Connexion

Phantoms
GP: 17 | W: 11 | L: 6 | OTL: 0 | P: 22
GF: 48 | GA: 41 | PP%: 14.95% | PK%: 87.85%
DG: Mathieu Gendron | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #201 vs Bruins
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Centre de jeu
Phantoms
11-6-0, 22pts
1
FINAL
0 Condors
8-7-3, 19pts
Team Stats
W3SéquenceOTL1
5-4-0Fiche domicile4-4-0
6-2-0Fiche domicile4-3-3
7-3-0Derniers 10 matchs3-5-2
2.82Buts par match 2.50
2.41Buts contre par match 2.78
14.95%Pourcentage en avantage numérique12.50%
87.85%Pourcentage en désavantage numérique90.91%
Stars
8-4-6, 22pts
3
FINAL
4 Phantoms
11-6-0, 22pts
Team Stats
SOL1SéquenceW3
6-1-2Fiche domicile5-4-0
2-3-4Fiche domicile6-2-0
3-2-5Derniers 10 matchs7-3-0
2.56Buts par match 2.82
2.33Buts contre par match 2.41
13.33%Pourcentage en avantage numérique14.95%
85.44%Pourcentage en désavantage numérique87.85%
Bruins
14-3-1, 29pts
Jour 35
Phantoms
11-6-0, 22pts
Statistiques d’équipe
W2SéquenceW3
8-0-1Fiche domicile5-4-0
6-3-0Fiche visiteur6-2-0
8-2-010 derniers matchs7-3-0
3.33Buts par match 2.82
2.00Buts contre par match 2.82
13.79%Pourcentage en avantage numérique14.95%
89.13%Pourcentage en désavantage numérique87.85%
Phantoms
11-6-0, 22pts
Jour 36
Monsters
8-7-2, 18pts
Statistiques d’équipe
W3SéquenceL3
5-4-0Fiche domicile3-4-2
6-2-0Fiche visiteur5-3-0
7-3-010 derniers matchs5-4-1
2.82Buts par match 2.88
2.41Buts contre par match 2.88
14.95%Pourcentage en avantage numérique15.00%
87.85%Pourcentage en désavantage numérique87.64%
Monarchs
7-9-2, 16pts
Jour 38
Phantoms
11-6-0, 22pts
Statistiques d’équipe
L1SéquenceW3
3-4-1Fiche domicile5-4-0
4-5-1Fiche visiteur6-2-0
4-6-010 derniers matchs7-3-0
2.61Buts par match 2.82
3.11Buts contre par match 2.82
15.52%Pourcentage en avantage numérique14.95%
80.33%Pourcentage en désavantage numérique87.85%
Meneurs d'équipe
Buts
Alex Limoges
7
Passes
Jordan Harris
10
Points
Nicholas Robertson
15
Plus/Moins
David Farrance
6
Victoires
Joseph Woll
9
Pourcentage d’arrêts
Leevi Merilainen
0.925

Statistiques d’équipe
Buts pour
48
2.82 GFG
Tirs pour
279
16.41 Avg
Pourcentage en avantage numérique
15.0%
16 GF
Début de zone offensive
38.2%
Buts contre
41
2.41 GAA
Tirs contre
314
18.47 Avg
Pourcentage en désavantage numérique
87.9%%
13 GA
Début de la zone défensive
40.5%
Informations de l'équipe

Directeur généralMathieu Gendron
EntraîneurDavid Hakstol
DivisionDivision 2
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure19
Limite contact 46 / 60
Espoirs19


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
1John Leonard (R)0XX100.007567927267778261505959645644446450002511,137,500$
2Grigori Denisenko (R)0XX100.007643927864556958256355612546466250002311,775,000$
3Quinton Byfield0XX98.007544837981677770487857657556576750002113,544,167$
4Nicholas Robertson0X100.00774299745858516856656470254646685000211821,667$
5Tyce Thompson (R)0X100.00716683666657585650565161484444575000242762,500$
6Alex Limoges (R)0XX100.00807494587476796480626267594444665000251867,000$
7Lane Pederson0X100.00909273717262676372606064255454655000264750,000$
8Givani Smith0XX100.00849947718147695925585662255858605000252750,000$
