Connexion

Phantoms
GP: 10 | W: 5 | L: 2 | OTL: 3 | P: 13
GF: 42 | GA: 44 | PP%: 15.63% | PK%: 76.67%
DG: Frank Grimard | Morale : 50 | Moyenne d’équipe : 67
Prochain matchs #174 vs Comets
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Centre de jeu
Wolves
3-5-2, 8pts
3
FINAL
5 Phantoms
5-2-3, 13pts
Team Stats
W1StreakW3
3-2-0Home Record3-0-2
0-3-2Away Record2-2-1
3-5-2Last 10 Games5-2-3
3.80Buts par match 4.20
4.60Buts contre par match 4.40
30.00%Pourcentage en avantage numérique15.63%
81.08%Pourcentage en désavantage numérique76.67%
Phantoms
5-2-3, 13pts
5
FINAL
3 W-B/Scranton Penguins
3-7-0, 6pts
Team Stats
W3StreakL2
3-0-2Home Record2-3-0
2-2-1Away Record1-4-0
5-2-3Last 10 Games3-7-0
4.20Buts par match 3.10
4.40Buts contre par match 4.40
15.63%Pourcentage en avantage numérique21.21%
76.67%Pourcentage en désavantage numérique80.56%
Phantoms
5-2-3, 13pts
2022-08-03
Comets
6-3-1, 13pts
Statistiques d’équipe
W3SéquenceSOL1
3-0-2Fiche domicile4-1-0
2-2-1Fiche visiteur2-2-1
5-2-310 derniers matchs6-3-1
4.20Buts par match 4.50
4.40Buts contre par match 4.20
15.63%Pourcentage en avantage numérique25.71%
76.67%Pourcentage en désavantage numérique70.59%
W-B/Scranton Penguins
3-7-0, 6pts
2022-08-04
Phantoms
5-2-3, 13pts
Statistiques d’équipe
L2SéquenceW3
2-3-0Fiche domicile3-0-2
1-4-0Fiche visiteur2-2-1
3-7-010 derniers matchs5-2-3
3.10Buts par match 4.20
4.40Buts contre par match 4.40
21.21%Pourcentage en avantage numérique15.63%
80.56%Pourcentage en désavantage numérique76.67%
Monsters
7-2-1, 15pts
2022-08-05
Phantoms
5-2-3, 13pts
Statistiques d’équipe
W2SéquenceW3
3-2-0Fiche domicile3-0-2
4-0-1Fiche visiteur2-2-1
7-2-110 derniers matchs5-2-3
4.40Buts par match 4.20
3.10Buts contre par match 4.40
18.75%Pourcentage en avantage numérique15.63%
91.30%Pourcentage en désavantage numérique76.67%
Meneurs d'équipe
Victoires
Ken Appleby
4
Pourcentage d’arrêts
Adam Scheel
0.958

Statistiques d’équipe
Buts pour
42
4.20 GFG
Tirs pour
391
39.10 Avg
Pourcentage en avantage numérique
15.6%
5 GF
Début de zone offensive
40.8%
Buts contre
44
4.40 GAA
Tirs contre
406
40.60 Avg
Pourcentage en désavantage numérique
76.7%
7 GA
Début de la zone défensive
41.9%
Information d’équipe

Directeur généralFrank Grimard
EntraîneurMichel Bergeron
DivisionMETROPOLITAINE
ConférenceEST
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Information formation

