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Phantoms
GP: 21 | W: 11 | L: 9 | OTL: 1 | P: 23
GF: 68 | GA: 69 | PP%: 22.64% | PK%: 76.00%
DG: Alexandre Fortier | Morale : 52 | Moyenne d’équipe : 62
Prochains matchs #350 vs Moose

Centre de jeu
Eagles
8-9-3, 19pts
3
4 Phantoms
11-9-1, 23pts
Team Stats
OTL1SéquenceL1
6-4-1Fiche domicile9-2-0
2-5-2Fiche domicile2-7-1
4-4-2Derniers 10 matchs7-3-0
3.40Buts par match 3.24
3.75Buts contre par match 3.29
34.92%Pourcentage en avantage numérique22.64%
76.19%Pourcentage en désavantage numérique76.00%
Phantoms
11-9-1, 23pts
0
4 Iowa Wild
12-5-3, 27pts
Team Stats
L1SéquenceW2
9-2-0Fiche domicile7-4-1
2-7-1Fiche domicile5-1-2
7-3-0Derniers 10 matchs7-2-1
3.24Buts par match 3.60
3.29Buts contre par match 3.20
22.64%Pourcentage en avantage numérique26.42%
76.00%Pourcentage en désavantage numérique84.78%
Moose
14-8-0, 28pts
2025-10-11
Phantoms
11-9-1, 23pts
Statistiques d’équipe
SOW1SéquenceL1
7-4-0Fiche domicile9-2-0
7-4-0Fiche visiteur2-7-1
6-4-010 derniers matchs7-3-0
3.55Buts par match 3.24
2.73Buts contre par match 3.24
14.06%Pourcentage en avantage numérique22.64%
74.60%Pourcentage en désavantage numérique76.00%
Phantoms
11-9-1, 23pts
2025-10-13
Canucks
12-8-2, 26pts
Statistiques d’équipe
L1SéquenceW1
9-2-0Fiche domicile6-3-2
2-7-1Fiche visiteur6-5-0
7-3-010 derniers matchs7-2-1
3.24Buts par match 3.32
3.29Buts contre par match 3.32
22.64%Pourcentage en avantage numérique22.86%
76.00%Pourcentage en désavantage numérique77.22%
Moose
14-8-0, 28pts
2025-10-15
Phantoms
11-9-1, 23pts
Statistiques d’équipe
SOW1SéquenceL1
7-4-0Fiche domicile9-2-0
7-4-0Fiche visiteur2-7-1
6-4-010 derniers matchs7-3-0
3.55Buts par match 3.24
2.73Buts contre par match 3.24
14.06%Pourcentage en avantage numérique22.64%
74.60%Pourcentage en désavantage numérique76.00%
Meneurs d'équipe
Buts
Ruslan Iskhakov
10
Passes
Sebastian Aho (DEF)
17
Points
Sebastian Aho (DEF)
19
Plus/Moins
Brendan Harms
3
Victoires
Malcolm Subban
9
Pourcentage d’arrêts
Jon Gillies
0.947

Statistiques d’équipe
Buts pour
68
3.24 GFG
Tirs pour
587
27.95 Avg
Pourcentage en avantage numérique
22.6%
12 GF
Début de zone offensive
39.0%
Buts contre
69
3.29 GAA
Tirs contre
655
31.19 Avg
Pourcentage en désavantage numérique
76.0%%
12 GA
Début de la zone défensive
42.0%
Informations de l'équipe

Directeur généralAlexandre Fortier
EntraîneurMike Sullivan
DivisionDivision Atlantique
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance3,000
Billets de saison300


