NY Rangers
GP: 34 | W: 17 | L: 15 | OTL: 2 | P: 36
GF: 88 | GA: 88 | PP%: 18.37% | PK%: 83.70%
GM : Pierre | Morale : 50 | Team Overall : 75
Next Games #572 vs Tampa Bay
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Game Center
Carolina
15-15-5, 35pts
1
FINAL
4 NY Rangers
17-15-2, 36pts
Team Stats
SOL1StreakL1
9-5-3Home Record11-5-1
6-10-2Away Record6-10-1
3-4-3Last 10 Games4-5-1
2.60Goals Per Game2.59
2.63Goals Against Per Game2.59
12.68%Power Play Percentage18.37%
83.72%Penalty Kill Percentage83.70%
NY Rangers
17-15-2, 36pts
3
FINAL
4 New Jersey
23-9-5, 51pts
Team Stats
L1StreakW4
11-5-1Home Record11-5-4
6-10-1Away Record12-4-1
4-5-1Last 10 Games7-2-1
2.59Goals Per Game3.24
2.59Goals Against Per Game2.62
18.37%Power Play Percentage26.36%
83.70%Penalty Kill Percentage84.26%
NY Rangers
17-15-2, 36pts
Day 55
Tampa Bay
19-11-3, 41pts
Team Stats
L1StreakOTW1
11-5-1Home Record11-4-2
6-10-1Away Record8-7-1
4-5-1Last 10 Games7-3-0
2.59Goals Per Game3.15
2.59Goals Against Per Game3.15
18.37%Power Play Percentage19.51%
83.70%Penalty Kill Percentage82.20%
NY Rangers
17-15-2, 36pts
Day 56
Florida
28-7-1, 57pts
Team Stats
L1StreakOTL1
11-5-1Home Record13-3-1
6-10-1Away Record15-4-0
4-5-1Last 10 Games8-1-1
2.59Goals Per Game3.69
2.59Goals Against Per Game3.69
18.37%Power Play Percentage21.71%
83.70%Penalty Kill Percentage83.45%
Boston
19-16-1, 39pts
Day 58
NY Rangers
17-15-2, 36pts
Team Stats
W2StreakL1
11-7-1Home Record11-5-1
8-9-0Away Record6-10-1
6-4-0Last 10 Games4-5-1
2.67Goals Per Game2.59
2.58Goals Against Per Game2.59
25.98%Power Play Percentage18.37%
79.89%Penalty Kill Percentage83.70%
Team Leaders
Chris KreiderGoals
Chris Kreider
17
Mika ZibanejadAssists
Mika Zibanejad
27
Mika ZibanejadPoints
Mika Zibanejad
38
Brandon CarloPlus/Minus
Brandon Carlo
13
Igor ShesterkinWins
Igor Shesterkin
15
Igor ShesterkinSave Percentage
Igor Shesterkin
0.903

Team Stats
Goals For
88
2.59 GFG
Shots For
907
26.68 Avg
Power Play Percentage
18.4%
18 GF
Offensive Zone Start
40.6%
Goals Against
88
2.59 GAA
Shots Against
826
24.29 Avg
Penalty Kill Percentage
83.7%%
22 GA
Defensive Zone Start
39.9%
Team Info

General ManagerPierre
DivisionMetropolitan
ConferenceEastern
CaptainJacob Trouba
Assistant #1Chris Kreider
Assistant #2Mika Zibanejad


Arena Info

NameMadison Square Garden
Capacity16,000
Attendance15,863
Season Tickets3,200


Roster Info

Pro Team22
Farm Team11
Contract Limit33 / 50
Prospects24


Salary Cap

Estimated Season Salary Cap61,692,870$
Available Salary Cap3,307,130$
Special Salary Cap Value0$
Players In Salary Cap22


Finance

Year to Date Revenue23,149,132$
Year To Date Expenses26,809,230$
Estimated Season Revenue32,681,128$
Estimated Season Expenses34,883,640$
Current Bank Account32,985,183$
Projected Bank Account30,254,338$


Team History

This Season17-15-2 (36PTS)
History111-72-12 (0.569%)
Playoff Appearances2
Playoff Record (W-L)17-16
Stanley Cup0


