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Phantoms
GP: 80 | W: 41 | L: 37 | OTL: 2 | P: 84
GF: 322 | GA: 321 | PP%: 22.57% | PK%: 75.15%
DG: Simon DeChamplain | Morale : 46 | Moyenne d’équipe : 64
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Centre de jeu
Marlies
34-38-8, 76pts
5
FINAL
3 Phantoms
41-37-2, 84pts
Team Stats
L1SéquenceW1
18-19-3Fiche domicile19-19-2
16-19-5Fiche domicile22-18-0
7-2-1Derniers 10 matchs6-4-0
3.65Buts par match 4.03
4.05Buts contre par match 4.01
22.30%Pourcentage en avantage numérique22.57%
80.63%Pourcentage en désavantage numérique75.15%
Marlies
34-38-8, 76pts
3
FINAL
6 Phantoms
41-37-2, 84pts
Team Stats
L1SéquenceW1
18-19-3Fiche domicile19-19-2
16-19-5Fiche domicile22-18-0
7-2-1Derniers 10 matchs6-4-0
3.65Buts par match 4.03
4.05Buts contre par match 4.01
22.30%Pourcentage en avantage numérique22.57%
80.63%Pourcentage en désavantage numérique75.15%
Meneurs d'équipe
Buts
Rem Pitlick
44
Passes
Morgan Klimchuk
70
Points
Morgan Klimchuk
113
Plus/Moins
Nick Sorensen
22
Victoires
Anton Forsberg
37
Pourcentage d’arrêts
Zachary Fucale
0.886

Statistiques d’équipe
Buts pour
322
4.03 GFG
Tirs pour
2525
31.56 Avg
Pourcentage en avantage numérique
22.6%
72 GF
Début de zone offensive
35.3%
Buts contre
321
4.01 GAA
Tirs contre
2680
33.50 Avg
Pourcentage en désavantage numérique
75.1%%
83 GA
Début de la zone défensive
38.6%
Informations de l'équipe

Directeur généralSimon DeChamplain
EntraîneurKevin Dineen
DivisionFritz-Kraatz
ConférenceRobert-Lebel
CapitaineDave Bolland
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,791
Billets de saison300


Informations de la formation

Équipe Pro31
Équipe Mineure18
Limite contact 49 / 250
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
1Sven AndrighettoX100.008135827280767369766677627463534020710251700,000$
2Joe Snively (R)X100.006833828666776777737373538347486055700221500,000$
3Cristoval Nieves (R)X100.007226787768737775758069577250523962700242900,000$
4Lucas Wallmarkk (R)X100.007438757168757076747870686847454866700222800,000$
5Morgan Klimchuk (R)X100.007032747472777571667473737852464166700231650,000$
6David Kampf (R)X100.006143846572726974687076596846494666680233750,000$
7Erik NystromX100.007323776776737272656174677652503253680251800,000$
8Rem Pitlick (R)X100.006429718268766582736865627645466062680212900,000$
9Nick Sorensen (R)X100.006233797373706967655974557549514166660241525,000$
10A.J. Greer (R)X100.006243646968647362626263565547464159610223300,000$
11Brett Murray (R)X100.007741647078556661465764554442425754600204500,000$
12Oliver Wahlstrom (R)X100.005937754673696564666271416540408459600182500,000$
13Blake Heinrich (R)X100.007335737476776562527571785861474054710231500,000$
14Rinat Valiev (R)X100.007334817469696574576762726453484745690231500,000$
15Mikko Lehtonen (R)X100.007141776454687274536971616250524148660242750,000$
16Riley Stillman (R)X100.006842636262576353375953584642425666590204500,000$
17Ty Smith (R)X100.004826676553496073327148544440407566560182500,000$
18Victor Berglund (R)X100.006229675962544945315431683041416338560191500,000$
Rayé
1Laurent Dauphin (R)X100.007442806470657171637466526845453835650231500,000$
2Anthony Angello (R)X100.005139816665756757676664595644444035620221450,000$
3Cooper Marody (R)X100.004537716453606263747459415046444331590223300,000$
4Josiah Slavin (R)X100.005837735263715962686170385145455753590202500,000$
5Benoit-Olivier Groulx (R)X100.005942745765566258625860525740406531570182500,000$
6Fabian Zetterlund (R)X100.004736715665655855564869436141416135560191500,000$
7David Gustafsson (R)X100.005234705947535655716553415040407125540182500,000$
8Matt Kiersted (R)X80.206646656667585758465847625343435446600204500,000$
MOYENNE D’ÉQUIPE99.24643674676767666661666457614745525064
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
1Anton Forsberg100.00757574777079767373767573733467740261975,000$
2Zachary Fucale100.00697862697175747679756150484255720231500,000$
Rayé
1Kevin Lankinen100.00686766686671627167645642426019650233900,000$
2Zachary Sawchenko100.00635469555265674747737545475420580211500,000$
3Jacob Ingham (R)100.00694357606950425657505940406120550182500,000$
MOYENNE D’ÉQUIPE100.0069636666666864656568655050503665
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Kevin Dineen73656679327257Can503500,000$


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
1Morgan KlimchukPhantoms (Phi)LW80437011365401251402869518815.03%41191323.92919284725922462506243.06%3537136111.1803000643
2Rem PitlickPhantoms (Phi)RW80444892-3835107823079215614.33%42134616.8314152949225000145247.37%956827101.3700000386
3Joe SnivelyPhantoms (Phi)C71335487123551201442757417012.00%29146320.614172122203213121666250.13%15486124011.1933100725
4Lucas WallmarkkPhantoms (Phi)C80384684144401191482386813415.97%46143217.911011212615612351713151.04%14973932101.1704000752
5Cristoval NievesPhantoms (Phi)C77234164-142001281131906310512.11%42122815.9529111210713481151245.47%8054114001.0401000102
6Rinat ValievPhantoms (Phi)D71134760193958714213855569.42%113193527.2681119252551233255100%03575000.6200001032
7Erik NystromPhantoms (Phi)LW701833511222013091140588712.86%24113816.265712181810002274052.08%482819000.9000000333
8Nick SorensenPhantoms (Phi)RW80212344222808173157508113.38%22110013.752245104000061045.00%404819000.8000000052
9Sven AndrighettoPhantoms (Phi)RW4921214201006253110337319.09%2889018.188614181441126695041.90%2102911010.9400000131
10Mikko LehtonenPhantoms (Phi)D78102434-338109811612046458.33%92181323.2554992140113219210%03150100.3700002202
11David KampfPhantoms (Phi)C80171431-2605268123368613.82%3183610.46000010000052145.87%2182525000.7411000203
12A.J. GreerPhantoms (Phi)LW73161329-2360964876274821.05%2689112.211341342028860334.48%291219000.6500000111
13Cal FooteFlyersD38124259701091715927231.69%67104227.4405581380334127000%01334000.4800110011
14Oliver WahlstromPhantoms (Phi)RW7881018-14140473854152714.81%127629.7800004000001040.91%22710000.4700000001
15Riley StillmanPhantoms (Phi)D8021517156071815415223.70%76133116.6405531080220109000%0737000.2600000020
16Ty SmithPhantoms (Phi)D801141514202362391982.56%54105513.19101121011070000%0728000.2800000100
17Matt KierstedPhantoms (Phi)D7321315-1252071943617215.56%89128217.5710151570110149100%0850000.2300000001
18Brett MurrayPhantoms (Phi)LW745914-234077385117449.80%166058.1800001000060038.46%13116100.4600000000
19Victor BerglundPhantoms (Phi)D562810-524034622011610.00%6280514.38202466000071000%0335000.2500000010
20Anthony AngelloPhantoms (Phi)C551345004742225.00%21292.36000091013230052.94%1700000.6200000000
21Laurent DauphinPhantoms (Phi)C55033-4602211348130%52103.8200018011020043.10%5822000.2900000000
22Josiah SlavinPhantoms (Phi)LW70022-1020219105140%32623.75000010001360040.00%2022000.1500000000
23Blake HeinrichPhantoms (Phi)D1000200133200%32929.030000600003000%00000000000000
24Benoit-Olivier GroulxPhantoms (Phi)C52000000010000%020.050000000000000%00000000000000
25Cooper MarodyPhantoms (Phi)C52000000001130%0350.68000000001280035.00%200000000000000
26Fabian ZetterlundPhantoms (Phi)LW55000000000000%050.090000000001000%00000000000000
Statistiques d’équipe totales ou en moyenne17083195358543271535166716952525836141212.63%9252354813.79721141862542422112031632009381448.21%4993548555530.73412213343835
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
1Anton ForsbergPhantoms (Phi)73372820.8813.9939404026222021078440.90911737411
2Zachary FucalePhantoms (Phi)224900.8863.6788200544732250100767100
Statistiques d’équipe totales ou en moyenne95413720.8823.934822403162675130345118074511


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Non Activé 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 10Non-échange Année 2Non-échange Année 3Non-échange Année 4Non-échange Année 5Non-échange Année 6Non-échange Année 7Non-échange Année 8Non-échange Année 9Non-échange Année 10Lien
A.J. GreerPhantoms (Phi)LW221996-01-01Yes210 Lbs6 ft3NoNoN/ANoNo3FalseFalsePro & Farm300,000$1,493$0$0$No350,000$400,000$-------NoNo-------
Anthony AngelloPhantoms (Phi)C221996-01-01Yes210 Lbs6 ft5NoNoN/ANoNo1FalseFalsePro & Farm450,000$2,239$0$0$No------------------
Anton ForsbergPhantoms (Phi)G261992-01-01No191 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm975,000$4,851$0$0$No------------------
Benoit-Olivier GroulxPhantoms (Phi)C182000-01-01Yes200 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Blake HeinrichPhantoms (Phi)D231995-01-01Yes185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Brett MurrayPhantoms (Phi)LW201998-01-01Yes216 Lbs6 ft4NoNoN/ANoNo4FalseFalsePro & Farm500,000$2,488$0$0$No500,000$500,000$500,000$------NoNoNo------
Cooper MarodyPhantoms (Phi)C221996-01-01Yes184 Lbs6 ft0NoNoN/ANoNo3FalseFalsePro & Farm300,000$1,493$0$0$No350,000$400,000$-------NoNo-------
Cristoval NievesPhantoms (Phi)C241994-01-01Yes192 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm900,000$4,478$0$0$No900,000$--------No--------
David GustafssonPhantoms (Phi)LW182000-01-01Yes196 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
David KampfPhantoms (Phi)C231995-01-01Yes188 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm750,000$3,731$0$0$No800,000$900,000$-------NoNo-------
Erik NystromPhantoms (Phi)LW251993-01-01No176 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm800,000$3,980$0$0$No------------------
Fabian ZetterlundPhantoms (Phi)LW191999-01-01Yes220 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Jacob InghamPhantoms (Phi)G182000-01-01Yes205 Lbs6 ft5NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Joe SnivelyPhantoms (Phi)C221996-01-01Yes176 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Josiah SlavinPhantoms (Phi)LW201998-01-01Yes189 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Kevin LankinenPhantoms (Phi)G231995-01-01No185 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm900,000$4,478$0$0$No900,000$900,000$-------NoNo-------
Laurent DauphinPhantoms (Phi)C231995-01-01Yes185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Lucas WallmarkkPhantoms (Phi)C221996-01-01Yes178 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm800,000$3,980$0$0$No900,000$--------No--------
Matt Kiersted (sur la masse salariale)Phantoms (Phi)D201998-01-01Yes184 Lbs5 ft11NoNoN/ANoNo4FalseFalsePro & Farm500,000$2,488$0$0$Yes500,000$500,000$500,000$------NoNoNo------
Mikko LehtonenPhantoms (Phi)D241994-01-01Yes196 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm750,000$3,731$0$0$No750,000$--------No--------
Morgan KlimchukPhantoms (Phi)LW231995-01-01Yes185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm650,000$3,234$0$0$No------------------
Nick SorensenPhantoms (Phi)RW241994-01-01Yes185 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm525,000$2,612$0$0$No------------------
Oliver WahlstromPhantoms (Phi)RW182000-01-01Yes204 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Rem PitlickPhantoms (Phi)RW211997-01-01Yes196 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm900,000$4,478$0$0$No900,000$--------No--------
Riley StillmanPhantoms (Phi)D201998-01-01Yes196 Lbs6 ft1NoNoN/ANoNo4FalseFalsePro & Farm500,000$2,488$0$0$No500,000$500,000$500,000$------NoNoNo------
Rinat ValievPhantoms (Phi)D231995-01-01Yes185 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Sven AndrighettoPhantoms (Phi)RW251993-01-01No185 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm700,000$3,483$0$0$No------------------
Ty SmithPhantoms (Phi)D182000-01-01Yes180 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Victor BerglundPhantoms (Phi)D191999-01-01Yes183 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Zachary FucalePhantoms (Phi)G231995-01-01No185 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Zachary SawchenkoPhantoms (Phi)G211997-01-01No185 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3121.58191 Lbs6 ft11.87587,097$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Morgan KlimchukJoe SnivelySven Andrighetto40122
2Erik NystromCristoval NievesRem Pitlick30122
3A.J. GreerLucas WallmarkkNick Sorensen20122
4Brett MurrayDavid KampfOliver Wahlstrom10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Blake HeinrichRinat Valiev40122
2Mikko LehtonenRiley Stillman30122
3Ty SmithVictor Berglund20122
4Blake HeinrichRinat Valiev10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Morgan KlimchukJoe SnivelySven Andrighetto60122
2Erik NystromCristoval NievesRem Pitlick40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Blake HeinrichRinat Valiev60122
2Mikko LehtonenRiley Stillman40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Sven AndrighettoMorgan Klimchuk60122
2Joe SnivelyCristoval Nieves40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Blake HeinrichRinat Valiev60122
2Mikko LehtonenRiley Stillman40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Sven Andrighetto60122Blake HeinrichRinat Valiev60122
2Morgan Klimchuk40122Mikko LehtonenRiley Stillman40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Sven AndrighettoMorgan Klimchuk60122
2Joe SnivelyCristoval Nieves40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Blake HeinrichRinat Valiev60122
2Mikko LehtonenRiley Stillman40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Morgan KlimchukJoe SnivelySven AndrighettoBlake HeinrichRinat Valiev
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Morgan KlimchukJoe SnivelySven AndrighettoBlake HeinrichRinat Valiev
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Lucas Wallmarkk, David Kampf, Nick SorensenLucas Wallmarkk, David KampfNick Sorensen
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ty Smith, Victor Berglund, Mikko LehtonenTy SmithVictor Berglund, Mikko Lehtonen
Tirs de pénalité
Sven Andrighetto, Morgan Klimchuk, Joe Snively, Cristoval Nieves, Lucas Wallmarkk
Gardien
#1 : Anton Forsberg, #2 : Zachary Fucale
Lignes d’attaque personnalisées en prolongation
Sven Andrighetto, Morgan Klimchuk, Joe Snively, Cristoval Nieves, Lucas Wallmarkk, Erik Nystrom, Erik Nystrom, Rem Pitlick, David Kampf, Nick Sorensen, A.J. Greer
Lignes de défense personnalisées en prolongation
Blake Heinrich, Rinat Valiev, Mikko Lehtonen, Riley Stillman, Ty Smith


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
1Admirals3110001014113211000007521000001076140.66714233700819314091028258348562010637205710110.00%10460.00%0888175350.66%856191844.63%663129551.20%162688317637631442711
2Americans32001000191271100000084421001000118361.000193453008193140910182583485620994516676116.67%8187.50%0888175350.66%856191844.63%663129551.20%162688317637631442711
3Barracuda30300000922-1320200000514-91010000048-400.000917260081931409858258348562010134435811327.27%19952.63%1888175350.66%856191844.63%663129551.20%162688317637631442711
4Bears20200000610-41010000024-21010000046-200.000691510819314096082583485620732120344125.00%11372.73%0888175350.66%856191844.63%663129551.20%162688317637631442711
5Canucks2110000079-21010000036-31100000043120.50071219008193140959825834856205919144013646.15%7357.14%0888175350.66%856191844.63%663129551.20%162688317637631442711
6Checkers211000007701010000024-21100000053220.5007111810819314095682583485620612912376233.33%60100.00%0888175350.66%856191844.63%663129551.20%162688317637631442711
7Comets20200000912-31010000046-21010000056-100.000915241081931409728258348562053231435100.00%7271.43%1888175350.66%856191844.63%663129551.20%162688317637631442711
8Condors421010001714321100000101002100100074360.75017324900819314091128258348562013346398814321.43%17382.35%1888175350.66%856191844.63%663129551.20%162688317637631442711
9Crunch41300000161511010000035-2312000001310320.25016294500819314091338258348562013938267913323.08%13192.31%3888175350.66%856191844.63%663129551.20%162688317637631442711
10Eagles211000006511010000012-11100000053220.50061016008193140965825834856206122123513430.77%6183.33%0888175350.66%856191844.63%663129551.20%162688317637631442711
11Griffins3210000012102110000007432110000056-140.667121931008193140910082583485620884424681119.09%12375.00%1888175350.66%856191844.63%663129551.20%162688317637631442711
12Icehogs31000110963210001005321000001043150.8339132200819314097782583485620773730649333.33%15286.67%0888175350.66%856191844.63%663129551.20%162688317637631442711
13Islander21100000761110000006151010000015-420.50071219008193140968825834856205919123711327.27%6183.33%1888175350.66%856191844.63%663129551.20%162688317637631442711
14Little Stars20200000912-31010000035-21010000067-100.0009122100819314097682583485620783122417114.29%11281.82%1888175350.66%856191844.63%663129551.20%162688317637631442711
15Marlies6320001026215311000101412232100000129380.667264672208193140919382583485620199618112330620.00%33972.73%0888175350.66%856191844.63%663129551.20%162688317637631442711
16Moose311001001618-22100010012931010000049-530.500162743008193140993825834856201092949611119.09%13284.62%1888175350.66%856191844.63%663129551.20%162688317637631442711
17Penguins312000001113-21010000045-12110000078-120.333111627008193140998825834856201054221618225.00%8275.00%0888175350.66%856191844.63%663129551.20%162688317637631442711
18Punishers220000001064110000003211100000074341.00010162600819314097382583485620662914438225.00%7185.71%0888175350.66%856191844.63%663129551.20%162688317637631442711
19Reign624000001725-831200000511-6312000001214-240.333172744008193140918082583485620199598013826415.38%411075.61%0888175350.66%856191844.63%663129551.20%162688317637631442711
20Rocket31101000131122100100011651010000025-340.6671323360081931409888258348562011434227612325.00%11281.82%1888175350.66%856191844.63%663129551.20%162688317637631442711
21Senators7420100036261042101000191273210000017143100.714365692008193140923182583485620251864414925832.00%22577.27%0888175350.66%856191844.63%663129551.20%162688317637631442711
22Silver Knights2110000058-3110000003211010000026-420.500591400819314095182583485620712214538112.50%6266.67%0888175350.66%856191844.63%663129551.20%162688317637631442711
23Thunderbirds2020000049-51010000024-21010000025-300.00047110081931409768258348562073321028800.00%5180.00%0888175350.66%856191844.63%663129551.20%162688317637631442711
24Wolfpack3300000013851100000032122000000106461.0001319320081931409958258348562010324227513430.77%11372.73%0888175350.66%856191844.63%663129551.20%162688317637631442711
25Wranglers623010002425-130201000812-4321000001613360.500244165008193140918182583485620203625812041921.95%291162.07%0888175350.66%856191844.63%663129551.20%162688317637631442711
Total803337052303223211401519032101501500401818020201721711840.5253225358575081931409252582583485620268092571916673197222.57%3348375.15%11888175350.66%856191844.63%663129551.20%162688317637631442711
_Since Last GM Reset803337052303223211401519032101501500401818020201721711840.5253225358575081931409252582583485620268092571916673197222.57%3348375.15%11888175350.66%856191844.63%663129551.20%162688317637631442711
_Vs Conference50211905230212201112711100321011110292310902020101992600.6002123585702081931409154382583485620167957450610692064320.87%2306173.48%5888175350.66%856191844.63%663129551.20%162688317637631442711
_Vs Division1879010106771-4925010102735-89540000040364180.50067114181208193140955482583485620601182219381971919.59%1033070.87%0888175350.66%856191844.63%663129551.20%162688317637631442711

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8084W132253585725252680925719166750
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8033375230322321
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4015193210150150
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4018182020172171
Derniers 10 matchs
WLOTWOTL SOWSOL
442000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3197222.57%3348375.15%11
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
8258348562081931409
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
888175350.66%856191844.63%663129551.20%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
162688317637631442711


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
26Phantoms8Crunch2WSommaire du match
419Senators3Phantoms2LSommaire du match
636Wranglers6Phantoms2LR1Sommaire du match
953Phantoms6Marlies3WSommaire du match
1161Marlies4Phantoms5WXXSommaire du match
1477Phantoms6Reign5WR1Sommaire du match
1791Senators4Phantoms5WXSommaire du match
18100Phantoms3Senators4LSommaire du match
21111Reign1Phantoms3WR1Sommaire du match
23124Phantoms9Senators7WSommaire du match
24127Phantoms8Wranglers5WR1Sommaire du match
27145Wranglers3Phantoms4WXSommaire du match
29159Phantoms5Wolfpack2WSommaire du match
31170Moose4Phantoms8WSommaire du match
36189Icehogs2Phantoms1LXSommaire du match
40213Admirals4Phantoms2LSommaire du match
42223Phantoms7Admirals6WXXSommaire du match
44231Phantoms2Rocket5LSommaire du match
46243Phantoms5Americans3WSommaire du match
48251Phantoms4Icehogs3WXXSommaire du match
50258Wranglers3Phantoms2LR1Sommaire du match
52268Phantoms1Islander5LSommaire du match
54278Islander1Phantoms6WSommaire du match
56288Phantoms2Thunderbirds5LSommaire du match
60306Eagles2Phantoms1LSommaire du match
62317Phantoms5Eagles3WSommaire du match
64331Crunch5Phantoms3LSommaire du match
66344Phantoms7Punishers4WSommaire du match
68356Senators1Phantoms4WSommaire du match
71375Phantoms6Americans5WXSommaire du match
73383Comets6Phantoms4LSommaire du match
76400Phantoms3Penguins5LSommaire du match
78408Canucks6Phantoms3LSommaire du match
81421Phantoms4Penguins3WSommaire du match
83432Phantoms2Silver Knights6LSommaire du match
84440Thunderbirds4Phantoms2LSommaire du match
87458Phantoms3Marlies5LSommaire du match
88465Moose5Phantoms4LXSommaire du match
91472Phantoms4Moose9LSommaire du match
94491Phantoms3Griffins2WSommaire du match
95494Checkers4Phantoms2LSommaire du match
98514Phantoms4Bears6LSommaire du match
99520Rocket2Phantoms6WSommaire du match
101536Phantoms3Reign5LR1Sommaire du match
104545Admirals1Phantoms5WSommaire du match
106557Phantoms3Marlies1WSommaire du match
108569Punishers2Phantoms3WSommaire du match
112588Phantoms6Little Stars7LSommaire du match
114597Barracuda8Phantoms4LSommaire du match
116607Phantoms5Wolfpack4WSommaire du match
118618Phantoms4Barracuda8LSommaire du match
119623Griffins4Phantoms7WSommaire du match
122644Phantoms4Canucks3WSommaire du match
123650Little Stars5Phantoms3LSommaire du match
126664Phantoms5Comets6LSommaire du match
128676Penguins5Phantoms4LSommaire du match
130688Phantoms3Reign4LR1Sommaire du match
132698Phantoms2Griffins4LSommaire du match
133703Condors2Phantoms5WSommaire du match
137728Condors8Phantoms5LSommaire du match
141752Icehogs1Phantoms4WSommaire du match
143766Phantoms6Wranglers4WR1Sommaire du match
145778Bears4Phantoms2LSommaire du match
147790Phantoms5Checkers3WSommaire du match
149800Phantoms3Condors1WSommaire du match
150806Barracuda6Phantoms1LSommaire du match
153816Phantoms2Wranglers4LR1Sommaire du match
156832Wolfpack2Phantoms3WSommaire du match
158838Phantoms2Crunch3LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
162858Americans4Phantoms8WSommaire du match
167883Reign2Phantoms1LR1Sommaire du match
170899Phantoms5Senators3WSommaire du match
171908Reign8Phantoms1LR1Sommaire du match
176934Rocket4Phantoms5WXSommaire du match
177939Phantoms4Condors3WXSommaire du match
181957Silver Knights2Phantoms3WSommaire du match
184979Phantoms3Crunch5LSommaire du match
185986Senators4Phantoms8WSommaire du match
1911010Marlies5Phantoms3LSommaire du match
1981031Marlies3Phantoms6WSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance74,33237,320
Assistance PCT92.92%93.30%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2791 - 93.04% 175,771$7,030,843$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,287,420$ 2,270,000$ 2,152,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
11,045$ 1,785,938$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 1 13,781$ 13,781$




Phantoms Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Phantoms Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Phantoms Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT

Phantoms Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Phantoms Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA