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Connexion

Checkers
GP: 80 | W: 44 | L: 30 | OTL: 6 | P: 94
GF: 358 | GA: 338 | PP%: 22.79% | PK%: 75.17%
DG: Jean-Francois Chouinard | Morale : 51 | Moyenne d’équipe : 66
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Centre de jeu
Checkers
44-30-6, 94pts
8
FINAL
6 Admirals
33-35-12, 78pts
Team Stats
L1SéquenceW1
25-13-2Fiche domicile18-17-5
19-17-4Fiche domicile15-18-7
5-5-0Derniers 10 matchs3-7-0
4.48Buts par match 4.15
4.23Buts contre par match 4.44
22.79%Pourcentage en avantage numérique26.45%
75.17%Pourcentage en désavantage numérique77.44%
Checkers
44-30-6, 94pts
4
FINAL
7 Bears
43-32-5, 91pts
Team Stats
L1SéquenceW2
25-13-2Fiche domicile23-15-2
19-17-4Fiche domicile20-17-3
5-5-0Derniers 10 matchs6-4-0
4.48Buts par match 4.26
4.23Buts contre par match 3.79
22.79%Pourcentage en avantage numérique18.60%
75.17%Pourcentage en désavantage numérique80.20%
Meneurs d'équipe
Buts
Drake Batherson
66
Passes
Drake Batherson
83
Points
Drake Batherson
149
Plus/Moins
Kale Clague
24
Victoires
Brandon Halverson
36
Pourcentage d’arrêts
Brandon Halverson
0.874

Statistiques d’équipe
Buts pour
358
4.48 GFG
Tirs pour
2665
33.31 Avg
Pourcentage en avantage numérique
22.8%
80 GF
Début de zone offensive
38.3%
Buts contre
338
4.23 GAA
Tirs contre
2496
31.20 Avg
Pourcentage en désavantage numérique
75.2%%
71 GA
Début de la zone défensive
34.3%
Informations de l'équipe

Directeur généralJean-Francois Chouinard
EntraîneurPavel Bure
DivisionPaul-Loicq
ConférenceLouis-Magnus
CapitaineAnthony Beauvillier
Assistant #1Andrei Svechnikov
Assistant #2Radim Simek


Informations de l’aréna

Capacité3,000
Assistance2,793
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure19
Limite contact 46 / 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
1Drake Batherson (R)X100.006141809164826484687074618851526265720201500,000$
2Patrick BrownX100.007454776674667576777381647560554849720262950,000$
3Anthony Beauvillier (R) (C)X100.007247777474697573777772687554475771710213800,000$
4Dominik Kahun (R)X100.006330827268817976868171596058505071710231975,000$
5Tanner Laczynski (R)X100.005935797763736273717469628046465565680213700,000$
6Matt PuempelX100.007040827370687369686674567450514069670251600,000$
7Dylan Gambrell (R)X100.006333766568666667768372556348465571670222900,000$
8Austin Poganski (R)X100.006945767371597666636470646148453923660221500,000$
9Roberts Lipsbergs (R)X100.007232756878736467776768606948513771660242550,000$
10Morgan Frost (R)X100.005832776659686468827968506042417162640191500,000$
11Andrei Svechnikov (R) (A)X100.005733767848655780646468528740409071640182500,000$
12Kirill Marchenko (R)X100.005430706565675860475079415940407242580182500,000$
13John DraegerX100.006922757576727363487366846266533469720252950,000$
14Radim Simek (R) (A)X100.0075379069736771603877508352524661617102231,200,000$
15Jake Walman (R)X100.006434867474736965426652764646454661680221600,000$
16Timothy Liljegren (R)X100.005426837860627276418366705249417235670191500,000$
17Kale Clague (R)X100.005733827565586778407755744647446574670204700,000$
18Jared McIsaac (R)X100.005032727051526372257147583740406237580182500,000$
Rayé
1Mitchell HeardX100.007632717476636765637271666153532818670261650,000$
2Nicklas JensenX100.006553806967707074697066616751513819670251600,000$
3Artur Kayumov (R)X100.006648775656605760546258526842426120580202800,000$
4Viktor Baldayev (R)X100.007149737175647271486755775350484119690232700,000$
5Simon Bourque (R)X100.004134555747516056286342604643434520520211300,000$
MOYENNE D’ÉQUIPE100.00633777716666687059716563634947535166
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
1Brandon Halverson100.00727974727770727470707552464872710223900,000$
2Joseph Woll (R)100.00706479594980755553786843427072630202500,000$
Rayé
1Ivan Prosvetov (R)100.00774566677851456159556843425920590192500,000$
2Jakub Skarek (R)100.00735457727456545858477141436320590192500,000$
MOYENNE D’ÉQUIPE100.0073616968706462626063714543604663
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Pavel Bure54607666334563RUS483800,000$


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
1Drake BathersonCheckers (Flo)RW78668314975601209345116924414.63%29156720.0922274968291000037243.06%14412924061.90110001686
2Dominik KahunCheckers (Flo)C80477612374201341432528914518.65%37174421.8014264043301101111308456.29%24963730011.41010007711
3Anthony BeauvillierCheckers (Flo)LW7938478555801631122276312616.74%38167721.24913223324722472113047.06%1364827101.0114000445
4Andrei SvechnikovCheckers (Flo)LW804137787460120802177014818.89%29139417.4310102033270000055145.00%804316001.1214000732
5Dylan GambrellCheckers (Flo)C8019496815460115106138358013.77%20125315.6721113112240001223053.69%8682116001.0900000124
6Patrick BrownCheckers (Flo)RW612628541026012568149498317.45%31101416.629514191850001393149.12%573122001.0701000233
7Tanner LaczynskiCheckers (Flo)C792924531243558541905711615.26%2290711.493034140001353243.70%1194416001.1702000232
8Timothy LiljegrenCheckers (Flo)D74103545-352605910510340489.71%89153020.68791617274000036200%03439000.5900000021
9Kale ClagueCheckers (Flo)D8073643243758813213436565.22%110189823.742911162830002157120%02653000.4500100011
10Matt PuempelCheckers (Flo)LW801724411028012471131468112.98%18106013.2603314700041043145.45%332710000.7711000121
11Radim SimekCheckers (Flo)D804293314801161579846454.08%143215126.8926882450000253100%01393000.3100000103
12Morgan FrostCheckers (Flo)C78131932-171403741110326911.82%66748.650000130000371354.59%229143000.9500000022
13Roberts LipsbergsCheckers (Flo)LW80101525-11100955379286112.66%117429.29000010003842247.83%231412010.6700000120
14John DraegerCheckers (Flo)D72024241857584918936230%91132818.450112390001172000%01942000.3600000001
15Jake WalmanCheckers (Flo)D700101088055852912240%62105315.050000190110199000%0732000.1900000000
16Jared McIsaacCheckers (Flo)D61088-822026402417170%4385314.00022112900008000%0316000.1900000000
17Kirill MarchenkoCheckers (Flo)RW56527-722035123371415.15%84848.6400000000000036.36%1199000.2900000000
18Austin PoganskiCheckers (Flo)RW2251608025122791218.52%31768.03000020000011100.00%344000.6800000000
19Viktor BaldayevCheckers (Flo)D35066-2200394918750%2952314.95000049000016000%0715000.2300000000
20Nicklas JensenCheckers (Flo)RW30314-120027194113237.32%42498.3000004000001150.00%2112000.3200000000
21Jerry D'AmigoPanthersRW2011-100143210%02512.580000000003000%211000.8000000000
22Mitchell HeardCheckers (Flo)C31010203240025.00%0217.0300000000000050.00%1411000.9500000000
23Artur KayumovCheckers (Flo)LW2000-100110000%0105.0800000000010050.00%20000000000000
Statistiques d’équipe totales ou en moyenne13623415558964357915165015302547863142113.39%8232234216.40801222022562646336311526442054.04%4219543483180.80414100423942
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
1Brandon HalversonCheckers (Flo)65361950.8743.9236714024019079551020.500126119220
2Joseph WollCheckers (Flo)2481110.8424.801162209358829350001961000
Statistiques d’équipe totales ou en moyenne89443060.8674.1348346033324951248152128080220


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
Andrei SvechnikovCheckers (Flo)LW182000-01-01Yes195 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Anthony BeauvillierCheckers (Flo)LW211997-01-01Yes182 Lbs5 ft11NoNoN/ANoNo3FalseFalsePro & Farm800,000$3,980$0$0$No1,000,000$1,500,000$-------NoNo-------
Artur KayumovCheckers (Flo)LW201998-01-01Yes176 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm800,000$3,980$0$0$No800,000$--------No--------
Austin PoganskiCheckers (Flo)RW221996-01-01Yes198 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Brandon HalversonCheckers (Flo)G221996-01-01No203 Lbs6 ft4NoNoN/ANoNo3FalseFalsePro & Farm900,000$4,478$0$0$No1,300,000$1,500,000$-------NoNo-------
Dominik KahunCheckers (Flo)C231995-01-01Yes175 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm975,000$4,851$0$0$No------------------
Drake BathersonCheckers (Flo)RW201998-01-01Yes204 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Dylan GambrellCheckers (Flo)C221996-01-01Yes194 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm900,000$4,478$0$0$No900,000$--------No--------
Ivan ProsvetovCheckers (Flo)G191999-01-01Yes195 Lbs6 ft5NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Jake WalmanCheckers (Flo)D221996-01-01Yes180 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm600,000$2,985$0$0$No------------------
Jakub SkarekCheckers (Flo)G191999-01-01Yes205 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Jared McIsaacCheckers (Flo)D182000-01-01Yes192 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
John DraegerCheckers (Flo)D251993-01-01No186 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm950,000$4,726$0$0$No950,000$--------No--------
Joseph WollCheckers (Flo)G201998-01-01Yes203 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Kale ClagueCheckers (Flo)D201998-01-01Yes176 Lbs6 ft0NoNoN/ANoNo4FalseFalsePro & Farm700,000$3,483$0$0$No950,000$1,300,000$1,900,000$------NoNoNo------
Kirill MarchenkoCheckers (Flo)RW182000-01-01Yes187 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm500,000$2,488$0$0$No500,000$--------No--------Lien
Matt PuempelCheckers (Flo)LW251993-01-01No190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm600,000$2,985$0$0$No------------------
Mitchell HeardCheckers (Flo)C261992-01-01No188 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm650,000$3,234$0$0$No------------------
Morgan FrostCheckers (Flo)C191999-01-01Yes170 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Nicklas JensenCheckers (Flo)RW251993-01-01No186 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm600,000$2,985$0$0$No------------------
Patrick BrownCheckers (Flo)RW261992-01-01No210 Lbs6 ft1NoNoN/ANoYes2FalseFalsePro & Farm950,000$4,726$0$0$No950,000$--------No--------
Radim SimekCheckers (Flo)D221996-01-01Yes204 Lbs6 ft0NoNoN/ANoNo3FalseFalsePro & Farm1,200,000$5,970$0$0$No1,600,000$2,100,000$-------NoNo-------
Roberts LipsbergsCheckers (Flo)LW241994-01-01Yes185 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm550,000$2,736$0$0$No550,000$--------No--------
Simon BourqueCheckers (Flo)D211997-01-01Yes198 Lbs6 ft1NoNoN/ANoNo1FalseFalseFarm Only300,000$1,493$0$0$No------------------
Tanner LaczynskiCheckers (Flo)C211997-01-01Yes205 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm700,000$3,483$0$0$No900,000$1,200,000$-------NoNo-------
Timothy LiljegrenCheckers (Flo)D191999-01-01Yes192 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$2,488$0$0$No------------------
Viktor BaldayevCheckers (Flo)D231995-01-01Yes185 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm700,000$3,483$0$0$No700,000$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2721.48191 Lbs6 ft11.85662,037$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anthony BeauvillierDominik KahunDrake Batherson40023
2Andrei SvechnikovDylan GambrellPatrick Brown30023
3Matt PuempelTanner LaczynskiKirill Marchenko20023
4Roberts LipsbergsMorgan FrostAustin Poganski10023
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Radim SimekKale Clague40023
2John DraegerTimothy Liljegren30023
3Jake WalmanJared McIsaac20023
4Radim SimekKale Clague10023
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anthony BeauvillierDominik KahunDrake Batherson60014
2Andrei SvechnikovDylan GambrellPatrick Brown40014
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Timothy LiljegrenRadim Simek60023
2Kale ClagueJared McIsaac40023
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Dominik KahunAnthony Beauvillier60032
2Dylan GambrellPatrick Brown40032
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Radim SimekJohn Draeger60041
2Kale ClagueJake Walman40041
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Anthony Beauvillier60032Radim SimekJohn Draeger60041
2Dominik Kahun40032Kale ClagueJake Walman40041
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Dominik KahunDrake Batherson60023
2Dylan GambrellAnthony Beauvillier40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Radim SimekKale Clague60023
2John DraegerTimothy Liljegren40023
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Anthony BeauvillierDominik KahunDrake BathersonTimothy LiljegrenKale Clague
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Anthony BeauvillierDominik KahunPatrick BrownRadim SimekJohn Draeger
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Andrei Svechnikov, Anthony Beauvillier, Drake BathersonAndrei Svechnikov, Drake BathersonMatt Puempel
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Kale Clague, Timothy Liljegren, Radim SimekRadim SimekKale Clague, Timothy Liljegren
Tirs de pénalité
Patrick Brown, Drake Batherson, Andrei Svechnikov, Dominik Kahun, Anthony Beauvillier
Gardien
#1 : Joseph Woll, #2 : Brandon Halverson
Lignes d’attaque personnalisées en prolongation
Patrick Brown, Drake Batherson, Anthony Beauvillier, Dominik Kahun, Kirill Marchenko, Tanner Laczynski, Tanner Laczynski, Dylan Gambrell, Morgan Frost, Andrei Svechnikov, Matt Puempel
Lignes de défense personnalisées en prolongation
Radim Simek, John Draeger, Kale Clague, Timothy Liljegren, Jake Walman


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
1Admirals431000002319421100000880220000001511460.7502341640096116139815187093485023107441810015320.00%9277.78%0982186952.54%891167453.23%755133956.39%176199216287401448739
2Americans220000001046110000006241100000042241.000102030009611613987287093485023621712508112.50%60100.00%0982186952.54%891167453.23%755133956.39%176199216287401448739
3Barracuda2100010014951000010056-11100000093630.750142438009611613986187093485023581611508225.00%3166.67%0982186952.54%891167453.23%755133956.39%176199216287401448739
4Bears413000001522-72110000089-120200000713-620.25015254000961161398138870934850231293530838225.00%15566.67%1982186952.54%891167453.23%755133956.39%176199216287401448739
5Canucks403000011323-1020100001710-320200000613-710.125131831009611613981358709348502312535268713215.38%14285.71%0982186952.54%891167453.23%755133956.39%176199216287401448739
6Comets31100100912-31100000041320100100511-630.50091221009611613981018709348502378342078600.00%10370.00%1982186952.54%891167453.23%755133956.39%176199216287401448739
7Condors2110000089-11010000036-31100000053220.50081018009611613987587093485023693116318337.50%8275.00%0982186952.54%891167453.23%755133956.39%176199216287401448739
8Crunch613020002627-1310020001376303000001320-760.5002645710096116139819787093485023205646013624729.17%30486.67%0982186952.54%891167453.23%755133956.39%176199216287401448739
9Eagles6310100128262321000001315-2310010011511490.7502849770096116139819387093485023185596912639820.51%28871.43%0982186952.54%891167453.23%755133956.39%176199216287401448739
10Griffins2010100068-2100010004311010000025-320.50061016109611613985087093485023532325509111.11%5180.00%0982186952.54%891167453.23%755133956.39%176199216287401448739
11Icehogs20200000711-41010000046-21010000035-200.000781500961161398718709348502369198416116.67%4175.00%1982186952.54%891167453.23%755133956.39%176199216287401448739
12Islander412001001819-121100000131212010010057-230.375182745009611613981298709348502312547287216637.50%14471.43%0982186952.54%891167453.23%755133956.39%176199216287401448739
13Little Stars31200000710-3110000003122020000049-520.333713200096116139871870934850237628206510110.00%10460.00%0982186952.54%891167453.23%755133956.39%176199216287401448739
14Marlies211000009811010000023-11100000075220.50091827009611613987187093485023662514417114.29%7271.43%0982186952.54%891167453.23%755133956.39%176199216287401448739
15Moose210010001293110000007521000100054141.000121830009611613986287093485023623014447228.57%70100.00%0982186952.54%891167453.23%755133956.39%176199216287401448739
16Penguins65100000312293300000018993210000013130100.8333151820096116139820887093485023182695213038821.05%26676.92%0982186952.54%891167453.23%755133956.39%176199216287401448739
17Phantoms211000007701010000035-21100000042220.500791610961161398618709348502356241257600.00%6266.67%0982186952.54%891167453.23%755133956.39%176199216287401448739
18Punishers321000001495211000007701100000072540.66714253900961161398113870934850239530187511327.27%9188.89%0982186952.54%891167453.23%755133956.39%176199216287401448739
19Reign22000000853110000004221100000043141.00081624009611613987087093485023502664112325.00%3166.67%0982186952.54%891167453.23%755133956.39%176199216287401448739
20Rocket21100000121111010000047-31100000084420.500122032009611613986987093485023822512449111.11%6183.33%0982186952.54%891167453.23%755133956.39%176199216287401448739
21Senators2110000011101110000009631010000024-220.5001119300096116139856870934850236281651800.00%8275.00%0982186952.54%891167453.23%755133956.39%176199216287401448739
22Silver Knights32100000151231100000054121100000108240.66715233800961161398107870934850239530186816531.25%9366.67%1982186952.54%891167453.23%755133956.39%176199216287401448739
23Thunderbirds321000001082211000007611100000032140.66710172700961161398100870934850231003718561119.09%9277.78%0982186952.54%891167453.23%755133956.39%176199216287401448739
24Wolfpack7410101037251243001000241593110001013103120.85737589500961161398228870934850232277270150481735.42%351071.43%0982186952.54%891167453.23%755133956.39%176199216287401448739
25Wranglers20100001813-51010000037-41000000156-110.25081220009611613987687093485023781910438225.00%5420.00%0982186952.54%891167453.23%755133956.39%176199216287401448739
Total8037300631335833820402113041011841622240161702212174176-2940.58835858894620961161398266587093485023249684760317693518022.79%2867175.17%4982186952.54%891167453.23%755133956.39%176199216287401448739
_Since Last GM Reset8037300631335833820402113041011841622240161702212174176-2940.58835858894620961161398266587093485023249684760317693518022.79%2867175.17%4982186952.54%891167453.23%755133956.39%176199216287401448739
_Vs Conference522320042122232158261660300112296262671401211101119-18600.57722336358600961161398172087093485023162254042911262406025.00%2095275.12%3982186952.54%891167453.23%755133956.39%176199216287401448739
_Vs Division25136040111221002213910300068462212450101154540370.74012220332500961161398826870934850237992642515421494026.85%1192876.47%0982186952.54%891167453.23%755133956.39%176199216287401448739

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8094L135858894626652496847603176920
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8037306313358338
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4021134101184162
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4016172212174176
Derniers 10 matchs
WLOTWOTL SOWSOL
451000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3518022.79%2867175.17%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
87093485023961161398
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
982186952.54%891167453.23%755133956.39%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
176199216287401448739


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
313Checkers6Eagles5WXSommaire du match
423Wolfpack3Checkers6WSommaire du match
738Wolfpack4Checkers5WXSommaire du match
846Checkers8Wolfpack1WSommaire du match
1164Crunch2Checkers3WXSommaire du match
1476Checkers3Crunch5LSommaire du match
1790Penguins2Checkers5WSommaire du match
1898Checkers6Penguins3WSommaire du match
21116Admirals2Checkers4WSommaire du match
26136Checkers3Wolfpack2WXXSommaire du match
27143Bears6Checkers4LSommaire du match
30162Eagles4Checkers6WSommaire du match
34183Crunch2Checkers3WXSommaire du match
36191Checkers3Little Stars5LSommaire du match
39206Checkers4Silver Knights5LSommaire du match
40216Comets1Checkers4WSommaire du match
43227Checkers2Griffins5LSommaire du match
45237Checkers7Marlies5WSommaire du match
46245Rocket7Checkers4LSommaire du match
52267Wolfpack4Checkers6WSommaire du match
54282Checkers3Icehogs5LSommaire du match
56289Little Stars1Checkers3WSommaire du match
58299Checkers4Americans2WSommaire du match
61315Checkers4Reign3WSommaire du match
63325Thunderbirds4Checkers1LSommaire du match
65337Checkers5Wranglers6LXXSommaire du match
67349Silver Knights4Checkers5WSommaire du match
71373Admirals6Checkers4LSommaire du match
73384Checkers5Crunch7LSommaire du match
75395Wolfpack4Checkers7WSommaire du match
77405Checkers6Silver Knights3WSommaire du match
82423Checkers7Punishers2WSommaire du match
83431Condors6Checkers3LSommaire du match
86447Checkers3Thunderbirds2WSommaire du match
87455Americans2Checkers6WSommaire du match
90470Checkers8Rocket4WSommaire du match
93481Penguins3Checkers7WSommaire du match
95494Checkers4Phantoms2WSommaire du match
96505Wranglers7Checkers3LSommaire du match
99518Checkers5Condors3WSommaire du match
101532Icehogs6Checkers4LSommaire du match
105551Checkers2Wolfpack7LSommaire du match
106560Senators6Checkers9WSommaire du match
110576Checkers7Admirals5WSommaire du match
112585Eagles2Checkers3WSommaire du match
115605Canucks6Checkers5LXXSommaire du match
118621Checkers4Canucks8LSommaire du match
120629Checkers1Islander2LXSommaire du match
121638Griffins3Checkers4WXSommaire du match
124652Checkers4Eagles5LXXSommaire du match
125662Canucks4Checkers2LSommaire du match
128679Checkers5Crunch8LSommaire du match
131690Moose5Checkers7WSommaire du match
132702Checkers5Eagles1WSommaire du match
135715Bears3Checkers4WSommaire du match
138734Marlies3Checkers2LSommaire du match
140743Checkers2Comets7LSommaire du match
142759Thunderbirds2Checkers6WSommaire du match
144771Checkers2Senators4LSommaire du match
146782Checkers4Islander5LSommaire du match
147790Phantoms5Checkers3LSommaire du match
151811Checkers6Penguins5WSommaire du match
153817Islander6Checkers4LSommaire du match
158839Barracuda6Checkers5LXSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
160851Checkers9Barracuda3WSommaire du match
163866Reign2Checkers4WSommaire du match
165875Checkers2Canucks5LSommaire du match
169891Eagles9Checkers4LSommaire du match
171904Checkers3Comets4LXSommaire du match
173919Islander6Checkers9WSommaire du match
175925Checkers5Moose4WXSommaire du match
178943Checkers1Little Stars4LSommaire du match
179950Punishers4Checkers1LSommaire du match
182968Penguins4Checkers6WSommaire du match
184978Checkers1Penguins5LSommaire du match
185982Checkers3Bears6LSommaire du match
187995Crunch3Checkers7WSommaire du match
1941017Punishers3Checkers6WSommaire du match
1961025Checkers8Admirals6WSommaire du match
1981034Checkers4Bears7LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance74,54637,185
Assistance PCT93.18%92.96%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2793 - 93.11% 176,023$7,040,900$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
3,239,298$ 2,642,500$ 2,307,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
13,147$ 2,435,076$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 1 17,127$ 17,127$




Checkers 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

Checkers 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

Checkers 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

Checkers 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

Checkers 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