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Punishers
GP: 80 | W: 37 | L: 42 | OTL: 1 | P: 75
GF: 314 | GA: 343 | PP%: 18.60% | PK%: 75.74%
DG: Jean-Sebastien Larin | Morale : 36 | Moyenne d’équipe : 65
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Centre de jeu
Punishers
37-42-1, 75pts
4
FINAL
3 Thunderbirds
48-30-2, 98pts
Team Stats
W1SéquenceL1
22-17-1Fiche domicile25-13-2
15-25-0Fiche domicile23-17-0
7-3-0Derniers 10 matchs6-3-1
3.93Buts par match 3.98
4.29Buts contre par match 3.51
18.60%Pourcentage en avantage numérique19.06%
75.74%Pourcentage en désavantage numérique79.34%
Americans
31-42-7, 69pts
2
FINAL
4 Punishers
37-42-1, 75pts
Team Stats
L1SéquenceW1
18-18-4Fiche domicile22-17-1
13-24-3Fiche domicile15-25-0
5-4-1Derniers 10 matchs7-3-0
3.85Buts par match 3.93
4.44Buts contre par match 4.29
19.25%Pourcentage en avantage numérique18.60%
76.87%Pourcentage en désavantage numérique75.74%
Meneurs d'équipe
Buts
John Quenneville
43
Passes
John Quenneville
75
Points
John Quenneville
118
Plus/Moins
Kevin Roy
11
Victoires
Antoine Bibeau
28
Pourcentage d’arrêts
Antoine Bibeau
0.885

Statistiques d’équipe
Buts pour
314
3.93 GFG
Tirs pour
2607
32.59 Avg
Pourcentage en avantage numérique
18.6%
56 GF
Début de zone offensive
36.2%
Buts contre
343
4.29 GAA
Tirs contre
2683
33.54 Avg
Pourcentage en désavantage numérique
75.7%%
74 GA
Début de la zone défensive
37.0%
Informations de l'équipe

Directeur généralJean-Sebastien Larin
EntraîneurJohn Anderson
DivisionGunther-Sabetzki
ConférenceLouis-Magnus
CapitaineJake Evans
Assistant #1Brett Seney
Assistant #2Tanner Kero


Informations de l’aréna

Capacité3,000
Assistance2,722
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure18
Limite contact 45 / 250
Espoirs0


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
1Zemgus Girgensons (R)X100.007934827578807373767579637561524034730242950,000$
2Corey TroppX100.007429747781727474736982676772622348720291995,000$
3John Quenneville (R)X100.007327777775747370818375576852475156710221750,000$
4Anton Blidh (R)X100.007933767870677573657373585952474056690233800,000$
5Kevin RoyX100.006827796675717367737379646150513356690251700,000$
6Oskar Lindblom (R)X100.007244807467736874756875597250465056690224925,000$
7Daniel Audette (R)X100.007143846770616771657460687046474556670221500,000$
8Kole Lind (R)X100.005733756357686371758466526343445956650201500,000$
9Carson Meyer (R)X100.007244736573577763617169565947464836640211500,000$
10Joel Kiviranta (R)X100.006142737065626069705764586847464530630221550,000$
11Jesse Ylonen (R)X100.006343766567686764616369526441436556620192500,000$
12Adam Ruzicka (R)X100.007039676780537762516467525641417240610191500,000$
13Noah Juulsen (R)X100.007239827472757674586869786060465648720212800,000$
14Artem Zub (R)X100.006854837876717878487263736565524259720233975,000$
15Ben Betker (R)X100.006729807375766965497065806264503846710242950,000$
16Connor Clifton (R)X100.006535786564747061696863755751484156660231500,000$
17Niko Mikkola (R)X100.006741807163696661507151706249494756660224650,000$
18Nicolas Beaudin (R)X100.005328687656556764346758653943436233610192500,000$
19Jack Ahcan (R)X100.005729736163616454265842724044474419600212350,000$
20Urho Vaakanainen (R)X100.005824786058585850306138684141416928580191500,000$
Rayé
1John Hayden (R)X100.006243826866686667716763536146463919640231500,000$
2Warren Foegele (R)X100.005036956872807263646854636044444932640224500,000$
3Ben Meyers (R)X100.006433716660656054565166575444424720580201500,000$
4Marcus Karlberg (R)X100.005126625941485952606754425240407020530182500,000$
MOYENNE D’ÉQUIPE100.00663677696867696660686463605047494265
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
1Antoine Bibeau97.00697163667066667878676651513753690242800,000$
2Cal Petersen100.00616668596279805555857147483957660242600,000$
Rayé
1Jack LaFontaine100.00606270504270635253665942425519560202300,000$
MOYENNE D’ÉQUIPE99.0063666758587270626273654747444364
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John Anderson67736666458551Can562300,000$


