Islanders

GP: 33 | W: 16 | L: 13 | OTL: 4 | P: 36
GF: 67 | GA: 74 | PP%: 16.44% | PK%: 90.22%
GM : Pascal Labarre | Morale : 50 | Team Overall : 62
Next Games #538 vs Phantoms

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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
1Ross Johnston0X100.008285596596728162536160635872743450640
2Jonah Gadjovich0XX100.008377566586717562586061635967686050630
3Brian Halonen0X100.006739796376867861565963586266684250620
4Josh Dunne0X100.007842745889797759645756555867693750610
5Cedric Pare0X100.007553745984798258655958575666684750610
6Ty Mueller0X100.006136886069807259696058635962646550610
7Austin Wagner0X100.006740796376817158575556615968705150600
8Avery Hayes0XXX100.005639776365867659605862576163654650600
9Lleyton Roed0X100.006137895870827157615959565863654450590
10Dino Kambeitz0X100.007441795783708056535258595665674250590
11Anthony Romano0X100.005936955669686955605453525665674850560
12Jaxsen Wiebe0XX100.007040755679676654515355525463654350560
13Joel Hanley0X100.007043836770877763306856655174752350660
14Robert Hagg0X100.009142756182788158306056635272715950660
15Nils Lundkvist0X100.006635897276847869307454635265677750660
16Corey Schueneman0X100.006137895972818458305756604970723550620
17Aaron Ness0X100.005838855567638254305653544575803950590
18Connor Corcoran0X100.006838915577746853305452564565674750590
19Alex Kannok-Leipert0X100.007377655572637852305453564565674750590
Scratches
TEAM AVERAGE100.00694679607776765848585759546769475061
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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
# Goalie Name CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Georgi Romanov99.00758278917473757473757466755550740
2Dustin Tokarski100.00748175747372747372747376904250730
Scratches
TEAM AVERAGE99.5075827783747375747375747183495074
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Marc Savard66687267706579CAN4741,000,000$


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
1Ty MuellerIslanders (NYI)C3371219620125262155611.29%861618.672791910501131782056.39%50900000.6214000131
2Nils LundkvistIslanders (NYI)D3321618-92604345479304.26%3481324.64246351260114195000.00%000000.4400000102
3Josh DunneIslanders (NYI)C337916-2395584669204810.14%770221.283141612800051452159.85%54800000.4600001600
4Joel HanleyIslanders (NYI)D283912-852054293518228.57%2460721.7136929910000121200.00%000000.3900000001
5Cedric PareIslanders (NYI)C3310212-54810463653183718.87%462819.03325107910111300157.89%5700000.3813101211
6Corey SchuenemanIslanders (NYI)D332911-436052334115224.88%3475222.81268271040000168100.00%000000.2900000112
7Florian XhekajNew York IslandersLW/RW31281022551812259368.00%52347.570441280110150050.00%1800000.8513010000
8Austin WagnerIslanders (NYI)LW23639-440142956123910.71%241418.01000140000331048.57%3500000.4300000020
9Andrew AgozzinoNew York IslandersC174593204244123319.76%321412.61213948000021045.00%2000000.8401000102
10Ross JohnstonIslanders (NYI)LW22369-147554264611386.52%541118.7122410681015440164.80%19600000.4400001121
11Brian HalonenIslanders (NYI)LW23178-512021204514282.22%234314.93156753000080044.09%12700000.4700000100
12Alex Kannok-LeipertIslanders (NYI)D332570535679229169.09%3457617.4612311104000183000.00%000000.2400100000
13Robert HaggIslanders (NYI)D331676315321073414.29%172507.5900001011149000.00%000000.5600100001
14Aaron NessIslanders (NYI)D33246-45203715175811.76%2056717.20112642000068000.00%000000.2100000010
15Dino KambeitzIslanders (NYI)RW33156-928041355914401.69%361018.490221010300021071054.74%13700000.2000000000
16Jonah GadjovichIslanders (NYI)LW/RW2324632604130306246.67%424310.570003210000121054.50%21100000.4900000000
17Avery HayesIslanders (NYI)C/LW/RW27224-71957373613285.56%137113.7400008000041047.66%25600000.2212001001
18Lleyton RoedIslanders (NYI)LW33224-13407143410195.88%334710.5400000000031049.42%25700000.2300000000
19Connor CorcoranIslanders (NYI)D29022-32403658260.00%2941914.4600008000197000.00%000000.1000000000
20Anthony RomanoIslanders (NYI)C20000-200102010.00%0462.30000040001250045.16%3100000.0000000000
21Jaxsen WiebeIslanders (NYI)LW/RW33000-100310000.00%070.22000000000000100.00%100000.0000000000
Team Total or Average60659116175-57530406485087352265338.03%239917715.14224365194113424624149713354.93%240300000.38413314141012
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
1Georgi RomanovIslanders (NYI)199720.9132.18107320394490000.85771815031
2Dustin TokarskiIslanders (NYI)177620.9122.1993261343880200.85771518120
Team Total or Average36161340.9132.18200681738370200.857143333151


