Connexion

Checkers
GP: 49 | W: 28 | L: 14 | OTL: 7 | P: 63
GF: 194 | GA: 156 | PP%: 26.62% | PK%: 81.20%
DG: Dan Rhéaume | Morale : 54 | Moyenne d’équipe : 63
Prochains matchs #806 vs Admirals
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Centre de jeu
Checkers
28-14-7, 63pts
3
FINAL
2 SenatorsF
24-21-4, 52pts
Team Stats
W2SéquenceL2
17-6-2Fiche domicile12-10-3
11-8-5Fiche domicile12-11-1
4-5-1Derniers 10 matchs6-2-2
3.96Buts par match 2.94
3.18Buts contre par match 2.90
26.62%Pourcentage en avantage numérique20.66%
81.20%Pourcentage en désavantage numérique81.13%
PenguinsF
28-19-3, 59pts
4
FINAL
5 Checkers
28-14-7, 63pts
Team Stats
L2SéquenceW2
14-7-3Fiche domicile17-6-2
14-12-0Fiche domicile11-8-5
3-6-1Derniers 10 matchs4-5-1
3.68Buts par match 3.96
3.26Buts contre par match 3.18
28.48%Pourcentage en avantage numérique26.62%
75.17%Pourcentage en désavantage numérique81.20%
Admirals
20-27-3, 43pts
2023-12-12
Checkers
28-14-7, 63pts
Statistiques d’équipe
W1SéquenceW2
13-11-0Fiche domicile17-6-2
7-16-3Fiche visiteur11-8-5
5-5-010 derniers matchs4-5-1
3.08Buts par match 3.96
3.72Buts contre par match 3.96
17.20%Pourcentage en avantage numérique26.62%
77.46%Pourcentage en désavantage numérique81.20%
Checkers
28-14-7, 63pts
2023-12-14
Wolves
20-25-5, 45pts
Statistiques d’équipe
W2SéquenceL1
17-6-2Fiche domicile11-13-1
11-8-5Fiche visiteur9-12-4
4-5-110 derniers matchs4-4-2
3.96Buts par match 2.46
3.18Buts contre par match 2.46
26.62%Pourcentage en avantage numérique20.81%
81.20%Pourcentage en désavantage numérique80.61%
Checkers
28-14-7, 63pts
2023-12-16
StarsF
31-12-5, 67pts
Statistiques d’équipe
W2SéquenceSOL1
17-6-2Fiche domicile15-6-4
11-8-5Fiche visiteur16-6-1
4-5-110 derniers matchs5-4-1
3.96Buts par match 3.75
3.18Buts contre par match 3.75
26.62%Pourcentage en avantage numérique26.45%
81.20%Pourcentage en désavantage numérique76.86%
Meneurs d'équipe
Buts
Joey Anderson
27
Passes
Mason Appleton
32
Points
Mason Appleton
54
Plus/Moins
John Gilmour
20
Victoires
Joseph Woll
16
Pourcentage d’arrêts
Joseph Woll
0.902

Statistiques d’équipe
Buts pour
194
3.96 GFG
Tirs pour
1630
33.27 Avg
Pourcentage en avantage numérique
26.6%
41 GF
Début de zone offensive
40.4%
Buts contre
156
3.18 GAA
Tirs contre
1424
29.06 Avg
Pourcentage en désavantage numérique
81.2%%
22 GA
Début de la zone défensive
39.2%
Informations de l'équipe

Directeur généralDan Rhéaume
EntraîneurSheldon Keefe
DivisionDivision Sud-Est
ConférenceConference 1
CapitaineKevin Gravel
Assistant #1Adam Polasek
Assistant #2Jerome Flaake