Informations de la formation

Équipe Pro26
Équipe Mineure18
Limite Contrat44 / 56
Espoirs20


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
1Pascal Laberge0X100.0065458872687877707764696559575054536402821,000,000$
2Jeff Malott (R)0X100.007555828074698471507066726050454056640301900,000$
3Mathieu Joseph0XXX100.0063458670737262656865676463727154536402931,000,000$
4Kailer Yamamoto0XXX99.005845947068727164666564646368665452630283900,000$
5Ivan Chekhovich0XX97.006145947267727566646868626254475457620273800,000$
6Kirill Slepets0XX100.005945957265767665706561686054485857620273800,000$
7Ruslan Iskhakov (R)0X100.005646787465707069706768706549517057620263750,000$
8Brendan Harms0XX100.005946997170686669576666686648463855610311650,000$
9jake wise (R)0X99.006447857169606066716765686252526057610263750,000$
10Jakub Izacky0XX100.005944927071656467616363686149453447600323800,000$
11Sebastian Aho (DEF)0X100.0066458475677491754573687559675646546703022,500,000$
12Kale Clague0X100.0062468972697980694572707160604954576502821,200,000$
13Maxwell Gildon0X100.0065448772687573694568697356544858476402731,000,000$
14Filip Westerlund0X100.007053877268737258456058685752455853610273700,000$
15arvid bergstrom (R)0X100.005346847164676764456364676145458057600213750,000$
16Ben Thomas0X100.006647897069686957456062645753465055600301700,000$
Rayé
1Samuel Blais0XX93.0077458873737481686367666664715654486603022,000,000$
2Zachary Senyshyn0XXX92.1772598972718076696769727370605154416602911,200,000$
3Filip Chlapik0X92.0077457470717676676770676662605054576402911,000,000$
4Robin Kovacs0XX100.006545897071656868566565656054474650620291650,000$
5Karl Henriksson (R)0XX100.006653617367707067586569706549517044610253750,000$
6Timotej Sille0XX100.005446957174666367586061665948454242590311650,000$
7Josh Wesley0X69.636445817072676158455654735850485317600301700,000$
MOYENNE D’ÉQUIPE97.43644787726971726658666568615550545163
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
1Malcolm Subban099.007983817980738076777981616334536403221,200,000$
2Jon Gillies099.007576788579767977787781545534626303221,200,000$
Rayé
1Edwin Minney0100.00756367817973747373686753555744600303500,000$
MOYENNE D’ÉQUIPE99.3376747582797478757675765658425362
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Sullivan86619377999947USA572100,000$


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
1Sebastian Aho (DEF)Phantoms (Phi)D21217192402324378185.41%3749723.681231541000040000%000000.7600000130
2Ruslan IskhakovPhantoms (Phi)C2110717-460112955154518.18%134716.55112525000142244.13%34900000.9800000210
3Kale ClaguePhantoms (Phi)D216101612016192952320.69%2047222.513141037000040100%000100.6800000110
4Maxwell GildonPhantoms (Phi)D216915-160231435111817.14%2142120.093361238000039110%000000.7100000012
5Kirill SlepetsPhantoms (Phi)LW/RW2121113-26012224216344.76%834016.210114120000140037.84%3700000.7600000100
6Pascal LabergePhantoms (Phi)C193912-2002226329279.38%436919.450225420000300045.41%18500000.6500000101
7Jeff MalottPhantoms (Phi)RW217512-280322854204112.96%435416.882245340000181146.34%12300000.6811000121
8Zachary SenyshynPhantoms (Phi)C/LW/RW16481212025244312269.30%631419.660223350000271045.67%30000000.7600000200
9Mathieu JosephPhantoms (Phi)C/LW/RW1747112809113371712.12%429017.100335240000241057.78%4500000.7601000100
10arvid bergstromPhantoms (Phi)D212911-42010161331115.38%1937918.07000218000012000%000000.5800000011
11jake wisePhantoms (Phi)C21551014011192681919.23%324211.5300000000000041.45%15200000.8300000000
12Filip ChlapikPhantoms (Phi)C2054904039264292711.90%233716.890113250000130044.64%28900000.5300000002
13Ivan ChekhovichPhantoms (Phi)LW/RW21257-2602016389305.26%437417.83123524000010048.94%4700000.3700000001
14Brendan HarmsPhantoms (Phi)LW/RW16235300281151318.18%3996.2400012000080050.00%3800001.0000000000
15Filip WesterlundPhantoms (Phi)D210552395251012380%2341219.62022135000033000%000000.2400000000
16Robin KovacsPhantoms (Phi)LW/RW17325-200811248912.50%320712.19101390000101043.59%7800000.4811000100
17Kailer YamamotoPhantoms (Phi)C/LW/RW18224-140416257228.00%526214.560001200000142053.66%4100000.3100000000
18Samuel BlaisPhantoms (Phi)LW/RW14224-20011131751311.76%015611.1501105000000041.67%1200000.5100000011
19Ben ThomasPhantoms (Phi)D19044-180201010230%1232317.050000100002000%000000.2500000000
20Josh WesleyPhantoms (Phi)D2000-320011110%22211.370000000000000%00000000000000
21Jakub IzackyPhantoms (Phi)LW/RW3000000001000%000.090000000000000%00000000000000
22Timotej SillePhantoms (Phi)LW/RW5000100039250%0418.3300000000000050.00%20000000000000
23Karl HenrikssonPhantoms (Phi)LW/RW11000-120526370%1555.0500000000000050.00%40000000000000
Statistiques d’équipe totales ou en moyenne38767124191-14113532834859516841711.26%182632416.3412233580437000133810445.24%170200100.602300011109
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
1Malcolm SubbanPhantoms (Phi)199910.8893.381100406255800200192030
2Jon GilliesPhantoms (Phi)32000.9471.72174005950000.6673219001
Statistiques d’équipe totales ou en moyenne2211910.8973.161274406765300232121031


