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New York Rangers
GP: 47 | W: 31 | L: 13 | OTL: 3 | P: 65
GF: 165 | GA: 133 | PP%: 24.67% | PK%: 81.48%
DG: Alexandre Gagné | Morale : 50 | Moyenne d’équipe : 79
Prochains matchs #737 vs Ottawa Senators

Centre de jeu
New York Rangers
31-13-3, 65pts
3
FINAL
4 Boston Bruins
38-8-1, 77pts
Team Stats
W1SéquenceW10
15-4-2Fiche domicile21-3-1
16-9-1Fiche visiteur17-5-0
6-4-0Derniers 10 matchs10-0-0
3.51Buts par match 4.60
2.83Buts contre par match 2.91
24.67%Pourcentage en avantage numérique20.81%
81.48%Pourcentage en désavantage numérique82.50%
Seattle Kraken
21-18-5, 47pts
2
FINAL
4 New York Rangers
31-13-3, 65pts
Team Stats
L1SéquenceW1
11-8-3Fiche domicile15-4-2
10-10-2Fiche visiteur16-9-1
4-3-3Derniers 10 matchs6-4-0
3.30Buts par match 3.51
3.66Buts contre par match 2.83
18.24%Pourcentage en avantage numérique24.67%
79.63%Pourcentage en désavantage numérique81.48%
Ottawa Senators
16-24-5, 37pts
Jour 100
New York Rangers
31-13-3, 65pts
Statistiques d’équipe
W1SéquenceW1
10-11-2Fiche domicile15-4-2
6-13-3Fiche visiteur16-9-1
5-4-110 derniers matchs6-4-0
3.18Buts par match 3.51
3.58Buts contre par match 3.51
20.29%Pourcentage en avantage numérique24.67%
77.59%Pourcentage en désavantage numérique81.48%
New York Rangers
31-13-3, 65pts
Jour 103
Philadelphia Flyers
18-18-8, 44pts
Statistiques d’équipe
W1SéquenceW2
15-4-2Fiche domicile11-10-3
16-9-1Fiche visiteur7-8-5
6-4-010 derniers matchs5-3-2
3.51Buts par match 2.98
2.83Buts contre par match 2.98
24.67%Pourcentage en avantage numérique18.25%
81.48%Pourcentage en désavantage numérique81.98%
New York Rangers
31-13-3, 65pts
Jour 105
Anaheim Ducks
23-21-2, 48pts
Statistiques d’équipe
W1SéquenceL1
15-4-2Fiche domicile11-9-2
16-9-1Fiche visiteur12-12-0
6-4-010 derniers matchs6-4-0
3.51Buts par match 3.65
2.83Buts contre par match 3.65
24.67%Pourcentage en avantage numérique23.49%
81.48%Pourcentage en désavantage numérique77.78%
Meneurs d'équipe
Nathan MacKinnonButs
Nathan MacKinnon
21
Mike MathesonPasses
Mike Matheson
35
Mike MathesonPoints
Mike Matheson
43
Mark ScheifelePlus/Moins
Mark Scheifele
16
Andrei VasilevskiyVictoires
Andrei Vasilevskiy
22
Andrei VasilevskiyPourcentage d’arrêts
Andrei Vasilevskiy
0.899

Statistiques d’équipe
Buts pour
165
3.51 GFG
Tirs pour
1480
31.49 Avg
Pourcentage en avantage numérique
24.7%
37 GF
Début de zone offensive
41.2%
Buts contre
133
2.83 GAA
Tirs contre
1307
27.81 Avg
Pourcentage en désavantage numérique
81.5%%
30 GA
Début de la zone défensive
39.0%
Informations de l'équipe

Directeur généralAlexandre Gagné
EntraîneurPaul Maurice
DivisionMetro Division
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

NomMadison Square Garden
Capacité19,000
Assistance18,151
Billets de saison17,670


Informations de la formation

Équipe Pro20
Équipe Mineure22
Limite contact 42 / 60
Espoirs7


Plafond salarial

Cap Salarial de la Saison estimé95,364,046$
Plafond salarial disponible135,954$
Valeur du plafond salarial spécial0$
Joueurs Inclus dans le plafond salarial20


Finance

Revenu annuel à ce jour37,328,831$
Dépenses annuelles à ce jour49,192,744$
Revenus de la saison estimés35,551,268$
Dépenses de la saison estimées46,191,984$
Compte bancaire actuel15,783,288$
Compte bancaire projeté10,840,326$


