Checkers
GP: 0 | W: 0 | L: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Dylan Jacob-Smith | Morale : 50 | Moyenne d'Équipe : 64
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Statistiques d'Équipe


Directeur généralDylan Jacob-Smith
Atlantic Division
Eastern Conference
Mike Reilly
Brad Hunt




Capacité de l'Aréna5,000
Assistance
5,000




21
20
41 / 55
Éspoirs40


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 Moyen
1Pat Maroon0XX100.008156867484489759406870686565650507503521,000,000$
2Jakub Lauko (R)0XX100.00835394808439555840697155656565050740231925,000$
3Vitali Kravtsov (R)0XX100.00705296668349555840677063646464050720231750,000$
4Will Cuylle (R)0X100.00546581555481944336586546542540050630212828,333$
5Xavier Simoneau (R)0X100.00556179555573844265616342532540050620221750,000$
6Byron Froese0X100.00535881555565754365606444542540050610322750,000$
7Tim Gettinger (R)0XX100.00535382565658614436606447542540050610253787,500$
8Emilio Pettersen (R)0X100.00536083555569804365596448542540050610231925,000$
9Jamieson Rees (R)0X100.00556180555472834265606442532540050610222925,000$
10Greg McKegg0XX100.00546381525378903865576440512540050600311762,500$
11Jonathan Gruden (R)0X100.00545781555563734236586541532540050600231925,000$
12Jayce Hawryluk (R)0XX100.00554380535758454036586441522540050590271750,000$
13Mike Reilly (C)0X100.007451966980655566406768556767670507502943,480,000$
14Brad Hunt (A)0X100.00685296688047566140696963656565050730341772,500$
15Brian Lashoff0X100.00526483515279913736566336502540050590321750,000$
16Cameron Gaunce0X100.00546181525372833836576340512540050590331750,000$
17Seth Helgeson0X100.00566578515281943636566336502540050590321750,000$
18Kim Nousiainen (R)0X100.00514985515358503736566335502540050560222859,167$
Rayé
1Brad Lambert (R)0XX100.00533782525758453765566429512540050560194925,000$
MOYENNE D'ÉQUIPE100.0059568458626472454661654656364705063
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 Moyen
1Malcolm Subban100.0073707777767574767774762555050780291867,000$
2Logan Flodell100.0066655340636055556067582555050590261750,000$
Rayé
MOYENNE D'ÉQUIPE100.007068655970686566697167255505069
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'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
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


