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Phantoms
GP: 80 | W: 38 | L: 33 | OTL: 9 | P: 85
GF: 344 | GA: 333 | PP%: 21.92% | PK%: 79.36%
DG: Simon DeChamplain | Morale : 31 | Moyenne d’équipe : 65
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Centre de jeu
Admirals
34-42-4, 72pts
4
FINAL
3 Phantoms
38-33-9, 85pts
Team Stats
L3StreakL3
17-19-4Home Record16-19-5
17-23-0Away Record22-14-4
3-6-1Last 10 Games5-5-0
3.83Buts par match 4.30
4.45Buts contre par match 4.16
24.11%Pourcentage en avantage numérique21.92%
75.09%Pourcentage en désavantage numérique79.36%
Heat
42-33-5, 89pts
4
FINAL
1 Phantoms
38-33-9, 85pts
Team Stats
W1StreakL3
22-15-3Home Record16-19-5
20-18-2Away Record22-14-4
5-3-2Last 10 Games5-5-0
4.06Buts par match 4.30
4.05Buts contre par match 4.16
26.77%Pourcentage en avantage numérique21.92%
76.83%Pourcentage en désavantage numérique79.36%
Meneurs d'équipe
Buts
Michael Bournival
53
Passes
Nick Shore
71
Points
Alex DeBrincat
114
Plus/Moins
Nick Shore
18
Victoires
Anton Forsberg
32
Pourcentage d’arrêts
Zachary Fucale
0.879

Statistiques d’équipe
Buts pour
344
4.30 GFG
Tirs pour
2768
34.60 Avg
Pourcentage en avantage numérique
21.9%
73 GF
Début de zone offensive
36.7%
Buts contre
333
4.16 GAA
Tirs contre
2616
32.70 Avg
Pourcentage en désavantage numérique
79.4%%
71 GA
Début de la zone défensive
36.5%
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
Assistance2,452
Billets de saison300


Informations de la formation

Équipe Pro34
Équipe Mineure20
Limite contact 54 / 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
1Michael BournivalX100.007939797677757475716879717674603734730251995,000$
2Alex DeBrincat (R)X100.007754867877707769747475617851447156710201500,000$
3Sven Andrighetto (R)X100.007934816980747169746679607357514455700242700,000$
4Nick ShoreX100.005827737172757075837475555958593535690251850,000$
5Joe Snively (R)X100.006333818758725775717171508343466751680212500,000$
6Cristoval Nieves (R)X100.006926777667707573767969557048504243680231600,000$
7Lucas Wallmarkk (R)X100.007238736865736474727667666544445339680213700,000$
8Morgan Klimchuk (R)X100.006732727271757569667270707647444551680222650,000$
9Erik Nystrom (R)X100.007023756973706771656372677550483551670241600,000$
10David Kampf (R)X100.005943836671716972666774566644475051660224700,000$
11Brendan Leipsic (R)X100.005033706666656265747172556347494028640231500,000$
12Nick Sorensen (R)X100.005933787469666965635672527348494540640232525,000$
13Laurent Dauphin (R)X100.007340796169637070607163506744444344630222500,000$
14JC Lipon (R)X100.007156696966516867685762525749503851620241450,000$
15Anthony Angello (R)X100.004938806363746555656561575343434544600212450,000$
16A.J. Greer (R)X100.006043616769627258595962525245444444590214250,000$
17Brett Murray (R)X100.007639626776546558445563544241416450580191500,000$
18Reid McNeillX100.007647797378658275596857726871513652710251975,000$
19Blake Heinrich (R)X100.007034717273746258497268795454464435690222500,000$
20Brenden KichtonX100.006730787168706865565960736357583234670251750,000$
21Rinat Valiev (R)X100.007334807267686273546560696248465151670222500,000$
22Cal Foote (R)X100.008047646480845357336452695043418251660192500,000$
23Mikko Lehtonen (R)X100.006941766152667074506871586149504552650231500,000$
24Matt Kiersted (R)X100.006446636165555455415543574941415922570191500,000$
25Riley Stillman (R)X100.006741625961566152355751554541416222570191500,000$
Rayé
1Cooper Marody (R)X100.004335706251596160727256384745434920560214250,000$
2Fabian Zetterlund (R)X100.004535685362645654554568415840406920540182500,000$
3Devon Teows (R)X100.007347747066646270526455725449504639670233700,000$
4Victor Berglund (R)X100.006126655761514743285230662840407120550182500,000$
MOYENNE D’ÉQUIPE100.00663873686867666560656460614947504164
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 Forsberg100.00757473777279767272767469713750740251975,000$
2Zachary Fucale100.00667759687074737578745948464651710222500,000$
Rayé
1Jason Kasdorf100.00676778656470687067696653533720670251750,000$
2Kevin Lankinen (R)100.00676564676369596963635541416815630221500,000$
3Zachary Sawchenko (R)100.00605368515062664645717344466020560202500,000$
MOYENNE D’ÉQUIPE100.0067676866647168666571655151503166
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Kevin Dineen73656679327257Can494500,000$


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
1Alex DeBrincatPhantoms (Phi)RW80466811412291510210631410218114.65%45183322.921828465527500092945047.92%2408420101.243101025311
2Nick ShorePhantoms (Phi)C68387110918875941062609517914.62%30141620.839283735236202131083555.41%20974024001.5414000294
3Michael BournivalPhantoms (Phi)LW715352105230013112331711619416.72%58166123.411623395224500072425050.57%5266337041.26180001043
4Joe SnivelyPhantoms (Phi)C80244266334068822158512911.16%17103012.89347161140001221347.34%6955311001.2814000304
5Cristoval NievesPhantoms (Phi)C78234063-133008771184599012.50%1792411.85291111640001123251.37%6563815001.3600000323
6Morgan KlimchukPhantoms (Phi)LW802339629540951052135511110.80%27129016.133710182190001213151.02%494616000.9612000144
7Sven AndrighettoPhantoms (Phi)RW80263056143010128901714712215.20%23142817.864481622101181613245.54%1123726010.7837101331
8Lucas WallmarkkPhantoms (Phi)C7724285272806676133439718.05%187669.95235582000092046.23%491198001.3600000141
9Reid McNeillPhantoms (Phi)D79730371471511514311558636.09%107209426.515813262970003305100.00%03466000.3500111011
10Erik NystromPhantoms (Phi)LW79151833-1528086711415210310.64%3287511.08011222000053056.76%372620000.7500000330
11Blake HeinrichPhantoms (Phi)D717233016981010112411537396.09%99158822.37347202150004211210.00%02850000.3800101021
12Brendan LeipsicPhantoms (Phi)LW7014132711602024100265214.00%95197.42000000000251066.67%12126001.0400000102
13Nick SorensenPhantoms (Phi)RW7471825-1416034487525439.33%1578310.5801108000000048.00%25188000.6400000002
14Jake DotchinFlyersD21516212200264642152011.90%3956526.933471179000090010.00%0821000.7400000100
15Devon TeowsPhantoms (Phi)D6831518-1034078916022235.00%63126918.6722441530113177000.00%01644000.2800000000
16Brenden KichtonPhantoms (Phi)D715111610200447545212311.11%5196413.58000073011275000.00%0332000.3300000001
17David KampfPhantoms (Phi)C807916-1008164392816.28%112583.23000090001101037.23%9490001.2400000003
18Rinat ValievPhantoms (Phi)D8001515-620059765720330.00%62125815.7402231160002118000.00%01132000.2400000000
19Ivan ProvorovFlyersD173111438025323612138.33%2445226.642241175000059000.00%01016000.6200000110
20Cal FootePhantoms (Phi)D8001414432042543013160.00%366878.5900005000032000.00%0122000.4100000001
21JC LiponPhantoms (Phi)RW8057128300901950204810.00%106287.8600008000001037.50%879000.3800000001
22Mikko LehtonenPhantoms (Phi)D801675235262828763.57%175466.8400001000028000.00%0413000.2600001000
23A.J. GreerPhantoms (Phi)LW75213940171182725.00%21962.63000000000940045.45%1111000.3000000010
24Brett MurrayPhantoms (Phi)LW7812321609671314.29%2921.1800004000000133.33%303000.6501000000
25Laurent DauphinPhantoms (Phi)C76202-1403030266.67%1550.7310119000001028.57%701000.7200000000
26Anthony AngelloPhantoms (Phi)C75011-100332110.00%01341.79000030002960040.43%4701000.1500000000
27Matt KierstedPhantoms (Phi)D50000-16011131310.00%92064.140000000006000.00%003000.00%00000000
28Riley StillmanPhantoms (Phi)D31000280313020.00%1912.940000200007000.00%003000.00%00000000
Statistiques d’équipe totales ou en moyenne19493415809216675260157116402768946162912.32%8252362312.12731302032862549235572220351651.23%5110568508150.781036416343743
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)73322280.8754.073818602592076998400.581317010222
2Zachary FucalePhantoms (Phi)2861110.8793.8110240165538272120.50081070101
Statistiques d’équipe totales ou en moyenne101383390.8764.014843613242614127052398080323


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
A.J. GreerPhantoms (Phi)LW211996-01-01Yes210 Lbs6 ft3NoNoNo4Pro & Farm250,000$0$0$No300,000$350,000$400,000$Lien
Alex DeBrincatPhantoms (Phi)RW201997-01-01Yes165 Lbs5 ft7NoNoNo1Pro & Farm500,000$0$0$NoLien
Anthony AngelloPhantoms (Phi)C211996-01-01Yes210 Lbs6 ft5NoNoNo2Pro & Farm450,000$0$0$No450,000$Lien
Anton ForsbergPhantoms (Phi)G251992-01-01No191 Lbs6 ft3NoNoNo1Pro & Farm975,000$0$0$No
Blake HeinrichPhantoms (Phi)D221995-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Brendan LeipsicPhantoms (Phi)LW231994-01-01Yes165 Lbs5 ft8NoNoNo1Pro & Farm500,000$0$0$NoLien
Brenden KichtonPhantoms (Phi)D251992-01-01No185 Lbs5 ft10NoNoNo1Pro & Farm750,000$0$0$No
Brett MurrayPhantoms (Phi)LW191998-01-01Yes216 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$NoLien
Cal FootePhantoms (Phi)D191998-01-01Yes227 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Cooper MarodyPhantoms (Phi)C211996-01-01Yes184 Lbs6 ft0NoNoNo4Pro & Farm250,000$0$0$No300,000$350,000$400,000$Lien
Cristoval NievesPhantoms (Phi)C231994-01-01Yes192 Lbs6 ft2NoNoNo1Pro & Farm600,000$0$0$NoLien
David KampfPhantoms (Phi)C221995-01-01Yes188 Lbs6 ft2NoNoNo4Pro & Farm700,000$0$0$No750,000$800,000$900,000$Lien
Devon TeowsPhantoms (Phi)D231994-01-01Yes191 Lbs5 ft11NoNoNo3Pro & Farm700,000$0$0$No800,000$900,000$Lien
Erik NystromPhantoms (Phi)LW241993-01-01Yes176 Lbs5 ft11NoNoNo1Pro & Farm600,000$0$0$NoLien
Fabian ZetterlundPhantoms (Phi)LW181999-01-01Yes220 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
JC LiponPhantoms (Phi)RW241993-01-01Yes185 Lbs6 ft0NoNoNo1Pro & Farm450,000$0$0$NoLien
Jason KasdorfPhantoms (Phi)G251992-01-01No172 Lbs6 ft3NoNoNo1Pro & Farm750,000$0$0$No
Joe SnivelyPhantoms (Phi)C211996-01-01Yes176 Lbs5 ft9NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Kevin LankinenPhantoms (Phi)G221995-01-01Yes185 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLien
Laurent DauphinPhantoms (Phi)C221995-01-01Yes185 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Lucas WallmarkkPhantoms (Phi)C211996-01-01Yes178 Lbs6 ft0NoNoNo3Pro & Farm700,000$0$0$No800,000$900,000$
Matt KierstedPhantoms (Phi)D191998-01-01Yes184 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$NoLien
Michael BournivalPhantoms (Phi)LW251992-01-01No195 Lbs5 ft11NoNoNo1Pro & Farm995,000$0$0$No
Mikko LehtonenPhantoms (Phi)D231994-01-01Yes196 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$NoLien
Morgan KlimchukPhantoms (Phi)LW221995-01-01Yes185 Lbs5 ft11NoNoNo2Pro & Farm650,000$0$0$No650,000$Lien
Nick ShorePhantoms (Phi)C251992-01-01No194 Lbs6 ft1NoNoNo1Pro & Farm850,000$0$0$No
Nick SorensenPhantoms (Phi)RW231994-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm525,000$0$0$No525,000$Lien
Reid McNeillPhantoms (Phi)D251992-01-01No210 Lbs6 ft3NoNoNo1Pro & Farm975,000$0$0$No
Riley StillmanPhantoms (Phi)D191998-01-01Yes196 Lbs6 ft1NoNoNo1Pro & Farm500,000$0$0$NoLien
Rinat ValievPhantoms (Phi)D221995-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Sven AndrighettoPhantoms (Phi)RW241993-01-01Yes185 Lbs5 ft10NoNoNo2Pro & Farm700,000$0$0$No700,000$Lien
Victor BerglundPhantoms (Phi)D181999-01-01Yes183 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Zachary FucalePhantoms (Phi)G221995-01-01No185 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Zachary SawchenkoPhantoms (Phi)G201997-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3422.00190 Lbs6 ft01.76584,412$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael BournivalNick ShoreAlex DeBrincat40122
2Morgan KlimchukLucas WallmarkkSven Andrighetto30122
3Erik NystromCristoval NievesNick Sorensen20122
4Brendan LeipsicJoe SnivelyJC Lipon10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Reid McNeillBlake Heinrich40122
2Rinat ValievBrenden Kichton30122
3Cal FooteMikko Lehtonen20122
4Matt KierstedRiley Stillman10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael BournivalNick ShoreAlex DeBrincat60122
2Morgan KlimchukLucas WallmarkkSven Andrighetto40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Reid McNeillBlake Heinrich60122
2Rinat ValievBrenden Kichton40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Michael BournivalAlex DeBrincat60122
2Sven AndrighettoNick Shore40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Reid McNeillBlake Heinrich60122
2Rinat ValievBrenden Kichton40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Michael Bournival60122Reid McNeillBlake Heinrich60122
2Alex DeBrincat40122Rinat ValievBrenden Kichton40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Michael BournivalAlex DeBrincat60122
2Sven AndrighettoNick Shore40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Reid McNeillBlake Heinrich60122
2Rinat ValievBrenden Kichton40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Michael BournivalNick ShoreAlex DeBrincatReid McNeillBlake Heinrich
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Michael BournivalNick ShoreAlex DeBrincatReid McNeillBlake Heinrich
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
David Kampf, Laurent Dauphin, Anthony AngelloDavid Kampf, Laurent DauphinAnthony Angello
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Cal Foote, Mikko Lehtonen, Matt KierstedCal FooteMikko Lehtonen, Matt Kiersted
Tirs de pénalité
Michael Bournival, Alex DeBrincat, Sven Andrighetto, Nick Shore, Lucas Wallmarkk
Gardien
#1 : Zachary Fucale, #2 : Anton Forsberg


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
1Admirals31100001131302010000168-21100000075230.500132437009014310711121962936858488536316312325.00%10460.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
2Barracuda30300000915-62020000068-21010000037-400.00091726009014310711114962936858489325326110440.00%16475.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
3Bears211000009811010000024-21100000074320.500915240090143107116896293685848772816335240.00%8362.50%0980187352.32%934186750.03%704137051.39%173699416927551422702
4Comets742000012728-1311000011113-2431000001615190.64327457210901431071124296293685848239775411927414.81%26869.23%0980187352.32%934186750.03%704137051.39%173699416927551422702
5Condors31000101141312100000110821000010045-140.66714223600901431071197962936858489525225815426.67%11281.82%0980187352.32%934186750.03%704137051.39%173699416927551422702
6Crunch211000008711010000035-21100000052320.500813210090143107117796293685848582426425360.00%13284.62%0980187352.32%934186750.03%704137051.39%173699416927551422702
7Devils21000010853100000103211100000053241.00081321009014310711659629368584861162238500.00%110100.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
8Eagles32100000191362110000012841100000075240.6671936550090143107111069629368584810433275510550.00%11190.91%0980187352.32%934186750.03%704137051.39%173699416927551422702
9Griffins312000001112-1211000009811010000024-220.3331121320090143107111099629368584810636287910220.00%14378.57%0980187352.32%934186750.03%704137051.39%173699416927551422702
10Heat623000102429-530200010915-6321000001514160.50024355900901431071117696293685848194668213135720.00%411173.17%0980187352.32%934186750.03%704137051.39%173699416927551422702
11Icehogs32100000161241010000036-322000000136740.66716284400901431071110296293685848943428618225.00%14471.43%0980187352.32%934186750.03%704137051.39%173699416927551422702
12Little Stars31100001811-3210000015321010000038-530.5008142200901431071110096293685848100402650800.00%13284.62%0980187352.32%934186750.03%704137051.39%173699416927551422702
13Marlies72300101302913110000115141412001001515060.42930477700901431071123696293685848197759112839820.51%33584.85%1980187352.32%934186750.03%704137051.39%173699416927551422702
14Monsters3300000014682200000010461100000042261.000142640009014310711107962936858488232336211436.36%13192.31%1980187352.32%934186750.03%704137051.39%173699416927551422702
15Moose31200000151501010000046-221100000119220.333152540009014310711111962936858489931235711436.36%9188.89%0980187352.32%934186750.03%704137051.39%173699416927551422702
16Penguins20200000511-61010000048-41010000013-200.0005813009014310711619629368584880201631400.00%8275.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
17Punishers211000009901010000036-31100000063320.500913220090143107116696293685848812128466116.67%9188.89%0980187352.32%934186750.03%704137051.39%173699416927551422702
18Rampage20200000510-51010000036-31010000024-200.000591400901431071166962936858486016184410220.00%9188.89%0980187352.32%934186750.03%704137051.39%173699416927551422702
19Reign65100000312293210000015132330000001697100.83331538411901431071120496293685848190545213231722.58%26580.77%0980187352.32%934186750.03%704137051.39%173699416927551422702
20Rocket31200000151321100000061520200000912-320.333152439009014310711110962936858481081912511516.67%6266.67%0980187352.32%934186750.03%704137051.39%173699416927551422702
21Senators311000011113-21010000024-22100000199030.5001120310090143107111079629368584810628247216212.50%12283.33%0980187352.32%934186750.03%704137051.39%173699416927551422702
22Sound Tigers210010001073100010004311100000064241.0001017270090143107116496293685848681716409222.22%8187.50%0980187352.32%934186750.03%704137051.39%173699416927551422702
23Thunderbirds20200000611-51010000045-11010000026-400.0006111700901431071172962936858486424829700.00%4175.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
24Wolfpack301000111214-2100000106512010000169-330.5001221330090143107111129629368584810530245212433.33%12375.00%0980187352.32%934186750.03%704137051.39%173699416927551422702
25Wolves220000001578110000007431100000083541.00015233800901431071175962936858487018193712216.67%7271.43%0980187352.32%934186750.03%704137051.39%173699416927551422702
Total803433012373443331140121901035162167-54022140020218216616850.531344580924219014310711276896293685848261682575815713337321.92%3447179.36%2980187352.32%934186750.03%704137051.39%173699416927551422702
_Since Last GM Reset803433012373443331140121901035162167-54022140020218216616850.531344580924219014310711276896293685848261682575815713337321.92%3447179.36%2980187352.32%934186750.03%704137051.39%173699416927551422702
_Vs Conference462019002142031921123811000139595023128002011089711480.52220334254511901431071115949629368584814494614589552134822.54%2054478.54%2980187352.32%934186750.03%704137051.39%173699416927551422702
_Vs Division19970011185805934000113942-310630010046388220.57985135220119014310711616962936858485811952253911052220.95%1002179.00%1980187352.32%934186750.03%704137051.39%173699416927551422702

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8085L334458092427682616825758157121
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8034331237344333
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4012191035162167
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4022140202182166
Derniers 10 matchs
WLOTWOTL SOWSOL
550000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3337321.92%3447179.36%2
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
962936858489014310711
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
980187352.32%934186750.03%704137051.39%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
173699416927551422702


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 - 2022-10-271Marlies6Phantoms5BLXXSommaire du match
3 - 2022-10-2914Phantoms3Comets2AWSommaire du match
4 - 2022-10-3016Phantoms4Marlies6ALSommaire du match
9 - 2022-11-0448Heat4Phantoms5BWXXR1Sommaire du match
11 - 2022-11-0653Phantoms4Marlies5ALXSommaire du match
13 - 2022-11-0868Phantoms5Heat4AWR1Sommaire du match
15 - 2022-11-1076Comets5Phantoms1BLSommaire du match
17 - 2022-11-1287Phantoms3Comets5ALSommaire du match
19 - 2022-11-14101Reign7Phantoms6BLR1Sommaire du match
21 - 2022-11-16113Phantoms4Comets3AWSommaire du match
22 - 2022-11-17117Phantoms7Reign6AWR1Sommaire du match
23 - 2022-11-18129Little Stars1Phantoms4BWSommaire du match
29 - 2022-11-24153Griffins2Phantoms4BWSommaire du match
32 - 2022-11-27170Phantoms4Reign0AWR1Sommaire du match
34 - 2022-11-29178Marlies2Phantoms5BWSommaire du match
37 - 2022-12-02198Condors5Phantoms4BLXXSommaire du match
40 - 2022-12-05212Phantoms4Monsters2AWSommaire du match
43 - 2022-12-08225Wolfpack5Phantoms6BWXXSommaire du match
46 - 2022-12-11239Phantoms5Reign3AWR1Sommaire du match
48 - 2022-12-13250Moose6Phantoms4BLSommaire du match
52 - 2022-12-17266Phantoms6Comets5AWSommaire du match
54 - 2022-12-19275Bears4Phantoms2BLSommaire du match
58 - 2022-12-23295Heat7Phantoms3BLR1Sommaire du match
60 - 2022-12-25308Phantoms5Crunch2AWSommaire du match
63 - 2022-12-28320Phantoms8Wolves3AWSommaire du match
64 - 2022-12-29329Monsters1Phantoms3BWSommaire du match
67 - 2023-01-01347Eagles5Phantoms3BLSommaire du match
69 - 2023-01-03357Phantoms4Heat9ALR1Sommaire du match
71 - 2023-01-05365Phantoms2Thunderbirds6ALSommaire du match
73 - 2023-01-07379Monsters3Phantoms7BWSommaire du match
77 - 2023-01-11400Phantoms7Admirals5AWSommaire du match
79 - 2023-01-13406Thunderbirds5Phantoms4BLSommaire du match
81 - 2023-01-15415Phantoms6Heat1AWR1Sommaire du match
84 - 2023-01-18430Barracuda6Phantoms5BLSommaire du match
86 - 2023-01-20440Phantoms2Griffins4ALSommaire du match
89 - 2023-01-23457Crunch5Phantoms3BLSommaire du match
92 - 2023-01-26476Phantoms6Sound Tigers4AWSommaire du match
93 - 2023-01-27485Rampage6Phantoms3BLSommaire du match
96 - 2023-01-30500Phantoms2Rampage4ALSommaire du match
97 - 2023-01-31509Reign2Phantoms4BWR1Sommaire du match
101 - 2023-02-04526Phantoms1Penguins3ALSommaire du match
103 - 2023-02-06535Penguins8Phantoms4BLSommaire du match
106 - 2023-02-09551Phantoms4Moose5ALSommaire du match
108 - 2023-02-11560Little Stars2Phantoms1BLXXSommaire du match
111 - 2023-02-14580Phantoms6Punishers3AWSommaire du match
112 - 2023-02-15587Senators4Phantoms2BLSommaire du match
117 - 2023-02-20611Condors3Phantoms6BWSommaire du match
119 - 2023-02-22619Phantoms4Condors5ALXSommaire du match
123 - 2023-02-26637Marlies6Phantoms5BLSommaire du match
125 - 2023-02-28648Phantoms5Rocket7ALSommaire du match
127 - 2023-03-02661Sound Tigers3Phantoms4BWXSommaire du match
129 - 2023-03-04671Phantoms3Barracuda7ALSommaire du match
132 - 2023-03-07688Rocket1Phantoms6BWSommaire du match
134 - 2023-03-09698Phantoms7Senators6AWSommaire du match
137 - 2023-03-12714Phantoms5Marlies1AWSommaire du match
138 - 2023-03-13720Comets6Phantoms5BLXXSommaire du match
140 - 2023-03-15734Phantoms7Eagles5AWSommaire du match
142 - 2023-03-17743Admirals4Phantoms3BLXXSommaire du match
146 - 2023-03-21763Griffins6Phantoms5BLSommaire du match
148 - 2023-03-23775Phantoms2Wolfpack3ALXXSommaire du match
150 - 2023-03-25780Phantoms2Senators3ALXXSommaire du match
152 - 2023-03-27794Phantoms2Marlies3ALSommaire du match
153 - 2023-03-28800Eagles3Phantoms9BWSommaire du match
157 - 2023-04-01819Devils2Phantoms3BWXXSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
160 - 2023-04-04830Phantoms5Devils3AWSommaire du match
163 - 2023-04-07846Barracuda2Phantoms1BLSommaire du match
166 - 2023-04-10857Phantoms3Little Stars8ALSommaire du match
168 - 2023-04-12872Reign4Phantoms5BWR1Sommaire du match
170 - 2023-04-14883Phantoms7Bears4AWSommaire du match
173 - 2023-04-17897Phantoms4Rocket5ALSommaire du match
174 - 2023-04-18903Icehogs6Phantoms3BLSommaire du match
179 - 2023-04-23923Comets2Phantoms5BWSommaire du match
181 - 2023-04-25936Phantoms7Moose4AWSommaire du match
183 - 2023-04-27944Phantoms5Icehogs3AWSommaire du match
184 - 2023-04-28952Phantoms4Wolfpack6ALSommaire du match
186 - 2023-04-30960Wolves4Phantoms7BWSommaire du match
188 - 2023-05-02970Phantoms8Icehogs3AWSommaire du match
192 - 2023-05-06988Punishers6Phantoms3BLSommaire du match
197 - 2023-05-111008Admirals4Phantoms3BLSommaire du match
203 - 2023-05-171030Heat4Phantoms1BLR1Sommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3520
Assistance74,31123,762
Assistance PCT92.89%59.41%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2452 - 81.73% 80,748$3,229,933$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,650,138$ 1,987,000$ 1,769,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,646$ 2,141,725$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 12,073$ 0$




Phantoms Leaders statistiques (saison régulière)

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

Phantoms Leaders des statistiques des gardiens (saison régulière)

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

Phantoms Statistiques de l'Équipe de Carrière

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

Phantoms Leaders statistiques (séries éliminatoires)

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

Phantoms Leaders des statistiques des gardiens (séries éliminatoires)

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