Islanders

GP: 78 | W: 41 | L: 29 | OTL: 8 | P: 90
GF: 233 | GA: 226 | PP%: 24.19% | PK%: 80.53%
DG: Libre | Morale : 66 | Moyenne d'Équipe : 66
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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 SP
1Ryan StromeX100.006240878075829280867781847778747781760
2Valeri NichushkinX100.005237938181767974617678787275718574730
3Blake Coleman (R)X100.008744727369819566786664775467595675690
4Ryan Dzingel (R)X100.006542828068859472676774615775544783690
5Jared McCann (R)X100.006342787573818269737065675668538184670
6Tanner Kero (R)X100.005234847772667362735959785962665884650
7Jordan Nolan (R)X100.007645697083748760566361606465594084640
8Darren Archibald (R)X100.007042806681766961546062755165513676640
9Anders Bjork (R)X100.006041827267766865656663625166515640630
10Andrew Miller (R)X100.007174616861666763597062636372686584630
11William Carrier (R)X100.008841756979726360606261625365576784630
12Ben Street (R)X100.006442747272565764806263656674715582630
13Chris TanevX100.006141927880837775307171965082773669760
14John MooreX100.007543867078859772306776856770616884740
15Brenden Dillon (R)X100.008544766787809671306867796369683684730
16Derrick Pouliot (R)X100.006741856674818791308583687175708584730
17Nick Jensen (R)X100.006542846669779670306965725562534184680
18Anthony Bitetto (R)X100.006842796679786577306469685867664165670
Rayé
1Colin White (R)X100.005944726370669160656060605162518264610
2Alexander Nylander (R)X100.005541776069598059506056605056508920580
3Riley Barber (R)X100.004735807174454458305155535559517919540
4Blake Speers (R)X100.003728917169454038283333684853499520480
5Markus Nutivaara (R)X100.006341856771778377307370625565534819660
6Justin Holl (R)X100.006443725079609158306055695055506720610
7Oliver Kylington (R)X100.005058767167535849254241575560605320550
MOYENNE D'ÉQUIPE100.00644380707471776650646469586760626365
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 SP
1Mike Condon (R)100.00798883818093919098828477683675830
2Harri Sateri (R)100.00747792827691818080725172634984770
Rayé
MOYENNE D'ÉQUIPE100.0077838882789286858977687566438080
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John Tortorella64696866999977USA602800,000$


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 GP 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
1Ryan StromeIslanders (NYI)C80315283022012522730311417910.23%37172821.601324375024701152545154.79%15047233010.96316000936
2Valeri NichushkinIslanders (NYI)RW733145764401061703109719610.00%42154921.231624406324802292395241.29%3736327110.98412000583
3Ryan Dzingel Islanders (NYI)RW78362561-33801641333069019411.76%34152319.53612183122210141658241.41%1286525000.80310000775
4Derrick PouliotIslanders (NYI)D8294049162609213316981885.33%80174421.2721416182710002148200.00%04645000.5611000114
5Jared McCannIslanders (NYI)C78113243-4740155212196621135.61%40137217.595914232090003530048.72%14473822010.6312000112
6Blake ColemanIslanders (NYI)LW7818234141300210150139347412.95%47154519.82812202928800021212151.11%8551039200.5326000002
7John MooreIslanders (NYI)D7882432-12601491649549438.42%105187123.997613172720001246000.00%01657000.3401000023
8Chris TanevIslanders (NYI)D7732528-12558814513141432.29%103163421.222572117811210238100.00%04453000.3400001004
9Tanner Kero Islanders (NYI)LW7817926-71408993113437115.04%23123415.82741112180000021046.97%661424000.4200000031
10Brenden DillonIslanders (NYI)D7841721196001731579035474.44%93168421.6013481970000191000.00%02160000.2500000012
11Jordan NolanIslanders (NYI)LW786121816801889110840625.56%21107113.740000450001761146.43%561321000.3400000012
12Ben StreetIslanders (NYI)C789817-452107710215145905.96%1486411.0800000000292050.41%6152615000.3900011011
13Andrew MillerIslanders (NYI)C7831114-726080457434514.05%175917.59000070000350142.59%54139000.4700000000
14Darren ArchibaldIslanders (NYI)RW7841014-4280127888236584.88%2395012.19022134000001143.24%371423000.2900000110
15Anthony BitettoIslanders (NYI)D7511112-2338077837325301.37%69107814.38000013000135010.00%01632000.2200000100
16Nick JensenIslanders (NYI)D78189-2039549966128261.64%76113614.56000023000025000.00%01236000.1600001000
17William CarrierIslanders (NYI)LW78617-1016092466814248.82%186017.71000030003641047.06%17911000.2300000000
