Milwaukee Admirals

GP: 25 | W: 16 | L: 6 | OTL: 3 | P: 35
GF: 78 | GA: 66 | PP%: 25.00% | PK%: 78.22%
DG: Mathieu Boudreault | Morale : 61 | Moyenne d'Équipe : N/A
Prochain matchs #432 vs Springfield Falcons
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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 SPÂgeContratSalaire Moyen
1Nicholas Caamano (R)X100.00844867788181837865777773706875706700223900,000$
2Luke Adam (A)XX100.00754085758783827781777766748991706700301850,000$
3Mathieu PerreaultXX100.005533887771767477757875627795967041003211,000,000$
4Nick PalmieriX100.00764388748677757773767670759092706700311850,000$
5Drew Shore (A)XX100.006535857981838481767980667785857067002911,567,043$
6Mitch Moroz (R)X100.009548717690777676557574697075777045002611,200,000$
7Mark Jankowski (R)XX100.007935818079797779747876717368697057002611,200,000$
8Marc-Olivier Roy (R)XXX100.006835848176807778747777727168707067002631,300,000$
9Miikka SalomäkiXXX100.008440757782858177757877737375687067002731,500,000$
10Cristoval Nieves (R)XX100.00834081768680807773787674716868706700261950,000$
11Logan Brown (R)X100.00803879768678757873787570706363705400221950,000$
12Tage Thompson (R)XX100.00834082758678797870787872736868706700232900,000$
13Spencer Stastney (R)X100.00643082767382827450755780566060706700203800,000$
14Patrick WierciochX100.00714383818376747850786182608792706700301900,000$
15Nate SchmidtX100.007743817977797780507872816777797067002911,150,000$
16Joshua JacobsX100.008745727782807875517767846774757049002432,000,000$
17Stuart PercyX100.007135838576777379507963787070747041002721,000,000$
18Dylan Blujus (R)X100.00804576708376737150716181606060703200261650,000$
Rayé
1Brett PollockXX91.418643758381778182757979717269707029002411,200,000$
2Kyle Platzer (R)XX100.00623581787175747271727265686464702700251750,000$
3Bode Wilde (R)X96.77814574758380747750756078606360705900203850,000$
4T.J. Brodie (C)X83.987040867976767575517860836088927059003021,200,000$
MOYENNE D'ÉQUIPE98.6476408078817977776477717469747570560
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
1Christopher Gibson100.0086828484928987868886857884706700
2Chet Pickard100.0083848688908889878989919096706200
Rayé
1Jonas Johansson (R)100.0083838492858787868484836565703200
MOYENNE D'ÉQUIPE100.008483858889888886878686788270540
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
D.J. Smith85888585808070CAN4211,000,000$


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
1Miikka SalomäkiMilwaukee Admirals (NSH)C/LW/RW2512102214120274270163917.14%745418.191123130001474052.66%54500000.9700000341
2Nicholas CaamanoMilwaukee Admirals (NSH)RW251091913140373576184813.16%349119.64000020004980044.00%5000010.7700000211
3Spencer StastneyMilwaukee Admirals (NSH)D25316191122028262651711.54%3152420.973471561000070100.00%000000.7200000030
4Patrick WierciochMilwaukee Admirals (NSH)D2521416-31202228378155.41%3148919.601341549000156000.00%000000.6500000001
5Nate SchmidtMilwaukee Admirals (NSH)D2531316-110035214017357.50%3553621.442572566000075100.00%000000.6000000021
6Tage ThompsonMilwaukee Admirals (NSH)LW/RW257916-360393369193710.14%546318.5433613620000171143.33%3000000.6900000021
7T.J. BrodieMilwaukee Admirals (NSH)D2401414151603629195110.00%4046719.4900024000073000.00%000000.6000000100
8Bode WildeMilwaukee Admirals (NSH)D213912516024232191614.29%1538818.522461148000010100.00%000000.6200000100
9Mathieu PerreaultMilwaukee Admirals (NSH)C/LW19279500072810187.14%025213.28033438000042030.00%2000000.7102000010
10Joshua JacobsMilwaukee Admirals (NSH)D2127913404821258148.00%3543920.91101818000057100.00%000000.4100000001
11Marc-Olivier RoyMilwaukee Admirals (NSH)C/LW/RW25459-54012265319557.55%740816.331457650001131046.22%11900000.4400000000