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 ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer UFA Rappel d'urgence Type Salaire actuel Plafond 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
Ben ThomasPhantoms (Phi)D301996-05-28CANNo187 Lbs6 ft1NoNoN/ANoNo12024-05-29FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Brendan HarmsPhantoms (Phi)LW/RW311994-12-02CANNo183 Lbs6 ft0NoNoFree Agent2024-09-20NoNo12025-08-22FalseFalsePro & Farm650,000$0$0$No---------------------------Lien
Edwin MinneyPhantoms (Phi)G301996-03-29USANo208 Lbs6 ft5NoNoFree Agent2024-07-27NoNo32026-09-30FalseFalsePro & Farm500,000$0$0$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien
Filip Chlapik (sur la masse salariale)Phantoms (Phi)C291997-06-03CZENo207 Lbs6 ft2NoNoN/ANoNo12024-05-29FalseFalsePro & Farm1,000,000$0$0$Yes---------------------------Lien
Filip WesterlundPhantoms (Phi)D271999-04-17SWENo180 Lbs5 ft11NoNoN/ANoNo32026-05-12FalseFalsePro & Farm700,000$0$0$No700,000$700,000$-------700,000$700,000$-------NoNo-------Lien
Ivan ChekhovichPhantoms (Phi)LW/RW271999-01-04RUSNo185 Lbs5 ft10NoNoN/ANoNo32026-05-12FalseFalsePro & Farm800,000$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien
Jakub IzackyPhantoms (Phi)LW/RW321993-11-25CZENo187 Lbs6 ft0NoNoFree AgentNoNo32026-09-27FalseFalsePro & Farm800,000$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien
Jeff MalottPhantoms (Phi)RW301996-08-07CANYes215 Lbs6 ft5NoNoFree AgentNoNo12026-05-11FalseFalsePro & Farm900,000$0$0$No---------900,000$900,000$----------------Lien
Jon GilliesPhantoms (Phi)G321994-01-22USANo223 Lbs6 ft6NoNoFree AgentNoNo22025-07-03FalseFalsePro & Farm1,200,000$0$0$No1,200,000$--------1,200,000$--------No--------Lien
Josh Wesley (sur la masse salariale)Phantoms (Phi)D301996-04-09USANo201 Lbs6 ft3NoNoTrade2026-09-25NoNo12024-04-29FalseFalsePro & Farm700,000$0$0$Yes---------------------------Lien
Kailer YamamotoPhantoms (Phi)C/LW/RW281998-09-29USANo178 Lbs5 ft9NoNoFree AgentNoNo32026-05-12FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------Lien
Kale ClaguePhantoms (Phi)D281998-06-05CANNo192 Lbs6 ft0NoNoN/ANoNo22025-05-28FalseFalsePro & Farm1,200,000$0$0$No1,200,000$--------1,200,000$--------No--------Lien
Karl HenrikssonPhantoms (Phi)LW/RW252001-02-05SWEYes174 Lbs5 ft9NoNoProspectNoNo32026-06-18FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Kirill SlepetsPhantoms (Phi)LW/RW271999-04-06RUSNo165 Lbs5 ft10NoNoN/ANoNo32026-05-12FalseFalsePro & Farm800,000$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien
Malcolm SubbanPhantoms (Phi)G321993-12-21USANo215 Lbs6 ft1NoNoFree Agent2024-01-13NoNo22025-07-03FalseFalsePro & Farm1,200,000$0$0$No1,200,000$--------1,200,000$--------No--------Lien
Mathieu JosephPhantoms (Phi)C/LW/RW291997-02-09CANNo190 Lbs6 ft2NoNoFree Agent2025-05-01NoNo32026-05-12FalseFalsePro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien
Maxwell GildonPhantoms (Phi)D271999-05-17USANo194 Lbs6 ft3NoNoN/ANoNo32026-05-12FalseFalsePro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien
Pascal LabergePhantoms (Phi)C281998-04-09CANNo172 Lbs6 ft1NoNoN/ANoNo22025-05-28FalseFalsePro & Farm1,000,000$0$0$No1,000,000$--------1,000,000$--------No--------Lien
Robin KovacsPhantoms (Phi)LW/RW291996-11-16SWENo192 Lbs6 ft0NoNoFree AgentNoNo12025-08-22FalseFalsePro & Farm650,000$0$0$No---------------------------Lien
Ruslan IskhakovPhantoms (Phi)C262000-07-22RUSYes152 Lbs5 ft8NoNoProspectNoNo32026-05-15FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Samuel Blais (sur la masse salariale)Phantoms (Phi)LW/RW301996-06-17CANNo206 Lbs6 ft2NoNoTrade2026-09-25NoNo22025-05-28FalseFalsePro & Farm2,000,000$0$0$Yes2,000,000$--------2,000,000$--------No--------Lien
Sebastian Aho (DEF)Phantoms (Phi)D301996-02-17SWENo177 Lbs5 ft11NoNoTrade2025-04-09NoNo22025-05-28FalseFalsePro & Farm2,500,000$0$0$No2,500,000$--------2,500,000$--------No--------Lien
Timotej SillePhantoms (Phi)LW/RW311995-06-22SVKNo209 Lbs6 ft3NoNoFree AgentNoNo12025-08-22FalseFalsePro & Farm650,000$0$0$No---------------------------Lien
Zachary Senyshyn (sur la masse salariale)Phantoms (Phi)C/LW/RW291997-03-30CANNo207 Lbs6 ft1NoNoN/ANoNo12024-05-29FalseFalsePro & Farm1,200,000$0$0$Yes---------------------------Lien
arvid bergstromPhantoms (Phi)D212005-06-12SWEYes154 Lbs5 ft10NoNoProspectNoNo32026-05-15FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
jake wisePhantoms (Phi)C262000-02-28USAYes190 Lbs5 ft10NoNoProspectNoNo32026-05-15FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2628.62190 Lbs6 ft12.15963,462$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Pascal LabergeJeff Malott25122
2Mathieu JosephRuslan Iskhakov25122
3Kailer Yamamotojake wiseIvan Chekhovich25122
4Kirill Slepets25122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sebastian Aho (DEF)Kale Clague25122
2Maxwell GildonFilip Westerlund25122
3Ben Thomasarvid bergstrom25122
4Sebastian Aho (DEF)Maxwell Gildon25122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jeff Malott50122
2Ruslan IskhakovIvan ChekhovichPascal Laberge50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sebastian Aho (DEF)Filip Westerlund50122
2Maxwell Gildonarvid bergstrom50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Kirill Slepets50122
2Jeff MalottPascal Laberge50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Maxwell GildonSebastian Aho (DEF)50122
2arvid bergstromFilip Westerlund50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jeff Malott50122Maxwell GildonSebastian Aho (DEF)50122
2Pascal Laberge50122arvid bergstromFilip Westerlund50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Ruslan Iskhakov50122
2Jeff MalottPascal Laberge50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sebastian Aho (DEF)arvid bergstrom50122
2Maxwell GildonFilip Westerlund50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Pascal LabergeJeff MalottSebastian Aho (DEF)Kale Clague
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Kirill SlepetsSebastian Aho (DEF)arvid bergstrom
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, Pascal Laberge, jake wiseKirill Slepets, Ruslan IskhakovJeff Malott
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
arvid bergstrom, Sebastian Aho (DEF), Filip WesterlundSebastian Aho (DEF)Filip Westerlund, Sebastian Aho (DEF)
Tirs de pénalité
Jeff Malott, Kirill Slepets, Pascal Laberge, Ruslan Iskhakov,
Gardien
#1 : Malcolm Subban, #2 : Jon Gillies


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
TotalDomicile Visiteur
# 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 RI
1Americans1010000024-2000000000001010000024-200.000246102819184271892021909227616200.00%30100.00%030665147.00%31970145.51%14231644.94%477328527152273133
2Bears10000010431100000104310000000000021.0004610002819184211892021909361810132150.00%5180.00%030665147.00%31970145.51%14231644.94%477328527152273133
3BruinsF3210000013762200000011471010000023-140.667132437002819184671892021909893512395240.00%6350.00%030665147.00%31970145.51%14231644.94%477328527152273133
4Checkers10001000431100010004310000000000021.00047110028191842618920219095213812000%30100.00%030665147.00%31970145.51%14231644.94%477328527152273133
5Comets1010000034-1000000000001010000034-100.0003690028191842818920219092310819100.00%3233.33%030665147.00%31970145.51%14231644.94%477328527152273133
6Condors1010000035-21010000035-20000000000000.000369002819184121892021909408424000%20100.00%030665147.00%31970145.51%14231644.94%477328527152273133
7Crunch11000000541110000005410000000000021.0005914002819184241892021909366231211100.00%5260.00%030665147.00%31970145.51%14231644.94%477328527152273133
8Eagles10001000431100010004310000000000021.0004812002819184381892021909288413100.00%2150.00%030665147.00%31970145.51%14231644.94%477328527152273133
9Firebirds1010000014-3000000000001010000014-300.000123002819184341892021909274417500.00%20100.00%030665147.00%31970145.51%14231644.94%477328527152273133
10Iowa Wild1010000004-4000000000001010000004-400.000000002819184211892021909364210300.00%110.00%030665147.00%31970145.51%14231644.94%477328527152273133
11Islanders1010000013-21010000013-20000000000000.0001120028191842618920219092551017100.00%5180.00%030665147.00%31970145.51%14231644.94%477328527152273133
12Monsters11000000312110000003120000000000021.0003690028191843518920219092376129222.22%30100.00%030665147.00%31970145.51%14231644.94%477328527152273133
13PenguinsF1000010023-1000000000001000010023-110.500246002819184211892021909357412200.00%20100.00%030665147.00%31970145.51%14231644.94%477328527152273133
14Roadrunners1010000046-2000000000001010000046-200.00047110028191842618920219093112220300.00%10100.00%030665147.00%31970145.51%14231644.94%477328527152273133
15SenatorsF11000000541000000000001100000054121.000510150028191844818920219092780203266.67%000%030665147.00%31970145.51%14231644.94%477328527152273133
16StarsF1010000024-2000000000001010000024-200.0002351028191842818920219093074134125.00%20100.00%030665147.00%31970145.51%14231644.94%477328527152273133
17Wolf Pack22000000963110000006421100000032141.00091726002819184741892021909641710409333.33%5180.00%030665147.00%31970145.51%14231644.94%477328527152273133
18Wolves11000000312110000003120000000000021.000347002819184311892021909316015200.00%000%030665147.00%31970145.51%14231644.94%477328527152273133
Total2189021106869-11162020104431131027001002438-14230.548681241922028191845871892021909655182117324531222.64%501276.00%030665147.00%31970145.51%14231644.94%477328527152273133
_Since Last GM Reset2189021106869-11162020104431131027001002438-14230.548681241922028191845871892021909655182117324531222.64%501276.00%030665147.00%31970145.51%14231644.94%477328527152273133
_Vs Conference1575011105246685101010342212724001001824-6190.633529414610281918442718920219094671369523233927.27%391074.36%030665147.00%31970145.51%14231644.94%477328527152273133
_Vs Division7230010029227411000002011931200100911-250.357295483102819184192189202190922669499911545.45%17570.59%030665147.00%31970145.51%14231644.94%477328527152273133