Astuces sur les filtres (anglais seulement)
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
# Nom du joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire
1Nathan MacKinnonX100.0068507390799292977398917892878305087030512,600,000$
2Mark ScheifeleX100.007161698182899491748589738789850508303258,500,000$
3Filip ForsbergX100.007945738381889293518488718888820508203158,500,000$
4Brad MarchandXXX100.007450678468899488508182738491920508003755,250,000$
5Lucas RaymondXX100.007041878979898290418684728763530508002358,075,000$
6Zach HymanXX100.007042758181889089457788728684740508003334,125,000$
7Frank VatranoXX100.007748648278889089507883748484740507903134,571,189$
8Jake EvansXX100.007544898276868578807771827773630507702942,850,000$
9Casey CizikasXX100.008358727675849475837168777389790507503421,250,000$
10Logan O'ConnorX100.007462808472858675517271787776660507502952,500,000$
11Mark JankowskiXX100.00645077748584847477667172738272050730311800,000$
12Tyson JostXXX100.00705172757681817065666569708272050700271775,000$
13Mike MathesonX100.007052708679928986408173928184790508203154,875,000$
14Travis SanheimX100.007141738386948885407875938179690508202956,250,000$
15Brent BurnsX100.006643837385898986407973837798880508004011,000,000$
16Neal PionkX100.007547698876918684407975878379690508003057,000,000$
17Brandon MontourX100.007057668278908889407982758482720507903157,142,857$
18Jackson LaCombeX100.00704283858590778140767585805950050780255925,000$
Rayé
Équipe Mineure
1Justin DowlingX100.00654182716577796769646163667767050670352775,000$
2Brennan OthmannX96.00654274717474656642636060665550050640231863,333$
3Matthew StienburgX100.00635665707169616341585861635150050620251775,000$
4Dominik ShineX100.00535160645972716444635655626558050610321775,000$
5Danila KlimovichX97.00664465656762606243565961625050050600231833,333$
6Joakim KemellX100.00604269666461586344615954635050050600212886,667$
7Brad LambertX100.00564269656361586444635552615050050590222886,667$
8Reid SchaeferX100.00684266607259565942555460585050050590222886,667$
9Drew HellesonX100.007151677179777269406563716856500506902421,100,000$
10Marc Del GaizoX100.00704676747177707040666273695650050690261775,000$
11Adam WilsbyX100.00634178747378646740626170675250050670252775,000$
12Phil KempX100.00654566656767666240545668615450050630262775,000$
13Artem DudaX100.00634169676262616240615765625050050620212950,000$
14Nate ClurmanX100.00634270656566635840535367585550050620271775,000$
15Mikulas HovorkaX100.00644264606863626040555564585150050610241950,000$
16Marek AlscherX100.00614263626361595840555561585050050590212865,000$
17David GoyetteX100.00594167625861595841575559585050050580212891,667$
18Tyler BoucherX100.00634366596762605841525354565050050570221863,333$
19Hunter BrzustewiczX95.76594169646260586240625664615050050610212950,000$
20Aidan FulpX100.005941715968646257405352585652500505902500$
MOYENNE D’ÉQUIPE99.6867467273737775734868677071676205070
Astuces sur les filtres (anglais seulement)
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
# Nom du gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SPÂgeContratSalaire
1Andrei Vasilevskiy100.00929496929493939292948785780508503137,125,000$
2Jonas Johansson96.00817979898179777878817471640507303021,250,000$
Rayé
Équipe Mineure
1Brandon Halverson100.0072666871707172717170675952050650291775,000$
2T.J. Semptimphelter100.00595757635856555455585451500505302300$
MOYENNE D’ÉQUIPE99.007674757976757474747671676105069
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Paul Maurice1111111CAN5851$


Astuces sur les filtres (anglais seulement)
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
# Nom du joueur Nom de l’équipePOSGP 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
1Mike MathesonNew York RangersD478354311435726278334610.26%85113824.2351015381270000120220%000000.7600001313
2Brandon MontourNew York RangersD4712304295151203485274414.12%5199521.194913421220001139200%000000.8400010424
3Nathan MacKinnonNew York RangersC462121421114103699114277818.42%585718.653710171250003125151.34%104800000.9811101541
4Mark ScheifeleNew York RangersC47172441161755999129429513.18%585418.194812241220001172150.42%106300100.9601100324
5Lucas RaymondNew York RangersLW/RW47162238154026581365410111.76%382017.4553821122000002232.81%6400000.9300000161
6Brad MarchandNew York RangersC/LW/RW47132437142608045130359710.00%685218.154711301220000222034.88%8600000.8701000315
7Neal PionkNew York RangersD4711213211520964996286611.46%62113724.214610431260000126220%000000.5600000100
8Zach HymanNew York RangersLW/RW4714183231003946107248213.08%885018.093710251290000192036.92%6500000.7501000402
9Travis SanheimNew York RangersD47526315400774041151512.20%4268114.510000200002010%000000.9100000412
10Filip ForsbergNew York RangersLW479202942201004913334986.77%785318.15369401290001195148.45%9700000.6801000014
11Brent BurnsNew York RangersD4742327718039476324486.35%6199121.09246341240000134100%000000.5400000221
12Jake EvansNew York RangersC/RW478816-4100221018111449.88%1570114.920000100001191054.10%87800000.4600000110
13Frank VatranoNew York RangersLW/RW477714-4180674310334816.80%870414.990000500031133054.17%7200000.4000000101
14Mark JankowskiNew York RangersC/RW47751292011939121817.95%33036.4600000000001152.17%2300000.7900000011
15Jackson LaCombeNew York RangersD47381151605121346288.82%3771715.2600012000036000%000000.3100000000
16Casey CizikasNew York RangersC/LW464610714037463072913.33%74179.070000000021181056.71%52900000.4800000100
17Logan O'ConnorNew York RangersRW47459-4403344709535.71%569414.770000000021150046.94%4900000.2600000020
18Tyson JostNew York RangersC/LW/RW47213740169124916.67%12826.0200000000000044.00%5000000.2100000001
19Joakim KemellHartford Wolf Pack (NYR)RW1000-100000000%066.35000000000000100.00%10000000000000
Statistiques d’équipe totales ou en moyenne845165304469121365259819011481426103211.14%4111386116.4037671043151264000131118311151.38%402500100.6815212332430
Astuces sur les filtres (anglais seulement)
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
# Nom du gardien Nom de l’équipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Andrei VasilevskiyNew York Rangers3622930.8992.79208622979590100.60053511130
2Jonas JohanssonNew York Rangers149400.8992.807492135348000001235101
Statistiques d’équipe totales ou en moyenne50311330.8992.79283643132130701054746231