Équipe Pro31
Équipe Mineure21
Limite contact 52 / 55
Espoirs27


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
1Joachim Blichfeld0XX100.00643881677982836657626761696466050700241790,000$
2Vasily Podkolzin0X100.006435827275818370566467587161640507002131,775,000$
3Andrew Poturalski0X100.00583693646987886677686259656873050690282937,500$
4Gerald Mayhew0XX100.006835946662737466686466656677720506902911,003,000$
5Glenn Gawdin0X100.00713987637680826475655861596567050680253795,000$
6Riley Barber0X100.006438846274807863666164596769700506802811,000,000$
7Dylan Holloway0XX100.006939856578916268706459616663620506802031,441,667$
8Gage Quinney0X100.006037926172896863566164596267690506702711,062,500$
9Ben Jones0X100.007139736172808759665860556264650506602321,254,000$
10David Cotton0X100.007139855780798258625659586165670506602511,093,000$
11Michal Teply0X100.00723894578179835561595660576163050660212919,167$
12Ben McCartney0X100.00793966587184825658575960586163050660213813,333$
13Kurtis MacDermid0X100.00778961599674835730605866516870050690281902,000$
14Jakub Galvas0X100.00623581636883876230615866526367050680233925,000$
15Santeri Hatakka0X100.00603883647677746030655864506163050670213925,000$
16Dmitri Samorukov0X100.00683882628173776030595856496365050660231863,333$
17Cavan Fitzgerald0X100.00663891577571825630555458456668050640261861,000$
18Ryan O'Rourke0X100.00615471567079845830575356455962050630203894,167$
Rayé
1Tyce Thompson0X100.006340875972796658676157625663650506502311,125,000$
2Aarne Talvitie0X100.00633792557268885461555657586365050630231925,000$
3Jamieson Rees0X100.00583776596778875866575654596163050630213910,833$
4Jonathan Davidsson0X100.00583595597063666156605859616764050630251850,000$
5Lukas Rousek0X100.00583692636874655952575553596365050630233830,000$
6Tye Felhaber0X100.00593788566870675351545652576466050610241867,000$
7Mark Friedman0X100.00643670667182736530676566556768050700262918,000$
8Brennan Menell0X100.00613473576866675930585257456567050620253806,000$
9Matthew Kessel (R)0X100.00723883548166645230565052456264050610221700,000$
MOYENNE D’ÉQUIPE100.0065408361747777605260595957646605066
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
1Ken Appleby100.0073686788727173727173726777050750271700,000$
2Adam Scheel100.0070737482696870696870696369050720233910,000$
Rayé
1Kirill Ustimenko100.0066686781656466656466656369050690232925,000$
2Ryan Fanti100.0067646582666567666567666369050690224950,000$
MOYENNE D’ÉQUIPE100.006968688368676968676968647105071
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Michel Bergeron75757575757575CAN7250$


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
1Dylan HollowayPhantoms (PHI)C/LW10771430021148132314.58%212512.5100000000001152.94%3400012.2400000110
2Vasily PodkolzinPhantoms (PHI)RW10013134607264218340.00%321021.080223270000220031.75%6300001.2301000001
3Jakub GalvasPhantoms (PHI)D1056116606153071316.67%1124124.152131427000021100.00%000000.9100000120
4Andrew PoturalskiPhantoms (PHI)C1046102003352853114.29%319919.901013270000240052.74%29200001.0001000000
5Gerald MayhewPhantoms (PHI)LW/RW10369-62012243516378.57%420420.481236270000251125.00%1200000.8801000002
6Ben JonesPhantoms (PHI)C102684201113941122.22%3999.9500000000001054.40%12500001.6100000000
7Michal TeplyPhantoms (PHI)RW10156300910166136.25%112412.4300000000000036.36%1100000.9700000000
8Ben McCartneyPhantoms (PHI)LW104265002331031340.00%212812.8600000000000040.00%1000000.9300000011
9Ryan O'RourkePhantoms (PHI)D10055-81001686030.00%1815615.6400000000012000.00%000000.6400000000
10Glenn GawdinPhantoms (PHI)C10235-5402022244208.33%117817.84112627000000052.80%25000000.5601000000
11Kurtis MacDermidPhantoms (PHI)D10235614047921779.52%1323923.990111027000017000.00%000000.4200000010
12Dmitri SamorukovPhantoms (PHI)D102354802112103520.00%1421121.13011127000123000.00%000000.4700000101
13Riley BarberPhantoms (PHI)RW10325-50010103310149.09%217817.84011627000001050.00%1600000.5600000000
14Santeri HatakkaPhantoms (PHI)D10145420102016996.25%1121321.34000327000024010.00%000000.4700000100
15Cavan FitzgeraldPhantoms (PHI)D10145-86012362116.67%914414.400000000000000.00%000000.6900000000
16Joachim BlichfeldPhantoms (PHI)LW/RW10224000124317216.45%314714.750118280001240114.81%2700100.5401000000
17David CottonPhantoms (PHI)C1011200048741114.29%0747.4100000000000053.47%10100000.5400000000
18Gage QuinneyPhantoms (PHI)LW10202-100091942010.53%0919.1700000000030050.00%1000000.4400000000
Statistiques d’équipe totales ou en moyenne1804278120860022524239112228610.74%100296816.49510156027600022005449.84%95100110.8105000455
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
1Ken ApplebyPhantoms (PHI)104220.8854.5953600413580000.8005100000
2Adam ScheelPhantoms (PHI)21010.9581.7170002480000.0000010000
Statistiques d’équipe totales ou en moyenne125230.8944.2560700434060000.80051010000