9Jan Mysak (R)0XX100.00736493726464685063455160484444575000213902,500$
10Brandon Gignac0XX100.00716390716352506480606265595555645000251921,666$
11Michael Sgarbossa0X100.00726882796867676680656464614545675000312750,000$
12Andreas Johnsson0XX98.006542868268657768426855627965656450002813,400,000$
13Zachary Jones0X100.00614191706468836025454870754747595000223925,000$
14Jordan Harris (R)0X98.007142876767765863255448812553536250002331,137,500$
15Thomas Harley0X100.007671887871788457254949644747476050002211,288,333$
16David Farrance0X100.007367887967504954255241613944445550002411,350,000$
17Simon Lundmark (R)0X100.00807590707571774825404063384444545000222925,000$
18Josh Brook (R)0X100.00737178657142405225494161394444525000242910,833$
Rayé
1Tye Kartye (R)0X100.0073727666728084645060656462444467500N0223925,000$
2Josiah Slavin (R)0X100.00706190706175825063474859464444565000241925,000$
3Taro Hirose0X100.00705994695984906450655864555050655000271850,000$
4Stelio Mattheos (R)0X100.00717171647157595063494759454444545000241925,000$
5Mark Friedman0X99.00887581736965586125484874255253615000271775,000$
6Layton Ahac (R)0X100.00767286617252554525344060384444515000221925,000$
MOYENNE D’ÉQUIPE99.7175648571696468594655536447484861500
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
1Jiri Patera (R)0100.0054475980585551585554304444545000242800,000$
2Joseph Woll (R)099.0063486077686361686564304545625000251766,667$
Rayé
1Leevi Merilainen (R)0100.004757716845934551908145444463500N0213820,000$
MOYENNE D’ÉQUIPE99.675551637557705259706635444460500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
David Hakstol80868885807569CAN5521,500,000$


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
1Nicholas RobertsonPhantoms (PHI)LW1769150206182762322.22%330517.955389730000350044.68%4700000.9801000013
2Jordan HarrisPhantoms (PHI)D1731013-2280262519101515.79%1941024.162571584000074000%000000.6300000100
3Michael SgarbossaPhantoms (PHI)C174913-12011322131119.05%125414.951675460000502065.82%19600001.0200000031
4Quinton ByfieldPhantoms (PHI)C/LW154812116020281871722.22%230820.542134650000450144.27%25300000.7803000210
5Alex LimogesPhantoms (PHI)C/LW1773102001013153846.67%017810.501123310000100160.58%13700001.1200000120
6Givani SmithPhantoms (PHI)LW/RW175510327527111551433.33%126415.531125520000352025.00%1600000.7611010201
7Lane PedersonPhantoms (PHI)C172573100224132366.25%026115.37000160000550254.87%27700000.5400000211
8Andreas JohnssonPhantoms (PHI)LW/RW17156-44082112388.33%226215.420222570000451042.11%1900000.4622000001
9Zachary JonesPhantoms (PHI)D1714531806916676.25%1336021.230221175000075000%000000.2800000010
10John LeonardPhantoms (PHI)LW/RW17224-6180141119111310.53%127916.461235870001230050.00%2000000.2900000000
11Grigori DenisenkoPhantoms (PHI)LW/RW17044460518128120%125615.10000029000050033.33%900000.3100000000
12Taro HirosePhantoms (PHI)LW1022410021971628.57%114714.7900007000011025.00%800000.5400000001
13Jan MysakPhantoms (PHI)C/LW72243000450240.00%08211.74000010000131025.00%1200000.9711000100
14David FarrancePhantoms (PHI)D173146260211081437.50%1131018.29101447000055100%000000.2600000020
15Tye KartyePhantoms (PHI)LW10033000247220%0474.72011000000000100.00%200001.2700000000