Astuces sur les filtres (anglais seulement)
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
Nom du joueur Nom de l’équipePOS Âge Date de naissance Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Andrei VasilevskiyNew York RangersG311994-07-25RUSNo228 Lbs6 ft4NoNoTrade2025-09-09NoYes32025-09-09FalseFalsePro & Farm7,125,000$3,451,172$7,125,000$3,451,172$No7,125,000$7,125,000$-------7,125,000$7,125,000$-------NoNo-------Lien NHL
Brad MarchandNew York RangersC/LW/RW371988-05-11CANNo180 Lbs5 ft9NoNoAssign ManuallyNoNo52025-07-02FalseFalsePro & Farm5,250,000$2,542,969$5,250,000$2,542,969$No5,250,000$5,250,000$5,250,000$5,250,000$-----5,250,000$5,250,000$5,250,000$5,250,000$-----NoNoNoNo-----Lien NHL
Brandon MontourNew York RangersD311994-04-11CANNo199 Lbs6 ft0NoNoAssign ManuallyNoNo52025-05-26FalseFalsePro & Farm7,142,857$3,459,821$7,142,857$3,459,821$No7,142,857$7,142,857$7,142,857$7,142,857$-----7,142,857$7,142,857$7,142,857$7,142,857$-----NoNoNoNo-----Lien NHL
Brent BurnsNew York RangersD401985-03-09CANNo228 Lbs6 ft5NoNoTrade2025-09-20NoNo12025-07-03FalseFalsePro & Farm1,000,000$484,375$1,000,000$484,375$No---------------------------Lien NHL
Casey CizikasNew York RangersC/LW341991-02-27CANNo194 Lbs5 ft11NoNoTrade2025-10-09NoNo22025-10-09FalseFalsePro & Farm1,250,000$605,469$1,250,000$605,469$No1,250,000$--------1,250,000$--------No--------Lien NHL
Filip ForsbergNew York RangersLW311994-08-13SWENo205 Lbs6 ft1NoNoAssign ManuallyNoNo52025-05-26FalseFalsePro & Farm8,500,000$4,117,188$8,500,000$4,117,188$No8,500,000$8,500,000$8,500,000$8,500,000$-----8,500,000$8,500,000$8,500,000$8,500,000$-----NoNoNoNo-----Lien NHL
Frank VatranoNew York RangersLW/RW311994-03-14USANo206 Lbs5 ft11NoNoAssign ManuallyNoNo32025-06-29FalseFalsePro & Farm4,571,189$2,214,170$4,571,189$2,214,170$No4,571,189$4,571,189$-------4,571,189$4,571,189$-------NoNo-------Lien NHL
Jackson LaCombeNew York RangersD252001-01-09USANo205 Lbs6 ft2NoNoTrade2025-09-20NoNo52025-10-03FalseFalsePro & Farm925,000$448,047$925,000$448,047$No9,000,000$9,000,000$9,000,000$9,000,000$-----9,000,000$9,000,000$9,000,000$9,000,000$-----NoNoNoNo-----Lien NHL
Jake EvansNew York RangersC/RW291996-06-02CANNo190 Lbs6 ft0NoNoAssign ManuallyNoNo42025-06-29FalseFalsePro & Farm2,850,000$1,380,469$2,850,000$1,380,469$No2,850,000$2,850,000$2,850,000$------2,850,000$2,850,000$2,850,000$------NoNoNo------Lien NHL
Jonas JohanssonNew York RangersG301995-09-19SWENo218 Lbs6 ft5NoNoAssign ManuallyNoYes22025-06-29FalseFalsePro & Farm1,250,000$605,469$1,250,000$605,469$No1,250,000$--------1,250,000$--------No--------Lien NHL
Logan O'ConnorNew York RangersRW291996-08-14USANo175 Lbs6 ft0NoNoAssign ManuallyNoNo52025-06-29FalseFalsePro & Farm2,500,000$1,210,938$2,500,000$1,210,938$No2,500,000$2,500,000$2,500,000$2,500,000$-----2,500,000$2,500,000$2,500,000$2,500,000$-----NoNoNoNo-----Lien NHL
Lucas RaymondNew York RangersLW/RW232002-03-28SWENo188 Lbs5 ft11NoNoAssign ManuallyNoNo52025-05-26FalseFalsePro & Farm8,075,000$3,911,328$8,075,000$3,911,328$No8,075,000$8,075,000$8,075,000$8,075,000$-----8,075,000$8,075,000$8,075,000$8,075,000$-----NoNoNoNo-----Lien NHL
Mark JankowskiNew York RangersC/RW311994-09-13CANNo212 Lbs6 ft4NoNoAssign ManuallyNoYes12025-05-26FalseFalsePro & Farm800,000$387,500$800,000$387,500$No---------------------------Lien NHL
Mark ScheifeleNew York RangersC321993-03-15CANNo207 Lbs6 ft3NoNoAssign ManuallyNoNo52025-05-26FalseFalsePro & Farm8,500,000$4,117,188$8,500,000$4,117,188$No8,500,000$8,500,000$8,500,000$8,500,000$-----8,500,000$8,500,000$8,500,000$8,500,000$-----NoNoNoNo-----Lien NHL
Mike MathesonNew York RangersD311994-02-27CANNo196 Lbs6 ft2NoNoAssign ManuallyNoNo52025-12-03FalseFalsePro & Farm4,875,000$2,361,328$4,875,000$2,361,328$No6,000,000$6,000,000$6,000,000$6,000,000$-----6,000,000$6,000,000$6,000,000$6,000,000$-----NoNoNoNo-----Lien NHL
Nathan MacKinnonNew York RangersC301995-09-01CANNo200 Lbs6 ft0NoNoAssign ManuallyNoNo52025-05-26FalseFalsePro & Farm12,600,000$6,103,125$12,600,000$6,103,125$No12,600,000$12,600,000$12,600,000$12,600,000$-----12,600,000$12,600,000$12,600,000$12,600,000$-----NoNoNoNo-----Lien NHL
Neal PionkNew York RangersD301995-07-29USANo190 Lbs6 ft0NoNoAssign ManuallyNoNo52025-06-29FalseFalsePro & Farm7,000,000$3,390,625$7,000,000$3,390,625$No7,000,000$7,000,000$7,000,000$7,000,000$-----7,000,000$7,000,000$7,000,000$7,000,000$-----NoNoNoNo-----Lien NHL
Travis SanheimNew York RangersD291996-03-29CANNo222 Lbs6 ft4NoNoTrade2025-09-21NoNo52025-05-26FalseFalsePro & Farm6,250,000$3,027,344$6,250,000$3,027,344$No6,250,000$6,250,000$6,250,000$6,250,000$-----6,250,000$6,250,000$6,250,000$6,250,000$-----NoNoNoNo-----Lien NHL
Tyson JostNew York RangersC/LW/RW271998-03-14CANNo187 Lbs5 ft11NoNoTrade2025-10-07NoYes12025-07-02FalseFalsePro & Farm775,000$375,391$775,000$375,391$No---------------------------Lien NHL
Zach HymanNew York RangersLW/RW331992-06-09CANNo206 Lbs6 ft1NoNoTrade2025-09-15NoNo32025-09-15FalseFalsePro & Farm4,125,000$1,998,047$4,125,000$1,998,047$No4,125,000$4,125,000$-------4,125,000$4,125,000$-------NoNo-------Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2030.70202 Lbs6 ft13.754,768,202$