12Cristoval NievesMilwaukee Admirals (NSH)C/LW255497120244634122714.71%732012.820000000031050049.07%43000000.5600000100
13Drew ShoreMilwaukee Admirals (NSH)C/RW2553856018195115409.80%233813.553141667000001070.00%2000000.4712000002
14Logan BrownMilwaukee Admirals (NSH)C19448-48020233381612.12%132317.05134843000000050.12%40500000.4900000000
15Brett PollockMilwaukee Admirals (NSH)C/LW1143728018172492016.67%019617.871124260000120168.00%5000000.7100000002
16Nick PalmieriMilwaukee Admirals (NSH)RW25426440992681115.38%21857.40000318000000050.00%600100.6500000011
17Mark JankowskiMilwaukee Admirals (NSH)C/LW23235016032325217363.85%334414.990227330003270049.54%21600000.2900000001
18Luke AdamMilwaukee Admirals (NSH)C/LW25224-14014242071310.00%22419.64000040000151058.37%24500000.3300000011
19Stuart PercyMilwaukee Admirals (NSH)D131230404973914.29%1015211.7010161300005010.00%000000.3900000100
20Mitch MorozMilwaukee Admirals (NSH)LW14101210094104710.00%2976.9700000000000125.00%400000.2100000000
21Dylan BlujusMilwaukee Admirals (NSH)D8011000113000.00%0172.170002000000000.00%000001.1500000000
Stats d'équipe Total ou en Moyenne4487613721367218045747572421748410.50%238713315.922034541496380001369314451.36%214000110.601400091513
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
1Chet PickardMilwaukee Admirals (NSH)1812500.9162.51105421445250101.0003182600
2Christopher GibsonMilwaukee Admirals (NSH)84130.9162.6046221202370010.3333718100
Stats d'équipe Total ou en Moyenne2616630.9162.53151642647620110.66762520700


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Bode WildeMilwaukee Admirals (NSH)D201999-01-02 03:20:27Yes192 Lbs6 ft3NoNoNo3Pro & Farm850,000$592,287$850,000$592,287$0$0$No850,000$850,000$
Brett Pollock (Sur la Masse Salariale)Milwaukee Admirals (NSH)C/LW241995-01-22 02:00:42No194 Lbs6 ft2NoNoNo1Pro & Farm1,200,000$836,170$1,200,000$836,170$0$0$Yes
Chet PickardMilwaukee Admirals (NSH)G311988-01-22 12:29:38No206 Lbs6 ft3NoNoNo2Pro & Farm1,500,000$1,045,212$1,500,000$1,045,212$0$0$No1,500,000$
Christopher GibsonMilwaukee Admirals (NSH)G281991-01-22 12:30:26No198 Lbs6 ft1NoNoNo3Pro & Farm1,500,000$1,045,212$1,500,000$1,045,212$0$0$No1,500,000$1,500,000$
Cristoval NievesMilwaukee Admirals (NSH)C/LW261993-01-22 04:19:11Yes212 Lbs6 ft3NoNoNo1Pro & Farm950,000$661,968$950,000$661,968$0$0$No
Drew ShoreMilwaukee Admirals (NSH)C/RW291990-01-22 15:55:26No190 Lbs6 ft2NoNoNo1Pro & Farm1,567,043$1,091,928$1,567,043$1,091,928$0$0$No
Dylan BlujusMilwaukee Admirals (NSH)D261993-01-22 05:19:59Yes203 Lbs6 ft3NoNoNo1Pro & Farm650,000$452,925$650,000$452,925$0$0$No
Jonas JohanssonMilwaukee Admirals (NSH)G251994-01-02 03:15:19Yes214 Lbs6 ft5NoNoNo1Pro & Farm850,000$592,287$850,000$592,287$0$0$No
Joshua JacobsMilwaukee Admirals (NSH)D241995-01-22 07:27:05No195 Lbs6 ft2NoNoNo3Pro & Farm2,000,000$1,393,617$2,000,000$1,393,617$0$0$No2,000,000$2,000,000$
Kyle PlatzerMilwaukee Admirals (NSH)C/RW251994-01-22 05:12:19Yes181 Lbs6 ft0NoNoNo1Pro & Farm750,000$522,606$750,000$522,606$0$0$No
Logan BrownMilwaukee Admirals (NSH)C221997-01-22 09:26:05Yes220 Lbs6 ft6NoNoNo1Pro & Farm950,000$661,968$950,000$661,968$0$0$No
Luke AdamMilwaukee Admirals (NSH)C/LW301989-01-22 12:29:38No203 Lbs6 ft2NoNoNo1Pro & Farm850,000$592,287$850,000$592,287$0$0$No
Marc-Olivier RoyMilwaukee Admirals (NSH)C/LW/RW261993-01-22 17:02:20Yes183 Lbs6 ft0NoNoNo3Pro & Farm1,300,000$905,851$1,300,000$905,851$0$0$No1,300,000$1,300,000$
Mark JankowskiMilwaukee Admirals (NSH)C/LW261993-01-22 16:05:15Yes185 Lbs6 ft3NoNoNo1Pro & Farm1,200,000$836,170$1,200,000$836,170$0$0$No
