Predators

GP: 82 | W: 38 | L: 35 | OTL: 9 | P: 85
GF: 225 | GA: 232 | PP%: 18.63% | PK%: 77.00%
DG: Libre | Morale : 29 | Moyenne d'Équipe : 66
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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 SP
1Micheal Ferland (R)X100.008142837377799482677782856077595350750
2Melker Karlsson (R)X100.006334996871748177577482889080777018730
3Colton Sissons (R)X100.007241777175858869857367836169536876700
4Phil Di Giuseppe (R)X100.008049696376787879608182705663576939700
5Brandon Tanev (R)X100.009647687170809368636667856858523645690
6Oskar Sundqvist (R)X100.007135737085828769756868745669526254680
7Nolan Patrick (R)X100.006741767080838569846968696656529140670
8Josh Jooris (R)X100.006338846773696971786770749078757547670
9Byron Froese (R)X100.007145766873738566746862695467554847650
10Adam Erne (R)X100.008444686880767867686765666555517549650
11Boo Nieves (R)X100.006335756685687265696262675362516643620
12Denis Gurianov (R)X100.005735736979576068566665665451508526610
13Lukas KrajicekX100.0091995979959993499393287688993036680
14Chris Summers (R)X100.008631946277525866485750825783753916660
15Nikita Nesterov (R)X100.007241917172737957256057715077734343660
16Alexey Marchenko (R)X100.005531997178648459185146795067674349650
17Christian Jaros (R)X100.007641726484757564306661665363515650650
18Frank Corrado (R)X100.006040826574616669306457655478734534630
Rayé
1Viktor TikhonovX100.007755546675586059605663776570916119630
2Jesse Puljujarvi (R)X100.006735746487767562506763635356528927620
3Frederick Gaudreau (R)X100.006035736770736862786162645362514219610
4Sergei Plotnikov (R)X100.008235776773426762655757725055554419600
5Nicholas Baptiste (R)X100.005436826277638560505960605165526519590
6Nicholas Merkley (R)X100.004835816570606860515859615067517719580
7Tim Heed (R)X100.006035757071716868307268666070534722640
8Samuel Morin (R)X100.006935755393645253305651815057548219620
9Alexandre Carrier (R)X100.004228817169484660305653675259619219580
10Josh Mahura (R)X100.005135736773565867305755575451506419570
MOYENNE D'ÉQUIPE100.00663779677769746754656470596660613465
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
1Carter Hutton (R)100.00868993748589919089907864752349830
2Niklas Svedberg (R)100.00777070737291969999747982786949800
Rayé
MOYENNE D'ÉQUIPE100.0082808274799094959482797377464982
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jim Playfair69686971877573CAN533900,000$


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
1Micheal FerlandPredators (NSH)LW814146871761022121236411123711.26%55176321.771921407531712372554247.68%5608730020.99190021153
2Phil Di Giuseppe Predators (NSH)LW7931487918891523014429810119010.40%29152119.25513183824121371504140.00%1105415001.0405111585
3Oskar Sundqvist Predators (NSH)C75214061210810197227139429315.11%32136618.2112213337293000032051.23%18291126100.8902101123
4Colton SissonsPredators (NSH)RW712733601330101861412325514511.64%33135719.1196153121910171176143.53%852225000.8827101674
5Melker KarlssonPredators (NSH)RW66184159280117102230661437.83%46141121.38519245827212382162135.58%1045121000.8426000165
6Lukas KrajicekPredators (NSH)D73103949900912018773935.35%57181624.8861420383110003265110.00%07527000.5400000122
7Nolan PatrickPredators (NSH)C811827451567151562331575510811.46%25144617.863710202440001443154.92%15442221000.6200003331
8Josh JoorisPredators (NSH)RW821113242201010383182551206.04%27110913.533471178000021052.94%513117000.4322011003
9Byron FroesePredators (NSH)C8281119-20461014413312636756.35%17105212.842022310002412247.78%7892112000.3600011120
10Nikita NesterovPredators (NSH)D792151729514115010242381.96%114194824.67055243251012268100.00%01655000.1700010003
11Brandon TanevPredators (NSH)LW819716-19715170103159461025.66%28100312.390002190001343044.64%562916000.3213010022
12Adam ErnePredators (NSH)LW829514-4320111679432589.57%116788.270112100002564054.05%37910000.4100000002
13Christian JarosPredators (NSH)D8221214-98351401266218233.23%75144417.610336124000078000.00%01535000.1900001010
14Chris SummersPredators (NSH)D6321113-3401371144715144.26%69140122.2424671940000172000.00%01042000.1900000000
15Alexey MarchenkoPredators (NSH)D8221113340621497037232.86%100164020.0024651610220152010.00%01042000.1600000000
16Boo NievesPredators (NSH)C80459-416055686917465.80%146047.5500006000040145.32%27877000.3000000001
17Jesse PuljujarviPredators (NSH)RW65257-814070475020224.00%176049.30000070001210140.00%30810000.2300000001
18Tim HeedPredators (NSH)D67167-436048664824222.08%4697614.58000049000011100.00%01824000.1400000001
19Denis GurianovPredators (NSH)RW43246-311522285016284.00%72876.70000030000000100.00%173000.4200001020
20Frank CorradoPredators (NSH)D1610137571984312.50%922514.1100000000010010.00%0110000.0900100001
21Samuel MorinPredators (NSH)D310110180284117580.00%3343313.990000000005000.00%0112000.0500000001
22Frederick GaudreauPredators (NSH)C11000-42061213530.00%2948.6300001000050061.29%3112000.0000000000
23Josh MahuraPredators (NSH)D1000000000000.00%011.400000000000000.00%000000.0000000000
24Viktor TikhonovPredators (NSH)LW3000-200445100.00%03612.00000010000200100.00%100000.0000000000
25Nicholas MerkleyPredators (NSH)RW1000000000000.00%011.750000000000000.00%000000.0000000000
26Sergei Plotnikov Predators (NSH)LW1000000000000.00%000.450000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne1478221380601-1075110523642389270987615948.16%8462422716.396812219035629176713411922341350.45%5506506462120.508344512294038
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
1Carter HuttonPredators (NSH)44191640.9023.102438001261290559000.680254042312
2Niklas SvedbergPredators (NSH)44191950.9242.402522021011332553300.75084240724
Stats d'équipe Total ou en Moyenne88383590.9132.7549610222726221112300.6973382821036


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 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
Adam ErnePredators (NSH)LW251995-04-20 09:47:57Yes214 Lbs6 ft1NoNoNo1Pro & Farm874,167$0$0$No
Alexandre CarrierPredators (NSH)D231996-10-08 04:11:56Yes177 Lbs5 ft11NoNoNo1Pro & Farm688,333$0$0$No
Alexey MarchenkoPredators (NSH)D281992-01-02 05:11:13Yes218 Lbs6 ft2NoNoNo2Pro & Farm700,000$0$0$No700,000$
Boo NievesPredators (NSH)C261994-01-23 09:51:40Yes210 Lbs6 ft3NoNoNo1Pro & Farm755,000$0$0$No
Brandon TanevPredators (NSH)LW281991-12-31 09:49:43Yes180 Lbs6 ft0NoNoNo1Pro & Farm700,000$0$0$No
Byron FroesePredators (NSH)C291991-03-12 10:21:16Yes191 Lbs6 ft0NoNoNo2Pro & Farm575,000$0$0$No575,000$
Carter HuttonPredators (NSH)G341985-12-19 11:11:14Yes198 Lbs6 ft0NoNoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$
Chris SummersPredators (NSH)D321988-02-05 05:11:13Yes213 Lbs6 ft2NoNoNo3Pro & Farm700,000$0$0$No700,000$700,000$
Christian JarosPredators (NSH)D241996-04-02 04:19:52Yes201 Lbs6 ft3NoNoNo3Pro & Farm755,000$0$0$No755,000$755,000$
Colton SissonsPredators (NSH)RW261993-11-05 11:11:13Yes200 Lbs6 ft1NoNoNo1Pro & Farm575,000$0$0$No
Denis GurianovPredators (NSH)RW221997-06-07 09:53:45Yes195 Lbs6 ft2NoNoNo1Pro & Farm894,166$0$0$No
Frank CorradoPredators (NSH)D271993-03-26 11:11:13Yes193 Lbs6 ft0NoNoNo2Pro & Farm575,000$0$0$No575,000$
Frederick GaudreauPredators (NSH)C271993-05-01 03:42:10Yes179 Lbs6 ft0NoNoNo1Pro & Farm666,667$0$0$No
Jesse PuljujarviPredators (NSH)RW211998-05-07 09:56:00Yes201 Lbs6 ft4NoNoNo1Pro & Farm925,000$0$0$No
Josh JoorisPredators (NSH)RW291990-07-14 17:11:13Yes194 Lbs6 ft1NoNoNo2Pro & Farm700,000$0$0$No700,000$
Josh MahuraPredators (NSH)D211998-05-05 12:47:30Yes192 Lbs6 ft0NoNoNo3Pro & Farm745,000$0$0$No745,000$745,000$
Lukas KrajicekPredators (NSH)D371983-03-11 23:11:13No220 Lbs6 ft2NoNoNo3Pro & Farm800,000$0$0$No800,000$800,000$
Melker KarlssonPredators (NSH)RW291990-07-18 17:11:13Yes186 Lbs6 ft0NoNoNo1Pro & Farm1,200,000$0$0$No
Micheal FerlandPredators (NSH)LW281992-04-20 05:11:13Yes222 Lbs6 ft0NoNoNo2Pro & Farm1,500,000$0$0$No1,500,000$
Nicholas BaptistePredators (NSH)RW241995-08-04 10:00:24Yes207 Lbs6 ft1NoNoNo1Pro & Farm718,333$0$0$No
Nicholas MerkleyPredators (NSH)RW221997-05-23 09:35:43Yes194 Lbs5 ft10NoNoNo2Pro & Farm863,333$0$0$No863,333$
Nikita NesterovPredators (NSH)D271993-03-28 11:11:13Yes188 Lbs6 ft0NoNoNo2Pro & Farm700,000$0$0$No700,000$
Niklas SvedbergPredators (NSH)G301989-09-04 11:11:14Yes179 Lbs6 ft0NoNoNo1Pro & Farm800,000$0$0$No
Nolan PatrickPredators (NSH)C211998-09-19 09:32:24Yes198 Lbs6 ft2NoNoNo2Pro & Farm3,575,000$0$0$No3,575,000$
Oskar Sundqvist Predators (NSH)C261994-03-23 10:24:07Yes209 Lbs6 ft3NoNoNo3Pro & Farm800,000$0$0$No800,000$800,000$
Phil Di Giuseppe Predators (NSH)LW261993-10-09 10:25:56Yes202 Lbs6 ft0NoNoNo3Pro & Farm1,250,000$0$0$No1,250,000$1,250,000$
Samuel MorinPredators (NSH)D241995-07-12 10:02:08Yes204 Lbs6 ft6NoNoNo1Pro & Farm863,333$0$0$No
Sergei Plotnikov Predators (NSH)LW291990-06-03 10:27:25Yes207 Lbs6 ft2NoNoNo1Pro & Farm575,000$0$0$No
Tim HeedPredators (NSH)D291991-01-27 04:34:13Yes180 Lbs5 ft11NoNoNo2Pro & Farm650,000$0$0$No650,000$
Viktor TikhonovPredators (NSH)LW311988-05-12 05:11:13No199 Lbs6 ft2NoNoNo2Pro & Farm575,000$0$0$No575,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3026.83198 Lbs6 ft11.80923,278$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Micheal FerlandOskar Sundqvist Melker Karlsson35122
2Phil Di Giuseppe Nolan PatrickColton Sissons35122
3Brandon TanevByron FroeseJosh Jooris25122
4Adam ErneBoo NievesDenis Gurianov5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Lukas KrajicekNikita Nesterov35122
2Chris SummersAlexey Marchenko35122
3Christian JarosFrank Corrado30122
4Lukas KrajicekNikita Nesterov0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Micheal FerlandOskar Sundqvist Melker Karlsson60122
2Phil Di Giuseppe Nolan PatrickColton Sissons40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Lukas KrajicekNikita Nesterov60122
2Chris SummersAlexey Marchenko40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Micheal FerlandMelker Karlsson60122
2Phil Di Giuseppe Colton Sissons40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Lukas KrajicekNikita Nesterov60122
2Chris SummersAlexey Marchenko40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Micheal Ferland60122Lukas KrajicekNikita Nesterov60122
2Melker Karlsson40122Chris SummersAlexey Marchenko40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Micheal FerlandMelker Karlsson60122
2Phil Di Giuseppe Colton Sissons40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Lukas KrajicekNikita Nesterov60122
2Chris SummersAlexey Marchenko40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Micheal FerlandOskar Sundqvist Melker KarlssonLukas KrajicekNikita Nesterov
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Micheal FerlandOskar Sundqvist Melker KarlssonLukas KrajicekNikita Nesterov
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brandon Tanev, Josh Jooris, Adam ErneBrandon Tanev, Josh JoorisAdam Erne
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Christian Jaros, Frank Corrado, Chris SummersChristian JarosFrank Corrado, Chris Summers
Tirs de Pénalité
Micheal Ferland, Melker Karlsson, Phil Di Giuseppe , Colton Sissons, Brandon Tanev
Gardien
#1 : Carter Hutton, #2 : Niklas Svedberg


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
1Avalanche734000002117442200000136731200000811-360.429213051008163778217921917861442097011821845715.56%44686.36%21121218851.23%1088214650.70%569114549.69%1780102417767641410704
2Blackhawks614000101317-43020001058-33120000089-140.33313213400816377818892191786144196586217337410.81%26580.77%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
3Blues633000001918132100000107331200000911-260.500193251018163778187921917861441756482181391333.33%36975.00%11121218851.23%1088214650.70%569114549.69%1780102417767641410704
4Bruins21100000541110000004221010000012-120.5005813008163778609219178614465276569111.11%3166.67%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
5Canadiens22000000844110000004221100000042241.00081321008163778679219178614467282057100.00%10190.00%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
6Canucks41200100813-52010010027-52110000066030.3758152300816377812592191786144116453210918422.22%16662.50%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
7Capitals211000004401010000014-31100000030320.500461001816377873921917861446518853100.00%4175.00%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
8Devils3110000178-11010000023-12100000155030.50071219008163778109921917861441122886313215.38%4175.00%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
9Ducks41100011161512100001010732010000168-250.62516274300816377812592191786144128414110416425.00%18288.89%11121218851.23%1088214650.70%569114549.69%1780102417767641410704
10Flames41100002811-32010000147-32100000144040.500815230081637781279219178614412334229820315.00%11281.82%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
11Flyers32100000844211000006331100000021140.6678142200816377810392191786144109436816116.67%30100.00%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
12Islanders22000000532110000003211100000021141.00051015008163778639219178614477218576116.67%4175.00%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
13Kings514000001221-92020000059-431200000712-520.20012223400816377816892191786144158535416019315.79%27870.37%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
14Maple Leafs22000000844110000005321100000031241.0008162400816377866921917861447129642500.00%3166.67%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
15Oilers41200010912-32110000067-12010001035-240.5009132200816377814192191786144127352611719421.05%13561.54%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
16Penguins21100000431110000004131010000002-220.50047110081637786092191786144732619594125.00%7185.71%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
17Rangers220000001147110000005231100000062441.000112031008163778909219178614458216696233.33%3166.67%11121218851.23%1088214650.70%569114549.69%1780102417767641410704
18Red Wings2110000047-31010000016-51100000031220.5004610008163778629219178614470228544125.00%4250.00%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
19Sabres2010010029-71000010012-11010000017-610.2502460081637785992191786144711433725120.00%4250.00%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
20Senateurs201000106601010000023-11000001043120.50068140081637787892191786144782012525120.00%6266.67%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
21Sharks421001001215-32100010065121100000610-450.62512213300816377813292191786144125394112516318.75%8275.00%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
22Stars64100001231583200000114773210000098190.75023406300816377820792191786144188608318735617.14%34779.41%11121218851.23%1088214650.70%569114549.69%1780102417767641410704
Total82343500445225232-741171600422121113841171900023104119-15850.518225380605028163778270992191786144262284675123643656818.63%3137277.00%61121218851.23%1088214650.70%569114549.69%1780102417767641410704
24Wild614001001218-631100100810-23030000048-430.25012203200816377820292191786144161505017736616.67%25676.00%01121218851.23%1088214650.70%569114549.69%1780102417767641410704
_Since Last GM Reset82343500445225232-741171600422121113841171900023104119-15850.518225380605028163778270992191786144262284675123643656818.63%3137277.00%61121218851.23%1088214650.70%569114549.69%1780102417767641410704
_Vs Conference56192700334153172-19281011003228380328916000127092-22510.455153256409018163778181992191786144170654961116493005719.00%2585877.52%51121218851.23%1088214650.70%569114549.69%1780102417767641410704
_Vs Division311216001118885316760011150381215510000003847-9280.452881432310181637781001921917861449293023959361923618.75%1653380.00%41121218851.23%1088214650.70%569114549.69%1780102417767641410704

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8285W322538060527092622846751236402
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8234350445225232
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4117160422121113
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4117190023104119
Derniers 10 Matchs
WLOTWOTL SOWSOL
730000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3656818.63%3137277.00%6
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
921917861448163778
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
1121218851.23%1088214650.70%569114549.69%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1780102417767641410704


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 - 2019-10-077Predators2Blues4LR5Sommaire du Match
4 - 2019-10-0918Avalanche1Predators6WR5Sommaire du Match
6 - 2019-10-1134Wild3Predators1LSommaire du Match
9 - 2019-10-1448Predators3Stars2WSommaire du Match
11 - 2019-10-1660Avalanche2Predators1LR5Sommaire du Match
14 - 2019-10-1974Blues5Predators3LSommaire du Match
17 - 2019-10-2290Predators2Kings8LR2Sommaire du Match
19 - 2019-10-2499Blackhawks2Predators3WXXSommaire du Match
21 - 2019-10-26109Predators3Blackhawks5LR5Sommaire du Match
23 - 2019-10-28121Predators1Wild2LR5Sommaire du Match
25 - 2019-10-30133Stars2Predators5WSommaire du Match
27 - 2019-11-01146Predators3Avalanche5LR5Sommaire du Match
28 - 2019-11-02153Blackhawks4Predators1LSommaire du Match
33 - 2019-11-07173Ducks4Predators6WR2Sommaire du Match
35 - 2019-11-09187Predators4Devils3WSommaire du Match
37 - 2019-11-11197Ducks3Predators4WXXR2Sommaire du Match
39 - 2019-11-13207Predators3Blackhawks1WSommaire du Match
41 - 2019-11-15222Blackhawks2Predators1LR5Sommaire du Match
43 - 2019-11-17232Predators2Flyers1WSommaire du Match
45 - 2019-11-19241Predators3Maple Leafs1WSommaire du Match
47 - 2019-11-21249Rangers2Predators5WSommaire du Match
51 - 2019-11-25268Capitals4Predators1LSommaire du Match
53 - 2019-11-27282Predators3Red Wings1WSommaire du Match
55 - 2019-11-29293Red Wings6Predators1LSommaire du Match
60 - 2019-12-04315Canucks5Predators1LR2Sommaire du Match
65 - 2019-12-09338Avalanche2Predators1LR5Sommaire du Match
67 - 2019-12-11351Predators3Stars4LSommaire du Match
68 - 2019-12-12361Flyers2Predators1LSommaire du Match
71 - 2019-12-15375Predators4Senateurs3WXXSommaire du Match
73 - 2019-12-17385Penguins1Predators4WSommaire du Match
75 - 2019-12-19396Predators2Flames3LXXR2Sommaire du Match
77 - 2019-12-21409Flames4Predators2LSommaire du Match
79 - 2019-12-23416Predators0Penguins2LSommaire du Match
81 - 2019-12-25429Predators2Islanders1WSommaire du Match
82 - 2019-12-26437Flyers1Predators5WSommaire du Match
86 - 2019-12-30456Predators1Devils2LXXSommaire du Match
87 - 2019-12-31461Canadiens2Predators4WSommaire du Match
91 - 2020-01-04480Predators6Rangers2WSommaire du Match
92 - 2020-01-05485Blues0Predators4WR5Sommaire du Match
96 - 2020-01-09505Blues2Predators3WSommaire du Match
98 - 2020-01-11515Predators2Blues3LR5Sommaire du Match
100 - 2020-01-13530Sharks2Predators1LXR2Sommaire du Match
105 - 2020-01-18553Sharks3Predators5WSommaire du Match
108 - 2020-01-21569Predators2Blackhawks3LR5Sommaire du Match
109 - 2020-01-22577Flames3Predators2LXXR2Sommaire du Match
111 - 2020-01-24590Predators4Sharks2WR2Sommaire du Match
113 - 2020-01-26601Avalanche1Predators5WSommaire du Match
117 - 2020-01-30622Predators2Flames1WR2Sommaire du Match
118 - 2020-01-31624Bruins2Predators4WSommaire du Match
121 - 2020-02-03640Predators1Wild2LR5Sommaire du Match
123 - 2020-02-05650Kings5Predators4LR2Sommaire du Match
124 - 2020-02-06655Predators3Stars2WSommaire du Match
128 - 2020-02-10674Canucks2Predators1LXR2Sommaire du Match
130 - 2020-02-12689Predators3Ducks4LSommaire du Match
131 - 2020-02-13696Senateurs3Predators2LSommaire du Match
134 - 2020-02-16711Predators4Canadiens2WSommaire du Match
136 - 2020-02-18721Devils3Predators2LSommaire du Match
139 - 2020-02-21739Predators3Ducks4LXXR2Sommaire du Match
141 - 2020-02-23746Islanders2Predators3WSommaire du Match
142 - 2020-02-24756Predators2Avalanche1WR5Sommaire du Match
145 - 2020-02-27769Sabres2Predators1LXSommaire du Match
147 - 2020-02-29777Predators1Sabres7LSommaire du Match
148 - 2020-03-01787Predators4Kings1WR2Sommaire du Match
150 - 2020-03-03795Stars4Predators3LXXSommaire du Match
152 - 2020-03-05806Predators2Wild4LR5Sommaire du Match
154 - 2020-03-07818Predators1Oilers4LSommaire du Match
155 - 2020-03-08822Kings4Predators1LR2Sommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
158 - 2020-03-11836Predators2Canucks3LSommaire du Match
159 - 2020-03-12845Predators1Bruins2LSommaire du Match
160 - 2020-03-13848Wild5Predators4LXR5Sommaire du Match
163 - 2020-03-16867Predators2Oilers1WXXSommaire du Match
164 - 2020-03-17870Oilers4Predators2LSommaire du Match
167 - 2020-03-20885Predators4Canucks3WR2Sommaire du Match
169 - 2020-03-22894Wild2Predators3WSommaire du Match
171 - 2020-03-24902Predators1Kings3LR2Sommaire du Match
173 - 2020-03-26915Predators5Blues4WSommaire du Match
175 - 2020-03-28922Maple Leafs3Predators5WSommaire du Match
176 - 2020-03-29927Predators3Avalanche5LR5Sommaire du Match
177 - 2020-03-30931Predators2Sharks8LR2Sommaire du Match
179 - 2020-04-01943Predators3Capitals0WSommaire du Match
183 - 2020-04-05960Stars1Predators6WSommaire du Match
189 - 2020-04-11984Oilers3Predators4WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3525
Assistance77,14137,674
Assistance PCT94.07%91.89%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2800 - 93.35% 94,277$3,865,372$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,590,741$ 2,769,833$ 2,004,833$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
14,578$ 2,690,738$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 19,315$ 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
Saison Régulière
1378302704458224212123916130221511510510391414022431091072602243635871365787213254178691381081255284377020643025317.55%3346680.24%51020201150.72%977204747.73%576112751.11%166594517387321362666
1482343500445225232-741171600422121113841171900023104119-1585225380605028163778270992191786144262284675123643656818.63%3137277.00%61121218851.23%1088214650.70%569114549.69%1780102417767641410704
Total Saison Régulière16064620489134494445803329026372362181880313302266213226-13145449743119215146141149215250170718301671125517416891521442866712118.14%64713878.67%112141419950.99%2065419349.25%1145227250.40%344619693514149627721371