Connexion

islanders
GP: 19 | W: 9 | L: 8 | OTL: 2 | P: 20
GF: 71 | GA: 71 | PP%: 26.67% | PK%: 80.88%
DG: David Mapp | Morale : 50 | Moyenne d’équipe : 67
Prochain matchs #307 vs Binghamton Senateurs
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Centre de jeu
Condors
9-8-1, 19pts
7
FINAL
2 islanders
9-8-2, 20pts
Team Stats
L1StreakSOL1
5-4-1Home Record4-3-2
4-4-0Away Record5-5-0
4-6-0Last 10 Games4-5-1
3.06Buts par match 3.74
2.61Buts contre par match 3.74
19.44%Pourcentage en avantage numérique26.67%
84.21%Pourcentage en désavantage numérique80.88%
Americans
11-6-3, 25pts
3
FINAL
2 islanders
9-8-2, 20pts
Team Stats
W8StreakSOL1
5-2-2Home Record4-3-2
6-4-1Away Record5-5-0
8-2-0Last 10 Games4-5-1
3.55Buts par match 3.74
3.50Buts contre par match 3.74
15.28%Pourcentage en avantage numérique26.67%
81.08%Pourcentage en désavantage numérique80.88%
islanders
9-8-2, 20pts
2022-11-28
Binghamton Senateurs
9-9-1, 19pts
Statistiques d’équipe
SOL1SéquenceW2
4-3-2Fiche domicile4-4-1
5-5-0Fiche visiteur5-5-0
4-5-110 derniers matchs5-4-1
3.74Buts par match 3.53
3.74Buts contre par match 3.79
26.67%Pourcentage en avantage numérique17.50%
80.88%Pourcentage en désavantage numérique78.13%
Wolf Pack
11-6-2, 24pts
2022-11-30
islanders
9-8-2, 20pts
Statistiques d’équipe
W2SéquenceSOL1
6-3-0Fiche domicile4-3-2
5-3-2Fiche visiteur5-5-0
5-3-210 derniers matchs4-5-1
4.42Buts par match 3.74
3.53Buts contre par match 3.74
24.24%Pourcentage en avantage numérique26.67%
77.61%Pourcentage en désavantage numérique80.88%
islanders
9-8-2, 20pts
2022-12-02
Phantoms
9-8-1, 19pts
Statistiques d’équipe
SOL1SéquenceL1
4-3-2Fiche domicile4-5-1
5-5-0Fiche visiteur5-3-0
4-5-110 derniers matchs6-4-0
3.74Buts par match 3.39
3.74Buts contre par match 3.28
26.67%Pourcentage en avantage numérique15.49%
80.88%Pourcentage en désavantage numérique72.55%
Meneurs d'équipe
Victoires
Eetu Makiniemi
9
Pourcentage d’arrêts
Pyotr Kochetkov
0.947

Statistiques d’équipe
Buts pour
71
3.74 GFG
Tirs pour
683
35.95 Avg
Pourcentage en avantage numérique
26.7%
20 GF
Début de zone offensive
40.2%
Buts contre
71
3.74 GAA
Tirs contre
727
38.26 Avg
Pourcentage en désavantage numérique
80.9%
13 GA
Début de la zone défensive
40.5%
Information d’équipe

Directeur généralDavid Mapp
EntraîneurDaniel Sedin
DivisionMETROPOLITAINE
ConférenceEST
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,985
Billets de saison300