Informations de l’aréna

Capacité3,000
Assistance2,872
Billets de saison300


Informations de la formation

Équipe Pro28
Équipe Mineure20
Limite contact 48 / 55
Espoirs52


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
1Hudson FaschingX100.0071508373757576716270726564666060566602821,700,000$
2Joey AndersonX100.005547917471747475627172656770516667660251750,000$
3Marko DanoX100.0061449472707674706968696966635559596502921,250,000$
4Mason AppletonX100.0065458572707886697169717271665657676502711,000,000$
5Jack Studnicka (R)X99.006945887269708070726869716355456066640243900,000$
6Josiah SlavinX100.0064459173687971706368657363544968646402421,100,000$
7Gemel SmithX100.0065518571717468716870707168554856676402931,300,000$
8Kenny AgostinoX100.005941967171737670626869716754485066630311800,000$
9Dan O'ReganX100.005944937068677668756762735862545366630291900,000$
10Maxim ShalunovX100.006144937173717171616970686845455366630302900,000$
11Taylor LeierX100.005943957269657967686464736064525466630291900,000$
12Jerome Flaake (A)X100.005642977173696870606668716645454266620331700,000$
13Benjamin GleasonX100.006544867471727470456868735655506656650251750,000$
14Kevin Gravel (C)X100.005944917075697269456662736061485069640311900,000$
15Carl DahlstromX100.0061449471777173714569667064524659666402831,250,000$
16Adam Polasek (A)X100.005843957173717171456867706450475059640321900,000$
17John GilmourX100.0063449470717171704569677165494553666403031,250,000$
18Jacob MoverareX100.006644857273717469456769715455506666640251750,000$
Rayé
1Anton LanderX100.006545926970687068726665706360494619630321800,000$
2Ludwig BlomstrandX100.005741957075687169626564696245455320610301650,000$
3David GilbertX100.005623937171676668686365706345454620610321650,000$
4Henrik BjorklundX100.006547906973676768626465696345454620610331650,000$
5Luca CuntiX100.005844957072686868636463716145454219610341650,000$
6Viktor SvedbergX100.005642986777706869456564706248454619620321700,000$
7Steve OleksyX100.005947966971656569456765706353472419620371700,000$
8Ryan ButtonX100.006145926971717068456564706245454620620321700,000$
MOYENNE D’ÉQUIPE99.96614492717271727059676770635448535163
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
1Luka Gracnar100.007680807377788381817879505456436403021,500,000$
2Joseph Woll100.00808376797878787878757961556668640251750,000$
Rayé
MOYENNE D’ÉQUIPE100.0078827876787881808077795655615664
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Sheldon Keefe85807870778289CAN445100,000$


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
1Mason AppletonCheckers (Flo)C492232541719562931452911915.17%989518.274711261220002203051.78%112200011.2113001274
2Joey AndersonCheckers (Flo)RW492726531715523421454312218.62%587217.81681434121000006146.27%6700021.2105001340
3Gemel SmithCheckers (Flo)LW4916274319411566351412610811.35%783717.09381124120000004041.82%5500001.0302102205
4John GilmourCheckers (Flo)D4913263920160444094243313.83%61107321.91671336115000190110%000010.7300000330
5Benjamin GleasonCheckers (Flo)D491029394180613379235612.66%74107021.85761338121000189110%000000.7300000222
6Jacob MoverareCheckers (Flo)D498263417240784674233810.81%52107221.88471136119000087030%000000.6300000113
7Hudson FaschingCheckers (Flo)RW49132033-948106941130318310.00%484317.22471118119000001259.70%6700000.7814020230
8Jack StudnickaCheckers (Flo)C4982432-8806310312643896.35%693219.0221214151200001952050.61%122900000.6900000203
9Carl DahlstromCheckers (Flo)D4952732418041426018498.33%54102720.9715629114000041100%000000.6200000002
10Kenny AgostinoCheckers (Flo)LW49161430-91001147123329413.01%883917.1336922120000013045.21%7300000.7100000111
11Marko DanoCheckers (Flo)C461510258120367486237117.44%771315.5001116000022153.18%85000000.7011000311
12Josiah SlavinCheckers (Flo)LW4912132571810525012625989.52%1083917.14011160003973156.72%6700100.6000011310
13Maxim ShalunovCheckers (Flo)RW49617234120323210232775.88%573915.0810118000000041.30%4600000.6201000021
14Adam PolasekCheckers (Flo)D44418227180252527152214.81%4271516.2701122000011000%000000.6100000000
15Kevin GravelCheckers (Flo)D4961420029537374042815.00%6887517.8700014000189110%000100.4600100120
16Jerome FlaakeCheckers (Flo)RW4931215124012113914387.69%33116.3501113000000076.47%1700100.9600000100
17Dan O'ReganCheckers (Flo)C494711114023543593811.43%34058.280000000031000157.77%56600000.5400000001
18Taylor LeierCheckers (Flo)LW49639960142251203211.76%53948.06000000008950046.15%2600000.4600000010
19Steve OleksyCheckers (Flo)D5022-400360010%18216.540000000001000%000000.4800000000
20Luca CuntiCheckers (Flo)C3000-420137100%05016.9300000000000044.07%590000000000000
Statistiques d’équipe totales ou en moyenne882194347541122322507538361630435119611.90%4241459416.554177118285123000020824281252.24%424400340.74316235262823
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
1Joseph WollCheckers (Flo)2716530.9022.91138020676860000.40052029110
2Luka GracnarCheckers (Flo)3112940.8873.15158201837370310.300102920131
Statistiques d’équipe totales ou en moyenne58281470.8953.042963211501423031154949241


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 Type Salaire actuel Plafond 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 PolasekCheckers (Flo)D321991-07-12No207 Lbs6 ft2NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Anton LanderCheckers (Flo)C321991-04-24No191 Lbs5 ft11NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Benjamin GleasonCheckers (Flo)D251998-03-25No185 Lbs6 ft1NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Carl DahlstromCheckers (Flo)D281995-01-28No231 Lbs6 ft4NoNoN/ANoNo3Pro & Farm1,250,000$0$0$No1,250,000$1,250,000$-------NoNo-------Lien
Dan O'ReganCheckers (Flo)C291994-01-30No180 Lbs5 ft10NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
David GilbertCheckers (Flo)LW321991-02-09No185 Lbs6 ft2NoNoN/ANoNo1Pro & Farm650,000$0$0$No------------------Lien
Gemel SmithCheckers (Flo)LW291994-04-16No203 Lbs5 ft10NoNoN/ANoNo3Pro & Farm1,300,000$0$0$No1,300,000$1,300,000$-------NoNo-------Lien
Henrik BjorklundCheckers (Flo)RW331990-09-22No209 Lbs6 ft2NoNoN/ANoNo1Pro & Farm650,000$0$0$No------------------Lien
Hudson FaschingCheckers (Flo)RW281995-07-28No204 Lbs6 ft3NoNoN/ANoNo2Pro & Farm1,700,000$0$0$No1,700,000$--------No--------Lien
Jack StudnickaCheckers (Flo)C241999-02-18Yes187 Lbs6 ft1NoNoN/ANoNo3Pro & Farm900,000$0$0$No900,000$900,000$-------NoNo-------Lien
Jacob MoverareCheckers (Flo)D251998-08-31No198 Lbs6 ft4NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Jerome FlaakeCheckers (Flo)RW331990-03-02No202 Lbs6 ft2NoNoN/ANoNo1Pro & Farm700,000$0$0$No------------------Lien
Joey AndersonCheckers (Flo)RW251998-06-19No192 Lbs5 ft11NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
John GilmourCheckers (Flo)D301993-05-17No191 Lbs6 ft0NoNoN/ANoNo3Pro & Farm1,250,000$0$0$No1,250,000$1,250,000$-------NoNo-------Lien
Joseph WollCheckers (Flo)G251998-07-12No198 Lbs6 ft2NoNoN/ANoNo1Pro & Farm750,000$0$0$No------------------Lien
Josiah SlavinCheckers (Flo)LW241998-12-31No161 Lbs6 ft0NoNoN/ANoNo2Pro & Farm1,100,000$0$0$No1,100,000$--------No--------Lien
Kenny AgostinoCheckers (Flo)LW311992-04-30No198 Lbs6 ft0NoNoN/ANoNo1Pro & Farm800,000$0$0$No------------------Lien
Kevin GravelCheckers (Flo)D311992-03-06No215 Lbs6 ft4NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Luca CuntiCheckers (Flo)C341989-07-04No209 Lbs6 ft0NoNoN/ANoNo1Pro & Farm650,000$0$0$No------------------Lien
Ludwig BlomstrandCheckers (Flo)LW301993-03-08No225 Lbs6 ft2NoNoN/ANoNo1Pro & Farm650,000$0$0$No------------------Lien
Luka GracnarCheckers (Flo)G301993-10-31No187 Lbs5 ft10NoNoN/ANoNo2Pro & Farm1,500,000$0$0$No1,500,000$--------No--------Lien
Marko DanoCheckers (Flo)C291994-11-30No201 Lbs5 ft11NoNoN/ANoNo2Pro & Farm1,250,000$0$0$No1,250,000$--------No--------Lien
Mason AppletonCheckers (Flo)C271996-01-15No193 Lbs6 ft3NoNoN/ANoNo1Pro & Farm1,000,000$0$0$No------------------Lien
Maxim ShalunovCheckers (Flo)RW301993-01-31No205 Lbs6 ft3NoNoN/ANoNo2Pro & Farm900,000$0$0$No900,000$--------No--------Lien
Ryan ButtonCheckers (Flo)D321991-03-26No194 Lbs6 ft0NoNoN/ANoNo1Pro & Farm700,000$0$0$No------------------Lien
Steve OleksyCheckers (Flo)D371986-02-04No190 Lbs6 ft0NoNoN/ANoNo1Pro & Farm700,000$0$0$No------------------Lien
Taylor LeierCheckers (Flo)LW291994-02-15No180 Lbs5 ft11NoNoN/ANoNo1Pro & Farm900,000$0$0$No------------------Lien
Viktor SvedbergCheckers (Flo)D321991-05-24No231 Lbs6 ft9NoNoN/ANoNo1Pro & Farm700,000$0$0$No------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2829.50198 Lbs6 ft11.46919,643$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Gemel SmithMason AppletonJoey Anderson30023
2Kenny AgostinoMarko DanoHudson Fasching30023
3Josiah SlavinJack StudnickaMaxim Shalunov30023
4Taylor LeierDan O'ReganJerome Flaake10032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Carl DahlstromBenjamin Gleason35041
2John GilmourJacob Moverare35041
3Kevin GravelAdam Polasek30041
4Carl DahlstromBenjamin Gleason0041
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Gemel SmithMason AppletonJoey Anderson50005
2Kenny AgostinoJack StudnickaHudson Fasching50005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Carl DahlstromBenjamin Gleason50014
2John GilmourJacob Moverare50014
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Dan O'ReganJosiah Slavin50041
2Jack StudnickaTaylor Leier50041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Benjamin GleasonJacob Moverare50041
2Kevin GravelJohn Gilmour50041
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Dan O'Regan50050Benjamin GleasonJacob Moverare50050
2Jack Studnicka50050Kevin GravelJohn Gilmour50050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Mason AppletonJoey Anderson50023
2Marko DanoHudson Fasching50023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Carl DahlstromBenjamin Gleason50032
2John GilmourJacob Moverare50032
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Gemel SmithMason AppletonJoey AndersonJacob MoverareBenjamin Gleason
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Josiah SlavinDan O'ReganJerome FlaakeBenjamin GleasonKevin Gravel
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Marko Dano, Josiah Slavin, Maxim ShalunovJosiah Slavin, Jerome FlaakeMason Appleton
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Adam Polasek, Kevin Gravel, Benjamin GleasonAdam PolasekCarl Dahlstrom, Adam Polasek
Tirs de pénalité
Joey Anderson, Mason Appleton, Gemel Smith, Marko Dano, Hudson Fasching
Gardien
#1 : Joseph Woll, #2 : Luka Gracnar, #3 : 0


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
1Barracuda21100000871000000000002110000087120.500815230084515937851252058628641515227342.86%5420.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
2Bears42100001131302200000010732010000136-350.6251325380084515931205125205862812739336118527.78%7185.71%0890171451.93%873166552.43%45486552.49%12008291119365651330
3BruinsF220000001310322000000131030000000000041.000132336008451593715125205862844246296116.67%20100.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
4Comets21100000990211000009900000000000020.500916250084515937951252058628532210335120.00%4175.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
5Crunch41300000813-52020000027-52110000066020.25081220008451593131512520586289533227415213.33%11463.64%0890171451.93%873166552.43%45486552.49%12008291119365651330
6Firebirds2020000079-22020000079-20000000000000.00071320008451593775125205862844188325240.00%4175.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
7Icehogs11000000624110000006240000000000021.00068140084515934151252058628319412300.00%20100.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
8Iowa Wild1000010034-11000010034-10000000000010.500369008451593315125205862838122114000%30100.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
9Islanders402001011317-420100001810-22010010057-220.2501325380084515931235125205862812746216111327.27%8187.50%0890171451.93%873166552.43%45486552.49%12008291119365651330
10Marlies3210000017107110000008262110000098140.667172845108451593102512520586288822213611654.55%80100.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
11Monsters1000000145-1000000000001000000145-110.500481200845159333512520586283912418200.00%2150.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
12Moose330000001459220000009361100000052361.0001428420084515938951252058628952920486350.00%10190.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
13PenguinsF3200000112111220000009721000000134-150.83312223400845159311051252058628982918356233.33%9188.89%0890171451.93%873166552.43%45486552.49%12008291119365651330
14Phantoms21100000660000000000002110000066020.50061218008451593795125205862859212532600.00%5340.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
15Reign11000000835000000000001100000083521.0008142200845159337512520586283052114125.00%10100.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
16Rocket5310000118126220000009543110000197270.7001829470184515931505125205862815033398619631.58%150100.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
17SenatorsF21100000550000000000002110000055020.5005914008451593635125205862843144298112.50%20100.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
18Thunderbirds11000000422000000000001100000042221.00047110084515934051252058628277818500.00%30100.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
19Wolf Pack440000001679330000009451100000073481.0001629450084515931155125205862812522247612216.67%9277.78%0890171451.93%873166552.43%45486552.49%12008291119365651330
20Wolves11000000633110000006330000000000021.00061016008451593295125205862831610132150.00%5180.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
21Wranglers11000000431000000000001100000043121.000481200845159332512520586281669133266.67%2150.00%0890171451.93%873166552.43%45486552.49%12008291119365651330
Total4928140020519415638251760010110882262411800104867412630.64319434754111845159316305125205862814244243247531544126.62%1172281.20%0890171451.93%873166552.43%45486552.49%12008291119365651330
_Since Last GM Reset4928140020519415638251760010110882262411800104867412630.64319434754111845159316305125205862814244243247531544126.62%1172281.20%0890171451.93%873166552.43%45486552.49%12008291119365651330
_Vs Conference4123130010415713027231660000199762318770010358544510.62215728143811845159313385125205862811793582616451303526.92%991683.84%0890171451.93%873166552.43%45486552.49%12008291119365651330

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4963W21943475411630142442432475311
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4928140205194156
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
25176010110882
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2411801048674
Derniers 10 matchs
WLOTWOTL SOWSOL
450001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1544126.62%1172281.20%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
512520586288451593
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
890171451.93%873166552.43%45486552.49%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
12008291119365651330


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
2 - 2023-08-2612Wolf Pack1Checkers3BWSommaire du match
5 - 2023-08-2934BruinsF5Checkers7BWSommaire du match
6 - 2023-08-3038Checkers6Rocket0AWSommaire du match
9 - 2023-09-0267Wolf Pack1Checkers2BWSommaire du match
10 - 2023-09-0379Checkers7Marlies4AWSommaire du match
13 - 2023-09-0699Bears4Checkers6BWSommaire du match
15 - 2023-09-08108Checkers6Barracuda3AWSommaire du match
17 - 2023-09-10130Moose2Checkers5BWSommaire du match
19 - 2023-09-12145Checkers7Wolf Pack3AWSommaire du match
21 - 2023-09-14161Checkers5Moose2AWSommaire du match
23 - 2023-09-16175Rocket1Checkers3BWSommaire du match
25 - 2023-09-18193Checkers2Islanders3ALXSommaire du match
28 - 2023-09-21209Firebirds4Checkers3BLSommaire du match
31 - 2023-09-24226Crunch5Checkers1BLSommaire du match
33 - 2023-09-26247Checkers2SenatorsF3ALSommaire du match
35 - 2023-09-28261Marlies2Checkers8BWSommaire du match
39 - 2023-10-02288Wolf Pack2Checkers4BWSommaire du match
41 - 2023-10-04303Checkers3Islanders4ALSommaire du match
43 - 2023-10-06320Iowa Wild4Checkers3BLXSommaire du match
45 - 2023-10-08335Checkers4Wranglers3AWSommaire du match
47 - 2023-10-10349Checkers2Rocket3ALXXSommaire du match
48 - 2023-10-11360BruinsF5Checkers6BWSommaire du match
51 - 2023-10-14376Checkers1Phantoms3ALSommaire du match
53 - 2023-10-16387Comets4Checkers3BLSommaire du match
55 - 2023-10-18407Checkers5Phantoms3AWSommaire du match
57 - 2023-10-20422Comets5Checkers6BWSommaire du match
59 - 2023-10-22441Checkers4Monsters5ALXXSommaire du match
61 - 2023-10-24455Wolves3Checkers6BWSommaire du match
65 - 2023-10-28479Checkers3PenguinsF4ALXXSommaire du match
67 - 2023-10-30489Moose1Checkers4BWSommaire du match
69 - 2023-11-01502Checkers5Crunch1AWSommaire du match
72 - 2023-11-04523Crunch2Checkers1BLSommaire du match
74 - 2023-11-06540Checkers2Barracuda4ALSommaire du match
76 - 2023-11-08551Bears3Checkers4BWSommaire du match
78 - 2023-11-10565Checkers2Bears3ALXXSommaire du match
80 - 2023-11-12580Checkers4Thunderbirds2AWSommaire du match
81 - 2023-11-13592Firebirds5Checkers4BLSommaire du match
83 - 2023-11-15609Checkers8Reign3AWSommaire du match
85 - 2023-11-17624Icehogs2Checkers6BWSommaire du match
88 - 2023-11-20646Checkers2Marlies4ALSommaire du match
90 - 2023-11-22655PenguinsF3Checkers4BWSommaire du match
93 - 2023-11-25680Rocket4Checkers6BWSommaire du match
94 - 2023-11-26694Checkers1Rocket4ALSommaire du match
97 - 2023-11-29712Islanders4Checkers3BLSommaire du match
100 - 2023-12-02732Checkers1Bears3ALSommaire du match
101 - 2023-12-03745Islanders6Checkers5BLXXSommaire du match
104 - 2023-12-06764Checkers1Crunch5ALSommaire du match
105 - 2023-12-07776Checkers3SenatorsF2AWSommaire du match
107 - 2023-12-09785PenguinsF4Checkers5BWSommaire du match
110 - 2023-12-12806Admirals-Checkers-
112 - 2023-12-14827Checkers-Wolves-
114 - 2023-12-16840Checkers-StarsF-
115 - 2023-12-17847Griffins-Checkers-
119 - 2023-12-21872Griffins-Checkers-
121 - 2023-12-23894Checkers-Wolf Pack-
123 - 2023-12-25904Checkers-Gulls-
124 - 2023-12-26912Marlies-Checkers-
127 - 2023-12-29932Checkers-Roadrunners-
128 - 2023-12-30941Eagles-Checkers-
131 - 2024-01-02966Condors-Checkers-
133 - 2024-01-04978Checkers-Firebirds-
134 - 2024-01-05988Checkers-Wolves-
137 - 2024-01-081005SenatorsF-Checkers-
138 - 2024-01-091015Checkers-PenguinsF-
140 - 2024-01-111033Checkers-Comets-
142 - 2024-01-131045SenatorsF-Checkers-
144 - 2024-01-151064Wolves-Checkers-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
147 - 2024-01-181081Checkers-BruinsF-
149 - 2024-01-201096Checkers-Comets-
151 - 2024-01-221103Checkers-BruinsF-
152 - 2024-01-231112Silver Knights-Checkers-
155 - 2024-01-261134Canucks-Checkers-
157 - 2024-01-281147Checkers-Americans-
160 - 2024-01-311166Checkers-Firebirds-
161 - 2024-02-011180Silver Knights-Checkers-
163 - 2024-02-031195Checkers-Moose-
165 - 2024-02-051208Phantoms-Checkers-
169 - 2024-02-091232Checkers-Americans-
171 - 2024-02-111245Americans-Checkers-
176 - 2024-02-161273Americans-Checkers-
178 - 2024-02-181287Phantoms-Checkers-
180 - 2024-02-201302Checkers-Condors-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3315
Assistance47,97323,827
Assistance PCT95.95%95.31%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
16 2872 - 95.73% 112,550$2,813,745$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,525,495$ 2,575,000$ 2,575,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,466,737$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,800,797$ 75 14,698$ 1,102,350$




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