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 SPAgeContractSalary
1Chris Kreider (A)X99.006336918580769988537985716887740508423314,600,000$
2Mika Zibanejad (A)X100.006136908472789886568475746490750508323126,000,000$
3Vincent TrocheckX99.007445847766819984798774736781690508323014,600,000$
4Pavel BuchnevichXX99.005938847970789783497976776567580508022944,300,000$
5Alexis LafreniereXX100.00633985797073998150737769655355050781221950,000$
6Andrei SvechnikovXX98.007452717971727884538475645560580507712435,000,000$
7Yegor SharangovichXXX99.005630967471739980477280687752520507712611,500,000$
8Morgan BarronXXX100.00764586837859976647455570534549050700251900,000$
9Jesper FastX100.006638917469639163465645684880680506903211,900,000$
10Kaapo KakkoX100.00583785797365806848466562585351050690231950,000$
11Will Cuylle (R)X100.00916169717560986346465864543946050690222828,333$
12Barclay GoodrowXXX100.008260627174639757504640734571660506803111,000,000$
13Noah HanifinX99.006436938074789774507758815478670508022756,000,000$
14Jacob Trouba (C)X100.008053757675748770486638824483720507713035,800,000$
15K'Andre MillerX97.007344857677749770486649825053550507612442,000,000$
16Brandon CarloX100.007344867378719365475040884570650507512713,000,000$
17Neal PionkX100.007949817468739968487243724764580507512813,100,000$
18Jarred TinordiX100.008562617182627263465630774047520507003211,100,000$
Scratches
1Filip ChytilX100.005950598274703471456651645155520506602431,700,000$
2Marc StaalX100.00644476577659575242493566439982050660371850,000$
Farm Team
1Jonny BrodzinskiXX100.0062359369716076654862496050444605066X03141,200,000$
2Adam Edstrom (R)XXX100.00685657708455355844404864493441050600231846,667$
3Benoit-Olivier Groulx (R)XX100.00774980667262664938373067403743050600244800,000$
4Matt Rempe (R)XX100.00898225778549406045474260463439050600222820,000$
5Nolan Foote (R)X100.006859506972582964435354595235440506002331,000,000$
6Shane Bowers (R)XX100.00533780716957326139514658483443050590241500,000$
7Sam Colangelo (R)XX100.00605452667363286246505649533339050580221925,000$
8Nils Lundkvist (R)X100.006035907669597863466735604343480536602341,000,000$
9Dylan McIlrathX100.00817825678152285443423267413847050590321700,000$
10Brandon ScanlinX100.00635456677853265343483358423343050570251775,000$
TEAM AVERAGE99.6769487474746674684860526852565505070
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 SPAgeContractSalary
1Igor Shesterkin95.00738282706974777679757846470507812863,600,000$
2Jonathan Quick100.00696666747067697172677099740507613822,000,000$
Scratches
Farm Team
1Matt Tomkins100.0061545472606262606060552633056620301775,000$
TEAM AVERAGE98.336867677266686969706768575105272
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary


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
1Mika ZibanejadNY RangersC341127381260206590267612.22%165619.3117815780000402152.90%81100001.1612000512
2Chris KreiderNY RangersLW34171633126026311424810111.97%568620.1971821760005833256.25%4800000.9624000333
3Noah HanifinNY RangersD34125261310015385012362.00%2878523.101562373000298000%000000.6600000012
4Andrei SvechnikovNY RangersLW/RW3451520120060296826587.35%560317.75077270000012042.11%3800000.6600000010
5Alexis LafreniereNY RangersLW/RW34108184160222574256213.51%355716.38000536000080042.42%3300000.6501000213
6Pavel BuchnevichNY RangersLW/RW347916-920233611738845.98%867819.9543717790003813040.38%5200000.4722000111
7Yegor SharangovichNY RangersC/LW/RW341061602023068184514.71%443812.911123530000111046.88%3200000.7314000200
8Vincent TrocheckNY RangersC346814-926048747920677.59%563118.5714515790000261063.26%72400100.4401000003
9K'Andre MillerNY RangersD346713-821531333091520.00%3874021.783031678000071110%000000.3500010111
10Jacob TroubaNY RangersD3211011-10501052271910175.26%3866720.85011676000063000%000000.3300011000
11Brandon CarloNY RangersD29279132404027324106.25%3657319.7601118000073000%000000.3100000010
12Neal PionkNY RangersD3407723406615193130%2861318.04011771000131000%000000.2300000000
13Jarred TinordiNY RangersD29145-1595701595811.11%2749016.9300016000073000%000000.2000001010
14Jesper FastNY RangersRW341341001141710225.88%42868.4200002000090057.89%1900000.2800000000
15Kaapo KakkoNY RangersRW34224-360416297216.90%134710.2300000000000075.00%2000000.2300000000
16Morgan BarronNY RangersC/LW/RW3422412154126329276.25%341512.22000000000901046.30%43200000.1900010020
17Barclay GoodrowNY RangersC/LW/RW34123-31405831126148.33%738611.37000010001920045.85%41000000.1600000010
18Will CuylleNY RangersLW34202-119542121841011.11%02547.4900000000000078.57%1400000.1600010000
19Marc StaalNY RangersD11000-300522530%919717.9800001000036000%00000000000000
20Nils LundkvistFarm Team 5 (NYR)D1000-200100000%01717.130000000000000%00000000000000
Team Total or Average6128515824310336306275469072856899.37%2501002816.391831491327950001289414453.36%263300100.48614042141415
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
1Igor ShesterkinNY Rangers29151220.9032.30174602676940110.80015295320
2Jonathan QuickNY Rangers62300.8623.40318001813000100529000
3Matt TomkinsFarm Team 5 (NYR)10000.8893.002000190000002000
Team Total or Average36171520.8972.4820850286833012153436320


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 Country Rookie Weight Height No Trade Available For Trade Acquired By Last Trade Date Force Waivers Waiver Possible Contract Contract Signature Date Force UFA Emergency Recall Type Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Salary Cap Year 2Salary Cap Year 3Salary Cap Year 4Salary Cap Year 5Salary Cap Year 6Salary Cap Year 7Salary Cap Year 8Salary Cap Year 9Salary Cap Year 10No Trade Year 2No Trade Year 3No Trade Year 4No Trade Year 5No Trade Year 6No Trade Year 7No Trade Year 8No Trade Year 9No Trade Year 10Link
Alexis Lafreniere (1 Way Contract)NY RangersLW/RW222001-10-11CANNo194 Lbs6 ft1NoNoN/AYesYes12024-07-13FalseFalsePro & Farm950,000$950,000$537,295$No---------------------------Link / NHL Link
Andrei Svechnikov (1 Way Contract)NY RangersLW/RW242000-03-26RUSNo195 Lbs6 ft2NoNoN/AYesYes32024-09-11FalseFalsePro & Farm5,000,000$5,000,000$2,827,869$No5,000,000$5,000,000$----------------NoNo-------Link / NHL Link
Barclay Goodrow (1 Way Contract)NY RangersC/LW/RW311993-02-26CANNo209 Lbs6 ft2NoNoN/AYesYes12024-07-13FalseFalsePro & Farm1,000,000$1,000,000$565,574$No---------------------------NHL Link
Brandon Carlo (1 Way Contract)NY RangersD271996-11-26USANo217 Lbs6 ft5NoNoTrade2024-08-19YesYes12024-09-11FalseFalsePro & Farm3,000,000$3,000,000$1,696,721$No---------------------------Link / NHL Link
Chris Kreider (1 Way Contract)NY RangersLW331991-04-30USANo233 Lbs6 ft3NoNoN/AYesYes12024-07-13FalseFalsePro & Farm4,600,000$4,600,000$2,601,639$No---------------------------Link / NHL Link
Filip Chytil (1 Way Contract)NY RangersC241999-09-05CZENo208 Lbs6 ft2NoNoN/AYesYes32024-07-13FalseFalsePro & Farm1,700,000$1,700,000$961,475$No1,700,000$1,700,000$-------1,700,000$1,700,000$-------NoNo-------Link / NHL Link
Igor Shesterkin (1 Way Contract)NY RangersG281995-12-30RUSNo197 Lbs6 ft1NoNoN/AYesYes62024-07-29FalseFalsePro & Farm3,600,000$3,600,000$2,036,066$No3,600,000$3,600,000$3,600,000$3,600,000$3,600,000$-------------NoNoNoNoNo----Link / NHL Link
Jacob Trouba (1 Way Contract)NY RangersD301994-02-26USANo209 Lbs6 ft3NoNoN/AYesYes32024-07-13FalseFalsePro & Farm5,800,000$5,800,000$3,280,328$No5,800,000$5,800,000$-------5,800,000$5,800,000$-------NoNo-------Link / NHL Link
Jarred Tinordi (1 Way Contract)NY RangersD321992-02-20USANo229 Lbs6 ft6NoNoTrade2024-09-06YesYes12024-08-01FalseFalsePro & Farm1,100,000$1,100,000$622,131$No---------------------------Link / NHL Link
Jesper Fast (1 Way Contract)NY RangersRW321991-12-02SWENo191 Lbs6 ft1NoNoN/AYesYes12024-07-13FalseFalsePro & Farm1,900,000$1,900,000$1,074,590$No---------------------------Link / NHL Link
Jonathan Quick (1 Way Contract)NY RangersG381986-01-21USANo215 Lbs6 ft1NoNoTrade2024-07-26YesYes22024-07-31FalseFalsePro & Farm2,000,000$2,000,000$1,131,148$No2,000,000$-----------------No--------Link / NHL Link
K'Andre Miller (1 Way Contract)NY RangersD242000-01-21USANo210 Lbs6 ft5NoNoN/AYesYes42024-07-31FalseFalsePro & Farm2,000,000$2,000,000$1,131,148$No2,000,000$2,000,000$2,000,000$---------------NoNoNo------Link / NHL Link
Kaapo Kakko (1 Way Contract)NY RangersRW232001-02-13FINNo205 Lbs6 ft2NoNoN/AYesYes12024-07-13FalseFalsePro & Farm950,000$950,000$537,295$No---------------------------Link / NHL Link
Marc Staal (1 Way Contract)NY RangersD371987-01-13CANNo208 Lbs6 ft4NoNoAssign ManuallyYesYes12024-09-06FalseFalsePro & Farm850,000$850,000$480,738$No---------------------------NHL Link
Mika Zibanejad (1 Way Contract)NY RangersC311993-04-18SWENo201 Lbs6 ft2NoNoTrade2024-03-09YesYes22024-07-13FalseFalsePro & Farm6,000,000$6,000,000$3,393,443$No6,000,000$--------6,000,000$--------No--------NHL Link
Morgan BarronNY RangersC/LW/RW251998-12-02CANNo220 Lbs6 ft4NoNoN/AYesYes12024-07-13FalseFalsePro & Farm900,000$900,000$509,016$No---------------------------Link / NHL Link
Neal Pionk (1 Way Contract)NY RangersD281995-07-29USANo190 Lbs6 ft0NoNoN/AYesYes12024-09-11FalseFalsePro & Farm3,100,000$3,100,000$1,753,279$No---------------------------Link / NHL Link
Noah Hanifin (1 Way Contract)NY RangersD271997-01-25USANo207 Lbs6 ft3NoNoN/AYesYes52024-07-31FalseFalsePro & Farm6,000,000$6,000,000$3,393,443$No6,000,000$6,000,000$6,000,000$6,000,000$--------------NoNoNoNo-----Link / NHL Link
Pavel Buchnevich (1 Way Contract)NY RangersLW/RW291995-04-17RUSNo196 Lbs6 ft1NoNoN/AYesYes42024-07-13FalseFalsePro & Farm4,300,000$4,300,000$2,431,967$No4,300,000$4,300,000$4,300,000$------4,300,000$4,300,000$4,300,000$------NoNoNo------NHL Link
Vincent Trocheck (1 Way Contract)NY RangersC301993-07-11USANo187 Lbs5 ft11NoNoN/AYesYes12024-07-13FalseFalsePro & Farm4,600,000$4,600,000$2,601,639$No---------------------------Link / NHL Link
Will CuylleNY RangersLW222002-02-05CANYes210 Lbs6 ft3NoNoN/ANoNo22024-07-13FalseFalsePro & Farm828,333$828,333$468,483$No828,333$--------828,333$--------No--------Link
Yegor Sharangovich (1 Way Contract)NY RangersC/LW/RW261998-06-06BLRNo196 Lbs6 ft2NoNoN/AYesYes12024-07-13FalseFalsePro & Farm1,500,000$1,500,000$848,361$No---------------------------Link / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2228.32206 Lbs6 ft22.092,803,561$