Information formation

Équipe Pro29
Équipe Mineure21
Limite contact 50 / 55
Espoirs17


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
1Logan Brown0X100.008475806496787967756864656366680507202442,421,000$
2Aliaksei Protas0X100.00805292639779836375626163596163050700212883,333$
3Fabian Zetterlund0X100.00663791677688876663686562676365050700231925,000$
4MacKenzie Entwistle0X100.00774582648076816257646166626467050690231894,167$
5Jesse Ylonen0X100.00583682697083846862676364686365050690231925,000$
6Michael Dal Colle0X100.00723888628281706358625961656668050680262814,000$
7Serron Noel0X100.00844567579371925856575459556264050670222894,167$
8Henrik Borgstrom0X97.005837876183787662776064576265670506602532,456,000$
9Jimmy Huntington0X100.006639826075728759686158605964660506602421,768,000$
10Trey Fix-Wolansky0X100.00623880646386826364616260636465050660231925,000$
11William Lockwood0X100.008238765967798157635859625964660506602411,156,250$
12Linus Weissbach0X99.00563784596773856257605853596466050640242925,000$
13Ian Mitchell0X98.006335926869818966306762645263650506902321,775,000$
14Gavin Bayreuther0X99.00685176617781766230715964516870050690281750,000$
15Mattias Norlinder0X100.00613687667177656330645861506264050660223925,000$
16Samuel Bolduc0X100.007739825489688354305755594762640506502141,965,000$
17David Farrance0X100.005836946270837561306056634862650506502311,350,000$
18Tyler Tucker0X100.00693466557875815330565351466264050620222803,333$
Rayé
1Evan Barratt0X100.00633372567478855766585956586365050640232925,000$
2Gabriel Fortier0X98.00733585566676855764585960636264050640222880,000$
3Alex Beaucage0X100.00673982587681685554565558596163050630213925,000$
4Ivan Lodnia0X100.00643786577377665652545553586365050620231871,667$
5Philippe Daoust (R)0X100.00563692566569625568595153576163050600211700,000$
6Reece Newkirk0X100.00613975537069615262545055536163050590213823,333$
MOYENNE D’ÉQUIPE99.6368408360767778605561586058636505066
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
1Eetu Makiniemi100.0074697077737274737274736369050740232925,000$
2Pyotr Kochetkov (R)100.0072737284717072717072716369050730232925,000$
Rayé
1Arturs Silovs100.0068666786676668676668676165050700212796,111$
2Trent Miner100.0069676674686769686769686165050690212828,333$
3Filip Lindberg100.0068666772676668676668676369050690232925,000$
MOYENNE D’ÉQUIPE100.007068687969687069687069626705071
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Daniel Sedin75757575757575Sue4250$


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
1Jesse Ylonenislanders (NYI)RW1771522-340174470205810.00%333919.98371013530000172146.30%5400001.3011000121
2Mattias Norlinderislanders (NYI)D19612186140292938122515.79%2340221.212462663000150100.00%000000.8900000110
3Aliaksei Protasislanders (NYI)C17511169100173744133811.36%434620.4022414560000350055.98%49300000.9202000021
4Henrik Borgstromislanders (NYI)C196814-42084252203411.54%532617.1942615510000290155.18%47300000.8600000011
5MacKenzie Entwistleislanders (NYI)RW1941014-910027265714417.02%235118.4822414510000311140.00%3500000.8001000100
6Michael Dal Colleislanders (NYI)LW1710414080222255212718.18%431618.632247500001230053.85%2600000.8800000100
7Logan Brownislanders (NYI)C1376133155342545113815.56%226020.000225410001231051.63%21500001.0000001202
8David Farranceislanders (NYI)D194913140161925101716.00%2436919.451561342000047100.00%000000.7000000100
9Gavin Bayreutherislanders (NYI)D1921012-618051254013305.00%2646124.291231661000149100.00%000000.5200000020
10Ian Mitchellislanders (NYI)D192911-62017423720295.41%3747124.821122163000060000.00%000000.4700000002
11Trey Fix-Wolanskyislanders (NYI)RW195611-40011305112369.80%1126113.75112310000080047.37%5700000.8401000110
12Samuel Bolducislanders (NYI)D193811-12004182281213.64%3431416.54112725000018000.00%000000.7000000122
13Fabian Zetterlundislanders (NYI)LW163691008244612316.52%129918.720228320003360051.39%7200000.6001000010
14Gabriel Fortierislanders (NYI)LW133582407112771711.11%519214.8301159000081136.36%1100000.8301000000
15Jimmy Huntingtonislanders (NYI)C19325-611511242982710.34%322311.7800000000001048.38%27700000.4500010001
16Serron Noelislanders (NYI)RW17145-5140278207165.00%718610.990221130000100030.43%2300000.5400000101
17Tyler Tuckerislanders (NYI)D19022-51803974230.00%2126814.140000200007000.00%000000.1500000000
18William Lockwoodislanders (NYI)RW1902234012512390.00%4834.4200027000000066.67%900000.4801000000
19Linus Weissbachislanders (NYI)LW8022-2003274100.00%08110.1901109000050033.33%300000.4900000000
20Evan Barrattislanders (NYI)C9000-200442030.00%0394.3500000000000039.66%5800000.0000000000
Statistiques d’équipe totales ou en moyenne33671131202-281581040143468321750110.40%216559816.6620375717064800074689452.05%180600000.7218011101211
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
1Eetu Makiniemiislanders (NYI)189810.9003.7996500616110010.3333181200
2Pyotr Kochetkovislanders (NYI)50010.9471.961840061140010.6676118000
Statistiques d’équipe totales ou en moyenne239820.9083.50114900677250020.55691919200


