AdmiralsMilwaukee Admirals
29-19-10, 68pts · 6th in Conference 2
Roster
Player # POS CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV AGE CONTRACT
Shane Wright0C/LW100.006840837974747175597272687556501506921975,000$/2yrs
Tye Kartye0C/LW/RW100.008455717680787572506768707256501506924975,000$/1yrs
Vasily Podkolzin0LW/RW100.0075567273757775724869656870625315068241,200,000$/4yrs
Brennan Othmann0LW100.006542747174746566426360606655501506322975,000$/2yrs
Kole Lind0RW100.0058535869626967664665616266545015062261,500,000$/2yrs
Raphael Lavoie0C/RW100.0062446564676563644458615663525015060241,200,000$/3yrs
Jake Wise0C/LW/RW100.005941716562666462436057596252501505925975,000$/2yrs
Danila Klimovich0RW100.0066446565676260624356596162505015059221,100,000$/4yrs
Cameron Wright0RW100.0060466363646765634256575661535015058261,000,000$/3yrs
Parker Wotherspoon0D100.0070508175778573694066617468595015069271,200,000$/3yrs
Declan Chisholm0D100.0063428575788276714068647270625315069251,200,000$/3yrs
Owen Pickering (R)0D100.005840746977756264406161666551501506421886,667$/2yrs
Victtorio Mancini (R)0D100.006140736780756265406362646551501506423975,000$/3yrs
Alex Petrovic0D100.006246636468727264406255686168611506433975,000$/1yrs
Carson Lambos0D100.006245646565636263405856646150501506122975,000$/2yrs
Artem Duda (R)0D100.006341696762626162406157656250501506121950,000$/2yrs
Adam Ginning0D100.006349606468666563405953656053501506125975,000$/1yrs
Billy Sweezey0D100.0060496164657069594053526658595215061291,200,000$/1yrs
Scratches
Jagger Joshua0LW100.0062535861676563574154525857545015057261,000,000$/3yrs
Ethan de Jong0RW100.0057417064616462564154525557525015056251,000,000$/3yrs
Hunter Johannes0LW100.0062426559696563574052525456535015056261,000,000$/3yrs
Zach Dean0C/LW/RW100.005841706562605856415253565850501505622975,000$/2yrs
Danny Katic0LW100.0062416458666058554054545756515015056241,000,000$/3yrs
Jakub Rychlovský0LW100.0058416762616158574054545558515015056231,000,000$/3yrs
Joey Abate0C/LW/RW100.0055555664616664584252535359545015056261,000,000$/3yrs
Carson Golder0RW100.0062406961665956554052515456505015055221,000,000$/3yrs
Jaxsen Wiebe0RW100.0063416960676058554051525556515015055231,000,000$/3yrs
Connor Mylymok0LW100.0061425658646158554053535555525015055251,000,000$/3yrs
Gunnarwolfe Fontaine0LW100.0056406662576058544053535556515015055241,000,000$/3yrs
Joey Larson0C/LW/RW100.0059405958626058554054545456515015055241,000,000$/3yrs
Lucas Mercuri (R)0C100.006140626062595754465353565551501505523975,000$/1yrs
Leo Lööf0D100.0059456465636463594059516458515015060233,000,000$/1yrs
Lucas Johansen0D100.0058417067616563584055516459555015060271,200,000$/1yrs
Colton Poolman0D100.0060407265626765574052536758595015060291,000,000$/1yrs
Marshall Warren (R)0D100.005642636261626160405856595951501505824825,000$/1yrs
Connor Corcoran0D100.0057417264646361584053525758525015058241,000,000$/4yrs
