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Phantoms
GP: 8 | W: 3 | L: 4 | OTL: 1 | P: 7
GF: 24 | GA: 30 | PP%: 23.53% | PK%: 84.00%
DG: Alexandre Fortier | Morale : 48 | Moyenne d’équipe : 63
Prochains matchs #152 vs BruinsF

Centre de jeu
Bears
5-3-1, 11pts
3
4 Phantoms
3-4-1, 7pts
Team Stats
L1SéquenceL1
4-1-0Fiche domicile3-2-0
1-2-1Fiche domicile0-2-1
5-3-1Derniers 10 matchs3-4-1
3.33Buts par match 3.00
3.33Buts contre par match 3.75
19.05%Pourcentage en avantage numérique23.53%
70.59%Pourcentage en désavantage numérique84.00%
Phantoms
3-4-1, 7pts
1
4 Firebirds
3-6-0, 6pts
Team Stats
L1SéquenceW1
3-2-0Fiche domicile3-1-0
0-2-1Fiche domicile0-5-0
3-4-1Derniers 10 matchs3-6-0
3.00Buts par match 2.78
3.75Buts contre par match 4.11
23.53%Pourcentage en avantage numérique13.04%
84.00%Pourcentage en désavantage numérique72.73%
BruinsF
4-4-1, 9pts
2025-09-12
Phantoms
3-4-1, 7pts
Statistiques d’équipe
L1SéquenceL1
2-2-0Fiche domicile3-2-0
2-2-1Fiche visiteur0-2-1
4-4-110 derniers matchs3-4-1
2.67Buts par match 3.00
3.11Buts contre par match 3.00
10.53%Pourcentage en avantage numérique23.53%
76.47%Pourcentage en désavantage numérique84.00%
Phantoms
3-4-1, 7pts
2025-09-14
BruinsF
4-4-1, 9pts
Statistiques d’équipe
L1SéquenceL1
3-2-0Fiche domicile2-2-0
0-2-1Fiche visiteur2-2-1
3-4-110 derniers matchs4-4-1
3.00Buts par match 2.67
3.75Buts contre par match 2.67
23.53%Pourcentage en avantage numérique10.53%
84.00%Pourcentage en désavantage numérique76.47%
Phantoms
3-4-1, 7pts
2025-09-16
Comets
2-7-1, 5pts
Statistiques d’équipe
L1SéquenceOTW1
3-2-0Fiche domicile2-3-0
0-2-1Fiche visiteur0-4-1
3-4-110 derniers matchs2-7-1
3.00Buts par match 2.00
3.75Buts contre par match 2.00
23.53%Pourcentage en avantage numérique20.00%
84.00%Pourcentage en désavantage numérique52.00%
Meneurs d'équipe
Buts
Pascal Laberge
3
Passes
Mathieu Joseph
5
Points
Mathieu Joseph
7
Plus/Moins
Mathieu Joseph
2
Victoires
Malcolm Subban
2
Pourcentage d’arrêts
Jon Gillies
0.917