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 Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire restantSalaire moyenPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Alex Beaucageislanders (NYI)RW212001-07-25No192 Lbs6 ft1NoNoNo3Pro & Farm925,000$711,155$700,000$0$0$No925,000$925,000$Lien
Aliaksei Protasislanders (NYI)C212001-01-06No225 Lbs6 ft6NoNoNo2Pro & Farm883,333$679,121$883,333$0$0$No883,333$Lien
Arturs Silovsislanders (NYI)G212001-03-22No203 Lbs6 ft4NoNoNo2Pro & Farm796,111$612,063$796,111$0$0$No796,111$Lien
David Farranceislanders (NYI)D231999-06-23No189 Lbs5 ft11NoNoNo1Pro & Farm1,350,000$1,037,903$700,000$0$0$NoLien
Eetu Makiniemiislanders (NYI)G231999-04-19No184 Lbs6 ft2NoNoNo2Pro & Farm925,000$711,155$700,000$0$0$No925,000$Lien
Evan Barrattislanders (NYI)C231999-02-18No188 Lbs6 ft0NoNoNo2Pro & Farm925,000$711,155$925,000$0$0$No925,000$Lien
Fabian Zetterlundislanders (NYI)LW231999-08-25No220 Lbs5 ft11NoNoNo1Pro & Farm925,000$711,155$809,169$0$0$NoLien
Filip Lindbergislanders (NYI)G231999-01-31No180 Lbs6 ft0NoNoNo2Pro & Farm925,000$711,155$700,000$0$0$No925,000$Lien
Gabriel Fortierislanders (NYI)LW222000-02-06No173 Lbs5 ft10NoNoNo2Pro & Farm880,000$676,559$880,000$0$0$No880,000$Lien
Gavin Bayreutherislanders (NYI)D281994-05-12No196 Lbs6 ft1NoNoNo1Pro & Farm750,000$576,612$650,000$0$0$NoLien
Henrik Borgstromislanders (NYI)C251997-08-06No199 Lbs6 ft3NoNoNo3Pro & Farm2,456,000$1,888,215$650,000$0$0$No2,456,000$2,456,000$Lien
Ian Mitchellislanders (NYI)D231999-01-18No173 Lbs5 ft11NoNoNo2Pro & Farm1,775,000$1,364,650$1,775,000$0$0$No1,775,000$Lien
Ivan Lodniaislanders (NYI)RW231999-08-31No202 Lbs5 ft11NoNoNo1Pro & Farm871,667$670,152$700,000$0$0$NoLien
Jesse Ylonenislanders (NYI)RW231999-10-03No167 Lbs6 ft0NoNoNo1Pro & Farm925,000$711,155$925,000$0$0$NoLien
Jimmy Huntingtonislanders (NYI)C241998-11-18No204 Lbs6 ft0NoNoNo2Pro & Farm1,768,000$1,359,268$812,500$0$0$No1,768,000$Lien
Linus Weissbachislanders (NYI)LW241998-04-19No177 Lbs5 ft9NoNoNo2Pro & Farm925,000$711,155$700,000$0$0$No925,000$Lien
Logan Brownislanders (NYI)C241998-03-05No218 Lbs6 ft6NoNoNo4Pro & Farm2,421,000$1,861,306$650,000$0$0$No2,421,000$2,421,000$2,421,000$Lien
MacKenzie Entwistleislanders (NYI)RW231999-07-14No184 Lbs6 ft3NoNoNo1Pro & Farm894,167$687,450$650,000$0$0$NoLien
Mattias Norlinderislanders (NYI)D222000-04-12No185 Lbs6 ft0NoNoNo3Pro & Farm925,000$711,155$700,000$0$0$No925,000$925,000$Lien
Michael Dal Colleislanders (NYI)LW261996-06-20No195 Lbs6 ft3NoNoNo2Pro & Farm814,000$625,817$700,000$0$0$No814,000$Lien
Philippe Daoustislanders (NYI)C212001-05-11Yes151 Lbs6 ft0NoNoNo1Pro & Farm700,000$538,172$700,000$0$0$No
Pyotr Kochetkovislanders (NYI)G231999-06-25Yes205 Lbs6 ft3NoNoNo2Pro & Farm925,000$711,155$700,000$0$0$No925,000$
Reece Newkirkislanders (NYI)C212001-02-20No178 Lbs6 ft0NoNoNo3Pro & Farm823,333$632,992$700,000$0$0$No823,333$823,333$Lien
Samuel Bolducislanders (NYI)D212000-12-09No213 Lbs6 ft4NoNoNo4Pro & Farm1,965,000$1,510,725$925,000$0$0$No1,965,000$1,965,000$1,965,000$Lien