Sum Year 1 Salary Sum Year 2 Salary Sum Year 3 Salary Sum Year 4 Salary Sum Year 5 Salary
61,678,333$37,228,333$28,400,000$15,900,000$9,600,000$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Chris KreiderMika ZibanejadAndrei Svechnikov35113
2Alexis LafreniereVincent TrocheckPavel Buchnevich35113
3Yegor SharangovichMorgan BarronKaapo Kakko20122
4Will CuylleBarclay GoodrowJesper Fast10221
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Jacob TroubaK'Andre Miller32122
2Noah HanifinNeal Pionk30122
3Jarred TinordiBrandon Carlo28131
4Noah HanifinK'Andre Miller10220
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Chris KreiderMika ZibanejadPavel Buchnevich55014
2Yegor SharangovichVincent TrocheckAndrei Svechnikov45014
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Jacob TroubaK'Andre Miller55113
2Noah HanifinNeal Pionk45113
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Morgan BarronYegor Sharangovich55140
2Barclay GoodrowJesper Fast45140
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Brandon CarloNoah Hanifin50230
2Jarred TinordiK'Andre Miller50230
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Barclay Goodrow55140Brandon CarloNoah Hanifin50230
2Morgan Barron45140Jarred TinordiK'Andre Miller50230
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Mika ZibanejadYegor Sharangovich50212
2Vincent TrocheckAndrei Svechnikov50212
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Jacob TroubaK'Andre Miller50122
2Noah HanifinBrandon Carlo50122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Chris KreiderMika ZibanejadPavel BuchnevichNeal PionkNoah Hanifin
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Chris KreiderVincent TrocheckPavel BuchnevichBrandon CarloNoah Hanifin
Extra Forwards
Normal PowerPlayPenalty Kill
Andrei Svechnikov, Yegor Sharangovich, Pavel BuchnevichAndrei Svechnikov, Yegor SharangovichVincent Trocheck
Extra Defensemen
Normal PowerPlayPenalty Kill
Noah Hanifin, Brandon Carlo, K'Andre MillerBrandon CarloK'Andre Miller, Neal Pionk
Penalty Shots
Chris Kreider, Yegor Sharangovich, Mika Zibanejad, Pavel Buchnevich, Vincent Trocheck
Goalie
#1 : Igor Shesterkin, #2 : Jonathan Quick
Custom OT Lines Forwards
Chris Kreider, Mika Zibanejad, Pavel Buchnevich, Vincent Trocheck, Andrei Svechnikov, Alexis Lafreniere, Alexis Lafreniere, Yegor Sharangovich, Barclay Goodrow, Morgan Barron, Will Cuylle
Custom OT Lines Defensemen
K'Andre Miller, Noah Hanifin, Jacob Trouba, Brandon Carlo, Neal Pionk