Somme salaire 1e année Somme salaire 2e année Somme salaire 3e année Somme salaire 4e année Somme salaire 5e année
95,364,046$101,989,046$99,489,046$83,667,857$80,817,857$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Filip ForsbergNathan MacKinnonZach Hyman30122
2Brad MarchandMark ScheifeleLucas Raymond30122
3Frank VatranoJake EvansLogan O'Connor25122
4Tyson JostCasey CizikasMark Jankowski15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mike MathesonNeal Pionk30122
2Brandon MontourBrent Burns30122
3Jackson LaCombeTravis Sanheim25122
4Mike MathesonNeal Pionk15122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Filip ForsbergNathan MacKinnonZach Hyman50122
2Brad MarchandMark ScheifeleLucas Raymond50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mike MathesonNeal Pionk50122
2Brandon MontourBrent Burns50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jake EvansLogan O'Connor50122
2Casey CizikasFrank Vatrano50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mike MathesonNeal Pionk50122
2Brandon MontourBrent Burns50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jake Evans50122Mike MathesonNeal Pionk50122
2Logan O'Connor50122Brandon MontourBrent Burns50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Brad MarchandFilip Forsberg50122
2Mark ScheifeleZach Hyman50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mike MathesonNeal Pionk50122
2Brandon MontourBrent Burns50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Filip ForsbergNathan MacKinnonZach HymanMike MathesonNeal Pionk
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Filip ForsbergNathan MacKinnonZach HymanMike MathesonNeal Pionk
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nathan MacKinnon, Frank Vatrano, Jake EvansNathan MacKinnon, Frank VatranoJake Evans
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Mike Matheson, Neal Pionk, Brandon MontourMike MathesonNeal Pionk, Brandon Montour
Tirs de pénalité
Nathan MacKinnon, Mark Scheifele, Filip Forsberg, Zach Hyman, Brad Marchand
Gardien
#1 : Jonas Johansson, #2 : Andrei Vasilevskiy
Lignes d’attaque personnalisées en prolongation
Nathan MacKinnon, Mark Scheifele, Filip Forsberg, Zach Hyman, Brad Marchand, Lucas Raymond, Frank Vatrano, Jake Evans, Logan O'Connor, Casey Cizikas
Lignes de défense personnalisées en prolongation
Mike Matheson, Neal Pionk, Brandon Montour, Brent Burns, Jackson LaCombe