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 Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire restantSalaire moyenPlafond 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 10Link
Aarne TalvitiePhantoms (PHI)C231999-02-11No198 Lbs5 ft11NoNoNo1Pro & Farm925,000$925,000$925,000$0$0$NoLien
Adam ScheelPhantoms (PHI)G231999-05-01No192 Lbs6 ft3NoNoNo3Pro & Farm910,000$910,000$910,000$0$0$No910,000$910,000$Lien
Andrew PoturalskiPhantoms (PHI)C281994-01-14No183 Lbs5 ft10NoNoNo2Pro & Farm937,500$937,500$2,175,167$0$0$No937,500$Lien
Ben JonesPhantoms (PHI)C231999-02-26No187 Lbs6 ft0NoNoNo2Pro & Farm1,254,000$1,254,000$1,156,250$0$0$No1,026,000$Lien
Ben McCartneyPhantoms (PHI)LW212001-07-13No182 Lbs6 ft0NoNoNo3Pro & Farm813,333$813,333$700,000$0$0$No813,333$813,333$Lien
Brennan MenellPhantoms (PHI)D251997-05-24No177 Lbs5 ft11NoNoNo3Pro & Farm806,000$806,000$650,000$0$0$No806,000$806,000$Lien
Cavan FitzgeraldPhantoms (PHI)D261996-08-23No190 Lbs6 ft1NoNoNo1Pro & Farm861,000$861,000$0$0$NoLien
David CottonPhantoms (PHI)C251997-07-09No200 Lbs6 ft2NoNoNo1Pro & Farm1,093,000$1,093,000$600,000$0$0$NoLien
Dmitri SamorukovPhantoms (PHI)D231999-06-16No188 Lbs6 ft3NoNoNo1Pro & Farm863,333$863,333$825,002$0$0$NoLien
Dylan HollowayPhantoms (PHI)C/LW202001-09-23No203 Lbs6 ft1NoNoNo3Pro & Farm1,441,667$1,441,667$700,000$0$0$No1,441,667$1,441,667$Lien
Gage QuinneyPhantoms (PHI)LW271995-07-29No200 Lbs5 ft11NoNoNo1Pro & Farm1,062,500$1,062,500$750,000$0$0$NoLien
Gerald MayhewPhantoms (PHI)LW/RW291992-12-31No161 Lbs5 ft9NoNoNo1Pro & Farm1,003,000$1,003,000$650,000$0$0$NoLien
Glenn GawdinPhantoms (PHI)C251997-03-25No191 Lbs6 ft1NoNoNo3Pro & Farm795,000$795,000$650,000$0$0$No700,000$700,000$Lien
Jakub GalvasPhantoms (PHI)D231999-06-15No161 Lbs5 ft11NoNoNo3Pro & Farm925,000$925,000$700,000$0$0$No925,000$925,000$Lien
Jamieson ReesPhantoms (PHI)C212001-02-26No172 Lbs5 ft11NoNoNo3Pro & Farm910,833$910,833$700,000$0$0$No910,833$910,833$Lien
Joachim BlichfeldPhantoms (PHI)LW/RW241998-07-17No180 Lbs6 ft2NoNoNo1Pro & Farm790,000$790,000$736,666$0$0$NoLien
Jonathan DavidssonPhantoms (PHI)RW251997-03-12No185 Lbs5 ft11NoNoNo1Pro & Farm850,000$850,000$768,334$0$0$NoLien
Ken ApplebyPhantoms (PHI)G271995-04-10No210 Lbs6 ft4NoNoNo1Pro & Farm700,000$700,000$700,000$0$0$NoLien
Kirill UstimenkoPhantoms (PHI)G231999-01-29No187 Lbs6 ft3NoNoNo2Pro & Farm925,000$925,000$925,000$0$0$No925,000$Lien
Kurtis MacDermidPhantoms (PHI)D281994-03-25No233 Lbs6 ft5NoNoNo1Pro & Farm902,000$902,000$0$0$NoLien
Lukas RousekPhantoms (PHI)RW231999-04-20No171 Lbs5 ft11NoNoNo3Pro & Farm830,000$830,000$700,000$0$0$No830,000$830,000$Lien
Mark FriedmanPhantoms (PHI)D261995-12-25No185 Lbs5 ft11NoNoNo2Pro & Farm918,000$918,000$650,000$0$0$No918,000$Lien
Matthew KesselPhantoms (PHI)D222000-06-23Yes205 Lbs6 ft2NoNoNo1Pro & Farm700,000$700,000$700,000$0$0$No
Michal TeplyPhantoms (PHI)RW212001-05-27No187 Lbs6 ft3NoNoNo2Pro & Farm919,167$919,167$919,167$0$0$No919,167$Lien
Riley BarberPhantoms (PHI)RW281994-02-07No199 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLien
Ryan FantiPhantoms (PHI)G221999-10-03No194 Lbs6 ft3NoNoNo4Pro & Farm950,000$950,000$950,000$0$0$No950,000$950,000$950,000$Lien
Ryan O'RourkePhantoms (PHI)D202002-05-16No178 Lbs6 ft0NoNoNo3Pro & Farm894,167$894,167$700,000$0$0$No894,167$894,167$Lien
Santeri HatakkaPhantoms (PHI)D212001-01-15No191 Lbs6 ft1NoNoNo3Pro & Farm925,000$925,000$700,000$0$0$No925,000$925,000$Lien
Tyce ThompsonPhantoms (PHI)RW231999-07-12No175 Lbs6 ft1NoNoNo1Pro & Farm1,125,000$1,125,000$1,125,000$0$0$NoLien
Tye FelhaberPhantoms (PHI)LW241998-08-05No180 Lbs5 ft11NoNoNo1Pro & Farm867,000$867,000$925,001$0$0$NoLien
Vasily PodkolzinPhantoms (PHI)RW212001-06-24No190 Lbs6 ft1NoNoNo3Pro & Farm1,775,000$1,775,000$700,000$0$0$No1,775,000$1,775,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3123.87188 Lbs6 ft11.97957,145$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ben McCartneyAndrew PoturalskiVasily Podkolzin30014
2Gerald MayhewGlenn GawdinRiley Barber30023
3Dylan HollowayBen JonesMichal Teply24032
4Gage QuinneyDavid CottonJoachim Blichfeld16131
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kurtis MacDermidJakub Galvas30032
2Santeri HatakkaDmitri Samorukov30032
3Cavan FitzgeraldRyan O'Rourke24032
4Kurtis MacDermidJakub Galvas16032
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Joachim BlichfeldAndrew PoturalskiVasily Podkolzin50014
2Gerald MayhewGlenn GawdinRiley Barber50014
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kurtis MacDermidJakub Galvas50023
2Santeri HatakkaDmitri Samorukov50023
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Glenn GawdinGerald Mayhew50041
2Dylan HollowayJoachim Blichfeld50041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kurtis MacDermidJakub Galvas50140
2Santeri HatakkaCavan Fitzgerald50140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Glenn Gawdin50050Kurtis MacDermidJakub Galvas50140
2Dylan Holloway50050Santeri HatakkaCavan Fitzgerald50140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Dylan HollowayVasily Podkolzin50032
2Andrew PoturalskiJoachim Blichfeld50032
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kurtis MacDermidJakub Galvas50023
2Santeri HatakkaDmitri Samorukov50023
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Joachim BlichfeldAndrew PoturalskiVasily PodkolzinKurtis MacDermidJakub Galvas
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Gerald MayhewGlenn GawdinJoachim BlichfeldKurtis MacDermidJakub Galvas
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Ben Jones, Dylan Holloway, Gage QuinneyBen Jones, Dylan HollowayGage Quinney
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Cavan Fitzgerald, Ryan O'Rourke, Santeri HatakkaCavan FitzgeraldRyan O'Rourke, Santeri Hatakka
Tirs de pénalité
Vasily Podkolzin, Joachim Blichfeld, Riley Barber, Gerald Mayhew, Dylan Holloway
Gardien
#1 : Adam Scheel, #2 : Ken Appleby
Lignes d’attaque personnalisées en prolongation
Vasily Podkolzin, Joachim Blichfeld, Andrew Poturalski, Gerald Mayhew, Glenn Gawdin, Riley Barber, Riley Barber, Dylan Holloway, Gage Quinney, Ben McCartney, Michal Teply
Lignes de défense personnalisées en prolongation
Kurtis MacDermid, Jakub Galvas, Santeri Hatakka, Dmitri Samorukov, Cavan Fitzgerald


