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Phantoms
GP: 82 | W: 33 | L: 46 | OTL: 3 | P: 69
GF: 247 | GA: 329 | PP%: 14.29% | PK%: 77.35%
DG: Richard Duguay | Morale : 50 | Moyenne d’équipe : 57
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Centre de jeu
Monsters
49-24-9, 107pts
3
FINAL
4 Phantoms
33-46-3, 69pts
Team Stats
W1StreakL1
24-13-4Home Record17-21-3
25-11-5Away Record16-25-0
4-2-4Last 10 Games5-5-0
3.50Buts par match 3.01
3.15Buts contre par match 4.01
19.75%Pourcentage en avantage numérique14.29%
80.38%Pourcentage en désavantage numérique77.35%
Phantoms
33-46-3, 69pts
3
FINAL
7 Baby Hawks
50-23-9, 109pts
Team Stats
L1StreakW1
17-21-3Home Record27-9-5
16-25-0Away Record23-14-4
5-5-0Last 10 Games7-3-0
3.01Buts par match 3.61
4.01Buts contre par match 2.88
14.29%Pourcentage en avantage numérique22.11%
77.35%Pourcentage en désavantage numérique86.05%
Meneurs d'équipe
Buts
Reese Johnson
28
Passes
Alexander Nylander
37
Points
Alexander Nylander
59
Plus/Moins
Roby Jarventie
10
Victoires
Joey Daccord
15
Pourcentage d’arrêts
Kyle Keyser
0.946

Statistiques d’équipe
Buts pour
247
3.01 GFG
Tirs pour
2989
36.45 Avg
Pourcentage en avantage numérique
14.3%
34 GF
Début de zone offensive
40.9%
Buts contre
329
4.01 GAA
Tirs contre
3106
37.88 Avg
Pourcentage en désavantage numérique
77.4%%
77 GA
Début de la zone défensive
39.5%
Informations de l'équipe

Directeur généralRichard Duguay
DivisionNord-Est
ConférenceEst
CapitaineMatt Bartkowski
Assistant #1
Assistant #2Gavin Bayreuther


Informations de l’aréna

Capacité3,000
Assistance2,854
Billets de saison300


Informations de la formation

Équipe Pro22
Équipe Mineure21
Limite contact 43 / 50
Espoirs16


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 moyen
1Reese JohnsonX100.00998087637257615571625680254747050600233600,000$
2Josiah SlavinX100.00714391707362656157575577254545050600224600,000$
3Morgan BarronXXX100.00834690728356675761585665754646050600222925,000$
4Alexander NylanderXX100.007871947371565562505663666044440505902311,000,000$
5Jakob Pelletier (R)XX100.00726589636557556680636664634444050590204863,333$
6Sam Poulin (R)XX100.00797880677857575950565865554444050580204863,333$
7Jonah GadjovichX100.00899954748052605534555560254848050570221783,333$
8Trey Fix-WolanskyX100.00656370686361616250586359604444050570223809,166$
9Roby Jarventie (R)X100.00736982686958585850565662534444050570194894,167$
10Austin PoganskiX100.00798786657754626025505565254646050560252750,000$
11Logan HutskoXX100.00696285636257575873595360504444050560223867,000$
12Ben HarpurX100.00849962659163585525444778256263050640262750,000$
13Juuso ValimakiX100.00734470757869725825564777255050050640221925,000$
14Gavin Bayreuther (A)X100.00777585737462626025544773535353050620271650,000$
15Jarred TinordiX100.00809154689156594725364066385657050590292800,000$
16Matt Bartkowski (C)X100.00787487637461654925374167396465050590331655,000$
17Mac HollowellX100.00656173676155565525524357414444050540233799,766$
Rayé
1Dillon Hamaliuk (R)X100.00777776647748484950474662444444050520204789,167$
2Mason Millman (R)X100.00716681676640404425343958374444050510201700,123$
MOYENNE D’ÉQUIPE100.0077717968745759564352526643484805058
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 moyen
1Hunter Jones (R)100.0046496181454645504545454444050500212825,833$
2Arvid Holm (R)100.0044405086434451524849304444050500222845,833$
Rayé
1Beck Warm (R)100.0045455666454545504545454444050480223650,000$
MOYENNE D’ÉQUIPE100.004545567844454751464640444405049
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Alexander NylanderPhantoms (Phi)LW/RW82223759-23340126119311782567.07%22147718.027815481682026741241.18%10200000.8001000322
2Reese JohnsonPhantoms (Phi)RW82282654-151095292155338862768.28%37166820.351564419100091644059.07%21500010.6535001502
3Gavin BayreutherPhantoms (Phi)D82143751-29321011411314937829.40%128176621.545611661740002246110.00%000000.5800110132
4Sam PoulinPhantoms (Phi)LW/RW82252449-6500139992507417010.00%17125015.2533616680001114147.30%7400000.7800000314
5Logan HutskoPhantoms (Phi)C/RW82183048-7180511581744211110.34%14119914.63145963000032354.91%145500000.8000000011
6Josiah SlavinPhantoms (Phi)LW75192645-2714068163291891776.53%24155520.7425742164011111824146.69%52900000.5815000331
7Trey Fix-WolanskyPhantoms (Phi)RW822618442200611021964616413.27%31119814.620002190000543144.54%11900000.7301000143
8Roby JarventiePhantoms (Phi)LW82152843102405489209631477.18%2199612.1512323720001501139.26%13500000.8602000112
9Jonah GadjovichPhantoms (Phi)LW82112839-23125152559312926788.53%48118514.4600010000051137.42%48100000.6600101213
10Jakob PelletierPhantoms (Phi)C/LW68162339-214065155245691856.53%14131019.272810381461015992257.28%107900000.6026000151
11Tommy NovakPhiladelphieC52102434-2412015110161581196.21%1193417.97088241230003421051.32%117500000.7312000211
12Ben HarpurPhantoms (Phi)D7382230-12125252535512536956.40%120166422.80358471720113220210.00%000000.3600320034
13Juuso ValimakiPhantoms (Phi)D3971724-222055608226598.54%6093223.91516481100003115000.00%000100.5100000102
14Mac HollowellPhantoms (Phi)D8132124-1522056405118235.88%99142917.6501111880002157010.00%000000.3400000101
15Austin PoganskiPhantoms (Phi)RW8241620-6580114389728574.12%707138.7100088000020019.05%2100000.5600000110
16Morgan BarronPhantoms (Phi)C/LW/RW3311718212038508526521.18%566620.1903316920002891053.52%39800000.5412000002
17Dominic ToninatoPhiladelphieC/LW/RW1551116-36010376013408.33%732321.560336300006592044.67%40300000.9902000111
18Jarred TinordiPhantoms (Phi)D33312157475109222842610.71%5567620.510331058011099000.00%100000.4400001010
19Matt BartkowskiPhantoms (Phi)D495813-20340891843192411.63%62101520.73314181140000124000.00%000000.2600000100
20Matt MartinPhiladelphieLW10471178034134414339.09%022622.620225320001220045.36%9700000.9700000110
21Dylan SikuraPhiladelphieLW/RW5224-40051023798.70%110921.821121100000250156.36%5500000.7300000000
22Dillon HamaliukPhantoms (Phi)LW15011-400526010.00%2805.37000380000120037.50%1600000.2500000000
23Sasha ChmelevskiPhiladelphieC/RW1000000042250.00%02323.2700003000000043.75%3200000.00%00000000
24Mason MillmanPhantoms (Phi)D8000-200516020.00%413016.350000400009000.00%000000.00%00000000
Statistiques d’équipe totales ou en moyenne1295246435681-1967866020131706310586121917.92%8522253617.4034691034861929336551873291650.87%638700110.60826533282932
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
1Joey DaccordPhiladelphie2315710.9232.67139360628090000.76913230232
2Arvid HolmPhantoms (Phi)39122210.8924.3020532014713580300.83363557101
3Hunter JonesPhantoms (Phi)1941110.8824.7297900776550000.66761712100
4Beck WarmPhantoms (Phi)72500.8464.2338300271750000.00%075000
5Kyle KeyserPhiladelphie21000.9461.61112003560000.00%0111001
Statistiques d’équipe totales ou en moyenne90344530.8963.854923803163053030258385434


