Snipers
GP: 82 | W: 44 | L: 29 | T: 3 | P: 97
GF: 278 | GA: 261 | PP%: 15.57% | PK%: 80.56%
DG: Farlou Ferland | Morale : 60 | Moyenne d'Équipe : 64
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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
1Kevin MillerX100.005639846773767970677571786755604636680291435,000$
2Bobby Smith (A)X100.00574773617869736964686680659094180680363694,000$
3Michael Peca (R)X100.005647677470676777677772856427319869670203480,000$
4Todd KrygierX100.007552757070757375677571686641524782670292475,000$
5Rob ZamunerX100.006550777277777867647373797030407562670252625,000$
6Alexandre Daigle (R)X99.005644747462757278617776587535358880660193250,000$
7Bob KudelskiX100.006348766574737670657164776245444155650303511,000$
8Evgeny DavydovX100.006748786871707270656674687041355430640282575,000$
9Brian LawtonX100.006353646371636465637070666752484573630293410,000$
10Dave ChyzowskiX100.007360606675676863606564726241439078620233386,000$
11Mike Knuble (R)X100.005646716778707059556259685626359766590222200,000$
12Rene Corbet (R)X100.005648647072686858566357675429299676590212285,000$
13Mikhail TatarinovX100.006145776574737375667864825758615480680282480,000$
14Chris Dahlquist (C)X100.006243856072838259566446824570772480670321300,000$
15Roger JohanssonX100.007151736776727264706560805858446182660273532,000$
16Bill HoulderX100.007049756376777865586460775551595982660273450,000$
17Brad ShawX100.006748806772737561606852795058643881660303675,000$
18Jim Kyte (A)X100.007368536179677154525642814063654185640301620,000$
Rayé
1Mike HoughX100.006852696774717376687574666859663378680312482,500$
2Jan ErixonX100.006035966472747371646863856052672220670322495,000$
3Wayne PresleyX100.006255666871727571667270656837474820650293514,000$
4Paul KruseX100.007572416774646759576661755831318320610241200,000$
5Sean ProngerX100.006050756876656663596563686028349620610222300,000$
6Ben HankinsonX100.006661606876666762596463746229297420610251417,000$
7Viktor GordioukX100.005245747369666664586665596431288220600242275,000$
8Craig Darby (R)X100.006348826872606261576360605836369619590222225,000$
9Craig WolaninX100.007960676578777856525856745352575920650273543,000$
10Brian GlynnX100.006848816667767852516058815637446220640271370,000$
MOYENNE D'ÉQUIPE99.96645072677371726661686373604548615564
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
1Robb Stauber100.00717673727168818176717251546024690
2Geoff Sarjeant100.00697276737556696663726838427526630
Rayé
1Chad Erickson100.00687271716937606855655826358238570
MOYENNE D'ÉQUIPE100.0069737372725470726569663844722963
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Lou Lamoriello75756981828265USA52295,000$


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
1Alexandre DaigleSnipers (EDM)RW823448829340761172458715513.88%7163319.9281523733980000976347.28%18400011.0000000529
2Bob KudelskiSnipers (EDM)C8033467983551262091824311618.13%11158719.85722294737810141294252.35%206300001.0000010763
3Rob ZamunerSnipers (EDM)LW812649751241151431282477817610.53%16158919.621015257038101131093150.00%16400000.9400030594
4Mikhail TatarinovSnipers (EDM)D81144862-1836052149149591159.40%84174921.609162594390000063110.00%000000.7100000412
5Bobby SmithSnipers (EDM)C82223254-93801011942015214910.95%7151818.52717246434610181972253.98%176000000.7100000352
6Bill HoulderSnipers (EDM)D82104252491514910313247817.58%85182822.3071118923880000241010.00%000000.5700100122
7Todd KrygierSnipers (EDM)LW8224214575351081311794213013.41%13102612.520005250002671351.79%36300000.8800100322
8Kevin MillerSnipers (EDM)RW6224143806042991603914415.00%13105717.0594134722010161884553.55%15500000.7200000522
9Jim KyteSnipers (EDM)D791226387168402154074225216.22%72160620.34641051345000094300.00%000000.4700413120
10Chris DahlquistSnipers (EDM)D8282937734078738719769.20%105187122.8241115573740110235300.00%000000.4000000213
11Roger JohanssonSnipers (EDM)D82726331895151429054173112.96%100144617.640226410000264100.00%000000.4600002222
12Rene CorbetSnipers (EDM)LW7992130-43601006212031847.50%6135517.161672625800031632043.33%9000100.4400000021
13Michael PecaSnipers (EDM)C3516102611203386115328513.91%1371620.464593214601121265248.24%71100100.7300000231
14Brad ShawSnipers (EDM)D822222454357467349225.88%77134216.380001210113261000.00%000000.3600001130
15Mike KnubleSnipers (EDM)RW79914237120173560255015.00%590611.47000016000031150.00%5600000.5100000100
16Brian LawtonSnipers (EDM)C82715224415621048525508.24%38179.97000016000021050.50%80600000.5400100200
17Mike HoughSnipers (EDM)RW81128203220295481186014.81%45897.280002150112145050.00%4400000.6800000013
18Dave ChyzowskiSnipers (EDM)LW816101653005446719368.45%35586.90000213000020043.55%6200000.5700000002
19Sean ProngerSnipers (EDM)C381780401027238174.35%52606.8600015000191046.60%29400000.6100000000
20Evgeny DavydovSnipers (EDM)LW173584100141323111313.04%326815.791347560002450052.38%2100000.6000000011
21Craig DarbySnipers (EDM)C19123-82012913097.69%028815.16112976000061061.67%6000000.2100000000
22Grant LedyardOilersD1033220010000.00%01414.070000000001000.00%000004.2700000000
23Paul KruseSnipers (EDM)LW1000000000000.00%011.570000000001000.00%000000.0000000000
24Wayne PresleySnipers (EDM)RW3000020425230.00%03712.4800000000020050.00%400000.0000000000
25Craig WolaninSnipers (EDM)D3000360501010.00%04314.440000000004000.00%000000.0000000000
26Jan ErixonSnipers (EDM)LW3000000106390.00%13913.3100000000010050.00%400000.0000000000
Stats d'équipe Total ou en Moyenne14792804987786785395164718392347678166411.93%6332415616.33741322066863918358362338442151.53%684100210.6400756444439
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
1Geoff SarjeantSnipers (EDM)67332730.8743.2437196020115910220.00006616412
2Robb StauberSnipers (EDM)1611500.9022.2795021363670010.00001610001
3Chad EricksonSnipers (EDM)110300.8654.4528300211560000.0000056000
Stats d'équipe Total ou en Moyenne94443530.8783.1349528125821140230.00008282413


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 Cap 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
Alexandre DaigleSnipers (EDM)RW192001-08-11 9:18:49 AMYes200 Lbs6 ft0NoNoNo3Pro & Farm250,000$25,000$184$No250,000$250,000$
Ben HankinsonSnipers (EDM)RW251996-02-09 9:08:37 PMNo210 Lbs6 ft2NoNoNo1Pro & Farm417,000$41,700$307$No
Bill HoulderSnipers (EDM)D271994-02-09 9:08:37 PMNo210 Lbs6 ft2NoNoNo3Pro & Farm450,000$45,000$331$No450,000$450,000$
Bob KudelskiSnipers (EDM)C301991-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo3Pro & Farm511,000$51,100$376$No511,000$511,000$
Bobby SmithSnipers (EDM)C361985-02-09 9:08:37 PMNo210 Lbs6 ft4NoNoNo3Pro & Farm694,000$69,400$510$No694,000$694,000$
Brad ShawSnipers (EDM)D301991-02-09 9:08:37 PMNo190 Lbs6 ft0NoNoNo3Pro & Farm675,000$67,500$496$No675,000$675,000$
Brian GlynnSnipers (EDM)D271994-02-09 9:08:37 PMNo165 Lbs5 ft10NoNoNo1Pro & Farm370,000$37,000$272$No
Brian LawtonSnipers (EDM)C291992-02-09 9:08:37 PMNo180 Lbs6 ft0NoNoNo3Pro & Farm410,000$41,000$301$No410,000$410,000$
Chad EricksonSnipers (EDM)G241997-02-09 9:08:37 PMNo176 Lbs5 ft9NoNoNo3Pro & Farm150,000$15,000$110$No150,000$150,000$
Chris DahlquistSnipers (EDM)D321989-02-09 9:08:37 PMNo195 Lbs6 ft1NoNoNo1Pro & Farm300,000$30,000$221$No
Craig DarbySnipers (EDM)C221999-02-09 9:08:37 PMYes200 Lbs6 ft3NoNoNo2Pro & Farm225,000$22,500$165$No225,000$
Craig WolaninSnipers (EDM)D271994-02-09 9:08:37 PMNo207 Lbs6 ft3NoNoNo3Pro & Farm543,000$54,300$399$No543,000$543,000$
Dave ChyzowskiSnipers (EDM)LW231998-02-09 9:08:37 PMNo200 Lbs6 ft1NoNoNo3Pro & Farm386,000$38,600$284$No386,000$386,000$
Evgeny DavydovSnipers (EDM)LW281993-02-09 9:08:37 PMNo183 Lbs6 ft0NoNoNo2Pro & Farm575,000$57,500$423$No575,000$
Geoff SarjeantSnipers (EDM)G251996-02-09 9:08:37 PMNo180 Lbs5 ft9NoNoNo2Pro & Farm325,000$32,500$239$No325,000$
Jan ErixonSnipers (EDM)LW321989-02-09 9:08:37 PMNo196 Lbs6 ft0NoNoNo2Pro & Farm495,000$49,500$364$No495,000$
Jim KyteSnipers (EDM)D301991-02-09 9:08:37 PMNo211 Lbs6 ft5NoNoNo1Pro & Farm620,000$62,000$456$No
Kevin MillerSnipers (EDM)RW291992-02-09 9:08:37 PMNo190 Lbs5 ft11NoNoNo1Pro & Farm435,000$43,500$320$No
Michael PecaSnipers (EDM)C202001-02-09 9:08:37 PMYes181 Lbs5 ft11NoNoNo3Pro & Farm480,000$480,000$3,529$No480,000$480,000$
Mike HoughSnipers (EDM)RW311990-02-09 9:08:37 PMNo192 Lbs6 ft1NoNoNo2Pro & Farm482,500$48,250$355$No482,500$
Mike KnubleSnipers (EDM)RW221999-02-09 9:08:37 PMYes215 Lbs6 ft3NoNoNo2Pro & Farm200,000$20,000$147$No200,000$
Mikhail TatarinovSnipers (EDM)D281993-02-09 9:08:37 PMNo195 Lbs6 ft0NoNoNo2Pro & Farm480,000$48,000$353$No480,000$
Paul KruseSnipers (EDM)LW241997-02-09 9:08:37 PMNo202 Lbs6 ft0NoNoNo1Pro & Farm200,000$20,000$147$No
Rene CorbetSnipers (EDM)LW212000-02-09 9:08:37 PMYes187 Lbs6 ft0NoNoNo2Pro & Farm285,000$28,500$210$No285,000$
Rob ZamunerSnipers (EDM)LW251996-02-09 9:08:37 PMNo203 Lbs6 ft3NoNoNo2Pro & Farm625,000$62,500$460$No625,000$
Robb StauberSnipers (EDM)G271994-02-09 9:08:37 PMNo170 Lbs6 ft0NoNoNo3Pro & Farm425,000$42,500$312$No425,000$425,000$
Roger JohanssonSnipers (EDM)D271994-02-09 9:08:37 PMNo193 Lbs6 ft4NoNoNo3Pro & Farm532,000$53,200$391$No532,000$532,000$
Sean ProngerSnipers (EDM)C221999-02-09 9:08:37 PMNo202 Lbs6 ft3NoNoNo2Pro & Farm300,000$30,000$221$No300,000$
Todd KrygierSnipers (EDM)LW291992-02-09 9:08:37 PMNo180 Lbs5 ft11NoNoNo2Pro & Farm475,000$47,500$349$No475,000$
Viktor GordioukSnipers (EDM)LW241997-02-09 9:08:37 PMNo178 Lbs5 ft10NoNoNo2Pro & Farm275,000$27,500$202$No275,000$
Wayne PresleySnipers (EDM)RW291992-02-09 9:08:37 PMNo180 Lbs5 ft11NoNoNo3Pro & Farm514,000$51,400$378$No514,000$514,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3126.58193 Lbs6 ft12.23422,726$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Rob ZamunerBob KudelskiAlexandre Daigle35032
2Bobby SmithMichael PecaKevin Miller30032
3Rene CorbetTodd KrygierMike Knuble25032
4Dave ChyzowskiBrian LawtonEvgeny Davydov10032
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Roger JohanssonChris Dahlquist38032
2Bill HoulderMikhail Tatarinov35032
3Brad ShawJim Kyte27032
4Jim KyteMikhail Tatarinov0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Michael PecaBob KudelskiAlexandre Daigle60005
2Rob ZamunerBobby SmithKevin Miller40005
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Bill HoulderMikhail Tatarinov60005
2Jim KyteChris Dahlquist40005
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Michael PecaEvgeny Davydov60050
2Bobby SmithRene Corbet40050
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brad ShawRoger Johansson51140
2Jim KyteBill Houlder49140
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Evgeny Davydov52050Brad ShawRoger Johansson54050
2Bobby Smith48050Jim KyteBill Houlder46050
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Michael PecaAlexandre Daigle53032
2Bob KudelskiRob Zamuner47032
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Bill HoulderMikhail Tatarinov54032
2Jim KyteChris Dahlquist46032
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Rob ZamunerMichael PecaAlexandre DaigleBill HoulderMikhail Tatarinov
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Rob ZamunerBob KudelskiMichael PecaJim KyteMikhail Tatarinov
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Peca, Rob Zamuner, Alexandre DaigleMichael Peca, Rob ZamunerAlexandre Daigle
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mikhail Tatarinov, Roger Johansson, Chris DahlquistMikhail TatarinovRoger Johansson, Chris Dahlquist
Tirs de Pénalité
Alexandre Daigle, Evgeny Davydov, Kevin Miller, Bobby Smith, Brian Lawton
Gardien
#1 : Robb Stauber, #2 : Geoff Sarjeant


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
1Ailes Rouges54100000151323300000010552110000058-380.80015284300109778931657707707742112734441242229.09%22386.36%11513287052.72%1266250650.52%688133551.54%2010135818706391081546
2As530002002216621000100761320001001510580.800224163001097789315677077077421131354082381026.32%18288.89%01513287052.72%1266250650.52%688133551.54%2010135818706391081546
3Banshees715001001326-1330300000815-741200100511-630.214132437001097789315977077077421172646713433618.18%331069.70%01513287052.72%1266250650.52%688133551.54%2010135818706391081546
4Canadiens642000002517843100000171162110000086280.667254772101097789317077077077421148385210137821.62%20575.00%01513287052.72%1266250650.52%688133551.54%2010135818706391081546
5Chiefs512011001419-52010010058-331101000911-250.50014223600109778931457707707742112334499426311.54%20575.00%11513287052.72%1266250650.52%688133551.54%2010135818706391081546
6Citadelles84120100262155212000015141320001001174110.688264470001097789321877077077421205616519251611.76%29582.76%01513287052.72%1266250650.52%688133551.54%2010135818706391081546
7Croque-Morts523000001720-331200000912-32110000088040.40017314800109778931677707707742112939438326519.23%17570.59%01513287052.72%1266250650.52%688133551.54%2010135818706391081546
8Harvard72311000262513120000012102411110001415-170.500264975001097789319677077077421172535715435720.00%23769.57%01513287052.72%1266250650.52%688133551.54%2010135818706391081546
9Isotopes5500000020614330000001421222000000642101.00020325201109778931587707707742113237649321419.05%25484.00%01513287052.72%1266250650.52%688133551.54%2010135818706391081546
10Pacifiques de la route1164001004141053200000212106320010020200130.591416810900109778933367707707742130184149224731115.07%55885.45%11513287052.72%1266250650.52%688133551.54%2010135818706391081546
11Riverman86200000322394310000017152431000001587120.7503261930010977893215770770774211916511218358813.79%49785.71%01513287052.72%1266250650.52%688133551.54%2010135818706391081546
12Spoonman's523000001419-52200000075230300000714-740.400142741201097789311977077077421146294710327311.11%18666.67%01513287052.72%1266250650.52%688133551.54%2010135818706391081546
13Wolves513010001315-2211000009633020100049-540.4001322350010977893131770770774211405672792200.00%31390.32%01513287052.72%1266250650.52%688133551.54%2010135818706391081546
Total8241293360027826117412314202001511302141181513400127131-4970.5912784967743110977893233577077077421211762986116464697315.57%3607080.56%31513287052.72%1266250650.52%688133551.54%2010135818706391081546
_Since Last GM Reset82442903600278261174123142020015113021412115-23400127131-41000.6102784967743110977893233577077077421211762986116464697315.57%3607080.56%31513287052.72%1266250650.52%688133551.54%2010135818706391081546
_Vs Conference3922130130014012812191260010073658201070120067634490.628140251391001097789311707707707742110193134607752393615.06%1922885.42%21513287052.72%1266250650.52%688133551.54%2010135818706391081546
_Vs Division191260010073649963000003836210630010035287250.658731292020010977893551770770774214921492614071311914.50%1041585.58%11513287052.72%1266250650.52%688133551.54%2010135818706391081546

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8297W227849677423352117629861164631
Tous les Matchs
GPWLOTWOTL TGFGA
824129363278261
Matchs locaux
GPWLOTWOTL TGFGA
412314022151130
Matchs Éxtérieurs
GPWLOTWOTL TGFGA
411815341127131
Derniers 10 Matchs
WLOTWOTL T
64000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4697315.57%3607080.56%3
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
7707707742110977893
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
1513287052.72%1266250650.52%688133551.54%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2010135818706391081546


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 - 2020-09-216Snipers5Harvard5TXSommaire du Match
2 - 2020-09-227Snipers4Pacifiques de la route5LXSommaire du Match
3 - 2020-09-2313Citadelles2Snipers2TXSommaire du Match
5 - 2020-09-2525Pacifiques de la route2Snipers3WSommaire du Match
6 - 2020-09-2631Snipers3Pacifiques de la route1WSommaire du Match
7 - 2020-09-2736Pacifiques de la route5Snipers6WSommaire du Match
9 - 2020-09-2944Snipers4Pacifiques de la route3WSommaire du Match
10 - 2020-09-3047Snipers1Riverman2LR2Sommaire du Match
11 - 2020-10-0154Riverman2Snipers3WSommaire du Match
13 - 2020-10-0364Pacifiques de la route4Snipers3LSommaire du Match
15 - 2020-10-0569Snipers0Banshees3LSommaire du Match
17 - 2020-10-0778Harvard2Snipers7WSommaire du Match
19 - 2020-10-0984Snipers4Banshees3WSommaire du Match
21 - 2020-10-1190Snipers0Wolves3LSommaire du Match
23 - 2020-10-1396Canadiens4Snipers6WSommaire du Match
25 - 2020-10-15105Snipers4Pacifiques de la route2WSommaire du Match
27 - 2020-10-17110Snipers8As3WSommaire du Match
29 - 2020-10-19117Pacifiques de la route7Snipers4LSommaire du Match
31 - 2020-10-21124Chiefs6Snipers4LSommaire du Match
33 - 2020-10-23134Snipers2Ailes Rouges1WSommaire du Match
35 - 2020-10-25139Banshees5Snipers3LSommaire du Match
37 - 2020-10-27149Wolves5Snipers4LSommaire du Match
39 - 2020-10-29154Snipers2Chiefs7LSommaire du Match
41 - 2020-10-31161Snipers5Pacifiques de la route7LSommaire du Match
42 - 2020-11-01167Canadiens3Snipers1LSommaire du Match
44 - 2020-11-03173Snipers6Canadiens3WSommaire du Match
46 - 2020-11-05182Harvard3Snipers2LSommaire du Match
47 - 2020-11-06190Ailes Rouges2Snipers4WSommaire du Match
49 - 2020-11-08196Snipers4As5LXSommaire du Match
50 - 2020-11-09205Snipers3As2WSommaire du Match
52 - 2020-11-11208Citadelles1Snipers3WSommaire du Match
53 - 2020-11-12217Snipers1Harvard5LSommaire du Match
55 - 2020-11-14220Snipers6Riverman2WR2Sommaire du Match
56 - 2020-11-15227Spoonman's2Snipers3WSommaire du Match
58 - 2020-11-17236Riverman4Snipers5WR2Sommaire du Match
60 - 2020-11-19246Snipers4Chiefs2WSommaire du Match
61 - 2020-11-20249Riverman3Snipers6WR2Sommaire du Match
62 - 2020-11-21260Snipers0Pacifiques de la route2LSommaire du Match
64 - 2020-11-23262Isotopes1Snipers3WSommaire du Match
66 - 2020-11-25274Snipers1Banshees2LXSommaire du Match
67 - 2020-11-26279Canadiens3Snipers7WSommaire du Match
68 - 2020-11-27288As3Snipers2LXSommaire du Match
70 - 2020-11-29290Snipers4Isotopes3WSommaire du Match
71 - 2020-11-30299Snipers3Spoonman's5LSommaire du Match
73 - 2020-12-02307Banshees5Snipers2LSommaire du Match
74 - 2020-12-03316Snipers0Banshees3LSommaire du Match
75 - 2020-12-04320Citadelles5Snipers3LSommaire du Match
77 - 2020-12-06329Snipers4Croque-Morts7LSommaire du Match
78 - 2020-12-07333Citadelles4Snipers4TXSommaire du Match
79 - 2020-12-08344Harvard5Snipers3LSommaire du Match
80 - 2020-12-09350Snipers3Chiefs2WXSommaire du Match
83 - 2020-12-12357Snipers4Riverman3WR2Sommaire du Match
84 - 2020-12-13364Spoonman's3Snipers4WSommaire du Match
86 - 2020-12-15372Snipers3Ailes Rouges7LSommaire du Match
88 - 2020-12-17377Croque-Morts5Snipers1LSommaire du Match
90 - 2020-12-19381Snipers2Spoonman's5LSommaire du Match
92 - 2020-12-21388Ailes Rouges1Snipers3WSommaire du Match
94 - 2020-12-23396Snipers3Citadelles4LXSommaire du Match
96 - 2020-12-25405Pacifiques de la route3Snipers5WSommaire du Match
98 - 2020-12-27413Snipers4Croque-Morts1WSommaire du Match
100 - 2020-12-29419Chiefs2Snipers1LXSommaire du Match
101 - 2020-12-30421Snipers4Harvard3WXSommaire du Match
103 - 2021-01-01433Riverman6Snipers3LR2Sommaire du Match
104 - 2021-01-02435Snipers4Citadelles2WSommaire du Match
106 - 2021-01-04445As3Snipers5WSommaire du Match
108 - 2021-01-06451Snipers2Isotopes1WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
111 - 2021-01-09462Wolves1Snipers5WSommaire du Match
112 - 2021-01-10467Snipers2Wolves5LSommaire du Match
113 - 2021-01-11474Canadiens1Snipers3WSommaire du Match
115 - 2021-01-13481Snipers2Wolves1WXSommaire du Match
116 - 2021-01-14488Citadelles2Snipers3WSommaire du Match
117 - 2021-01-15493Snipers4Citadelles1WSommaire du Match
119 - 2021-01-17503Banshees5Snipers3LSommaire du Match
120 - 2021-01-18511Croque-Morts6Snipers3LSommaire du Match
121 - 2021-01-19516Snipers4Harvard2WSommaire du Match
122 - 2021-01-20522Snipers2Canadiens3LSommaire du Match
123 - 2021-01-21529Ailes Rouges2Snipers3WSommaire du Match
126 - 2021-01-24540Croque-Morts1Snipers5WSommaire du Match
127 - 2021-01-25545Snipers4Riverman1WR2Sommaire du Match
129 - 2021-01-27552Snipers2Spoonman's4LSommaire du Match
131 - 2021-01-29559Isotopes1Snipers4WSommaire du Match
135 - 2021-02-02574Isotopes0Snipers7WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

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

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,574,433$ 1,742,450$ 1,742,450$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
1,742,450$ 1,574,433$ 31 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 1 13,511$ 13,511$




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