Connexion

Phantoms
GP: 49 | W: 12 | L: 32 | OTL: 5 | P: 29
GF: 122 | GA: 197 | PP%: 15.94% | PK%: 73.33%
DG: Alexandre Fortier | Morale : 23 | Moyenne d’équipe : 61
Prochains matchs #807 vs StarsF
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Centre de jeu
Moose
21-22-6, 48pts
3
FINAL
1 Phantoms
12-32-5, 29pts
Team Stats
W2SéquenceW1
11-11-3Fiche domicile6-14-5
10-11-3Fiche domicile6-18-0
4-4-2Derniers 10 matchs3-6-1
3.20Buts par match 2.49
3.41Buts contre par match 4.02
19.02%Pourcentage en avantage numérique15.94%
76.35%Pourcentage en désavantage numérique73.33%
Phantoms
12-32-5, 29pts
4
FINAL
2 Wolves
20-25-5, 45pts
Team Stats
W1SéquenceL1
6-14-5Fiche domicile11-13-1
6-18-0Fiche domicile9-12-4
3-6-1Derniers 10 matchs4-4-2
2.49Buts par match 2.46
4.02Buts contre par match 3.10
15.94%Pourcentage en avantage numérique20.81%
73.33%Pourcentage en désavantage numérique80.61%
Phantoms
12-32-5, 29pts
2023-12-12
StarsF
31-12-5, 67pts
Statistiques d’équipe
W1SéquenceSOL1
6-14-5Fiche domicile15-6-4
6-18-0Fiche visiteur16-6-1
3-6-110 derniers matchs5-4-1
2.49Buts par match 3.75
4.02Buts contre par match 3.75
15.94%Pourcentage en avantage numérique26.45%
73.33%Pourcentage en désavantage numérique76.86%
Wolves
20-25-5, 45pts
2023-12-13
Phantoms
12-32-5, 29pts
Statistiques d’équipe
L1SéquenceW1
11-13-1Fiche domicile6-14-5
9-12-4Fiche visiteur6-18-0
4-4-210 derniers matchs3-6-1
2.46Buts par match 2.49
3.10Buts contre par match 2.49
20.81%Pourcentage en avantage numérique15.94%
80.61%Pourcentage en désavantage numérique73.33%
Marlies
28-19-2, 58pts
2023-12-16
Phantoms
12-32-5, 29pts
Statistiques d’équipe
L1SéquenceW1
14-9-2Fiche domicile6-14-5
14-10-0Fiche visiteur6-18-0
5-4-110 derniers matchs3-6-1
3.59Buts par match 2.49
3.18Buts contre par match 2.49
29.66%Pourcentage en avantage numérique15.94%
78.95%Pourcentage en désavantage numérique73.33%
Meneurs d'équipe
Buts
Zachary Senyshyn
17
Passes
Jakub Zboril
24
Points
Jesper Boqvist
33
Plus/Moins
Peter Regin
2
Victoires
Dan Blackburn
7
Pourcentage d’arrêts
Mattias Modig
0.92

Statistiques d’équipe
Buts pour
122
2.49 GFG
Tirs pour
1280
26.12 Avg
Pourcentage en avantage numérique
15.9%
22 GF
Début de zone offensive
38.4%
Buts contre
197
4.02 GAA
Tirs contre
1545
31.53 Avg
Pourcentage en désavantage numérique
73.3%%
40 GA
Début de la zone défensive
41.1%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,447
Billets de saison300


Informations de la formation

Équipe Pro31
Équipe Mineure18
Limite contact 49 / 55
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
1Filip ChlapikX98.007145737071707169667069696651476028630261750,000$
2Zachary SenyshynX96.006955897271747466636668716651476044630261750,000$
3Marek TvrdonX99.0066468669756865696165676665454553406203021,000,000$
4Erik Karlsson (foward)X99.0060459373667068666166616460484559356002921,000,000$
5Spencer WatsonX100.005645927265666864615962686049455819590271800,000$
6Peter ReginX100.0059418865705960646360596658625525175903721,000,000$
7Graham KnottX100.006445816871687062605962635948455819590261800,000$
8Nathan NoelX100.0058455755555457535553525555494560195002611,000,000$
9Jakub ZborilX100.007045857772828572457462715656476626660261900,000$
10Robin SaloX100.006345917369787671457269716048456835650252900,000$
11Kale ClagueX100.006345857269778269457269696053466035640252900,000$
12Filip Westerlund (R)X100.006650867268707060456262675745456028610243750,000$
13Brycen MartinX100.006551807272716863456262655452466017610273800,000$
14Ben ThomasX100.006648897069697158456363645750466019600271750,000$
Rayé
1Jesper BoqvistX97.006445917369789071667472696958466832660252900,000$
2Kiefer SherwoodX100.0065459772706870697668676966594759206402831,200,000$
3Ivan Chekhovich (R)X94.006445907267707068667070646445456033630243750,000$
4Pascal LabergeX100.006545857268727271726667676148476034620252750,000$
5Justin KeaX100.007456676876697264716464645956524834620293900,000$
6Kirill Slepets (R)X100.006345907265707066666563686045456036610243750,000$
7Scott TimminsX100.005442876870727361676059666461564019600341800,000$
8Tim BozonX100.006045856972696961645860686053495326590291800,000$
9Jakub IzackyX100.006042817065616662625962686256545219590303500,000$
10Joel MustonenX98.945443907166667762636060656061495128590312500,000$
11Rob O'GaraX79.4865439170747675694572637056595252296503021,300,000$
12Maxwell Gildon (R)X92.716544857268707066456664725645456028620243750,000$
13Johan MotinX100.006344846772667062455959675960454118600341800,000$
14Ryan RehillX100.008573546575655657455754665452525620590283500,000$
MOYENNE D’ÉQUIPE98.29644784706970716558646367605248562761
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
1Mattias Modig100.00736565727266697066687478752840600361800,000$
2Dan Blackburn96.007067677571646464646569938810176004011,000,000$
Rayé
1Marek Langhamer97.00788478797675827474767949565419620293900,000$
MOYENNE D’ÉQUIPE97.6774727075736872696870747373312561
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mike Sullivan89678768999958USA545100,000$


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
1Jesper BoqvistPhantoms (Phi)C45151833-191603796121408612.40%688119.58279161090000370247.82%94100000.7514000321
2Jakub ZborilPhantoms (Phi)D4622426-526038443212296.25%4484518.381121244000050100%000000.6200000010
3Zachary SenyshynPhantoms (Phi)RW4617926-2338205153116278414.66%977816.923361484000071145.59%13600000.6702103022
4Ivan ChekhovichPhantoms (Phi)LW4781725-2180515110725637.48%387618.64134201140000470145.99%18700000.5716000103
5Pascal LabergePhantoms (Phi)C4913821-2314041103122406810.66%991918.760111210200011051348.64%91700000.4600000231
6Kale ClaguePhantoms (Phi)D4941721-2926046556419486.25%64104221.2824626107000088100%000000.4000000111
7Robin SaloPhantoms (Phi)D4931720-2126045496727404.48%72109422.33224381130000109000%000000.3700000000
8Rob O'GaraPhantoms (Phi)D3511920-1024040284711272.13%3577422.140442885000075000%000000.5200000003
9Kiefer SherwoodPhantoms (Phi)LW3791019-9135264676236311.84%1070419.0311211810001723151.91%18300000.5423010200
10Filip ChlapikPhantoms (Phi)C3671118-9200713058194012.07%659116.4344814660001311044.16%39400000.6103000201
11Kirill SlepetsPhantoms (Phi)RW489817-122020349928709.09%880816.84123188900011030047.09%18900000.4212000100
12Maxwell GildonPhantoms (Phi)D3851116-1220033385318389.43%4575719.923362196000074000%000000.4200000000
13Brendan PerliniFlyersLW2461016-280161951173711.76%639516.501239500002531056.25%3200100.8113000101
14Erik Karlsson (foward)Phantoms (Phi)LW498816-1880215073357010.96%674315.181122180001111038.24%3400000.4300000110
15Justin KeaPhantoms (Phi)C394610-1315563375612397.14%658014.890002450000110052.88%53900000.3400100020
16Brycen MartinPhantoms (Phi)D19178-1718022111051010.00%1834618.2501103000020100%000000.4600000001
17Tim BozonPhantoms (Phi)RW35437-114025104115189.76%42988.5400015000000040.00%2000000.4700000000
18Filip WesterlundPhantoms (Phi)D40077-12301060153811150%4877519.38011737000146000%000000.1800010000
19Joel MustonenPhantoms (Phi)LW29437-12011153132312.90%231110.7400000000000038.10%2100000.4500000110
20Johan MotinPhantoms (Phi)D81671608242325.00%212115.180000000000000%000001.1500000000
21Marek TvrdonPhantoms (Phi)RW27336-32010102751811.11%21886.99112413000040038.24%6800000.6400000001
22Spencer WatsonPhantoms (Phi)C220551409251611220%428212.82000050000510044.70%34900000.3511000000
23Nathan NoelPhantoms (Phi)RW40033-151206166650%355713.9300000000000050.00%2600000.1100000000
24Ben ThomasPhantoms (Phi)D10112-42016353520.00%1118118.1500025000020000%000000.2200000000
25Peter ReginPhantoms (Phi)LW161012002380312.50%0563.520000200000000%200000.3600000000
26Jakub IzackyPhantoms (Phi)LW4000000001000%000.090000000000000%00000000000000
27Scott TimminsPhantoms (Phi)C5000-120442010%05310.6300000000000057.58%330000000000000
28Graham KnottPhantoms (Phi)LW13000000000000%010.100000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne905126231357-2763564082783713314149259.47%4231496716.5423416425712830008102511847.85%407100100.48724223151315
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
1Dan BlackburnPhantoms (Phi)2871810.8723.78144320917110110.71472611110
2Marek LanghamerPhantoms (Phi)2451340.8724.24130120927200100.57114234200
3Mattias ModigPhantoms (Phi)60100.9202.4022500911300000034000
Statistiques d’équipe totales ou en moyenne58123250.8763.882970401921544021214949310


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 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 Type Salaire actuel Plafond salarial Non Activé Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 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)D271996-05-28No187 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Brycen MartinPhantoms (Phi)D271996-05-09No210 Lbs6 ft2NoNoN/ANoNo3Pro & Farm800,000$0$0$No800,000$800,000$-------NoNo-------Lien
Dan BlackburnPhantoms (Phi)G401983-05-20No180 Lbs6 ft0NoNoN/ANoNo1Pro & Farm1,000,000$0$0$No------------------Lien
Erik Karlsson (foward)Phantoms (Phi)LW291994-07-28No160 Lbs5 ft11NoNoN/ANoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------Lien
Filip ChlapikPhantoms (Phi)C261997-06-03No207 Lbs6 ft2NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Filip WesterlundPhantoms (Phi)D241999-04-17Yes180 Lbs5 ft11NoNoN/ANoNo3Pro & Farm750,000$0$0$No750,000$750,000$-------NoNo-------Lien
Graham KnottPhantoms (Phi)LW261997-01-13No192 Lbs6 ft4NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Ivan Chekhovich (sur la masse salariale)Phantoms (Phi)LW241999-01-04Yes185 Lbs5 ft10NoNoN/ANoNo3Pro & Farm750,000$0$0$Yes750,000$750,000$-------NoNo-------
Jakub IzackyPhantoms (Phi)LW301993-11-25No187 Lbs6 ft0NoNoN/ANoNo3Pro & Farm500,000$0$0$No500,000$500,000$-------NoNo-------Lien
Jakub ZborilPhantoms (Phi)D261997-02-21No200 Lbs6 ft0NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Jesper BoqvistPhantoms (Phi)C251998-10-30No180 Lbs6 ft0NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Joel MustonenPhantoms (Phi)LW311992-09-17No174 Lbs5 ft10NoNoN/ANoNo2Pro & Farm500,000$0$0$No500,000$--------No--------Lien
Johan MotinPhantoms (Phi)D341989-10-10No200 Lbs6 ft1NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Justin KeaPhantoms (Phi)C291994-02-07No215 Lbs6 ft5NoNoN/ANoNo3Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------Lien
