Phantoms

GP: 46 | W: 22 | L: 20 | OTL: 4 | P: 48
GF: 123 | GA: 122 | PP%: 12.26% | PK%: 84.57%
DG: Yannick Bernier | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #527 vs Penguins
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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
1Lane PedersonX100.00717170667168696780636763644444675000223777,500$
2Gemel SmithXXX100.006968727268747667805968656556566750002611,000,000$
3Givani SmithXX100.00857687667654787025555961254545635000222913,333$
4Melker KarlssonXX100.006742897865628757406059777566696545002912,000,000$
5Mikkel BoedkerXX100.006743998576546362326059726175776444003011,000,000$
6Maxim LetunovX100.007771916271707265806660665744446550002411,000,000$
7Nathan BastianX100.00777875627877816250586265594444645000223992,500$
8Pontus AbergXX100.007370817670757866506265676254556750002611,000,000$
9Lean Bergmann (R)XX100.008946897576516451265855562545456050002111,000,000$
10Jack Studnicka (R)X100.00716585736575786580616563624444675000213863,333$
11Evan RodriguesXXX100.006541907766597761655964707563636650002611,000,000$
12Valentin ZykovXX100.007845877180625964256558562548486250002511,000,000$
13Alex Formenton (R)X100.00727371767367686650616864654444675000203888,333$
14Mark AltX100.00787781657770764725374262404444535000281650,000$
15Luke GreenX100.00756990606940404225284159394444485000222838,333$
16Mark FriedmanX100.00716781646775815125474159394444545000242825,000$
17Reece Willcox (R)X100.00777092627071784725394061384444535000263675,000$
18Josh Brook (R)X100.00737179697173804725374159394444525000213910,833$
Rayé
1Cole Bardreau (R)XX100.00864582636652625459605968255555635000263700,000$
2Jack KopackaX100.00807298627256565650505765544444605000222910,833$
3Stelio MattheosX100.00787291557262645550495764544444605000212925,000$
4Danil Yurtaykin (R)XX100.006961897161606255506046594444445650002211,000,000$
5Tyrell GoulbourneXX100.00727078687069764550414458424444525000261775,000$
MOYENNE D'ÉQUIPE100.0075648569716471574654566349494961500
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 SP
1Anton Forsberg100.0055617678555750585352304848555000
2Charlie Lindgren100.0051587375485354585252304646535000
Rayé
1Joseph Woll (R)100.0050648080455250554949304444525000
MOYENNE D'ÉQUIPE100.005261767849545157515130464653500
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dominique Ducharme73727068696479CAN493850,000$


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
1Gemel SmithPhantoms (PHI)C/LW/RW4622173983406171114419819.30%885218.5494133520310131096059.92%50400020.9100000633
2Pontus AbergPhantoms (PHI)LW/RW4692130-3420106719624649.38%1395420.75211132821811272541047.25%9100000.6325000314
3Mikkel BoedkerPhantoms (PHI)LW/RW44151429-380329590264916.67%993221.2057122418911222261140.53%52800000.6204000223
4Evan RodriguesPhantoms (PHI)C/LW/RW4682129-46023958429579.52%882117.8657122519011211592056.04%77800000.7123000013
5Alex FormentonPhantoms (PHI)LW4681725135715436110023698.00%366714.50066131260001193148.78%4100000.7500021144
6Valentin ZykovPhantoms (PHI)LW/RW4613102316240453862174620.97%466914.5423516147000002029.63%2700000.6900000211
7Jack StudnickaPhantoms (PHI)C468142211240218572175911.11%866514.480004260001522158.13%52300000.6600000231
8Melker KarlssonPhantoms (PHI)C/RW1991120280203035112225.71%735418.6732512940111550245.38%36800001.1313000132
9Nathan BastianPhantoms (PHI)RW4678153375403064164210.94%552411.4100003000001044.44%1800000.5700001103
10Lean BergmannPhantoms (PHI)LW/RW4648124440393332111612.50%248910.6400016000000138.46%2600000.4900000100
11Mark FriedmanPhantoms (PHI)D46191021055881618795.56%29106623.1804492150001202000.00%000000.1900010001
12Josh BrookPhantoms (PHI)D362810534073181451114.29%2578521.8122481490000171000.00%000000.2500000000
13Reece WillcoxPhantoms (PHI)D46279466083191581113.33%1776816.71011272000196100.00%000000.2300000200
14Maxim LetunovPhantoms (PHI)C463581010017331911815.79%63698.040110100000910059.71%20600100.4300000001
15Mark AltPhantoms (PHI)D401674595821619555.26%2785121.29011101740110164000.00%000000.1600001000
16Givani SmithPhantoms (PHI)LW/RW11156-3140184125128.33%016915.42112550000000050.00%1000000.7100000010
17Lane PedersonPhantoms (PHI)C46145519541152211164.55%63677.990002270000130054.55%5500000.2700000010
18Cole BardreauPhantoms (PHI)C/RW44123-11801413236124.35%32124.83000113000030048.94%4700000.2800000000
19Luke GreenPhantoms (PHI)D2401143003744050.00%835414.7700009000054000.00%000000.0600000000
20Jack KopackaPhantoms (PHI)LW9000-200001010.00%1262.94000180000100020.00%500000.0000000000
Stats d'équipe Total ou en Moyenne779115188303756393588374789626362212.83%1891190515.28295079196193845918168819652.49%322700120.51515033212026
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)46222040.8682.602700021178850020.73315460112
2Charlie LindgrenPhantoms (PHI)40000.9730.7184001370000.0000046000
Stats d'équipe Total ou en Moyenne50222040.8722.542785021189220020.733154646112


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 RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Alex FormentonPhantoms (PHI)LW201999-09-13Yes190 Lbs6 ft3NoNoNo3Pro & Farm888,333$365,363$888,333$365,363$0$0$No888,333$888,333$
Anton ForsbergPhantoms (PHI)G271992-11-26No192 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$411,290$1,000,000$411,290$0$0$NoLien
Charlie LindgrenPhantoms (PHI)G261993-12-17No190 Lbs6 ft2NoNoNo1Pro & Farm1,300,000$534,677$1,300,000$534,677$0$0$NoLien
Cole BardreauPhantoms (PHI)C/RW261993-07-22Yes185 Lbs5 ft10NoNoNo3Pro & Farm700,000$287,903$700,000$287,903$0$0$No700,000$700,000$
Danil YurtaykinPhantoms (PHI)LW/RW221997-07-01Yes165 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$411,290$1,000,000$411,290$0$0$NoLien
Evan RodriguesPhantoms (PHI)C/LW/RW261993-07-28No182 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$411,290$1,000,000$411,290$0$0$NoLien
Gemel Smith (Contrat à 1 Volet)Phantoms (PHI)C/LW/RW261994-04-16No190 Lbs5 ft10NoNoNo1Pro & Farm1,000,000$411,290$1,000,000$411,290$100,000$41,129$NoLien
Givani SmithPhantoms (PHI)LW/RW221998-02-27No204 Lbs6 ft2NoNoNo2Pro & Farm913,333$375,645$913,333$375,645$0$0$No913,333$Lien
Jack KopackaPhantoms (PHI)LW221998-05-05No192 Lbs6 ft2NoNoNo2Pro & Farm910,833$374,617$910,000$374,274$0$0$No910,833$Lien
Jack StudnickaPhantoms (PHI)C211999-02-17Yes171 Lbs6 ft1NoNoNo3Pro & Farm863,333$355,081$863,333$355,081$0$0$No863,333$863,333$Lien
Joseph WollPhantoms (PHI)G211998-07-12Yes200 Lbs6 ft3NoNoNo3Pro & Farm850,000$349,597$800,000$329,032$0$0$No800,000$800,000$Lien
Josh BrookPhantoms (PHI)D211999-06-17Yes192 Lbs6 ft1NoNoNo3Pro & Farm910,833$374,617$910,833$374,617$0$0$No910,833$910,833$
Lane PedersonPhantoms (PHI)C221997-08-04No192 Lbs6 ft1NoNoNo3Pro & Farm777,500$319,778$690,000$283,790$0$0$No690,000$690,000$Lien
Lean BergmannPhantoms (PHI)LW/RW211998-10-04Yes205 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$411,290$1,000,000$411,290$0$0$NoLien
Luke GreenPhantoms (PHI)D221998-01-11No188 Lbs6 ft1NoNoNo2Pro & Farm838,333$344,798$850,000$349,597$0$0$No838,333$Lien
Mark AltPhantoms (PHI)D281991-10-17No201 Lbs6 ft4NoNoNo1Pro & Farm650,000$267,339$650,000$267,339$0$0$NoLien
Mark FriedmanPhantoms (PHI)D241995-12-25No185 Lbs5 ft11NoNoNo2Pro & Farm825,000$339,315$825,000$339,315$0$0$No825,000$Lien
Maxim LetunovPhantoms (PHI)C241996-02-19No180 Lbs6 ft4NoNoNo1Pro & Farm1,000,000$411,290$1,000,000$411,290$0$0$NoLien
Melker KarlssonPhantoms (PHI)C/RW291990-07-18No182 Lbs5 ft10NoNoNo1Pro & Farm2,000,000$822,581$2,000,000$822,581$0$0$NoLien
Mikkel BoedkerPhantoms (PHI)LW/RW301989-12-15No210 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$411,290$1,000,000$411,290$0$0$NoLien
Nathan BastianPhantoms (PHI)RW221997-12-06No205 Lbs6 ft4NoNoNo3Pro & Farm992,500$408,206$905,000$372,218$0$0$No905,000$905,000$Lien
Pontus AbergPhantoms (PHI)LW/RW261993-09-22No196 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$411,290$1,000,000$411,290$0$0$NoLien
Reece WillcoxPhantoms (PHI)D261994-05-20Yes183 Lbs6 ft3NoNoNo3Pro & Farm675,000$277,621$675,000$277,621$0$0$No675,000$675,000$
Stelio MattheosPhantoms (PHI)RW211999-06-13No198 Lbs6 ft1NoNoNo2Pro & Farm925,000$380,444$925,000$380,444$0$0$No925,000$Lien
Tyrell GoulbournePhantoms (PHI)LW/RW261994-01-25No195 Lbs5 ft11NoNoNo1Pro & Farm775,000$318,750$775,000$318,750$0$0$NoLien
Valentin ZykovPhantoms (PHI)LW/RW251995-05-14No224 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$411,290$1,000,000$411,290$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2624.08192 Lbs6 ft11.81953,654$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mikkel BoedkerMelker KarlssonPontus Aberg35122
2Evan RodriguesGemel SmithGivani Smith30122
3Alex FormentonJack StudnickaValentin Zykov25122
4Lean BergmannLane PedersonNathan Bastian10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark FriedmanReece Willcox35122
2Mark AltJosh Brook30122
3Luke GreenLane Pederson25122
4Mark FriedmanReece Willcox10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Mikkel BoedkerMelker KarlssonPontus Aberg60122
2Evan RodriguesGemel SmithGivani Smith40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark FriedmanReece Willcox60122
2Mark AltJosh Brook40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Mikkel BoedkerMelker Karlsson60122
2Pontus AbergGemel Smith40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark FriedmanReece Willcox60122
2Mark AltJosh Brook40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Mikkel Boedker60122Mark FriedmanReece Willcox60122
2Melker Karlsson40122Mark AltJosh Brook40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Mikkel BoedkerMelker Karlsson60122
2Pontus AbergGemel Smith40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mark FriedmanReece Willcox60122
2Mark AltJosh Brook40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mikkel BoedkerMelker KarlssonPontus AbergMark FriedmanReece Willcox
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Mikkel BoedkerMelker KarlssonPontus AbergMark FriedmanReece Willcox
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Maxim Letunov, Alex Formenton, Jack StudnickaMaxim Letunov, Alex FormentonJack Studnicka
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Luke Green, Mark Alt, Josh BrookLuke GreenMark Alt, Josh Brook
Tirs de Pénalité
Mikkel Boedker, Melker Karlsson, Pontus Aberg, Gemel Smith, Evan Rodrigues
Gardien
#1 : Anton Forsberg, #2 : Charlie Lindgren


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
LigueDomicileVisiteur
# 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
1Admirals1000010012-1000000000001000010012-110.50012300493437623334302313281542821200.00%130100.00%0728132754.86%651129150.43%33465550.99%11167701126343550270
2Bruins2010001046-22010001046-20000000000020.5004590049343763933430231328444224219210.53%11372.73%0728132754.86%651129150.43%33465550.99%11167701126343550270
3Crunch11000000541110000005410000000000021.00059140049343762733430231328221142312216.67%2150.00%0728132754.86%651129150.43%33465550.99%11167701126343550270
4Flames1000010034-1000000000001000010034-110.50036900493437618334302313281981424600.00%7271.43%0728132754.86%651129150.43%33465550.99%11167701126343550270
5Griffins21100000963211000009630000000000020.500918270049343763833430231328441228481317.69%13192.31%0728132754.86%651129150.43%33465550.99%11167701126343550270
6Marlies22000000734220000007340000000000041.00071118004934376503343023132835829421119.09%14378.57%0728132754.86%651129150.43%33465550.99%11167701126343550270
7Monarchs1010000024-21010000024-20000000000000.000246104934376283343023132821414246116.67%50100.00%1728132754.86%651129150.43%33465550.99%11167701126343550270
8Monsters116300002312834300000115105733000011618-2140.6363153840049343762263343023132818550154200691014.49%681282.35%1728132754.86%651129150.43%33465550.99%11167701126343550270
9Penguins4130000057-2211000004132020000016-520.25058130149343766133430231328762565782428.33%29293.10%0728132754.86%651129150.43%33465550.99%11167701126343550270
10Rampage321000001495211000008621100000063340.66714243800493437685334302313287923386419631.58%18477.78%0728132754.86%651129150.43%33465550.99%11167701126343550270
11Rocket32100000752220000004131010000034-140.6677132001493437654334302313285518344415213.33%16193.75%0728132754.86%651129150.43%33465550.99%11167701126343550270
12Senators2020000058-31010000023-11010000035-200.000581300493437642334302313283773635400.00%17476.47%0728132754.86%651129150.43%33465550.99%11167701126343550270
13Soldiers11000000211000000000001100000021121.00023500493437624334302313282182018500.00%9188.89%0728132754.86%651129150.43%33465550.99%11167701126343550270
14Sound Tigers513000101315-22020000036-331100010109140.40013223500493437612733430231328137399411825312.00%40685.00%0728132754.86%651129150.43%33465550.99%11167701126343550270
Total4619200023212312212412100001168571122710002215565-10480.522123212335224934376961334302313289242556879282613212.26%3114884.57%4728132754.86%651129150.43%33465550.99%11167701126343550270
15Wolf Pack724000101520-53120000057-2412000101013-360.42915264110493437611933430231328134341071473126.45%49883.67%2728132754.86%651129150.43%33465550.99%11167701126343550270
_Since Last GM Reset4619200023212312212412100001168571122710002215565-10480.522123212335224934376961334302313289242556879282613212.26%3114884.57%4728132754.86%651129150.43%33465550.99%11167701126343550270
_Vs Conference331414001228285-317105000114635111649001113650-14350.53082139221124934376636334302313286071654656351912110.99%2133683.10%3728132754.86%651129150.43%33465550.99%11167701126343550270
_Vs Division27910001126470-6115300001272431647001113746-9230.42664109173114934376533334302313285321484205431491711.41%1862884.95%3728132754.86%651129150.43%33465550.99%11167701126343550270

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4648L112321233596192425568792822
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4619200232123122
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
24121000116857
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2271002215565
Derniers 10 Matchs
WLOTWOTL SOWSOL
440200
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2613212.26%3114884.57%4
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
334302313284934376
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
728132754.86%651129150.43%33465550.99%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
11167701126343550270


Derniers Match 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 - 2020-09-271Phantoms5Wolf Pack4WXXSommaire du Match
2 - 2020-09-2813Monsters1Phantoms3WSommaire du Match
4 - 2020-09-3030Phantoms3Monsters1WSommaire du Match
5 - 2020-10-0137Monsters4Phantoms3LXXSommaire du Match
6 - 2020-10-0247Phantoms0Monsters1LSommaire du Match
8 - 2020-10-0461Wolf Pack2Phantoms1LSommaire du Match
10 - 2020-10-0675Wolf Pack4Phantoms2LSommaire du Match
12 - 2020-10-0882Phantoms3Monsters4LXXSommaire du Match
15 - 2020-10-1198Bruins2Phantoms3WXXSommaire du Match
16 - 2020-10-12104Phantoms2Monsters4LSommaire du Match
18 - 2020-10-14114Phantoms0Penguins3LSommaire du Match
20 - 2020-10-16129Sound Tigers2Phantoms0LSommaire du Match
22 - 2020-10-18137Monsters4Phantoms6WSommaire du Match
23 - 2020-10-19149Phantoms1Penguins3LSommaire du Match
24 - 2020-10-20156Phantoms3Wolf Pack2WSommaire du Match
25 - 2020-10-21168Rampage5Phantoms4LSommaire du Match
26 - 2020-10-22178Phantoms0Monsters3LSommaire du Match
28 - 2020-10-24190Monsters1Phantoms3WSommaire du Match
31 - 2020-10-27206Senators3Phantoms2LSommaire du Match
32 - 2020-10-28216Phantoms4Monsters2WSommaire du Match
34 - 2020-10-30224Phantoms0Wolf Pack3LSommaire du Match
36 - 2020-11-01235Sound Tigers4Phantoms3LSommaire du Match
38 - 2020-11-03250Rocket0Phantoms2WSommaire du Match
40 - 2020-11-05261Phantoms2Soldiers1WSommaire du Match
42 - 2020-11-07269Marlies2Phantoms5WSommaire du Match
45 - 2020-11-10287Wolf Pack1Phantoms2WSommaire du Match
46 - 2020-11-11301Phantoms3Senators5LSommaire du Match
48 - 2020-11-13310Penguins0Phantoms4WSommaire du Match
50 - 2020-11-15332Penguins1Phantoms0LSommaire du Match
51 - 2020-11-16343Phantoms6Rampage3WSommaire du Match
53 - 2020-11-18353Phantoms2Sound Tigers3LSommaire du Match
54 - 2020-11-19360Rampage1Phantoms4WSommaire du Match
55 - 2020-11-20370Phantoms4Sound Tigers3WSommaire du Match
56 - 2020-11-21379Rocket1Phantoms2WSommaire du Match
58 - 2020-11-23397Phantoms4Sound Tigers3WXXSommaire du Match
59 - 2020-11-24407Monarchs4Phantoms2LSommaire du Match
60 - 2020-11-25418Griffins2Phantoms7WSommaire du Match
62 - 2020-11-27431Phantoms3Flames4LXSommaire du Match
63 - 2020-11-28441Marlies1Phantoms2WSommaire du Match
64 - 2020-11-29449Phantoms4Monsters3WSommaire du Match
66 - 2020-12-01461Griffins4Phantoms2LSommaire du Match
68 - 2020-12-03477Phantoms3Rocket4LSommaire du Match
69 - 2020-12-04486Phantoms1Admirals2LXSommaire du Match
70 - 2020-12-05490Bruins4Phantoms1LSommaire du Match
71 - 2020-12-06506Crunch4Phantoms5WSommaire du Match
73 - 2020-12-08518Phantoms2Wolf Pack4LSommaire du Match
74 - 2020-12-09527Penguins-Phantoms-
75 - 2020-12-10538Phantoms-Crunch-
77 - 2020-12-12544Phantoms-Sound Tigers-
78 - 2020-12-13556Condors-Phantoms-
79 - 2020-12-14565Phantoms-Griffins-
80 - 2020-12-15577Sharks-Phantoms-
82 - 2020-12-17591Penguins-Phantoms-
84 - 2020-12-19602Phantoms-Moose-
86 - 2020-12-21614Phantoms-Stars-
87 - 2020-12-22624Flames-Phantoms-
88 - 2020-12-23632Phantoms-Marlies-
90 - 2020-12-25642Phantoms-Crunch-
91 - 2020-12-26649IceHogs-Phantoms-
93 - 2020-12-28666Moose-Phantoms-
95 - 2020-12-30684Wolves-Phantoms-
96 - 2020-12-31695Phantoms-Sharks-
97 - 2021-01-01707Admirals-Phantoms-
98 - 2021-01-02714Phantoms-Wolves-
99 - 2021-01-03725Soldiers-Phantoms-
101 - 2021-01-05740Phantoms-Crunch-
102 - 2021-01-06748Wolf Pack-Phantoms-
103 - 2021-01-07756Phantoms-Crunch-
105 - 2021-01-09769Phantoms-Senators-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10778Rampage-Phantoms-
107 - 2021-01-11790Phantoms-Bruins-
108 - 2021-01-12796Stars-Phantoms-
110 - 2021-01-14814Sound Tigers-Phantoms-
112 - 2021-01-16827Phantoms-Condors-
114 - 2021-01-18839Sound Tigers-Phantoms-
115 - 2021-01-19848Phantoms-Penguins-
117 - 2021-01-21860Monsters-Phantoms-
118 - 2021-01-22869Phantoms-IceHogs-
120 - 2021-01-24883Monsters-Phantoms-
121 - 2021-01-25891Phantoms-Penguins-
122 - 2021-01-26900Phantoms-Griffins-
123 - 2021-01-27902Phantoms-Monarchs-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
17 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,926,697$ 2,379,498$ 2,358,082$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,426,292$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 51 26,044$ 1,328,244$




LigueDomicileVisiteur
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