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 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 10Link
Alexander NylanderPhantoms (Phi)LW/RW231998-03-02No192 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$0$0$NoLien
Arvid HolmPhantoms (Phi)G221998-11-03Yes205 Lbs6 ft5NoNoNo2Pro & Farm845,833$0$0$No845,833$Lien
Austin PoganskiPhantoms (Phi)RW251996-02-16No201 Lbs6 ft2NoNoYes2Pro & Farm750,000$0$0$No750,000$Lien
Beck WarmPhantoms (Phi)G221999-04-21Yes181 Lbs6 ft0NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Lien
Ben Harpur (contrat à 1 volet)Phantoms (Phi)D261995-01-11No231 Lbs6 ft6NoNoYes2Pro & Farm750,000$0$0$No750,000$Lien
Dillon HamaliukPhantoms (Phi)LW202000-10-30Yes201 Lbs6 ft4NoNoNo4Pro & Farm789,167$0$0$No789,167$789,167$789,167$Lien
Gavin Bayreuther (contrat à 1 volet)Phantoms (Phi)D271994-05-12No195 Lbs6 ft1NoNoYes1Pro & Farm650,000$0$0$NoLien
Hunter JonesPhantoms (Phi)G212000-09-21Yes194 Lbs6 ft4NoNoNo2Pro & Farm825,833$0$0$No825,833$Lien
Jakob PelletierPhantoms (Phi)C/LW202001-03-07Yes181 Lbs5 ft10NoNoNo4Pro & Farm863,333$0$0$No863,333$863,333$863,333$Lien
Jarred Tinordi (contrat à 1 volet)Phantoms (Phi)D291992-02-20No230 Lbs6 ft6NoNoYes2Pro & Farm800,000$0$0$No800,000$Lien
Jonah GadjovichPhantoms (Phi)LW221998-10-12No209 Lbs6 ft2NoNoNo1Pro & Farm783,333$0$0$NoLien
Josiah SlavinPhantoms (Phi)LW221998-12-31No190 Lbs6 ft3YesNoNo4Pro & Farm600,000$0$0$No600,000$600,000$600,000$Lien
Juuso ValimakiPhantoms (Phi)D221998-10-06No212 Lbs6 ft2NoNoNo1Pro & Farm925,000$0$0$NoLien
Logan HutskoPhantoms (Phi)C/RW221999-02-11No172 Lbs5 ft10NoNoNo3Pro & Farm867,000$0$0$No867,000$867,000$Lien
Mac HollowellPhantoms (Phi)D231998-09-26No172 Lbs5 ft9NoNoNo3Pro & Farm799,766$0$0$No799,766$799,766$Lien
Mason MillmanPhantoms (Phi)D202001-07-18Yes175 Lbs6 ft1YesNoNo1Pro & Farm700,123$0$0$NoLien
Matt Bartkowski (contrat à 1 volet)Phantoms (Phi)D331988-06-04No201 Lbs6 ft1NoNoYes1Pro & Farm575,000$0$0$NoLien
Morgan BarronPhantoms (Phi)C/LW/RW221998-12-02No220 Lbs6 ft4NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Reese JohnsonPhantoms (Phi)RW231998-07-10No193 Lbs6 ft1YesNoNo3Pro & Farm600,000$0$0$No600,000$600,000$Lien
Roby JarventiePhantoms (Phi)LW192002-08-08Yes184 Lbs6 ft2NoNoNo4Pro & Farm894,167$0$0$No894,167$894,167$894,167$Lien
Sam PoulinPhantoms (Phi)LW/RW202001-02-25Yes214 Lbs6 ft2NoNoNo4Pro & Farm863,333$0$0$No863,333$863,333$863,333$Lien
Trey Fix-WolanskyPhantoms (Phi)RW221999-05-26No187 Lbs5 ft7NoNoNo3Pro & Farm809,166$0$0$No809,166$809,166$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2222.95197 Lbs6 ft22.41784,821$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Josiah SlavinJakob PelletierReese Johnson40122
2Alexander NylanderLogan HutskoSam Poulin30122
3Roby JarventieJonah GadjovichTrey Fix-Wolansky20122
4Jonah GadjovichJosiah SlavinAustin Poganski10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben HarpurGavin Bayreuther40122
2Jarred TinordiMac Hollowell30122
3Austin Poganski20122
4Ben HarpurGavin Bayreuther10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Josiah SlavinJakob PelletierReese Johnson60122
2Alexander NylanderLogan HutskoSam Poulin40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben HarpurGavin Bayreuther60122
2Jarred TinordiMac Hollowell40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Josiah SlavinReese Johnson60122
2Jakob PelletierAlexander Nylander40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben HarpurGavin Bayreuther60122
2Jarred TinordiMac Hollowell40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Josiah Slavin60122Ben HarpurGavin Bayreuther60122
2Reese Johnson40122Jarred TinordiMac Hollowell40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Josiah SlavinReese Johnson60122
2Jakob PelletierAlexander Nylander40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben HarpurGavin Bayreuther60122
2Jarred TinordiMac Hollowell40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Josiah SlavinJakob PelletierReese JohnsonBen HarpurGavin Bayreuther
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Josiah SlavinJakob PelletierReese JohnsonBen HarpurGavin Bayreuther
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Roby Jarventie, Trey Fix-Wolansky, Roby Jarventie, Trey Fix-Wolansky
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jarred Tinordi, Mac Hollowell, Ben HarpurJarred TinordiMac Hollowell, Ben Harpur
Tirs de pénalité
Josiah Slavin, Reese Johnson, Jakob Pelletier, Alexander Nylander, Sam Poulin
Gardien
#1 : , #2 : Arvid Holm


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
1Admirals21000010862100000104311100000043141.0008142200104706511691004991968506818203812325.00%10370.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
2Baby Hawks20200000511-61010000024-21010000037-400.00058130010470651151100499196850791920648112.50%5180.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
3Bears412010001114-32010100089-12110000035-240.5001122330010470651112110049919685012828459512325.00%19478.95%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
4Bruins31200000612-61010000035-22110000037-420.3336111700104706511107100499196850911821731417.14%7185.71%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
5Cabaret Lady Mary Ann33000000201192200000012661100000085361.000203656001047065111971004991968501253352855120.00%16287.50%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
6Caroline412010001114-3201010008802110000036-340.5001121320010470651114010049919685013946348310220.00%17476.47%11422285749.77%1300275747.15%648137147.26%1956132919266101084546
7Chiefs22000000936110000003121100000062441.000917260010470651165100499196850561284612325.00%30100.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
8Chill2020000069-31010000034-11010000035-200.000611170010470651168100499196850922924373133.33%12375.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
9Comets2110000046-21010000025-31100000021120.5004711001047065116510049919685088291641500.00%8187.50%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
10Cougars32100000131122110000068-21100000073440.6671324370010470651112410049919685011236227911218.18%11281.82%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
11Crunch321000001013-321100000812-41100000021140.667101929001047065111391004991968501193832621200.00%14564.29%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
12Heat2110000067-11010000014-31100000053220.500610160010470651188100499196850782418533133.33%8187.50%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
13Jayhawks22000000844110000004131100000043141.00081220001047065116810049919685067211839300.00%7271.43%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
14Las Vegas20200000813-51010000056-11010000037-400.000813210010470651186100499196850682218422150.00%8450.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
15Manchots30200100411-71000010034-12020000017-610.167461000104706511851004991968501072748718112.50%14378.57%11422285749.77%1300275747.15%648137147.26%1956132919266101084546
16Marlies312000001015-51100000064220200000411-720.333101525001047065111001004991968501114116701119.09%8362.50%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
17Minnesota2020000046-21010000023-11010000023-100.00048120010470651159100499196850762010542150.00%5180.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
18Monarchs22000000743110000004311100000031241.0007121900104706511105100499196850752618555120.00%80100.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
19Monsters403000101017-72010001068-22020000049-520.250101626001047065111481004991968501483716101800.00%7185.71%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
20Monsters20200000411-71010000025-31010000026-400.00048120010470651150100499196850822126516116.67%12375.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
21Oceanics22000000844110000004221100000042241.00081321001047065117210049919685076242856600.00%14192.86%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
22Oil Kings210000017611000000112-11100000064230.75071219001047065117910049919685069151449700.00%60100.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
23Rocket3100002015114210000108531000001076161.00015254000104706511108100499196850122343676700.00%17382.35%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
24Seattle2020000027-51010000003-31010000024-200.0002460010470651110210049919685075211253300.00%6183.33%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
25Senators30201000814-61000100043120200000411-720.333815230010470651111810049919685010728246715320.00%12375.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
26Sharks21100000810-2110000003211010000058-320.50081422001047065117510049919685077278646350.00%40100.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
27Sound Tigers40400000718-1120200000410-62020000038-500.00071118001047065111091004991968501675056964125.00%22481.82%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
28Spiders40400000521-162020000019-820200000412-800.000571200104706511112100499196850174514911413215.38%22672.73%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
29Stars2010001078-11010000035-21000001043120.50071017001047065117210049919685064262450600.00%11372.73%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
30Thunder30200001817-91000000134-120200000513-810.1678162400104706511891004991968501203229817114.29%12650.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
31Wolf Pack30300000815-720200000511-61010000034-100.00081321001047065111181004991968501463230781200.00%15660.00%01422285749.77%1300275747.15%648137147.26%1956132919266101084546
Total82254603152247329-8241112103132128159-3141142500020119170-51690.421247430677001047065112989100499196850310688579220232383414.29%3407777.35%21422285749.77%1300275747.15%648137147.26%1956132919266101084546
_Since Last GM Reset82254603152247329-8241112103132128159-3141142500020119170-51690.421247430677001047065112989100499196850310688579220232383414.29%3407777.35%21422285749.77%1300275747.15%648137147.26%1956132919266101084546
_Vs Conference4492902121114187-7320410021216181-20245190000053106-53280.318114196310001047065111496100499196850168746843210961362115.44%1864476.34%11422285749.77%1300275747.15%648137147.26%1956132919266101084546
_Vs Division260140001056110-541307000103559-241307000002151-3020.038569615200104706511833100499196850100927127863867913.43%1162875.86%21422285749.77%1300275747.15%648137147.26%1956132919266101084546