16Brandon GignacPhantoms (PHI)C/LW17123120413173115.88%21428.39101443000000157.50%12000000.4211000000
17Thomas HarleyPhantoms (PHI)D17022-4160361215190%539123.020221282000068000%000000.1000000000
18Nathan BastianFlyersC/RW2112-20012451520.00%04623.04112214000020141.51%5300000.8700000100
19Simon LundmarkPhantoms (PHI)D17112136026550220.00%1027716.32000220000023000%000000.1400000001
20Josh BrookPhantoms (PHI)D14011-31401822210%923216.59011023000029000%000000.0900000000
21Tyce ThompsonPhantoms (PHI)RW7000-2175662200%27210.31000040001220046.67%300000000000000
22Mark FriedmanPhantoms (PHI)D3000040660020%35618.9300009000013000%00000000000000
Statistiques d’équipe totales ou en moyenne30645791244246102883122797817816.13%86494816.171628448486300026898652.88%119900000.505901010119
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
1Joseph WollPhantoms (PHI)169600.8582.6085502372610000.80010160101
2Leevi MerilainenPhantoms (PHI)52000.9251.35133013400000019010
3Jiri PateraPhantoms (PHI)10000.9231.2847001130000008000
Statistiques d’équipe totales ou en moyenne2211600.8692.3810360341314000101717111


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 Ballotage forcé Waiver Possible Contrat Type Salaire actuel Salaire restantSalaire moyenSalaire moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Lien
Alex LimogesPhantoms (PHI)C/LW251997-09-16Yes201 Lbs6 ft1NoNoNoNo1Pro & Farm867,000$682,413$867,000$682,413$0$0$NoLien
Andreas JohnssonPhantoms (PHI)LW/RW281994-11-20No194 Lbs5 ft10NoNoNoNo1Pro & Farm3,400,000$2,676,129$3,400,000$2,676,129$0$0$NoLien
Brandon GignacPhantoms (PHI)C/LW251997-11-07No170 Lbs5 ft11NoNoNoNo1Pro & Farm921,666$725,440$921,666$725,440$0$0$NoLien
David FarrancePhantoms (PHI)D241999-06-23No189 Lbs5 ft11NoNoNoNo1Pro & Farm1,350,000$1,062,581$1,350,000$1,062,581$0$0$NoLien
Givani SmithPhantoms (PHI)LW/RW251998-02-27No210 Lbs6 ft2NoNoNoNo2Pro & Farm750,000$590,323$750,000$590,323$0$0$No750,000$Lien
Grigori DenisenkoPhantoms (PHI)LW/RW232000-06-24Yes175 Lbs5 ft11NoNoNoNo1Pro & Farm1,775,000$1,397,097$450,000$354,194$0$0$NoLien
Jan MysakPhantoms (PHI)C/LW212002-06-24Yes175 Lbs5 ft11NoNoNoNo3Pro & Farm902,500$710,355$902,500$710,355$0$0$No902,500$902,500$
Jiri PateraPhantoms (PHI)G241999-02-24Yes209 Lbs6 ft2NoNoNoNo2Pro & Farm800,000$629,677$800,000$629,677$0$0$No800,000$Lien
John LeonardPhantoms (PHI)LW/RW251998-08-07Yes185 Lbs5 ft11NoNoNoNo1Pro & Farm1,137,500$895,323$1,137,500$895,323$0$0$NoLien
Jordan HarrisPhantoms (PHI)D232000-07-07Yes189 Lbs5 ft11NoNoNoNo3Pro & Farm1,137,500$895,323$1,137,500$895,323$0$0$No1,137,500$1,137,500$Lien
Joseph WollPhantoms (PHI)G251998-07-12Yes198 Lbs6 ft2NoNoNoNo1Pro & Farm766,667$603,441$766,667$603,441$0$0$NoLien
Josh BrookPhantoms (PHI)D241999-06-17Yes194 Lbs6 ft1NoNoNoNo2Pro & Farm910,833$716,914$910,833$716,914$0$0$No910,833$Lien
Josiah SlavinPhantoms (PHI)C241998-12-31Yes161 Lbs6 ft0NoNoNoNo1Pro & Farm925,000$728,065$925,000$728,065$0$0$NoLien
Lane PedersonPhantoms (PHI)C261997-08-04No190 Lbs6 ft0NoNoNoNo4Pro & Farm750,000$590,323$750,000$590,323$0$0$No750,000$750,000$750,000$Lien
Layton AhacPhantoms (PHI)D222001-02-22Yes190 Lbs6 ft2NoNoNoNo1Pro & Farm925,000$728,065$925,000$728,065$0$0$NoLien
Leevi MerilainenPhantoms (PHI)G212002-08-13Yes175 Lbs6 ft2YesNoNoNo3Pro & Farm820,000$645,419$820,000$645,419$0$0$No820,000$820,000$Lien
Mark FriedmanPhantoms (PHI)D271995-12-25No185 Lbs5 ft11NoNoNoNo1Pro & Farm775,000$610,000$775,000$610,000$0$0$NoLien
Michael SgarbossaPhantoms (PHI)C311992-07-25No185 Lbs6 ft0NoNoNoNo2Pro & Farm750,000$590,323$750,000$590,323$0$0$No750,000$Lien
Nicholas RobertsonPhantoms (PHI)LW212001-09-11No162 Lbs5 ft9NoNoNoNo1Pro & Farm821,667$646,731$821,667$646,731$0$0$NoLien
Quinton ByfieldPhantoms (PHI)C/LW212002-08-19No215 Lbs6 ft4NoNoNoNo1Pro & Farm3,544,167$2,789,602$3,544,167$2,789,602$0$0$NoLien
Simon LundmarkPhantoms (PHI)D222000-10-08Yes201 Lbs6 ft2NoNoNoNo2Pro & Farm925,000$728,065$925,000$728,065$0$0$No925,000$Lien
Stelio MattheosPhantoms (PHI)C241999-06-14Yes194 Lbs6 ft1NoNoNoNo1Pro & Farm925,000$728,065$925,000$728,065$0$0$NoLien
Taro HirosePhantoms (PHI)LW271996-06-30No162 Lbs5 ft10NoNoNoNo1Pro & Farm850,000$669,032$850,000$669,032$0$0$NoLien
Thomas HarleyPhantoms (PHI)D222001-08-18No188 Lbs6 ft3NoNoNoNo1Pro & Farm1,288,333$1,014,043$1,288,333$1,014,043$0$0$NoLien
Tyce ThompsonPhantoms (PHI)RW241999-07-11Yes178 Lbs6 ft1NoNoNoNo2Pro & Farm762,500$600,161$762,500$600,161$0$0$No762,500$Lien
Tye KartyePhantoms (PHI)LW222001-04-30Yes202 Lbs5 ft11YesNoNoNo3Pro & Farm925,000$728,065$925,000$728,065$0$0$No925,000$925,000$Lien
Zachary JonesPhantoms (PHI)D222000-10-18No175 Lbs5 ft11NoNoNoNo3Pro & Farm925,000$728,065$925,000$728,065$0$0$No925,000$925,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2724.00187 Lbs6 ft01.701,134,457$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Quinton ByfieldAlex LimogesGrigori Denisenko35122
2Nicholas RobertsonBrandon GignacJohn Leonard30122
3Jan MysakLane PedersonGivani Smith25122
4Andreas JohnssonMichael SgarbossaTyce Thompson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan HarrisThomas Harley35122
2Josh BrookZachary Jones30122
3Simon LundmarkDavid Farrance25122
4Jordan HarrisThomas Harley10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nicholas RobertsonQuinton ByfieldGrigori Denisenko60122
2Alex LimogesBrandon GignacJohn Leonard40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan HarrisThomas Harley60122
2Josh BrookZachary Jones40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Lane PedersonGivani Smith60122
2Tyce ThompsonMichael Sgarbossa40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan HarrisThomas Harley60122
2David FarranceZachary Jones40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Nicholas Robertson60122Jordan HarrisThomas Harley60122
2Lane Pederson40122Simon LundmarkZachary Jones40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Alex LimogesNicholas Robertson60122
2Quinton ByfieldJohn Leonard40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jordan HarrisThomas Harley60122
2Josh BrookZachary Jones40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Givani SmithBrandon GignacAndreas JohnssonJordan HarrisThomas Harley
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jan MysakBrandon GignacAndreas JohnssonJordan HarrisThomas Harley
