Connexion

Phantoms
GP: 72 | W: 28 | L: 41 | OTL: 3 | P: 59
GF: 212 | GA: 289 | PP%: 13.46% | PK%: 78.11%
DG: Richard Duguay | Morale : 50 | Moyenne d’équipe : 57
Prochains matchs #1177 vs Rocket
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Centre de jeu
Minnesota
32-35-6, 70pts
3
FINAL
2 Phantoms
28-41-3, 59pts
Team Stats
W2StreakL2
21-14-2Home Record14-20-3
11-21-4Away Record14-21-0
7-3-0Last 10 Games2-8-0
3.10Buts par match 2.94
3.36Buts contre par match 4.01
21.93%Pourcentage en avantage numérique13.46%
79.78%Pourcentage en désavantage numérique78.11%
Cougars
41-25-6, 88pts
6
FINAL
1 Phantoms
28-41-3, 59pts
Team Stats
W6StreakL2
18-15-3Home Record14-20-3
23-10-3Away Record14-21-0
7-2-1Last 10 Games2-8-0
4.24Buts par match 2.94
3.76Buts contre par match 4.01
21.40%Pourcentage en avantage numérique13.46%
70.54%Pourcentage en désavantage numérique78.11%
Rocket
22-37-14, 58pts
2023-03-28
Phantoms
28-41-3, 59pts
Statistiques d’équipe
L3SéquenceL2
10-21-5Fiche domicile14-20-3
12-16-9Fiche visiteur14-21-0
3-6-110 derniers matchs2-8-0
3.15Buts par match 2.94
4.01Buts contre par match 2.94
20.57%Pourcentage en avantage numérique13.46%
74.41%Pourcentage en désavantage numérique78.11%
Phantoms
28-41-3, 59pts
2023-03-30
Senators
41-26-6, 88pts
Statistiques d’équipe
L2SéquenceL2
14-20-3Fiche domicile24-12-0
14-21-0Fiche visiteur17-14-6
2-8-010 derniers matchs3-6-1
2.94Buts par match 3.45
4.01Buts contre par match 3.45
13.46%Pourcentage en avantage numérique22.03%
78.11%Pourcentage en désavantage numérique79.31%
Crunch
32-33-8, 72pts
2023-04-01
Phantoms
28-41-3, 59pts
Statistiques d’équipe
L2SéquenceL2
19-16-2Fiche domicile14-20-3
13-17-6Fiche visiteur14-21-0
4-6-010 derniers matchs2-8-0
3.34Buts par match 2.94
3.67Buts contre par match 2.94
19.72%Pourcentage en avantage numérique13.46%
75.10%Pourcentage en désavantage numérique78.11%
Meneurs d'équipe
Buts
Reese Johnson
27
Passes
Gavin Bayreuther
36
Points
Reese Johnson
48
Plus/Moins
Roby Jarventie
8
Victoires
Joey Daccord
15
Pourcentage d’arrêts
Kyle Keyser
0.946

Statistiques d’équipe
Buts pour
212
2.94 GFG
Tirs pour
2639
36.65 Avg
Pourcentage en avantage numérique
13.5%
28 GF
Début de zone offensive
41.0%
Buts contre
289
4.01 GAA
Tirs contre
2711
37.65 Avg
Pourcentage en désavantage numérique
78.1%%
65 GA
Début de la zone défensive
39.7%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,847
Billets de saison300


Informations de la formation

Équipe Pro23
Équipe Mineure21
Limite contact 44 / 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
1Kyle Keyser (R)100.0054415169585553585756304444050540221650,000$
2Arvid Holm (R)100.0044405086434451524849304444050500222845,833$
Rayé
1Hunter Jones (R)98.0246496181454645504545454444050500212825,833$
2Beck Warm (R)100.0045455666454545504545454444050480223650,000$
MOYENNE D’ÉQUIPE99.504744557648484953494938444405051
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
1Reese JohnsonPhantoms (Phi)RW72272148-10915257139300762559.00%31145520.211453617000061324058.50%20000010.6623001502
2Gavin BayreutherPhantoms (Phi)D72113647-2232109910013132688.40%109154021.39459561510002206110.00%000000.6100110131
3Alexander NylanderPhantoms (Phi)LW/RW72192847-25300112101271622137.01%19127217.686713401451015521240.48%8400000.7401000221
4Josiah SlavinPhantoms (Phi)LW65172340-2312065142258771526.59%21132320.3625738142011101413147.25%40000000.6003000321
5Sam PoulinPhantoms (Phi)LW/RW72202040-738012286211601529.48%13107114.891237440001113148.44%6400000.7500000304
6Logan HutskoPhantoms (Phi)C/RW72122638-81604113815337947.84%13102014.17011538000032155.08%123100000.7400000011
7Trey Fix-WolanskyPhantoms (Phi)RW72221537118056841674114013.17%26104514.520002150000543144.74%11400000.7101000133
8Roby JarventiePhantoms (Phi)LW7213243782404978176571267.39%1983811.6412323680001501139.68%12600000.8802000112
9Jakob PelletierPhantoms (Phi)C/LW58152035214058125219621626.85%12110719.10279331251015762259.17%84000000.6314000150
10Tommy NovakPhiladelphieC52102434-2412015110161581196.21%1193417.97088241230003421051.32%117500000.7312000211
11Jonah GadjovichPhantoms (Phi)LW7282432-259752187110820677.41%43103214.3400010000050039.70%33500000.6200100013
12Ben HarpurPhantoms (Phi)D6371926-7112202215011230846.25%102143622.80246401480113183210.00%000000.3600310034
13Juuso ValimakiPhantoms (Phi)D3971724-222055608226598.54%6093223.91516481100003115000.00%000100.5100000102
14Mac HollowellPhantoms (Phi)D7121719-1922045344313174.65%84121917.180005670002121010.00%000000.3100000100
15Morgan BarronPhantoms (Phi)C/LW/RW3311718212038508526521.18%566620.1903316920002891053.52%39800000.5412000002
16Dominic ToninatoPhiladelphieC/LW/RW1551116-36010376013408.33%732321.560336300006592044.67%40300000.9902000111
17Matt BartkowskiPhantoms (Phi)D495813-20340891843192411.63%62101520.73314181140000124000.00%000000.2600000100
18Austin PoganskiPhantoms (Phi)RW723811-746078347723483.90%525467.6000057000020019.05%2100000.4000000000
19Matt MartinPhiladelphieLW10471178034134414339.09%022622.620225320001220045.36%9700000.9700000110
20Jarred TinordiPhantoms (Phi)D23358324081162031615.00%4247220.56011436000068000.00%100000.3400000010
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 moyenne1155213373586-1896704017581503275875819387.72%7381982617.172857854161694224501613261351.41%559200110.59520521242528
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)2971710.8894.451443201079630000.00%02547101
3Hunter JonesPhantoms (Phi)1941110.8824.7297900776550000.66761712100
4Beck WarmPhantoms (Phi)72500.8464.2338300271750000.00%075000
5Kyle KeyserPhantoms (Phi)21000.9461.61112003560000.00%0111001
Statistiques d’équipe totales ou en moyenne80294030.8963.844313802762658000197375434


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$100,000$0$0$NoLien
Arvid HolmPhantoms (Phi)G221998-11-03Yes205 Lbs6 ft5NoNoNo2Pro & Farm845,833$84,583$0$0$No845,833$Lien
Austin PoganskiPhantoms (Phi)RW251996-02-16No201 Lbs6 ft2NoNoYes2Pro & Farm750,000$75,000$0$0$No750,000$Lien
Beck WarmPhantoms (Phi)G221999-04-21Yes181 Lbs6 ft0NoNoNo3Pro & Farm650,000$65,000$0$0$No650,000$650,000$Lien
Ben Harpur (contrat à 1 volet)Phantoms (Phi)D261995-01-11No231 Lbs6 ft6NoNoYes2Pro & Farm750,000$75,000$0$0$No750,000$Lien
Dillon HamaliukPhantoms (Phi)LW202000-10-30Yes201 Lbs6 ft4NoNoNo4Pro & Farm789,167$78,917$0$0$No789,167$789,167$789,167$Lien
Gavin Bayreuther (contrat à 1 volet)Phantoms (Phi)D271994-05-12No195 Lbs6 ft1NoNoYes1Pro & Farm650,000$65,000$0$0$NoLien
Hunter JonesPhantoms (Phi)G212000-09-21Yes194 Lbs6 ft4NoNoNo2Pro & Farm825,833$82,583$0$0$No825,833$Lien
Jakob PelletierPhantoms (Phi)C/LW202001-03-07Yes181 Lbs5 ft10NoNoNo4Pro & Farm863,333$86,333$0$0$No863,333$863,333$863,333$Lien
Jarred Tinordi (contrat à 1 volet)Phantoms (Phi)D291992-02-20No230 Lbs6 ft6NoNoYes2Pro & Farm800,000$80,000$0$0$No800,000$Lien
Jonah GadjovichPhantoms (Phi)LW221998-10-12No209 Lbs6 ft2NoNoNo1Pro & Farm783,333$78,333$0$0$NoLien
Josiah SlavinPhantoms (Phi)LW221998-12-31No190 Lbs6 ft3YesNoNo4Pro & Farm600,000$60,000$0$0$No600,000$600,000$600,000$Lien
Juuso ValimakiPhantoms (Phi)D221998-10-06No212 Lbs6 ft2NoNoNo1Pro & Farm925,000$92,500$0$0$NoLien
Kyle KeyserPhantoms (Phi)G221999-03-08Yes178 Lbs6 ft2NoNoNo1Pro & Farm650,000$65,000$0$0$NoLien
Logan HutskoPhantoms (Phi)C/RW221999-02-11No172 Lbs5 ft10NoNoNo3Pro & Farm867,000$86,700$0$0$No867,000$867,000$Lien
Mac HollowellPhantoms (Phi)D231998-09-26No172 Lbs5 ft9NoNoNo3Pro & Farm799,766$79,977$0$0$No799,766$799,766$Lien
Mason MillmanPhantoms (Phi)D202001-07-18Yes175 Lbs6 ft1YesNoNo1Pro & Farm700,123$70,012$0$0$NoLien
Matt Bartkowski (contrat à 1 volet)Phantoms (Phi)D331988-06-04No201 Lbs6 ft1NoNoYes1Pro & Farm575,000$65,500$0$0$NoLien
Morgan BarronPhantoms (Phi)C/LW/RW221998-12-02No220 Lbs6 ft4NoNoNo2Pro & Farm925,000$92,500$0$0$No925,000$Lien
Reese JohnsonPhantoms (Phi)RW231998-07-10No193 Lbs6 ft1YesNoNo3Pro & Farm600,000$60,000$0$0$No600,000$600,000$Lien
Roby JarventiePhantoms (Phi)LW192002-08-08Yes184 Lbs6 ft2NoNoNo4Pro & Farm894,167$89,417$0$0$No894,167$894,167$894,167$Lien
Sam PoulinPhantoms (Phi)LW/RW202001-02-25Yes214 Lbs6 ft2NoNoNo4Pro & Farm863,333$86,333$0$0$No863,333$863,333$863,333$Lien
Trey Fix-WolanskyPhantoms (Phi)RW221999-05-26No187 Lbs5 ft7NoNoNo3Pro & Farm809,166$80,917$0$0$No809,166$809,166$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2322.91196 Lbs6 ft22.35778,959$



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
1Admirals21000010862100000104311100000043141.0008142200925856869912869840366818203812325.00%10370.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
2Baby Hawks1010000024-21010000024-20000000000000.0002240092585682291286984036313425300.00%20100.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
3Bears412010001114-32010100089-12110000035-240.5001122330092585681219128698403612828459512325.00%19478.95%01278252750.57%1149244447.01%560119147.02%173011801677533949480
4Bruins2110000037-4000000000002110000037-420.5003580092585687691286984036521117451200.00%5180.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
5Cabaret Lady Mary Ann33000000201192200000012661100000085361.000203656009258568197912869840361253352855120.00%16287.50%01278252750.57%1149244447.01%560119147.02%173011801677533949480
6Caroline412010001114-3201010008802110000036-340.5001121320092585681409128698403613946348310220.00%17476.47%11278252750.57%1149244447.01%560119147.02%173011801677533949480
7Chiefs11000000312110000003120000000000021.00036900925856833912869840362048228112.50%30100.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
8Chill2020000069-31010000034-11010000035-200.000611170092585686891286984036922924373133.33%12375.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
9Comets2110000046-21010000025-31100000021120.5004711009258568659128698403688291641500.00%8187.50%01278252750.57%1149244447.01%560119147.02%173011801677533949480
10Cougars32100000131122110000068-21100000073440.6671324370092585681249128698403611236227911218.18%11281.82%01278252750.57%1149244447.01%560119147.02%173011801677533949480
11Crunch2110000048-41010000027-51100000021120.5004711009258568819128698403686252237700.00%9366.67%01278252750.57%1149244447.01%560119147.02%173011801677533949480
12Heat2110000067-11010000014-31100000053220.500610160092585688891286984036782418533133.33%8187.50%01278252750.57%1149244447.01%560119147.02%173011801677533949480
13Jayhawks22000000844110000004131100000043141.00081220009258568689128698403667211839300.00%7271.43%01278252750.57%1149244447.01%560119147.02%173011801677533949480
14Las Vegas20200000813-51010000056-11010000037-400.000813210092585688691286984036682218422150.00%8450.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
15Manchots2010010038-51000010034-11010000004-410.2503580092585685791286984036711722506116.67%10280.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
16Marlies312000001015-51100000064220200000411-720.333101525009258568100912869840361114116701119.09%8362.50%01278252750.57%1149244447.01%560119147.02%173011801677533949480
17Minnesota2020000046-21010000023-11010000023-100.00048120092585685991286984036762010542150.00%5180.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
18Monarchs22000000743110000004311100000031241.0007121900925856810591286984036752618555120.00%80100.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
19Monsters30300000614-81010000025-32020000049-500.000610160092585681099128698403611525880700.00%4175.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
20Monsters20200000411-71010000025-31010000026-400.00048120092585685091286984036822126516116.67%12375.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
21Oceanics22000000844110000004221100000042241.00081321009258568729128698403676242856600.00%14192.86%01278252750.57%1149244447.01%560119147.02%173011801677533949480
22Oil Kings210000017611000000112-11100000064230.75071219009258568799128698403669151449700.00%60100.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
23Rocket200000201082100000103211000001076141.000101626009258568719128698403692232251500.00%10280.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
24Seattle2020000027-51010000003-31010000024-200.0002460092585681029128698403675211253300.00%6183.33%01278252750.57%1149244447.01%560119147.02%173011801677533949480
25Senators20101000710-3100010004311010000037-420.5007132000925856884912869840366219204711218.18%10280.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
26Sharks21100000810-2110000003211010000058-320.50081422009258568759128698403677278646350.00%40100.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
27Sound Tigers30300000513-820200000410-61010000013-200.00057120092585688191286984036113343861200.00%130100.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
28Spiders40400000521-162020000019-820200000412-800.000571200925856811291286984036174514911413215.38%22672.73%01278252750.57%1149244447.01%560119147.02%173011801677533949480
29Stars1010000035-21010000035-20000000000000.0003580092585683891286984036235829300.00%3166.67%01278252750.57%1149244447.01%560119147.02%173011801677533949480
30Thunder30200001817-91000000134-120200000513-810.1678162400925856889912869840361203229817114.29%12650.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
31Wolf Pack30300000815-720200000511-61010000034-100.00081321009258568118912869840361463230781200.00%15660.00%01278252750.57%1149244447.01%560119147.02%173011801677533949480
Total72224103132212289-773792003122110143-3335132100010102146-44590.410212368580009258568263991286984036271176267617642082813.46%2976578.11%11278252750.57%1149244447.01%560119147.02%173011801677533949480
_Since Last GM Reset72224103132212289-773792003122110143-3335132100010102146-44590.410212368580009258568263991286984036271176267617642082813.46%2976578.11%11278252750.57%1149244447.01%560119147.02%173011801677533949480
_Vs Conference3992502111103167-641849021115473-1921516000004994-45260.33310317728000925856813369128698403614804143729711251814.40%1663877.11%01278252750.57%1149244447.01%560119147.02%173011801677533949480
_Vs Division23013000004999-501207000003156-251106000001843-2500.00049851340092585687389128698403688623322656162812.90%1002377.00%11278252750.57%1149244447.01%560119147.02%173011801677533949480

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7259L221236858026392711762676176400
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7222413132212289
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
379203122110143
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3513210010102146
Derniers 10 matchs
WLOTWOTL SOWSOL
280000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2082813.46%2976578.11%1
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
912869840369258568
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
1278252750.57%1149244447.01%560119147.02%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
173011801677533949480


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 - 2023-03-281177Rocket-Phantoms-
175 - 2023-03-301193Phantoms-Senators-
177 - 2023-04-011206Crunch-Phantoms-
178 - 2023-04-021221Phantoms-Manchots-
180 - 2023-04-041234Phantoms-Chiefs-
182 - 2023-04-061252Phantoms-Stars-
184 - 2023-04-081268Phantoms-Sound Tigers-
185 - 2023-04-091273Bruins-Phantoms-
187 - 2023-04-111287Monsters-Phantoms-
189 - 2023-04-131306Phantoms-Baby Hawks-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance70,02635,301
Assistance PCT94.63%95.41%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
4 2847 - 94.89% 80,552$2,980,425$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,320,260$ 1,514,105$ 1,514,105$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
7,969$ 1,318,005$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
322,208$ 19 7,969$ 151,411$




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