Serron Noelislanders (NYI)RW222000-08-08No216 Lbs6 ft5NoNoNo2Pro & Farm894,167$687,450$700,000$0$0$No894,167$Lien
Trent Minerislanders (NYI)G212001-02-05No185 Lbs6 ft1NoNoNo2Pro & Farm828,333$636,836$828,333$0$0$No828,333$Lien
Trey Fix-Wolanskyislanders (NYI)RW231999-05-26No186 Lbs5 ft7NoNoNo1Pro & Farm925,000$711,155$809,168$0$0$NoLien
Tyler Tuckerislanders (NYI)D222000-03-01No203 Lbs6 ft1NoNoNo2Pro & Farm803,333$617,616$803,333$0$0$No803,333$Lien
William Lockwoodislanders (NYI)RW241998-06-20No172 Lbs5 ft11NoNoNo1Pro & Farm1,156,250$888,944$925,000$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2922.86192 Lbs6 ft11.971,106,196$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Logan BrownAliaksei ProtasWilliam Lockwood30113
2Linus WeissbachFabian ZetterlundJesse Ylonen30113
3MacKenzie EntwistleJimmy HuntingtonTrey Fix-Wolansky24122
4MacKenzie EntwistleAliaksei ProtasWilliam Lockwood16122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ian MitchellGavin Bayreuther30122
2Mattias NorlinderSamuel Bolduc30122
3David FarranceTyler Tucker24122
4Ian MitchellGavin Bayreuther16122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1William LockwoodAliaksei ProtasMacKenzie Entwistle50122
2Linus WeissbachLogan BrownJesse Ylonen50122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ian MitchellGavin Bayreuther50122
2Mattias NorlinderSamuel Bolduc50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Aliaksei ProtasMacKenzie Entwistle50122
2William LockwoodLinus Weissbach50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ian MitchellGavin Bayreuther50122
2Mattias NorlinderSamuel Bolduc50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Aliaksei Protas50122Ian MitchellGavin Bayreuther50122
2MacKenzie Entwistle50122Mattias NorlinderSamuel Bolduc50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Aliaksei ProtasMacKenzie Entwistle50122
2William LockwoodLinus Weissbach50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ian MitchellGavin Bayreuther50122
2Mattias NorlinderSamuel Bolduc50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Logan BrownAliaksei ProtasMacKenzie EntwistleIan MitchellGavin Bayreuther
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Logan BrownAliaksei ProtasMacKenzie EntwistleIan MitchellGavin Bayreuther
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
William Lockwood, Aliaksei Protas, Jimmy HuntingtonWilliam Lockwood, Aliaksei ProtasWilliam Lockwood
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Samuel Bolduc, David Farrance, Tyler TuckerSamuel BolducSamuel Bolduc, David Farrance
Tirs de pénalité
Aliaksei Protas, MacKenzie Entwistle, Jesse Ylonen, Trey Fix-Wolansky, William Lockwood
Gardien
#1 : Pyotr Kochetkov, #2 : Eetu Makiniemi
Lignes d’attaque personnalisées en prolongation
Aliaksei Protas, MacKenzie Entwistle, Jesse Ylonen, Trey Fix-Wolansky, William Lockwood, Logan Brown, Logan Brown, Jimmy Huntington, Fabian Zetterlund, Linus Weissbach, Michael Dal Colle
Lignes de défense personnalisées en prolongation
Ian Mitchell, Gavin Bayreuther, Mattias Norlinder, Samuel Bolduc, David Farrance