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
1Anaheim11000000321110000003210000000000021.00036900111029111260199413300.00%10100.00%0588105455.79%536103751.69%28150655.53%2720206116
2Buffalo2020000026-41010000003-31010000023-100.0002460020003711179057141844400.00%6183.33%0588105455.79%536103751.69%28150655.53%473346132512
3Calgary11000000422000000000001100000042221.00048120011202268802164174125.00%20100.00%0588105455.79%536103751.69%28150655.53%2619216116
4Carolina21100000541110000004131010000013-220.500591400122053131624053111042200.00%50100.00%0588105455.79%536103751.69%28150655.53%463148152512
5Chicago11000000624110000006240000000000021.00061218002130281747013229155240.00%5180.00%0588105455.79%536103751.69%28150655.53%2618207136
6Dallas1010000002-2000000000001010000002-200.0000001000002088402241214400.00%6183.33%0588105455.79%536103751.69%28150655.53%2518227116
7Detroit3120000047-3110000003122020000016-520.333481200103080192437088192474900.00%11281.82%0588105455.79%536103751.69%28150655.53%684773213719
8Edmonton11000000101000000000001100000010121.0001230100102461080221016213133.33%60100.00%0588105455.79%536103751.69%28150655.53%2114267115
9Florida1010000035-21010000035-20000000000000.000358000120252815027410144125.00%5260.00%0588105455.79%536103751.69%28150655.53%2619206126
10Los Angeles10000010211100000102110000000000021.000224000102235108438111718400.00%60100.00%0588105455.79%536103751.69%28150655.53%2517267125
11Montreal211000004401010000002-21100000042220.500471100211063281421045122044400.00%8187.50%0588105455.79%536103751.69%28150655.53%483547132312
12NY Isles10000010431100000104310000000000021.00045900120227413933481623200.00%80100.00%0588105455.79%536103751.69%28150655.53%2517278115
13Nashville1010000003-3000000000001010000003-300.0000000000002561360131814500.00%40100.00%0588105455.79%536103751.69%28150655.53%2719197126
14New Jersey21100000770110000004311010000034-120.50071219003310441415150592440338225.00%10280.00%0588105455.79%536103751.69%28150655.53%443051132412
15Ottawa10000010321100000103210000000000021.000347001101269685211110232150.00%5180.00%0588105455.79%536103751.69%28150655.53%2416277136
16Philadelphia1010000046-2000000000001010000046-200.0004711101030368131501976134125.00%3233.33%0588105455.79%536103751.69%28150655.53%2618207136
17Pittsburgh2020000036-31010000013-21010000023-100.00036900102050151421060182043300.00%9277.78%0588105455.79%536103751.69%28150655.53%442951152412
18San Jose11000000615110000006150000000000021.0006111700420027166502468143266.67%40100.00%0588105455.79%536103751.69%28150655.53%2618217126
19Seattle21001000743110000003121000100043141.0007132000312154261963381814377228.57%7185.71%0588105455.79%536103751.69%28150655.53%533745152613
20St-Louis21000100642110000004131000010023-130.75061218000150521011256562412364125.00%6183.33%0588105455.79%536103751.69%28150655.53%503446142713
21Toronto11000000651000000000001100000065121.000611170041103615129025106183266.67%3233.33%0588105455.79%536103751.69%28150655.53%2216237136
22Utah1010000025-31010000025-30000000000000.00024600110036141480226616400.00%20100.00%0588105455.79%536103751.69%28150655.53%2720207125
23Vancouver11000000312000000000001100000031221.0003470002103241612019410132150.00%5180.00%0588105455.79%536103751.69%28150655.53%2619207136
24Washington1010000035-2000000000001010000035-200.000369001110285158018712143133.33%6266.67%0588105455.79%536103751.69%28150655.53%2517216136
25Winnipeg1000000101-11000000101-10000000000010.500000000001301011411134414200.00%20100.00%0588105455.79%536103751.69%28150655.53%2618237147
Total341315011318888017850003148371117510011004051-11360.5298815824621302331790728230929832826250336627981818.37%1352283.70%0588105455.79%536103751.69%28150655.53%842591794247431215
_Since Last GM Reset341315011318888017850003148371117510011004051-11360.5298815824621302331790728230929832826250336627981818.37%1352283.70%0588105455.79%536103751.69%28150655.53%842591794247431215
_Vs Conference19512000204860-12934000202223-11028000002637-11140.3684884132101812163505143167191850614519238548816.67%791778.48%0588105455.79%536103751.69%28150655.53%450313459137239118
_Vs Division926000102631-54210001013103505000001321-860.33326457110889223859869232437510416822418.18%41880.49%0588105455.79%536103751.69%28150655.53%2111452216611255

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
3436L18815824690782625033662721
All Games
GPWLOTWOTL SOWSOLGFGA
34131511318888
Home Games
GPWLOTWOTL SOWSOLGFGA
178500314837
Visitor Games
GPWLOTWOTL SOWSOLGFGA
1751011004051
Last 10 Games
WLOTWOTL SOWSOL
350110
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
981818.37%1352283.70%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
282309298323023317
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
588105455.79%536103751.69%28150655.53%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
842591794247431215


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
27NY Rangers2Pittsburgh3LBoxScore
430Utah5NY Rangers2LBoxScore
545Detroit1NY Rangers3WBoxScore
763NY Rangers0Detroit3LBoxScore
879NY Rangers6Toronto5WBoxScore
1096NY Rangers4Montreal2WBoxScore
11113Florida5NY Rangers3LBoxScore
12128Anaheim2NY Rangers3WBoxScore
14151NY Rangers3Washington5LBoxScore
16169Ottawa2NY Rangers3WXXBoxScore
17185NY Isles3NY Rangers4WXXBoxScore
20213Buffalo3NY Rangers0LBoxScore
21228NY Rangers1Detroit3LBoxScore
24247Winnipeg1NY Rangers0LXXBoxScore
25261San Jose1NY Rangers6WBoxScore
28287NY Rangers4Seattle3WXBoxScore
29300NY Rangers3Vancouver1WBoxScore
31314NY Rangers4Calgary2WBoxScore
32332NY Rangers1Edmonton0WBoxScore
33337St-Louis1NY Rangers4WBoxScore
34349NY Rangers1Carolina3LBoxScore
36362NY Rangers4Philadelphia6LBoxScore
37376Montreal2NY Rangers0LBoxScore
38393New Jersey3NY Rangers4WBoxScore
42421Pittsburgh3NY Rangers1LBoxScore
43436Seattle1NY Rangers3WBoxScore
44444Chicago2NY Rangers6WBoxScore
45457NY Rangers2Buffalo3LBoxScore
47475Los Angeles1NY Rangers2WXXBoxScore
48492NY Rangers2St-Louis3LXBoxScore
49502NY Rangers0Nashville3LBoxScore
51525NY Rangers0Dallas2LBoxScore
52539Carolina1NY Rangers4WBoxScore
53545NY Rangers3New Jersey4LBoxScore
55572NY Rangers-Tampa Bay-
56586NY Rangers-Florida-
58604Boston-NY Rangers-
59620NY Rangers-Washington-
60632NY Rangers-Chicago-
61643Dallas-NY Rangers-
63656New Jersey-NY Rangers-
65682NY Rangers-Las Vegas-
67703NY Rangers-Colorado-
68717NY Rangers-Utah-
69728Columbus-NY Rangers-
70738NY Rangers-Montreal-
71750Ottawa-NY Rangers-
72763Philadelphia-NY Rangers-
74789Colorado-NY Rangers-
76802Carolina-NY Rangers-
78827NY Rangers-Boston-
79839Las Vegas-NY Rangers-
80859Boston-NY Rangers-
81871Pittsburgh-NY Rangers-
82882NY Rangers-Columbus-
84895NY Rangers-Buffalo-
85907NY Rangers-Pittsburgh-
86925NY Rangers-NY Isles-
88945Toronto-NY Rangers-
90965Nashville-NY Rangers-
91970NY Isles-NY Rangers-
92983Washington-NY Rangers-
941003NY Rangers-Ottawa-
951017Columbus-NY Rangers-
971031NY Rangers-Winnipeg-
Trade Deadline --- Trades can’t be done after this day is simulated!
981046NY Rangers-Minnesota-
991062NY Rangers-Columbus-
1001069Edmonton-NY Rangers-
1021079Calgary-NY Rangers-
1031091Toronto-NY Rangers-
1041104Vancouver-NY Rangers-
1061138NY Rangers-Los Angeles-
1081158NY Rangers-Anaheim-
1091168NY Rangers-San Jose-
1111192Minnesota-NY Rangers-
1121209NY Rangers-New Jersey-
1141230Tampa Bay-NY Rangers-
1161246Philadelphia-NY Rangers-
1171254NY Rangers-NY Isles-
1181266NY Rangers-Carolina-
1191287NY Rangers-Florida-
1221310Tampa Bay-NY Rangers-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2Level 3Level 4Luxury
Capacity50005000200040000
Ticket Price1701057050400
Attendance84,54284,14534,00066,9810
Attendance PCT99.46%98.99%100.00%98.50%0%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
24 15863 - 99.14% 1,361,714$23,149,132$16000128

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Salaries CapCoaches SalariesSpecial Salary Cap Value
26,809,230$ 61,678,333$ 49,628,333$ 0$ 0$
Salary Cap Per DaysSalary Cap To DateLuxury Taxe TotalPlayers In Salary CapPlayers Out of Salary Cap
505,560$ 26,809,230$ 0$ 22 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
32,681,128$ 69 505,560$ 34,883,640$

Team Total Estimate
Estimated Season Expenses Current Bank Account Projected Bank Account
35,411,973$ 32,985,183$ 30,254,338$
Estimated Season Salary CapAvailable Salary CapMaximum Salary CapOver Minimum Salary Cap
61,692,870$ 3,307,130$ 65,000,000$ 16,692,870$



Depth Chart

Left WingCenterRight Wing
Chris KreiderAGE:33PO:0OV:84
Pavel BuchnevichAGE:29PO:0OV:80
Alexis LafreniereAGE:22PO:0OV:78
Andrei SvechnikovAGE:24PO:0OV:77
Yegor SharangovichAGE:26PO:0OV:77
Morgan BarronAGE:25PO:0OV:70
Will Cuylle (R)AGE:22PO:0OV:69
Barclay GoodrowAGE:31PO:0OV:68
Adam Edstrom (R)AGE:23PO:0OV:60
Benoit-Olivier Groulx (R)AGE:24PO:0OV:60
Nolan Foote (R)AGE:23PO:0OV:60
Mika ZibanejadAGE:31PO:0OV:83
Vincent TrocheckAGE:30PO:0OV:83
Yegor SharangovichAGE:26PO:0OV:77
Morgan BarronAGE:25PO:0OV:70
Barclay GoodrowAGE:31PO:0OV:68
Filip ChytilAGE:24PO:0OV:66
Jonny BrodzinskiAGE:31PO:0OV:66
Adam Edstrom (R)AGE:23PO:0OV:60
Benoit-Olivier Groulx (R)AGE:24PO:0OV:60
Matt Rempe (R)AGE:22PO:0OV:60
Shane Bowers (R)AGE:24PO:0OV:59
Sam Colangelo (R)AGE:22PO:0OV:58
Pavel BuchnevichAGE:29PO:0OV:80
Alexis LafreniereAGE:22PO:0OV:78
Andrei SvechnikovAGE:24PO:0OV:77
Yegor SharangovichAGE:26PO:0OV:77
Morgan BarronAGE:25PO:0OV:70
Jesper FastAGE:32PO:0OV:69
Kaapo KakkoAGE:23PO:0OV:69
Barclay GoodrowAGE:31PO:0OV:68
Jonny BrodzinskiAGE:31PO:0OV:66
Adam Edstrom (R)AGE:23PO:0OV:60
Matt Rempe (R)AGE:22PO:0OV:60
Shane Bowers (R)AGE:24PO:0OV:59
Sam Colangelo (R)AGE:22PO:0OV:58

Defense #1Defense #2Goalie
Noah HanifinAGE:27PO:0OV:80
Jacob TroubaAGE:30PO:0OV:77
K'Andre MillerAGE:24PO:0OV:76
Brandon CarloAGE:27PO:0OV:75
Neal PionkAGE:28PO:0OV:75
Jarred TinordiAGE:32PO:0OV:70
Marc StaalAGE:37PO:0OV:66
Nils Lundkvist (R)AGE:23PO:0OV:66
Dylan McIlrathAGE:32PO:0OV:59
Brandon ScanlinAGE:25PO:0OV:57
Igor ShesterkinAGE:28PO:0OV:78
Jonathan QuickAGE:38PO:0OV:76
Matt TomkinsAGE:30PO:0OV:62

Prospects

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
ProspectTeam NameDraft YearOverall PickInformationLast Trade DateLink
Adam SykoraNY Rangers202252
Albert WikmanNY Rangers2023126
Antonio StrangesNY Rangers2020137
Brody LambNY Rangers20211122024-07-16
Bryce Mcconnell-BarkerNY Rangers202287
Cameron AllenNY Rangers202393
Cameron BergNY Rangers2021135
Christian HumphreysNY Rangers2024159
Cole BeaudoinNY Rangers202430
Drew FortescueNY Rangers202385
Dylan GarandNY Rangers20201022024-07-16
Frederik Nissen DichowNY Rangers2019147
Gabriel PerreaultNY Rangers202321
Hunter SkinnerNY Rangers2019116
Jackson KunzNY Rangers2020142
Jayden GrubbeNY Rangers202171
Jeremie PoirierNY Rangers202049
Justin PoirierNY Rangers202494
Kody ClarkNY Rangers201852
Lauri PajuniemiNY Rangers2018114
Max CurranNY Rangers2024158
Maxim CajkovicNY Rangers201985
Maxim MasseNY Rangers202462
Noah LabaNY Rangers2022119

Draft Picks

Year R1R2R3R4R5
2025
2026
2027
2028
2029
Conditional Draft Picks



Zibanejad rejoint les Rangers !

By Pierre (NY Rangers) On Monday 11th March 2024 / 9:50am

Énorme nouvelle à la date limite des échanges hier soir. Le centre d'Ottawa, Mika Zibanejad rejoint les Rangers pour ce sprint de fin de saison !

C'est un gros renfort pour l'équipe qui est sur une dynamique très positive depuis la fin novembre. Le DG montre qu'il a des ambitions pour cette fin de saison.
Dans l'autre sens, c'est Josh Norris qui part au Canada. Il laissera un gros vide dans l'équipe, bien revenu de blessure, il apportait beaucoup en infériorité numérique et sur le bottom 6.
L'équipe avait aussi beaucoup d'espoirs en son grand potentiel, les centres de qualité étant rares.

Heureusement, la ligne de centre est maintenant très bien fournies aux Rangers Zibanejad, Trotcheck, Chytil, Goodrow... l'équipe est prête pour les playoffs même s'il faudra se qualifier.

La concurrence est très forte dans l'Est !

New Comment

Trade Deadline: Arrivée de Barclay Goodrow

By Pierre (NY Rangers) On Monday 26th February 2024 / 1:57pm

Expérience, efficacité défensive, Barclay Goodrow arrive sur les bords de l'Hudson pour solidifier le bottom 6 des Rangers.

Quelques joueurs ont dû partir renforcer l'équipe AHL pour faire de la place et il n'est pas impossible que d'autres joueurs partent d'ici à la date limite des transferts (annoncée le 10 mars prochain).
Les Rangers sont actuellement à la limite de la qualification, il est clair que le DG essaie de renforcer son équipe pour aller chercher cette place qualificative et peut-être un aussi beau parcours que l'année passée.

New Comment

La qualification est encore lointaine...

By Pierre (NY Rangers) On Thursday 28th December 2023 / 2:27pm

La saison version 2023 se termine mieux qu'elle n'a commencé.
Avec 10 victoires en 20 matchs, l'équipe reste plus ou moins au contact des qualifiés, mais pour le moment ne progresse pas dans le classement…
La direction devra prendre des décisions d'ici à la Trade Deadline pour savoir s'il faut investir pour se qualifier, ou s'il faut plutôt dégrossir un peu l'équipe pour préparer la suite.

Sur la sellette, si c'est cette option qui est retenue par la direction, des joueurs comme Neal Pionk, Derek Forbort, Matt Grzelcyk, ou encore Tyler Motte et Sammy Blais pourraient faire leurs valises.
Dans le cas contraire, il se murmure déjà des noms pour améliorer la défense et sa transition vers l'attaque.

Les unités spéciales sont souci récurrent cette saison même si cela va mieux depuis quelques matchs. C'est clairement sur cet aspect que l'équipe perd des points.
Dernier sur le PK (77.04% pour une moyenne de 82% dans la ligue) c'est ici que les réglages sont encore à trouver, malgré des joueurs talentueux alignés. Du côté du PP, nous n'étions aussi pas loin de la dernière place récemment, nous sommes remontés à la 24ᵉ place (14,37% pour une moyenne a 17%). Toujours insuffisant pour prétendre à une place en playoffs.

Les prochaines semaines seront décisives. Si le rythme a .500 se maintient. Cela ne sera pas suffisant et la direction se devra de réagir. Dans un sens comme dans un autre.

New Comment

Un impressionnant Dylan McIlrath (D) signe chez les Rangers

By Pierre (NY Rangers) On Thursday 12th October 2023 / 9:12am

C'est du haut impressionnant de ses 72 matchs en NHL depuis la draft 2010 (10ᵉ choix des Rangers il y a 13 ans) que Dylan McIlrath (D) revient dans son équipe d'origine !
Solution de secours de la solution de secours, il ira faire les beaux jours de l'équipe ferme des Rangers, où il essaiera de ne tuer personne (1 104 minutes de pénalités en 560 matchs AHL)

Une référence ! Bienvenue à lui

New Comment

Nouvelle saison, mais objectif identique : Les playoffs !

By Pierre (NY Rangers) On Monday 18th September 2023 / 2:42pm

Après une saison 2022-2023 historique, les objectifs restent les mêmes en 2024 : atteindre les playoffs et y faire bonne figure !

L'équipe semble meilleure que l'année dernière, plus solide encore. La grosse progression de Filip Chytil permet d'attendre le retour de Josh Norris à 100% plus tranquillement.
Un bon début de saison pour le moment, avec deux victoires en trois matchs.
Avec un étonnant Alexis Lafreniere en leader des marqueurs (1 but, deux assistances). Mais nous y trouverons bientôt un Andrei Svechnikov qui tente beaucoup (17 tirs en trois matchs) mais n'a pas encore trouvé son rythme avec un seul but.
Une défense cependant qui va devoir se calmer un peu, avec 19 min cumulées entre Hanifin, Pionk et Trouba. C'est un peu trop.

Bonne saison à tous !

New Comment



NY Rangers Trade History







No Injury or Suspension.


NY Rangers Players Stat Leaders (Regular Season)

# Player Name GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS
1Chris Kreider19898101199676120022378312.52%24365718.472530551460005171054.14%31.09413
2Andrei Svechnikov19879931723819639021459413.30%32364918.43193150110000315446.60%10.9428
3Pavel Buchnevich1897092162394015524464110.92%27349318.482022421170001217542.33%10.9334
4Vincent Trocheck15247781251613326130640211.69%17279918.421131426900016357.58%00.8902
5Mika Zibanejad108447712140185825239411.17%23227021.03822307000087653.10%01.07510

NY Rangers Goalies Stat Leaders (Regular Season)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA
1Igor Shesterkin1599051110.9072.45916581237440420350.79434
2Jaroslav Halak37131530.8823.231896611028620420.6679
3Adam Huska85200.8692.91330011612200000
4Jonathan Quick62300.8623.40318001813000100
5Louis Domingue51110.8952.89249001211400000

NY Rangers Career Team Stats

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
202282413000641255228274122130042013011713411917002211251111497255445700268090817232271676282337217159482215363187322.96%3466581.21%11265265047.74%1285265148.47%609122949.55%1923132520086041025506
2023824227063132602194141221104112136108284120160220112411113104260458718468390808241676383280034228163677115043235416.72%3306181.52%21273265248.00%1256265747.27%603126747.59%1963136819745931017507
2024341315011318888017850003148371117510011004051-11368815824621302331790728230929832826250336627981818.37%1352283.70%0588105455.79%536103751.69%28150655.53%842591794247431215
Total Regular Season1989672071085603535689952290456331426252994443035222892731623760310611664813193203192225645176119031921103527814801929366773914519.62%81114881.75%33126635649.18%3077634548.49%1493300249.73%472932854777144524741229
Playoff
20211367000003343-106420000017143725000001629-13123359920011812230092103911438410312725844818.18%58984.48%016537643.88%17545638.38%7720737.20%2952003329616881
2022201190000063576963000003323101156000003034-422631141771025181736442042232011660118723536664914.06%97792.78%132269446.40%32469846.42%16130153.49%480334498153252122
Total Playoff3317160000096100-4151050000050371318711000004663-173496173269103626295944296326292309852903626241081715.74%1551689.68%1487107045.51%499115443.24%23850846.85%775535831250421204

NY Rangers Players Stat Leaders (Play-Off)

# Player Name GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS
1Pavel Buchnevich328233172739361147.02%1059718.671342600001138.46%01.0400
2Josh Norris33141630918465510313.59%259718.094371510122149.34%11.0000
3Mats Zuccarello331016263412268012.50%657317.383471600002032.50%00.9100
4Chris Kreider33131225226454111211.61%759818.132242500012154.76%00.8400
5Jacob Trouba33320232638833378.11%5177523.49044170111100%10.5900

NY Rangers Goalies Stat Leaders (Play-Off)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA
1Igor Shesterkin2413830.9032.871486207173000100
2Jaroslav Halak32100.8803.3517900108300000
3Adam Huska11000.9412.00600023400000
4Louis Domingue51400.8833.22298201613701000