18Colin WhiteIslanders (NYI)C67044-121002041207170.00%104426.6000002000020043.10%174011000.1800000000
19Anders BjorkIslanders (NYI)RW11202120351741011.76%2938.48000020001180033.33%920000.4300000000
20Riley BarberIslanders (NYI)RW5000-300045020.00%2346.840000100000000.00%000000.0000000000
21Markus NutivaaraIslanders (NYI)D4000120544210.00%65714.350000000000000.00%032000.0000000000
Stats d'équipe Total ou en Moyenne1410200357557-646802020692189251588114197.95%8622280916.18671151822732449246441928291049.95%5335497545330.491448013252935
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
1Mike CondonIslanders (NYI)57292170.9152.673410611521793789310.742315711754
2Harri SateriIslanders (NYI)71200.8883.46260001513463100.0000276000
Stats d'équipe Total ou en Moyenne64302370.9132.733670611671927852410.742315987754


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Alexander NylanderIslanders (NYI)LW211998-03-02 09:06:12Yes181 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm894,166$0$0$No
Anders BjorkIslanders (NYI)RW221996-08-05 11:08:17Yes186 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm1,066,670$0$0$No
Andrew MillerIslanders (NYI)C301988-09-18 05:11:13Yes184 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm575,000$0$0$No
Anthony BitettoIslanders (NYI)D281990-07-15 17:11:13Yes210 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm700,000$0$0$No
Ben StreetIslanders (NYI)C321987-02-13 23:11:13Yes199 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm575,000$0$0$No
Blake ColemanIslanders (NYI)LW271991-11-28 09:08:43Yes201 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm660,000$0$0$No
Blake SpeersIslanders (NYI)RW221997-01-02 09:11:02Yes189 Lbs5 ft11NoNoNo2Contrat d'EntréePro & Farm728,333$0$0$No
Brenden DillonIslanders (NYI)D281990-11-13 12:29:45Yes227 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm3,270,000$0$0$No
Chris TanevIslanders (NYI)D291989-12-20 11:11:13No195 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm2,500,000$0$0$No
Colin WhiteIslanders (NYI)C221997-01-30 09:13:28Yes184 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm925,000$0$0$No
Darren ArchibaldIslanders (NYI)RW291990-02-09 03:35:07Yes210 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm650,000$0$0$No
Derrick PouliotIslanders (NYI)D251994-01-16 17:11:13Yes208 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm1,500,000$0$0$No
Harri SateriIslanders (NYI)G291989-12-29 07:21:10Yes205 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm650,000$0$0$No
Jared McCannIslanders (NYI)C221996-05-30 05:11:13Yes198 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm1,107,000$0$0$No
John MooreIslanders (NYI)D281990-11-19 17:11:13No210 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm1,850,000$0$0$No
Jordan NolanIslanders (NYI)LW291989-06-23 11:11:13Yes219 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm575,000$0$0$No
Justin HollIslanders (NYI)D271992-01-30 03:50:34Yes205 Lbs6 ft3NoNoNo3Avec RestrictionPro & Farm750,000$0$0$No
Markus NutivaaraIslanders (NYI)D241994-06-06 08:48:59Yes191 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm817,500$0$0$No
Mike CondonIslanders (NYI)G281990-04-27 04:16:15Yes198 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm575,000$0$0$No
Nick JensenIslanders (NYI)D281990-09-21 04:18:15Yes199 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm812,500$0$0$No
Oliver KylingtonIslanders (NYI)D211997-05-19 11:11:13Yes182 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm925,000$0$0$No
Riley BarberIslanders (NYI)RW251994-02-07 09:24:16Yes197 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm692,500$0$0$No
Ryan Dzingel Islanders (NYI)RW271992-03-09 06:32:49Yes190 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Ryan StromeIslanders (NYI)C251993-07-11 11:11:13No195 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm2,500,000$0$0$No
Tanner Kero Islanders (NYI)LW261992-07-24 19:58:52Yes185 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm667,000$0$0$No
Valeri NichushkinIslanders (NYI)RW241995-03-04 23:11:13No214 Lbs6 ft6NoNoNo2Avec RestrictionPro & Farm1,100,000$0$0$No
William CarrierIslanders (NYI)LW241994-12-20 09:15:44Yes215 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm689,167$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2726.00199 Lbs6 ft11.931,061,290$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Blake ColemanRyan StromeValeri Nichushkin35122
2Tanner Kero Jared McCannRyan Dzingel 35122
3Jordan NolanBen StreetDarren Archibald25122
4William CarrierAndrew MillerAnders Bjork5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris TanevJohn Moore35122
2Brenden DillonDerrick Pouliot35122
3Nick JensenAnthony Bitetto30122
4Chris TanevJohn Moore0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Blake ColemanRyan StromeValeri Nichushkin60122
2Tanner Kero Jared McCannRyan Dzingel 40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris TanevJohn Moore60122
2Brenden DillonDerrick Pouliot40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Ryan StromeValeri Nichushkin60122
2Ryan Dzingel Blake Coleman40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris TanevJohn Moore60122
2Brenden DillonDerrick Pouliot40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Ryan Strome60122Chris TanevJohn Moore60122
2Valeri Nichushkin40122Brenden DillonDerrick Pouliot40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Ryan StromeValeri Nichushkin60122
2Ryan Dzingel Blake Coleman40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris TanevJohn Moore60122
2Brenden DillonDerrick Pouliot40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Blake ColemanRyan StromeValeri NichushkinChris TanevJohn Moore
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Blake ColemanRyan StromeValeri NichushkinChris TanevJohn Moore
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jordan Nolan, Darren Archibald, Anders BjorkJordan Nolan, Darren ArchibaldAnders Bjork
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nick Jensen, Anthony Bitetto, Brenden DillonNick JensenAnthony Bitetto, Brenden Dillon
Tirs de Pénalité
Ryan Strome, Valeri Nichushkin, Ryan Dzingel , Blake Coleman, Jared McCann
Gardien
#1 : Mike Condon, #2 : Harri Sateri


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
LigueDomicileVisiteur
# 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
1Avalanche2010100057-2100010004311010000014-320.50059140058808416638718839008274211866600.00%9366.67%01040209349.69%1042208350.02%579115450.17%169697317087301356674
2Blackhawks200010014401000000123-11000100021130.7504812005880841674871883900826020864700.00%40100.00%01040209349.69%1042208350.02%579115450.17%169697317087301356674
3Blues20200000413-91010000024-21010000029-700.000481200588084166587188390082671936544125.00%8537.50%01040209349.69%1042208350.02%579115450.17%169697317087301356674
4Bruins401000211416-22010001068-22000001188050.625142236005880841612987188390082138333012317529.41%15286.67%01040209349.69%1042208350.02%579115450.17%169697317087301356674
5Canadiens41300000910-12020000036-32110000064220.25091625005880841615787188390082137582210813323.08%11372.73%01040209349.69%1042208350.02%579115450.17%169697317087301356674
6Canucks21000100440110000002111000010023-130.75047110058808416778718839008253248441000.00%4175.00%01040209349.69%1042208350.02%579115450.17%169697317087301356674
7Capitals65100000271413330000001266321000001587100.8332745720058808416208871883900822047376178301033.33%38781.58%11040209349.69%1042208350.02%579115450.17%169697317087301356674
8Devils64100010231673110001012120330000001147100.8332340630058808416206871883900822047056160431330.23%28485.71%01040209349.69%1042208350.02%579115450.17%169697317087301356674
9Ducks2110000037-4110000002111010000016-520.5003580058808416708718839008259231849400.00%9188.89%01040209349.69%1042208350.02%579115450.17%169697317087301356674
10Flames2010000146-21000000123-11010000023-110.250461000588084166587188390082732128474250.00%14471.43%01040209349.69%1042208350.02%579115450.17%169697317087301356674
11Flyers631010102012832100000128431001010844100.833203454005880841619887188390082198686317439717.95%29486.21%01040209349.69%1042208350.02%579115450.17%169697317087301356674
12Kings2020000037-41010000023-11010000014-300.0003580058808416638718839008271222250300.00%11463.64%01040209349.69%1042208350.02%579115450.17%169697317087301356674
13Maple Leafs41200001910-12010000147-32110000053230.37591726005880841614587188390082128433610111218.18%18477.78%01040209349.69%1042208350.02%579115450.17%169697317087301356674
