Connexion

Phantoms
GP: 80 | W: 43 | L: 33 | OTL: 4 | P: 90
GF: 344 | GA: 324 | PP%: 19.38% | PK%: 81.21%
DG: Simon DeChamplain | Morale : 49 | Moyenne d’équipe : 65
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Centre de jeu
Heat
40-32-8, 88pts
5
FINAL
4 Phantoms
43-33-4, 90pts
Team Stats
W1StreakL2
16-18-6Home Record19-19-2
24-14-2Away Record24-14-2
7-3-0Last 10 Games6-4-0
4.21Buts par match 4.30
4.39Buts contre par match 4.05
23.62%Pourcentage en avantage numérique19.38%
77.43%Pourcentage en désavantage numérique81.21%
Comets
40-29-11, 91pts
4
FINAL
3 Phantoms
43-33-4, 90pts
Team Stats
W1StreakL2
20-12-8Home Record19-19-2
20-17-3Away Record24-14-2
3-5-2Last 10 Games6-4-0
4.08Buts par match 4.30
3.90Buts contre par match 4.05
18.36%Pourcentage en avantage numérique19.38%
78.22%Pourcentage en désavantage numérique81.21%
Meneurs d'équipe
Buts
Travis Konecny
65
Passes
Calle Jarnkrok
74
Points
Travis Konecny
135
Plus/Moins
Calle Jarnkrok
18
Victoires
Anton Forsberg
35
Pourcentage d’arrêts
Zachary Fucale
0.886

Statistiques d’équipe
Buts pour
344
4.30 GFG
Tirs pour
2774
34.68 Avg
Pourcentage en avantage numérique
19.4%
62 GF
Début de zone offensive
36.1%
Buts contre
324
4.05 GAA
Tirs contre
2658
33.23 Avg
Pourcentage en désavantage numérique
81.2%
62 GA
Début de la zone défensive
37.0%
Informations de l'équipe

Directeur généralSimon DeChamplain
EntraîneurKevin Dineen
DivisionFritz-Kraatz
ConférenceRobert-Lebel
CapitaineDave Bolland
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,502
Billets de saison300


Informations de la formation

Équipe Pro33
Équipe Mineure20
Limite contact 53 / 250
Espoirs0


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
1Calle Jarnkrok (R)X100.006631757475797771817677667263573869720251995,000$
2Michael Bournival (R)X100.007739787778737474687078717765534146720241950,000$
3Travis Konecny (R)X100.006231748363766786686971628145446969700191500,000$
4Sven Andrighetto (R)X100.007734796578747068716478577148484869680233700,000$
5Alex DeBrincat (R)X100.007454847574667465717271577543417970680192500,000$
6Nick Shore (R)X100.005426746969726773827573535852553960670242800,000$
7Cristoval Nieves (R)X100.006626757464677270747668526745464659660222600,000$
8Morgan Klimchuk (R)X100.006432727268737367666966687345434938660213650,000$
9Erik Nystrom (R)X100.006823747074686769676170647348473858650232600,000$
10Lucas Wallmarkk (R)X100.007038716462716172717364636243435859650204600,000$
11David Kampf (R)X100.005742816268686669656571546543465869640211500,000$
12Brendan Leipsic (R)X100.005233686364636064757170526145464457620222500,000$
13Laurent Dauphin (R)X100.007037775967616768576861486543435057610213500,000$
14Nick Sorensen (R)X100.005633757166656662595272527146464969610223525,000$
15JC Lipon (R)X100.007256666569496762645460495448474252590232450,000$
16Anthony Angello (R)X100.004836786062736453646259565042425154580203450,000$
17A.J. Greer (R)X100.005942596566597056575559494944435028570201500,000$
18Jake Dotchin (R)X100.007940787475736167537453755859464641710223800,000$
19Reid McNeill (R)X100.007547787480678173596758706662483928710241650,000$
20Ivan Provorov (R)X100.007147797373726567477165715549427659690191500,000$
21Blake Heinrich (R)X100.006734686870715955457066755146444869660213500,000$
22Brenden Kichton (R)X100.006530766866686666536060716154553557650241400,000$
23Devon Teows (R)X100.007248726764646068496252695147485153650224600,000$
24Rinat Valiev (R)X100.007134786865666471506257655945445656650213500,000$
25Mikko Lehtonen (R)X100.007041745750657175466975546148484969640222500,000$
Rayé
1Brett Murray (R)X100.007436616474536254435360524040407323560182500,000$
2Cooper Marody (R)X100.004234685950585858707154364644425520550201500,000$
3Mark Alt (R)X63.707032736868676855516758805354543139670251400,000$
4Matt Kiersted (R)X100.006345615762535151395340554640406720550182500,000$
5Riley Stillman (R)X100.006539615660545950325550534440407020550182500,000$
MOYENNE D’ÉQUIPE98.79663773676766666560666460614846525164
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
1Anton Forsberg100.00737271787378747072747261554067720241500,000$
2Zachary Fucale100.00657555636771707276715644445046680213500,000$
Rayé
1Jason Kasdorf100.00666578636370686864696652524119660241500,000$
MOYENNE D’ÉQUIPE100.0068716868687371707171655250444469
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Kevin Dineen73656679327257Can484500,000$