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
1John QuennevillePunishers (Bos)C804375118-228201221522918016214.78%42179322.421116273126201162297251.52%26635230101.3203000282
2Anton BlidhPunishers (Bos)LW80385593-2440123772818315613.52%28143517.94616222919110161484244.59%747323031.30020001022
3Oskar LindblomPunishers (Bos)LW80335083-13601371092608415812.69%31154419.306121828203101111695050.38%1333930001.0712000458
4Corey TroppPunishers (Bos)RW59423375-144093792137514419.72%22115619.6011718381981012851547.57%2064828041.3012000460
5Kevin RoyPunishers (Bos)C8026376311320131116153518516.99%26132416.556814152120000751051.64%9432620000.9501000232
6Artem ZubPunishers (Bos)D7811516292359914916965826.51%132213227.352911292861123260210%04772000.5811100343
7Kole LindPunishers (Bos)RW80213960-148082711645810112.80%30124815.61651120166000003056.00%503116000.9600000204
8Zemgus GirgensonsPunishers (Bos)LW42211536-810077461263410216.67%2778618.7334761010004683051.40%1073410000.9212000314
9Ben BetkerPunishers (Bos)D80627330240831589037306.67%116179122.39347102460113219100%02646000.3700000003
10Daniel AudettePunishers (Bos)C80179264808384117387414.53%2186710.84000010002573247.03%3701310000.6000000112
11Noah JuulsenPunishers (Bos)D5541923-10180649310238363.92%85133224.24224121310110123000%02749000.3500000000
12Niko MikkolaPunishers (Bos)D8031720-13260521195218115.77%67131816.4903371190111121000%01135000.3000000000
13Carson MeyerPunishers (Bos)RW571271910160382962283719.35%94918.6300004000001137.50%8164000.7700000001
14Connor CliftonPunishers (Bos)D8011617034048935723301.75%59107213.41022457000465000%01337000.3200000002
15John HaydenPunishers (Bos)C4931013-30024244522386.67%53978.1200000000000047.66%128113000.6500000001
16Jesse YlonenPunishers (Bos)RW803811-1318041275914495.08%75987.49000012000000043.75%3297000.3700000000
17Adam RuzickaPunishers (Bos)C34549-224039173791813.51%73309.73000010000262135.29%13657000.5400000011
18Nicolas BeaudinPunishers (Bos)D590774180635201030%235529.3601113000019000%0412000.2500000000
19Joel KivirantaPunishers (Bos)LW225162201593391815.15%41999.0600000000050025.00%445000.6000000000
20Jack AhcanPunishers (Bos)D450331001165510%91683.740000000002000%017000.3600000000
21Ben MeyersPunishers (Bos)C41011-300421020%1832.0300006000070034.78%2303000.2400000000
22Warren FoegelePunishers (Bos)LW180111008124470%41669.26000000001360050.00%407000.1200000000
23Urho VaakanainenPunishers (Bos)D18000-440275110%121639.0700000000011000%00600000000000
24Marcus KarlbergPunishers (Bos)LW34000-300120000%0441.30000020000310061.54%130000000000000
Statistiques d’équipe totales ou en moyenne1411294485779-445115137315262346786134512.53%7672100114.8856891452302211459431766331450.25%4894490467170.74413100313135
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
1Antoine BibeauPunishers (Bos)56281910.8853.913041411981727904410.923135312421
2Cal PetersenPunishers (Bos)3691900.8554.5516220012384838711002753000
3Jack LaFontainePunishers (Bos)50400.8217.551512019106581000015000
Statistiques d’équipe totales ou en moyenne97374210.8734.244816613402681134962138080421


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 Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Non Activé 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 10Non-échange Année 2Non-échange Année 3Non-échange Année 4Non-échange Année 5Non-échange Année 6Non-échange Année 7Non-échange Année 8Non-échange Année 9Non-échange Année 10Lien
Adam RuzickaPunishers (Bos)C191999-01-01Yes220 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Antoine BibeauPunishers (Bos)G241994-01-01No185 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm800,000$3,980$0$0$No900,000$--------No--------
Anton BlidhPunishers (Bos)LW231995-01-01Yes185 Lbs6 ft0NoNoN/ANoNo3FalseFalsePro & Farm800,000$3,980$0$0$No800,000$800,000$-------NoNo-------
Artem ZubPunishers (Bos)D231995-01-01Yes198 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm975,000$4,851$0$0$No975,000$975,000$-------NoNo-------
Ben BetkerPunishers (Bos)D241994-01-01Yes185 Lbs6 ft6NoNoN/ANoNo2FalseFalsePro & Farm950,000$4,726$0$0$No950,000$--------No--------
Ben MeyersPunishers (Bos)C201998-01-01Yes194 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Cal PetersenPunishers (Bos)G241994-01-01No185 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm600,000$2,985$0$0$No600,000$--------No--------
Carson MeyerPunishers (Bos)RW211997-01-01Yes184 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Connor CliftonPunishers (Bos)D231995-01-01Yes185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Corey TroppPunishers (Bos)RW291989-01-01No185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm995,000$4,950$0$0$No------------------
Daniel AudettePunishers (Bos)C221996-01-01Yes176 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Jack AhcanPunishers (Bos)D211997-01-01Yes180 Lbs5 ft9NoNoN/ANoNo2FalseFalsePro & Farm350,000$1,741$0$0$No350,000$--------No--------
Jack LaFontainePunishers (Bos)G201998-01-01No205 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm300,000$1,493$0$0$No300,000$--------No--------
Jesse YlonenPunishers (Bos)RW191999-01-01Yes188 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Joel KivirantaPunishers (Bos)LW221996-01-01Yes180 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm550,000$2,736$0$0$No------------------
John HaydenPunishers (Bos)C231995-01-01Yes185 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
John QuennevillePunishers (Bos)C221996-01-01Yes195 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm750,000$3,731$0$0$No------------------
Kevin RoyPunishers (Bos)C251993-01-01No156 Lbs5 ft8NoNoN/ANoNo1FalseFalsePro & Farm700,000$3,483$0$0$No------------------
Kole LindPunishers (Bos)RW201998-01-01Yes178 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Marcus KarlbergPunishers (Bos)LW182000-01-01Yes165 Lbs5 ft8NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Nicolas BeaudinPunishers (Bos)D191999-01-01Yes168 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Niko MikkolaPunishers (Bos)D221996-01-01Yes185 Lbs6 ft4NoNoN/ANoNo4FalseFalsePro & Farm650,000$3,234$0$0$No650,000$650,000$650,000$------NoNoNo------
Noah JuulsenPunishers (Bos)D211997-01-01Yes198 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm800,000$3,980$0$0$No900,000$--------No--------
Oskar LindblomPunishers (Bos)LW221996-01-01Yes191 Lbs6 ft1NoNoN/ANoNo4FalseFalsePro & Farm925,000$4,602$0$0$No925,000$925,000$925,000$------NoNoNo------
Urho VaakanainenPunishers (Bos)D191999-01-01Yes200 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Warren FoegelePunishers (Bos)LW221996-01-01Yes198 Lbs6 ft2NoNoN/ANoNo4FalseFalsePro & Farm500,000$2,488$0$0$No500,000$500,000$500,000$------NoNoNo------
Zemgus GirgensonsPunishers (Bos)LW241994-01-01Yes186 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm950,000$4,726$0$0$No950,000$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2721.89187 Lbs6 ft11.85633,148$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Oskar LindblomJohn QuennevilleKole Lind40023
2Zemgus GirgensonsKevin RoyCorey Tropp31023
3Anton BlidhAdam RuzickaJesse Ylonen20122
4Joel KivirantaDaniel AudetteCarson Meyer9122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Noah JuulsenArtem Zub40122
2Ben BetkerNiko Mikkola31122
3Connor CliftonNicolas Beaudin19122
4Urho VaakanainenJack Ahcan10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Zemgus GirgensonsJohn QuennevilleCorey Tropp60023
2Oskar LindblomKevin RoyKole Lind40023
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben BetkerArtem Zub60023
2Connor CliftonNiko Mikkola40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1John QuennevilleOskar Lindblom60032
2Kevin RoyCorey Tropp40032
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben BetkerArtem Zub60131
2Connor CliftonNiko Mikkola40131
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1John Quenneville60041Ben BetkerArtem Zub60041
2Corey Tropp40041Connor CliftonNiko Mikkola40041
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1John QuennevilleZemgus Girgensons60122
2Kevin RoyKole Lind40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ben BetkerArtem Zub60122
2Connor CliftonNiko Mikkola40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Zemgus GirgensonsJohn QuennevilleCorey TroppNoah JuulsenArtem Zub
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Oskar LindblomJohn QuennevilleCorey TroppBen BetkerArtem Zub
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Zemgus Girgensons, John Quenneville, Corey TroppJesse Ylonen, Kole LindKevin Roy
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Connor Clifton, Artem Zub, Ben BetkerConnor CliftonNiko Mikkola, Urho Vaakanainen
Tirs de pénalité
John Quenneville, Corey Tropp, Zemgus Girgensons, Anton Blidh, Oskar Lindblom
Gardien
#1 : Antoine Bibeau, #2 : Cal Petersen
Lignes d’attaque personnalisées en prolongation
John Quenneville, Zemgus Girgensons, Corey Tropp, Kole Lind, Oskar Lindblom, Anton Blidh, Anton Blidh, Kevin Roy, Adam Ruzicka, Jesse Ylonen, Joel Kiviranta
Lignes de défense personnalisées en prolongation
Artem Zub, Ben Betker, Niko Mikkola, Urho Vaakanainen, Connor Clifton


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
1Admirals2110000011110110000007431010000047-320.50011203100981139676886290582626662220429111.11%10370.00%0887176950.14%911180950.36%670131450.99%167793717307491415702
2Americans431000002216611000000422321000001814460.75022396100981139671428629058262613732306910220.00%15286.67%1887176950.14%911180950.36%670131450.99%167793717307491415702
3Barracuda21100000811-3110000005411010000037-420.5008142200981139675286290582626642116357114.29%8275.00%0887176950.14%911180950.36%670131450.99%167793717307491415702
4Bears422000001624-822000000106420200000618-1240.5001623390098113967134862905826261444532831119.09%16475.00%0887176950.14%911180950.36%670131450.99%167793717307491415702
5Canucks614000102326-3302000101011-1312000001315-240.333233760009811396719286290582626202545013026623.08%25676.00%0887176950.14%911180950.36%670131450.99%167793717307491415702
6Checkers31200000914-51010000027-52110000077020.33391726009811396795862905826261133322449111.11%11372.73%0887176950.14%911180950.36%670131450.99%167793717307491415702
7Comets412010001618-2311010001314-11010000034-140.5001625410098113967129862905826261405642756116.67%22672.73%1887176950.14%911180950.36%670131450.99%167793717307491415702
8Condors2020000058-31010000024-21010000034-100.000510151098113967688629058262664191836800.00%9277.78%0887176950.14%911180950.36%670131450.99%167793717307491415702
9Crunch32100000137622000000122101010000015-440.667132235019811396787862905826269924277011218.18%11190.91%0887176950.14%911180950.36%670131450.99%167793717307491415702
10Eagles30300000516-1120200000410-61010000016-500.00051015009811396710886290582626992324531218.33%12558.33%0887176950.14%911180950.36%670131450.99%167793717307491415702
11Griffins2010000169-31000000145-11010000024-210.2506111700981139676386290582626693118439111.11%9455.56%0887176950.14%911180950.36%670131450.99%167793717307491415702
12Icehogs413000001217-531200000811-31010000046-220.25012183000981139671248629058262614546327911436.36%16568.75%0887176950.14%911180950.36%670131450.99%167793717307491415702
13Islander311010001214-21100000042220101000812-440.667122234009811396793862905826267427226116318.75%11281.82%1887176950.14%911180950.36%670131450.99%167793717307491415702
14Little Stars624000002728-1312000001011-1312000001717040.333274774009811396722586290582626198635611726830.77%28775.00%0887176950.14%911180950.36%670131450.99%167793717307491415702
15Marlies2200000014104110000009631100000054141.00014223600981139677686290582626702116407114.29%8450.00%0887176950.14%911180950.36%670131450.99%167793717307491415702
16Moose21100000910-11010000058-31100000042220.5009162500981139676486290582626592510519222.22%4175.00%0887176950.14%911180950.36%670131450.99%167793717307491415702
17Penguins3020001078-1201000105501010000023-120.333712190098113967101862905826269043227112216.67%11372.73%0887176950.14%911180950.36%670131450.99%167793717307491415702
18Phantoms20200000610-41010000047-31010000023-100.0006111700981139676686290582626731816357114.29%8275.00%0887176950.14%911180950.36%670131450.99%167793717307491415702
19Reign220000001688110000009451100000074341.000162440009811396772862905826266522163644100.00%8187.50%0887176950.14%911180950.36%670131450.99%167793717307491415702
20Rocket2110000011110110000007251010000049-520.5001120310098113967658629058262678201935700.00%6433.33%0887176950.14%911180950.36%670131450.99%167793717307491415702
21Senators2020000058-31010000013-21010000045-100.00059140098113967648629058262658282459111.11%20100.00%0887176950.14%911180950.36%670131450.99%167793717307491415702
22Silver Knights321000001394110000006242110000077040.6671321341098113967102862905826261023166814428.57%3166.67%0887176950.14%911180950.36%670131450.99%167793717307491415702
23Thunderbirds834010002230-8422000001213-1412010001017-780.500223860009811396723586290582626277996216432515.63%31487.10%0887176950.14%911180950.36%670131450.99%167793717307491415702
24Wolfpack411020001715210001000321311010001413160.75017324900981139671138629058262613145269421314.29%13284.62%1887176950.14%911180950.36%670131450.99%167793717307491415702
25Wranglers22000000954110000005321100000042241.0009162500981139676986290582626662216368112.50%80100.00%0887176950.14%911180950.36%670131450.99%167793717307491415702
Total80304205021314343-29401817020211611481340122503000153195-42750.4693145368502198113967260786290582626268387062016123015618.60%3057475.74%4887176950.14%911180950.36%670131450.99%167793717307491415702
_Since Last GM Reset80304205021314343-29401817020211611481340122503000153195-42750.4693145368502198113967260786290582626268387062016123015618.60%3057475.74%4887176950.14%911180950.36%670131450.99%167793717307491415702
_Vs Conference50162705020180209-292510110202091856256160300089124-35460.4601803064861198113967161486290582626166954339110301963718.88%1944477.32%3887176950.14%911180950.36%670131450.99%167793717307491415702
_Vs Division20612010107284-121036000103235-31036010004049-9160.40072122194009811396765286290582626677216168411841922.62%841779.76%0887176950.14%911180950.36%670131450.99%167793717307491415702

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8075W131453685026072683870620161221
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8030425021314343
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4018172021161148
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4012253000153195
Derniers 10 matchs
WLOTWOTL SOWSOL
532000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3015618.60%3057475.74%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
8629058262698113967
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
887176950.14%911180950.36%670131450.99%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
167793717307491415702


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
315Thunderbirds6Punishers2LSommaire du match
529Thunderbirds4Punishers1LSommaire du match
842Punishers8Canucks6WSommaire du match
1056Comets3Punishers5WSommaire du match
1163Punishers5Americans8LSommaire du match
1266Punishers4Thunderbirds2WSommaire du match
1475Punishers3Little Stars6LSommaire du match
1897Canucks5Punishers4LSommaire du match
20110Little Stars4Punishers2LSommaire du match
21113Punishers6Wolfpack4WSommaire du match
24129Punishers4Silver Knights6LSommaire du match
25132Punishers1Thunderbirds6LSommaire du match
28151Little Stars3Punishers2LSommaire du match
30163Punishers4Little Stars9LSommaire du match
32174Punishers7Americans2WSommaire du match
33181Icehogs4Punishers1LSommaire du match
38203Canucks3Punishers2LSommaire du match
40215Punishers4Moose2WSommaire du match
44229Moose8Punishers5LSommaire du match
47247Little Stars4Punishers6WSommaire du match
53272Condors4Punishers2LSommaire du match
56290Reign4Punishers9WSommaire du match
60309Punishers1Crunch5LSommaire du match
62318Griffins5Punishers4LXXSommaire du match
65335Punishers4Icehogs6LSommaire du match
66344Phantoms7Punishers4LSommaire du match
69359Punishers3Silver Knights1WSommaire du match
71370Silver Knights2Punishers6WSommaire du match
74388Punishers4Senators5LSommaire du match
76399Wranglers3Punishers5WSommaire du match
80417Punishers1Eagles6LSommaire du match
82423Checkers7Punishers2LSommaire du match
84439Punishers2Griffins4LSommaire du match
86451Marlies6Punishers9WSommaire du match
88459Punishers7Reign4WSommaire du match
92477Bears3Punishers6WSommaire du match
94489Punishers4Wranglers2WSommaire du match
96502Canucks3Punishers4WXXSommaire du match
99519Punishers4Canucks5LSommaire du match
101530Bears3Punishers4WSommaire du match
104548Thunderbirds2Punishers6WSommaire du match
108569Punishers2Phantoms3LSommaire du match
110575Barracuda4Punishers5WSommaire du match
115599Penguins2Punishers1LSommaire du match
117613Punishers10Little Stars2WSommaire du match
119625Rocket2Punishers7WSommaire du match
121633Punishers2Penguins3LSommaire du match
123646Punishers5Bears10LSommaire du match
124656Comets8Punishers4LSommaire du match
127670Punishers1Thunderbirds6LSommaire du match
128681Thunderbirds1Punishers3WSommaire du match
131694Punishers5Marlies4WSommaire du match
134708Wolfpack2Punishers3WXSommaire du match
136722Punishers4Rocket9LSommaire du match
138733Comets3Punishers4WXSommaire du match
140746Punishers3Condors4LSommaire du match
142757Punishers6Americans4WSommaire du match
143764Senators3Punishers1LSommaire du match
146785Admirals4Punishers7WSommaire du match
147791Punishers4Admirals7LSommaire du match
149803Punishers1Canucks4LSommaire du match
152814Eagles4Punishers2LSommaire du match
157837Penguins3Punishers4WXXSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
159847Punishers3Comets4LSommaire du match
162862Punishers6Wolfpack5WXSommaire du match
163867Icehogs4Punishers3LSommaire du match
166876Punishers1Bears8LSommaire du match
168889Punishers2Wolfpack4LSommaire du match
170897Crunch0Punishers6WSommaire du match
172910Punishers3Barracuda7LSommaire du match
174922Eagles6Punishers2LSommaire du match
178942Icehogs3Punishers4WSommaire du match
179950Punishers4Checkers1WSommaire du match
182966Crunch2Punishers6WSommaire du match
183974Punishers1Islander6LSommaire du match
187993Punishers7Islander6WXSommaire du match
1891000Islander2Punishers4WSommaire du match
1941017Punishers3Checkers6LSommaire du match
1961022Punishers4Thunderbirds3WXSommaire du match
2001039Americans2Punishers4WSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance72,12936,759
Assistance PCT90.16%91.90%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2722 - 90.74% 171,134$6,845,357$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,172,125$ 2,429,500$ 2,284,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
12,087$ 1,813,962$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 1 13,580$ 13,580$




Punishers Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Punishers Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Punishers Statistiques de l'Équipe de Carrière

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

Punishers Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Punishers Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA