WEB CLIENT LEAGUE FILES


Milwaukee Admirals


GP: 52 | W: 19 | L: 29 | OTL: 4 | P: 42
GF: 115 | GA: 140 | PP%: 13.16% | PK%: 81.29%
GM : Richard Miller | Team Overall : 66
Next Games vs Denver Spurs
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

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 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
1Zemgus GirgensonsXX97.00764092747980907371706974666458050690
2Taylor BeckXX99.00764583717682847166676774747779050680
3Nic Dowd (R)XX99.00744387727178806778646372648076050670
4Jacob JosefsonXX100.00683391757080757075676274648073050670
5Alex Friesen (R)XX100.00743376737081846872656473616566050660
6Cedric Paquette (R)XXX100.00785276717978766874666370595960050660
7Zac RinaldoXX99.00878563697676856663646170527464050660
8Landon Ferraro (R)XX100.00744781797276796670656369635650050650
9Liam O'Brien (R)X100.00823780747876756464616173575352050640
10Felix Girard (R)X100.00744276747078826573626071575052050640
11Martin Frk (R)X100.00744388707675726558636067725350050630
12Andrew MacWilliamX100.00824580708582826430626073477876050690
13Anthony Bitetto (R)X100.00815270737684847030676673676464050690
14Yannick WeberX100.00673988727481836630646173518380050680
15Robbie Russo (R)X100.00733284757284866730656173465858050680
16Codey GoloubefX100.00734284757679786330626169507373050670
17Jake Dotchin (R)X100.00807073707979786130595369485450050650
18Dakota Mermis (R)X100.00733982747377686130595269504853050640
Scratches
1Quentin Shore (R)XX100.00723283687168686168595566575252050600
2Austin Fyten (R)X100.00634970656670505150504567484040050540
3Nick DeSimoneX100.00683088766973686230615669484747050630
4Daniel Maggio (R)X100.00777372687676645730554168404343050620
5Bryce Aneloski (R)X100.00734278607277685730545068454645050610
TEAM AVERAGE99.7475458072747876645162597156615905065
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 CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Marek Mazanec (R)100.0079767883788080808077815957050750
2Adam Wilcox (R)100.0082757580837979797978815252050750
Scratches
1Martin Ouellette (R)100.0079757279817677787875745755050730
TEAM AVERAGE100.008075758181787979797779565505074
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Peter Horachek84767073797976CAN581875,000$


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 NamePOS GP 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
1Nic DowdMilwaukee Admirals (NSH)C/RW521416300604713715136789.27%8112021.5403315991015842053.40%130900000.5426000115
2Jacob JosefsonMilwaukee Admirals (NSH)C/LW52101929-14037111122591078.20%14103519.921672412810181301153.00%75100000.5617000014
3Anthony BitettoMilwaukee Admirals (NSH)D5162228-1595148658230607.32%54102320.0824637100011053110.00%000000.5500000021
4Landon FerraroMilwaukee Admirals (NSH)C/RW52101222-9140717999307610.10%989517.230114260001871144.29%21900000.4900000221
5Zac RinaldoMilwaukee Admirals (NSH)LW/RW52913224300168609641969.38%589017.1313414940000300054.10%6100000.4901000413
6Cedric PaquetteMilwaukee Admirals (NSH)C/LW/RW48910197140818380176911.25%776916.03213135101111072149.16%77300000.4913000211
7Robbie RussoMilwaukee Admirals (NSH)D5231518212066625919415.08%65106620.5011224931123138000.00%000000.3400000001
8Taylor BeckMilwaukee Admirals (NSH)LW/RW3861117-280377412237964.92%1173519.350111279000010357.14%4200000.4615000100
9Alex FriesenMilwaukee Admirals (NSH)C/LW52124160140709512438999.68%989317.192027330000372148.55%17300000.3600000012
10Yannick WeberMilwaukee Admirals (NSH)D5221416-926066564616194.35%71106120.420000100006400100.00%100000.3000000011
11Liam O'BrienMilwaukee Admirals (NSH)C448816-380606165164712.31%1057813.16000000000471042.73%66000000.5500000210
12Andrew MacWilliamMilwaukee Admirals (NSH)D52211130380114423013206.67%4683216.0100000000017100.00%000000.3100000121
13Zemgus GirgensonsMilwaukee Admirals (NSH)C/LW145813140233540155312.50%531722.680227230111371050.50%10100000.8211000210
14Codey GoloubefMilwaukee Admirals (NSH)D523811-9460120405019316.00%4485416.44202239400000000.00%000000.2600000100
15Quentin ShoreMilwaukee Admirals (NSH)C/RW38538-860192235112414.29%248712.82000020000131046.30%5400000.3300000001
16Martin FrkMilwaukee Admirals (NSH)RW51448214022305414367.41%360911.96112632000001033.33%4500000.2601000101
17Austin FytenMilwaukee Admirals (NSH)LW37347-111003220334209.09%670619.1000000000010020.83%4800000.2000000000
18Felix GirardMilwaukee Admirals (NSH)C52347-106037475611455.36%54278.21011321000022046.88%44800000.3300000011
19Jake DotchinMilwaukee Admirals (NSH)D52055316055198250.00%173446.63000030002124000.00%000000.2900000010
20Bryce AneloskiMilwaukee Admirals (NSH)D1011000000000.00%066.720000000000000.00%000002.9800000000
21Dakota MermisMilwaukee Admirals (NSH)D10011-2001639430.00%919419.47000218000020000.00%000000.1000000000
22Matt HunwickNashville PredatorsD1000-100150000.00%22121.400000100004000.00%000000.0000000000
23Daniel MaggioMilwaukee Admirals (NSH)D9000000000000.00%030.340000000000000.00%000000.0000000000
24Colin GreeningNashville PredatorsLW/RW1000-100110040.00%11818.450000100000000.00%100000.0000000000
25Nick DeSimoneMilwaukee Admirals (NSH)D10000000201000.00%1151.5200000000011000.00%000000.0000000000
Team Total or Average925114193307-48335512931147136243210298.37%4041491116.1212243619190934721101716849.27%468600000.41624000171623
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
1Adam WilcoxMilwaukee Admirals (NSH)32111630.9212.46185462769660110.706173022530
2Marek MazanecMilwaukee Admirals (NSH)2271210.9102.71117300535900100.80052030121
3Martin OuelletteMilwaukee Admirals (NSH)21100.9053.03119006630000.000020000
Team Total or Average56192940.9172.5831466213516190210.727225252651


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 NamePOS Age Birthday Rookie Weight Height No Trade Available For Trade Force Waivers Contract StatusType Current Salary Salary Year 2 Salary Year 3 Salary Year 4 Salary Year 5 Salary Year 6 Salary Year 7 Salary Year 8 Salary Year 9 Salary Year 10 Link
Adam WilcoxMilwaukee Admirals (NSH)C/LW/RW2611/26/1992 11:10:15 AMYes187 Lbs6 ft0NoNoNo3RFAPro & Farm700,000$700,000$700,000$Link / NHL Link
Alex FriesenMilwaukee Admirals (NSH)C/LW271/30/1991 7:21:30 AMYes186 Lbs5 ft9NoNoNo1RFAPro & Farm600,000$Link / NHL Link
Andrew MacWilliamMilwaukee Admirals (NSH)D283/25/1990 5:03:43 AMNo223 Lbs6 ft2NoNoNo1RFAPro & Farm742,500$Link / NHL Link
Anthony BitettoMilwaukee Admirals (NSH)D287/15/1990 10:25:38 AMYes210 Lbs6 ft1NoNoNo2RFAPro & Farm1,000,000$1,000,000$Link / NHL Link
Austin FytenMilwaukee Admirals (NSH)LW275/3/1991 5:47:05 AMYes190 Lbs6 ft1NoNoNo1RFAPro & Farm600,000$NHL Link