14Oilers2020000047-31010000023-11010000024-200.000461000588084166087188390082632716556116.67%8187.50%01040209349.69%1042208350.02%579115450.17%169697317087301356674
15Penguins63000021272073100001115123320000101284110.917274067005880841621087188390082210797614935925.71%37781.08%01040209349.69%1042208350.02%579115450.17%169697317087301356674
16Predators2020000029-71010000024-21010000005-500.0002461058808416658718839008267171252600.00%60100.00%01040209349.69%1042208350.02%579115450.17%169697317087301356674
17Rangers614001001624-831200000712-530200100912-330.250162541005880841619087188390082205908616531929.03%38976.32%01040209349.69%1042208350.02%579115450.17%169697317087301356674
18Red Wings4220000013121211000007612110000066040.50013213400588084161448718839008214049267917635.29%13284.62%01040209349.69%1042208350.02%579115450.17%169697317087301356674
19Sabres4210001013103211000005502100001085360.750132134005880841613987188390082121522011113215.38%10190.00%11040209349.69%1042208350.02%579115450.17%169697317087301356674
20Senateurs4400000014410220000005142200000093681.00014223601588084161458718839008213341189917317.65%90100.00%11040209349.69%1042208350.02%579115450.17%169697317087301356674
21Sharks210000015321000000112-11100000041330.750591400588084167187188390082632412468337.50%60100.00%01040209349.69%1042208350.02%579115450.17%169697317087301356674
22Stars21100000541110000004221010000012-120.500571200588084167087188390082653010568450.00%5180.00%01040209349.69%1042208350.02%579115450.17%169697317087301356674
Total783029032862332267391514010451161142391515022411171125900.5772333846171158808416269287188390082258392271520893398224.19%3396680.53%31040209349.69%1042208350.02%579115450.17%169697317087301356674
24Wild2010001057-2100000103211010000025-320.500571200588084167887188390082501818597228.57%9366.67%01040209349.69%1042208350.02%579115450.17%169697317087301356674
_Since Last GM Reset783029032862332267391514010451161142391515022411171125900.5772333846171158808416269287188390082258392271520893398224.19%3396680.53%31040209349.69%1042208350.02%579115450.17%169697317087301356674
_Vs Conference542616011731851483727121000032888352714601141976532720.6671853034880158808416187187188390082181865650914472666925.94%2464382.52%31040209349.69%1042208350.02%579115450.17%169697317087301356674
_Vs Division3016701141113862715840002158508158301120553619440.733113184297005880841610128718839008210213803578261784826.97%1703181.76%11040209349.69%1042208350.02%579115450.17%169697317087301356674

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7890W323338461726922583922715208911
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7830293286233226
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3915141045116114
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3915152241117112
Derniers 10 Matchs
WLOTWOTL SOWSOL
720001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3398224.19%3396680.53%3
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
8718839008258808416
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
1040209349.69%1042208350.02%579115450.17%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
169697317087301356674


Derniers Match 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
2 - 2018-09-305Islanders4Devils2WSommaire du Match
4 - 2018-10-0216Islanders4Penguins2WR3Sommaire du Match
6 - 2018-10-0424Devils4Islanders5WXXSommaire du Match
8 - 2018-10-0635Islanders3Flyers2WXXSommaire du Match
10 - 2018-10-0845Flyers1Islanders5WSommaire du Match
13 - 2018-10-1162Capitals3Islanders5WR3Sommaire du Match
16 - 2018-10-1475Islanders8Capitals1WSommaire du Match
18 - 2018-10-1686Rangers4Islanders3LSommaire du Match
21 - 2018-10-19103Islanders1Rangers2LSommaire du Match
23 - 2018-10-21113Penguins3Islanders6WR3Sommaire du Match
25 - 2018-10-23124Red Wings4Islanders3LSommaire du Match
27 - 2018-10-25131Islanders3Sabres1WSommaire du Match
32 - 2018-10-30153Rangers7Islanders2LSommaire du Match
34 - 2018-11-01168Islanders1Canadiens3LSommaire du Match
36 - 2018-11-03177Maple Leafs3Islanders2LXXSommaire du Match
38 - 2018-11-05191Islanders2Flyers1WXSommaire du Match
41 - 2018-11-08204Flames3Islanders2LXXSommaire du Match
44 - 2018-11-11219Red Wings2Islanders4WSommaire du Match
