Admirals

GP: 4 | W: 0 | L: 4 | OTL: 0 | P: 0
GF: 11 | GA: 17 | PP%: 5.88% | PK%: 66.67%
GM : Yves Cardinal | Morale : 75 | Team Overall : 62

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# 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
1Hendrix Lapierre (R)0X100.00633793727080856776716163686465075650
2Reese Johnson0X100.00796574627677786164605966586769075630
3Joakim Kemell (R)0X100.00683785646982856352605957616263075620
4Jacob Gaucher0X100.00703984578078855967565855576466075610
5Jaxon Nelson0X100.00803992578977675661555459536567075610
6Yegor Sidorov (R)0X100.00623791617193706063596157626361075610
7Lleyton Roed0X100.00613789587082715761595956586365075600
8Adam Erne (C)0X100.00716982588073725752565359557072075600
9Lucas Edmonds (R)0X100.00603792566967755559545753566466075590
10Parker Wotherspoon (A)0X100.00735483657686816330685871506870075650
11Tristan Luneau (R)0X100.00683888667885746530676064526163075640
12Robert Hagg (A)0X100.00914275618278815830605663527271075630
13Mac Hollowell (R)0X100.00633972646375826230675254476769075610
14Tyrel Bauer (R)0X100.00765661548564815330525156456365075580
Scratches
1Raphael Lavoie (R)0X100.00774273638987835964586257636667075630
2Patrick Giles (R)0X100.00804182579376845955565857596567075620
3Bradley Marek0X100.00774372558677745451535759566567075600
4Danny Katic0X100.00844761579365615558565460536567075600
5Gabriel Seger0X100.00793994558867705460535759546668075600
6Ben Steeves0X100.00613972596185725660585753556365075590
7Matthew Seminoff (R)0X100.00573889567068845557545358526264075580
8Denton Mateychuk (R)0X100.00613689716987736830696365586165075650
9Alex Kannok-Leipert69X100.00737765557263785230545356456567075580
10Joseph Arntsen0X100.00764371538566605230505554466264075570
TEAM AVERAGE100.0071458060787776585059575955656607561
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3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
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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
1Devon Levi (R)100.0081908673807981807981806471075680
2Cooper Black100.0073747098727173727173726471075650
Scratches
1Henrik Tikkanen100.0070807698696870696870696573075640
2Talyn Boyko100.0069716794686769686769686369075620
TEAM AVERAGE100.007379759172717372717372647107565
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Steve Potvin75677160777276CAN503750,000$


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 NamePOSGP 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
1Hendrix LapierreAdmirals (NSH)C4235-220212225179.09%111829.56011315000070045.71%17500000.8500000000
2Reese JohnsonAdmirals (NSH)RW4224-29518101761211.76%210726.78011214000010058.33%1200000.7500001000
3Jaxon NelsonAdmirals (NSH)C42132209451740.00%16015.0000001000010053.19%4700001.0000000000
4Yegor SidorovAdmirals (NSH)RW41232000412688.33%18621.6100013000000048.28%2900000.6900000000
5Tyrel BauerAdmirals (NSH)D4112211521370214.29%77017.730000400001000.00%000000.5600100000
6Adam ErneAdmirals (NSH)LW4202-21752360433.33%17719.30101112000000020.00%500000.5200001000
7Mac HollowellAdmirals (NSH)D4022340540120.00%47218.220000400000000.00%000000.5500000000
8Robert HaggAdmirals (NSH)D40221002379570.00%810025.0400031300005000.00%000000.4000000000
9Ben SteevesAdmirals (NSH)LW11011000231133.33%01717.6500000000000043.75%1600001.1300000000
10Denton MateychukAdmirals (NSH)D4011-800067470.00%49824.6700041200008000.00%000000.2000000000
11Lucas EdmondsAdmirals (NSH)RW4011-3003710350.00%08621.6800000000000048.98%4900000.2300000000
12Jacob GaucherAdmirals (NSH)C4011100635270.00%15413.6300001000050046.34%4100000.3700000000
13Tristan LuneauAdmirals (NSH)D4011200379560.00%1110626.6500051300005000.00%000000.1900000000
14Joakim KemellAdmirals (NSH)RW4000-420810176120.00%39122.77000615000010025.00%400000.0000000000
15Lleyton RoedAdmirals (NSH)LW4000-520518460.00%19423.62000015000000025.00%400000.0000000000
16Parker WotherspoonAdmirals (NSH)D4000-8001547660.00%89423.6700061200006000.00%000000.0000000000
Team Total or Average61111728-20491512087144551097.64%53133721.92123311390000430046.86%38200000.4200102000
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
1Devon LeviAdmirals (NSH)10001.0000.0011000110000.000004000
2Cooper BlackAdmirals (NSH)40220.9003.8226700171700000.000040000
Team Total or Average50220.9063.6727800171810000.000044000


