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Phantoms
GP: 29 | W: 16 | L: 9 | OTL: 4 | P: 36
GF: 109 | GA: 103 | PP%: 26.32% | PK%: 73.85%
DG: Bela Michalski | Morale : 93 | Moyenne d’équipe : N/A
Prochains matchs #489 vs Norsemen

Centre de jeu
Crunch
17-12-4, 38pts
5
FINAL
4 Phantoms
16-9-4, 36pts
Team Stats
W3SéquenceSOL2
10-3-2Fiche domicile7-5-3
7-9-2Fiche domicile9-4-1
5-3-2Derniers 10 matchs4-3-3
3.45Buts par match 3.76
3.15Buts contre par match 3.55
34.06%Pourcentage en avantage numérique26.32%
76.32%Pourcentage en désavantage numérique73.85%
Phantoms
16-9-4, 36pts
3
FINAL
4 Senators
17-10-3, 37pts
Team Stats
SOL2SéquenceW5
7-5-3Fiche domicile9-4-2
9-4-1Fiche domicile8-6-1
4-3-3Derniers 10 matchs8-2-0
3.76Buts par match 3.90
3.55Buts contre par match 3.73
26.32%Pourcentage en avantage numérique35.00%
73.85%Pourcentage en désavantage numérique75.97%
Norsemen
16-9-6, 38pts
Jour 69
Phantoms
16-9-4, 36pts
Statistiques d’équipe
SOL1SéquenceSOL2
7-5-3Fiche domicile7-5-3
9-4-3Fiche visiteur9-4-1
4-3-310 derniers matchs4-3-3
3.97Buts par match 3.76
3.77Buts contre par match 3.76
31.11%Pourcentage en avantage numérique26.32%
72.27%Pourcentage en désavantage numérique73.85%
Phantoms
16-9-4, 36pts
Jour 73
Admirals
12-14-2, 26pts
Statistiques d’équipe
SOL2SéquenceW1
7-5-3Fiche domicile4-9-2
9-4-1Fiche visiteur8-5-0
4-3-310 derniers matchs4-4-2
3.76Buts par match 3.57
3.55Buts contre par match 3.57
26.32%Pourcentage en avantage numérique24.00%
73.85%Pourcentage en désavantage numérique68.35%
Gorillas
11-17-4, 26pts
Jour 74
Phantoms
16-9-4, 36pts
Statistiques d’équipe
L5SéquenceSOL2
7-8-0Fiche domicile7-5-3
4-9-4Fiche visiteur9-4-1
2-7-110 derniers matchs4-3-3
3.16Buts par match 3.76
4.28Buts contre par match 3.76
25.93%Pourcentage en avantage numérique26.32%
72.92%Pourcentage en désavantage numérique73.85%
Meneurs d'équipe
Buts
Alexandre Doucet
13
Passes
Logan Mailloux
16
Points
Kurtis MacDermid
25
Plus/Moins
Alexandre Doucet
9
Victoires
Josef Korenar
10
Pourcentage d’arrêts
Lawton Zacher
0.916

Statistiques d’équipe
Buts pour
109
3.76 GFG
Tirs pour
998
34.41 Avg
Pourcentage en avantage numérique
26.3%
35 GF
Début de zone offensive
38.2%
Buts contre
103
3.55 GAA
Tirs contre
949
32.72 Avg
Pourcentage en désavantage numérique
73.8%%
34 GA
Début de la zone défensive
36.4%
Informations de l'équipe

Directeur généralBela Michalski
EntraîneurJim Hiller
DivisionNorth Division
ConférenceEastern Conference
CapitaineElliot Desnoyers
Assistant #1Alexandre Doucet
Assistant #2Grant Hutton


Informations de l’aréna

Capacité8,000
Assistance5,302
Billets de saison800


Informations de la formation

Équipe Pro28
Équipe Mineure21
Limite contact 49 / 65
Espoirs13


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
1Riley ThompsonX100.0060606060607070606060606060425608000223650,000$
2Santeri HuovilaX100.0060606060607070606060606060445707900203650,000$
3Patrick BrownXX100.0073509170827792696470687365717307900321650,000$
4Kurtis MacDermidXX100.0074648561887577656165656965576107800301650,000$
5Alexandre Doucet (A)XXX100.0060606060607070606060606060495608900221771,750$
6Elliot Desnoyers (C)XX100.0060606060607070606060606060505808300221735,000$
7Danil GushchinXX100.0060508973627991696168696765465808700221866,250$
8Joey AndersonXX100.00665095627879856764656578655564081002611,700,000$
9Matt MartinXX100.0080589263817579676265657265756706900351650,000$
10Matthew SopXX100.0060606060607070606060606060415608500211650,000$
11Hudson SchandorXX100.0060606060607070606060606060405507800241650,000$
12Jeremy WilmerXX100.0060606060607070606060606060405507700212650,000$
13Ben RobertsonX100.0060606060607070606060606060445707700203650,000$
14Grant Hutton (A)X100.0062508561808083652566647365576607800293650,000$
15Logan MaillouxX100.00625084708183926525666471664156081002121,312,500$
16Billy SweezeyX100.0060606060607070606060606060626408100283650,000$
17Jimi SuomiX100.0060606060607070606060606060405508200211675,000$
18Luca Munzenberger (R)X100.0060606060607070606060606060485508200222750,000$
Rayé
1Brady StonehouseXX100.0060606060607070606060606060445707800203650,000$
2Dalton BancroftXX100.0060606060607070606060606060465807500233650,000$
3Israel MianscumXXX93.0560606060607070606060606060405507700211650,000$
4Lucas OlvestadX100.0060606060607070606060606060405507000221650,000$
5Tom Willander (R)X100.00606060606070706060606060604455069001931,500,000$
6Sam Dickinson (R)X100.00606060606070706060606060604655078001831,500,000$
7Viktor Hurtig (R)X100.0060606060607070606060606060465507700222650,000$
MOYENNE D’ÉQUIPE99.726258686265727462586262636148580790
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
1Lawton Zacher100.006070706060606060606060445907900213650,000$
2Josef Korenar100.006070706060606060606060576607600261682,500$
Rayé
1Georgi Romanov100.006070706060606060606060415508900251682,500$
MOYENNE D’ÉQUIPE100.00607070606060606060606047600810
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jim Hiller7989809169731CAN561600,000$


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
1Kurtis MacDermidPhantoms (PHI)LW/RW29101525-48460494811035629.09%1153218.35481220871125742150.00%402511000.9433327214
2Alexandre DoucetPhantoms (PHI)C/LW/RW2913122598755495453294224.53%1253418.43561110912028861148.09%551118000.9417515022
3Patrick BrownPhantoms (PHI)C/RW2611132472525373288284912.50%438014.642571048011070151.82%247118001.2611005211
4Elliot DesnoyersPhantoms (PHI)LW/RW291392216935513268222719.12%745615.7654912880000100245.00%8087000.9615223211
5Matt MartinPhantoms (PHI)LW/RW218122073220272266223712.12%1634016.223476350001341150.00%32151001.1711121301
6Logan MaillouxPhantoms (PHI)D29316191714517363915197.69%2961021.05310131090011293100%01910000.6201351020
7Danil GushchinPhantoms (PHI)LW/RW2961117-35535237532578.00%744115.232133200000192045.83%48259000.7713001210
8Joey AndersonPhantoms (PHI)LW/RW291061692020292979154312.66%1134912.06000010000111022.22%9117000.9200022120
9Israel MianscumPhantoms (PHI)C/LW/RW1821012-9383041293521275.71%529816.561453410001370049.48%28745000.8011204000
10Billy SweezeyPhantoms (PHI)D29110113875546443413172.94%3867023.13145893000395010%0716000.3300334002
11Hudson SchandorPhantoms (PHI)C/LW1764106582033132351126.09%421912.88000000002260147.96%9866000.9100121012
12Grant HuttonPhantoms (PHI)D232790121028304914124.08%3651622.462131263000076010%01213000.3500011100
13Matthew SopPhantoms (PHI)C/LW26369-2241034223513228.57%128611.040000100002150052.13%18853000.6300110010
14Luca MunzenbergerPhantoms (PHI)D2018964830181819465.26%1436918.45134447000019100%0611000.4900213000
15Brady StonehousePhantoms (PHI)LW/RW1535807145222030162010.00%224316.261232400000300047.06%1743000.6611414100
16Riley ThompsonPhantoms (PHI)C14268-220102593713175.41%819814.2100002000080050.64%15642000.8000110010
17Ben RobertsonPhantoms (PHI)D26088-28155503437990%3054320.90022211000341000%01015000.2900433000
18Dalton BancroftPhantoms (PHI)LW/RW255274301052413411914.71%1036314.551123330002321139.58%4834000.3801101001
19Jeremy WilmerPhantoms (PHI)LW/RW21325-66830161226222511.54%624811.83213845000001127.78%1840000.4000024001
20Santeri HuovilaPhantoms (PHI)LW15224-52620181823568.70%118612.421121220000111027.78%1824000.4300220000
21Viktor HurtigPhantoms (PHI)D13134639351812102410.00%720916.11112128000019000%034000.3800223000
22Jimi SuomiPhantoms (PHI)D15022-4281019228260%1923515.6900001000028000%039000.1700110000
23Tom WillanderPhantoms (PHI)D10022029151285430%719319.33022040000023000%014000.2100102000
24Sam DickinsonPhantoms (PHI)D14022-2954915650%1220414.5800000000014000%026000.2000100001
Statistiques d’équipe totales ou en moyenne52210517327820106165573061799835853510.52%297863316.5435609511595033629819121148.56%1837201166000.641024403455141316
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
1Josef KorenarPhantoms (PHI)1810610.8823.9510172067568330300.75012182001
2Lawton ZacherPhantoms (PHI)74120.9162.514310018214129000.444976010
3Georgi RomanovPhantoms (PHI)82210.9102.75327001516795000.6673421100
Statistiques d’équipe totales ou en moyenne3316940.8953.3817762010094955430242929111


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Alexandre DoucetPhantoms (PHI)C/LW/RW222002-01-12CANNo187 Lbs6 ft0NoNoTrade2025-07-02NoNo12025-09-08FalseFalsePro & Farm771,750$492,606$77,175$49,261$No---------------------------
Ben RobertsonPhantoms (PHI)D202004-09-18USANo192 Lbs5 ft9NoNoAssign ManuallyNoNo32025-11-16FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Billy SweezeyPhantoms (PHI)D281996-02-06USANo206 Lbs6 ft1NoNoAssign ManuallyNoNo32025-11-08FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Brady StonehousePhantoms (PHI)LW/RW202004-08-06CANNo194 Lbs5 ft8NoNoAssign ManuallyNoNo32025-11-16FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Dalton BancroftPhantoms (PHI)LW/RW232001-02-26CANNo212 Lbs6 ft1NoNoAssign ManuallyNoNo32025-11-16FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Danil GushchinPhantoms (PHI)LW/RW222002-02-06RUSNo165 Lbs5 ft8NoNoN/ANoNo12024-08-31FalseFalsePro & Farm866,250$552,926$86,625$55,293$No---------------------------
Elliot DesnoyersPhantoms (PHI)LW/RW222002-01-21CANNo183 Lbs5 ft11NoNoN/ANoNo12024-08-31FalseFalsePro & Farm735,000$469,149$73,500$46,915$No---------------------------
Georgi RomanovPhantoms (PHI)G251999-12-15RUSNo207 Lbs6 ft5NoNoN/ANoNo12025-09-08FalseFalsePro & Farm682,500$435,638$68,250$43,564$No---------------------------
Grant HuttonPhantoms (PHI)D291995-07-25USANo210 Lbs6 ft3NoNoAssign ManuallyNoNo32025-11-04FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Hudson SchandorPhantoms (PHI)C/LW242000-09-29CANNo100 Lbs4 ft0NoNoFree AgentNoNo12025-07-04FalseFalsePro & Farm650,000$414,894$65,000$41,489$No---------------------------
Israel Mianscum (sur la masse salariale)Phantoms (PHI)C/LW/RW212003-04-18CANNo198 Lbs6 ft1NoNoTrade2025-07-02NoNo1FalseFalsePro & Farm650,000$414,894$65,000$41,489$No---------------------------
Jeremy WilmerPhantoms (PHI)LW/RW212003-08-16USANo100 Lbs4 ft0NoNoFree AgentNoNo22025-07-04FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$--------650,000$--------No--------
Jimi SuomiPhantoms (PHI)D212003-03-01FINNo165 Lbs5 ft10NoNoTrade2025-07-04NoNo1FalseFalsePro & Farm675,000$430,851$67,500$43,085$No---------------------------
Joey AndersonPhantoms (PHI)LW/RW261998-06-19USANo207 Lbs6 ft0NoNoN/ANoNo12024-08-31FalseFalsePro & Farm1,700,000$1,085,106$170,000$108,511$No---------------------------
Josef KorenarPhantoms (PHI)G261998-01-31CZENo185 Lbs6 ft1NoNoN/ANoNo12025-09-08FalseFalsePro & Farm682,500$435,638$68,250$43,564$No---------------------------
Kurtis MacDermidPhantoms (PHI)LW/RW301994-03-25CANNo233 Lbs6 ft5NoNoTrade2025-11-10NoNo12025-06-26FalseFalsePro & Farm650,000$414,894$65,000$41,489$No---------------------------
Lawton ZacherPhantoms (PHI)G212003-12-01USANo179 Lbs6 ft0NoNoAssign ManuallyNoNo32025-11-16FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Logan MaillouxPhantoms (PHI)D212003-04-15CANNo213 Lbs6 ft3NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,312,500$837,766$131,250$83,777$No1,312,500$--------1,312,500$--------No--------
Luca MunzenbergerPhantoms (PHI)D222002-11-24GERYes201 Lbs6 ft0NoNoProspectNoNo22025-08-20FalseFalsePro & Farm750,000$478,723$75,000$47,872$No750,000$--------750,000$--------No--------
Lucas OlvestadPhantoms (PHI)D222002-03-19SWENo190 Lbs6 ft1NoNoFree AgentNoNo12025-07-05FalseFalsePro & Farm650,000$414,894$65,000$41,489$No---------------------------
Matt Martin (contrat à 1 volet)Phantoms (PHI)LW/RW351989-05-08CANNo215 Lbs6 ft3NoNoFree AgentNoNo12025-06-09FalseFalsePro & Farm650,000$412,366$650,000$412,366$No---------------------------
Matthew SopPhantoms (PHI)C/LW212003-02-04CANNo183 Lbs6 ft0NoNoTrade2025-07-02NoNo1FalseFalsePro & Farm650,000$414,894$65,000$41,489$No---------------------------
Patrick Brown (contrat à 1 volet)Phantoms (PHI)C/RW321992-05-29USANo218 Lbs6 ft1NoNoFree AgentNoNo12025-06-26FalseFalsePro & Farm650,000$412,366$650,000$412,366$No---------------------------
Riley ThompsonPhantoms (PHI)C222002-08-17CANNo216 Lbs6 ft2NoNoAssign ManuallyNoNo32025-11-16FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Sam DickinsonPhantoms (PHI)D182006-06-07CANYes209 Lbs6 ft1NoNoDraftNoNo32025-08-20FalseFalsePro & Farm1,500,000$957,447$150,000$95,745$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------
Santeri HuovilaPhantoms (PHI)LW202004-07-16FINNo172 Lbs5 ft10NoNoAssign ManuallyNoNo32025-11-16FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Tom WillanderPhantoms (PHI)D192005-02-09SWEYes190 Lbs5 ft11NoNoProspectNoNo32025-08-20FalseFalsePro & Farm1,500,000$957,447$150,000$95,745$No1,500,000$1,500,000$-------1,500,000$1,500,000$-------NoNo-------
Viktor HurtigPhantoms (PHI)D222002-04-28SWEYes198 Lbs6 ft4NoNoProspectNoNo22025-08-20FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$--------650,000$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2823.39190 Lbs5 ft111.86793,768$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matt MartinAlexandre DoucetPatrick Brown28122
2Kurtis MacDermidRiley ThompsonSanteri Huovila28122
3Joey AndersonHudson SchandorDanil Gushchin25122
4Elliot DesnoyersMatthew SopJeremy Wilmer19122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben RobertsonLuca Munzenberger32122
2Logan MaillouxBilly Sweezey30122
3Grant HuttonJimi Suomi28122
4Ben RobertsonBilly Sweezey10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Patrick BrownAlexandre DoucetElliot Desnoyers50122
2Kurtis MacDermidDanil GushchinSanteri Huovila50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Grant HuttonLuca Munzenberger50122
2Logan MaillouxBilly Sweezey50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Alexandre DoucetJoey Anderson50122
2Hudson SchandorSanteri Huovila50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jimi SuomiGrant Hutton50122
2Logan MaillouxBilly Sweezey50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Riley Thompson50122Jimi SuomiLuca Munzenberger50122
2Alexandre Doucet50122Logan MaillouxBilly Sweezey50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Patrick BrownDanil Gushchin50122
2Kurtis MacDermidSanteri Huovila50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben RobertsonJimi Suomi50122
2Logan MaillouxBilly Sweezey50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Danil GushchinRiley ThompsonPatrick BrownLuca MunzenbergerLogan Mailloux
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Hudson SchandorAlexandre DoucetKurtis MacDermidLogan MaillouxBilly Sweezey
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Kurtis MacDermid, Elliot Desnoyers, Danil GushchinDanil Gushchin, Elliot DesnoyersKurtis MacDermid
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Billy Sweezey, Jimi Suomi, Luca MunzenbergerBilly SweezeyBilly Sweezey, Luca Munzenberger
Tirs de pénalité
Alexandre Doucet, Danil Gushchin, Elliot Desnoyers, Kurtis MacDermid, Patrick Brown
Gardien
#1 : Lawton Zacher, #2 : Josef Korenar


