Phantoms

GP: 82 | W: 35 | L: 40 | OTL: 7 | P: 77
GF: 277 | GA: 306 | PP%: 23.25% | PK%: 73.72%
DG: Richard Duguay | Morale : 50 | Moyenne d'Équipe : 47
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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 SP
1Dwight KingX100.00574388658263765135465770545755050590
2Nail YakupovXX100.0059358468666372603555645856504205059X0
3Oskar SundqvistX100.0059358669736146457645446848413905054X0
4Marko DanoXX100.00583588617357425135465650484236050520
5Michael Amadio (R)X100.00493589657151415060455456483532050520
6Michael MerschX100.00473593667544324335424465463532050500
7Nicholas MerkleyXX100.00473555686455353535353557483532050460
8Tyler Benson (R)X100.00454545456245454545454545453230050450
9Roope Hintz (R) (C)X100.00434545456042424345434345443230050440
10Haydn Fleury (R)X100.00673589617454493735413277483532050560
11Jyrki JokipakkaX100.0059358662716052463547436744373405056X0
12Matt Grzelcyk (R)X100.00523585745159484535474369483734050560
13Sebastien Aho (R)X100.00464387724955374766464761483734050530
14Michael PaliottaX100.0045354160694231383546306646353205050X0
15Alexandre CarrierX100.00473594745243333035293168473532050500
16Dillon Simpson (R)X100.00483578626344333035293166473532050490
Rayé
1Emerson EtemXX100.00584387637356385035465562544943050540
2Brandon KozunX100.0043358471474031434939466145353205048X0
3Brian FerlinX100.0045359263734029363542315645353205046X0
4Sebastian Collberg (R) (A)XX100.0041454545553939414541414543323005043X0
5Dennis Yan (R)X100.00414343437040404143414143423230050430
6Connor Bunnaman (R)X100.00404040407540404040404040403230050420
7Martins Dzierkals (R)X100.00414343435140404143414143423230050420
8Austin Poganski (R)X100.00364040406835353640363640383230050400
9Christoffer Ehn (R)X100.00364040405735353640363640383230050390
10Jake Evans (R)XX100.00373737376037373737373737373230050390
11Jordy Stallard (R)X100.00373737375837373737373737373230050390
12Sergei Boikov (R)X100.00373737376637373737373737373230050400
13Maxim ChudinovX100.00333737375833333337333337353230050380
MOYENNE D'ÉQUIPE100.0047386556644641424141425445363305048
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
1Brandon Halverson (R)100.0035454580354545354565453532050460
2Philippe Desrosiers (R)100.0043454366424141414141403230050430
Rayé
1Fredrik Bergvik (R)100.0038403869373636363636353230050400
MOYENNE D'ÉQUIPE100.003943427238414137414740333105043
Nom du Coach 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'ÉquipePOS GP 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
1Nail YakupovPhantoms (Phi)LW/RW673952913260791332418118716.18%15152122.711319325522511272064342.56%58500011.2027000763
2Dwight KingPhantoms (Phi)LW68474390132757213028910721216.26%14145521.411515306822211242343250.61%40700041.2414001947
3Michael AmadioPhantoms (Phi)C7929568520195391442035816714.29%10151719.21819273725000051376358.34%166100001.1213010375
4Matt GrzelcykPhantoms (Phi)D77195473-422054891706011611.18%90170422.13142135109248000321021100.00%200000.8600000244
5Haydn FleuryPhantoms (Phi)D80155065-474013990122399412.30%115170321.3081624612560222178110.00%200000.7600000425
6Sebastien AhoPhantoms (Phi)D82163955-224105196144509411.11%84169320.6671320842520223209110.00%000000.6512011114
7Michael MerschPhantoms (Phi)LW82172744-1613535140202611338.42%15142617.406511281460003983144.19%12900000.6202001211
8Marko DanoPhantoms (Phi)LW/RW82241842424095511655911014.55%10160819.624592827301141583144.24%16500000.5226000117
9Oskar SundqvistPhantoms (Phi)C40191938-125565109113309216.81%1385621.403811261381013892061.56%92600000.8915100312
10Nicholas MerkleyPhantoms (Phi)C/RW82142438248101489788286615.91%11144617.644913172580000282042.59%84300010.5300200132
11Emerson EtemPhantoms (Phi)LW/RW2520163615135353492276821.74%652220.88381118822025631040.77%13000011.3813001402
12Alexandre CarrierPhantoms (Phi)D8252328-1724049857328476.85%84144917.681232914101101110150.00%200000.3900000012
13Tyler BensonPhantoms (Phi)LW8210919-3297251246377276912.99%18124215.161015200000333151.18%42200000.3100013101
14Jyrki JokipakkaPhantoms (Phi)D3741317328037326222316.45%3173119.78268391260001100100.00%000000.4600000112
15Dillon SimpsonPhantoms (Phi)D7031114-1330064544623396.52%6792213.1821313460000780012.50%800000.3000000010
16Michael PaliottaPhantoms (Phi)D4121113-751574392110129.52%4065916.080115300000452025.00%400000.3900000011
17Roope HintzPhantoms (Phi)LW825712-18520742534163214.71%1396011.711013370000451050.00%7400000.2500000000
18Sebastian CollbergPhantoms (Phi)LW/RW43459-1723535183282912.50%355312.880114570000140045.16%3100000.3200001011
19Nick JensenPhiladelphieD1134739518122771611.11%824021.882242140000020100.00%000000.5800010000
20Connor BunnamanPhantoms (Phi)C43066-172005844173150.00%358513.620113270000140045.52%58000000.2000000001
21Christoffer EhnPhantoms (Phi)C43134-31602938133107.69%34039.3800015000060042.21%39800000.2000000000
22Brandon KozunPhantoms (Phi)RW12314-640318325189.38%021217.732133280000100136.84%1900000.3811000000
23Brian FerlinPhantoms (Phi)RW14134-600321282123.57%321815.63011311000060080.00%500000.3701000000
24Ben ChiarotPhiladelphieD8123-316016151913195.26%718322.971121430000018000.00%000000.3300000000
25Sergei BoikovPhantoms (Phi)D27033-11803411040.00%1436513.54000114000033000.00%000000.1600000000
26Dennis YanPhantoms (Phi)LW34112-42012390211.11%21614.750111220001320138.46%3900000.2500000000
27Martins DzierkalsPhantoms (Phi)RW21011-1060101216580.00%32029.64000215000020050.00%1800000.1000000000
28Jake EvansPhantoms (Phi)C/RW26000-111602034120.00%134513.3000006000000025.00%3200000.0000000000
Stats d'équipe Total ou en Moyenne1440302501803-12972785147215962340773170412.91%6832489717.299715625367830185813412191361750.65%648200070.651034348393550
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
1Brandon HalversonPhantoms (Phi)76323650.8673.6841406225419040500.54224757221
2Philippe DesrosiersPhantoms (Phi)213420.9003.3482600464620100.72711775000
Stats d'équipe Total ou en Moyenne97354070.8733.6349666230023660600.600358282221


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Alexandre CarrierPhantoms (Phi)D201996-10-08No174 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm640,000$64,000$0$NoLien
Austin PoganskiPhantoms (Phi)RW211996-02-16Yes198 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Brandon HalversonPhantoms (Phi)G211996-05-29Yes209 Lbs6 ft4NoNoNo2Contrat d'EntréePro & Farm743,000$74,300$0$NoLien
Brandon KozunPhantoms (Phi)RW271990-03-08No167 Lbs5 ft8NoYesNo1Avec RestrictionPro & Farm550,000$55,000$0$NoLien
Brian FerlinPhantoms (Phi)RW251992-06-03No209 Lbs6 ft2NoYesNo1Avec RestrictionPro & Farm825,000$82,500$0$NoLien
Christoffer EhnPhantoms (Phi)C211996-04-05Yes181 Lbs6 ft3NoNoNo2Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Connor BunnamanPhantoms (Phi)C191998-04-16Yes214 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm730,000$73,000$0$NoLien
Dennis YanPhantoms (Phi)LW201997-04-14Yes202 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Dillon SimpsonPhantoms (Phi)D241993-02-10Yes194 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm843,000$84,300$0$NoLien
Dwight KingPhantoms (Phi)LW281989-07-05No229 Lbs6 ft4NoNoNo1Sans RestrictionPro & Farm500,000$50,000$0$NoLien
Emerson EtemPhantoms (Phi)LW/RW251992-06-16No212 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm550,000$55,000$0$NoLien
Fredrik BergvikPhantoms (Phi)G221995-02-14Yes189 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Haydn FleuryPhantoms (Phi)D211996-07-08Yes221 Lbs6 ft3NoNoNo2Contrat d'EntréePro & Farm925,000$92,500$0$NoLien
Jake EvansPhantoms (Phi)C/RW211996-06-02Yes188 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Jordy StallardPhantoms (Phi)C201997-09-18Yes185 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Jyrki JokipakkaPhantoms (Phi)D261991-08-20No215 Lbs6 ft3NoYesNo1Avec RestrictionPro & Farm728,000$72,800$0$NoLien
Marko DanoPhantoms (Phi)LW/RW221994-11-30No212 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm925,000$92,500$0$NoLien
Martins DzierkalsPhantoms (Phi)RW201997-04-04Yes173 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Matt GrzelcykPhantoms (Phi)D231994-01-05Yes174 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Maxim ChudinovPhantoms (Phi)D271990-03-25No187 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Michael AmadioPhantoms (Phi)C211996-05-13Yes204 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm700,000$70,000$0$NoLien
Michael MerschPhantoms (Phi)LW251992-10-02No218 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm792,000$79,200$0$NoLien
Michael PaliottaPhantoms (Phi)D241993-04-06No207 Lbs6 ft3NoYesNo1Avec RestrictionPro & Farm925,000$92,500$0$NoLien
Nail YakupovPhantoms (Phi)LW/RW231993-10-06No195 Lbs5 ft11NoYesNo2Avec RestrictionPro & Farm1,400,000$140,000$0$NoLien
Nicholas MerkleyPhantoms (Phi)C/RW201997-05-23No194 Lbs5 ft10NoNoNo3Contrat d'EntréePro & Farm895,000$89,500$0$NoLien
Oskar SundqvistPhantoms (Phi)C231994-03-23No209 Lbs6 ft3NoYesNo2Avec RestrictionPro & Farm667,000$66,700$0$NoLien
Philippe DesrosiersPhantoms (Phi)G221995-08-15Yes182 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm642,000$64,200$0$NoLien
Roope HintzPhantoms (Phi)LW201996-11-17Yes185 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm825,000$82,500$0$NoLien
Sebastian CollbergPhantoms (Phi)LW/RW231994-02-23Yes180 Lbs5 ft11NoYesNo2Avec RestrictionPro & Farm925,000$92,500$0$NoLien
Sebastien AhoPhantoms (Phi)D211996-02-17Yes170 Lbs5 ft10NoNoNo2Contrat d'EntréePro & Farm825,000$82,500$0$NoLien
Sergei BoikovPhantoms (Phi)D211996-01-24Yes200 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm705,000$70,500$0$NoLien
Tyler BensonPhantoms (Phi)LW191998-03-15Yes190 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm792,500$79,250$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3222.34196 Lbs6 ft12.34739,922$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nail YakupovOskar SundqvistMarko Dano40122
2Dwight KingMichael AmadioNicholas Merkley30122
3Michael MerschTyler BensonRoope Hintz20122
4Tyler BensonNail YakupovDwight King10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykJyrki Jokipakka40122
2Haydn FleurySebastien Aho30122
3Alexandre CarrierMichael Paliotta20122
4Dillon SimpsonMatt Grzelcyk10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Nail YakupovOskar SundqvistMarko Dano60122
2Dwight KingMichael AmadioNicholas Merkley40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykJyrki Jokipakka60122
2Haydn FleurySebastien Aho40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Nail YakupovDwight King60122
2Oskar SundqvistMarko Dano40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykJyrki Jokipakka60122
2Haydn FleurySebastien Aho40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Nail Yakupov60122Matt GrzelcykJyrki Jokipakka60122
2Dwight King40122Haydn FleurySebastien Aho40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Nail YakupovDwight King60122
2Oskar SundqvistMarko Dano40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykJyrki Jokipakka60122
2Haydn FleurySebastien Aho40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nail YakupovOskar SundqvistMarko DanoMatt GrzelcykJyrki Jokipakka
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Nail YakupovOskar SundqvistMarko DanoMatt GrzelcykJyrki Jokipakka
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Mersch, Roope Hintz, Michael AmadioMichael Mersch, Roope HintzMichael Amadio
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Alexandre Carrier, Michael Paliotta, Dillon SimpsonAlexandre CarrierMichael Paliotta, Dillon Simpson
Tirs de Pénalité
Nail Yakupov, Dwight King, Oskar Sundqvist, Marko Dano, Michael Amadio
Gardien
#1 : Brandon Halverson, #2 : Philippe Desrosiers


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
1Admirals220000001192110000006511100000054141.0001119300011978751155736681697666319122911436.36%6266.67%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
2Baby Hawks21100000651110000005231010000013-220.50061117001197875114573668169766511640286233.33%16381.25%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
3Bears413000001113-2211000007702020000046-220.250112031001197875111007366816976612233307021314.29%15566.67%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
4Bruins3100100110821000000112-12100100096350.83310192900119787511567366816976662201845800.00%9188.89%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
5Cabaret Lady Mary Ann31200000710-32020000048-41100000032120.33371320001197875111147366816976612039437317317.65%18477.78%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
6Caroline42100001181442100000110912110000085350.62518325000119787511151736681697668729287426726.92%13469.23%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
7Chiefs220000001183110000006511100000053241.000111829001197875115073668169766551316319333.33%8275.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
8Chill2020000069-31010000034-11010000035-200.0006111700119787511547366816976649920368225.00%10280.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
9Comets22000000844110000005231100000032141.000813210011978751154736681697665219203210110.00%10190.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
10Cougars31100001111102010000168-21100000053230.5001119300011978751192736681697669730244517529.41%11281.82%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
11Crunch321000001174110000006242110000055040.6671120310011978751194736681697666823105512650.00%5340.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
12Heat21100000945110000006061010000034-120.50091625011197875116273668169766461317345240.00%6183.33%21222236851.60%1194240249.71%693138650.00%1963130118896301119574
13Jayhawks20200000711-41010000046-21010000035-200.00071118001197875113973668169766751818395240.00%9455.56%11222236851.60%1194240249.71%693138650.00%1963130118896301119574
14Las Vegas2020000049-51010000025-31010000024-200.000481200119787511357366816976658818369333.33%9544.44%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
15Manchots4210000110100210000015412110000056-150.6251017270111978751177736681697668228316715320.00%11281.82%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
16Marlies30300000815-71010000045-120200000410-600.0008142200119787511577366816976610330265911654.55%13469.23%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
17Minnesota2110000078-11010000024-21100000054120.50071219001197875114673668169766351010236233.33%5260.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
18Monarchs20200000710-31010000034-11010000046-200.00071118001197875115373668169766772315307342.86%5180.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
19Monsters404000001219-72020000069-320200000610-400.00012203200119787511677366816976612927347019210.53%17758.82%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
20Monsters20200000214-121010000027-51010000007-700.00024600119787511577366816976683201336800.00%4325.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
21Oceanics20200000611-51010000056-11010000015-400.00061016001197875115473668169766761918366116.67%9633.33%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
22Oil Kings22000000945110000005141100000043141.00091423001197875114373668169766531839379111.11%11281.82%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
23Rocket320001001192110000005322100010066050.8331120310011978751177736681697666326264220630.00%130100.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
24Senators320010001275210010007341100000054161.000121931001197875117773668169766712120519111.11%9188.89%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
25Sharks20100010710-31010000037-41000001043120.500710170011978751179736681697667629213914214.29%8275.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
26Sound Tigers421000101293211000005502100001074360.750122032001197875119173668169766893433821516.67%9188.89%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
27Spiders403000101218-620100010810-22020000048-420.250121729001197875111017366816976615632428017423.53%20575.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
28Stars210000018711000000145-11100000042230.7508152300119787511617366816976641816269444.44%7271.43%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
29Thunder31200000612-6211000006511010000007-720.3336101600119787511587366816976698273758900.00%16287.50%11222236851.60%1194240249.71%693138650.00%1963130118896301119574
Total82304002136277306-2941151901015149152-341152101121128154-26770.47027747675302119787511214673668169766236667273214433578323.25%3128273.72%41222236851.60%1194240249.71%693138650.00%1963130118896301119574
31Wolf Pack412000011821-32110000089-1201000011012-230.375183351001197875111477366816976612931378019421.05%10370.00%01222236851.60%1194240249.71%693138650.00%1963130118896301119574
_Since Last GM Reset82304002136277306-2941151901015149152-341152101121128154-26770.47027747675302119787511214673668169766236667273214433578323.25%3128273.72%41222236851.60%1194240249.71%693138650.00%1963130118896301119574
_Vs Conference46122602033148181-3323712010127785-823514010217196-25370.4021482503980111978751111267366816976613823823948321893619.05%1674473.65%11222236851.60%1194240249.71%693138650.00%1963130118896301119574
_Vs Division283100002193104-111425000104953-41415000114451-7110.1969315925201119787511734736681697667942142355231322418.18%952771.58%01222236851.60%1194240249.71%693138650.00%1963130118896301119574

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8277SOL127747675321462366672732144302
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8230402136277306
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4115191015149152
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4115211121128154
Derniers 10 Matchs
WLOTWOTL SOWSOL
450001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3578323.25%3128273.72%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
73668169766119787511
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
1222236851.60%1194240249.71%693138650.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1963130118896301119574


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
2 - 2018-10-0414Phantoms2Las Vegas4LSommaire du Match
4 - 2018-10-0627Phantoms0Monsters7LSommaire du Match
7 - 2018-10-0936Sharks7Phantoms3LSommaire du Match
8 - 2018-10-1042Phantoms5Senators4WSommaire du Match
11 - 2018-10-1358Las Vegas5Phantoms2LSommaire du Match
14 - 2018-10-1680Cabaret Lady Mary Ann6Phantoms3LSommaire du Match
16 - 2018-10-1892Phantoms2Monsters5LSommaire du Match
18 - 2018-10-20102Spiders5Phantoms2LSommaire du Match
20 - 2018-10-22118Monsters7Phantoms2LSommaire du Match
23 - 2018-10-25134Phantoms5Bruins4WXSommaire du Match
25 - 2018-10-27149Sound Tigers3Phantoms2LSommaire du Match
28 - 2018-10-30176Phantoms5Admirals4WSommaire du Match
30 - 2018-11-01190Phantoms4Monarchs6LSommaire du Match
32 - 2018-11-03206Phantoms4Sharks3WXXSommaire du Match
34 - 2018-11-05214Phantoms3Jayhawks5LSommaire du Match
37 - 2018-11-08229Jayhawks6Phantoms4LSommaire du Match
39 - 2018-11-10243Baby Hawks2Phantoms5WSommaire du Match
42 - 2018-11-13267Cabaret Lady Mary Ann2Phantoms1LSommaire du Match
44 - 2018-11-15278Spiders5Phantoms6WXXSommaire du Match
46 - 2018-11-17293Thunder4Phantoms2LSommaire du Match
50 - 2018-11-21318Phantoms3Crunch2WSommaire du Match
52 - 2018-11-23332Wolf Pack4Phantoms5WSommaire du Match
53 - 2018-11-24349Phantoms3Marlies4LSommaire du Match
56 - 2018-11-27368Senators2Phantoms3WXSommaire du Match
60 - 2018-12-01403Phantoms4Manchots2WSommaire du Match
65 - 2018-12-06431Monsters4Phantoms2LSommaire du Match
67 - 2018-12-08444Phantoms2Crunch3LSommaire du Match
68 - 2018-12-09455Phantoms1Oceanics5LSommaire du Match
71 - 2018-12-12477Phantoms3Heat4LSommaire du Match
73 - 2018-12-14494Phantoms4Oil Kings3WSommaire du Match
74 - 2018-12-15504Phantoms3Comets2WSommaire du Match
77 - 2018-12-18520Cougars4Phantoms3LXXSommaire du Match
79 - 2018-12-20532Chill4Phantoms3LSommaire du Match
81 - 2018-12-22546Monsters5Phantoms4LSommaire du Match
82 - 2018-12-23562Phantoms5Wolf Pack6LXXSommaire du Match
86 - 2018-12-27571Phantoms0Thunder7LSommaire du Match
88 - 2018-12-29591Phantoms3Cabaret Lady Mary Ann2WSommaire du Match
90 - 2018-12-31603Phantoms7Caroline3WSommaire du Match
91 - 2019-01-01613Phantoms3Chill5LSommaire du Match
93 - 2019-01-03625Caroline3Phantoms5WSommaire du Match
95 - 2019-01-05636Heat0Phantoms6WSommaire du Match
97 - 2019-01-07653Chiefs5Phantoms6WSommaire du Match
98 - 2019-01-08661Phantoms2Bears3LSommaire du Match
100 - 2019-01-10674Stars5Phantoms4LXXSommaire du Match
102 - 2019-01-12687Phantoms2Spiders5LSommaire du Match
104 - 2019-01-14708Minnesota4Phantoms2LSommaire du Match
106 - 2019-01-16722Bruins2Phantoms1LXXSommaire du Match
109 - 2019-01-19745Phantoms3Rocket4LXSommaire du Match
118 - 2019-01-28771Oceanics6Phantoms5LSommaire du Match
119 - 2019-01-29774Phantoms5Wolf Pack6LSommaire du Match
121 - 2019-01-31778Phantoms4Bruins2WSommaire du Match
123 - 2019-02-02789Oil Kings1Phantoms5WSommaire du Match
125 - 2019-02-04807Comets2Phantoms5WSommaire du Match
128 - 2019-02-07826Monarchs4Phantoms3LSommaire du Match
130 - 2019-02-09842Admirals5Phantoms6WSommaire du Match
132 - 2019-02-11860Manchots4Phantoms3LXXSommaire du Match
133 - 2019-02-12871Phantoms5Minnesota4WSommaire du Match
137 - 2019-02-16892Cougars4Phantoms3LSommaire du Match
138 - 2019-02-17907Phantoms5Cougars3WSommaire du Match
140 - 2019-02-19918Thunder1Phantoms4WSommaire du Match
142 - 2019-02-21934Phantoms3Rocket2WSommaire du Match
144 - 2019-02-23953Manchots0Phantoms2WSommaire du Match
147 - 2019-02-26970Crunch2Phantoms6WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
149 - 2019-02-28986Phantoms4Monsters5LSommaire du Match
150 - 2019-03-01992Phantoms2Spiders3LSommaire du Match
152 - 2019-03-031010Phantoms3Sound Tigers1WSommaire du Match
155 - 2019-03-061029Bears1Phantoms4WSommaire du Match
158 - 2019-03-091053Phantoms4Sound Tigers3WXXSommaire du Match
160 - 2019-03-111067Senators1Phantoms4WSommaire du Match
163 - 2019-03-141085Bears6Phantoms3LSommaire du Match
164 - 2019-03-151093Phantoms1Marlies6LSommaire du Match
166 - 2019-03-171115Phantoms1Manchots4LSommaire du Match
168 - 2019-03-191125Rocket3Phantoms5WSommaire du Match
170 - 2019-03-211142Phantoms1Baby Hawks3LSommaire du Match
172 - 2019-03-231151Sound Tigers2Phantoms3WSommaire du Match
173 - 2019-03-241164Phantoms2Bears3LSommaire du Match
176 - 2019-03-271185Marlies5Phantoms4LSommaire du Match
179 - 2019-03-301203Phantoms1Caroline2LSommaire du Match
180 - 2019-03-311215Wolf Pack5Phantoms3LSommaire du Match
182 - 2019-04-021235Phantoms4Stars2WSommaire du Match
184 - 2019-04-041248Phantoms5Chiefs3WSommaire du Match
186 - 2019-04-061263Caroline6Phantoms5LXXSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance61,04431,217
Assistance PCT74.44%76.14%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2250 - 75.01% 63,532$2,604,795$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,218,880$ 2,367,750$ 2,367,750$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
12,662$ 2,218,880$ 32 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 12,662$ 0$




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
201882304002136277306-2941151901015149152-341152101121128154-267727747675302119787511214673668169766236667273214433578323.25%3128273.72%41222236851.60%1194240249.71%693138650.00%1963130118896301119574
Total Saison Régulière82304002136277306-2941151901015149152-341152101121128154-267727747675302119787511214673668169766236667273214433578323.25%3128273.72%41222236851.60%1194240249.71%693138650.00%1963130118896301119574