Mathieu PerreaultMilwaukee Admirals (NSH)C/LW321987-01-22 00:29:38No174 Lbs5 ft10NoNoNo1Pro & Farm1,000,000$696,808$1,000,000$696,808$0$0$No
Miikka SalomäkiMilwaukee Admirals (NSH)C/LW/RW271992-01-22 02:08:57No198 Lbs5 ft11NoNoNo3Pro & Farm1,500,000$1,045,212$1,500,000$1,045,212$0$0$No1,500,000$1,500,000$
Mitch MorozMilwaukee Admirals (NSH)LW261993-01-22 04:57:59Yes208 Lbs6 ft2NoNoNo1Pro & Farm1,200,000$836,170$1,200,000$836,170$0$0$No
Nate SchmidtMilwaukee Admirals (NSH)D291990-01-22 14:51:34No195 Lbs6 ft0NoNoNo1Pro & Farm1,150,000$801,329$1,150,000$801,329$0$0$No
Nicholas CaamanoMilwaukee Admirals (NSH)RW221997-01-02 02:57:09Yes194 Lbs6 ft2NoNoNo3Pro & Farm900,000$627,127$900,000$627,127$0$0$No900,000$900,000$
Nick PalmieriMilwaukee Admirals (NSH)RW311988-01-22 06:29:38No220 Lbs6 ft3NoNoNo1Pro & Farm850,000$592,287$850,000$592,287$0$0$No
Patrick WierciochMilwaukee Admirals (NSH)D301989-01-22 12:29:38No192 Lbs6 ft4NoNoNo1Pro & Farm900,000$627,127$900,000$627,127$0$0$No
Spencer StastneyMilwaukee Admirals (NSH)D201999-01-02 03:25:28Yes179 Lbs5 ft10NoNoNo3Pro & Farm800,000$557,446$800,000$557,446$0$0$No800,000$800,000$
Stuart PercyMilwaukee Admirals (NSH)D271992-01-22 02:33:32No185 Lbs6 ft0NoNoNo2Pro & Farm1,000,000$696,808$1,000,000$696,808$0$0$No1,000,000$
T.J. Brodie (Sur la Masse Salariale)Milwaukee Admirals (NSH)D301989-01-22 12:29:38No182 Lbs6 ft1NoNoNo2Pro & Farm1,200,000$836,170$1,200,000$836,170$0$0$Yes1,200,000$
Tage ThompsonMilwaukee Admirals (NSH)LW/RW231996-01-22 15:06:33Yes205 Lbs6 ft6NoNoNo2Pro & Farm900,000$627,127$900,000$627,127$0$0$No900,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2526.36196 Lbs6 ft21.721,100,682$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tage ThompsonMiikka SalomäkiNicholas Caamano35023
2Mark JankowskiLogan BrownMarc-Olivier Roy32023
3Mathieu PerreaultCristoval NievesDrew Shore23023
4Mitch MorozLuke AdamNick Palmieri10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Joshua JacobsStuart Percy35131
2Dylan BlujusSpencer Stastney33131
3Patrick WierciochNate Schmidt32131
4Nate SchmidtJoshua Jacobs0131
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tage ThompsonLogan BrownDrew Shore60005
2Mark JankowskiMarc-Olivier RoyNick Palmieri40005
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nate SchmidtJoshua Jacobs60005
2Stuart PercySpencer Stastney40005
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Cristoval NievesNicholas Caamano60050
2Miikka SalomäkiTage Thompson40050
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Patrick WierciochJoshua Jacobs60050
2Nate SchmidtSpencer Stastney40050
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Cristoval Nieves60050Patrick WierciochJoshua Jacobs60050
2Miikka Salomäki40050Nate SchmidtSpencer Stastney40050
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Logan BrownTage Thompson60023
2Miikka SalomäkiNicholas Caamano40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Joshua JacobsStuart Percy60122
2Nate SchmidtSpencer Stastney40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tage ThompsonLogan BrownNicholas CaamanoNate SchmidtJoshua Jacobs
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tage ThompsonMiikka SalomäkiNicholas CaamanoJoshua JacobsPatrick Wiercioch
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Logan Brown, Miikka Salomäki, Tage ThompsonMathieu Perreault, Miikka SalomäkiMarc-Olivier Roy
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nate Schmidt, Joshua Jacobs, Patrick WierciochJoshua JacobsJoshua Jacobs, Stuart Percy
Tirs de Pénalité
Drew Shore, Mathieu Perreault, Nick Palmieri, Luke Adam, Miikka Salomäki
Gardien
#1 : Chet Pickard, #2 : Christopher Gibson
Lignes d'Attaque Perso. en Prol.
