Connexion

Phantoms
GP: 58 | W: 31 | L: 26 | OTL: 1 | P: 63
GF: 230 | GA: 218 | PP%: 28.92% | PK%: 74.34%
DG: | Morale : 40 | Moyenne d’équipe : 60
Prochains matchs #942 vs Wild
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Centre de jeu
Rocket
37-20-1, 75pts
2
FINAL
6 Phantoms
31-26-1, 63pts
Team Stats
L2StreakL1
15-13-1Home Record17-11-1
22-7-0Away Record14-15-0
8-2-0Last 10 Games6-4-0
4.29Buts par match 3.97
3.47Buts contre par match 3.76
28.89%Pourcentage en avantage numérique28.92%
71.60%Pourcentage en désavantage numérique74.34%
Phantoms
31-26-1, 63pts
3
FINAL
4 Monsters
31-25-3, 65pts
Team Stats
L1StreakW3
17-11-1Home Record15-12-2
14-15-0Away Record16-13-1
6-4-0Last 10 Games7-3-0
3.97Buts par match 5.25
3.76Buts contre par match 5.27
28.92%Pourcentage en avantage numérique33.93%
74.34%Pourcentage en désavantage numérique61.19%
Wild
34-18-8, 76pts
2022-10-08
Phantoms
31-26-1, 63pts
Statistiques d’équipe
SOL1SéquenceL1
16-9-4Fiche domicile17-11-1
18-9-4Fiche visiteur14-15-0
4-3-310 derniers matchs6-4-0
5.12Buts par match 3.97
4.32Buts contre par match 3.97
35.26%Pourcentage en avantage numérique28.92%
72.67%Pourcentage en désavantage numérique74.34%
Phantoms
31-26-1, 63pts
2022-10-11
Penguins
20-38-2, 42pts
Statistiques d’équipe
L1SéquenceW3
17-11-1Fiche domicile10-19-0
14-15-0Fiche visiteur10-19-2
6-4-010 derniers matchs5-5-0
3.97Buts par match 3.98
3.76Buts contre par match 3.98
28.92%Pourcentage en avantage numérique28.57%
74.34%Pourcentage en désavantage numérique72.33%
Senators
28-26-2, 58pts
2022-10-13
Phantoms
31-26-1, 63pts
Statistiques d’équipe
W1SéquenceL1
12-16-2Fiche domicile17-11-1
16-10-0Fiche visiteur14-15-0
5-5-010 derniers matchs6-4-0
4.18Buts par match 3.97
4.11Buts contre par match 3.97
26.99%Pourcentage en avantage numérique28.92%
71.18%Pourcentage en désavantage numérique74.34%
Meneurs d'équipe
Linus SandinButs
Linus Sandin
26
Linus HogbergPasses
Linus Hogberg
46
Nick SeelerPoints
Nick Seeler
62
Plus/Moins
Jackson Cates
20
Felix SandstromVictoires
Felix Sandstrom
19
Pourcentage d’arrêts
Samuel Ersson
0.908

Statistiques d’équipe
Buts pour
230
3.97 GFG
Tirs pour
1902
32.79 Avg
Pourcentage en avantage numérique
28.9%
48 GF
Début de zone offensive
38.0%
Buts contre
218
3.76 GAA
Tirs contre
2085
35.95 Avg
Pourcentage en désavantage numérique
74.3%
39 GA
Début de la zone défensive
41.1%
Informations de l'équipe

Directeur général
EntraîneurIan Laperriere
DivisionDivision 2
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro20
Équipe Mineure22
Limite contact 42 / 20
Espoirs0


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
1Tanner LaczynskiX98.006937946276876660746258626166684640620241925,000$
2David KaseX99.0069468769757580605060585961656678406202510$
3Linus SandinX100.006338875980776864566260636267695440620261750,000$
4Jackson CatesX97.006336856373757462736163596266685340620241925,000$
5Matthew StromeX99.008040875689739155535655585464665840600231775,000$
6Maksim SushkoX100.006638936077738059525658545964666040600231775,000$
7Tyson Foerster (R)X98.006053837479607657705460557054567940600203894,167$
8Zayde Wisdom (R)X100.006350746577698261696060606954567040600193820,000$
9Zack MacEwenX100.008782655484748757705556545967684140590251825,000$
10Nick SeelerX100.007645786081827458306559694770724740630281750,000$
11Linus HogbergX99.0062378065748279653069616653656754406302310$
12Kevin ConnautonX99.008038835981867560306357635075734140620321825,000$
13Adam ClendeningX100.006441736073769561306759584871736040620291750,000$
14Wyatte WylieX100.006338875973698755305654544564665640580222820,833$
15Keaton ThompsonX100.0062416956716668563055535545687053405702610$
16Cooper ZechX100.006136885463687951305651504565675240560232837,500$
17Mason MillmanX100.006239805473626354305350524562646140550203818,333$
Rayé
MOYENNE D’ÉQUIPE99.35684382617674785947595758556567574060
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
1Felix Sandstrom96.017477767973737574737473667463406202510$
2Kirill Ustimenko97.006668678165646665646665636964405802310$
Rayé
1Samuel Ersson100.006467667663626463626463656955405702210$
MOYENNE D’ÉQUIPE97.6768717079676668676668676571614059
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ian Laperriere63636371736878CAN4821,000,000$


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Nick SeelerPhantoms (PHI)D57184462936010876116396915.52%96112019.66101222551230110101100.00%000001.1100000142
2Linus HogbergPhantoms (PHI)D5814466012006582130409510.77%89130222.455813611380002118210.00%000000.9200000132
3Adam ClendeningPhantoms (PHI)D5815395411120485892375316.30%74114819.8071421491280002108210.00%000000.9400000114
4Zayde WisdomPhantoms (PHI)C58262652316085992025412912.87%1697216.782571347000003216.7872100021.0722000331
5David KasePhantoms (PHI)RW50193150-919563110200441609.50%12106721.35279331290000411221.3511300010.9411100240
6Linus SandinPhantoms (PHI)RW48262450012044561712911015.20%1480616.806101629930001233016.805800001.2412000541
7Maksim SushkoPhantoms (PHI)RW5817264311602450132338312.88%1684714.62000011013194014.628000001.0100000204
8Jackson CatesPhantoms (PHI)C461924432080241181674211811.38%488019.1424620660002533019.14110600000.9802000151
9Matthew StromePhantoms (PHI)LW541621374300163681404412411.43%14110620.48167211230001132120.486500010.6700000501
10Tanner LaczynskiPhantoms (PHI)C391025353806184133331097.52%682821.254101425840001862021.2585500000.8401000124
11Kevin ConnautonPhantoms (PHI)D5782533-6340117689132558.79%81107018.7942652102000292110.00%000100.6200000210
12Zack MacEwenPhantoms (PHI)C57111526768101452658223918.97%1072212.68011030000181012.688500100.7200101212
13Tyson FoersterPhantoms (PHI)C40101121-4155503885186411.76%657314.34156648000011114.3410000000.7300100002
14Keaton ThompsonPhantoms (PHI)D5511617-42807335255244.00%4258010.5500002000026000.00%000000.5900000001
15Wyatte WyliePhantoms (PHI)D5811415-814051372712203.70%4266411.460111400005000.00%000000.4500000010
16Yegor ZamulaFlyersD164913031533143162312.90%1932520.351231323000027100.00%000000.8000010001
17Isaac RatcliffeFlyersLW8671332038172992420.69%319224.101455250000171024.104700011.3500000122
18Ryan FitzgeraldFlyersC/RW8358-14018292172014.29%317021.312025210000130121.3121200000.9401000001
19Cooper ZechPhantoms (PHI)D580551602415184120.00%284056.9800012000010000.00%200000.2500000000
20Mason MillmanPhantoms (PHI)D58145-32026973614.29%222884.970001200002000.00%000000.3500000000
Statistiques d’équipe totales ou en moyenne9412254176423837125126010891875513133712.00%5971507516.024891139390117411214779281052.82%344400250.8549311273129
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
1Felix SandstromPhantoms (PHI)3119910.9053.221772009510000000.6676310300
2Samuel ErssonPhantoms (PHI)106400.9083.3751600293160000.00%0100102
3Kirill UstimenkoPhantoms (PHI)145700.8983.8272200464520001.00041242001
Statistiques d’équipe totales ou en moyenne55302010.9043.3930120017017680000.800105342403


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 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
Adam ClendeningPhantoms (PHI)D291992-10-26No194 Lbs6 ft0NoNoNo1Pro & Farm750,000$225,806$0$0$NoLien / Lien NHL
Cooper ZechPhantoms (PHI)D231998-12-18No161 Lbs5 ft9NoNoNo2Pro & Farm837,500$252,151$0$0$No837,500$Lien / Lien NHL
David KasePhantoms (PHI)RW251997-01-28No169 Lbs5 ft11NoNoNo1Pro & Farm0$0$NoLien / Lien NHL
Felix SandstromPhantoms (PHI)G251997-01-12No191 Lbs6 ft2NoNoNo1Pro & Farm0$0$NoLien / Lien NHL
Jackson CatesPhantoms (PHI)C241997-09-26No190 Lbs6 ft0NoNoNo1Pro & Farm925,000$278,495$0$0$NoLien
Keaton ThompsonPhantoms (PHI)D261995-09-14No182 Lbs6 ft0NoNoNo1Pro & Farm0$0$NoLien / Lien NHL
Kevin ConnautonPhantoms (PHI)D321990-02-23No205 Lbs6 ft2NoNoNo1Pro & Farm825,000$248,387$0$0$NoLien / Lien NHL
Kirill UstimenkoPhantoms (PHI)G231999-01-29No187 Lbs6 ft3NoNoNo1Pro & Farm0$0$NoLien
Linus HogbergPhantoms (PHI)D231998-09-04No176 Lbs6 ft1NoNoNo1Pro & Farm0$0$NoLien / Lien NHL
Linus SandinPhantoms (PHI)RW261996-05-19No209 Lbs6 ft1NoNoNo1Pro & Farm750,000$225,806$0$0$NoLien / Lien NHL
Maksim SushkoPhantoms (PHI)RW231999-02-10No206 Lbs6 ft0NoNoNo1Pro & Farm775,000$233,333$0$0$NoLien / Lien NHL
Mason MillmanPhantoms (PHI)D202001-07-18No175 Lbs6 ft1NoNoNo3Pro & Farm818,333$246,380$0$0$No818,333$818,333$Lien / Lien NHL
Matthew StromePhantoms (PHI)LW231999-01-06No206 Lbs6 ft4NoNoNo1Pro & Farm775,000$233,333$0$0$NoLien / Lien NHL
Nick SeelerPhantoms (PHI)D281993-06-03No201 Lbs6 ft2NoNoNo1Pro & Farm750,000$225,806$0$0$NoLien / Lien NHL
Samuel ErssonPhantoms (PHI)G221999-10-20No176 Lbs6 ft2NoNoNo1Pro & Farm0$0$NoLien
Tanner LaczynskiPhantoms (PHI)C241997-06-01No190 Lbs6 ft1NoNoNo1Pro & Farm925,000$278,495$0$0$NoLien / Lien NHL
Tyson FoersterPhantoms (PHI)C202002-01-18Yes194 Lbs6 ft2NoNoNo3Pro & Farm894,167$269,212$0$0$No894,167$894,167$Lien / Lien NHL
Wyatte WyliePhantoms (PHI)D221999-11-02No190 Lbs6 ft0NoNoNo2Pro & Farm820,833$247,133$0$0$No820,833$Lien / Lien NHL
Zack MacEwenPhantoms (PHI)C251996-07-08No205 Lbs6 ft3NoNoNo1Pro & Farm825,000$248,387$0$0$NoLien / Lien NHL
Zayde WisdomPhantoms (PHI)C192002-07-07Yes201 Lbs5 ft10NoNoNo3Pro & Farm820,000$246,882$0$0$No820,000$820,000$Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2024.10190 Lbs6 ft11.40574,542$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matthew StromeDavid Kase40122
2Tyson FoersterTanner Laczynski30122
3Zack MacEwenZayde WisdomMaksim Sushko20122
4Tyson FoersterTanner Laczynski10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Linus HogbergKevin Connauton40122
2Nick SeelerAdam Clendening30122
3Wyatte WylieKeaton Thompson20122
4Cooper ZechMason Millman10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matthew StromeDavid Kase60122
2Tyson FoersterTanner Laczynski40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Linus HogbergKevin Connauton60122
2Nick SeelerAdam Clendening40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Tanner Laczynski60122
2David Kase40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Linus HogbergKevin Connauton60122
2Nick SeelerAdam Clendening40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
160122Linus HogbergKevin Connauton60122
2Tanner Laczynski40122Nick SeelerAdam Clendening40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Tanner Laczynski60122
2David Kase40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Linus HogbergKevin Connauton60122
2Nick SeelerAdam Clendening40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matthew StromeDavid KaseLinus HogbergKevin Connauton
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matthew StromeDavid KaseLinus HogbergKevin Connauton
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Zayde Wisdom, Maksim Sushko, Zack MacEwenZayde Wisdom, Maksim SushkoZack MacEwen
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Wyatte Wylie, Keaton Thompson, Cooper ZechWyatte WylieKeaton Thompson, Cooper Zech
Tirs de pénalité
, Tanner Laczynski, David Kase, , Zayde Wisdom
Gardien
#1 : , #2 : Kirill Ustimenko
Lignes d’attaque personnalisées en prolongation
, Tanner Laczynski, David Kase, , Zayde Wisdom, Maksim Sushko, Maksim Sushko, Matthew Strome, Tyson Foerster, Zack MacEwen,
Lignes de défense personnalisées en prolongation
Linus Hogberg, Kevin Connauton, Nick Seeler, Adam Clendening, Wyatte Wylie


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
1Admirals220000001138110000004221100000071641.00011193000918648778608622653294791148500.00%30100.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
2American1010000023-1000000000001010000023-100.000246009186487296086226532942126135240.00%30100.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
3Barrucada1010000023-1000000000001010000023-100.00024600918648729608622653293512433300.00%2150.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
4Bears412001001015-5210001006602020000049-530.375102030009186487100608622653291534027969444.44%11281.82%0880183348.01%858198243.29%468100346.66%13799721388398727366
5Bruins2110000089-1110000004311010000046-220.50081422009186487646086226532978258535360.00%2150.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
6Canucks20200000410-620200000410-60000000000000.00048120091864875860862265329722121517114.29%7185.71%0880183348.01%858198243.29%468100346.66%13799721388398727366
7Checkers21100000710-31010000016-51100000064220.500713200091864875360862265329843114436233.33%6350.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
8Comets413000001122-1120200000413-92110000079-220.2501119300091864871136086226532915336227010330.00%10460.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
9Crunch10000010431100000104310000000000021.000461000918648747608622653293911618300.00%20100.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
10Eagles210010001165100010004311100000073441.0001119300091864877060862265329601885310330.00%30100.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
11Griffins11000000945000000000001100000094521.00091726009186487446086226532940130203133.33%000.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
12Gulls21100000910-1110000006511010000035-220.500917260091864874560862265329722112467571.43%6350.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
13Heat21100000770110000003121010000046-220.500713200091864875560862265329841722444125.00%9188.89%0880183348.01%858198243.29%468100346.66%13799721388398727366
14IceHogs11000000431000000000001100000043121.0004711009186487406086226532931121018200.00%4175.00%1880183348.01%858198243.29%468100346.66%13799721388398727366
15Islanders30300000922-1320200000717-101010000025-300.00091726009186487122608622653291142216708337.50%8625.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
16Marlies21100000862110000005141010000035-220.50081321009186487706086226532964311047400.00%40100.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
17Monsters3210000012111110000006512110000066040.66712243600918648792608622653291312616665120.00%8275.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
18Moose11000000615110000006150000000000021.00061016009186487396086226532927742511100.00%20100.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
19Penguins440000002391422000000954220000001441081.0002342650091864871626086226532913247189510440.00%9277.78%0880183348.01%858198243.29%468100346.66%13799721388398727366
20Reign1010000035-2000000000001010000035-200.00036900918648747608622653292480156233.33%000.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
21Roadrunners2110000012931010000048-41100000081720.50012233500918648765608622653297830639200.00%3166.67%0880183348.01%858198243.29%468100346.66%13799721388398727366
22Rocket11000000624110000006240000000000021.00061117009186487316086226532932101215100.00%6266.67%0880183348.01%858198243.29%468100346.66%13799721388398727366
23Senators11000000514000000000001100000051421.0005101500918648741608622653292888135240.00%30100.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
24Silver Knights201000108801010000012-11000001076120.500813210091864877360862265329541312417342.86%6183.33%0880183348.01%858198243.29%468100346.66%13799721388398727366
25Stars2010100058-31010000026-41000100032120.50059140091864876160862265329762518567228.57%8187.50%0880183348.01%858198243.29%468100346.66%13799721388398727366
26Thunderbirds2110000036-3000000000002110000036-320.500369009186487416086226532958221040800.00%4250.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
27Wild1010000035-21010000035-20000000000000.000369009186487356086226532951238134125.00%4175.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
28Wolf Pack412010001314-12100100063320200000711-440.5001324370091864871106086226532917236308713323.08%14378.57%0880183348.01%858198243.29%468100346.66%13799721388398727366
29Wolves220000001531222000000153120000000000041.0001525400091864878860862265329541234476116.67%5180.00%0880183348.01%858198243.29%468100346.66%13799721388398727366
Total58262603120230218122914110211011011002912150101012010812630.543230419649009186487190260862265329208559837312751664828.92%1523974.34%1880183348.01%858198243.29%468100346.66%13799721388398727366
_Since Last GM Reset58262603120230218122914110211011011002912150101012010812630.543230419649009186487190260862265329208559837312751664828.92%1523974.34%1880183348.01%858198243.29%468100346.66%13799721388398727366
_Vs Conference351715011101421348181050111073676177100000069672390.5571422594010091864871166608622653291316360227753932931.18%912671.43%0880183348.01%858198243.29%468100346.66%13799721388398727366
_Vs Division241111011009396-3137401100535211147000004044-4250.5219317126400918648778760862265329909219163531611931.15%652069.23%0880183348.01%858198243.29%468100346.66%13799721388398727366

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
5863L123041964919022085598373127500
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
5826263120230218
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2914112110110110
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2912151010120108
Derniers 10 matchs
WLOTWOTL SOWSOL
640000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1664828.92%1523974.34%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
608622653299186487
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
880183348.01%858198243.29%468100346.66%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
13799721388398727366


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
1 - 2022-05-317Phantoms4Wolf Pack5ALSommaire du match
4 - 2022-06-0323Phantoms2Bears3ALSommaire du match
5 - 2022-06-0432Comets8Phantoms3BLSommaire du match
7 - 2022-06-0645Phantoms3Thunderbirds2AWSommaire du match
10 - 2022-06-0961Bears2Phantoms3BWSommaire du match
12 - 2022-06-1177Phantoms6Penguins2AWSommaire du match
15 - 2022-06-1496Penguins3Phantoms6BWSommaire du match
16 - 2022-06-15107Phantoms3Monsters2AWSommaire du match
18 - 2022-06-17122Canucks6Phantoms2BLSommaire du match
21 - 2022-06-20137Phantoms2Islanders5ALSommaire du match
23 - 2022-06-22154Wolf Pack2Phantoms4BWSommaire du match
25 - 2022-06-24169Phantoms2Comets1AWSommaire du match
27 - 2022-06-26182Phantoms8Penguins2AWSommaire du match
28 - 2022-06-27191Monsters5Phantoms6BWSommaire du match
32 - 2022-07-01219Wolves2Phantoms8BWSommaire du match
36 - 2022-07-05245Islanders7Phantoms4BLSommaire du match
37 - 2022-07-06253Phantoms3Wolf Pack6ALSommaire du match
40 - 2022-07-09273Phantoms2American3ALSommaire du match
41 - 2022-07-10284Bears4Phantoms3BLXSommaire du match
44 - 2022-07-13306Wolves1Phantoms7BWSommaire du match
46 - 2022-07-15322Phantoms4Bruins6ALSommaire du match
48 - 2022-07-17335Phantoms3Gulls5ALSommaire du match
50 - 2022-07-19349Silver Knights2Phantoms1BLSommaire du match
53 - 2022-07-22373Comets5Phantoms1BLSommaire du match
55 - 2022-07-24393Moose1Phantoms6BWSommaire du match
56 - 2022-07-25402Phantoms8Roadrunners1AWSommaire du match
59 - 2022-07-28424Phantoms7Silver Knights6AWXXSommaire du match
61 - 2022-07-30435Crunch3Phantoms4BWXXSommaire du match
63 - 2022-08-01453Phantoms2Barrucada3ALSommaire du match
65 - 2022-08-03463Phantoms9Griffins4AWSommaire du match
66 - 2022-08-04476Wolf Pack1Phantoms2BWXSommaire du match
69 - 2022-08-07491Phantoms3Stars2AWXSommaire du match
71 - 2022-08-09504Stars6Phantoms2BLSommaire du match
75 - 2022-08-13534Islanders10Phantoms3BLSommaire du match
79 - 2022-08-17556Phantoms5Comets8ALSommaire du match
81 - 2022-08-19566Heat1Phantoms3BWSommaire du match
83 - 2022-08-21583Phantoms4IceHogs3AWSommaire du match
84 - 2022-08-22595Penguins2Phantoms3BWSommaire du match
87 - 2022-08-25615Phantoms0Thunderbirds4ALSommaire du match
88 - 2022-08-26625Admirals2Phantoms4BWSommaire du match
91 - 2022-08-29638Phantoms6Checkers4AWSommaire du match
93 - 2022-08-31656Eagles3Phantoms4BWXSommaire du match
95 - 2022-09-02671Phantoms4Heat6ALSommaire du match
98 - 2022-09-05688Phantoms2Bears6ALSommaire du match
99 - 2022-09-06700Wild5Phantoms3BLSommaire du match
101 - 2022-09-08719Bruins3Phantoms4BWSommaire du match
104 - 2022-09-11738Phantoms3Marlies5ALSommaire du match
106 - 2022-09-13752Roadrunners8Phantoms4BLSommaire du match
108 - 2022-09-15768Phantoms5Senators1AWSommaire du match
110 - 2022-09-17782Marlies1Phantoms5BWSommaire du match
114 - 2022-09-21812Checkers6Phantoms1BLSommaire du match
117 - 2022-09-24839Phantoms3Reign5ALSommaire du match
118 - 2022-09-25847Canucks4Phantoms2BLSommaire du match
121 - 2022-09-28869Gulls5Phantoms6BWSommaire du match
123 - 2022-09-30886Phantoms7Admirals1AWSommaire du match
125 - 2022-10-02894Phantoms7Eagles3AWSommaire du match
127 - 2022-10-04909Rocket2Phantoms6BWSommaire du match
130 - 2022-10-07926Phantoms3Monsters4ALSommaire du match
131 - 2022-10-08942Wild-Phantoms-
134 - 2022-10-11960Phantoms-Penguins-
136 - 2022-10-13973Senators-Phantoms-
137 - 2022-10-14985Phantoms-Canucks-
140 - 2022-10-171003Monsters-Phantoms-
142 - 2022-10-191014Phantoms-Chekers-
144 - 2022-10-211028Phantoms-Wolves-
146 - 2022-10-231044Chekers-Phantoms-
149 - 2022-10-261070Thunderbirds-Phantoms-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
151 - 2022-10-281082Phantoms-Wolf Pack-
153 - 2022-10-301097Phantoms-Condors-
154 - 2022-10-311106Barrucada-Phantoms-
158 - 2022-11-041133Bruins-Phantoms-
160 - 2022-11-061147Phantoms-Moose-
162 - 2022-11-081164Phantoms-Islanders-
164 - 2022-11-101173Griffins-Phantoms-
167 - 2022-11-131195IceHogs-Phantoms-
168 - 2022-11-141207Phantoms-Wild-
172 - 2022-11-181229American-Phantoms-
174 - 2022-11-201243Phantoms-Crunch-
176 - 2022-11-221260Reign-Phantoms-
179 - 2022-11-251279Phantoms-Rocket-
180 - 2022-11-261283Phantoms-Wolves-
183 - 2022-11-291300Condors-Phantoms-



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

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
12 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,550,109$ 1,149,083$ 1,149,083$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
6,178$ 851,229$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 56 11,554$ 647,024$




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