Calle Odelius (R)0D100.005541676161616059405754535850501505721815,000$/2yrs
Josh Maniscalco0D100.005541635658565453405150555353501505426975,000$/1yrs
Filter Tips
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
Goalie # CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV AGE CONTRACT
Ty Young098.00675757636364666565625750501505820975,000$/2yrs
Hunter Miska0100.00645955555755565357585760521505329975,000$/1yrs
Scratches
Evan Cormier0100.005650485854515147535344545015049271,000,000$/3yrs
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Troy Mann6261646162571CAN551500,000$
General Manager
Player Stats
Filter Tips
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
# Player Name Team Name# POS GP G A P +/- PIM PIM5 HIT SHT OSB OSM SHT% SB MP PPG PPA PPP PKG PKA PKP PKM GW GT FO% EG HT P/GP PSG PSS GSAVG
1Tye KartyeAdmiralsAdmirals (NAS)C/LW/RW58222749-185515105130469916.92%2623.9791019101882447.44%000.845110.55
2Shane WrightAdmiralsAdmirals (NAS)C/LW58202646-24155651745810211.49%2822.5571118011933257.40%000.795110.68
3Vasily PodkolzinAdmiralsAdmirals (NAS)LW/RW58152439-17583078108347513.89%2421.1681018213425242.86%000.676100.39
4Brennan OthmannAdmiralsAdmirals (NAS)LW5815213614191576128326411.72%2120.97033112692051.47%100.62130.68
5Kole LindAdmiralsAdmirals (NAS)RW581514298340110114236013.16%1318.9913400015051.28%000.50010.51
6Parker WotherspoonAdmiralsAdmirals (NAS)D5861723-821157252432811.54%8025.656511000103000.00%000.40000.31
7Raphael LavoieAdmiralsAdmirals (NAS)C/RW5891423730107251144217.65%2319.70325000251046.53%000.40000.31
8Declan ChisholmAdmiralsAdmirals (NAS)D5821921-81210487733252.60%6525.40178011108000.00%000.36000.31
9Owen PickeringAdmiralsAdmirals (NAS)D582810-11155452820147.14%3620.1402202268100.00%000.17000.08
10Danila KlimovichAdmiralsAdmirals (NAS)RW58718-101607559173711.86%815.4610100000032.50%000.14000.11
11Victtorio ManciniAdmiralsAdmirals (NAS)D58077-1180413712140.00%3420.0701100070000.00%000.12000.07
12Alex PetrovicAdmiralsAdmirals (NAS)D580556295322360.00%2214.320000000000.00%000.09000.03
13Zach DeanAdmiralsAdmirals (NAS)C/LW/RW143142001155560.00%17.6100000060043.33%000.29000.31
14Jagger JoshuaAdmiralsAdmirals (NAS)LW40134-315549176215.88%415.2001100031025.00%000.10000.03
15Carson LambosAdmiralsAdmirals (NAS)D58033312041141880.00%2015.79000000120040.00%000.05000.06
16Jake WiseAdmiralsAdmirals (NAS)C/LW/RW32213-995274311304.65%914.79000000301042.67%000.09000.05
17Cameron WrightAdmiralsAdmirals (NAS)RW441120803151520.00%19.5301100031043.18%000.05000.02
18Artem DudaAdmiralsAdmirals (NAS)D44011000133020.00%05.0200000000050.00%000.02000.02
19Carson GolderAdmiralsAdmirals (NAS)RW1400040012100.00%04.8200000000054.55%000.00000.11
20Ethan de JongAdmiralsAdmirals (NAS)RW1400024076060.00%26.980000000000.00%000.00000.05
21Adam GinningAdmiralsAdmirals (NAS)D44000-20040000.00%02.1700000000050.00%000.0000-0.02