Astuces sur les filtres (anglais seulement)
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
TotalDomicileVisiteur
# VS Équipe 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
1Anaheim Ducks11000000541110000005410000000000021.000591400221031149802976173133.33%3166.67%0849164551.61%822155952.73%40779351.32%2316247126
2Boston Bruins2020000047-3000000000002020000047-300.000481200112054171621072211443400.00%6433.33%0849164551.61%822155952.73%40779351.32%422952142511
3Buffalo Sabres20002000972100010003211000100065141.00091827003222572317125742814556233.33%70100.00%0849164551.61%822155952.73%40779351.32%503549152512
4Calgary Flames11000000752000000000001100000075221.000714210023203615714028201225100.00%6183.33%0849164551.61%822155952.73%40779351.32%2315247126
5Carolina Hurricanes31200000711-4110000004222020000039-620.33371219003220782122350912627629222.22%10190.00%0849164551.61%822155952.73%40779351.32%704872203718
6Chicago Blackhawks11000000303000000000001100000030321.00036901012034516130144212000%10100.00%0849164551.61%822155952.73%40779351.32%3022166137
7Colorado Avalanche20200000610-41010000034-11010000036-300.00061016002400531526120642416516116.67%8275.00%0849164551.61%822155952.73%40779351.32%463349132311
8Columbus Blue Jackets1000010012-1000000000001000010012-110.5001230001002911143152141618000%80100.00%0849164551.61%822155952.73%40779351.32%2214287126
9Dallas Stars11000000321110000003210000000000021.00036900210035141110020910214125.00%5180.00%0849164551.61%822155952.73%40779351.32%2618216126
10Detroit Red Wings210000016601000000134-11100000032130.75061016002131501610209601116465240.00%8187.50%0849164551.61%822155952.73%40779351.32%493449142613
11Edmonton Oilers2010010057-21000010034-11010000023-110.25051015001310642520181632012508112.50%6183.33%0849164551.61%822155952.73%40779351.32%513744132613
12Florida Panthers1010000012-1000000000001010000012-100.00012300010023610702671418600.00%7271.43%0849164551.61%822155952.73%40779351.32%2417227126
13Minnesota Wild10001000211100010002110000000000021.0002460010013011973208022200.00%000%0849164551.61%822155952.73%40779351.32%2619217136
14Montreal Canadiens22000000853110000003121100000054141.0008152300332062202418046181245700.00%6266.67%0849164551.61%822155952.73%40779351.32%493443132613
15Nashville Predators2020000049-51010000025-31010000024-200.0004711001120651425260551212418112.50%6183.33%0849164551.61%822155952.73%40779351.32%523844132211
16New York Islanders21001000963110000005321000100043141.00091625002331661424271741416528450.00%8187.50%0849164551.61%822155952.73%40779351.32%483346142512
17Ottawa Senators11000000532000000000001100000053221.00051015002120341510901966253133.33%3166.67%0849164551.61%822155952.73%40779351.32%2517207147
18Philadelphia Flyers10001000211100010002110000000000021.000246000011359811722812194125.00%60100.00%0849164551.61%822155952.73%40779351.32%2719237136
19Pittsburgh Penguins220000001257110000007251100000053241.000122335005250741927280462520346466.67%8187.50%0849164551.61%822155952.73%40779351.32%513643122412
20San Jose Sharks11000000532110000005320000000000021.000571200122032169702514417000%20100.00%0849164551.61%822155952.73%40779351.32%2619216125
21Seattle Kraken220000001165110000004221100000074341.0001122330034407725331904214133311436.36%30100.00%0849164551.61%822155952.73%40779351.32%503545152412
22St. Louis Blues22000000624110000005231100000010141.0006121801312065182423046146366350.00%3166.67%0849164551.61%822155952.73%40779351.32%523742122513
23Tampa Bay Lightning211000006511010000023-11100000042220.500691500222055112420053182236400.00%11372.73%0849164551.61%822155952.73%40779351.32%503544132412
24Toronto Maple Leafs1010000028-6000000000001010000028-600.00023500101035910160511310134125.00%5180.00%0849164551.61%822155952.73%40779351.32%2315247125
25Utah Mammoth22000000927110000004131100000051441.000918270042308524204105011104310330.00%5260.00%0849164551.61%822155952.73%40779351.32%513643142512
26Vancouver Canucks21001000752100010005411100000021141.00071219001321601617234531521434125.00%5180.00%0849164551.61%822155952.73%40779351.32%554041132613
27Vegas Golden Knights211000007611010000034-11100000042220.5007142100043053112616052152536500.00%10280.00%0849164551.61%822155952.73%40779351.32%453250132311
28Washington Capitals3300000013310110000005052200000083561.00013223501634010831265106015217016425.00%60100.00%0849164551.61%822155952.73%40779351.32%825959213720
Total47251306201165133322111404101785424261490210087798650.69116530547003535353714804454945153113074113699831503724.67%1623081.48%0849164551.61%822155952.73%40779351.32%11798351073329591300
_Since Last GM Reset47251306201165133322111404101785424261490210087798650.69116530547003535353714804454945153113074113699831503724.67%1623081.48%0849164551.61%822155952.73%40779351.32%11798351073329591300
_Vs Conference2512704101857114951020013418161676021005153-2340.6808515423901302229576022224227823746224220536822125.61%991782.83%0849164551.61%822155952.73%40779351.32%617431581178318161
_Vs Division12720210044281654001000238157320110021201190.79244791230116111523901051211559345102112255431534.88%46393.48%0849164551.61%822155952.73%40779351.32%3022122738415177

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4765W11653054701480130741136998303
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4725136201165133
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2111441017854
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2614921008779
Derniers 10 matchs
WLOTWOTL SOWSOL
640000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1503724.67%1623081.48%0
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
445494515315353537
Mises en jeu
Gagnées en zone offensiveTotal en zone offensive% gagnées en zone offensive Gagnées en zone défensiveTotal en zone défensive% gagnées en zone défensiveGagnées en zone neutreTotal en zone neutre% gagnées en zone neutre
849164551.61%822155952.73%40779351.32%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
11798351073329591300