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
1Bears2100010010100110000004311000010067-130.750102030001412160791181311398721812419111.11%6266.67%020538353.52%18139346.06%8816254.32%2321622517112361
2Comets11000000422110000004220000000000021.00048120014121603411813113982994276233.33%20100.00%020538353.52%18139346.06%8816254.32%2321622517112361
3Islanders2010010069-31000010023-11010000046-210.25061117001412160601181311398731214489111.11%70100.00%020538353.52%18139346.06%8816254.32%2321622517112361
4W-B/Scranton Penguins11000000532000000000001100000053221.00059140014121603511813113984412626000.00%3233.33%020538353.52%18139346.06%8816254.32%2321622517112361
5Wolf Pack20100001612-61000000156-11010000016-510.25061117001412160801181311398922014397114.29%7185.71%020538353.52%18139346.06%8816254.32%2321622517112361
6Wolves220000001183110000005321100000065141.000111930001412160103118131139896291044100.00%5260.00%020538353.52%18139346.06%8816254.32%2321622517112361
Total1052002014244-25300010120173522001002227-5130.650427812000141216039111813113984061006022532515.63%30776.67%020538353.52%18139346.06%8816254.32%2321622517112361
_Since Last GM Reset1052002014244-25300010120173522001002227-5130.650427812000141216039111813113984061006022532515.63%30776.67%020538353.52%18139346.06%8816254.32%2321622517112361
_Vs Conference1052002014244-25300010120173522001002227-5130.650427812000141216039111813113984061006022532515.63%30776.67%020538353.52%18139346.06%8816254.32%2321622517112361
_Vs Division1052002014244-25300010120173522001002227-5130.650427812000141216039111813113984061006022532515.63%30776.67%020538353.52%18139346.06%8816254.32%2321622517112361

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1013W342781203914061006022500
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
105202014244
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
53001012017
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
52201002227
Derniers 10 matchs
WLOTWOTL SOWSOL
520201
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
32515.63%30776.67%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
11813113981412160
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
20538353.52%18139346.06%8816254.32%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2321622517112361


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 - 2022-07-1815Wolf Pack6Phantoms5BLXXSommaire du match
3 - 2022-07-1929Phantoms1Wolf Pack6ALSommaire du match
5 - 2022-07-2147Phantoms4Islanders6ALSommaire du match
7 - 2022-07-2362Islanders3Phantoms2BLXSommaire du match
8 - 2022-07-2477Bears3Phantoms4BWSommaire du match
10 - 2022-07-26102Comets2Phantoms4BWSommaire du match
11 - 2022-07-27108Phantoms6Bears7ALXSommaire du match
12 - 2022-07-28119Phantoms6Wolves5AWSommaire du match
14 - 2022-07-30135Wolves3Phantoms5BWSommaire du match
15 - 2022-07-31152Phantoms5W-B/Scranton Penguins3AWSommaire du match
18 - 2022-08-03174Phantoms-Comets-
19 - 2022-08-04179W-B/Scranton Penguins-Phantoms-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
20 - 2022-08-05200Monsters-Phantoms-
21 - 2022-08-06211Phantoms-Monsters-



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
36 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,967,150$ 2,329,059$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 8 0$ 0$




Phantoms Leaders statistiques (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


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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 (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