46 - 2018-11-13229Islanders4Red Wings2WSommaire du Match
50 - 2018-11-17245Canadiens3Islanders2LSommaire du Match
52 - 2018-11-19258Islanders0Predators5LSommaire du Match
54 - 2018-11-21266Avalanche3Islanders4WXSommaire du Match
58 - 2018-11-25289Islanders1Stars2LSommaire du Match
59 - 2018-11-26294Devils3Islanders4WSommaire du Match
63 - 2018-11-30314Ducks1Islanders2WSommaire du Match
65 - 2018-12-02324Islanders5Canadiens1WSommaire du Match
68 - 2018-12-05335Islanders5Rangers6LSommaire du Match
69 - 2018-12-06343Penguins6Islanders7WXXR3Sommaire du Match
72 - 2018-12-09359Islanders2Blues9LSommaire du Match
73 - 2018-12-10365Oilers3Islanders2LSommaire du Match
77 - 2018-12-14387Flyers5Islanders1LSommaire du Match
79 - 2018-12-16396Islanders5Sabres4WXXSommaire du Match
81 - 2018-12-18407Islanders3Rangers4LXSommaire du Match
82 - 2018-12-19416Devils5Islanders3LSommaire du Match
85 - 2018-12-22432Islanders4Sharks1WSommaire du Match
86 - 2018-12-23439Penguins3Islanders2LXXR3Sommaire du Match
89 - 2018-12-26458Maple Leafs4Islanders2LSommaire du Match
90 - 2018-12-27467Islanders4Maple Leafs1WSommaire du Match
92 - 2018-12-29480Senateurs1Islanders3WSommaire du Match
94 - 2018-12-31489Islanders1Maple Leafs2LSommaire du Match
97 - 2019-01-03502Islanders2Wild5LSommaire du Match
98 - 2019-01-04512Canucks1Islanders2WSommaire du Match
102 - 2019-01-08531Canadiens3Islanders1LSommaire du Match
104 - 2019-01-10545Islanders2Oilers4LSommaire du Match
105 - 2019-01-11554Sabres2Islanders4WSommaire du Match
107 - 2019-01-13565Islanders3Flyers1WSommaire du Match
110 - 2019-01-16578Kings3Islanders2LSommaire du Match
112 - 2019-01-18589Islanders2Red Wings4LSommaire du Match
114 - 2019-01-20601Islanders5Capitals2WR3Sommaire du Match
116 - 2019-01-22607Blues4Islanders2LSommaire du Match
118 - 2019-01-24613Islanders2Devils1WSommaire du Match
120 - 2019-01-26629Islanders1Ducks6LSommaire du Match
121 - 2019-01-27634Blackhawks3Islanders2LXXSommaire du Match
125 - 2019-01-31651Islanders2Capitals5LR3Sommaire du Match
126 - 2019-02-01658Senateurs0Islanders2WSommaire du Match
129 - 2019-02-04670Islanders2Flames3LSommaire du Match
130 - 2019-02-05682Predators4Islanders2LSommaire du Match
134 - 2019-02-09693Islanders5Devils1WSommaire du Match
136 - 2019-02-11705Bruins3Islanders4WXXSommaire du Match
139 - 2019-02-14715Islanders2Blackhawks1WXSommaire du Match
142 - 2019-02-17730Wild2Islanders3WXXSommaire du Match
145 - 2019-02-20744Islanders1Avalanche4LSommaire du Match
147 - 2019-02-22752Sharks2Islanders1LXXSommaire du Match
149 - 2019-02-24763Islanders1Kings4LSommaire du Match
151 - 2019-02-26775Islanders5Bruins4WXXSommaire du Match
153 - 2019-02-28782Stars2Islanders4WSommaire du Match
155 - 2019-03-02794Islanders6Senateurs2WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
157 - 2019-03-04803Islanders2Canucks3LXSommaire du Match
158 - 2019-03-05810Capitals2Islanders4WR3Sommaire du Match
160 - 2019-03-07822Islanders4Penguins3WR3Sommaire du Match
162 - 2019-03-09833Bruins5Islanders2LSommaire du Match
165 - 2019-03-12850Islanders3Bruins4LXXSommaire du Match
167 - 2019-03-14859Capitals1Islanders3WR3Sommaire du Match
172 - 2019-03-19879Rangers1Islanders2WSommaire du Match
176 - 2019-03-23898Sabres3Islanders1LSommaire du Match
178 - 2019-03-25907Islanders4Penguins3WXXR3Sommaire du Match
179 - 2019-03-26913Islanders3Senateurs1WSommaire du Match
183 - 2019-03-30931Flyers2Islanders6WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3525
Assistance64,96932,020
Assistance PCT83.29%82.10%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2487 - 82.90% 70,652$2,755,440$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,563,316$ 2,865,484$ 1,704,784$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
15,489$ 2,763,361$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 19,813$ 0$




LigueDomicileVisiteur
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
13783029032862332267391514010451161142391515022411171125902333846171158808416269287188390082258392271520893398224.19%3396680.53%31040209349.69%1042208350.02%579115450.17%169697317087301356674
Total Saison Régulière783029032862332267391514010451161142391515022411171125902333846171158808416269287188390082258392271520893398224.19%3396680.53%31040209349.69%1042208350.02%579115450.17%169697317087301356674