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
John Leonard, Quinton Byfield, Andreas JohnssonJohn Leonard, Nicholas RobertsonJan Mysak
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Josh Brook, Simon Lundmark, Thomas HarleyJosh BrookJosh Brook, Thomas Harley
Tirs de pénalité
Brandon Gignac, Jan Mysak, Quinton Byfield, Givani Smith, Nicholas Robertson
Gardien
#1 : Joseph Woll, #2 : Jiri Patera
Lignes d’attaque personnalisées en prolongation
Andreas Johnsson, Quinton Byfield, Nicholas Robertson, Givani Smith, Grigori Denisenko, Jan Mysak, Jan Mysak, Lane Pederson, Michael Sgarbossa, John Leonard, Alex Limoges
Lignes de défense personnalisées en prolongation
Jordan Harris, Thomas Harley, Simon Lundmark, Zachary Jones, Josh Brook


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
167s21100000862000000000002110000086220.5008162400151415633909391143918283917423.53%13376.92%025245155.88%24547851.26%13725154.58%395262422139221108
2Bruins1010000026-4000000000001010000026-400.000246001514156169093911423318185120.00%9188.89%025245155.88%24547851.26%13725154.58%395262422139221108
3Condors11000000101000000000001100000010121.0001230115141566909391141921824300.00%70100.00%025245155.88%24547851.26%13725154.58%395262422139221108
4Griffins1010000002-21010000002-20000000000000.00000000151415610909391141551017100.00%5180.00%025245155.88%24547851.26%13725154.58%395262422139221108
5Monsters201010005501010000034-11000100021120.500581300151415630909391144015302710220.00%150100.00%025245155.88%24547851.26%13725154.58%395262422139221108
6Penguins21000010633110000004221000001021141.00068140015141563790939114291124251200.00%10190.00%025245155.88%24547851.26%13725154.58%395262422139221108
7Sound Tigers21000010624110000003031000001032141.000610160115141564490939114381028251119.09%140100.00%025245155.88%24547851.26%13725154.58%395262422139221108
8Stars10000010431100000104310000000000021.00045900151415615909391142641921500.00%7271.43%025245155.88%24547851.26%13725154.58%395262422139221108
9Wolf Pack22000000835110000004311100000040441.000814220115141562890939114348373116318.75%12191.67%025245155.88%24547851.26%13725154.58%395262422139221108
10Wolves31200000811-331200000811-30000000000020.3338122000151415660909391145110346127518.52%15473.33%025245155.88%24547851.26%13725154.58%395262422139221108
Total1776010304841794400010262518320102022166220.647487912703151415627990939114314862462881071614.95%1071387.85%025245155.88%24547851.26%13725154.58%395262422139221108
_Since Last GM Reset1776010304841794400010262518320102022166220.647487912703151415627990939114314862462881071614.95%1071387.85%025245155.88%24547851.26%13725154.58%395262422139221108
_Vs Conference94301010292363210000011926220101018144120.6672950790115141561449093911416555137140601016.67%59689.83%025245155.88%24547851.26%13725154.58%395262422139221108
_Vs Division83101010251312421000001495410010101147100.625254065021514156139909391141414411910849612.24%51296.08%025245155.88%24547851.26%13725154.58%395262422139221108

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1722W348791272793148624628803
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
177610304841