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8269L124743067729893106885792202300
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8225463152247329
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4111213132128159
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4114250020119170
Derniers 10 matchs
WLOTWOTL SOWSOL
550000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2383414.29%3407777.35%2
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
100499196850104706511
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
1422285749.77%1300275747.15%648137147.26%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1956132919266101084546


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
7 - 2022-10-1312Spiders5Phantoms1BLSommaire du match
9 - 2022-10-1526Comets5Phantoms2BLSommaire du match
12 - 2022-10-1853Phantoms2Thunder5ALSommaire du match
13 - 2022-10-1956Phantoms8Cabaret Lady Mary Ann5AWSommaire du match
16 - 2022-10-2283Phantoms3Chill5ALSommaire du match
17 - 2022-10-2391Sharks2Phantoms3BWSommaire du match
21 - 2022-10-27112Cabaret Lady Mary Ann4Phantoms6BWSommaire du match
23 - 2022-10-29132Caroline3Phantoms4BWXSommaire du match
26 - 2022-11-01149Phantoms3Wolf Pack4ALSommaire du match
27 - 2022-11-02159Phantoms2Marlies5ALSommaire du match
30 - 2022-11-05183Phantoms3Senators7ALSommaire du match
33 - 2022-11-08199Chiefs1Phantoms3BWSommaire du match
35 - 2022-11-10214Phantoms1Monsters4ALSommaire du match
37 - 2022-11-12225Senators3Phantoms4BWXSommaire du match
38 - 2022-11-13238Stars5Phantoms3BLSommaire du match
40 - 2022-11-15250Phantoms3Monsters5ALSommaire du match
42 - 2022-11-17265Phantoms0Bruins5ALSommaire du match
44 - 2022-11-19281Phantoms7Rocket6AWXXSommaire du match
46 - 2022-11-21292Heat4Phantoms1BLSommaire du match
48 - 2022-11-23312Phantoms0Bears4ALSommaire du match
50 - 2022-11-25324Manchots4Phantoms3BLXSommaire du match
51 - 2022-11-26337Phantoms1Sound Tigers3ALSommaire du match
54 - 2022-11-29353Sound Tigers6Phantoms1BLSommaire du match
56 - 2022-12-01367Thunder4Phantoms3BLXXSommaire du match
58 - 2022-12-03382Spiders4Phantoms0BLSommaire du match
60 - 2022-12-05397Monsters5Phantoms2BLSommaire du match
62 - 2022-12-07413Bears5Phantoms6BWXSommaire du match
64 - 2022-12-09432Phantoms3Las Vegas7ALSommaire du match
66 - 2022-12-11445Phantoms4Jayhawks3AWSommaire du match
68 - 2022-12-13464Phantoms2Monsters6ALSommaire du match
70 - 2022-12-15473Phantoms2Spiders4ALSommaire du match
72 - 2022-12-17489Wolf Pack7Phantoms2BLSommaire du match
75 - 2022-12-20510Monsters5Phantoms2BLSommaire du match
77 - 2022-12-22525Phantoms2Marlies6ALSommaire du match
78 - 2022-12-23535Phantoms2Caroline1AWSommaire du match
84 - 2022-12-29573Phantoms5Sharks8ALSommaire du match
86 - 2022-12-31580Phantoms3Monarchs1AWSommaire du match
88 - 2023-01-02597Phantoms4Admirals3AWSommaire du match
91 - 2023-01-05612Jayhawks1Phantoms4BWSommaire du match
94 - 2023-01-08643Marlies4Phantoms6BWSommaire du match
97 - 2023-01-11659Bears4Phantoms2BLSommaire du match
100 - 2023-01-14681Phantoms3Bears1AWSommaire du match
102 - 2023-01-16695Phantoms3Bruins2AWSommaire du match
103 - 2023-01-17705Admirals3Phantoms4BWXXSommaire du match
105 - 2023-01-19719Baby Hawks4Phantoms2BLSommaire du match
107 - 2023-01-21735Phantoms7Cougars3AWSommaire du match
108 - 2023-01-22749Oceanics2Phantoms4BWSommaire du match
110 - 2023-01-24757Monarchs3Phantoms4BWSommaire du match
112 - 2023-01-26779Phantoms2Minnesota3ALSommaire du match
114 - 2023-01-28790Phantoms4Oceanics2AWSommaire du match
123 - 2023-02-06807Sound Tigers4Phantoms3BLSommaire du match
126 - 2023-02-09822Oil Kings2Phantoms1BLXXSommaire du match
128 - 2023-02-11836Chill4Phantoms3BLSommaire du match
129 - 2023-02-12848Seattle3Phantoms0BLSommaire du match
133 - 2023-02-16876Phantoms2Seattle4ALSommaire du match
135 - 2023-02-18890Phantoms2Comets1AWSommaire du match
137 - 2023-02-20905Phantoms5Heat3AWSommaire du match
138 - 2023-02-21916Phantoms6Oil Kings4AWSommaire du match
141 - 2023-02-24932Rocket2Phantoms3BWXXSommaire du match
142 - 2023-02-25941Phantoms2Spiders8ALSommaire du match
146 - 2023-03-01968Wolf Pack4Phantoms3BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-03-04990Phantoms2Crunch1AWSommaire du match
150 - 2023-03-051003Cougars2Phantoms5BWSommaire du match
152 - 2023-03-071014Phantoms3Thunder8ALSommaire du match
154 - 2023-03-091030Phantoms1Caroline5ALSommaire du match
156 - 2023-03-111039Phantoms0Manchots4ALSommaire du match
159 - 2023-03-141066Las Vegas6Phantoms5BLSommaire du match
162 - 2023-03-171091Crunch7Phantoms2BLSommaire du match
163 - 2023-03-181099Caroline5Phantoms4BLSommaire du match
166 - 2023-03-211122Cabaret Lady Mary Ann2Phantoms6BWSommaire du match
168 - 2023-03-231136Minnesota3Phantoms2BLSommaire du match
170 - 2023-03-251150Cougars6Phantoms1BLSommaire du match
173 - 2023-03-281177Rocket3Phantoms5BWSommaire du match
175 - 2023-03-301193Phantoms1Senators4ALSommaire du match
177 - 2023-04-011206Crunch5Phantoms6BWSommaire du match
178 - 2023-04-021221Phantoms1Manchots3ALSommaire du match
180 - 2023-04-041234Phantoms6Chiefs2AWSommaire du match
182 - 2023-04-061252Phantoms4Stars3AWXXSommaire du match
184 - 2023-04-081268Phantoms2Sound Tigers5ALSommaire du match
185 - 2023-04-091273Bruins5Phantoms3BLSommaire du match
187 - 2023-04-111287Monsters3Phantoms4BWXXSommaire du match
189 - 2023-04-131306Phantoms3Baby Hawks7ALSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance77,82639,168
Assistance PCT94.91%95.53%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2854 - 95.12% 80,767$3,311,430$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,477,246$ 1,449,105$ 1,449,105$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
7,627$ 1,474,991$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 7,627$ 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

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