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’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
1Travis KonecnyPhantoms (Phi)RW806570135156201217241113126215.82%41167720.971618347726900031216349.41%1709127251.61350001377
2Calle JarnkrokPhantoms (Phi)C804374117184801382012958615614.58%64185923.259202938272213122654054.48%26545445041.26150001192
3Nick ShorePhantoms (Phi)C75384482857590822205312117.27%18118415.797132032203000074255.33%8913211021.3900100723
4Michael BournivalPhantoms (Phi)LW66304979126010112962327013812.93%45148722.548142240229224102114256.29%3345922001.0625010444
5Cristoval NievesPhantoms (Phi)C80303262-130069751815512416.57%2793211.660000130000172343.93%4534314001.3300000323
6Alex DeBrincatPhantoms (Phi)LW8023365913355113832055912211.22%33134216.784913162250114354348.57%704823000.8800001345
7Sven AndrighettoPhantoms (Phi)RW80232447332014790149349315.44%26137717.2292112121400031082050.68%733425000.6811000136
8Morgan KlimchukPhantoms (Phi)LW64222345-134062771425210115.49%1173411.48246631000052153.33%302912001.2200000012
9Jake DotchinPhantoms (Phi)D6553843176001061319641495.21%106169026.013710162430221211000.00%03156000.5100000013
10Ivan ProvorovPhantoms (Phi)D8033639-123807910411444412.63%85180522.5704492400115228000.00%03158000.4300000001
11Reid McNeillPhantoms (Phi)D527253212401074807530399.33%77129724.952810171830003175110.00%02352000.4900011013
12Erik NystromPhantoms (Phi)LW76191130-71205438139499013.67%186448.48000011011173036.36%22177000.9300000111
13Lucas WallmarkkPhantoms (Phi)C80101626-9180395310933689.17%75576.9700001000003145.85%2291515000.9300000121
14Nick SorensenPhantoms (Phi)RW8071421020042457416619.46%1789111.1510111000001040.00%202112000.4700000020
15Blake HeinrichPhantoms (Phi)D80016169580711067030270.00%81133116.6401151370000146000.00%01741000.2400000001
16Mark AltPhantoms (Phi)D5531316-1036045915621205.36%61106719.4012361320110120110.00%0845000.3000000011
17Brendan LeipsicPhantoms (Phi)LW715813-38016165714238.77%73194.50000131011332050.00%10155000.8100000000
18Brenden KichtonPhantoms (Phi)D7101313618022453018140.00%4571210.0400002000016000.00%0428000.3601000000
19Rinat ValievPhantoms (Phi)D75371081202758268911.54%3176110.15000233000059100.00%0421000.2600000010
20JC LiponPhantoms (Phi)RW64178-9803116299143.45%104517.0500004000000153.85%1313000.3500000000
21Devon TeowsPhantoms (Phi)D6905591002727177140.00%255528.00000115000042000.00%0318000.1800000000
22David KampfPhantoms (Phi)C8031440073165518.75%11541.93000010000030028.95%3813000.5200000000
23Mikko LehtonenPhantoms (Phi)D80033-12017816240.00%104225.2800002000018000.00%036000.1400000000
24Tomas KubalikFlyersRW11011004050320.00%02121.9700002000020060.00%511000.9100000000
25A.J. GreerPhantoms (Phi)LW47000020151110.00%0571.2200000000147000.00%001000.0000000000
26Anthony AngelloPhantoms (Phi)C70000320353000.00%0951.36000000001750040.00%3001000.0000000000
27Dylan OlsenFlyersD1000300323120.00%12626.450000300002000.00%010000.0000000000
28Laurent DauphinPhantoms (Phi)C71000020923130.00%0881.24000040000580036.00%2501000.0000000000
Statistiques d’équipe totales ou en moyenne18733415659068870430152916112774870160412.29%8472354612.576210216428824846814452033401852.60%50675865532110.77717122444143
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
1Anton ForsbergPhantoms (Phi)66352020.8794.023388402271876915900.55696416231
2Zachary FucalePhantoms (Phi)2671210.8863.7912512079690355010.33331646000
3Jason KasdorfPhantoms (Phi)61110.8355.0018000159137000.5002018000
Statistiques d’équipe totales ou en moyenne98433340.8794.0048206032126571307910.500148080231


