admirals3WSommaire du Match
76 - 2019-10-13736MILWAUKEE Admirals11CLEVELAND Monsters0WSommaire du Match
77 - 2019-10-14749HERSEY Bears2MILWAUKEE Admirals3WXXSommaire du Match
79 - 2019-10-16764MILWAUKEE Admirals4TORONTO Marlies2WSommaire du Match
80 - 2019-10-17775CLEVELAND Monsters1MILWAUKEE Admirals11WSommaire du Match
82 - 2019-10-19795TUSCON Roadrunners1MILWAUKEE Admirals3WSommaire du Match
83 - 2019-10-20812LAVAL Rockets1MILWAUKEE Admirals4WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
85 - 2019-10-22834IOWA Wild1MILWAUKEE Admirals5WSommaire du Match
86 - 2019-10-23848MILWAUKEE Admirals14WILKIES-BARRIE Penguins2WSommaire du Match
88 - 2019-10-25861BRIDGEPORT Sound Tigers2MILWAUKEE Admirals3WSommaire du Match
90 - 2019-10-27876MILWAUKEE Admirals10BROOKLYN Wolfpack0WSommaire du Match
91 - 2019-10-28884MILWAUKEE Admirals3COLORADO Eagles1WSommaire du Match
92 - 2019-10-29897PROVIDENCE Bruins2MILWAUKEE Admirals3WSommaire du Match
94 - 2019-10-31919BROOKLYN Wolfpack-MILWAUKEE Admirals-
96 - 2019-11-02933MILWAUKEE Admirals-COLORADO Eagles-
97 - 2019-11-03938ROCKFORD IceHogs-MILWAUKEE Admirals-
99 - 2019-11-05954MILWAUKEE Admirals-ROCKFORD IceHogs-
101 - 2019-11-07966HERSEY Bears-MILWAUKEE Admirals-
102 - 2019-11-08977MILWAUKEE Admirals-WILKIES-BARRIE Penguins-
104 - 2019-11-10992BROOKLYN Wolfpack-MILWAUKEE Admirals-
105 - 2019-11-111003MILWAUKEE Admirals-CHICAGO Wolves-
106 - 2019-11-121006MILWAUKEE Admirals-ROCKFORD IceHogs-



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
4 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,948,602$ 1,615,000$ 1,572,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,383,630$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 14 21,168$ 296,352$




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
32694914021123781142643525502111196571393424900001182571251073786931071017168131764319410141046112318144038448312421833116.94%2122687.74%91455234262.13%1006179456.08%690107963.95%217916991215392768434
Total Saison Régulière694914021123781142643525502111196571393424900001182571251073786931071017168131764319410141046112318144038448312421833116.94%2122687.74%91455234262.13%1006179456.08%690107963.95%217916991215392768434