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Penguins
GP: 7 | W: 3 | L: 4
GF: 23 | GA: 26 | PP%: 36.84% | PK%: 75.00%
DG: Sylvain Lemieux | Morale : 50 | Moyenne d’équipe : 62
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Centre de jeu
Checkers
7-3-0, 14pts
4
FINAL
5 Penguins
3-4-0, 6pts
Team Stats
OTW1StreakOTL1
5-1-0Home Record2-1-0
2-2-0Away Record1-3-0
7-1-2Last 10 Games3-3-1
4.10Goals Per Game3.29
3.00Goals Against Per Game3.71
28.00%Power Play Percentage36.84%
67.86%Penalty Kill Percentage75.00%
Penguins
3-4-0, 6pts
2
FINAL
3 Checkers
7-3-0, 14pts
Team Stats
OTL1StreakOTW1
2-1-0Home Record5-1-0
1-3-0Away Record2-2-0
3-3-1Last 10 Games7-1-2
3.29Goals Per Game4.10
3.71Goals Against Per Game3.00
36.84%Power Play Percentage28.00%
75.00%Penalty Kill Percentage67.86%
Meneurs d'équipe
Wade AllisonButs
Wade Allison
4
Wade AllisonPasses
Wade Allison
1
Wade AllisonPoints
Wade Allison
5
Wade AllisonPlus/Moins
Wade Allison
-5
Joel HoferVictoires
Joel Hofer
2
Joel HoferPourcentage d’arrêts
Joel Hofer
0.895

Statistiques d’équipe
Buts pour
23
3.29 GFG
Tirs pour
239
34.14 Avg
Pourcentage en avantage numérique
36.8%
7 GF
Début de zone offensive
40.6%
Buts contre
26
3.71 GAA
Tirs contre
239
34.14 Avg
Pourcentage en désavantage numérique
75.0%
4 GA
Début de la zone défensive
40.1%
Informations de l'équipe

Directeur généralSylvain Lemieux
DivisionAtlantique
ConférenceEst
Capitaine
Assistant #1Michael Mersch
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro29
Équipe Mineure22
Limite contact 51 / 250
Espoirs40


Historique d'équipe

Saison actuelle3-4
Historique329-357-44 (0.451%)
Apparitions en séries éliminatoires 3
Historique en séries éliminatoires (W-L)14-18
Coupe Stanley0


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
1Tobias RiederXXX100.00583594736978856660646376667568050660271700,000$
2Gemel SmithXXX100.00647157687170726577676664667367050640261700,000$
3Jan Jenik (R)XXX100.00583592657085736773627159666163050640203902,500$
4Angus Crookshank (R)XX100.00653788676974796573676159556364050630214838,333$
5Matthew PecaXX100.00733595646678806271636057617568050630271700,000$
6Michael Mersch (A)XX100.00745571608381865862596063567772050630281675,000$
7Seth GriffithXXX100.00583788636787926467626158647571050630272725,000$
8Riley Damiani (R)X100.00574283676882876678686259646163050630203891,667$
9Brendan Warren (R)X100.00643592597368716254596358626764050620231700,000$
10Curtis Douglas (R)XX100.00898377569971765472585563546163050610201700,000$
11Sean MaloneX100.00506356637486756273686057627166050610251750,000$
12Martin PospisilXX100.00663854597578736174605856616362050600202810,000$
13Colin MillerX100.008342846677878564307260595277690506602723,875,000$
14Oscar FantenbergX100.00843595647673796330705871507870050660291850,000$
15Ben HarpurX100.00796683649977786330665473507166050650251700,000$
16Kevin Bahl (R)X100.00817893629880736130655754526163050630203902,500$
17Calen Addison (R)X100.00563594656983776630645862546163050620203910,833$
18Christian WolaninX100.00523888647880786330675760457166050620251900,000$
Rayé
1Dennis YanX100.0068467959778287575556585957676405061X0231935,833$
2Justin Almeida (R)XX100.00563593556571745556555753566362050580212925,000$
3Axel Andersson (R)X100.00623593637173786230595661526364050610203871,667$
4Mitchell Vande Sompel (R)X100.00633986597286715730585256456764050590232725,000$
5Reilly Walsh (R)X100.00603887576979845830595655486362050590213925,000$
6Mac HollowellX100.00634381566369745630595453476563050580222799,766$
MOYENNE D’ÉQUIPE100.0066468362757879625263596056686505062
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SPÂgeContratSalaire
1Alexei Melnichuk (R)100.0075828078747375747375746570050640222925,000$
2Joel Hofer (R)100.0073848275727173727173726165050630203910,833$
Rayé
1Ivan Prosvetov100.0073808384727173727173726367050630212925,000$
2Nick Schneider100.006975737468676968676968677105061X0231675,000$
3Jakub Skarek100.0067787683666567666567666367050600202927,500$
MOYENNE D’ÉQUIPE100.007180797970697170697170646805062
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Tobias RiederPenguins (PIT)C/LW/RW7279-4006223213296.25%115221.832249150110100050.00%2000001.1800000100
2Angus CrookshankPenguins (PIT)C/LW72681004211762011.76%014520.85011312000041047.26%20100001.1000000001
3Riley DamianiPenguins (PIT)C7167-520424711814.29%014821.14145215000000050.49%20400000.9500000000
4Colin MillerPenguins (PIT)D706608021911270.00%916924.2300051300008000.00%000000.7100000001
5Christian WolaninPenguins (PIT)D7325-20061170542.86%016223.24213414000012000.00%000000.6100000000
6Wade AllisonPenguinsRW7415-56031122762314.81%514921.40011615101170083.33%600000.6700000010
7Ben HarpurPenguins (PIT)D7134-100131012788.33%1217324.85011313000013010.00%000000.4600000100
8Gemel SmithPenguins (PIT)C/LW/RW72240601418229189.09%215221.751125120000121051.72%2900000.5300000010
9Jan JenikPenguins (PIT)C/LW/RW7134-20008267173.85%39313.3500000000000133.33%600000.8600000000
10Michael MerschPenguins (PIT)LW/RW72241201681851111.11%015522.190004120002140020.00%500000.5200000000
11Oscar FantenbergPenguins (PIT)D7213-240317114418.18%1414721.0200000011011100.00%000000.4100000000
12Calen AddisonPenguins (PIT)D7112-4002613877.69%1012918.5211261400005000.00%000000.3100000000
13Kevin BahlPenguins (PIT)D7022-3801924010.00%811015.850000000000000.00%000000.3600000000
14Curtis DouglasPenguins (PIT)C/RW7011-4001872160.00%28612.3800000000000051.52%9900000.2300000000
15Matthew PecaPenguins (PIT)C/LW7101-4003711489.09%18612.3600000000000050.00%600000.2300000000
16Sean MalonePenguins (PIT)C71011207661816.67%1456.4600000000000055.56%4500000.4400000000
17Seth GriffithPenguins (PIT)C/LW/RW7011100356160.00%0456.4600000000000042.86%700000.4400000000
18Brendan WarrenPenguins (PIT)LW7000100257330.00%1466.6400000000000066.67%300000.0000000000
Statistiques d’équipe totales ou en moyenne126234467-31380200188239781999.62%69220117.47712194714312331023249.92%63100000.6100000222
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
1Joel HoferPenguins (PIT)42200.8953.4024700141330000.000043000
2Alexei MelnichukPenguins (PIT)31110.8873.6419800121060000.000034000
Statistiques d’équipe totales ou en moyenne73310.8913.5044600262390000.000077000


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 Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Alexei MelnichukPenguins (PIT)G221998-06-29Yes190 Lbs6 ft2NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Angus CrookshankPenguins (PIT)C/LW211999-10-02Yes181 Lbs5 ft11NoNoNo4Pro & Farm838,333$0$0$No838,333$838,333$838,333$Lien NHL
Axel AnderssonPenguins (PIT)D202000-02-10Yes178 Lbs6 ft0NoNoNo3Pro & Farm871,667$0$0$No871,667$871,667$Lien NHL
Ben HarpurPenguins (PIT)D251995-01-12No231 Lbs6 ft6NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Brendan WarrenPenguins (PIT)LW231997-05-07Yes191 Lbs6 ft0NoNoNo1Pro & Farm700,000$0$0$NoLien NHL
Calen AddisonPenguins (PIT)D202000-04-11Yes180 Lbs5 ft11NoNoNo3Pro & Farm910,833$0$0$No910,833$910,833$Lien NHL
Christian WolaninPenguins (PIT)D251995-03-17No190 Lbs6 ft2NoNoNo1Pro & Farm900,000$0$0$NoLien / Lien NHL
Colin MillerPenguins (PIT)D271992-10-29No199 Lbs6 ft1NoNoNo2Pro & Farm3,875,000$0$0$No3,875,000$Lien / Lien NHL
Curtis DouglasPenguins (PIT)C/RW202000-03-06Yes235 Lbs6 ft9NoNoNo1Pro & Farm700,000$0$0$NoLien NHL
Dennis YanPenguins (PIT)LW231997-04-14No197 Lbs6 ft1NoYesNo1Pro & Farm935,833$0$0$NoLien / Lien NHL
Gemel SmithPenguins (PIT)C/LW/RW261994-04-16No203 Lbs5 ft10NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Ivan ProsvetovPenguins (PIT)G211999-03-05No175 Lbs6 ft5NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Jakub SkarekPenguins (PIT)G201999-11-10No196 Lbs6 ft3NoNoNo2Pro & Farm927,500$0$0$No927,500$Lien / Lien NHL
Jan JenikPenguins (PIT)C/LW/RW202000-09-15Yes161 Lbs6 ft1NoNoNo3Pro & Farm902,500$0$0$No902,500$902,500$Lien NHL
Joel HoferPenguins (PIT)G202000-07-30Yes160 Lbs6 ft3NoNoNo3Pro & Farm910,833$0$0$No910,833$910,833$Lien / Lien NHL
Justin AlmeidaPenguins (PIT)C/LW211999-02-06Yes165 Lbs5 ft11NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien NHL
Kevin BahlPenguins (PIT)D202000-06-27Yes230 Lbs6 ft6NoNoNo3Pro & Farm902,500$0$0$No902,500$902,500$Lien NHL
Mac HollowellPenguins (PIT)D221998-09-26No170 Lbs5 ft9NoNoNo2Pro & Farm799,766$0$0$No799,766$Lien / Lien NHL
Martin PospisilPenguins (PIT)C/RW201999-11-19No173 Lbs6 ft2NoNoNo2Pro & Farm810,000$0$0$No810,000$Lien / Lien NHL
Matthew PecaPenguins (PIT)C/LW271993-04-27No182 Lbs5 ft8NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Michael MerschPenguins (PIT)LW/RW281992-10-02No213 Lbs6 ft2NoNoNo1Pro & Farm675,000$0$0$NoLien / Lien NHL
Mitchell Vande SompelPenguins (PIT)D231997-02-11Yes198 Lbs5 ft11NoNoNo2Pro & Farm725,000$0$0$No725,000$Lien / Lien NHL
Nick SchneiderPenguins (PIT)G231997-07-31No170 Lbs6 ft2NoYesNo1Pro & Farm675,000$0$0$NoLien / Lien NHL
Oscar FantenbergPenguins (PIT)D291991-10-07No206 Lbs6 ft0NoNoNo1Pro & Farm850,000$0$0$NoLien / Lien NHL
Reilly WalshPenguins (PIT)D211999-04-21Yes181 Lbs5 ft11NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien NHL
Riley DamianiPenguins (PIT)C202000-03-20Yes170 Lbs5 ft11NoNoNo3Pro & Farm891,667$0$0$No891,667$891,667$Lien NHL
Sean MalonePenguins (PIT)C251995-04-30No197 Lbs6 ft0NoNoNo1Pro & Farm750,000$0$0$NoLien / Lien NHL
Seth GriffithPenguins (PIT)C/LW/RW271993-01-04No190 Lbs5 ft9NoNoNo2Pro & Farm725,000$0$0$No725,000$Lien / Lien NHL
Tobias RiederPenguins (PIT)C/LW/RW271993-01-10No189 Lbs5 ft11NoNoNo1Pro & Farm700,000$0$0$NoLien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2922.97190 Lbs6 ft11.90923,325$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tobias RiederRiley Damiani40113
2Gemel SmithAngus CrookshankMichael Mersch40113
3Matthew PecaCurtis DouglasJan Jenik15131
4Brendan WarrenSean MaloneSeth Griffith5131
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben HarpurColin Miller40032
2Oscar FantenbergChristian Wolanin40032
3Calen AddisonKevin Bahl20041
4Ben HarpurColin Miller0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tobias RiederRiley Damiani55005
2Gemel SmithAngus CrookshankMichael Mersch45005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben HarpurColin Miller55014
2Calen AddisonChristian Wolanin45014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Gemel SmithMichael Mersch55140
2Tobias Rieder45140
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben HarpurColin Miller55140
2Oscar FantenbergChristian Wolanin45140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Gemel Smith55140Ben HarpurColin Miller55140
2Tobias Rieder45140Oscar FantenbergChristian Wolanin45140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Riley DamianiJan Jenik60023
2Angus CrookshankGemel Smith40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben HarpurColin Miller60032
2Calen AddisonKevin Bahl40032
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tobias RiederRiley DamianiJan JenikBen HarpurColin Miller
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matthew PecaRiley DamianiJan JenikBen HarpurColin Miller
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Michael Mersch, Riley Damiani, Brendan WarrenMichael Mersch, Riley DamianiMichael Mersch
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ben Harpur, Colin Miller, Calen AddisonOscar FantenbergBen Harpur, Colin Miller
Tirs de pénalité
Jan Jenik, Tobias Rieder, Gemel Smith, , Riley Damiani
Gardien
#1 : Alexei Melnichuk, #2 : Joel Hofer


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
TotalDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Checkers734000002326-3321000001213-1413000001113-260.4292344670096622398582639239693820019736.84%16475.00%113925654.30%11625345.85%6012249.18%177123174539548
Total734000002326-3321000001213-1413000001113-260.4292344670096622398582639239693820019736.84%16475.00%113925654.30%11625345.85%6012249.18%177123174539548
_Since Last GM Reset734000002326-3321000001213-1413000001113-260.4292344670096622398582639239693820019736.84%16475.00%113925654.30%11625345.85%6012249.18%177123174539548
_Vs Conference734000002326-3321000001213-1413000001113-260.4292344670096622398582639239693820019736.84%16475.00%113925654.30%11625345.85%6012249.18%177123174539548
_Vs Division734000002326-3321000001213-1413000001113-260.4292344670096622398582639239693820019736.84%16475.00%113925654.30%11625345.85%6012249.18%177123174539548

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
76OTL1234467239239693820000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
73400002326
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
32100001213
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
41300001113
Derniers 10 matchs
WLOTWOTL SOWSOL
132100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
19736.84%16475.00%1
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
85826399662
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
13925654.30%11625345.85%6012249.18%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
177123174539548


Derniers matchs joués
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe visiteuse Score Équipe locale Score ST OT SO RI Lien
1 - 2022-04-302Penguins5Checkers3AWSommaire du match
3 - 2022-05-0210Penguins1Checkers3ALSommaire du match
5 - 2022-05-0418Checkers4Penguins1BLSommaire du match
7 - 2022-05-0626Checkers5Penguins6BWXSommaire du match
9 - 2022-05-0834Penguins3Checkers4ALSommaire du match
11 - 2022-05-1042Checkers4Penguins5BWXSommaire du match
13 - 2022-05-1250Penguins2Checkers3ALXSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
38 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,677,643$ 387,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 9 0$ 0$




TotalDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
Saison régulière
2814530011132622174541251301101135963940201700012127121698262467729012092897925500807895836245771769714513808722.89%2714384.13%21181255246.28%1132267642.30%575130943.93%1898130119396121045523
3824428041232391885141191403113112971541251401010127913610423942366234094855427930888966907234565773513873566718.82%2874783.62%11707293758.12%1443266154.23%661121854.27%2128149517855871047549
48239220331052622154741238012431311003141161402162131115161122624497111408789732727092386490625047521320191457310317.98%5579882.41%51559310150.27%1417299347.34%617123849.84%2060139819176401033527
582225000226178308-1304114220021295141-46418280001483167-845617830748512066684222670738721787315690950320772043718.14%2105673.33%1842243434.59%869285830.41%397124331.94%186613242111566985482
682294400522296324-2841152100311150159-941142300211146165-19692965128084201221036932480106510581114329796641120062073617.39%1806365.00%01625291255.80%1385283848.80%801134959.38%207415221898536981497
78249220132534023810241241400111163121424125801214177117601123405869262601361069535300112311661221290184945421672256328.00%2064677.67%61650333049.55%1332296644.91%660136548.35%216315841803537993515
882186001003321565-24441102701003171272-1014183300000150293-143413215038240001469777380801229129612724447121422819121613018.63%1063765.09%01385302445.80%1167267443.64%724160745.05%178413152215530935432
98257400102264604-3404133800000141292-1514123600102123312-18913264461725100102867631640995108510784516134538319431812513.81%1646460.98%01226282543.40%1078273339.44%696159443.66%161711302348548968439
10824727012143092555441297002031731175641182001011136138-2104309565874101121009542947942102296534259572553020181944121.13%2375278.06%11654292056.64%1444272852.93%727132554.87%2103150118215621024526
Total Saison régulière73729835701118203324712914-443369162164061281712711395-124368136193056121612001519-319709247142736744133011294581856927034942879090168155282188134526116875248148919.71%221850677.19%16128292603549.28%112672512744.84%58581224847.83%176981257317840512190164494
Séries éliminatoires
31596000003434085300000191907430000015150183465991001310843601421511284771271352499199.89%53688.68%026155447.11%24854245.76%9521244.81%380257351119202104
451400000613-73120000047-32020000026-42610160000331460325856142457611234411.76%38781.58%06617038.82%7919640.31%196031.67%11474119426531
7514000001620-42020000079-231200000911-221628440007721820527151243865111518633.33%22577.27%07118438.59%8325532.55%328139.51%12186138366129
10734000002326-3321000001213-1413000001113-262344670096622398582639239693820019736.84%16475.00%113925654.30%11625345.85%6012249.18%177123174539548
Total Séries éliminatoires321418000007993-141688000004248-616610000003745-8287914722610926261510038530834324411013273006761622616.05%1292282.95%1537116446.13%526124642.22%20647543.37%794541783251424214