Statistiques d’équipe
Buts pour
24
3.00 GFG
Tirs pour
201
25.13 Avg
Pourcentage en avantage numérique
23.5%
4 GF
Début de zone offensive
36.6%
Buts contre
30
3.75 GAA
Tirs contre
262
32.75 Avg
Pourcentage en désavantage numérique
84.0%%
4 GA
Début de la zone défensive
43.5%
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 Pro22
Équipe Mineure18
Limite contact 40 / 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
1Jeff Malott (R)0X96.007555828074698471507066726050454050640301900,000$
2Mathieu Joseph0XXX97.0063458670737262656865676463727154506402931,000,000$
3Filip Chlapik0X100.0077457470717676676770676662605054506402911,000,000$
4Kailer Yamamoto0XXX100.005845947068727164666564646368665450630273900,000$
5Ivan Chekhovich0XX100.006145947267727566646868626254475450620273800,000$
6Kirill Slepets0XX100.005945957265767665706561686054485850620273800,000$
7Ruslan Iskhakov (R)0X99.005646787465707069706768706549517050620263750,000$
8Brendan Harms0XX100.005946997170686669576666686648463850610311650,000$
9jake wise (R)0X100.006447857169606066716765686252526050610263750,000$
10Karl Henriksson (R)0XX100.006653617367707067586569706549517047610253750,000$
11Timotej Sille0XX100.005446957174666367586061665948454245590311650,000$
12Sebastian Aho (DEF)0X100.0066458475677491754573687559675646476703022,500,000$
13Kale Clague0X100.0062468972697980694572707160604954506502821,200,000$
14Maxwell Gildon0X100.0065448772687574694568697356544858506402731,000,000$
15Filip Westerlund0X100.007053877268737258456058685752455846610273700,000$
16arvid bergstrom (R)0X100.005346847164676764456364676145458050600213750,000$
17Ben Thomas0X100.006647897069686957456062645753465050600301700,000$
Rayé
1Zachary Senyshyn0XXX100.0072598972718076696769727370605154466602911,200,000$
2Pascal Laberge0X100.0065458872687877707764696559575054486402821,000,000$
3Robin Kovacs0XX98.006545897071656868566565656054474649620291650,000$
MOYENNE D’ÉQUIPE99.50644786726972726758666668615550554963
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 Subban099.007983817980738076777981616334486403221,200,000$
2Jon Gillies0100.007576788579767977787781545534526303221,200,000$
Rayé
MOYENNE D’ÉQUIPE99.5077808082807580777878815859345064
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
1Mathieu JosephPhantoms (Phi)C/LW/RW8257260671741211.76%214918.710333130000190068.00%2500000.9401000000
2Pascal LabergePhantoms (Phi)C7336-100911104930.00%113719.650223110000180037.93%2900000.8700000101
3Kirill SlepetsPhantoms (Phi)LW/RW8246-320791751611.76%213817.3600000000000038.46%1300000.8600000100
4Ruslan IskhakovPhantoms (Phi)C8246-2404141561613.33%114217.7800024000000052.24%13400000.8400000100
5arvid bergstromPhantoms (Phi)D8156-1004630533.33%713416.790000000005000%000000.8900000011
6Maxwell GildonPhantoms (Phi)D8325-220148173817.65%1116320.40101412000024000%000000.6100000010
7Jeff MalottPhantoms (Phi)RW8224-28015131561613.33%313316.69101212000060144.19%4300000.6011000020
8Zachary SenyshynPhantoms (Phi)C/LW/RW6134-20071419375.26%212721.190110100000151045.98%17400000.6300000100
9Ben ThomasPhantoms (Phi)D8044020865000%613116.480000000001000%000000.6100000000
10Robin KovacsPhantoms (Phi)LW/RW8123-3004911369.09%211214.08101390000100049.21%6300000.5311000000
11Kale ClaguePhantoms (Phi)D8213-500691021020.00%719123.98101513000024000%000000.3100000000
12jake wisePhantoms (Phi)C8213-3402254440.00%0648.0700000000000025.00%400000.9300000000
13Ivan ChekhovichPhantoms (Phi)LW/RW8022-44073107100%014117.6500000000000066.67%600000.2800000000
14Kailer YamamotoPhantoms (Phi)C/LW/RW8112-2003714297.14%112015.04000012000071040.00%1500000.3300000000
15Sebastian Aho (DEF)Phantoms (Phi)D8022-50081317460%1118923.65000613000022000%000000.2100000000
16Filip ChlapikPhantoms (Phi)C711202014101051210.00%011616.5901103000080045.32%13900000.3400000000
17Brendan HarmsPhantoms (Phi)LW/RW6000000111200%1244.0500000000050046.67%150000000000000
18Filip WesterlundPhantoms (Phi)D80000275745050%915819.76000112000016000%00000000000000
Statistiques d’équipe totales ou en moyenne138234265-336151261462016015111.44%66237617.2247112913100001872147.58%66000000.5523000442
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)72410.8843.6942320262250010071000
2Jon GilliesPhantoms (Phi)11000.9172.7765003360000.667317000
Statistiques d’équipe totales ou en moyenne83410.8893.574882029261001388000


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
Filip ChlapikPhantoms (Phi)C291997-06-03CZENo207 Lbs6 ft2NoNoN/ANoNo12024-05-29FalseFalsePro & Farm1,000,000$0$0$No---------------------------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
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
Kailer YamamotoPhantoms (Phi)C/LW/RW271998-09-29USANo178 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
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 SenyshynPhantoms (Phi)C/LW/RW291997-03-30CANNo207 Lbs6 ft1NoNoN/ANoNo12024-05-29FalseFalsePro & Farm1,200,000$0$0$No---------------------------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
2228.23188 Lbs6 ft02.14956,818$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mathieu Joseph25122
2Jeff MalottKailer Yamamoto25122
3Kirill SlepetsRuslan IskhakovIvan Chekhovich25122
4jake wise25122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sebastian Aho (DEF)Kale Clague25122
2Maxwell GildonFilip Westerlund25122
3arvid bergstromBen Thomas25122
4Sebastian Aho (DEF)Kale Clague25122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Mathieu Joseph50122
2Jeff MalottKailer Yamamoto50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sebastian Aho (DEF)Kale Clague50122
2Maxwell GildonFilip Westerlund50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Mathieu Joseph50122
250122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kale ClagueSebastian Aho (DEF)50122
2Filip WesterlundMaxwell Gildon50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Mathieu Joseph50122Kale ClagueSebastian Aho (DEF)50122
250122arvid bergstromBen Thomas50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
150122
2Ruslan Iskhakov50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sebastian Aho (DEF)Kale Clague50122
2Ben Thomasarvid bergstrom50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mathieu JosephSebastian Aho (DEF)Kale Clague
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Mathieu JosephSebastian Aho (DEF)Kale Clague
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, , ,
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Kale Clague, Sebastian Aho (DEF), Maxwell GildonKale ClagueFilip Westerlund, Sebastian Aho (DEF)
Tirs de pénalité
, , , Kirill Slepets, Ivan Chekhovich
Gardien
#1 : , #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
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
1Bears10000010431100000104310000000000021.00046100012652217462626361810132150.00%5180.00%012023650.85%13128046.79%6312849.22%1721172125910449
2Condors1010000035-21010000035-20000000000000.0003690012652127462626408424000%20100.00%012023650.85%13128046.79%6312849.22%1721172125910449
3Crunch11000000541110000005410000000000021.00059140012652247462626366231211100.00%5260.00%012023650.85%13128046.79%6312849.22%1721172125910449
4Firebirds1010000014-3000000000001010000014-300.0001230012652347462626274417500.00%20100.00%012023650.85%13128046.79%6312849.22%1721172125910449
5Islanders1010000013-21010000013-20000000000000.00011200126522674626262551017100.00%5180.00%012023650.85%13128046.79%6312849.22%1721172125910449
6PenguinsF1000010023-1000000000001000010023-110.5002460012652217462626357412200.00%20100.00%012023650.85%13128046.79%6312849.22%1721172125910449
7StarsF1010000024-2000000000001010000024-200.00023510126522874626263074134125.00%20100.00%012023650.85%13128046.79%6312849.22%1721172125910449
8Wolf Pack11000000642110000006420000000000021.00061117001265235746262633114182150.00%20100.00%012023650.85%13128046.79%6312849.22%1721172125910449
Total824001102430-6522000101919030200100511-670.43824426610126522017462626262666312617423.53%25484.00%012023650.85%13128046.79%6312849.22%1721172125910449
_Since Last GM Reset824001102430-6522000101919030200100511-670.43824426610126522017462626262666312617423.53%25484.00%012023650.85%13128046.79%6312849.22%1721172125910449
_Vs Conference622001101921-242100010161422010010037-470.5831933520012652161746262619251558913323.08%21480.95%012023650.85%13128046.79%6312849.22%1721172125910449
_Vs Division11200100541111000005410010010000031.50059140012652247462626366231211100.00%5260.00%012023650.85%13128046.79%6312849.22%1721172125910449

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
87L1244266201262666312610
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
82401102430
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
52200101919
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3020100511
Derniers 10 matchs
WLOTWOTL SOWSOL
240110
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
17423.53%25484.00%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
746262612652
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
12023650.85%13128046.79%6312849.22%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1721172125910449


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 - 2025-08-2616Crunch4Phantoms5WSommaire du match
3 - 2025-08-2723Condors5Phantoms3LSommaire du match
6 - 2025-08-3044Islanders3Phantoms1LSommaire du match
8 - 2025-09-0171Phantoms2StarsF4LSommaire du match
10 - 2025-09-0386Wolf Pack4Phantoms6WSommaire du match
11 - 2025-09-0490Phantoms2PenguinsF3LXSommaire du match
14 - 2025-09-07112Bears3Phantoms4WXXSommaire du match
17 - 2025-09-10136Phantoms1Firebirds4LSommaire du match
19 - 2025-09-12152BruinsF-Phantoms-
21 - 2025-09-14163Phantoms-BruinsF-
23 - 2025-09-16174Phantoms-Comets-
25 - 2025-09-18190Monsters-Phantoms-
28 - 2025-09-21214Wolves-Phantoms-
30 - 2025-09-23232Phantoms-Americans-
32 - 2025-09-25247Phantoms-SenatorsF-
33 - 2025-09-26257Checkers-Phantoms-
36 - 2025-09-29271Phantoms-Wolf Pack-
38 - 2025-10-01285Phantoms-Roadrunners-
39 - 2025-10-02294BruinsF-Phantoms-
43 - 2025-10-06320Eagles-Phantoms-
45 - 2025-10-08337Phantoms-Iowa Wild-
47 - 2025-10-10350Moose-Phantoms-
49 - 2025-10-12365Phantoms-Canucks-
51 - 2025-10-14380Moose-Phantoms-
53 - 2025-10-16392Phantoms-Islanders-
55 - 2025-10-18412Phantoms-Gulls-
56 - 2025-10-19418Wolf Pack-Phantoms-
59 - 2025-10-22439Phantoms-Firebirds-
61 - 2025-10-24451Islanders-Phantoms-
64 - 2025-10-27477Canucks-Phantoms-
66 - 2025-10-29486Phantoms-Wolves-
68 - 2025-10-31502Phantoms-PenguinsF-
69 - 2025-11-01517Wolves-Phantoms-
72 - 2025-11-04535Phantoms-Checkers-
74 - 2025-11-06549Checkers-Phantoms-
76 - 2025-11-08566Phantoms-Checkers-
78 - 2025-11-10580Rocket-Phantoms-
80 - 2025-11-12600Phantoms-PenguinsF-
81 - 2025-11-13610Phantoms-BruinsF-
83 - 2025-11-15620Bears-Phantoms-
86 - 2025-11-18640Reign-Phantoms-
87 - 2025-11-19654Phantoms-Rocket-
91 - 2025-11-23673Phantoms-Wolves-
92 - 2025-11-24682Islanders-Phantoms-
95 - 2025-11-27704Griffins-Phantoms-
97 - 2025-11-29720Phantoms-Rocket-
100 - 2025-12-02740PenguinsF-Phantoms-
102 - 2025-12-04752Phantoms-StarsF-
104 - 2025-12-06769Condors-Phantoms-
107 - 2025-12-09791Phantoms-Crunch-
109 - 2025-12-11803Admirals-Phantoms-
112 - 2025-12-14828Rocket-Phantoms-
114 - 2025-12-16845Phantoms-Wolf Pack-
116 - 2025-12-18860Americans-Phantoms-
118 - 2025-12-20872Phantoms-Barracuda-
120 - 2025-12-22890Phantoms-SenatorsF-
121 - 2025-12-23898Wranglers-Phantoms-
125 - 2025-12-27925Phantoms-Marlies-
126 - 2025-12-28931Firebirds-Phantoms-
130 - 2026-01-01958Monsters-Phantoms-
132 - 2026-01-03978Phantoms-Silver Knights-
134 - 2026-01-05991Gulls-Phantoms-
137 - 2026-01-081016Marlies-Phantoms-
139 - 2026-01-101031Phantoms-Comets-
142 - 2026-01-131049PenguinsF-Phantoms-
143 - 2026-01-141054Phantoms-Americans-
146 - 2026-01-171075Phantoms-Marlies-
147 - 2026-01-181087Comets-Phantoms-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2026-01-201103Phantoms-Moose-
152 - 2026-01-231119Firebirds-Phantoms-
154 - 2026-01-251134Phantoms-Moose-
156 - 2026-01-271149Marlies-Phantoms-
158 - 2026-01-291162Phantoms-Icehogs-
160 - 2026-01-311182Comets-Phantoms-
164 - 2026-02-041208SenatorsF-Phantoms-
166 - 2026-02-061220Phantoms-Thunderbirds-
168 - 2026-02-081228Phantoms-Islanders-
170 - 2026-02-101239Phantoms-Crunch-
172 - 2026-02-121254SenatorsF-Phantoms-
175 - 2026-02-151280Phantoms-Bears-
176 - 2026-02-161291Americans-Phantoms-
180 - 2026-02-201313Crunch-Phantoms-
181 - 2026-02-211323Phantoms-Bears-
183 - 2026-02-231343Phantoms-Admirals-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4530
Assistance10,0005,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
37 3000 - 100.00% 178,800$894,000$3000125

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
210,574$ 2,105,000$ 2,105,000$ 100,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 200,786$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
6,615,600$ 166 11,984$ 1,989,344$




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