Admirals

GP: 20 | W: 8 | L: 11 | OTL: 1 | P: 17
GF: 22 | GA: 16 | PP%: 7.69% | PK%: 84.11%
GM : Pat Blais | Morale : 50 | Team Overall : 59
Next Games vs Rampage
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
1Daniel WinnikXXX100.006152896977669458486658802580836650650
2Chris StewartXX100.007378857385578458346071588276786750640
3Joel WardX98.006943887381628258596159716378826450640
4Chris MuellerX100.007975876575737663796260665744446550610
5Jordan SzwarzX99.007143946872598060627055672548486450610
6Miikka SalomakiXX100.008545837770565562366056722558596350610
7Peter CehlarikX100.007775816775666762505862655945456450600
8Wade MeganX100.007571846871808659745856635344446350600
9Max GortzX100.007874876674748054505647644544445850580
10Felix GirardX100.006866726766808851644354585144445750560
11Dalton ProutX100.008785926985555749253940723864655450620
12Tommy CrossX100.007477687177818853254943614144445650610
13Anthony BitettoX100.007865767078625456254648642556575750600
14Andrew CampbellX100.007878786878758345253340623847475350590
15Cameron GaunceX100.007377656777748051254641613945455450590
16Jonathan Diaby (R)X100.007682626082545646254542614044445150550
Scratches
1Brett Pollock (R)XX100.007773876873666957505158645544446150580
2Tyler Moy (R)XX100.007971966271667150634747634544445650550
3Justin Kirkland (R)XX100.007568906468697550634747614544445550550
4Joel HanleyX100.007267825567748052254840613846465450570
5Andre BenoitX100.007369816569606449254240603844445250560
TEAM AVERAGE99.86756882677567755444525164445252595059
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 Mazanec100.00556480795356505852523046465550560
2Jeff Zatkoff100.00485164704653505454533044445150520
Scratches
1Anthony Peters100.00556784745258536054543044445650570
TEAM AVERAGE100.0053617674505651575353304545545055
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Dean Evason44465958574852CAN501800,000$


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
1Jordan SzwarzAdmirals (NAS)RW206612240438230026.09%237118.572027550000252054.05%3700000.6511000202
2Daniel WinnikAdmirals (NAS)C/LW/RW1318972074528003.57%228421.910003360112540050.36%27800000.6302000020
3Miikka SalomakiAdmirals (NAS)LW/RW20369-22403636290010.34%737418.712248580000421050.00%2800000.4801000102
4Joel WardAdmirals (NAS)RW20268-160182633006.06%538219.130447600000600052.54%5900000.4202000201
5Peter CehlarikAdmirals (NAS)LW2035821202226280010.71%334517.290003251012231158.33%1200000.4600000020
6Chris MuellerAdmirals (NAS)C2043711801636270014.81%235517.800226550000131064.09%29800000.3900000020
7Anthony BitettoAdmirals (NAS)D201564100301490011.11%1343321.69000558011173000.00%000000.2800000011
8Chris StewartAdmirals (NAS)LW/RW103362601911210014.29%120320.360005280001380157.89%1900000.5902000200
9Wade MeganAdmirals (NAS)C20336-180183932009.38%233016.530003190000180161.51%25200000.3600000110
10Dalton ProutAdmirals (NAS)D192350260331170028.57%2340121.12112649000069000.00%000000.2500000010
11Max GortzAdmirals (NAS)RW2032501201916170017.65%731815.94000180001280044.00%2500000.3100000101
12Cameron GaunceAdmirals (NAS)D20033424042108000.00%1843521.79000560000064000.00%000000.1400000001
13Tommy CrossAdmirals (NAS)D20033224039119000.00%1746023.02022665000082000.00%000000.1300000000
14Ben StreetPredatorsC4022-1400127000.00%18120.270002150001100061.02%5900000.4900000000
15Lauri KorpikoskiPredatorsLW/RW11122000050020.00%12121.5001103000011050.00%800001.8600000010
16Andrew CampbellAdmirals (NAS)D6101-3607430033.33%810818.121012600006010.00%000000.1800000001
17Clayton StonerPredatorsD1501101802992000.00%821814.54000016000021000.00%000000.0900000000
18Felix GirardAdmirals (NAS)C18101-240101213007.69%11427.93000050000131059.79%9700000.1400000100
19Jonathan DiabyAdmirals (NAS)D18011-126102842000.00%628916.1100015000041000.00%000000.0700002000
20Brett PollockAdmirals (NAS)LW/RW4011000262000.00%0348.6000000000000050.00%200000.5800000000
21Griffin ReinhartPredatorsD1000100211000.00%11616.670000100000000.00%000000.0000000000
22Joel HanleyAdmirals (NAS)D2000020000000.00%13216.240000000001000.00%000000.0000000000
Team Total or Average31134629616236103813673060011.11%129564418.15612187063512386907457.84%117400000.341800210109
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
1Marek MazanecAdmirals (NAS)1861110.8982.28105402403920010.8758182112
2Anthony PetersAdmirals (NAS)22000.9521.00120002420000.000020000
3Jeff ZatkoffAdmirals (NAS)20001.0000.003200070000.0000018000
Team Total or Average2281110.9052.09120602424410010.87582020112