22Billy SweezeyAdmiralsAdmirals (NAS)D4400000000000.00%00.210000000000.00%000.0000-0.00
Team Total or Average1044120193313-753601201003105537764311.37%41716.68365692970461072822847.41%2470252298100.361736
Filter Tips
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
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Ty YoungAdmiralsAdmirals (NAS)492315100.9081.94293347951031560230.64531489731
2Hunter MiskaAdmiralsAdmirals (NAS)116400.8892.656110027243154301.00021048110
Team Total or Average602919100.9042.073545471221274714530.667335857841
Salary
Player Name POS Age Cap Hit 2017-18 2018-19 2019-20 2020-21 2021-22 2022-23 2023-24 2024-25
Adam Ginning D25975,000$975,000$ RFA
Alex Petrovic D33975,000$975,000$ UFA
Artem Duda D21950,000$975,000$ 975,000$ RFA
Billy Sweezey D291,200,000$1,200,000$ UFA
Brennan Othmann LW22975,000$975,000$ 975,000$ RFA
Calle Odelius D21815,000$975,000$ 975,000$ RFA
Cameron Wright RW261,000,000$1,000,000$ 1,000,000$ 1,000,000$ UFA
Carson Golder RW221,000,000$1,000,000$ 1,000,000$ 1,000,000$ RFA
Carson Lambos D22975,000$975,000$ 975,000$ RFA
Colton Poolman D291,000,000$1,000,000$ UFA
Connor Corcoran D241,000,000$1,000,000$ 1,000,000$ 1,000,000$ 1,000,000$ UFA
Connor Mylymok LW251,000,000$1,000,000$ 1,000,000$ 1,000,000$ UFA
Danila Klimovich RW221,100,000$1,100,000$ 1,100,000$ 1,100,000$ 1,100,000$ RFA
Danny Katic LW241,000,000$1,000,000$ 1,000,000$ 1,000,000$ UFA
Declan Chisholm D251,200,000$1,200,000$ 1,200,000$ 1,200,000$ UFA
Ethan de Jong RW251,000,000$1,000,000$ 1,000,000$ 1,000,000$ UFA
Evan Cormier G271,000,000$1,000,000$ 1,000,000$ 1,000,000$ UFA
Gunnarwolfe Fontaine LW241,000,000$1,000,000$ 1,000,000$ 1,000,000$ UFA
Hunter Johannes LW261,000,000$1,000,000$ 1,000,000$ 1,000,000$ UFA
Hunter Miska G29975,000$975,000$ UFA
Jagger Joshua LW261,000,000$1,000,000$ 1,000,000$ 1,000,000$ UFA
Jake Wise C/LW/RW25975,000$975,000$ 975,000$ RFA
Jakub Rychlovský LW231,000,000$1,000,000$ 1,000,000$ 1,000,000$ RFA
Jaxsen Wiebe RW231,000,000$1,000,000$ 1,000,000$ 1,000,000$ RFA
Joey Abate C/LW/RW261,000,000$1,000,000$ 1,000,000$ 1,000,000$ UFA
Joey Larson C/LW/RW241,000,000$1,000,000$ 1,000,000$ 1,000,000$ RFA
Josh Maniscalco D26975,000$975,000$ RFA
Kole Lind RW261,500,000$1,500,000$ 1,500,000$ UFA
Leo Lööf D233,000,000$3,000,000$ RFA
Lucas Johansen D271,200,000$1,200,000$ UFA
Lucas Mercuri C23975,000$975,000$ RFA
Marshall Warren D24825,000$975,000$ RFA
Owen Pickering D21886,667$975,000$ 975,000$ RFA
Parker Wotherspoon D271,200,000$1,200,000$ 1,200,000$ 1,200,000$ UFA
Raphael Lavoie C/RW241,200,000$1,200,000$ 1,200,000$ 1,200,000$ UFA
Shane Wright C/LW21975,000$975,000$ 975,000$ RFA
Ty Young G20975,000$975,000$ 975,000$ RFA
Tye Kartye C/LW/RW24975,000$975,000$ RFA
Vasily Podkolzin LW/RW241,200,000$1,200,000$ 1,200,000$ 1,200,000$ 1,200,000$ UFA
Victtorio Mancini D23975,000$975,000$ 975,000$ 975,000$ RFA
Zach Dean C/LW/RW22975,000$975,000$ 975,000$ RFA

Lines
Forward Lines


# - Shane Wright


# - Tye Kartye


# - Vasily Podkolzin


# - Brennan Othmann


# - Raphael Lavoie


# - Kole Lind


# - Shane Wright


# - Tye Kartye


# - Danila Klimovich


# - Tye Kartye


# - Shane Wright


# - Vasily Podkolzin

Defensive Pairings


# - Declan Chisholm


# - Parker Wotherspoon


# - Victtorio Mancini


# - Owen Pickering


# - Alex Petrovic


# - Carson Lambos

1st Power Play Unit


# - Shane Wright


# - Tye Kartye


# - Vasily Podkolzin


# - Declan Chisholm


# - Parker Wotherspoon

2nd Power Play Unit


# - Brennan Othmann


# - Raphael Lavoie


# - Kole Lind


# - Victtorio Mancini


# - Owen Pickering

Goalies


# - Hunter Miska


# - Ty Young

Team Stats
Filter Tips
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
# VS Team 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 GF% SH% SV% PDO PDOBRK
1AdmiralsGulls1100000020221.000246012842452292893474005550219000.00%10100.00%042688648.08%45795947.65%28858249.48%108145010816121385714100.0%22.2%100.0%122.2LUCKY
2AdmiralsMoose40200020813-540.50081018002842452295289347400558328286810440.00%9366.67%042688648.08%45795947.65%28858249.48%10814501081612138571428.6%8.4%84.3%92.8Unlucky
3AdmiralsBruins1010000023-100.0002350028424522172893474005538141117200.00%3166.67%042688648.08%45795947.65%28858249.48%10814501081612138571450.0%11.8%92.1%103.9LUCKY
4AdmiralsAmericans4010200189-150.6258122001284245228528934740055692927928225.00%11554.55%042688648.08%45795947.65%28858249.48%10814501081612138571460.0%9.4%87.0%96.4FUN
5AdmiralsHeat3200100072561.0007132001284245224228934740055371217446116.67%60100.00%042688648.08%45795947.65%28858249.48%10814501081612138571475.0%16.7%94.6%111.3LUCKY
6AdmiralsWolves2100001063341.000691500284245223028934740055502012209333.33%6183.33%142688648.08%45795947.65%28858249.48%10814501081612138571460.0%20.0%94.0%114.0LUCKY
7AdmiralsIceHogs2010010037-410.25035800284245223028934740055752717362150.00%6183.33%042688648.08%45795947.65%28858249.48%10814501081612138571425.0%10.0%90.7%100.7FUN
8AdmiralsEagles2110000034-120.5003690028424522512893474005544810404125.00%5180.00%042688648.08%45795947.65%28858249.48%10814501081612138571440.0%5.9%90.9%96.8Unlucky
9AdmiralsMonsters2010100067-120.50067131028424522502893474005537814385240.00%7271.43%042688648.08%45795947.65%28858249.48%10814501081612138571444.4%12.0%81.1%93.1FUN
10AdmiralsStars3100011074350.8337101700284245225428934740055321217535240.00%6183.33%042688648.08%45795947.65%28858249.48%10814501081612138571462.5%13.0%87.5%100.5FUN
11AdmiralsGriffins44000000126681.00012203200284245221062893474005510951198814535.71%7185.71%042688648.08%45795947.65%28858249.48%10814501081612138571458.3%11.3%94.5%105.8LUCKY
12AdmiralsCheckers 11010000012-100.00012300284245221328934740055152216000.00%10100.00%042688648.08%45795947.65%28858249.48%10814501081612138571433.3%7.7%86.7%94.4Unlucky
13AdmiralsReign1000010001-110.5000000028424522528934740055125013100.00%000.00%042688648.08%45795947.65%28858249.48%1081450108161213857140.0%0.0%91.7%91.7DULL
14AdmiralsWild412001001111030.37511193000284245228728934740055642466910220.00%3166.67%042688648.08%45795947.65%28858249.48%10814501081612138571447.4%12.6%82.8%95.5FUN
15AdmiralsRocket1010000003-300.00000000284245221328934740055165015400.00%000.00%042688648.08%45795947.65%28858249.48%1081450108161213857140.0%0.0%81.3%81.3Unlucky
16AdmiralsComets2100000121130.75023501284245221028934740055288937200.00%20100.00%042688648.08%45795947.65%28858249.48%10814501081612138571466.7%20.0%96.4%116.4LUCKY
17AdmiralsIslanders2200000092741.0009162501284245222728934740055281120264375.00%5180.00%042688648.08%45795947.65%28858249.48%10814501081612138571485.7%33.3%92.9%126.2LUCKY
18AdmiralsWolf Pack1010000013-200.00011200284245221828934740055451271711100.00%10100.00%042688648.08%45795947.65%28858249.48%1081450108161213857140.0%5.6%93.3%98.9DULL
19AdmiralsBelleville Senators2100100085341.0008122000284245224828934740055562711437342.86%30100.00%042688648.08%45795947.65%28858249.48%10814501081612138571450.0%16.7%91.1%107.7Unlucky
20AdmiralsPhantoms1000001021121.000213002842452272893474005510110162150.00%000.00%042688648.08%45795947.65%28858249.48%10814501081612138571450.0%28.6%90.0%118.6FUN
21AdmiralsRoadrunners1010000002-200.000000102842452262893474005574210200.00%10100.00%042688648.08%45795947.65%28858249.48%1081450108161213857140.0%0.0%71.4%71.4Unlucky
22Admirals Penguins1000000123-110.500246002842452218289347400553221414400.00%2150.00%042688648.08%45795947.65%28858249.48%10814501081612138571450.0%11.1%90.6%101.7FUN
23AdmiralsBarracuda2010001045-120.500459002842452220289347400552741027200.00%5260.00%242688648.08%45795947.65%28858249.48%10814501081612138571457.1%20.0%81.5%101.5FUN
24AdmiralsThunderbirds3210000084440.6678917102842452260289347400551162334469222.22%7185.71%042688648.08%45795947.65%28858249.48%10814501081612138571466.7%13.3%96.6%109.9LUCKY
25AdmiralsCrunch3000020147-330.50047110028424522472893474005561191645500.00%8187.50%042688648.08%45795947.65%28858249.48%10814501081612138571440.0%8.5%88.5%97.0Unlucky
26AdmiralsMarlies20200000511-600.000581300284245224128934740055962119377228.57%7271.43%142688648.08%45795947.65%28858249.48%10814501081612138571425.0%12.2%88.5%100.7FUN
27AdmiralsCanucks1010000012-100.000123002842452217289347400552322183133.33%10100.00%042688648.08%45795947.65%28858249.48%1081450108161213857140.0%5.9%91.3%97.2DULL
28AdmiralsHershey Bears1010000037-400.0003360028424522332893474005536113421100.00%2150.00%042688648.08%45795947.65%28858249.48%10814501081612138571433.3%9.1%80.6%89.6FUN
29AdmiralsCheckers 21000001021121.00022400284245221628934740055268418400.00%20100.00%042688648.08%45795947.65%28858249.48%10814501081612138571466.7%12.5%96.2%108.7LUCKY
_Vs Division9860033016115251.389162642022842452210928934740055130313513916212.50%15286.67%242688648.08%45795947.65%28858249.48%10814501081612138571460.9%14.7%91.5%106.2LUCKY
_Vs Conference311290145067607400.64567103170222842452258128934740055637206166531691826.09%581181.03%242688648.08%45795947.65%28858249.48%10814501081612138571450.0%11.5%90.6%102.1FUN
_Since Last GM Reset58171905674127129-2680.5861271933203528424522105528934740055127741736410031333627.07%1172677.78%442688648.08%45795947.65%28858249.48%10814501081612138571446.9%12.0%89.9%101.9FUN
Total58171905674127129-2680.5861271933203528424522105528934740055127741736410031333627.07%1172677.78%442688648.08%45795947.65%28858249.48%10814501081612138571446.9%12.0%89.9%101.9FUN

Puck Time
Offensive Zone 18
Neutral Zone 23
Defensive Zone 18
Puck Time
Offensive Zone Start 886
Neutral Zone Start 582
Defensive Zone Start 959
Puck Time
With Puck 30
Without Puck 30
Faceoffs
Faceoffs Won 1171
Faceoffs Lost 1256
Team Average Shots after League Average Shots after
1st Period 5.09.57
2nd Period 11.020.31
3rd Period 17.930.68
Overtime 18.831.4
Goals in Team Average Goals after League Average Goals after
1st Period 0.50.64
2nd Period 1.21.65
3rd Period 2.02.67
Overtime 2.42.83
Even Strenght Goal 84
PP Goal 36
PK Goal 4
Empty Net Goal 3
Home Away
Win 1514
Lost 109
Overtime Lost 46
PP Attempt 133
PP Goal 36
PK Attempt 117
PK Goal Against 26
Home
Shots For 18.2
Shots Against 22.0
Goals For 2.2
Goals Against 2.2
Hits 17.3
Shots Blocked 7.2
Pim 6.3
Schedule
DateMatchup Result Detail
Wed, Oct 8AdmiralsNAS@AdmiralsCHINAS1,CHI2 (OT)RECAP
Sat, Oct 11AdmiralsCAL@AdmiralsNASCAL1,NAS3RECAP
Tue, Oct 14AdmiralsTAM@AdmiralsNASTAM3,NAS2 (OT)RECAP
Thu, Oct 16AdmiralsNAS@AdmiralsBUFNAS3,BUF5RECAP
Sat, Oct 18AdmiralsSTL@AdmiralsNASSTL1,NAS6RECAP
Mon, Oct 20AdmiralsWPG@AdmiralsNASWPG8,NAS3RECAP
Tue, Oct 21AdmiralsNAS@AdmiralsDALNAS2,DAL1 (SO)RECAP
Fri, Oct 24AdmiralsBUF@AdmiralsNASBUF2,NAS3 (OT)RECAP
Sun, Oct 26AdmiralsNAS@AdmiralsMINNAS6,MIN2RECAP
Tue, Oct 28AdmiralsNAS@AdmiralsCOLNAS3,COL1RECAP
Wed, Oct 29AdmiralsNAS@AdmiralsSTLNAS2,STL1RECAP
Fri, Oct 31AdmiralsMIN@AdmiralsNASMIN4,NAS2RECAP
Mon, Nov 3AdmiralsDAL@AdmiralsNASDAL2,NAS5RECAP
Tue, Nov 4AdmiralsNAS@AdmiralsWASNAS3,WAS7RECAP
Thu, Nov 6AdmiralsDET@AdmiralsNASDET1,NAS2RECAP
Fri, Nov 7AdmiralsNAS@AdmiralsWPGNAS3,WPG2 (SO)RECAP
Mon, Nov 10AdmiralsNAS@AdmiralsDETNAS4,DET2RECAP
Wed, Nov 12AdmiralsOTT@AdmiralsNASOTT3,NAS4 (OT)RECAP
Thu, Nov 13AdmiralsDET@AdmiralsNASDET1,NAS2RECAP
Sun, Nov 16AdmiralsNAS@AdmiralsCOLNAS0,COL3RECAP
Mon, Nov 17AdmiralsTOR@AdmiralsNASTOR6,NAS2RECAP
Wed, Nov 19AdmiralsNAS@AdmiralsDETNAS4,DET2RECAP
Sat, Nov 22AdmiralsNYR@AdmiralsNASNYR3,NAS1RECAP
Sun, Nov 23AdmiralsNAS@AdmiralsCARNAS3,CAR2 (SO)RECAP
Tue, Nov 25AdmiralsFLO@AdmiralsNASFLO2,NAS1RECAP
Fri, Nov 28AdmiralsNAS@AdmiralsOTTNAS4,OTT2RECAP
Sat, Nov 29AdmiralsNAS@AdmiralsNJDNAS0,NJD1 (SO)RECAP
Mon, Dec 1AdmiralsBUF@AdmiralsNASBUF0,NAS1 (OT)RECAP
Wed, Dec 3AdmiralsMIN@AdmiralsNASMIN2,NAS1 (OT)RECAP
Fri, Dec 5AdmiralsNAS@AdmiralsCALNAS2,CAL1 (OT)RECAP
Mon, Dec 8AdmiralsNAS@AdmiralsMINNAS2,MIN3RECAP
Tue, Dec 9AdmiralsMTL@AdmiralsNASMTL3,NAS0RECAP
Fri, Dec 12AdmiralsNAS@AdmiralsBUFNAS1,BUF2 (SO)RECAP
Sat, Dec 13AdmiralsCAL@AdmiralsNASCAL0,NAS2RECAP
Tue, Dec 16AdmiralsNAS@AdmiralsCLBNAS3,CLB5RECAP
Wed, Dec 17AdmiralsANA@AdmiralsNASANA0,NAS2RECAP
Sat, Dec 20AdmiralsNJD@AdmiralsNASNJD0,NAS2RECAP
Sun, Dec 21AdmiralsNAS@AdmiralsDALNAS0,DAL1 (OT)RECAP
Wed, Dec 24AdmiralsNAS@AdmiralsVANNAS1,VAN2RECAP
Fri, Dec 26AdmiralsCLB@AdmiralsNASCLB2,NAS3 (OT)RECAP
Sun, Dec 28AdmiralsNAS@AdmiralsBOSNAS2,BOS3RECAP
Tue, Dec 30AdmiralsNYI@AdmiralsNASNYI2,NAS8RECAP
Fri, Jan 2AdmiralsNAS@AdmiralsSEANAS2,SEA1 (SO)RECAP
Mon, Jan 5AdmiralsTAM@AdmiralsNASTAM1,NAS0 (SO)RECAP
Wed, Jan 7AdmiralsWPG@AdmiralsNASWPG2,NAS0RECAP
Fri, Jan 9AdmiralsNAS@AdmiralsPHONAS0,PHO2RECAP
Sat, Jan 10AdmiralsNAS@AdmiralsTAMNAS2,TAM3 (OT)RECAP
Mon, Jan 12AdmiralsSTL@AdmiralsNASSTL2,NAS0RECAP
Thu, Jan 15AdmiralsLOS@AdmiralsNASLOS1,NAS0 (OT)RECAP
Fri, Jan 16AdmiralsNAS@AdmiralsNYINAS1,NYI0RECAP
Mon, Jan 19AdmiralsCHI@AdmiralsNASCHI5,NAS2RECAP
Wed, Jan 21AdmiralsPHI@AdmiralsNASPHI1,NAS2 (SO)RECAP
Fri, Jan 23AdmiralsNAS@AdmiralsWPGNAS2,WPG1 (SO)RECAP
Sun, Jan 25AdmiralsNAS@AdmiralsS JNAS3,S J2 (SO)RECAP
Mon, Jan 26AdmiralsNAS@AdmiralsPITNAS2,PIT3 (SO)RECAP
Wed, Jan 28AdmiralsCAR@AdmiralsNASCAR1,NAS3RECAP
Fri, Jan 30AdmiralsNAS@AdmiralsTORNAS3,TOR5RECAP
Sun, Feb 1AdmiralsS J@AdmiralsNASS J3,NAS1RECAP
Tue, Feb 3AdmiralsBOS@AdmiralsNAS
Fri, Feb 6AdmiralsCOL@AdmiralsNAS
Sun, Feb 8AdmiralsNAS@AdmiralsLOS
Mon, Feb 9AdmiralsNAS@AdmiralsFLO
Wed, Feb 11AdmiralsEDM@AdmiralsNAS
Fri, Feb 13AdmiralsNAS@AdmiralsWAS
Sun, Feb 15AdmiralsWAS@AdmiralsNAS
Wed, Feb 18AdmiralsNAS@AdmiralsCHI
Thu, Feb 19AdmiralsNAS@AdmiralsPHI
Fri, Feb 20AdmiralsDAL@AdmiralsNAS
Mon, Feb 23AdmiralsPHO@AdmiralsNAS
Thu, Feb 26AdmiralsCHI@AdmiralsNAS
Fri, Feb 27AdmiralsNAS@AdmiralsCHI
Mon, Mar 2AdmiralsCHI@AdmiralsNAS
Tue, Mar 3AdmiralsNAS@AdmiralsSTL
Thu, Mar 5AdmiralsNAS@AdmiralsANA
Sat, Mar 7AdmiralsNAS@AdmiralsMTL
Sun, Mar 8AdmiralsSEA@AdmiralsNAS
Trade Deadline --- Trades can’t be done after this day is simulated!
Tue, Mar 10AdmiralsNAS@AdmiralsCHI
Thu, Mar 12AdmiralsNAS@AdmiralsNYR
Sat, Mar 14AdmiralsCHI@AdmiralsNAS
Tue, Mar 17AdmiralsPIT@AdmiralsNAS
Wed, Mar 18AdmiralsNAS@AdmiralsEDM
Mon, Mar 23AdmiralsVAN@AdmiralsNAS

Finance
Salary Cap
Players Total SalariesRetained SalaryTotal Cap HitEstimated Cap Space
4,437,500$ 0$ 0$ 75,000,000$

ArenaAbout us
Name
CityMilwaukee
Capacity3000
Season Ticket Holders10%

Arena Capacity - Ticket Price Attendance - %
Arena Capacity20001000
Ticket Price35$15$$$$
Attendance00
Attendance PCT0.00%0.00%0.00%0.00%0.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
12 0 - 0.00% 0$0$3000100

Expenses
Players Total SalariesPlayers Total Average SalariesCoaches SalariesSpecial Salary Cap Value
4,437,500$ 4,437,500$ 0$ 0$
Year To Date ExpensesSalary Cap Per DaysSalary Cap To DateLuxury Taxe Total
3,391,304$ 0$ 3,042,142$ 0$

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 74 29,216$ 1,490,016$

Team Total Estimate
Estimated Season ExpensesEstimated Season Salary CapCurrent Bank AccountProjected Bank Account
1,490,016$ 0$ 0$ 0$

Sponsors
TV RightsPrimary SponsorSecondary SponsorSecondary Sponsor
Depth Chart RookieInjured Cold Streak Hot Streak
Left WingCenterRight Wing

Defense #1Defense #2Goalie

Transactions



Injuries
No Injury or Suspension.

Game Center

Admirals29-19-10, 68pts35Final
Marlies42-10-5, 89pts

Barracuda32-16-9, 73pts31Final
Admirals29-19-10, 68pts

Barracuda32-16-9, 73ptsMon, Feb 02
Admirals29-19-10, 68pts

Heat20-34-5, 45ptsSun, Oct 12
Admirals29-19-10, 68pts

Crunch26-24-8, 60ptsWed, Oct 15
Admirals29-19-10, 68pts

TRANSACTIONS



 

Team Info

Admirals
Head CoachTroy Mann
DivisionCentral Division
CityMilwaukee
Stadium Capacity3,000

Admirals Affiliation

Admirals
General ManagerManuel Beaulieu
Head CoachJared Bednar
StadiumGaylord Ent. Center
Capacity19,113

Team Leaders


GOALS
Tye Kartye
AdmiralsAdmirals
22
GOALS
POINTS
Tye Kartye
AdmiralsAdmirals
49
POINTS
WINS
Ty Young
AdmiralsAdmirals
23
WINS
Expanded Player Leaderboard

Team Stats


Goals For
127
2.19 GFG
Goals Against
129
2.22 GAA
Power Play Percentage
27.1%
36 GF
Penalty Kill Percentage
77.8%
26 GA
Expanded Team Stats

Team Captain - Alternate Captains

CaptainAlternate CaptainAlternate Captain