Bryce AneloskiMilwaukee Admirals (NSH)D284/27/1990 9:55:47 AMYes198 Lbs6 ft2NoNoNo1RFAPro & Farm600,000$NHL Link
Cedric PaquetteMilwaukee Admirals (NSH)C/LW/RW258/13/1993 9:15:26 AMYes198 Lbs6 ft1NoNoNo1RFAPro & Farm925,000$Link / NHL Link
Codey GoloubefMilwaukee Admirals (NSH)D2911/30/1989 1:59:52 PMNo200 Lbs6 ft1NoNoNo3UFAPro & Farm600,000$675,000$725,000$Link / NHL Link
Dakota MermisMilwaukee Admirals (NSH)D241/5/1994 10:29:07 AMYes195 Lbs6 ft0NoNoNo1RFAPro & Farm775,000$Link / NHL Link
Daniel MaggioMilwaukee Admirals (NSH)D273/4/1991 10:28:58 AMYes202 Lbs6 ft3NoNoNo1RFAPro & Farm600,000$Link / NHL Link
Felix GirardMilwaukee Admirals (NSH)C245/9/1994 8:57:41 AMYes197 Lbs5 ft10NoNoNo2RFAPro & Farm700,000$700,000$Link / NHL Link
Jacob JosefsonMilwaukee Admirals (NSH)C/LW273/2/1991 5:25:39 AMNo196 Lbs6 ft0NoNoNo1RFAPro & Farm1,250,000$Link / NHL Link
Jake DotchinMilwaukee Admirals (NSH)D243/24/1994 7:33:43 AMYes210 Lbs6 ft3NoNoNo1RFAPro & Farm500,000$Link / NHL Link
Landon FerraroMilwaukee Admirals (NSH)C/RW278/8/1991 5:29:18 AMYes176 Lbs6 ft0NoNoNo2RFAPro & Farm940,000$940,000$Link / NHL Link
Liam O'BrienMilwaukee Admirals (NSH)C247/29/1994 8:01:08 AMYes215 Lbs6 ft1NoNoNo3RFAPro & Farm825,000$825,000$825,000$Link / NHL Link
Marek MazanecMilwaukee Admirals (NSH)LW/RW277/18/1991 10:40:03 AMYes187 Lbs6 ft4NoNoNo1RFAPro & Farm900,000$Link / NHL Link
Martin FrkMilwaukee Admirals (NSH)RW2510/5/1993 5:11:50 AMYes205 Lbs6 ft1NoNoNo1RFAPro & Farm1,045,000$Link / NHL Link
Martin OuelletteMilwaukee Admirals (NSH)LW/RW2712/30/1991 11:11:42 AMYes160 Lbs6 ft1NoNoNo2RFAPro & Farm700,000$700,000$Link / NHL Link
Nic DowdMilwaukee Admirals (NSH)C/RW285/27/1990 10:22:01 AMYes197 Lbs6 ft2NoNoNo2RFAPro & Farm900,000$900,000$Link / NHL Link
Nick DeSimoneMilwaukee Admirals (NSH)D2411/21/1994 6:49:58 AMNo195 Lbs6 ft2NoNoNo1RFAPro & Farm750,000$NHL Link
Quentin ShoreMilwaukee Admirals (NSH)C/RW245/25/1994 11:04:49 AMYes183 Lbs6 ft2NoNoNo3RFAPro & Farm500,000$500,000$600,000$NHL Link
Robbie RussoMilwaukee Admirals (NSH)D252/15/1993 9:01:02 AMYes191 Lbs6 ft0NoNoNo2RFAPro & Farm700,000$700,000$Link / NHL Link
Taylor BeckMilwaukee Admirals (NSH)LW/RW275/13/1991 9:30:33 AMNo203 Lbs6 ft2NoNoNo1RFAPro & Farm850,000$Link / NHL Link
Yannick WeberMilwaukee Admirals (NSH)D309/23/1988 4:15:11 AMNo200 Lbs5 ft11NoNoNo1UFAPro & Farm1,500,000$Link / NHL Link
Zac RinaldoMilwaukee Admirals (NSH)LW/RW286/15/1990 9:44:48 AMNo192 Lbs5 ft10NoNoNo3RFAPro & Farm750,000$950,000$1,000,000$Link / NHL Link
Zemgus GirgensonsMilwaukee Admirals (NSH)C/LW241/5/1994 7:25:04 AMNo207 Lbs6 ft2NoNoNo1RFAPro & Farm1,100,000$Link / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2626.31196 Lbs6 ft11.62809,712$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Zac RinaldoNic DowdTaylor Beck33014
2Zemgus GirgensonsJacob JosefsonCedric Paquette30113
3Alex FriesenLiam O\'BrienLandon Ferraro25122
4Zemgus GirgensonsFelix GirardMartin Frk12230
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Anthony BitettoDakota Mermis33014
2Andrew MacWilliamRobbie Russo30113
3Yannick WeberCodey Goloubef30122
4Jake DotchinYannick Weber7122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Taylor BeckNic DowdJacob Josefson50005
2Zac RinaldoZemgus GirgensonsJacob Josefson50005
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Anthony BitettoDakota Mermis50005
2Codey GoloubefRobbie Russo50005
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Cedric PaquetteJacob Josefson50122
2Zemgus GirgensonsZac Rinaldo50122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Dakota MermisYannick Weber50122
2Jake DotchinRobbie Russo50122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Landon Ferraro50122Yannick WeberAndrew MacWilliam50122
2Felix Girard50122Dakota MermisRobbie Russo50122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Cedric PaquetteJacob Josefson50122
2Alex FriesenTaylor Beck50122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Yannick WeberAnthony Bitetto50122
2Dakota MermisRobbie Russo50122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Cedric PaquetteNic DowdTaylor BeckAnthony BitettoRobbie Russo
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Zemgus GirgensonsJacob JosefsonCedric PaquetteYannick WeberAndrew MacWilliam
Extra Forwards
Normal PowerPlayPenalty Kill
Landon Ferraro, Taylor Beck, Zemgus GirgensonsZac Rinaldo, Martin FrkLandon Ferraro
Extra Defensemen
Normal PowerPlayPenalty Kill
Codey Goloubef, Yannick Weber, Dakota MermisJake DotchinRobbie Russo, Yannick Weber
Penalty Shots
Jacob Josefson, Nic Dowd, Zemgus Girgensons, Cedric Paquette, Zac Rinaldo
Goalie
#1 : Adam Wilcox, #2 : Marek Mazanec


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
OverallHomeVisitor
# VS Team 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
1Adirondack Angels1010000016-51010000016-50000000000000.000123004536298294464434813543191042000.00%5260.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
2Austin Aces1000000123-1000000000001000000123-110.5002350045362982544644348135428822100.00%40100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
3Binghamton Senators20101000660100010003211010000034-120.5006111700453629850446443481353811660600.00%30100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
4Bridgeport Sound Tigers21100000734110000005051010000023-120.500712190145362984644644348135551227525240.00%60100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
5Carolina Panthers1010000013-2000000000001010000013-200.0001230045362982444644348135298616200.00%3166.67%0819164549.79%900183649.02%39277050.91%12088251268380679337
6Cleveland Monsters30300000510-51010000023-12020000037-400.000510150045362987744644348135931914758225.00%7185.71%0819164549.79%900183649.02%39277050.91%12088251268380679337
7Denver Spurs31100010770210000104221010000035-240.667712190145362988044644348135872522796116.67%9188.89%0819164549.79%900183649.02%39277050.91%12088251268380679337
8Durham Pioneers3020100069-3100010002112020000048-420.333612180045362986844644348135116362487300.00%12375.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
9Halifax Mooseheads20200000210-81010000026-41010000004-400.0002350045362983944644348135581518494125.00%9455.56%0819164549.79%900183649.02%39277050.91%12088251268380679337
10Hartford Wolfpack11000000312110000003120000000000021.0003690045362982044644348135271082211100.00%30100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
11Hershey Bears3120000069-3110000002112020000048-420.3336915004536298934464434813583161864600.00%9366.67%1819164549.79%900183649.02%39277050.91%12088251268380679337
12Iowa Wild20100010440000000000002010001044020.50045900453629864446443481356616858500.00%40100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
13Jacksonville Jokers211000009631010000034-11100000062420.500915240045362986444644348135711616549444.44%8275.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
14Laval Rocket1010000023-1000000000001010000023-100.00024600453629827446443481351914426300.00%20100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
15London Knights2020000048-41010000013-21010000035-200.00048121045362985344644348135661910429111.11%5260.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
16Louisville Thunder2020000036-31010000012-11010000024-200.000369004536298564464434813567192251400.00%11190.91%0819164549.79%900183649.02%39277050.91%12088251268380679337
17Oakville Wolves2010001034-1100000103211010000002-220.50034700453629848446443481355815643300.00%30100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
18Ontario Reign1000000112-1000000000001000000112-110.50012300453629844446443481352610617600.00%20100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
19Philadelphia Phantoms3210000056-13210000056-10000000000040.66759140045362987944644348135116292886300.00%12283.33%2819164549.79%900183649.02%39277050.91%12088251268380679337
20Richmond Renegades2020000036-31010000013-21010000023-100.000358004536298404464434813571281042100.00%30100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
21Rockford IceHogs32000001972110000003122100000166050.8339162500453629880446443481351242620714125.00%90100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
22Seattle Thunderbirds3030000069-32020000035-21010000034-100.00061016004536298784464434813584222674600.00%12558.33%0819164549.79%900183649.02%39277050.91%12088251268380679337
23Syracuse Crunch21000001761110000005321000000123-130.7507111800453629862446443481355515255400.00%10100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
24Texas Stars32100000743211000004311100000031240.667713200045362987744644348135883222719111.11%9188.89%0819164549.79%900183649.02%39277050.91%12088251268380679337
25Toronto Marlies11000000312110000003120000000000021.0003690045362983044644348135184425300.00%2150.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
Total52142902034115140-25261111020205956326318000145684-28420.404115202317124536298138144644348135162045134913061141513.16%1552981.29%3819164549.79%900183649.02%39277050.91%12088251268380679337
27Wilkes Barre-Scranton11000000312110000003120000000000021.00036900453629828446443481352074233133.33%20100.00%0819164549.79%900183649.02%39277050.91%12088251268380679337
_Since Last GM Reset52142902034115140-25261111020205956326318000145684-28420.404115202317124536298138144644348135162045134913061141513.16%1552981.29%3819164549.79%900183649.02%39277050.91%12088251268380679337
_Vs Conference28615010335869-111245010202520516210000133349-16230.41158103161014536298754446443481358882461866996158.20%861384.88%0819164549.79%900183649.02%39277050.91%12088251268380679337
_Vs Division14440001232320622000001394822000121923-4120.429325688014536298378446443481354581188635432515.63%38392.11%0819164549.79%900183649.02%39277050.91%12088251268380679337

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
5242W111520231713811620451349130612
All Games