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
1Americans1010000046-2000000000001010000046-200.000461000273839112532733232538371664235120.00%6350.00%034370248.86%32566948.58%22446648.07%612311580301585284
2Bills10000010431000000000001000001043121.0004610002738391137327332325384262619600.00%3166.67%034370248.86%32566948.58%22446648.07%612311580301585284
3Crunch20001001880200010018800000000000030.75081321002738391163327332325386622325110110.00%6350.00%034370248.86%32566948.58%22446648.07%612311580301585284
4Grisards422000001314-12110000067-12110000077040.500132134002738391111732733232538124431328920315.00%16568.75%134370248.86%32566948.58%22446648.07%612311580301585284
5Gulls1010000034-1000000000001010000034-100.0003580027383911303273323253840133819300.00%9188.89%034370248.86%32566948.58%22446648.07%612311580301585284
6Moose412000101213-12020000038-52100001095440.500121830002738391114832733232538128431011117228.57%18477.78%134370248.86%32566948.58%22446648.07%612311580301585284
7Norsemen20100010610-4100000105411010000016-520.500691500273839117032733232538732058478225.00%9277.78%034370248.86%32566948.58%22446648.07%612311580301585284
8Penguins22000000734000000000002200000073441.00071118002738391180327332325385118444411436.36%7185.71%034370248.86%32566948.58%22446648.07%612311580301585284
9Reign11000000725000000000001100000072521.0007121900273839113332733232538331674213266.67%7185.71%034370248.86%32566948.58%22446648.07%612311580301585284
10Roadrunners1000010056-11000010056-10000000000010.500581300273839113532733232538341825303266.67%7271.43%034370248.86%32566948.58%22446648.07%612311580301585284
11Senators20000011880000000000002000001188030.7508917002738391179327332325386413595810550.00%7271.43%034370248.86%32566948.58%22446648.07%612311580301585284
12Titans2110000067-12110000067-10000000000020.50061117002738391163327332325386615355210220.00%10280.00%134370248.86%32566948.58%22446648.07%612311580301585284
13Whalers22000000945110000005231100000042241.00091524002738391167327332325385519115577342.86%10190.00%034370248.86%32566948.58%22446648.07%612311580301585284
14White Wolves1000000156-11000000156-10000000000010.50057120027383911473273323253831885287114.29%5340.00%034370248.86%32566948.58%22446648.07%612311580301585284
15Wolves3210000012933210000012930000000000040.667122234002738391110432733232538105271758123730.43%10370.00%034370248.86%32566948.58%22446648.07%612311580301585284
Total291190114310910361555011125557-214640003154468360.62110917328200273839119983273323253894929710637301333526.32%1303473.85%334370248.86%32566948.58%22446648.07%612311580301585284
_Since Last GM Reset291190114310910361555011125557-214640003154468360.62110917328200273839119983273323253894929710637301333526.32%1303473.85%334370248.86%32566948.58%22446648.07%612311580301585284
_Vs Conference2310900031807821155000103737012540002143412270.587801272070027383911783327332325387432278215811042927.88%1022476.47%334370248.86%32566948.58%22446648.07%612311580301585284
_Vs Division8770003126242444000101214-24330002114104211.3132643690027383911260327332325382417621118541921.95%33875.76%234370248.86%32566948.58%22446648.07%612311580301585284

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2936SOL2109173282998949297106373000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
291191143109103
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
155511125557
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
146400315446
Derniers 10 matchs
WLOTWOTL SOWSOL
430003
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1333526.32%1303473.85%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
3273323253827383911
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
34370248.86%32566948.58%22446648.07%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
612311580301585284


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
318Wolves5Phantoms4LSommaire du match
533Wolves3Phantoms5WSommaire du match
642Phantoms4Americans6LSommaire du match
750Phantoms1Norsemen6LSommaire du match
1179Norsemen4Phantoms5WXXSommaire du match
14100Phantoms5Senators4WXXSommaire du match
15110Whalers2Phantoms5WSommaire du match
16120Phantoms2Grisards4LSommaire du match
19143Titans4Phantoms1LSommaire du match
20146Phantoms5Grisards3WSommaire du match
24174Grisards3Phantoms5WSommaire du match
26186Phantoms4Moose1WSommaire du match
29205Wolves1Phantoms3WSommaire du match
33232Crunch3Phantoms4WXSommaire du match
34238Phantoms4Whalers2WSommaire du match
38265Moose3Phantoms2LSommaire du match
41287Phantoms3Penguins1WSommaire du match
43298Titans3Phantoms5WSommaire du match
46321Roadrunners6Phantoms5LXSommaire du match
48335Phantoms4Bills3WXXSommaire du match
50350Phantoms4Penguins2WSommaire du match
51361Grisards4Phantoms1LSommaire du match
54380Phantoms7Reign2WSommaire du match
55392White Wolves6Phantoms5LXXSommaire du match
58416Phantoms3Gulls4LSommaire du match
60424Moose5Phantoms1LSommaire du match
62444Phantoms5Moose4WXXSommaire du match
64454Crunch5Phantoms4LXXSommaire du match
66464Phantoms3Senators4LXXSommaire du match
69489Norsemen-Phantoms-
73513Phantoms-Admirals-
74524Gorillas-Phantoms-
77542Phantoms-Titans-
79553Blood Miners-Phantoms-
81573Phantoms-Norsemen-
83583Wolves-Phantoms-
85598Phantoms-Norsemen-
87613Phantoms-Blossom Bytes-
89624Titans-Phantoms-
91641Phantoms-Rams-
92653Rams-Phantoms-
95671Phantoms-Grisards-
97687Octopus-Phantoms-
99698Phantoms-Moose-
101717Phantoms-Wolf Pack-
102726Blossom Bytes-Phantoms-
104740Phantoms-Blossom Bytes-
106754Whalers-Phantoms-
109771Phantoms-Whalers-
111785Gulls-Phantoms-
114811Phantoms-Wolf Pack-
115818Penguins-Phantoms-
118837Phantoms-Blood Miners-
120849Gulls-Phantoms-
122866Phantoms-Whalers-
124879Redhawks-Phantoms-
126902Phantoms-Reign-
128913Admirals-Phantoms-
130928Phantoms-Bears-
132944Silver Knights-Phantoms-
134957Phantoms-Grisards-
137976Eagles-Phantoms-
138987Phantoms-Bears-
1411009Phantoms-Americans-
1421018Admirals-Phantoms-
1451039Phantoms-Bulldogs-
1461048Phantoms-Americans-
1471053Rams-Phantoms-
1511079Griffins-Phantoms-
1531100Phantoms-Wolves-
1541106Phantoms-Rocket-
1561117Bears-Phantoms-
1591140Phantoms-Senators-
1601149Bears-Phantoms-
1641174Phantoms-Mountaineers-
1651182Americans-Phantoms-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1681205Americans-Phantoms-
1731233Wolf Pack-Phantoms-
1751248Phantoms-Saints-
1781263Phantoms-Wolves-
1801275Senators-Phantoms-
1861307Senators-Phantoms-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité25005500
Prix des billets4520
Assistance25,61353,921
Assistance PCT68.30%65.36%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
26 5302 - 66.28% 178,480$2,677,206$8000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
983,536$ 2,027,550$ 2,027,550$ 600,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
13,976$ 983,536$ 24 1

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
4,640,490$ 120 13,976$ 1,677,120$




Phantoms Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

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 des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

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