Logan Brown, Tage Thompson, Miikka Salomäki, Nicholas Caamano, Cristoval Nieves, Drew Shore, Drew Shore, Mark Jankowski, Marc-Olivier Roy, Luke Adam, Nick Palmieri
Lignes de Défense Perso. en Prol.
Nate Schmidt, Stuart Percy, Spencer Stastney, Patrick Wiercioch, Joshua Jacobs


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
1Chicago Wolves21000100770210001007700000000000030.7507142100342417360258229255186919244312325.00%11372.73%046387552.91%45789850.89%20538053.95%604416593187321161
2Gatineau Olympiques1010000034-1000000000001010000034-100.000369003424173262582292551854131613200.00%7271.43%046387552.91%45789850.89%20538053.95%604416593187321161
3Grand Rapids Griffins411001011315-21000000134-1311001001011-140.5001323360034241731232582292551812139367113323.08%18477.78%046387552.91%45789850.89%20538053.95%604416593187321161
4Henderson Silver Knights330000001174220000008531100000032161.0001120310034241738325822925518823418608112.50%8275.00%046387552.91%45789850.89%20538053.95%604416593187321161
5Joliette Sportif21001000743210010007430000000000041.0007121900342417364258229255185917244110330.00%10280.00%046387552.91%45789850.89%20538053.95%604416593187321161
6Lake Erie Monsters21000010642100000104311100000021141.000610160034241735525822925518611220316116.67%10190.00%046387552.91%45789850.89%20538053.95%604416593187321161
7Las Vegas Gamblers2010100078-1000000000002010100078-120.500714211034241735025822925518561522385240.00%10460.00%046387552.91%45789850.89%20538053.95%604416593187321161
8Peoria Rivermen11000000312000000000001100000031221.000369003424173322582292551823810142150.00%40100.00%046387552.91%45789850.89%20538053.95%604416593187321161
9Providence Bruins11000000211110000002110000000000021.00023500342417338258229255183110617300.00%30100.00%046387552.91%45789850.89%20538053.95%604416593187321161
10Rochester Americans1010000035-2000000000001010000035-200.00036900342417328258229255183411101611100.00%5260.00%046387552.91%45789850.89%20538053.95%604416593187321161
11Rockford IceHogs1010000003-3000000000001010000003-300.00000000342417332258229255182412619100.00%3166.67%046387552.91%45789850.89%20538053.95%604416593187321161
12Rouyn-Noranda Huskies11000000202110000002020000000000021.000246013424173322582292551822102265120.00%10100.00%046387552.91%45789850.89%20538053.95%604416593187321161
13Springfield Falcons11000000202000000000001100000020221.000246013424173332582292551833101020400.00%50100.00%046387552.91%45789850.89%20538053.95%604416593187321161
Total25136022117866121381011114531141255011003335-2350.7007814222012342417375625822925518763239222466802025.00%1012278.22%046387552.91%45789850.89%20538053.95%604416593187321161
14Trois-Rivières Draveurs21100000862211000008620000000000020.500813210034241736325822925518591910345240.00%3166.67%046387552.91%45789850.89%20538053.95%604416593187321161
15Wilkes-Barre/Scranton Penguins11000000413110000004130000000000021.0004711003424173372582292551835108233266.67%30100.00%046387552.91%45789850.89%20538053.95%604416593187321161
_Since Last GM Reset25136022117866121381011114531141255011003335-2350.7007814222012342417375625822925518763239222466802025.00%1012278.22%046387552.91%45789850.89%20538053.95%604416593187321161
_Vs Conference201040221161538950011113123811540110030300290.7256111317412342417359025822925518604189188376681522.06%871978.16%046387552.91%45789850.89%20538053.95%604416593187321161
_Vs Division1032001012931-220000001770832001002224-280.40029538210342417329225822925518285869417327725.93%451077.78%046387552.91%45789850.89%20538053.95%604416593187321161

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2535SOL17814222075676323922246612
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2513622117866
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
138111114531
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
125511003335
Derniers 10 Matchs
WLOTWOTL SOWSOL
630001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
802025.00%1012278.22%0
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
258229255183424173
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
46387552.91%45789850.89%20538053.95%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
604416593187321161


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
2 - 2020-10-2912Trois-Rivières Draveurs4Milwaukee Admirals3LSommaire du Match
5 - 2020-11-0135Chicago Wolves1Milwaukee Admirals2WSommaire du Match
7 - 2020-11-0354Milwaukee Admirals2Lake Erie Monsters1WSommaire du Match
9 - 2020-11-0567Trois-Rivières Draveurs2Milwaukee Admirals5WSommaire du Match
10 - 2020-11-0677Milwaukee Admirals2Las Vegas Gamblers1WXSommaire du Match
13 - 2020-11-0999Milwaukee Admirals3Peoria Rivermen1WSommaire du Match
15 - 2020-11-11114Milwaukee Admirals0Rockford IceHogs3LSommaire du Match
16 - 2020-11-12125Rouyn-Noranda Huskies0Milwaukee Admirals2WSommaire du Match
19 - 2020-11-15142Milwaukee Admirals5Las Vegas Gamblers7LSommaire du Match
20 - 2020-11-16149Milwaukee Admirals5Grand Rapids Griffins2WSommaire du Match
22 - 2020-11-18163Wilkes-Barre/Scranton Penguins1Milwaukee Admirals4WSommaire du Match
25 - 2020-11-21185Joliette Sportif2Milwaukee Admirals4WSommaire du Match
29 - 2020-11-25213Milwaukee Admirals2Grand Rapids Griffins3LXSommaire du Match
31 - 2020-11-27222Chicago Wolves6Milwaukee Admirals5LXSommaire du Match
33 - 2020-11-29239Milwaukee Admirals2Springfield Falcons0WSommaire du Match
34 - 2020-11-30251Milwaukee Admirals3Rochester Americans5LSommaire du Match
36 - 2020-12-02262Henderson Silver Knights2Milwaukee Admirals3WSommaire du Match
38 - 2020-12-04283Providence Bruins1Milwaukee Admirals2WSommaire du Match
41 - 2020-12-07300Milwaukee Admirals3Henderson Silver Knights2WSommaire du Match
43 - 2020-12-09318Henderson Silver Knights3Milwaukee Admirals5WSommaire du Match
46 - 2020-12-12339Lake Erie Monsters3Milwaukee Admirals4WXXSommaire du Match
48 - 2020-12-14352Milwaukee Admirals3Grand Rapids Griffins6LSommaire du Match
50 - 2020-12-16365Milwaukee Admirals3Gatineau Olympiques4LSommaire du Match
53 - 2020-12-19383Joliette Sportif2Milwaukee Admirals3WXSommaire du Match
56 - 2020-12-22407Grand Rapids Griffins4Milwaukee Admirals3LXXSommaire du Match
59 - 2020-12-25432Milwaukee Admirals-Springfield Falcons-
61 - 2020-12-27443Las Vegas Gamblers-Milwaukee Admirals-
65 - 2020-12-31472Chicago Wolves-Milwaukee Admirals-
67 - 2021-01-02483Milwaukee Admirals-Bridgeport Sound Tigers-
69 - 2021-01-04498Milwaukee Admirals-Peoria Rivermen-
70 - 2021-01-05510Providence Bruins-Milwaukee Admirals-
73 - 2021-01-08533The Nuuk Vikings-Milwaukee Admirals-
76 - 2021-01-11553Milwaukee Admirals-Connecticut Whale-
78 - 2021-01-13570Wilkes-Barre/Scranton Penguins-Milwaukee Admirals-
80 - 2021-01-15586Milwaukee Admirals-Lake Erie Monsters-
82 - 2021-01-17599Milwaukee Admirals-Rouyn-Noranda Huskies-
84 - 2021-01-19608Rouyn-Noranda Huskies-Milwaukee Admirals-
88 - 2021-01-23634Houston Aeros-Milwaukee Admirals-
91 - 2021-01-26666Milwaukee Admirals-Las Vegas Gamblers-
92 - 2021-01-27670Adirondack Phantoms-Milwaukee Admirals-
95 - 2021-01-30693Milwaukee Admirals-Manitoba Moose-
96 - 2021-01-31703Oklahoma City Barons-Milwaukee Admirals-
99 - 2021-02-03721Milwaukee Admirals-Binghamton Senators-
100 - 2021-02-04734The Nuuk Vikings-Milwaukee Admirals-
102 - 2021-02-06753Milwaukee Admirals-Rockford IceHogs-
104 - 2021-02-08768Milwaukee Admirals-Rouyn-Noranda Huskies-
106 - 2021-02-10776Charlotte Checkers-Milwaukee Admirals-
109 - 2021-02-13800Milwaukee Admirals-CCCP Red Army-
110 - 2021-02-14807Wilkes-Barre/Scranton Penguins-Milwaukee Admirals-
113 - 2021-02-17829Milwaukee Admirals-Mercer Island Hafgufa-
114 - 2021-02-18838Grand Rapids Griffins-Milwaukee Admirals-
118 - 2021-02-22863Milwaukee Admirals-Mercer Island Hafgufa-
119 - 2021-02-23870Milwaukee Admirals-San Antonio Rampage-
120 - 2021-02-24877Oklahoma City Barons-Milwaukee Admirals-
123 - 2021-02-27899Milwaukee Admirals-Joliette Sportif-
124 - 2021-02-28909Albany Devils-Milwaukee Admirals-
128 - 2021-03-04936Laval Chiefs-Milwaukee Admirals-
130 - 2021-03-06956Milwaukee Admirals-Norfolk Admirals-
132 - 2021-03-08968Milwaukee Admirals-Chicago Wolves-
133 - 2021-03-09977Springfield Falcons-Milwaukee Admirals-
136 - 2021-03-12998Milwaukee Admirals-Rochester Americans-
138 - 2021-03-141010Trois-Rivières Draveurs-Milwaukee Admirals-
140 - 2021-03-161024Milwaukee Admirals-Oklahoma City Barons-
142 - 2021-03-181040Trois-Rivières Draveurs-Milwaukee Admirals-
144 - 2021-03-201049Milwaukee Admirals-Laval Chiefs-
146 - 2021-03-221071Gatineau Olympiques-Milwaukee Admirals-
147 - 2021-03-231076Milwaukee Admirals-The Nuuk Vikings-
151 - 2021-03-271105Mercer Island Hafgufa-Milwaukee Admirals-
154 - 2021-03-301120Milwaukee Admirals-Laval Chiefs-
155 - 2021-03-311136Milwaukee Admirals-Roberval Dwarfs-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
157 - 2021-04-021144Rockford IceHogs-Milwaukee Admirals-
162 - 2021-04-071174Springfield Falcons-Milwaukee Admirals-
164 - 2021-04-091191Milwaukee Admirals-Chicoutimi Saguenéens-
167 - 2021-04-121209Gatineau Olympiques-Milwaukee Admirals-
169 - 2021-04-141226Milwaukee Admirals-Houston Aeros-
172 - 2021-04-171242Peoria Rivermen-Milwaukee Admirals-
175 - 2021-04-201259Milwaukee Admirals-Chicoutimi Saguenéens-
178 - 2021-04-231275Rockford IceHogs-Milwaukee Admirals-
184 - 2021-04-291301Milwaukee Admirals-Houston Aeros-
186 - 2021-05-011313Peoria Rivermen-Milwaukee Admirals-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets4020
Assistance26,00013,000
Assistance PCT100.00%100.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
27 3000 - 100.00% 100,000$1,300,000$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,106,552$ 2,511,704$ 2,511,704$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
13,360$ 801,340$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
2,700,000$ 131 18,679$ 2,446,949$




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