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 restantPlafond 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
A.J. GreerPhantoms (Phi)LW201996-01-01Yes210 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Alex DeBrincatPhantoms (Phi)LW191997-01-01Yes165 Lbs5 ft7NoNoNo2Pro & Farm500,000$0$0$No500,000$
Anthony AngelloPhantoms (Phi)C201996-01-01Yes210 Lbs6 ft5NoNoNo3Pro & Farm450,000$0$0$No450,000$450,000$
Anton ForsbergPhantoms (Phi)G241992-01-01No191 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Blake HeinrichPhantoms (Phi)D211995-01-01Yes185 Lbs5 ft11NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$
Brendan LeipsicPhantoms (Phi)LW221994-01-01Yes165 Lbs5 ft8NoNoNo2Pro & Farm500,000$0$0$No500,000$
Brenden KichtonPhantoms (Phi)D241992-01-01Yes185 Lbs5 ft10NoNoNo1Pro & Farm400,000$0$0$No
Brett MurrayPhantoms (Phi)LW181998-01-01Yes216 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$
Calle JarnkrokPhantoms (Phi)C251991-01-01Yes156 Lbs5 ft11NoNoNo1Pro & Farm995,000$0$0$No
Cooper MarodyPhantoms (Phi)C201996-01-01Yes184 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$No
Cristoval NievesPhantoms (Phi)C221994-01-01Yes192 Lbs6 ft2NoNoNo2Pro & Farm600,000$0$0$No600,000$
David KampfPhantoms (Phi)C211995-01-01Yes188 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$No
Devon TeowsPhantoms (Phi)D221994-01-01Yes191 Lbs5 ft11NoNoNo4Pro & Farm600,000$0$0$No700,000$800,000$900,000$
Erik NystromPhantoms (Phi)LW231993-01-01Yes176 Lbs5 ft11NoNoNo2Pro & Farm600,000$0$0$No600,000$
Ivan ProvorovPhantoms (Phi)D191997-01-01Yes201 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$No
JC LiponPhantoms (Phi)RW231993-01-01Yes185 Lbs6 ft0NoNoNo2Pro & Farm450,000$0$0$No450,000$
Jake DotchinPhantoms (Phi)D221994-01-01Yes207 Lbs6 ft2NoNoNo3Pro & Farm800,000$0$0$No800,000$800,000$
Jason KasdorfPhantoms (Phi)G241992-01-01No172 Lbs6 ft3NoNoNo1Pro & Farm500,000$0$0$No
Laurent DauphinPhantoms (Phi)C211995-01-01Yes185 Lbs6 ft0NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$
Lucas WallmarkkPhantoms (Phi)C201996-01-01Yes178 Lbs6 ft0NoNoNo4Pro & Farm600,000$0$0$No700,000$800,000$900,000$
Mark Alt (sur la masse salariale)Phantoms (Phi)D251991-01-01Yes201 Lbs6 ft1NoNoNo1Pro & Farm400,000$0$0$Yes
Matt KierstedPhantoms (Phi)D181998-01-01Yes184 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
Michael BournivalPhantoms (Phi)LW241992-01-01Yes195 Lbs5 ft11NoNoNo1Pro & Farm950,000$0$0$No
Mikko LehtonenPhantoms (Phi)D221994-01-01Yes196 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Morgan KlimchukPhantoms (Phi)LW211995-01-01Yes185 Lbs5 ft11NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$
Nick ShorePhantoms (Phi)C241992-01-01Yes194 Lbs6 ft1NoNoNo2Pro & Farm800,000$0$0$No850,000$
Nick SorensenPhantoms (Phi)RW221994-01-01Yes185 Lbs6 ft1NoNoNo3Pro & Farm525,000$0$0$No525,000$525,000$
Reid McNeillPhantoms (Phi)D241992-01-01Yes210 Lbs6 ft3NoNoNo1Pro & Farm650,000$0$0$No
Riley StillmanPhantoms (Phi)D181998-01-01Yes196 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Rinat ValievPhantoms (Phi)D211995-01-01Yes185 Lbs6 ft1NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$
Sven AndrighettoPhantoms (Phi)RW231993-01-01Yes185 Lbs5 ft10NoNoNo3Pro & Farm700,000$0$0$No700,000$700,000$
Travis KonecnyPhantoms (Phi)RW191997-01-01Yes175 Lbs5 ft10NoNoNo1Pro & Farm500,000$0$0$No
Zachary FucalePhantoms (Phi)G211995-01-01No185 Lbs6 ft1NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3321.58188 Lbs6 ft02.03565,758$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael BournivalCalle JarnkrokTravis Konecny40122
2Alex DeBrincatNick ShoreSven Andrighetto30122
3Erik NystromCristoval NievesNick Sorensen20122
4Brendan LeipsicLucas WallmarkkJC Lipon10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake DotchinReid McNeill40122
2Ivan ProvorovBlake Heinrich30122
3Rinat ValievBrenden Kichton20122
4Devon TeowsMikko Lehtonen10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael BournivalCalle JarnkrokTravis Konecny60122
2Alex DeBrincatNick ShoreSven Andrighetto40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake DotchinReid McNeill60122
2Ivan ProvorovBlake Heinrich40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Michael BournivalCalle Jarnkrok60122
2Travis KonecnySven Andrighetto40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake DotchinReid McNeill60122
2Ivan ProvorovBlake Heinrich40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Michael Bournival60122Jake DotchinReid McNeill60122
2Calle Jarnkrok40122Ivan ProvorovBlake Heinrich40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Michael BournivalCalle Jarnkrok60122
2Travis KonecnySven Andrighetto40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake DotchinReid McNeill60122
2Ivan ProvorovBlake Heinrich40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Michael BournivalCalle JarnkrokTravis KonecnyJake DotchinReid McNeill
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Michael BournivalCalle JarnkrokTravis KonecnyJake DotchinReid McNeill
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
David Kampf, Laurent Dauphin, Anthony AngelloDavid Kampf, Laurent DauphinAnthony Angello
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Rinat Valiev, Brenden Kichton, Devon TeowsRinat ValievBrenden Kichton, Devon Teows
Tirs de pénalité
Michael Bournival, Calle Jarnkrok, Travis Konecny, Sven Andrighetto, Alex DeBrincat
Gardien
#1 : Anton Forsberg, #2 : Zachary Fucale


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
1Admirals33000000211381100000095422000000128461.0002131520084126130892871941957211033640646233.33%20480.00%0946182951.72%989187552.75%730136353.56%169595516987541430709
2Barracuda3100001112102210000019811000001032150.833121830008412613081048719419572110234265717423.53%13192.31%0946182951.72%989187552.75%730136353.56%169595516987541430709
3Bears22000000853110000003211100000053241.00081523008412613087687194195721771512385120.00%60100.00%0946182951.72%989187552.75%730136353.56%169595516987541430709
4Comets52201000201732110000088031101000129360.600203555008412613081568719419572118074509713646.15%25388.00%0946182951.72%989187552.75%730136353.56%169595516987541430709
5Condors431000002214822000000127521100000107360.750223759008412613081528719419572116349357012325.00%15193.33%0946182951.72%989187552.75%730136353.56%169595516987541430709
6Crunch22000000936110000005141100000042241.00091625008412613087487194195721601816418112.50%8187.50%0946182951.72%989187552.75%730136353.56%169595516987541430709
7Devils2100000113121110000006421000000178-130.750131831008412613088887194195721621712326233.33%6183.33%0946182951.72%989187552.75%730136353.56%169595516987541430709
8Eagles21100000910-11010000037-41100000063320.50091322008412613086887194195721621516418337.50%8275.00%1946182951.72%989187552.75%730136353.56%169595516987541430709
9Griffins404000001122-111010000034-130300000818-1000.000111728008412613081238719419572113836287711327.27%14285.71%0946182951.72%989187552.75%730136353.56%169595516987541430709
10Heat6330000028262303000001316-3330000001510560.500284977008412613081828719419572119172739933618.18%30583.33%0946182951.72%989187552.75%730136353.56%169595516987541430709
11Icehogs532000002222020200000815-733000000147760.6002237590084126130818187194195721175552810816318.75%14378.57%0946182951.72%989187552.75%730136353.56%169595516987541430709
12Little Stars21100000710-31010000015-41100000065120.5007121900841261308738719419572177223531300.00%10280.00%0946182951.72%989187552.75%730136353.56%169595516987541430709
13Marlies73300010272434220000015141311000101210280.571274471008412613082468719419572122085381413825.26%20385.00%1946182951.72%989187552.75%730136353.56%169595516987541430709
14Monsters321000001611511000000615211000001010040.66716284400841261308115871941957218634405410220.00%15380.00%0946182951.72%989187552.75%730136353.56%169595516987541430709
15Moose32100000141042200000010461010000046-240.6671423371084126130811887194195721834016639111.11%80100.00%1946182951.72%989187552.75%730136353.56%169595516987541430709
16Penguins20200000814-61010000038-51010000056-100.00081523008412613086887194195721631524391218.33%12741.67%0946182951.72%989187552.75%730136353.56%169595516987541430709
17Punishers2010010058-31000010023-11010000035-210.2505611008412613087287194195721732412367114.29%6183.33%0946182951.72%989187552.75%730136353.56%169595516987541430709
18Rampage21100000550110000003211010000023-120.50057120084126130880871941957216312183612433.33%9188.89%0946182951.72%989187552.75%730136353.56%169595516987541430709
19Reign651000003119123210000016115330000001587100.8333153840084126130819687194195721200407012130310.00%33875.76%2946182951.72%989187552.75%730136353.56%169595516987541430709
20Rocket330000001596220000008441100000075261.0001525400084126130899871941957218827266014214.29%13469.23%1946182951.72%989187552.75%730136353.56%169595516987541430709
21Senators3110010011110211000008711000010034-130.500111829008412613089387194195721922732579333.33%16381.25%0946182951.72%989187552.75%730136353.56%169595516987541430709
22Sound Tigers20200000512-71010000024-21010000038-500.0005914008412613087887194195721672520339222.22%10280.00%0946182951.72%989187552.75%730136353.56%169595516987541430709
23Thunderbirds303000001218-620200000811-31010000047-300.000121931008412613081038719419572110936256417317.65%10370.00%0946182951.72%989187552.75%730136353.56%169595516987541430709
24Wolfpack20100010710-31010000037-41000001043120.50071017008412613086387194195721562310396350.00%5260.00%0946182951.72%989187552.75%730136353.56%169595516987541430709
25Wolves2020000069-31010000034-11010000035-200.0006101600841261308748719419572168168319111.11%40100.00%0946182951.72%989187552.75%730136353.56%169595516987541430709
Total80393301232344324204019190010116716254020140113117716215900.56334456590910841261308277487194195721265884771015293206219.38%3306281.21%6946182951.72%989187552.75%730136353.56%169595516987541430709
_Since Last GM Reset80393301232344324204019190010116716254020140113117716215900.56334456590910841261308277487194195721265884771015293206219.38%3306281.21%6946182951.72%989187552.75%730136353.56%169595516987541430709
_Vs Conference502917001212301913925141000001117962125157001201139518640.6402303806101084126130817018719419572116415354529712053416.59%2113782.46%5946182951.72%989187552.75%730136353.56%169595516987541430709
_Vs Division19117000108669171046000004441397100010422814240.6328614623200841261308624871941957216111971813611011110.89%831680.72%3946182951.72%989187552.75%730136353.56%169595516987541430709

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8090L234456590927742658847710152910
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8039331232344324
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4019190101167162
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4020141131177162
Derniers 10 matchs
WLOTWOTL SOWSOL
540010
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3206219.38%3306281.21%6
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
87194195721841261308
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
946182951.72%989187552.75%730136353.56%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
169595516987541430709


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 - 2021-11-305Phantoms7Marlies1AWSommaire du match
4 - 2021-12-0316Marlies5Phantoms2BLSommaire du match
8 - 2021-12-0735Heat5Phantoms4BLR1Sommaire du match
11 - 2021-12-1054Marlies4Phantoms3BLSommaire du match
14 - 2021-12-1365Phantoms2Griffins7ALSommaire du match
16 - 2021-12-1576Phantoms6Heat5AWR1Sommaire du match
20 - 2021-12-1992Reign4Phantoms8BWR1Sommaire du match
23 - 2021-12-22111Rocket2Phantoms4BWSommaire du match
24 - 2021-12-23117Phantoms5Reign3AWR1Sommaire du match
26 - 2021-12-25123Phantoms6Comets2AWSommaire du match
27 - 2021-12-26130Phantoms5Icehogs4AWSommaire du match
30 - 2021-12-29150Senators3Phantoms2BLSommaire du match
32 - 2021-12-31161Phantoms6Admirals3AWSommaire du match
34 - 2022-01-02173Moose2Phantoms4BWSommaire du match
37 - 2022-01-05190Phantoms7Monsters4AWSommaire du match
39 - 2022-01-07200Condors2Phantoms6BWSommaire du match
41 - 2022-01-09213Phantoms3Senators4ALXSommaire du match
43 - 2022-01-11224Barracuda3Phantoms5BWSommaire du match
45 - 2022-01-13233Phantoms2Rampage3ALSommaire du match
47 - 2022-01-15248Rocket2Phantoms4BWSommaire du match
50 - 2022-01-18268Wolfpack7Phantoms3BLSommaire du match
52 - 2022-01-20275Phantoms4Crunch2AWSommaire du match
55 - 2022-01-23290Phantoms7Rocket5AWSommaire du match
57 - 2022-01-25300Phantoms2Griffins5ALSommaire du match
58 - 2022-01-26308Wolves4Phantoms3BLSommaire du match
61 - 2022-01-29320Phantoms3Punishers5ALSommaire du match
63 - 2022-01-31333Phantoms6Heat3AWR1Sommaire du match
64 - 2022-02-01338Condors5Phantoms6BWSommaire du match
67 - 2022-02-04355Phantoms3Wolves5ALSommaire du match
68 - 2022-02-05360Bears2Phantoms3BWSommaire du match
71 - 2022-02-08379Phantoms3Heat2AWR1Sommaire du match
72 - 2022-02-09387Phantoms3Marlies2AWXXSommaire du match
73 - 2022-02-10389Admirals5Phantoms9BWSommaire du match
78 - 2022-02-15412Phantoms2Marlies7ALSommaire du match
79 - 2022-02-16417Sound Tigers4Phantoms2BLSommaire du match
84 - 2022-02-21439Phantoms5Bears3AWSommaire du match
85 - 2022-02-22444Icehogs8Phantoms3BLSommaire du match
88 - 2022-02-25464Reign1Phantoms3BWR1Sommaire du match
91 - 2022-02-28477Phantoms6Eagles3AWSommaire du match
93 - 2022-03-02487Phantoms6Little Stars5AWSommaire du match
94 - 2022-03-03494Crunch1Phantoms5BWSommaire du match
98 - 2022-03-07514Phantoms4Thunderbirds7ALSommaire du match
99 - 2022-03-08519Devils4Phantoms6BWSommaire du match
103 - 2022-03-12536Phantoms4Griffins6ALSommaire du match
105 - 2022-03-14544Icehogs7Phantoms5BLSommaire du match
107 - 2022-03-16557Phantoms7Devils8ALXXSommaire du match
110 - 2022-03-19571Eagles7Phantoms3BLSommaire du match
115 - 2022-03-24593Phantoms5Penguins6ALSommaire du match
116 - 2022-03-25598Punishers3Phantoms2BLXSommaire du match
120 - 2022-03-29619Reign6Phantoms5BLR1Sommaire du match
123 - 2022-04-01633Phantoms6Admirals5AWSommaire du match
125 - 2022-04-03647Monsters1Phantoms6BWSommaire du match
127 - 2022-04-05659Phantoms3Icehogs1AWSommaire du match
129 - 2022-04-07671Senators4Phantoms6BWSommaire du match
132 - 2022-04-10694Moose2Phantoms6BWSommaire du match
135 - 2022-04-13705Phantoms3Barracuda2AWXXSommaire du match
137 - 2022-04-15719Penguins8Phantoms3BLSommaire du match
139 - 2022-04-17728Phantoms4Moose6ALSommaire du match
142 - 2022-04-20746Thunderbirds5Phantoms4BLSommaire du match
144 - 2022-04-22758Phantoms3Monsters6ALSommaire du match
147 - 2022-04-25772Thunderbirds6Phantoms4BLSommaire du match
149 - 2022-04-27781Phantoms4Condors6ALSommaire du match
150 - 2022-04-28791Phantoms6Icehogs2AWSommaire du match
153 - 2022-05-01803Little Stars5Phantoms1BLSommaire du match
154 - 2022-05-02814Phantoms5Reign2AWR1Sommaire du match
157 - 2022-05-05828Griffins4Phantoms3BLSommaire du match
159 - 2022-05-07843Phantoms2Comets4ALSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
162 - 2022-05-10855Barracuda5Phantoms4BLXXSommaire du match
164 - 2022-05-12870Phantoms4Comets3AWXSommaire du match
166 - 2022-05-14880Marlies2Phantoms4BWSommaire du match
170 - 2022-05-18900Phantoms5Reign3AWR1Sommaire du match
172 - 2022-05-20907Rampage2Phantoms3BWSommaire du match
177 - 2022-05-25932Heat6Phantoms5BLR1Sommaire du match
180 - 2022-05-28948Phantoms3Sound Tigers8ALSommaire du match
182 - 2022-05-30956Comets4Phantoms5BWSommaire du match
184 - 2022-06-01970Phantoms4Wolfpack3AWXXSommaire du match
187 - 2022-06-04983Marlies3Phantoms6BWSommaire du match
189 - 2022-06-06990Phantoms6Condors1AWSommaire du match
192 - 2022-06-091010Heat5Phantoms4BLR1Sommaire du match
198 - 2022-06-151032Comets4Phantoms3BLSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3520
Assistance74,96325,114
Assistance PCT93.70%62.79%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2502 - 83.40% 81,700$3,267,991$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,366,485$ 1,827,000$ 1,490,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,135$ 1,850,860$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 11,635$ 0$




Phantoms 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

Phantoms 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

Phantoms 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

Phantoms 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

Phantoms 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