Derniers matchs joués
Astuces sur les filtres (anglais seulement)
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
JourMatch Équipe visiteuse Score Équipe locale Score ST OT SO RI Lien
12Pittsburgh Penguins2New York Rangers7WSommaire du match
39New York Rangers6Buffalo Sabres5WXSommaire du match
529New York Rangers5Pittsburgh Penguins3WSommaire du match
638Washington Capitals0New York Rangers5WSommaire du match
851Edmonton Oilers4New York Rangers3LXSommaire du match
1061New York Rangers2Toronto Maple Leafs8LSommaire du match
1280New York Rangers5Montreal Canadiens4WSommaire du match
1493Minnesota Wild1New York Rangers2WXSommaire du match
17116San Jose Sharks3New York Rangers5WSommaire du match
20146New York Rangers7Calgary Flames5WSommaire du match
22163New York Rangers2Vancouver Canucks1WSommaire du match
24175New York Rangers2Edmonton Oilers3LSommaire du match
26193New York Rangers7Seattle Kraken4WSommaire du match
29206Carolina Hurricanes2New York Rangers4WSommaire du match
32227New York Rangers3Detroit Red Wings2WSommaire du match
33237New York Islanders3New York Rangers5WSommaire du match
35253Nashville Predators5New York Rangers2LSommaire du match
37265New York Rangers4Tampa Bay Lightning2WSommaire du match
40290New York Rangers1Columbus Blue Jackets2LXSommaire du match
41299Detroit Red Wings4New York Rangers3LXXSommaire du match
43313New York Rangers4Vegas Golden Knights2WSommaire du match
45326New York Rangers3Colorado Avalanche6LSommaire du match
47344New York Rangers5Utah Mammoth1WSommaire du match
49355St. Louis Blues2New York Rangers5WSommaire du match
51368New York Rangers2Carolina Hurricanes6LSommaire du match
53376New York Rangers1Boston Bruins3LSommaire du match
54391Tampa Bay Lightning3New York Rangers2LSommaire du match
57415Dallas Stars2New York Rangers3WSommaire du match
59427New York Rangers5Ottawa Senators3WSommaire du match
61441Colorado Avalanche4New York Rangers3LSommaire du match
62458Vegas Golden Knights4New York Rangers3LSommaire du match
65476New York Rangers3Chicago Blackhawks0WSommaire du match
68500Montreal Canadiens1New York Rangers3WSommaire du match
70515Anaheim Ducks4New York Rangers5WSommaire du match
71523Vancouver Canucks4New York Rangers5WXSommaire du match
73541New York Rangers1St. Louis Blues0WSommaire du match
75549Philadelphia Flyers1New York Rangers2WXSommaire du match
76567New York Rangers2Nashville Predators4LSommaire du match
78576New York Rangers5Washington Capitals2WSommaire du match
82588New York Rangers4New York Islanders3WXSommaire du match
84608New York Rangers1Carolina Hurricanes3LSommaire du match
86622New York Rangers3Washington Capitals1WSommaire du match
88641New York Rangers1Florida Panthers2LSommaire du match
91662Utah Mammoth1New York Rangers4WSommaire du match
94685Buffalo Sabres2New York Rangers3WXSommaire du match
96697New York Rangers3Boston Bruins4LSommaire du match
98718Seattle Kraken2New York Rangers4WSommaire du match
100737Ottawa Senators-New York Rangers-
103755New York Rangers-Philadelphia Flyers-
105779New York Rangers-Anaheim Ducks-
106787New York Rangers-Los Angeles Kings-
109808New York Rangers-San Jose Sharks-
112826Boston Bruins-New York Rangers-
114842New York Rangers-New York Islanders-
115849New York Islanders-New York Rangers-
117861New York Rangers-Pittsburgh Penguins-
122906Carolina Hurricanes-New York Rangers-
143924Philadelphia Flyers-New York Rangers-
145934Pittsburgh Penguins-New York Rangers-
147953Columbus Blue Jackets-New York Rangers-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
150975Toronto Maple Leafs-New York Rangers-
152991New York Rangers-New Jersey Devils-
1541008New York Rangers-Philadelphia Flyers-
1551017Calgary Flames-New York Rangers-
1571036New York Rangers-Winnipeg Jets-
1591046New York Rangers-Minnesota Wild-
1611065Los Angeles Kings-New York Rangers-
1631077New Jersey Devils-New York Rangers-
1641086New York Rangers-Columbus Blue Jackets-
1671110Winnipeg Jets-New York Rangers-
1681119Ottawa Senators-New York Rangers-
1701136New York Rangers-Toronto Maple Leafs-
1721151Chicago Blackhawks-New York Rangers-
1741167Florida Panthers-New York Rangers-
1761182New Jersey Devils-New York Rangers-
1781195Montreal Canadiens-New York Rangers-
1801207Detroit Red Wings-New York Rangers-
1811227Washington Capitals-New York Rangers-
1841244Buffalo Sabres-New York Rangers-
1871268New York Rangers-Dallas Stars-
1891283New York Rangers-Florida Panthers-
1911302New York Rangers-Tampa Bay Lightning-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2Niveau 3Niveau 4Luxe
Capacité60005000200040002000
Prix des billets90604530190
Assistance120,496100,04240,26980,09940,275
Attendance PCT95.63%95.28%95.88%95.36%95.89%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
20 18151 - 95.53% 1,777,563$37,328,831$19000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineursValeur du plafond salarial spécial
49,192,744$ 95,364,046$ 95,364,046$ 1$0$ 0$
Plafond salarial par jourPlafond salarial à ce jourTaxe de luxe totaleJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
95,364,046$ 49,192,744$ 0$ 20 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
35,551,268$ 93 496,688$ 46,191,984$

Total de l’équipe estimé
Dépenses de la saison estimées Compte bancaire actuel Compte bancaire projeté
46,946,712$ 15,783,288$ 10,840,326$
Cap Salarial de la Saison estiméPlafond salarial disponiblePlafond salarial maximumAu dessus du plancher salarial
95,364,046$ 135,954$ 95,500,000$ 24,764,046$



Charte de profondeur

Ailier gaucheCentreAilier droit
Filip ForsbergAGE:31PO:0OV:82
Brad MarchandAGE:37PO:0OV:80
Lucas RaymondAGE:23PO:0OV:80
Zach HymanAGE:33PO:0OV:80
Frank VatranoAGE:31PO:0OV:79
Casey CizikasAGE:34PO:0OV:75
Tyson JostAGE:27PO:0OV:70
Brennan OthmannAGE:23PO:0OV:64
Reid SchaeferAGE:22PO:0OV:59
Nathan MacKinnonAGE:30PO:0OV:87
Mark ScheifeleAGE:32PO:0OV:83
Brad MarchandAGE:37PO:0OV:80
Jake EvansAGE:29PO:0OV:77
Casey CizikasAGE:34PO:0OV:75
Mark JankowskiAGE:31PO:0OV:73
Tyson JostAGE:27PO:0OV:70
Justin DowlingAGE:35PO:0OV:67
Matthew StienburgAGE:25PO:0OV:62
Brad LambertAGE:22PO:0OV:59
David GoyetteAGE:21PO:0OV:58
Brad MarchandAGE:37PO:0OV:80
Lucas RaymondAGE:23PO:0OV:80
Zach HymanAGE:33PO:0OV:80
Frank VatranoAGE:31PO:0OV:79
Jake EvansAGE:29PO:0OV:77
Logan O'ConnorAGE:29PO:0OV:75
Mark JankowskiAGE:31PO:0OV:73
Tyson JostAGE:27PO:0OV:70
Dominik ShineAGE:32PO:0OV:61
Danila KlimovichAGE:23PO:0OV:60
Joakim KemellAGE:21PO:0OV:60
Tyler BoucherAGE:22PO:0OV:57

Défense #1Défense #2Gardien
Mike MathesonAGE:31PO:0OV:82
Travis SanheimAGE:29PO:0OV:82
Brent BurnsAGE:40PO:0OV:80
Neal PionkAGE:30PO:0OV:80
Brandon MontourAGE:31PO:0OV:79
Jackson LaCombeAGE:25PO:0OV:78
Drew HellesonAGE:24PO:0OV:69
Marc Del GaizoAGE:26PO:0OV:69
Adam WilsbyAGE:25PO:0OV:67
Phil KempAGE:26PO:0OV:63
Artem DudaAGE:21PO:0OV:62
Nate ClurmanAGE:27PO:0OV:62
Hunter BrzustewiczAGE:21PO:0OV:61
Mikulas HovorkaAGE:24PO:0OV:61
Aidan FulpAGE:25PO:0OV:59
Marek AlscherAGE:21PO:0OV:59
Andrei VasilevskiyAGE:31PO:0OV:85
Jonas JohanssonAGE:30PO:0OV:73
Brandon HalversonAGE:29PO:0OV:65
T.J. SemptimphelterAGE:23PO:0OV:53

Espoirs

Astuces sur les filtres (anglais seulement)
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
EspoirNom de l’équipeAnnée de repêchageChoix totalInformationDate de la Dernière TransactionLien
Aidan ThompsonNew York Rangers2025289Fantasy DraftLien
Caden PriceNew York Rangers2025104Fantasy Draft2025-09-21Lien
E.J. EmeryNew York Rangers2025160Fantasy DraftLien
Lucas PetterssonNew York Rangers2025161Fantasy DraftLien
Maxim ShabanovNew York Rangers2025225Fantasy DraftLien
Milton GastrinNew York Rangers202596Fantasy DraftLien
Prokhor PoltapovNew York Rangers2025288Fantasy DraftLien

Choix au repêchage

Année R1R2R3R4R5R6R7
2026
2027
2028
2029
2030
Choix au repêchage conditionnel



Aucune nouvelle trouvée dans la base de données des nouvelles. Veuillez en créer une nouvelle.


New York Rangers Historique de transactions

[2025-12-23 08:00:54] New Record for Team's Most Shots (50) in 1 Game for New York Rangers!
[2025-12-06 08:42:12] New Record for Team's Most Hits (31) in 1 Game for New York Rangers!
[2025-11-22 09:49:58] New Record for Team's Most Shots (46) in 1 Game for New York Rangers!
[2025-11-18 08:03:17] New Record for Team's Most Penalties Minutes (19) in 1 Game for New York Rangers!
[2025-11-15 09:00:34] New Record for Team's Most Penalties Minutes (16) in 1 Game for New York Rangers!
[2025-10-26 09:56:11] New Record for Team's Most Penalties Minutes (12) in 1 Game for New York Rangers!
[2025-10-26 09:56:11] New Record for Team's Most Shots Blocked (20) in 1 Game for New York Rangers!
[2025-10-09 19:02:28] TRADE : From Philadelphia Flyers to New York Rangers : Casey Cizikas (75).
[2025-10-09 19:02:28] TRADE : From New York Rangers to Philadelphia Flyers : Oskar Sundqvist (74), Y:2026-RND:6-NYR.
[2025-10-09 08:02:57] New Record for Team's Most Hits (29) in 1 Game for New York Rangers!
[2025-10-09 08:02:57] New Record for Team's Most Shots Blocked (18) in 1 Game for New York Rangers!
[2025-10-09 08:02:57] New Record for Team's Most Shots Blocked (18) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Hits (18) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Penalties Minutes (10) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Shots Blocked (9) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Shots (45) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Points (21) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Assists (14) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Goals (7) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Penalties Minutes (10) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Shots (45) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Points (21) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Assists (14) in 1 Game for New York Rangers!
[2025-10-07 08:12:42] New Record for Team's Most Goals (7) in 1 Game for New York Rangers!
[2025-10-07 08:12:35] TRADE : From Anaheim Ducks to New York Rangers : Tyson Jost (70).
[2025-10-07 08:12:35] TRADE : From New York Rangers to Anaheim Ducks : Garnet Hathaway (75).
[2025-10-07 08:12:32] TRADE : From New York Rangers to Philadelphia Flyers : Erik Haula (76).
[2025-10-07 08:12:32] TRADE : From Philadelphia Flyers to New York Rangers : Y:2027-RND:3-FLA, Y:2022-RND:0-.
[2025-10-07 08:07:10] TRADE : From Anaheim Ducks to New York Rangers : Tyson Jost (70).
[2025-10-07 08:07:10] TRADE : From New York Rangers to Anaheim Ducks : Garnet Hathaway (75).
[2025-10-07 08:06:57] TRADE : From New York Rangers to Philadelphia Flyers : Erik Haula (76).
[2025-10-07 08:06:57] TRADE : From Philadelphia Flyers to New York Rangers : Y:2026-RND:3-PHI, Y:2022-RND:0-.
[2025-09-27 21:40:42] William Dufour was released.
[2025-09-27 21:40:42] William Dufour retired from New York Rangers
[2025-09-25 16:04:58] TRADE : From Minnesota Wild to New York Rangers : Erik Haula (76).
[2025-09-25 16:04:58] TRADE : From New York Rangers to Minnesota Wild : Y:2026-RND:2-NYR.
[2025-09-21 09:20:46] TRADE : From New York Rangers to Anaheim Ducks : Sam Dickinson (P).
[2025-09-21 09:20:46] TRADE : From Anaheim Ducks to New York Rangers : Travis Sanheim (82), Caden Price (P).
[2025-09-20 21:39:04] TRADE : From Ottawa Senators to New York Rangers : Jackson LaCombe (78), Sam Dickinson (P), Y:2026-RND:4-NYI.
[2025-09-20 21:39:04] TRADE : From New York Rangers to Ottawa Senators : Brock Faber (78), Cole Beaudoin (P), Y:2026-RND:3-NYR.
[2025-09-20 21:25:36] Garnet Hathaway was added to New York Rangers.
[2025-09-20 05:35:03] TRADE : From Columbus Blue Jackets to New York Rangers : Brent Burns (79).
[2025-09-20 05:35:03] TRADE : From New York Rangers to Columbus Blue Jackets : Nolan Allan (67), Y:2026-RND:5-NYR.
[2025-09-19 15:17:47] Conner Murphy was released.
[2025-09-19 15:17:47] Ales Stezka was released.
[2025-09-19 15:17:47] Nicky Leivermann was released.
[2025-09-19 15:17:47] Jere Innala was released.
[2025-09-19 15:17:47] Givani Smith was released.
[2025-09-19 15:17:47] Garnet Hathaway was released.
[2025-09-19 15:17:47] Brock McGinn was released.
[2025-09-19 15:17:47] Brian Pinho was released.
[2025-09-19 15:17:47] Anthony Angello was released.
[2025-09-15 21:17:12] TRADE : From New York Islanders to New York Rangers : Oskar Sundqvist (74), Zach Hyman (80).
[2025-09-15 21:17:12] TRADE : From New York Rangers to New York Islanders : Fabian Lysell (61), Morgan Barron (74), Danila Yurov (P).
[2025-09-10 23:10:45] Hartford Wolf Pack hired John Tortorella for $1 for 5 year(s).
[2025-09-10 23:10:37] New York Rangers hired Paul Maurice for $1 for 5 year(s).
[2025-09-09 11:23:05] TRADE : From Winnipeg Jets to New York Rangers : Andrei Vasilevskiy (85).
[2025-09-09 11:23:05] TRADE : From New York Rangers to Winnipeg Jets : Nikke Kokko (62), Maxim Strbak (P), Tom Willander (P), Y:2026-RND:1-NYR.



Pas de blessure ou de suspension.


New York Rangers Leaders statistiques des joueurs (saison régulière)

# Nom du joueur 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

New York Rangers Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

New York Rangers Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
Année 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

New York Rangers Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur 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

New York Rangers Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA