Connexion

Phantoms
GP: 81 | W: 40 | L: 33 | OTL: 8 | P: 88
GF: 172 | GA: 168 | PP%: 12.50% | PK%: 90.56%
DG: Richard Duguay | Morale : 50 | Moyenne d’équipe : 59
Prochains matchs #1299 vs Bears
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Centre de jeu
Phantoms
40-33-8, 88pts
5
FINAL
2 Wolf Pack
43-31-7, 93pts
Team Stats
W3SéquenceW1
25-12-3Fiche domicile22-15-3
15-21-5Fiche domicile21-16-4
7-2-1Derniers 10 matchs6-3-1
2.12Buts par match 2.63
2.07Buts contre par match 2.21
12.50%Pourcentage en avantage numérique15.36%
90.56%Pourcentage en désavantage numérique86.09%
Spiders
47-29-5, 99pts
2
FINAL
3 Phantoms
40-33-8, 88pts
Team Stats
SOL1SéquenceW3
26-13-1Fiche domicile25-12-3
21-16-4Fiche domicile15-21-5
4-4-2Derniers 10 matchs7-2-1
2.46Buts par match 2.12
1.94Buts contre par match 2.07
15.77%Pourcentage en avantage numérique12.50%
87.61%Pourcentage en désavantage numérique90.56%
Bears
29-37-14, 72pts
2024-04-16
Phantoms
40-33-8, 88pts
Statistiques d’équipe
W2SéquenceW3
16-17-7Fiche domicile25-12-3
13-20-7Fiche visiteur15-21-5
4-6-010 derniers matchs7-2-1
2.01Buts par match 2.12
2.46Buts contre par match 2.12
18.07%Pourcentage en avantage numérique12.50%
81.22%Pourcentage en désavantage numérique90.56%
Meneurs d'équipe
Buts
Elliot Desnoyers
17
Passes
Sasha Chmelevski
32
Points
Sasha Chmelevski
44
Plus/Moins
Topi Niemela
18
Victoires
Devon Levi
38
Pourcentage d’arrêts
Vadim Zherenko
1

Statistiques d’équipe
Buts pour
172
2.12 GFG
Tirs pour
1493
18.43 Avg
Pourcentage en avantage numérique
12.5%
28 GF
Début de zone offensive
38.9%
Buts contre
168
2.07 GAA
Tirs contre
1525
18.83 Avg
Pourcentage en désavantage numérique
90.6%%
22 GA
Début de la zone défensive
39.2%
Informations de l'équipe

Directeur généralRichard Duguay
DivisionNord-Est
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,865
Billets de saison300


Informations de la formation

Équipe Pro22
Équipe Mineure19
Limite contact 41 / 50
Espoirs19


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
1Sasha ChmelevskiXX100.00714390756860695954745174244646050640231778,335$
2Tanner LaczynskiXX100.00664476717475676653606062665852050630253775,000$
3Alexander NylanderXXX100.00594473696466656544636358665350050620242800,000$
4Anton BlidhXX100.00624463686671706441595960646355050620271900,000$
5Trey Fix-WolanskyX100.00544663715664636844656256675250050610232809,166$
6Elliot Desnoyers (R)XX100.00614070696260616442626260655050050610203825,000$
7Logan HutskoX100.00584471715765646242625462635250050600232867,000$
8Josiah SlavinX100.00584570646464636141575555605250050580233600,000$
9Oskar Olausson (R)X100.00594067656257576241565754615050050580193894,167$
10Sam Poulin (R)XX100.00634768606860585848545453575050050560213863,333$
11Brad Lambert (R)XX100.00604068626254535740545454575050050560183950,000$
12Dillon Hamaliuk (R)X100.00727774637744444649434261424444050530213789,167$
13Jack AhcanX100.0055437171576665654064556764545005062N0254750,000$
14Mac HollowellX100.00564466715562595940595164605250050600242799,766$
15Nikolai KnyzhovX100.00624068596860595640545360565250050580241796,667$
16Topi Niemela (R)X100.00564068695658575640545460595050050580203856,667$
17Mason Millman (R)X100.00534651595352505140505053525050050530213700,000$
Rayé
MOYENNE D’ÉQUIPE100.0060456967636160604358556058525005059
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
1Arvid Holm (R)100.0069636571696971686967555250050630231845,833$
2Devon Levi (R)100.0073666573696968666969705250050630203925,000$
Rayé
1Kyle Keyser (R)100.0071636362666769686867615250050610232725,000$
2Vadim Zherenko (R)100.0068616262656567656665585050050600213846,667$
3Beck Warm (R)100.0062575759585554535459535150050530232650,000$
MOYENNE D’ÉQUIPE100.006962626565656664656559515005060
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Sasha ChmelevskiPhantoms (Phi)C/RW75123244732097206100457612.00%21155120.693361516500001783252.47%135900100.57211000623
2Trey Fix-WolanskyPhantoms (Phi)RW811624404280551211463810010.96%5133516.4934712920002593253.85%7800000.6002000512
3Logan HutskoPhantoms (Phi)C8114243861806214277236618.18%29132516.360114300001242046.41%64000000.5700000164
4Tanner LaczynskiPhantoms (Phi)C/RW801719363180106119157409510.83%13155119.392572419100041482658.61%24400000.46411000362
5Jarred TinordiPhiladelphieD6210233337752106477173212.99%74150224.23459451530002141320%000000.4400001532
6Elliot DesnoyersPhantoms (Phi)C/LW76171431322079147145419011.72%10128916.9724610800000735245.94%102100000.4800000147
7Alexander NylanderPhantoms (Phi)C/LW/RW80141630227575127134409810.45%6146318.30022171800002593148.42%79100000.4125010126
8Jack AhcanPhantoms (Phi)D8052429-26340114946425307.81%53163620.46459351710000169200%000000.3500000122
9Mac HollowellPhantoms (Phi)D8091625-23540112624593220.00%60159619.95246211640001153110%000000.3100000311
10Nikolai KnyzhovPhantoms (Phi)D807152213480104403292121.88%35133816.73112858000083020%000000.3300000401
11Oskar OlaussonPhantoms (Phi)RW8171219-214051567320659.59%38079.972027140000201039.34%6100000.4700000112
12Ben HarpurPhiladelphieD3861117424063475072912.00%2792324.2935834106101195210%000000.3702000111
13Jakob PelletierPhiladelphieLW3651116-325540707824506.41%685223.67033139501121051045.53%25700000.3815010110
14Topi NiemelaPhantoms (Phi)D70313161826058331761817.65%2389312.76000329000066000%000000.3600000121
15Anton BlidhPhantoms (Phi)LW/RW457512-416067447926408.86%488219.62101101040001632145.00%4000000.2713000030
16Josiah SlavinPhantoms (Phi)C8121012-52204049465244.35%177058.720222310000241041.98%29300000.3400000110
17Sam PoulinPhantoms (Phi)C/LW3657124141037222181923.81%354315.101011240000120143.90%4100000.4400110001
18Dillon HamaliukPhantoms (Phi)LW22112-660231111179.09%227712.6301105000061046.15%1300000.1400000000
19Mason MillmanPhantoms (Phi)D911224023340025.00%515717.480000700004000%000000.2500000100
20Brad LambertPhantoms (Phi)C/RW361121402622182205.56%53549.8500009000080032.00%2500000.1100000000
Statistiques d’équipe totales ou en moyenne122915927943815132514421479137438691211.57%4012098917.082845732611715112161500322148.55%486300100.421039131363635
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
1Devon LeviPhantoms (Phi)76383080.8941.9745780815014130320.75040765542
2Arvid HolmPhantoms (Phi)62300.8972.06321001110700000553000
3Vadim ZherenkoPhantoms (Phi)10001.000012000300000021000
Statistiques d’équipe totales ou en moyenne83403380.8941.974912081611523032408179542


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 Ballotage forcé Waiver Possible Contrat Type Salaire actuel Salaire moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Lien
Alexander NylanderPhantoms (Phi)C/LW/RW241998-03-02No192 Lbs6 ft1NoNoYesYes2Pro & Farm800,000$20,833$0$0$No800,000$Lien
Anton Blidh (contrat à 1 volet)Phantoms (Phi)LW/RW271995-03-14No185 Lbs6 ft0NoNoYesYes1Pro & Farm900,000$23,438$0$0$NoLien
Arvid HolmPhantoms (Phi)G231998-11-03Yes214 Lbs6 ft4NoNoNoNo1Pro & Farm845,833$22,027$0$0$NoLien
Beck WarmPhantoms (Phi)G231999-04-22Yes172 Lbs6 ft0NoNoNoNo2Pro & Farm650,000$16,927$0$0$No650,000$Lien
Brad LambertPhantoms (Phi)C/RW182003-12-19Yes183 Lbs6 ft0NoNoNoNo3Pro & Farm950,000$24,740$0$0$No950,000$950,000$
Devon LeviPhantoms (Phi)G202001-12-27Yes184 Lbs6 ft0NoNoNoNo3Pro & Farm925,000$24,089$0$0$No925,000$925,000$
Dillon HamaliukPhantoms (Phi)LW212000-10-30Yes201 Lbs6 ft4NoNoNoNo3Pro & Farm789,167$20,551$0$0$No789,167$789,167$Lien
Elliot DesnoyersPhantoms (Phi)C/LW202002-01-21Yes183 Lbs5 ft11NoNoNoNo3Pro & Farm825,000$21,484$0$0$No825,000$825,000$
Jack Ahcan (contrat à 1 volet)Phantoms (Phi)D251997-05-18No179 Lbs5 ft8YesNoYesYes4Pro & Farm750,000$19,531$0$0$No750,000$750,000$750,000$Lien
Josiah SlavinPhantoms (Phi)C231998-12-31No190 Lbs6 ft3NoNoNoNo3Pro & Farm600,000$15,625$0$0$No600,000$600,000$Lien
Kyle KeyserPhantoms (Phi)G231999-03-08Yes179 Lbs6 ft2NoNoNoNo2Pro & Farm725,000$18,880$0$0$No725,000$Lien
Logan HutskoPhantoms (Phi)C231999-02-11No172 Lbs5 ft10NoNoNoNo2Pro & Farm867,000$22,578$0$0$No867,000$Lien
Mac HollowellPhantoms (Phi)D241998-09-26No170 Lbs5 ft9NoNoYesYes2Pro & Farm799,766$20,827$0$0$No799,766$Lien
Mason MillmanPhantoms (Phi)D212001-07-18Yes175 Lbs6 ft1NoNoNoNo3Pro & Farm700,000$18,229$0$0$No700,000$700,000$Lien
Nikolai KnyzhovPhantoms (Phi)D241998-03-20No218 Lbs6 ft2NoNoYesYes1Pro & Farm796,667$20,747$0$0$NoLien
Oskar OlaussonPhantoms (Phi)RW192002-11-10Yes181 Lbs6 ft1NoNoNoNo3Pro & Farm894,167$23,286$0$0$No894,167$894,167$
Sam PoulinPhantoms (Phi)C/LW212001-02-25Yes207 Lbs6 ft1NoNoNoNo3Pro & Farm863,333$22,483$0$0$No863,333$863,333$Lien
Sasha ChmelevskiPhantoms (Phi)C/RW231999-06-09No187 Lbs6 ft0NoNoNoNo1Pro & Farm778,335$20,269$0$0$NoLien
Tanner LaczynskiPhantoms (Phi)C/RW251997-06-01No190 Lbs6 ft1NoNoYesYes3Pro & Farm775,000$20,182$0$0$No775,000$775,000$Lien
Topi NiemelaPhantoms (Phi)D202002-03-25Yes157 Lbs5 ft11NoNoNoNo3Pro & Farm856,667$22,309$0$0$No856,667$856,667$
Trey Fix-WolanskyPhantoms (Phi)RW231999-05-26No179 Lbs5 ft7NoNoNoNo2Pro & Farm809,166$21,072$0$0$No809,166$Lien
Vadim ZherenkoPhantoms (Phi)G212001-03-15Yes176 Lbs6 ft2NoNoNoNo3Pro & Farm846,667$22,049$0$0$No846,667$846,667$
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2222.32185 Lbs6 ft02.41806,671$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Alexander NylanderSasha ChmelevskiTanner Laczynski40122
2Sam PoulinElliot DesnoyersTrey Fix-Wolansky30122
3Dillon HamaliukLogan HutskoOskar Olausson20122
4Sasha ChmelevskiJosiah SlavinBrad Lambert10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jack AhcanMac Hollowell40122
2Topi NiemelaNikolai Knyzhov30122
3Mason MillmanJosiah Slavin20122
4Jack AhcanMac Hollowell10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Alexander NylanderSasha ChmelevskiTanner Laczynski60122
2Sam PoulinElliot DesnoyersTrey Fix-Wolansky40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jack AhcanMac Hollowell60122
2Topi NiemelaNikolai Knyzhov40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Sasha ChmelevskiTanner Laczynski60122
2Alexander NylanderElliot Desnoyers40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jack AhcanMac Hollowell60122
2Topi NiemelaNikolai Knyzhov40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Sasha Chmelevski60122Jack AhcanMac Hollowell60122
2Tanner Laczynski40122Topi NiemelaNikolai Knyzhov40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Sasha ChmelevskiTanner Laczynski60122
2Alexander NylanderElliot Desnoyers40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jack AhcanMac Hollowell60122
2Topi NiemelaNikolai Knyzhov40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Alexander NylanderSasha ChmelevskiTanner LaczynskiJack AhcanMac Hollowell
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Alexander NylanderSasha ChmelevskiTanner LaczynskiJack AhcanMac Hollowell
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Logan Hutsko, Oskar Olausson, Brad LambertLogan Hutsko, Oskar OlaussonBrad Lambert
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Mason Millman, Topi Niemela, Nikolai KnyzhovMason MillmanTopi Niemela, Nikolai Knyzhov
Tirs de pénalité
Sasha Chmelevski, Tanner Laczynski, Alexander Nylander, Elliot Desnoyers, Trey Fix-Wolansky
Gardien
#1 : Devon Levi, #2 : Arvid Holm


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
TotalDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Admirals21100000440110000003121010000013-220.500471110476058123445347455057349833500.00%4175.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
2Baby Hawks21000001440110000002111000000123-130.75047110047605812344534745505736312263133.33%6266.67%0991199849.60%942201546.75%527112246.97%1997141219135681016510
3Bears22000000642110000003211100000032141.000610160047605812364534745505731512394250.00%5180.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
4Bruins32100000752211000004401100000031240.667712190047605812424534745505745233157800.00%120100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
5Cabaret Lady Mary Ann33000000817110000003032200000051461.00081422024760581257453474550574520234711327.27%80100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
6Caroline4120000110100210000016332020000047-330.37510162600476058125245347455057842646707114.29%18288.89%1991199849.60%942201546.75%527112246.97%1997141219135681016510
7Chiefs21100000330110000003211010000001-120.50036900476058123545347455057451818474125.00%80100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
8Chill20100010550100000103211010000023-120.5005611004760581232453474550574091647500.00%70100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
9Comets21100000440110000003211010000012-120.50046100047605812384534745505759101425500.00%70100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
10Cougars3110000178-1110000003212010000146-230.50071320004760581248453474550577016165210110.00%80100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
11Crunch3100010178-1110000003212000010146-240.667714210047605812564534745505761918619222.22%80100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
12Heat2020000035-21010000012-11010000023-100.0003690047605812444534745505746122024500.00%10190.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
13Jayhawks211000006421010000023-11100000041320.500612180047605812504534745505743114503266.67%20100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
14Las Vegas2020000024-21010000012-11010000012-100.000246004760581248453474550573191046500.00%4250.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
15Manchots4130000048-4211000003302020000015-420.250481211476058126245347455057722736641000.00%120100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
16Marlies31100010642210000105231010000012-140.66768140147605812514534745505753141445800.00%50100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
17Minnesota2010010038-51000010034-11010000004-410.250369004760581252453474550574781239600.00%60100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
18Monarchs211000001101010000001-11100000010120.5001230147605812354534745505731828425120.00%12191.67%0991199849.60%942201546.75%527112246.97%1997141219135681016510
19Monsters4130000046-2211000003302020000013-220.2504610014760581264453474550576523267216212.50%11281.82%0991199849.60%942201546.75%527112246.97%1997141219135681016510
20Monsters2020000026-41010000012-11010000014-300.0002460047605812434534745505732814427114.29%7271.43%0991199849.60%942201546.75%527112246.97%1997141219135681016510
21Oceanics22000000743110000005321100000021141.0007132000476058123345347455057279836600.00%40100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
22Oil Kings2010010049-51010000015-41000010034-110.2504711004760581238453474550573610650600.00%3166.67%0991199849.60%942201546.75%527112246.97%1997141219135681016510
23Rocket320000101064100000104312200000063361.00010162600476058125545347455057551014529111.11%7185.71%0991199849.60%942201546.75%527112246.97%1997141219135681016510
24Sags21001000523100010003211100000020241.000591401476058124045347455057318143210110.00%70100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
25Seattle21100000440110000002111010000023-120.5004812004760581239453474550573910123910110.00%30100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
26Senators3030000039-62020000027-51010000012-100.00036900476058123745347455057601821659111.11%80100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
27Sound Tigers32100000550110000003122110000024-240.667510150047605812394534745505755132453800.00%12283.33%0991199849.60%942201546.75%527112246.97%1997141219135681016510
28Spiders41200010911-2201000108802110000013-240.50091423014760581266453474550577819201188225.00%80100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
29Stars21000010743100000104311100000031241.0007111800476058123045347455057271516423133.33%8275.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
30Thunder330000001248220000007251100000052361.00012233500476058121114534745505764188674125.00%40100.00%0991199849.60%942201546.75%527112246.97%1997141219135681016510
31Wolf Pack411000111082200000114402110000064250.625101626004760581292453474550578315188115320.00%9277.78%0991199849.60%942201546.75%527112246.97%1997141219135681016510
Total81333301365172168440181201162988216411521002037486-12880.5431723004722847605812149345347455057152541353915632242812.50%2332290.56%1991199849.60%942201546.75%527112246.97%1997141219135681016510
_Since Last GM Reset81333301365172168440181201162988216411521002037486-12880.5431723004722847605812149345347455057152541353915632242812.50%2332290.56%1991199849.60%942201546.75%527112246.97%1997141219135681016510
_Vs Conference4319180104188808231070104156451120911000003235-3490.570881502382647605812774453474550577692182848511211310.74%120992.50%0991199849.60%942201546.75%527112246.97%1997141219135681016510
_Vs Division2557000214852-4122200021302461335000001828-10150.3004880128134760581241145347455057468128182497681014.71%75988.00%1991199849.60%942201546.75%527112246.97%1997141219135681016510

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8188W317230047214931525413539156328
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8133331365172168
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
40181211629882
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
41152102037486
Derniers 10 matchs
WLOTWOTL SOWSOL
720100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2242812.50%2332290.56%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
4534745505747605812
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
991199849.60%942201546.75%527112246.97%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1997141219135681016510


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
3 - 2023-10-1211Phantoms1Monsters2ALSommaire du match
5 - 2023-10-1419Phantoms1Senators2ALSommaire du match
8 - 2023-10-1742Comets2Phantoms3BWSommaire du match
10 - 2023-10-1954Oil Kings5Phantoms1BLSommaire du match
12 - 2023-10-2172Phantoms3Stars1AWSommaire du match
15 - 2023-10-2498Phantoms1Las Vegas2ALSommaire du match
17 - 2023-10-26104Minnesota4Phantoms3BLXSommaire du match
19 - 2023-10-28117Admirals1Phantoms3BWSommaire du match
21 - 2023-10-30131Caroline1Phantoms5BWSommaire du match
23 - 2023-11-01141Crunch2Phantoms3BWSommaire du match
25 - 2023-11-03157Phantoms2Crunch3ALXXSommaire du match
26 - 2023-11-04164Monarchs1Phantoms0BLSommaire du match
29 - 2023-11-07189Phantoms2Sags0AWSommaire du match
32 - 2023-11-10208Phantoms1Admirals3ALSommaire du match
33 - 2023-11-11221Phantoms1Monarchs0AWSommaire du match
37 - 2023-11-15238Phantoms2Caroline3ALSommaire du match
40 - 2023-11-18255Las Vegas2Phantoms1BLSommaire du match
41 - 2023-11-19268Monsters0Phantoms2BWSommaire du match
44 - 2023-11-22286Phantoms2Sound Tigers1AWSommaire du match
46 - 2023-11-24294Wolf Pack2Phantoms1BLXXSommaire du match
47 - 2023-11-25312Phantoms0Sound Tigers3ALSommaire du match
50 - 2023-11-28328Caroline2Phantoms1BLXXSommaire du match
52 - 2023-11-30344Spiders6Phantoms5BLSommaire du match
54 - 2023-12-02363Phantoms1Manchots3ALSommaire du match
56 - 2023-12-04374Manchots0Phantoms2BWSommaire du match
59 - 2023-12-07400Phantoms4Jayhawks1AWSommaire du match
61 - 2023-12-09417Phantoms1Monsters4ALSommaire du match
64 - 2023-12-12435Phantoms2Chill3ALSommaire du match
66 - 2023-12-14448Bears2Phantoms3BWSommaire du match
68 - 2023-12-16466Cougars2Phantoms3BWSommaire du match
71 - 2023-12-19487Phantoms0Spiders3ALSommaire du match
73 - 2023-12-21502Chill2Phantoms3BWXXSommaire du match
74 - 2023-12-22510Phantoms2Cougars3ALXXSommaire du match
80 - 2023-12-28543Phantoms1Comets2ALSommaire du match
81 - 2023-12-29554Phantoms2Seattle3ALSommaire du match
83 - 2023-12-31570Phantoms2Heat3ALSommaire du match
85 - 2024-01-02583Phantoms3Oil Kings4ALXSommaire du match
87 - 2024-01-04592Monsters3Phantoms1BLSommaire du match
89 - 2024-01-06605Heat2Phantoms1BLSommaire du match
91 - 2024-01-08622Manchots3Phantoms1BLSommaire du match
93 - 2024-01-10635Rocket3Phantoms4BWXXSommaire du match
95 - 2024-01-12652Phantoms0Minnesota4ALSommaire du match
96 - 2024-01-13657Phantoms2Oceanics1AWSommaire du match
98 - 2024-01-15679Phantoms0Chiefs1ALSommaire du match
101 - 2024-01-18694Stars3Phantoms4BWXXSommaire du match
103 - 2024-01-20707Monsters2Phantoms1BLSommaire du match
104 - 2024-01-21718Senators3Phantoms1BLSommaire du match
106 - 2024-01-23732Thunder1Phantoms3BWSommaire du match
108 - 2024-01-25747Phantoms2Cougars3ALSommaire du match
110 - 2024-01-27759Bruins2Phantoms3BWSommaire du match
120 - 2024-02-06786Phantoms2Cabaret Lady Mary Ann1AWSommaire du match
122 - 2024-02-08797Oceanics3Phantoms5BWSommaire du match
124 - 2024-02-10814Seattle1Phantoms2BWSommaire du match
126 - 2024-02-12821Jayhawks3Phantoms2BLSommaire du match
129 - 2024-02-15843Phantoms1Marlies2ALSommaire du match
131 - 2024-02-17859Phantoms1Spiders0AWSommaire du match
135 - 2024-02-21885Phantoms2Baby Hawks3ALXXSommaire du match
138 - 2024-02-24905Wolf Pack2Phantoms3BWXXSommaire du match
139 - 2024-02-25917Phantoms0Manchots2ALSommaire du match
141 - 2024-02-27930Thunder1Phantoms4BWSommaire du match
144 - 2024-03-01954Phantoms3Bears2AWSommaire du match
145 - 2024-03-02962Senators4Phantoms1BLSommaire du match
147 - 2024-03-04977Chiefs2Phantoms3BWSommaire du match
150 - 2024-03-07996Phantoms3Cabaret Lady Mary Ann0AWSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
152 - 2024-03-091016Phantoms5Thunder2AWSommaire du match
155 - 2024-03-121035Sags2Phantoms3BWXSommaire du match
157 - 2024-03-141050Marlies2Phantoms3BWXXSommaire du match
159 - 2024-03-161065Phantoms3Bruins1AWSommaire du match
162 - 2024-03-191086Marlies0Phantoms2BWSommaire du match
164 - 2024-03-211099Phantoms2Caroline4ALSommaire du match
166 - 2024-03-231114Bruins2Phantoms1BLSommaire du match
167 - 2024-03-241129Cabaret Lady Mary Ann0Phantoms3BWSommaire du match
169 - 2024-03-261137Phantoms1Wolf Pack2ALSommaire du match
171 - 2024-03-281152Phantoms3Rocket1AWSommaire du match
173 - 2024-03-301174Baby Hawks1Phantoms2BWSommaire du match
175 - 2024-04-011183Sound Tigers1Phantoms3BWSommaire du match
179 - 2024-04-051211Phantoms2Crunch3ALXSommaire du match
180 - 2024-04-061222Phantoms0Monsters1ALSommaire du match
183 - 2024-04-091242Phantoms3Rocket2AWSommaire du match
185 - 2024-04-111257Phantoms5Wolf Pack2AWSommaire du match
187 - 2024-04-131274Spiders2Phantoms3BWXXSommaire du match
190 - 2024-04-161299Bears-Phantoms-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance76,31538,301
Assistance PCT95.39%95.75%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
1 2865 - 95.51% 97,366$3,894,648$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,948,070$ 1,609,679$ 1,609,679$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,384$ 1,948,070$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
97,366$ 5 8,384$ 41,920$




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