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
94400102625
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
83210202216
Derniers 10 matchs
WLOTWOTL SOWSOL
730000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1071614.95%1071387.85%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
909391141514156
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
25245155.88%24547851.26%13725154.58%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
395262422139221108


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
415Wolves4Phantoms3BLSommaire du match
724Wolves2Phantoms3BWSommaire du match
944Griffins2Phantoms0BLSommaire du match
1050Phantoms367s4ALSommaire du match
1261Phantoms2Monsters1AWXSommaire du match
1367Phantoms4Wolf Pack0AWSommaire du match
1577Wolf Pack3Phantoms4BWSommaire du match
1891Phantoms567s2AWSommaire du match
1999Penguins2Phantoms4BWSommaire du match
20112Sound Tigers0Phantoms3BWSommaire du match
22122Phantoms2Bruins6ALSommaire du match
24135Monsters4Phantoms3BLSommaire du match
25140Phantoms2Penguins1AWXXSommaire du match
29160Wolves5Phantoms2BLSommaire du match
30167Phantoms3Sound Tigers2AWXXSommaire du match
31174Phantoms1Condors0AWSommaire du match
33187Stars3Phantoms4BWXXSommaire du match
35201Bruins-Phantoms-
36206Phantoms-Monsters-
38221Monarchs-Phantoms-
41236Phantoms-Moose-
42245Eagles-Phantoms-
44256Phantoms-Monarchs-
45263Phantoms-Condors-
47275Marlies-Phantoms-
49288Phantoms-Bruins-
50297Griffins-Phantoms-
52310Rocket-Phantoms-
53319Phantoms-Rocket-
56333Phantoms-Rocket-
57339Heat-Phantoms-
60353Bruins-Phantoms-
62361Phantoms-Monsters-
64371Phantoms-Bruins-
65381Wolves-Phantoms-
68394Phantoms-Heat-
69403Condors-Phantoms-
71416Phantoms-Crunch-
73426Sound Tigers-Phantoms-
75438Phantoms-Crunch-
76448Wolves-Phantoms-
78460Phantoms-Penguins-
80470IceHogs-Phantoms-
81479Phantoms-IceHogs-
84491Barracuda-Phantoms-
85501Phantoms-Wolves-
87513Phantoms-Eagles-
89521Rocket-Phantoms-
92534Wolf Pack-Phantoms-
94549Phantoms-Penguins-
95558Phantoms-Griffins-
9656567s-Phantoms-
98579Sound Tigers-Phantoms-
101595Phantoms-Gulls-
102604Penguins-Phantoms-
104618Phantoms-67s-
105624Moose-Phantoms-
109643Crunch-Phantoms-
111653Phantoms-Wolves-
112662Phantoms-67s-
113669Gulls-Phantoms-
117688Penguins-Phantoms-
118695Phantoms-Sound Tigers-
119708Phantoms-Marlies-
120713Crunch-Phantoms-
122730Griffins-Phantoms-
124739Phantoms-Barracuda-
126751Phantoms-Thunderbird-
127757Gulls-Phantoms-
130774Phantoms-Marlies-
131779Marlies-Phantoms-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
134797Wolf Pack-Phantoms-
135805Phantoms-Sound Tigers-
13781967s-Phantoms-
142838Thunderbird-Phantoms-
143841Phantoms-Griffins-
144845Phantoms-Condors-
146860Monsters-Phantoms-
147869Phantoms-Wolf Pack-
148877Phantoms-Stars-
151888Phantoms-Wolf Pack-
153896Monsters-Phantoms-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
27 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
955,995$ 3,063,034$ 2,930,534$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 636,652$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 122 29,439$ 3,591,558$




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