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 Cap Salary Cap Remaining Exclude from Salary Cap Link
Adam Erne (1 Way Contract)LW301995-04-20No215 Lbs6 ft1NoNoNo2UFAPro & Farm2,337,000$2,337,000$166,929$NoLink / NHL Link
Alex Kannok-LeipertD252000-07-20No190 Lbs6 ft0NoNoNo1RFAPro & Farm755,000$0$0$NoLink / NHL Link
Ben SteevesLW232002-05-10No165 Lbs5 ft8NoNoNo1RFAPro & Farm760,000$0$0$NoLink / NHL Link
Bradley MarekLW242000-11-13No212 Lbs6 ft3NoNoNo2RFAPro & Farm999,999$0$0$NoLink / NHL Link
Cooper BlackG242001-06-14No223 Lbs6 ft8NoNoNo3RFAPro & Farm999,999$0$0$NoLink / NHL Link
Danny KaticLW252000-08-04No220 Lbs6 ft5NoNoNo2RFAPro & Farm999,999$0$0$NoLink / NHL Link
Denton MateychukD212004-07-12Yes185 Lbs5 ft11NoNoNo3RFAPro & Farm950,000$0$0$NoLink / NHL Link
Devon LeviG232001-12-27Yes192 Lbs6 ft0NoNoYes1RFAPro & Farm950,000$0$0$NoLink / NHL Link
Gabriel SegerC251999-11-15No209 Lbs6 ft4NoNoNo1RFAPro & Farm760,000$0$0$NoLink / NHL Link
Hendrix LapierreC232002-02-09Yes180 Lbs6 ft0NoNoNo1RFAPro & Farm950,000$0$0$NoLink / NHL Link
Henrik TikkanenG252000-09-28No222 Lbs6 ft8NoNoNo2RFAPro & Farm985,000$0$0$NoLink / NHL Link
Jacob GaucherC242001-03-09No185 Lbs6 ft3NoNoNo2RFAPro & Farm999,999$0$0$NoLink / NHL Link
Jaxon NelsonC252000-03-30No215 Lbs6 ft4NoNoNo1RFAPro & Farm760,000$0$0$NoLink / NHL Link
Joakim KemellRW212004-04-27Yes182 Lbs5 ft11NoNoNo1RFAPro & Farm950,000$0$0$NoLink / NHL Link
Joseph ArntsenD222003-05-22No210 Lbs6 ft3NoNoNo1RFAPro & Farm755,000$0$0$NoLink / NHL Link
Lleyton RoedLW232002-08-08No179 Lbs6 ft0NoNoNo1RFAPro & Farm760,000$0$0$NoLink / NHL Link
Lucas EdmondsRW242001-01-27Yes185 Lbs5 ft11NoNoNo1RFAPro & Farm950,000$0$0$NoLink / NHL Link
Mac HollowellD271998-09-26Yes170 Lbs5 ft9NoNoNo1RFAPro & Farm850,000$0$0$NoLink / NHL Link
Matthew SeminoffRW212003-12-27Yes188 Lbs5 ft11NoNoNo2RFAPro & Farm950,000$0$0$NoLink / NHL Link
Parker WotherspoonD281997-08-24No192 Lbs6 ft1NoNoYes3UFAPro & Farm1,502,000$0$0$NoLink / NHL Link
Patrick GilesRW252000-01-03Yes218 Lbs6 ft5NoNoNo2RFAPro & Farm837,900$0$0$NoLink / NHL Link
Raphael LavoieC252000-09-25Yes215 Lbs6 ft4NoNoNo1RFAPro & Farm775,000$0$0$NoLink / NHL Link
Reese JohnsonRW271998-07-10No193 Lbs6 ft1NoNoNo2RFAPro & Farm867,100$0$0$NoLink / NHL Link
Robert Hagg (1 Way Contract)D301995-02-08No210 Lbs6 ft2NoNoNo2UFAPro & Farm2,955,000$2,955,000$211,071$NoLink / NHL Link
Talyn BoykoG222002-10-16No206 Lbs6 ft6NoNoNo3RFAPro & Farm999,999$0$0$NoLink / NHL Link
Tristan LuneauD212004-01-12Yes202 Lbs6 ft1NoNoNo2RFAPro & Farm950,000$0$0$NoLink / NHL Link
Tyrel BauerD232002-03-23Yes206 Lbs6 ft3NoNoNo1RFAPro & Farm950,000$0$0$NoLink / NHL Link
Yegor SidorovRW212004-06-18Yes184 Lbs6 ft0NoNoNo3RFAPro & Farm950,000$0$0$NoLink / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2824.18198 Lbs6 ft21.711,043,178$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Adam ErneHendrix LapierreReese Johnson40122
2Lleyton RoedJoakim Kemell30122
3Jaxon NelsonYegor Sidorov20122
4Jacob GaucherLucas Edmonds10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Parker Wotherspoon40122
2Tristan LuneauRobert Hagg30122
3Mac HollowellTyrel Bauer20122
4Parker Wotherspoon10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Adam ErneHendrix LapierreReese Johnson60122
2Lleyton RoedJoakim Kemell40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Parker Wotherspoon60122
2Tristan LuneauRobert Hagg40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Hendrix Lapierre60122
2Reese JohnsonJoakim Kemell40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Parker Wotherspoon60122
2Tristan LuneauRobert Hagg40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Hendrix Lapierre60122Parker Wotherspoon60122
240122Tristan LuneauRobert Hagg40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Hendrix Lapierre60122
2Reese JohnsonJoakim Kemell40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Parker Wotherspoon60122
2Tristan LuneauRobert Hagg40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Adam ErneHendrix LapierreReese JohnsonParker Wotherspoon
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Adam ErneHendrix LapierreReese JohnsonParker Wotherspoon
Extra Forwards
Normal PowerPlayPenalty Kill
Yegor Sidorov, Jaxon Nelson, Jacob GaucherYegor Sidorov, Jaxon NelsonJacob Gaucher
Extra Defensemen
Normal PowerPlayPenalty Kill
Mac Hollowell, Tyrel Bauer, Tristan LuneauMac HollowellTyrel Bauer, Tristan Luneau
Penalty Shots
Hendrix Lapierre, , Reese Johnson, Joakim Kemell, Yegor Sidorov
Goalie
#1 : Cooper Black, #2 : Devon Levi
Custom OT Lines Forwards
Hendrix Lapierre, , Reese Johnson, Joakim Kemell, Yegor Sidorov, Jaxon Nelson, Jaxon Nelson, Jacob Gaucher, Adam Erne, Lleyton Roed,
Custom OT Lines Defensemen
Parker Wotherspoon, , Tristan Luneau, Robert Hagg, Mac Hollowell