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 RestantSalaire MoyenSalaire Moyen 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
Brad HuntCheckers (FLA)D341988-08-24No185 Lbs5 ft9NoNoNo1Pro & Farm772,500$27,589$772,500$27,589$0$0$NoLien / Lien NHL
Brad LambertCheckers (FLA)C/RW192003-12-19Yes183 Lbs6 ft0NoNoNo4Farm Only925,000$33,036$925,000$33,036$0$0$No925,000$925,000$925,000$Lien NHL
Brian LashoffCheckers (FLA)D321990-07-16No215 Lbs6 ft3NoNoNo1Pro & Farm750,000$26,786$750,000$26,786$0$0$NoLien / Lien NHL
Byron FroeseCheckers (FLA)C321991-03-12No202 Lbs6 ft1NoNoNo2Pro & Farm750,000$26,786$750,000$26,786$0$0$No750,000$Lien / Lien NHL
Cameron GaunceCheckers (FLA)D331990-03-19No194 Lbs6 ft1NoNoNo1Pro & Farm750,000$26,786$750,000$26,786$0$0$NoLien / Lien NHL
Emilio PettersenCheckers (FLA)C232000-04-03Yes170 Lbs5 ft10NoNoNo1Pro & Farm925,000$33,036$925,000$33,036$0$0$NoLien / Lien NHL
Greg McKeggCheckers (FLA)C/LW311992-06-17No194 Lbs6 ft0NoNoNo1Pro & Farm762,500$27,232$762,500$27,232$0$0$NoLien / Lien NHL
Jakub LaukoCheckers (FLA)LW/RW232000-03-28Yes184 Lbs6 ft0NoNoNo1Farm Only925,000$33,036$925,000$33,036$0$0$NoLien / Lien NHL
Jamieson ReesCheckers (FLA)C222001-02-26Yes172 Lbs5 ft11NoNoNo2Farm Only925,000$33,036$925,000$33,036$0$0$No925,000$Lien / Lien NHL
Jayce HawrylukCheckers (FLA)LW/RW271996-01-01Yes189 Lbs5 ft11NoNoNo1Pro & Farm750,000$26,786$750,000$26,786$0$0$NoLien / Lien NHL
Jonathan GrudenCheckers (FLA)LW232000-05-04Yes172 Lbs6 ft0NoNoNo1Pro & Farm925,000$33,036$925,000$33,036$0$0$NoLien / Lien NHL
Kim NousiainenCheckers (FLA)D222000-11-14Yes181 Lbs5 ft8NoNoNo2Pro & Farm859,167$30,685$859,167$30,685$0$0$No859,167$Lien / Lien NHL
Logan FlodellCheckers (FLA)G261997-02-10No174 Lbs6 ft1NoNoNo1Pro & Farm750,000$26,786$750,000$26,786$0$0$NoLien / Lien NHL
Malcolm SubbanCheckers (FLA)G291993-12-21No217 Lbs6 ft2NoNoNo1Pro & Farm867,000$30,964$867,000$30,964$0$0$NoLien / Lien NHL
Mike Reilly (Contrat à 1 Volet)Checkers (FLA)D291993-07-13No190 Lbs6 ft1NoNoNo4Pro & Farm3,480,000$124,286$3,480,000$124,286$2,355,000$84,107$No3,480,000$3,480,000$3,480,000$Lien / Lien NHL
Pat MaroonCheckers (FLA)LW/RW351988-04-23No234 Lbs6 ft3NoNoNo2Pro & Farm1,000,000$35,714$1,000,000$35,714$0$0$No1,000,000$Lien / Lien NHL
Seth HelgesonCheckers (FLA)D321990-10-08No220 Lbs6 ft4NoNoNo1Pro & Farm750,000$26,786$750,000$26,786$0$0$NoLien / Lien NHL
Tim GettingerCheckers (FLA)LW/RW251998-04-14Yes218 Lbs6 ft6NoNoNo3Pro & Farm787,500$28,125$787,500$28,125$0$0$No787,500$787,500$Lien / Lien NHL
Vitali KravtsovCheckers (FLA)LW/RW231999-12-23Yes186 Lbs6 ft3NoNoNo1Pro & Farm750,000$26,786$750,000$26,786$0$0$NoLien / Lien NHL
Will CuylleCheckers (FLA)LW212002-02-05Yes204 Lbs6 ft3NoNoNo2Pro & Farm828,333$29,583$828,333$29,583$0$0$No828,333$Lien / Lien NHL
Xavier SimoneauCheckers (FLA)C222001-05-19Yes183 Lbs5 ft6NoNoNo1Pro & Farm750,000$26,786$750,000$26,786$0$0$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2126.81194 Lbs6 ft11.62951,524$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Pat MaroonXavier SimoneauVitali Kravtsov30122
2Jakub LaukoEmilio PettersenTim Gettinger30122
3Will CuylleJamieson ReesJayce Hawryluk20122
4Jonathan GrudenByron FroesePat Maroon20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mike ReillyKim Nousiainen30122
2Brad HuntCameron Gaunce30122
3Brian LashoffSeth Helgeson20122
4Mike ReillyBrad Hunt20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Pat MaroonXavier SimoneauWill Cuylle50122
2Jakub LaukoEmilio PettersenTim Gettinger50122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mike ReillyBrian Lashoff50122
2Brad HuntCameron Gaunce50122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Pat MaroonXavier Simoneau50122
2Jakub LaukoWill Cuylle50122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mike ReillyBrian Lashoff50122
2Brad HuntCameron Gaunce50122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Pat Maroon50122Mike ReillyBrian Lashoff50122
2Jakub Lauko50122Brad HuntCameron Gaunce50122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Pat MaroonXavier Simoneau50122
2Jakub LaukoWill Cuylle50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mike ReillyBrian Lashoff50122
2Brad HuntCameron Gaunce50122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Pat MaroonXavier SimoneauJakub LaukoMike ReillyBrad Hunt
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Pat MaroonXavier SimoneauJakub LaukoMike ReillyBrad Hunt
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Greg McKegg, Jamieson Rees, Byron FroeseGreg McKegg, Jamieson ReesByron Froese
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brian Lashoff, Mike Reilly, Brad HuntBrian LashoffMike Reilly, Brad Hunt
Tirs de Pénalité
Pat Maroon, Jamieson Rees, Jakub Lauko, Will Cuylle, Xavier Simoneau
Gardien
#1 : Malcolm Subban, #2 : Logan Flodell
Lignes d'Attaque Perso. en Prol.
Pat Maroon, Greg McKegg, Jakub Lauko, Will Cuylle, Xavier Simoneau, Tim Gettinger, Tim Gettinger, Emilio Pettersen, Jamieson Rees, Byron Froese, Jonathan Gruden
Lignes de Défense Perso. en Prol.
Mike Reilly, Kim Nousiainen, Brad Hunt, Cameron Gaunce, Brian Lashoff


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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
00N/A0000000000
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 Matchs
WLOTWOTL SOWSOL
000000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
000.00%000.00%0
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
00000000
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
000.00%000.00%000.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
000000


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



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna35001500
Prix des Billets5025
Assistance0.00%0.00%
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
41 0 - 0.00%0$0$5000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 16,502,000$ 16,502,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

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




Checkers

# 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
1Kyle Capobianco1389617226814436417416731030.97%169276020.00162642462466600.00%111.9400
2Mike Reilly95486911739217515938112.60%139231624.387916290224520.00%01.0101
3Jakub Lauko1674473117-804772251855877.50%105233413.985141930101105452.30%11.0048
4Brad Hunt8246539921210318138312.01%174176821.5788164002211650.00%31.1200
5Tim Gettinger16428679531842251363697.59%69296618.0964104300006235.90%10.6400

Checkers

# Nom du Gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA
1Malcolm Subban48291540.8973.552905001721663970600.84613
2Alex Lyon29161120.9033.2317480094965572400.0000
3Jon Gillies36151740.8863.752177001361197670310.7789
4Cameron Johnson1712410.9182.7610230147573355200.0000

Checkers

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
2021826215012205522712814132800100312135177413070112024013610413255289714490160189173187205405916548032182834170410451967136.22%2124678.30%14526111047.39%691147246.94%646143045.17%1711112220076171213607
2021821720144071536-465411330133043262-219410390011028274-24616711312020409183982501712404111768713143964922693.98%1074557.94%135075646.30%35984442.54%562121846.14%248019961489501974449
20228237320561131127932412210034111701195141152202200141160-19933115468571111211776628719941027831272736103733617211713721.64%1682883.33%8757150250.40%735149949.03%559113649.21%1798112418116681343675
2023823430059313232843941238045101821206241112201421141164-2394323538861001309986930661136978931392815107658717171343929.10%1283076.56%2796160949.47%755152649.48%586116150.47%1851118617586621349676
Total Saison Régulière3281341490122110212571370-113164785908135170763671164569004851550734-18433512572112336912124241435324188162130276726561280950136604066513272715621.46%61514975.77%252429497748.80%2540534147.56%2353494547.58%784154287066245048812409
Séries
2021404000002457-33202000001435-21202000001022-1202439630001428118043215412040805113323.08%10640.00%1357149.30%154235.71%5311546.09%966679296429
Total Séries404000002457-33202000001435-21202000001022-1202439630001428118043215412040805113323.08%10640.00%1357149.30%154235.71%5311546.09%966679296429

Checkers

# 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

Checkers

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