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2123L16812419258765518211732420
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
218921106869
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
116220104431
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
102701002438
Derniers 10 matchs
WLOTWOTL SOWSOL
532000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
531222.64%501276.00%0
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
18920219092819184
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
30665147.00%31970145.51%14231644.94%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
477328527152273133


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
2 - 2025-08-2716Crunch4Phantoms5WSommaire du match
3 - 2025-08-2823Condors5Phantoms3LSommaire du match
6 - 2025-08-3144Islanders3Phantoms1LSommaire du match
8 - 2025-09-0271Phantoms2StarsF4LSommaire du match
10 - 2025-09-0486Wolf Pack4Phantoms6WSommaire du match
11 - 2025-09-0590Phantoms2PenguinsF3LXSommaire du match
14 - 2025-09-08112Bears3Phantoms4WXXSommaire du match
17 - 2025-09-11136Phantoms1Firebirds4LSommaire du match
19 - 2025-09-13152BruinsF1Phantoms6WSommaire du match
21 - 2025-09-15163Phantoms2BruinsF3LSommaire du match
23 - 2025-09-17174Phantoms3Comets4LSommaire du match
25 - 2025-09-19190Monsters1Phantoms3WSommaire du match
28 - 2025-09-22214Wolves1Phantoms3WSommaire du match
30 - 2025-09-24232Phantoms2Americans4LSommaire du match
32 - 2025-09-26247Phantoms5SenatorsF4WSommaire du match
33 - 2025-09-27257Checkers3Phantoms4WXSommaire du match
36 - 2025-09-30271Phantoms3Wolf Pack2WSommaire du match
38 - 2025-10-02285Phantoms4Roadrunners6LSommaire du match
39 - 2025-10-03294BruinsF3Phantoms5WSommaire du match
43 - 2025-10-07320Eagles3Phantoms4WXSommaire du match
45 - 2025-10-09337Phantoms0Iowa Wild4LSommaire du match
47 - 2025-10-11350Moose-Phantoms-
49 - 2025-10-13365Phantoms-Canucks-
51 - 2025-10-15380Moose-Phantoms-
53 - 2025-10-17392Phantoms-Islanders-
55 - 2025-10-19412Phantoms-Gulls-
56 - 2025-10-20418Wolf Pack-Phantoms-
59 - 2025-10-23439Phantoms-Firebirds-
61 - 2025-10-25451Islanders-Phantoms-
64 - 2025-10-28477Canucks-Phantoms-
66 - 2025-10-30486Phantoms-Wolves-
68 - 2025-11-01502Phantoms-PenguinsF-
69 - 2025-11-02517Wolves-Phantoms-
72 - 2025-11-05535Phantoms-Checkers-
74 - 2025-11-07549Checkers-Phantoms-
76 - 2025-11-09566Phantoms-Checkers-
78 - 2025-11-11580Rocket-Phantoms-
80 - 2025-11-13600Phantoms-PenguinsF-
81 - 2025-11-14610Phantoms-BruinsF-
83 - 2025-11-16620Bears-Phantoms-
86 - 2025-11-19640Reign-Phantoms-
87 - 2025-11-20654Phantoms-Rocket-
91 - 2025-11-24673Phantoms-Wolves-
92 - 2025-11-25682Islanders-Phantoms-
95 - 2025-11-28704Griffins-Phantoms-
97 - 2025-11-30720Phantoms-Rocket-
100 - 2025-12-03740PenguinsF-Phantoms-
102 - 2025-12-05752Phantoms-StarsF-
104 - 2025-12-07769Condors-Phantoms-
107 - 2025-12-10791Phantoms-Crunch-
109 - 2025-12-12803Admirals-Phantoms-
112 - 2025-12-15828Rocket-Phantoms-
114 - 2025-12-17845Phantoms-Wolf Pack-
116 - 2025-12-19860Americans-Phantoms-
118 - 2025-12-21872Phantoms-Barracuda-
120 - 2025-12-23890Phantoms-SenatorsF-
121 - 2025-12-24898Wranglers-Phantoms-
125 - 2025-12-28925Phantoms-Marlies-
126 - 2025-12-29931Firebirds-Phantoms-
130 - 2026-01-02958Monsters-Phantoms-
132 - 2026-01-04978Phantoms-Silver Knights-
134 - 2026-01-06991Gulls-Phantoms-
137 - 2026-01-091016Marlies-Phantoms-
139 - 2026-01-111031Phantoms-Comets-
142 - 2026-01-141049PenguinsF-Phantoms-
143 - 2026-01-151054Phantoms-Americans-
146 - 2026-01-181075Phantoms-Marlies-
147 - 2026-01-191087Comets-Phantoms-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2026-01-211103Phantoms-Moose-
152 - 2026-01-241119Firebirds-Phantoms-
154 - 2026-01-261134Phantoms-Moose-
156 - 2026-01-281149Marlies-Phantoms-
158 - 2026-01-301162Phantoms-Icehogs-
160 - 2026-02-011182Comets-Phantoms-
164 - 2026-02-051208SenatorsF-Phantoms-
166 - 2026-02-071220Phantoms-Thunderbirds-
168 - 2026-02-091228Phantoms-Islanders-
170 - 2026-02-111239Phantoms-Crunch-
172 - 2026-02-131254SenatorsF-Phantoms-
175 - 2026-02-161280Phantoms-Bears-
176 - 2026-02-171291Americans-Phantoms-
180 - 2026-02-211313Crunch-Phantoms-
181 - 2026-02-221323Phantoms-Bears-
183 - 2026-02-241343Phantoms-Admirals-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4530
Assistance22,00011,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
31 3000 - 100.00% 178,800$1,966,800$3000125

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
547,341$ 2,015,000$ 2,015,000$ 100,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 522,882$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
5,542,800$ 139 11,495$ 1,597,805$




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