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
1Americans1000000123-11000000123-10000000000010.50024600281824256221213243143266176233.33%30100.00%039172154.23%38372652.75%16634747.84%456315447141246125
2Bears220000001073110000005321100000054141.00010192900281824273221213243147523204113646.15%10370.00%039172154.23%38372652.75%16634747.84%456315447141246125
3Comets20101000810-2100010004311010000047-320.5008142200281824271221213243149120193810110.00%6183.33%039172154.23%38372652.75%16634747.84%456315447141246125
4Condors1010000027-51010000027-50000000000000.000246002818242392212132431446146273133.33%3233.33%039172154.23%38372652.75%16634747.84%456315447141246125
5Marlies1010000047-3000000000001010000047-300.0004812002818242442212132431438148236116.67%4175.00%039172154.23%38372652.75%16634747.84%456315447141246125
6Monsters220000001147110000005231100000062441.0001119300028182429122121324314651716403133.33%7185.71%039172154.23%38372652.75%16634747.84%456315447141246125
7Phantoms210000016601000000134-11100000032130.75061016002818242532212132431481322233300.00%8187.50%039172154.23%38372652.75%16634747.84%456315447141246125
8W-B/Scranton Penguins31200000121021010000024-221100000106420.333122436102818242103221213243149622176014535.71%6183.33%039172154.23%38372652.75%16634747.84%456315447141246125
9Wolf Pack321000001082110000004132110000067-140.667101828102818242882212132431411339206815320.00%100100.00%039172154.23%38372652.75%16634747.84%456315447141246125
10Wolves2020000069-31010000034-11010000035-200.00061117002818242652212132431490292454200.00%11372.73%039172154.23%38372652.75%16634747.84%456315447141246125
Total19880100271710933010023031-110550000041401200.5267113120220281824268322121324314727216158401752026.67%681380.88%039172154.23%38372652.75%16634747.84%456315447141246125
_Since Last GM Reset19880100271710933010023031-110550000041401200.5267113120220281824268322121324314727216158401752026.67%681380.88%039172154.23%38372652.75%16634747.84%456315447141246125
_Vs Conference18870100269645832010022824410550000041401200.5566912719620281824264422121324314681202152374721926.39%651183.08%039172154.23%38372652.75%16634747.84%456315447141246125
_Vs Division1686010016354973201001262159540000037334190.5946311517820281824254422121324314611182138334601626.67%581082.76%039172154.23%38372652.75%16634747.84%456315447141246125