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
Aaron NessD351990-05-18No184 Lbs5 ft10NoNoNo2UFAPro & Farm300,000$0$0$NoLink / NHL Link
Alex Kannok-LeipertD252000-07-20No190 Lbs6 ft0NoNoNo1RFAPro & Farm300,000$0$0$NoLink / NHL Link
Anthony RomanoC252000-10-07No182 Lbs5 ft11NoNoNo1RFAPro & Farm0$0$NoLink
Austin WagnerLW281997-06-23No195 Lbs6 ft1NoNoNo2UFAPro & Farm300,000$0$0$NoLink
Avery HayesC/LW/RW232002-10-10No175 Lbs5 ft10NoNoNo1RFAPro & Farm300,000$0$0$NoLink / NHL Link
Brian HalonenLW271999-01-11No207 Lbs6 ft0NoNoNo4UFAPro & Farm300,000$0$0$NoLink / NHL Link
Cedric PareC261999-01-24No205 Lbs6 ft3NoNoNo1RFAPro & Farm300,000$0$0$NoLink / NHL Link
Connor CorcoranD252000-08-07No185 Lbs6 ft2NoNoNo4RFAPro & Farm300,000$0$0$NoLink
Corey SchuenemanD301995-09-02No197 Lbs5 ft11NoNoNo3UFAPro & Farm500,000$0$0$NoLink / NHL Link
Dino KambeitzRW252000-01-25No212 Lbs6 ft2NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Dustin TokarskiG361989-09-16No198 Lbs6 ft0NoNoNo1UFAPro & Farm1,000,000$0$0$NoLink / NHL Link
Georgi RomanovG261999-12-15No207 Lbs6 ft5NoNoNo1RFAPro & Farm500,000$0$0$NoLink / NHL Link
Jaxsen WiebeLW/RW232002-05-16No209 Lbs6 ft1NoNoNo1RFAPro & Farm300,000$0$0$NoLink / NHL Link
Joel HanleyD341991-06-08No186 Lbs5 ft11NoNoNo2UFAPro & Farm500,000$0$0$NoLink / NHL Link
Jonah GadjovichLW/RW271998-10-12No211 Lbs6 ft3NoNoNo1UFAPro & Farm300,000$0$0$NoLink / NHL Link
Josh DunneC271998-12-08No211 Lbs6 ft4NoNoNo1UFAPro & Farm300,000$0$0$NoLink / NHL Link
Lleyton RoedLW232002-08-08No179 Lbs6 ft0NoNoNo2RFAPro & Farm300,000$0$0$NoLink
Nils LundkvistD252000-07-27No191 Lbs6 ft1NoNoNo1RFAPro & Farm500,000$0$0$NoLink / NHL Link
Robert HaggD301995-02-08No210 Lbs6 ft2NoNoNo2UFAPro & Farm1,000,000$0$0$NoLink / NHL Link
Ross JohnstonLW311994-02-18No232 Lbs6 ft5NoNoNo1UFAPro & Farm500,000$0$0$NoLink / NHL Link
Ty MuellerC222003-02-26No185 Lbs5 ft11NoNoNo4ELCPro & Farm300,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2127.29198 Lbs6 ft11.81400,000$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Austin WagnerJonah GadjovichRoss Johnston40122
2Cedric PareLleyton RoedDino Kambeitz30122
3Brian HalonenJosh DunneTy Mueller20122
4Ross JohnstonJosh DunneLleyton Roed10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Nils LundkvistConnor Corcoran40122
2Corey SchuenemanAaron Ness30122
3Alex Kannok-LeipertRobert Hagg20122
4Nils LundkvistCorey Schueneman10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Josh DunneTy MuellerCedric Pare60122
2Jonah GadjovichRoss JohnstonDino Kambeitz40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Nils LundkvistAaron Ness60122
2Corey SchuenemanAlex Kannok-Leipert40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Ty MuellerCedric Pare60122
2Dino KambeitzJosh Dunne40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Nils LundkvistRobert Hagg60122
2Alex Kannok-LeipertCorey Schueneman40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Josh Dunne60122Aaron NessNils Lundkvist60122
2Ty Mueller40122Alex Kannok-LeipertCorey Schueneman40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Josh DunneRoss Johnston60122
2Ty MuellerCedric Pare40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Corey SchuenemanAlex Kannok-Leipert60122
2Aaron NessNils Lundkvist40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Jonah GadjovichRoss JohnstonCedric PareNils LundkvistRobert Hagg
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Jonah GadjovichRoss JohnstonCedric PareNils LundkvistRobert Hagg
Extra Forwards
Normal PowerPlayPenalty Kill
Ty Mueller, Cedric Pare, Josh DunneJosh Dunne, Cedric PareJosh Dunne
Extra Defensemen
Normal PowerPlayPenalty Kill
Corey Schueneman, Aaron Ness, Nils LundkvistNils LundkvistCorey Schueneman, Nils Lundkvist
Penalty Shots
Ty Mueller, Dino Kambeitz, Cedric Pare, Ross Johnston, Josh Dunne
Goalie
#1 : Georgi Romanov, #2 : Dustin Tokarski


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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
3336L26712118878083724454265601
All Games
GPWLOTWOTL SOWSOLGFGA
33111323316774
Home Games
GPWLOTWOTL SOWSOLGFGA
163713202735
Visitor Games
GPWLOTWOTL SOWSOLGFGA
178610114039
Last 10 Games
WLOTWOTL SOWSOL
440110
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1462416.44%2252290.22%2
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
229298241252024186
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
56998557.77%582108453.69%23343953.08%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
827571782238399203


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
9 - 2025-08-2311Bruins2Islanders1LXBoxScore
10 - 2025-08-2423Checkers1Islanders4WBoxScore
13 - 2025-08-2730Bears2Islanders1LBoxScore
16 - 2025-08-3045Islanders3Wolfpack4LXXBoxScore
17 - 2025-08-3158Wolfpack3Islanders4WXXBoxScore
22 - 2025-09-0571Islanders2Checkers1WBoxScore
23 - 2025-09-0684Islanders2Checkers0WBoxScore
27 - 2025-09-10105Penguins2Islanders0LBoxScore
29 - 2025-09-12116Islanders3Thunderbirds2WBoxScore
34 - 2025-09-17141Islanders3Thunderbirds2WXBoxScore
36 - 2025-09-19151Islanders3Bruins2WBoxScore
37 - 2025-09-20158Bruins3Islanders2LBoxScore
40 - 2025-09-23181Bears4Islanders0LBoxScore
43 - 2025-09-26191Islanders1Bears3LBoxScore
44 - 2025-09-27204Islanders0Penguins1LBoxScore
50 - 2025-10-03233Islanders2Penguins4LBoxScore
51 - 2025-10-04246Checkers2Islanders3WXBoxScore
52 - 2025-10-05255Islanders3Wolfpack2WXXBoxScore
58 - 2025-10-11283Senators2Islanders1LXBoxScore
59 - 2025-10-12293Senators1Islanders3WBoxScore
62 - 2025-10-15301Wolfpack3Islanders0LBoxScore
64 - 2025-10-17314Islanders2Thunderbirds1WBoxScore
65 - 2025-10-18324Islanders1Bruins5LBoxScore
69 - 2025-10-22344Bruins2Islanders3WXXBoxScore
71 - 2025-10-24355Islanders3Bruins1WBoxScore
73 - 2025-10-26375Rocket2Islanders0LBoxScore
79 - 2025-11-01410Islanders4Checkers1WBoxScore
80 - 2025-11-02425Islanders7Checkers1WBoxScore
85 - 2025-11-07429Bruins2Islanders3WBoxScore
86 - 2025-11-08447Islanders1Thunderbirds6LBoxScore
93 - 2025-11-15482Americans2Islanders1LXBoxScore
94 - 2025-11-16493Wolfpack2Islanders1LBoxScore
99 - 2025-11-21514Islanders0Bruins3LBoxScore
101 - 2025-11-23538Phantoms-Islanders-
104 - 2025-11-26546Thunderbirds-Islanders-
106 - 2025-11-28558Crunch-Islanders-
107 - 2025-11-29567Thunderbirds-Islanders-
109 - 2025-12-01589Islanders-Thunderbirds-
111 - 2025-12-03594Islanders-Comets-
113 - 2025-12-05603Islanders-Crunch-
114 - 2025-12-06620Islanders-Phantoms-
118 - 2025-12-10635Phantoms-Islanders-
120 - 2025-12-12646Islanders-Bears-
121 - 2025-12-13664Islanders-Bears-
127 - 2025-12-19681Islanders-Penguins-
128 - 2025-12-20694Checkers-Islanders-
132 - 2025-12-24713Islanders-Wolfpack-
135 - 2025-12-27731Bruins-Islanders-
136 - 2025-12-28744Islanders-Bruins-
142 - 2026-01-03779Comets-Islanders-
143 - 2026-01-04794Thunderbirds-Islanders-
146 - 2026-01-07806Bruins-Islanders-
148 - 2026-01-09819Islanders-Phantoms-
149 - 2026-01-10833Islanders-Phantoms-
153 - 2026-01-14849Islanders-Wolfpack-
Trade Deadline --- Trades can’t be done after this day is simulated!
156 - 2026-01-17875Marlies-Islanders-
157 - 2026-01-18884Thunderbirds-Islanders-
160 - 2026-01-21894Islanders-Rocket-
162 - 2026-01-23904Islanders-Senators-
163 - 2026-01-24914Islanders-Senators-
170 - 2026-01-31960Thunderbirds-Islanders-
171 - 2026-02-01972Penguins-Islanders-
174 - 2026-02-04982Bears-Islanders-
176 - 2026-02-06996Islanders-Americans-
178 - 2026-02-081020Islanders-Marlies-
181 - 2026-02-111028Phantoms-Islanders-
184 - 2026-02-141052Checkers-Islanders-
188 - 2026-02-181072Wolfpack-Islanders-
191 - 2026-02-211094Wolfpack-Islanders-
192 - 2026-02-221107Penguins-Islanders-
197 - 2026-02-271124Islanders-Wolfpack-
198 - 2026-02-281144Islanders-Bruins-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance30,09815,184
Attendance PCT94.06%94.90%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
20 2830 - 94.34% 70,465$1,127,447$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
543,845$ 84,000$ 84,000$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 43,845$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
1,409,309$ 100 5,420$ 542,000$




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
12824424053422651561094121130232013178534123110302213478561112654787433801088068222706977877191821510136218474285913.79%5997387.81%71521247861.38%1387242957.10%686110262.25%225516091734570979518
137640290321123915881382014031001217249382015001111188632912394296681120987859201206976526521685482106415234196615.75%4406485.45%61344231857.98%1228227154.07%600106256.50%200614261658534917477
147634240541817113239382011021138763243814130330584691592171314485113053674518050580618577171848762411023766316.76%2382091.60%41271224256.69%1152220152.34%573103455.42%195913861728535947498
147634240541817113239382011021138763243814130330584691592171314485113053674518050580618577171848762411023766316.76%2382091.60%41271224256.69%1152220152.34%573103455.42%195913861728535947498
147634240541817113239382011021138763243814130330584691592171314485113053674518050580618577171848762411023766316.76%2382091.60%41271224256.69%1152220152.34%573103455.42%195913861728535947498
1582502104115247160874127901013121744741231203102126864011624745470101401047464237307917787811915558106915434316414.85%4365886.70%31648266061.95%1446247758.38%683114459.70%220515851770573985517
1582502104115247160874127901013121744741231203102126864011624745470101401047464237307917787811915558106915434316414.85%4365886.70%31648266061.95%1446247758.38%683114459.70%220515851770573985517
168244240343426817791412212012041439548412212022301258243108268478746260939376233507187738151830503106614774838417.39%4246484.91%21605261661.35%1370235658.15%767121862.97%222016011775554973516
177242220131325215399362111002111338350362111011021197049942524787300100101836620130714640645163945197614533739024.13%4136284.99%21317214561.40%1239212858.22%665106462.50%201914631474479855465
18723922035302131427136211000320110684236181203210103742995213381594010080725518220595640572166346799713413666016.39%4225287.68%91143207855.00%1142218552.27%51995454.40%195114031543488851458
19703425043132101684236151601202988513341990311111283298421037158123062875619270625645638157550194112613996315.79%3885386.34%41272223956.81%1145206255.53%607101559.80%182412891560496849442
20331113023316774-71637013202735-8178601011403913667121188012024186780229298241258372445426561462416.44%2252290.22%256998557.77%582108453.69%23343953.08%827571782238399203
Total Regular Season87945627304437214825211744777440237134016191222126685341343921913902818926125589136411272521458671071111720933860649232772297666778873592003457351095815950460476316.57%449756687.41%50158802690559.02%144412607255.39%71621224458.49%2339416694192566114106385612
Playoff
1512750000030255633000001616064200000149514305888000910927408084913178320622563914.29%821186.59%115732548.31%20542648.12%9116854.17%2891973219615475
1715870000035287734000001313085300000221571635639802012129333011899106354127232273711622.54%961584.38%019340148.13%25351848.84%10921750.23%34923838411718891
18169700000332767610000019811936000001419-51833639612011912349011910011635488205286871314.94%86693.02%124647951.36%24449649.19%10221946.58%396270395125205103
Total Playoff43241900000988018201280000048371123121100000504374898184282140323130956031728331310252986437842213817.19%2643287.88%2596120549.46%702144048.75%30260450.00%10367051101339548270