GPWLOTWOTL SOWSOLGFGA
5214292034115140
Home Games
GPWLOTWOTL SOWSOLGFGA
26111120205956
Visitor Games
GPWLOTWOTL SOWSOLGFGA
2631800145684
Last 10 Games
WLOTWOTL SOWSOL
370000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1141513.16%1552981.29%3
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
446443481354536298
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
819164549.79%900183649.02%39277050.91%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
12088251268380679337


Last Played Games
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
DayGame Visitor Team Score Home Team Score ST OT SO RI Link
2 - 2018-11-2714Philadelphia Phantoms3Milwaukee Admirals0LBoxScore
4 - 2018-11-2937Denver Spurs2Milwaukee Admirals3WBoxScore
6 - 2018-12-0150Milwaukee Admirals1Iowa Wild2LBoxScore
7 - 2018-12-0261Milwaukee Admirals1Ontario Reign2LXXBoxScore
8 - 2018-12-0377Philadelphia Phantoms1Milwaukee Admirals2WBoxScore
9 - 2018-12-0489Milwaukee Admirals2Louisville Thunder4LBoxScore
11 - 2018-12-06108Texas Stars2Milwaukee Admirals1LBoxScore
13 - 2018-12-08128Oakville Wolves2Milwaukee Admirals3WXXBoxScore
14 - 2018-12-09136Milwaukee Admirals0Cleveland Monsters3LBoxScore
16 - 2018-12-11156Milwaukee Admirals2Hershey Bears5LBoxScore
17 - 2018-12-12166Milwaukee Admirals2Laval Rocket3LBoxScore
19 - 2018-12-14183Seattle Thunderbirds2Milwaukee Admirals1LBoxScore
21 - 2018-12-16199Toronto Marlies1Milwaukee Admirals3WBoxScore
22 - 2018-12-17212Milwaukee Admirals2Rockford IceHogs3LXXBoxScore
24 - 2018-12-19231Denver Spurs0Milwaukee Admirals1WXXBoxScore
26 - 2018-12-21245Milwaukee Admirals3Denver Spurs5LBoxScore
28 - 2018-12-23262Jacksonville Jokers4Milwaukee Admirals3LBoxScore
29 - 2018-12-24280Philadelphia Phantoms2Milwaukee Admirals3WBoxScore
32 - 2018-12-27299Milwaukee Admirals2Austin Aces3LXXBoxScore
33 - 2018-12-28313Milwaukee Admirals3Texas Stars1WBoxScore
34 - 2018-12-29324Halifax Mooseheads6Milwaukee Admirals2LBoxScore
36 - 2018-12-31336Milwaukee Admirals6Jacksonville Jokers2WBoxScore
38 - 2019-01-02354Syracuse Crunch3Milwaukee Admirals5WBoxScore
40 - 2019-01-04376Wilkes Barre-Scranton1Milwaukee Admirals3WBoxScore
41 - 2019-01-05392Milwaukee Admirals2Bridgeport Sound Tigers3LBoxScore
42 - 2019-01-06402Milwaukee Admirals2Syracuse Crunch3LXXBoxScore
44 - 2019-01-08415Seattle Thunderbirds3Milwaukee Admirals2LBoxScore
46 - 2019-01-10436Milwaukee Admirals0Halifax Mooseheads4LBoxScore
47 - 2019-01-11446Binghamton Senators2Milwaukee Admirals3WXBoxScore
49 - 2019-01-13460Milwaukee Admirals2Durham Pioneers4LBoxScore
50 - 2019-01-14474Milwaukee Admirals1Carolina Panthers3LBoxScore
52 - 2019-01-16491Richmond Renegades3Milwaukee Admirals1LBoxScore
54 - 2019-01-18508Hartford Wolfpack1Milwaukee Admirals3WBoxScore
55 - 2019-01-19523Milwaukee Admirals3London Knights5LBoxScore
57 - 2019-01-21543Rockford IceHogs1Milwaukee Admirals3WBoxScore
58 - 2019-01-22557Milwaukee Admirals3Cleveland Monsters4LBoxScore
60 - 2019-01-24571Hershey Bears1Milwaukee Admirals2WBoxScore
61 - 2019-01-25587Milwaukee Admirals4Rockford IceHogs3WBoxScore
63 - 2019-01-27602Adirondack Angels6Milwaukee Admirals1LBoxScore
65 - 2019-01-29622Milwaukee Admirals2Durham Pioneers4LBoxScore
66 - 2019-01-30636Louisville Thunder2Milwaukee Admirals1LBoxScore
68 - 2019-02-01650Milwaukee Admirals3Iowa Wild2WXXBoxScore
69 - 2019-02-02660Milwaukee Admirals0Oakville Wolves2LBoxScore
71 - 2019-02-04679Texas Stars1Milwaukee Admirals3WBoxScore
73 - 2019-02-06696Durham Pioneers1Milwaukee Admirals2WXBoxScore
74 - 2019-02-07714Milwaukee Admirals3Seattle Thunderbirds4LBoxScore
76 - 2019-02-09727Cleveland Monsters3Milwaukee Admirals2LBoxScore
78 - 2019-02-11745Milwaukee Admirals2Hershey Bears3LBoxScore
79 - 2019-02-12759London Knights3Milwaukee Admirals1LBoxScore
82 - 2019-02-15776Milwaukee Admirals3Binghamton Senators4LBoxScore
83 - 2019-02-16785Milwaukee Admirals2Richmond Renegades3LBoxScore
84 - 2019-02-17799Bridgeport Sound Tigers0Milwaukee Admirals5WBoxScore
87 - 2019-02-20821Denver Spurs-Milwaukee Admirals-
88 - 2019-02-21838Milwaukee Admirals-Philadelphia Phantoms-
89 - 2019-02-22850Toronto Marlies-Milwaukee Admirals-
90 - 2019-02-23861Milwaukee Admirals-Laval Rocket-
93 - 2019-02-26882Ontario Reign-Milwaukee Admirals-
95 - 2019-02-28903Iowa Wild-Milwaukee Admirals-
96 - 2019-03-01913Milwaukee Admirals-Toronto Marlies-
97 - 2019-03-02924Milwaukee Admirals-Ontario Reign-
98 - 2019-03-03938Milwaukee Admirals-Long Island Ducks-
100 - 2019-03-05956Long Island Ducks-Milwaukee Admirals-
103 - 2019-03-08979Butte Wolverines-Milwaukee Admirals-
104 - 2019-03-09997Carolina Panthers-Milwaukee Admirals-
Trade Deadline --- Trades can’t be done after this day is simulated!
105 - 2019-03-101003Milwaukee Admirals-Long Island Ducks-
107 - 2019-03-121027Austin Aces-Milwaukee Admirals-
109 - 2019-03-141039Milwaukee Admirals-Adirondack Angels-
110 - 2019-03-151053Milwaukee Admirals-Pensacola Ice Flyers-
111 - 2019-03-161065Milwaukee Admirals-Ontario Reign-
113 - 2019-03-181080Butte Wolverines-Milwaukee Admirals-
115 - 2019-03-201100Oakland Seals-Milwaukee Admirals-
117 - 2019-03-221113Milwaukee Admirals-Hartford Wolfpack-
118 - 2019-03-231126Milwaukee Admirals-Butte Wolverines-
119 - 2019-03-241142Pensacola Ice Flyers-Milwaukee Admirals-
122 - 2019-03-271161Oakland Seals-Milwaukee Admirals-
123 - 2019-03-281179Laval Rocket-Milwaukee Admirals-
126 - 2019-03-311201Milwaukee Admirals-Oakland Seals-
127 - 2019-04-011213Austin Aces-Milwaukee Admirals-
128 - 2019-04-021223Milwaukee Admirals-Oakland Seals-
129 - 2019-04-031229Milwaukee Admirals-Louisville Thunder-
132 - 2019-04-061255Oakville Wolves-Milwaukee Admirals-
133 - 2019-04-071263Milwaukee Admirals-Wilkes Barre-Scranton-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance00
Attendance PCT0.00%0.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
15 0 - 0.00% 0$0$3000100

Expenses
Players Total SalariesPlayers Total Average SalariesCoaches Salaries
2,105,250$ 2,102,750$ 0$
Year To Date ExpensesSalary Cap Per DaysSalary Cap To Date
1,829,161$ 15,711$ 1,280,643$

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 50 22,241$ 1,112,050$




OverallHomeVisitor
Year 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
201852142902034115140-25261111020205956326318000145684-2842115202317124536298138144644348135162045134913061141513.16%1552981.29%3819164549.79%900183649.02%39277050.91%12088251268380679337
Total Regular Season52142902034115140-25261111020205956326318000145684-2842115202317124536298138144644348135162045134913061141513.16%1552981.29%3819164549.79%900183649.02%39277050.91%12088251268380679337