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1920SOL17113120268372721615840120
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
198810027171
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
93310023031
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
105500004140
Derniers 10 matchs
WLOTWOTL SOWSOL
450001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
752026.67%681380.88%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
221213243142818242
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
39172154.23%38372652.75%16634747.84%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
456315447141246125


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
1 - 2022-10-166islanders2W-B/Scranton Penguins4ALSommaire du match
3 - 2022-10-1814islanders4Wolf Pack6ALSommaire du match
4 - 2022-10-1931Monsters2islanders5BWSommaire du match
6 - 2022-10-2143islanders3Phantoms2AWSommaire du match
8 - 2022-10-2358Phantoms4islanders3BLXXSommaire du match
11 - 2022-10-2678islanders8W-B/Scranton Penguins2AWSommaire du match
13 - 2022-10-2892Comets3islanders4BWXSommaire du match
15 - 2022-10-30101islanders3Wolves5ALSommaire du match
20 - 2022-11-04124Wolf Pack1islanders4BWSommaire du match
21 - 2022-11-05146islanders4Marlies7ALSommaire du match
23 - 2022-11-07155W-B/Scranton Penguins4islanders2BLSommaire du match
25 - 2022-11-09178Bears3islanders5BWSommaire du match
28 - 2022-11-12189islanders4Comets7ALSommaire du match
31 - 2022-11-15205islanders6Monsters2AWSommaire du match
33 - 2022-11-17219Wolves4islanders3BLSommaire du match
36 - 2022-11-20241islanders2Wolf Pack1AWSommaire du match
37 - 2022-11-21249islanders5Bears4AWSommaire du match
39 - 2022-11-23268Condors7islanders2BLSommaire du match
40 - 2022-11-24284Americans3islanders2BLXXSommaire du match
44 - 2022-11-28307islanders-Binghamton Senateurs-
46 - 2022-11-30316Wolf Pack-islanders-
48 - 2022-12-02330islanders-Phantoms-
50 - 2022-12-04344Providence Bruins-islanders-
51 - 2022-12-05352islanders-Eagles-
53 - 2022-12-07372islanders-Checkers-
55 - 2022-12-09381Wolves-islanders-
58 - 2022-12-12394islanders-Monsters-
59 - 2022-12-13409Marlies-islanders-
62 - 2022-12-16421islanders-Phantoms-
64 - 2022-12-18441Crunch-islanders-
65 - 2022-12-19459islanders-W-B/Scranton Penguins-
68 - 2022-12-22475Americans-islanders-
74 - 2022-12-28501islanders-Silver Knights-
75 - 2022-12-29507W-B/Scranton Penguins-islanders-
78 - 2023-01-01533Monsters-islanders-
81 - 2023-01-04551islanders-Griffins-
84 - 2023-01-07561islanders-Barracuda-
85 - 2023-01-08572IceHogs-islanders-
88 - 2023-01-11594islanders-Comets-
90 - 2023-01-13607Griffins-islanders-
92 - 2023-01-15628islanders-Wolves-
93 - 2023-01-16637islanders-Americans-
94 - 2023-01-17649Wolves-islanders-
96 - 2023-01-19665Wranglers-islanders-
99 - 2023-01-22685islanders-Providence Bruins-
101 - 2023-01-24698Monsters-islanders-
103 - 2023-01-26722islanders-Admirals-
104 - 2023-01-27733Checkers-islanders-
107 - 2023-01-30755islanders-Wolves-
108 - 2023-01-31766Monsters-islanders-
110 - 2023-02-02782islanders-Moose-
112 - 2023-02-04796Wolf Pack-islanders-
115 - 2023-02-07820Rockets-islanders-
117 - 2023-02-09830islanders-Rockets-
121 - 2023-02-13855Thunderbirds-islanders-
123 - 2023-02-15871islanders-W-B/Scranton Penguins-
127 - 2023-02-19888W-B/Scranton Penguins-islanders-
129 - 2023-02-21912Comets-islanders-
131 - 2023-02-23930islanders-Monsters-
132 - 2023-02-24944Iowa Wild-islanders-
136 - 2023-02-28959islanders-Texas Stars-
137 - 2023-03-01976islanders-Crunch-
139 - 2023-03-03983Reign-islanders-
143 - 2023-03-071002islanders-W-B/Scranton Penguins-
145 - 2023-03-091017islanders-Wolf Pack-
146 - 2023-03-101026Binghamton Senateurs-islanders-
148 - 2023-03-121045islanders-Wolf Pack-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-03-131054Admirals-islanders-
152 - 2023-03-161078Comets-islanders-
156 - 2023-03-201101islanders-Roadrunners-
158 - 2023-03-221114Gulls-islanders-
161 - 2023-03-251137Bears-islanders-
163 - 2023-03-271148islanders-Bears-
164 - 2023-03-281162islanders-Crunch-
166 - 2023-03-301180Bears-islanders-
170 - 2023-04-031204Firebirds-islanders-
171 - 2023-04-041214islanders-Bears-
174 - 2023-04-071233Phantoms-islanders-
178 - 2023-04-111259Phantoms-islanders-
179 - 2023-04-121261islanders-Comets-
181 - 2023-04-141284islanders-Comets-
184 - 2023-04-171306Canucks-islanders-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3525
Assistance13,4394,426
Assistance PCT74.66%49.18%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
32 1985 - 66.17% 96,190$865,712$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 3,207,969$ 2,309,694$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
3,078,087$ 143 17,247$ 2,466,321$




islanders Leaders statistiques (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

islanders 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

islanders 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

islanders Leaders statistiques (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

islanders 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