Kale ClaguePhantoms (Phi)D251998-06-05No192 Lbs6 ft0NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Kiefer SherwoodPhantoms (Phi)LW281995-03-21No194 Lbs6 ft0NoNoN/ANoNo3Pro & Farm1,200,000$0$0$No1,200,000$1,200,000$-------NoNo-------Lien
Kirill SlepetsPhantoms (Phi)RW241999-04-06Yes165 Lbs5 ft10NoNoN/ANoNo3Pro & Farm750,000$0$0$No750,000$750,000$-------NoNo-------Lien
Marek LanghamerPhantoms (Phi)G291994-07-22No190 Lbs6 ft2NoNoN/ANoNo3Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------Lien
Marek TvrdonPhantoms (Phi)RW301993-01-31No220 Lbs6 ft2NoNoN/ANoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------Lien
Mattias ModigPhantoms (Phi)G361987-04-01No165 Lbs6 ft0NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Maxwell Gildon (sur la masse salariale)Phantoms (Phi)D241999-05-17Yes194 Lbs6 ft3NoNoN/ANoNo3Pro & Farm750,000$0$0$Yes750,000$750,000$-------NoNo-------Lien
Nathan NoelPhantoms (Phi)RW261997-06-21No156 Lbs6 ft7NoNoN/ANoNo1Pro & Farm1,000,000$0$0$No------------------Lien
Pascal LabergePhantoms (Phi)C251998-04-09No172 Lbs6 ft1NoNoN/ANoNo2Pro & Farm750,000$0$0$No750,000$--------No--------Lien
Peter ReginPhantoms (Phi)LW371986-04-16No194 Lbs6 ft1NoNoN/ANoNo2Pro & Farm1,000,000$0$0$No1,000,000$--------No--------Lien
Rob O'Gara (sur la masse salariale)Phantoms (Phi)D301993-08-06No207 Lbs6 ft4NoNoN/ANoNo2Pro & Farm1,300,000$0$0$Yes1,300,000$--------No--------Lien
Robin SaloPhantoms (Phi)D251998-10-13No181 Lbs6 ft0NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Ryan RehillPhantoms (Phi)D281995-11-07No215 Lbs6 ft2NoNoN/ANoNo3Pro & Farm500,000$0$0$No500,000$500,000$-------NoNo-------Lien
Scott TimminsPhantoms (Phi)C341989-09-11No190 Lbs5 ft11NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Spencer WatsonPhantoms (Phi)C271996-04-25No170 Lbs5 ft10NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Tim BozonPhantoms (Phi)RW291994-03-24No199 Lbs6 ft1NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Zachary SenyshynPhantoms (Phi)RW261997-03-30No207 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3128.42189 Lbs6 ft11.94838,710$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Zachary Senyshyn25014
2Erik Karlsson (foward)Filip ChlapikMarek Tvrdon25122
3Peter ReginSpencer WatsonNathan Noel25122
4Graham KnottZachary Senyshyn25122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jakub ZborilRobin Salo35122
2Kale ClagueFilip Westerlund35122
3Brycen MartinBen Thomas30122
4Jakub ZborilRobin Salo0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Zachary Senyshyn50122
2Erik Karlsson (foward)Filip ChlapikMarek Tvrdon50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jakub ZborilRobin Salo50122
2Kale ClagueFilip Westerlund50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
150122
2Filip ChlapikErik Karlsson (foward)50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jakub ZborilRobin Salo50122
2Kale ClagueFilip Westerlund50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
150122Jakub ZborilRobin Salo50122
2Filip Chlapik50122Kale ClagueFilip Westerlund50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
150122
2Filip ChlapikErik Karlsson (foward)50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jakub ZborilRobin Salo50122
2Kale ClagueFilip Westerlund50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Zachary SenyshynJakub ZborilRobin Salo
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Zachary SenyshynJakub ZborilRobin Salo
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Marek Tvrdon, Erik Karlsson (foward), Peter ReginMarek Tvrdon, Erik Karlsson (foward)Marek Tvrdon
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Filip Westerlund, Brycen Martin, Ben ThomasFilip WesterlundFilip Westerlund, Brycen Martin
Tirs de pénalité
, Zachary Senyshyn, , Filip Chlapik, Marek Tvrdon
Gardien
#1 : Mattias Modig, #2 : Dan Blackburn


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
1Admirals1010000026-4000000000001010000026-400.0002460043393773040043343533353620300.00%30100.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
2Americans513000011419-52010000146-2312000001013-330.3001426400043393771284004334353318754328217211.76%16381.25%0725155246.71%814166049.04%39182747.28%11227561195369655321
3Barracuda1010000045-1000000000001010000045-100.00048120043393773340043343533311110132150.00%40100.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
4Bears422000001013-3220000007522020000038-540.50010182800433937793400433435331093025571317.69%10370.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
5BruinsF311000101414020100010911-21100000053240.6671424380043393777240043343533892718558337.50%9366.67%0725155246.71%814166049.04%39182747.28%11227561195369655321
6Canucks20200000110-91010000006-61010000014-300.000123004339377494004334353373202045400.00%10370.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
7Checkers21100000660211000006600000000000020.500611171043393775940043343533792317425360.00%60100.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
8Comets1010000014-31010000014-30000000000000.00011200433937727400433435333716821400.00%4175.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
9Crunch21000001101001000000167-11100000043130.750101929004339377654004334353376241838200.00%40100.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
10Eagles10000010321000000000001000001032121.00034700433937718400433435334571522000%5180.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
11Firebirds30300000410-61010000023-12020000027-500.00047110043393777140043343533812412497114.29%5260.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
12Gulls1010000036-3000000000001010000036-300.00036900433937726400433435333094154125.00%2150.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
13Icehogs1010000012-1000000000001010000012-100.0001230043393772940043343533172215600.00%10100.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
14Islanders30300000410-62020000025-31010000025-300.00047110043393776840043343533992912428112.50%6266.67%0725155246.71%814166049.04%39182747.28%11227561195369655321
15Marlies20200000212-101010000016-51010000016-500.000235004339377574004334353362201034300.00%3166.67%0725155246.71%814166049.04%39182747.28%11227561195369655321
16Moose2020000016-51010000013-21010000003-300.00012300433937757400433435335714630600.00%3166.67%0725155246.71%814166049.04%39182747.28%11227561195369655321
17PenguinsF401011011317-42000010179-22010100068-240.500132235004339377100400433435331512642536350.00%19573.68%0725155246.71%814166049.04%39182747.28%11227561195369655321
18Roadrunners1010000025-31010000025-30000000000000.0002350043393773540043343533256217300.00%110.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
19Rocket2020000028-61010000015-41010000013-200.000246004339377344004334353358182638700.00%13561.54%0725155246.71%814166049.04%39182747.28%11227561195369655321
20SenatorsF1010000036-3000000000001010000036-300.000369004339377294004334353325101518000%5180.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
21Silver Knights1000000145-11000000145-10000000000010.500481200433937736400433435333068136233.33%4325.00%0725155246.71%814166049.04%39182747.28%11227561195369655321
22Wolf Pack11000000431110000004310000000000021.00047110043393774640043343533174016800.00%000%0725155246.71%814166049.04%39182747.28%11227561195369655321
23Wolves32100000871110000003212110000055040.6678152300433937766400433435337123273513215.38%11372.73%0725155246.71%814166049.04%39182747.28%11227561195369655321
24Wranglers20200000611-520200000611-50000000000000.000612180043393775240043343533611117413266.67%6183.33%0725155246.71%814166049.04%39182747.28%11227561195369655321
Total4993201124122197-75255140011466102-3624418010105695-39290.29612222134310433937712804004334353315454173528111382215.94%1504073.33%0725155246.71%814166049.04%39182747.28%11227561195369655321
_Since Last GM Reset4993201124122197-75255140011466102-3624418010105695-39290.29612222134310433937712804004334353315454173528111382215.94%1504073.33%0725155246.71%814166049.04%39182747.28%11227561195369655321
_Vs Conference389230111396145-4920510001135475-2118413010004270-28260.342961722681043393779724004334353311983422686101071614.95%1143073.68%0725155246.71%814166049.04%39182747.28%11227561195369655321
_Vs Division1718011015175-24914001012741-14804010002434-1060.17651931441043393774444004334353357617613630742819.05%561376.79%0725155246.71%814166049.04%39182747.28%11227561195369655321

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4929W11222213431280154541735281110
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
499321124122197
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
25514011466102
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2441810105695
Derniers 10 matchs
WLOTWOTL SOWSOL
360001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1382215.94%1504073.33%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
400433435334339377
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
725155246.71%814166049.04%39182747.28%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
11227561195369655321


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 - 2023-08-2614Phantoms2Islanders5ALSommaire du match
4 - 2023-08-2827Rocket5Phantoms1BLSommaire du match
5 - 2023-08-2931Phantoms4Americans6ALSommaire du match
7 - 2023-08-3153Phantoms1Americans4ALSommaire du match
9 - 2023-09-0264Bears3Phantoms4BWSommaire du match
12 - 2023-09-0589Americans2Phantoms1BLSommaire du match
14 - 2023-09-07106PenguinsF4Phantoms3BLXXSommaire du match
16 - 2023-09-09118Phantoms3SenatorsF6ALSommaire du match
18 - 2023-09-11133Phantoms1Bears4ALSommaire du match
21 - 2023-09-14155Wolf Pack3Phantoms4BWSommaire du match
23 - 2023-09-16173Comets4Phantoms1BLSommaire du match
25 - 2023-09-18188Phantoms1Rocket3ALSommaire du match
27 - 2023-09-20203Islanders2Phantoms1BLSommaire du match
30 - 2023-09-23221Phantoms1Firebirds4ALSommaire du match
32 - 2023-09-25237Firebirds3Phantoms2BLSommaire du match
34 - 2023-09-27251Phantoms4PenguinsF3AWXSommaire du match
37 - 2023-09-30269Roadrunners5Phantoms2BLSommaire du match
39 - 2023-10-02285Phantoms4Barracuda5ALSommaire du match
41 - 2023-10-04298Phantoms5Americans3AWSommaire du match
42 - 2023-10-05311Silver Knights5Phantoms4BLXXSommaire du match
45 - 2023-10-08333Phantoms3Eagles2AWXXSommaire du match
46 - 2023-10-09342PenguinsF5Phantoms4BLXSommaire du match
49 - 2023-10-12363Phantoms1Wolves3ALSommaire du match
51 - 2023-10-14376Checkers1Phantoms3BWSommaire du match
54 - 2023-10-17397Phantoms2Bears4ALSommaire du match
55 - 2023-10-18407Checkers5Phantoms3BLSommaire du match
58 - 2023-10-21431BruinsF6Phantoms3BLSommaire du match
60 - 2023-10-23449Bears2Phantoms3BWSommaire du match
63 - 2023-10-26467Phantoms1Icehogs2ALSommaire du match
65 - 2023-10-28481BruinsF5Phantoms6BWXXSommaire du match
68 - 2023-10-31498Phantoms0Moose3ALSommaire du match
71 - 2023-11-03518Islanders3Phantoms1BLSommaire du match
75 - 2023-11-07545Wranglers7Phantoms3BLSommaire du match
77 - 2023-11-09561Phantoms1Marlies6ALSommaire du match
79 - 2023-11-11571Phantoms1Firebirds3ALSommaire du match
81 - 2023-11-13586Americans4Phantoms3BLXXSommaire du match
83 - 2023-11-15603Phantoms2PenguinsF5ALSommaire du match
84 - 2023-11-16617Wolves2Phantoms3BWSommaire du match
87 - 2023-11-19639Phantoms2Admirals6ALSommaire du match
89 - 2023-11-21648Phantoms3Gulls6ALSommaire du match
90 - 2023-11-22658Marlies6Phantoms1BLSommaire du match
93 - 2023-11-25681Canucks6Phantoms0BLSommaire du match
95 - 2023-11-27702Wranglers4Phantoms3BLSommaire du match
97 - 2023-11-29714Phantoms4Crunch3AWSommaire du match
99 - 2023-12-01725Phantoms1Canucks4ALSommaire du match
101 - 2023-12-03744Crunch7Phantoms6BLXXSommaire du match
103 - 2023-12-05758Phantoms5BruinsF3AWSommaire du match
105 - 2023-12-07775Moose3Phantoms1BLSommaire du match
106 - 2023-12-08784Phantoms4Wolves2AWSommaire du match
110 - 2023-12-12807Phantoms-StarsF-
111 - 2023-12-13816Wolves-Phantoms-
114 - 2023-12-16841Marlies-Phantoms-
118 - 2023-12-20870Firebirds-Phantoms-
120 - 2023-12-22883Phantoms-BruinsF-
122 - 2023-12-24900Condors-Phantoms-
123 - 2023-12-25910Phantoms-Iowa Wild-
126 - 2023-12-28930Rocket-Phantoms-
128 - 2023-12-30946Phantoms-Condors-
130 - 2024-01-01956Phantoms-Crunch-
132 - 2024-01-03967Comets-Phantoms-
135 - 2024-01-06989Phantoms-Islanders-
136 - 2024-01-071001Rocket-Phantoms-
139 - 2024-01-101023Phantoms-Rocket-
140 - 2024-01-111030Phantoms-SenatorsF-
142 - 2024-01-131040Wolf Pack-Phantoms-
144 - 2024-01-151062Griffins-Phantoms-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
146 - 2024-01-171074Phantoms-Comets-
149 - 2024-01-201089Phantoms-Thunderbirds-
150 - 2024-01-211102Monsters-Phantoms-
153 - 2024-01-241117Phantoms-Moose-
155 - 2024-01-261130Reign-Phantoms-
159 - 2024-01-301159Moose-Phantoms-
160 - 2024-01-311171Phantoms-Wolf Pack-
163 - 2024-02-031192Crunch-Phantoms-
165 - 2024-02-051208Phantoms-Checkers-
167 - 2024-02-071222Phantoms-Comets-
168 - 2024-02-081229Phantoms-Marlies-
170 - 2024-02-101236Condors-Phantoms-
173 - 2024-02-131257SenatorsF-Phantoms-
175 - 2024-02-151265Phantoms-Wolf Pack-
178 - 2024-02-181287Phantoms-Checkers-
181 - 2024-02-211312SenatorsF-Phantoms-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance37,57823,600
Assistance PCT75.16%94.40%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
16 2447 - 81.57% 96,815$2,420,383$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,483,552$ 2,320,000$ 2,320,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,425,307$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,549,045$ 76 13,297$ 1,010,572$




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