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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

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
40L1111728145181535112100
All Games
GPWLOTWOTL SOWSOLGFGA
40400001117
Home Games
GPWLOTWOTL SOWSOLGFGA
202000058
Visitor Games
GPWLOTWOTL SOWSOLGFGA
202000069
Last 10 Games
WLOTWOTL SOWSOL
020200
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1715.88%9366.67%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
435336134430
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
8216150.93%7417442.53%306744.78%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
11885104315528


Last Played Games
Filter Tips
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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
1 - 2026-04-185Admirals3Comets4LXBoxScore
2 - 2026-04-1913Admirals3Comets5LBoxScore
3 - 2026-04-2021Comets4Admirals3LXBoxScore
4 - 2026-04-2129Comets4Admirals2LBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3020
Attendance4,0002,000
Attendance PCT100.00%100.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
8 3000 - 100.00% 100,000$200,000$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
0$ 2,391,700$ 2,391,700$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 0$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 1 0$ 0$




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
Regular Season
202482333306613283300-1741201500411143145-241131806202140155-15892835127954010390839266785195683339296384472321302415824.07%3096977.67%21399289448.34%1473308447.76%624135146.19%1915129919806061066528
2025823634023432862779411814022321431291441182000111143148-59028651580102108918111273294187689247276383664719552616926.44%2745480.29%21624291655.69%1575292853.79%740134954.86%2073145718475871045537
Total Regular Season164696708956569577-8823829026432862741282313806313283303-20179569102715964221118116420539917921832172586572616801370408550212725.30%58312378.90%43023581052.03%3048601250.70%1364270050.52%398827573827119421111066
Playoff
2024514000001624-821100000610-4303000001014-42162642007540131384051220957461239444.44%22768.18%08916753.29%10422446.43%459149.45%10772133386330
2025404000001117-62020000058-32020000069-301117280044301454353361318153511211715.88%9366.67%08216150.93%7417442.53%306744.78%11885104315528
Total Playoff918000002741-14413000001118-7505000001623-722743700011970276819387153901109724426519.23%311067.74%017132852.13%17839844.72%7515847.47%2261572386911859