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 CONT 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
Andre BenoitAdmirals (NAS)D341984-01-06No191 Lbs5 ft11NoNoNo3UFAPro & Farm500,000$500,000$500,000$Link
Andrew CampbellAdmirals (NAS)D301988-02-03No205 Lbs6 ft4NoNoNo3UFAPro & Farm500,000$500,000$500,000$Link
Anthony BitettoAdmirals (NAS)D281990-07-14No210 Lbs6 ft1NoNoNo1UFAPro & Farm650,000$Link
Anthony PetersAdmirals (NAS)D271990-12-31No196 Lbs6 ft1NoNoNo3RFAPro & Farm500,000$500,000$500,000$Link
Brett PollockAdmirals (NAS)LW/RW221996-03-17Yes195 Lbs6 ft3NoNoNo3ELCPro & Farm850,000$850,000$850,000$Link
Cameron GaunceAdmirals (NAS)D281990-03-19No210 Lbs6 ft1NoNoNo1UFAPro & Farm575,000$Link
Chris MuellerAdmirals (NAS)C321986-03-06No209 Lbs5 ft11NoNoNo1UFAPro & Farm650,000$Link
Chris StewartAdmirals (NAS)LW/RW311987-10-30No239 Lbs6 ft2NoNoNo2UFAPro & Farm1,500,000$1,500,000$Link
Dalton ProutAdmirals (NAS)D281990-03-13No230 Lbs6 ft3NoNoNo2UFAPro & Farm650,000$650,000$Link
Daniel WinnikAdmirals (NAS)C/LW/RW331985-03-06No206 Lbs6 ft2NoNoNo1UFAPro & Farm2,150,000$Link
Felix GirardAdmirals (NAS)C241994-05-09No197 Lbs5 ft10NoNoNo3ELCPro & Farm850,000$850,000$850,000$Link
Jeff ZatkoffAdmirals (NAS)LW311987-06-09No179 Lbs6 ft2NoNoNo1UFAPro & Farm650,000$Link
Joel HanleyAdmirals (NAS)D271991-06-08No193 Lbs6 ft0NoNoNo1RFAPro & Farm550,000$Link
Joel WardAdmirals (NAS)RW371980-12-02No225 Lbs6 ft1NoNoNo1UFAPro & Farm650,000$Link
Jonathan DiabyAdmirals (NAS)D231994-11-16Yes218 Lbs6 ft5NoNoNo3ELCPro & Farm650,000$650,000$650,000$Link
Jordan SzwarzAdmirals (NAS)RW271991-05-14No200 Lbs5 ft11NoNoNo1RFAPro & Farm850,000$Link
Justin KirklandAdmirals (NAS)C/LW221996-08-01Yes183 Lbs6 ft1NoNoNo2ELCPro & Farm750,000$750,000$Link
Marek MazanecAdmirals (NAS)LW/RW271991-07-17No187 Lbs6 ft4NoNoNo2RFAPro & Farm550,000$550,000$Link
Max GortzAdmirals (NAS)RW251993-01-28No196 Lbs6 ft3NoNoNo1ELCPro & Farm500,000$Link
Miikka SalomakiAdmirals (NAS)LW/RW251993-03-08No203 Lbs5 ft11NoNoNo3ELCPro & Farm850,000$850,000$850,000$Link
Peter CehlarikAdmirals (NAS)LW231995-05-12No202 Lbs6 ft2NoNoNo2ELCPro & Farm700,000$700,000$Link
Tommy CrossAdmirals (NAS)D291989-09-11No205 Lbs6 ft3NoNoNo1UFAPro & Farm550,000$Link
Tyler MoyAdmirals (NAS)C/RW231995-07-18Yes201 Lbs6 ft1NoNoNo3ELCPro & Farm500,000$500,000$500,000$Link
Wade MeganAdmirals (NAS)C281990-07-21No192 Lbs6 ft1NoNoNo1UFAPro & Farm850,000$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2427.67203 Lbs6 ft11.88748,958$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Chris StewartDaniel WinnikJoel Ward40122
2Miikka SalomakiChris MuellerJordan Szwarz30122
3Peter CehlarikWade MeganMax Gortz20122
4Daniel WinnikFelix GirardJoel Ward10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Dalton ProutTommy Cross40122
2Anthony BitettoCameron Gaunce30122
3Andrew CampbellJonathan Diaby20122
4Dalton ProutTommy Cross10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Chris StewartDaniel WinnikJoel Ward60122
2Miikka SalomakiChris MuellerJordan Szwarz40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Dalton ProutTommy Cross60122
2Anthony BitettoCameron Gaunce40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Daniel WinnikJoel Ward60122
2Chris StewartChris Mueller40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Dalton ProutTommy Cross60122
2Anthony BitettoCameron Gaunce40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Daniel Winnik60122Dalton ProutTommy Cross60122
2Joel Ward40122Anthony BitettoCameron Gaunce40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Daniel WinnikJoel Ward60122
2Chris StewartChris Mueller40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Dalton ProutTommy Cross60122
2Anthony BitettoCameron Gaunce40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Chris StewartDaniel WinnikJoel WardDalton ProutTommy Cross
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Chris StewartDaniel WinnikJoel WardDalton ProutTommy Cross
Extra Forwards
Normal PowerPlayPenalty Kill
Peter Cehlarik, Wade Megan, Max GortzPeter Cehlarik, Wade MeganMax Gortz
Extra Defensemen
Normal PowerPlayPenalty Kill
Andrew Campbell, Jonathan Diaby, Anthony BitettoAndrew CampbellJonathan Diaby, Anthony Bitetto
Penalty Shots
Daniel Winnik, Joel Ward, Chris Stewart, Chris Mueller, Miikka Salomaki
Goalie
#1 : Marek Mazanec, #2 : Jeff Zatkoff


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
1Americans11000000211110000002110000000000021.000246001799115126909592361224300.00%50100.00%129049558.59%29953655.78%14425756.03%480332486143242121
2Comets1010000014-31010000014-30000000000000.000123001799116126909592154227114.29%2150.00%029049558.59%29953655.78%14425756.03%480332486143242121
3Condors1010000012-1000000000001010000012-100.00012300179911512690959231016205120.00%7271.43%029049558.59%29953655.78%14425756.03%480332486143242121
4Crunch2020000047-3000000000002020000047-300.0004711001799129126909594382330500.00%80100.00%029049558.59%29953655.78%14425756.03%480332486143242121
5Griffins2010001034-1100000103211010000002-220.50034700179913912690959491226381100.00%13284.62%029049558.59%29953655.78%14425756.03%480332486143242121
6Heat21100000330211000003300000000000020.5003580017991291269095939131635700.00%7271.43%029049558.59%29953655.78%14425756.03%480332486143242121
7IceCaps11000000202000000000001100000020221.000235011799118126909591768156116.67%30100.00%029049558.59%29953655.78%14425756.03%480332486143242121
8Icehogs1010000013-2000000000001010000013-200.00012310179919126909592488203133.33%4175.00%029049558.59%29953655.78%14425756.03%480332486143242121
9Phantoms11000000321000000000001100000032121.0003690017991151269095928612175120.00%50100.00%029049558.59%29953655.78%14425756.03%480332486143242121
10Rampage11000000514110000005140000000000021.0005914001799121126909591974145120.00%20100.00%029049558.59%29953655.78%14425756.03%480332486143242121
Since Last GM Reset20711000113644-8105300011221661028000001428-14170.42536641001217991312126909594421322403947867.69%1071784.11%129049558.59%29953655.78%14425756.03%480332486143242121
Total20711000113644-8105300011221661028000001428-14170.42536641001217991312126909594421322403947867.69%1071784.11%129049558.59%29953655.78%14425756.03%480332486143242121
Vs Conference1668000112833-5952000112114771600000719-12150.4692849771217991253126909593461151913236657.58%871681.61%129049558.59%29953655.78%14425756.03%480332486143242121
Vs Division62500011817-93200001147-330500000410-670.583815230017991881269095912843701282827.14%33972.73%029049558.59%29953655.78%14425756.03%480332486143242121
15Wild11000000211110000002110000000000021.00023500179911312690959145189300.00%9188.89%029049558.59%29953655.78%14425756.03%480332486143242121
16Wolf Pack1010000012-11010000012-10000000000000.000123001799115126909592531424200.00%7185.71%029049558.59%29953655.78%14425756.03%480332486143242121
17Wolves3110000156-1210000015231010000004-430.50059140117991501269095972284575700.00%18383.33%029049558.59%29953655.78%14425756.03%480332486143242121
18Wolves2020000038-5000000000002020000038-500.0003690017991281269095945153451900.00%17476.47%029049558.59%29953655.78%14425756.03%480332486143242121

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
2017SOL1366410031244213224039412
All Games
GPWLOTWOTL SOWSOLGFGA
2071100113644
Home Games
GPWLOTWOTL SOWSOLGFGA
105300112216
Visitor Games
GPWLOTWOTL SOWSOLGFGA
102800001428
Last 10 Games
WLOTWOTL SOWSOL
450001
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
7867.69%1071784.11%1
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
1269095917991
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
29049558.59%29953655.78%14425756.03%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
480332486143242121


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
3 - 2018-10-0415Rampage1Admirals5WBoxScore
5 - 2018-10-0635Heat1Admirals2WBoxScore
7 - 2018-10-0847Admirals1Icehogs3LBoxScore
9 - 2018-10-1064Admirals0Griffins2LBoxScore
11 - 2018-10-1277Griffins2Admirals3WXXBoxScore
12 - 2018-10-1382Admirals0Wolves3LBoxScore
15 - 2018-10-16107Wolves0Admirals4WBoxScore
17 - 2018-10-18121Admirals0Wolves4LBoxScore
19 - 2018-10-20133Admirals1Condors2LBoxScore
20 - 2018-10-21148Comets4Admirals1LBoxScore
23 - 2018-10-24166Admirals3Crunch4LBoxScore
25 - 2018-10-26179Heat2Admirals1LBoxScore
27 - 2018-10-28194Admirals2IceCaps0WBoxScore
29 - 2018-10-30205Wild1Admirals2WBoxScore
31 - 2018-11-01217Admirals3Wolves5LBoxScore
33 - 2018-11-03235Americans1Admirals2WBoxScore
36 - 2018-11-06259Wolf Pack2Admirals1LBoxScore
38 - 2018-11-08272Admirals3Phantoms2WBoxScore
41 - 2018-11-11291Admirals1Crunch3LBoxScore
43 - 2018-11-13303Wolves2Admirals1LXXBoxScore
46 - 2018-11-16325IceCaps-Admirals-
48 - 2018-11-18345Condors-Admirals-
50 - 2018-11-20359Admirals-IceCaps-
52 - 2018-11-22372Admirals-Wolves-
54 - 2018-11-24385Wolves-Admirals-
56 - 2018-11-26399Admirals-Heat-
58 - 2018-11-28414Americans-Admirals-
60 - 2018-11-30430Admirals-Americans-
62 - 2018-12-02441Admirals-Griffins-
63 - 2018-12-03455Marlies-Admirals-
65 - 2018-12-05469Admirals-Bears-
68 - 2018-12-08485Wild-Admirals-
72 - 2018-12-12512Falcons-Admirals-
74 - 2018-12-14528Admirals-Rampage-
76 - 2018-12-16539Moose-Admirals-
78 - 2018-12-18558Admirals-Wolves-
80 - 2018-12-20570Admirals-Condors-
82 - 2018-12-22580Heat-Admirals-
86 - 2018-12-26604Barracuda-Admirals-
88 - 2018-12-28624Admirals-Pirates-
89 - 2018-12-29634Devils-Admirals-
93 - 2019-01-02656Admirals-Bruins-
94 - 2019-01-03667Moose-Admirals-
96 - 2019-01-05686Admirals-Reign-
98 - 2019-01-07697Checkers-Admirals-
100 - 2019-01-09717Comets-Admirals-
103 - 2019-01-12736Admirals-Wild-
105 - 2019-01-14749Admirals-Rampage-
106 - 2019-01-15759Stars-Admirals-
109 - 2019-01-18780Griffins-Admirals-
110 - 2019-01-19790Admirals-Pirates-
112 - 2019-01-21809Griffins-Admirals-
115 - 2019-01-24825Admirals-Falcons-
117 - 2019-01-26835Admirals-Comets-
119 - 2019-01-28852Admirals-Wolves-
120 - 2019-01-29859Rampage-Admirals-
123 - 2019-02-01880Stars-Admirals-
124 - 2019-02-02893Admirals-Senators-
126 - 2019-02-04906Admirals-Marlies-
127 - 2019-02-05919Monsters-Admirals-
129 - 2019-02-07938Admirals-Sound Tigers-
132 - 2019-02-10950Checkers-Admirals-
134 - 2019-02-12965Admirals-Stars-
137 - 2019-02-15978Icehogs-Admirals-
139 - 2019-02-17996Admirals-Stars-
141 - 2019-02-191006Admirals-Icehogs-
142 - 2019-02-201018Sound Tigers-Admirals-
Trade Deadline --- Trades can’t be done after this day is simulated!
145 - 2019-02-231035Admirals-Icehogs-
147 - 2019-02-251048Icehogs-Admirals-
149 - 2019-02-271066Admirals-Penguins-
151 - 2019-03-011073Admirals-Checkers-
152 - 2019-03-021085Marlies-Admirals-
157 - 2019-03-071110Admirals-Gulls-
158 - 2019-03-081117Pirates-Admirals-
161 - 2019-03-111141Rampage-Admirals-
167 - 2019-03-171170Wolves-Admirals-



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
28 0 - 0.00% 0$0$3000100

Expenses
Players Total SalariesPlayers Total Average SalariesCoaches Salaries
1,797,500$ 1,782,500$ 0$
Year To Date ExpensesSalary Cap Per DaysSalary Cap To Date
690,640$ 0$ 482,371$

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 125 15,370$ 1,921,250$




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
201820711000113644-8105300011221661028000001428-141736641001217991312126909594421322403947867.69%1071784.11%129049558.59%29953655.78%14425756.03%480332486143242121
Total Regular Season20711000113644-8105300011221661028000001428-141736641001217991312126909594421322403947867.69%1071784.11%129049558.59%29953655.78%14425756.03%480332486143242121