Connexion

Checkers
GP: 48 | W: 27 | L: 14 | OTL: 7 | P: 61
GF: 189 | GA: 152 | PP%: 26.62% | PK%: 80.53%
DG: Dan Rhéaume | Morale : 53 | Moyenne d’équipe : 63
Prochains matchs #785 vs PenguinsF
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Centre de jeu
Checkers
27-14-7, 61pts
1
FINAL
5 Crunch
31-16-2, 64pts
Team Stats
W1SéquenceW1
16-6-2Fiche domicile16-7-1
11-8-5Fiche domicile15-9-1
4-5-1Derniers 10 matchs6-3-1
3.94Buts par match 3.47
3.17Buts contre par match 2.80
26.62%Pourcentage en avantage numérique23.60%
80.53%Pourcentage en désavantage numérique84.25%
Checkers
27-14-7, 61pts
3
FINAL
2 SenatorsF
24-20-4, 52pts
Team Stats
W1SéquenceL1
16-6-2Fiche domicile12-10-3
11-8-5Fiche domicile12-10-1
4-5-1Derniers 10 matchs7-1-2
3.94Buts par match 2.92
3.17Buts contre par match 2.85
26.62%Pourcentage en avantage numérique20.83%
80.53%Pourcentage en désavantage numérique81.41%
PenguinsF
28-18-3, 59pts
2023-12-09
Checkers
27-14-7, 61pts
Statistiques d’équipe
L1SéquenceW1
14-7-3Fiche domicile16-6-2
14-11-0Fiche visiteur11-8-5
4-5-110 derniers matchs4-5-1
3.67Buts par match 3.94
3.22Buts contre par match 3.94
29.25%Pourcentage en avantage numérique26.62%
75.17%Pourcentage en désavantage numérique80.53%
Admirals
20-27-3, 43pts
2023-12-12
Checkers
27-14-7, 61pts
Statistiques d’équipe
W1SéquenceW1
13-11-0Fiche domicile16-6-2
7-16-3Fiche visiteur11-8-5
5-5-010 derniers matchs4-5-1
3.08Buts par match 3.94
3.72Buts contre par match 3.94
17.20%Pourcentage en avantage numérique26.62%
77.46%Pourcentage en désavantage numérique80.53%
Checkers
27-14-7, 61pts
2023-12-14
Wolves
20-25-5, 45pts
Statistiques d’équipe
W1SéquenceL1
16-6-2Fiche domicile11-13-1
11-8-5Fiche visiteur9-12-4
4-5-110 derniers matchs4-4-2
3.94Buts par match 2.46
3.17Buts contre par match 2.46
26.62%Pourcentage en avantage numérique20.81%
80.53%Pourcentage en désavantage numérique80.61%
Meneurs d'équipe
Buts
Joey Anderson
26
Passes
Mason Appleton
31
Points
Mason Appleton
52
Plus/Moins
John Gilmour
19
Victoires
Joseph Woll
15
Pourcentage d’arrêts
Joseph Woll
0.9

Statistiques d’équipe
Buts pour
189
3.94 GFG
Tirs pour
1601
33.35 Avg
Pourcentage en avantage numérique
26.6%
41 GF
Début de zone offensive
40.5%
Buts contre
152
3.17 GAA
Tirs contre
1398
29.13 Avg
Pourcentage en désavantage numérique
80.5%%
22 GA
Début de la zone défensive
39.4%
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
Assistance2,871
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 FaschingX100.0071508373757576716270726564666060556602821,700,000$
2Joey AndersonX100.005547917471747475627172656770516666660251750,000$
3Marko DanoX100.0061449472707674706968696966635559586502921,250,000$
4Mason AppletonX100.0065458572707886697169717271665657666502711,000,000$
5Jack Studnicka (R)X100.006945887269708070726869716355456065640243900,000$
6Josiah SlavinX100.0064459173687971706368657363544968636402421,100,000$
7Gemel SmithX100.0065518571717468716870707168554856666402931,300,000$
8Kenny AgostinoX100.005941967171737670626869716754485065630311800,000$
9Dan O'ReganX100.005944937068677668756762735862545365630291900,000$
10Maxim ShalunovX100.006144937173717171616970686845455365630302900,000$
11Taylor LeierX100.005943957269657967686464736064525465630291900,000$
12Jerome Flaake (A)X100.005642977173696870606668716645454265620331700,000$
13Benjamin GleasonX100.006544867471727470456868735655506655650251750,000$
14Kevin Gravel (C)X100.005944917075697269456662736061485068640311900,000$
15Carl DahlstromX100.0061449471777173714569667064524659656402831,250,000$
16Adam Polasek (A)X100.005843957173717171456867706450475057640321900,000$
17John GilmourX100.0063449470717171704569677165494553656403031,250,000$
18Jacob MoverareX100.006644857273717469456769715455506665640251750,000$
Rayé
1Anton LanderX100.006545926970687068726665706360494620630321800,000$
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’ÉQUIPE100.00614492717271727059676770635448535063
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 Gracnar100.007680807377788381817879505456476403021,500,000$
2Joseph Woll100.00808376797878787878757961556666640251750,000$
Rayé
MOYENNE D’ÉQUIPE100.0078827876787881808077795655615764
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)C482131521619562901402711515.00%987818.314711261220002203051.76%110700011.1813001274
2Joey AndersonCheckers (Flo)RW482626521615523421424211818.31%585617.85681434121000005144.62%6500021.2105001340
3Gemel SmithCheckers (Flo)LW4816264218411563351382410511.59%782117.11381124120000004041.82%5500001.0202102205
4John GilmourCheckers (Flo)D4812263819160444093233312.90%58105321.94671336115000186110%000010.7200000330
5Benjamin GleasonCheckers (Flo)D481028386180593279225512.66%72104921.86761338121000185110%000000.7200000222
6Jacob MoverareCheckers (Flo)D488253316220774672223611.11%50105221.92471136119000084030%000000.6300000113
7Jack StudnickaCheckers (Flo)C4882432-8806310212443866.45%691219.0121214151200001912050.50%121200000.7000000203
8Hudson FaschingCheckers (Flo)RW48131932-848106741127307810.24%482717.25471118119000001259.09%6600000.7714020230
9Carl DahlstromCheckers (Flo)D4852631618040426018488.33%53100821.0115629114000039100%000000.6100000002
10Kenny AgostinoCheckers (Flo)LW48151429-81001147121329212.40%882317.1736922120000013045.83%7200000.7000000111
11Josiah SlavinCheckers (Flo)LW4812132571810514612624959.52%1082017.10011160003933155.38%6500100.6100011310
12Marko DanoCheckers (Flo)C45158239120367284226817.86%769715.5001116000022153.18%83300000.6611000311
13Maxim ShalunovCheckers (Flo)RW48617234100303210131765.94%572315.0810118000000042.22%4500000.6401000021
14Adam PolasekCheckers (Flo)D43417215160252526152215.38%4269716.2201122000011000%000000.6000000000
15Kevin GravelCheckers (Flo)D4861420-227537374042815.00%6885517.8200014000187110%000100.4700100120
16Jerome FlaakeCheckers (Flo)RW4831114114012113712368.11%33066.3801113000000075.00%1600100.9100000100
17Dan O'ReganCheckers (Flo)C48371010402354346378.82%33978.27000000003960058.08%55100000.5000000001
18Taylor LeierCheckers (Flo)LW48639860132150183112.00%53858.04000000008910046.15%2600000.4700000010
19Steve OleksyCheckers (Flo)D5022-400360010%18216.540000000001000%000000.4800000000
20Luca CuntiCheckers (Flo)C3000-420137100%05016.9300000000000044.07%590000000000000
Statistiques d’équipe totales ou en moyenne864189337526117314507408241601416116011.81%4161430216.554177118285123000020793271152.18%417200340.74316235262823
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)2615530.9003.00134120676720000.40052028110
2Luka GracnarCheckers (Flo)3012940.8913.04156201797250310.300102820131
Statistiques d’équipe totales ou en moyenne56271470.8953.022903211461397031154848241


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 : Luka Gracnar, #2 : Joseph Woll


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
1Barracuda21100000871000000000002110000087120.500815230082495837850251057728641515227342.86%5420.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
2Bears42100001131302200000010732010000136-350.6251325380082495831205025105772812739336118527.78%7185.71%0877168951.92%861164252.44%43984152.20%11748111097359638324
3BruinsF220000001310322000000131030000000000041.000132336008249583715025105772844246296116.67%20100.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
4Comets21100000990211000009900000000000020.500916250082495837950251057728532210335120.00%4175.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
5Crunch41300000813-52020000027-52110000066020.25081220008249583131502510577289533227415213.33%11463.64%0877168951.92%861164252.44%43984152.20%11748111097359638324
6Firebirds2020000079-22020000079-20000000000000.00071320008249583775025105772844188325240.00%4175.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
7Icehogs11000000624110000006240000000000021.00068140082495834150251057728319412300.00%20100.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
8Iowa Wild1000010034-11000010034-10000000000010.500369008249583315025105772838122114000%30100.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
9Islanders402001011317-420100001810-22010010057-220.2501325380082495831235025105772812746216111327.27%8187.50%0877168951.92%861164252.44%43984152.20%11748111097359638324
10Marlies3210000017107110000008262110000098140.667172845108249583102502510577288822213611654.55%80100.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
11Monsters1000000145-1000000000001000000145-110.500481200824958333502510577283912418200.00%2150.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
12Moose330000001459220000009361100000052361.0001428420082495838950251057728952920486350.00%10190.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
13PenguinsF21000001770110000004311000000134-130.750712190082495838150251057728722110226233.33%5180.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
14Phantoms21100000660000000000002110000066020.50061218008249583795025105772859212532600.00%5340.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
15Reign11000000835000000000001100000083521.0008142200824958337502510577283052114125.00%10100.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
16Rocket5310000118126220000009543110000197270.7001829470182495831505025105772815033398619631.58%150100.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
17SenatorsF21100000550000000000002110000055020.5005914008249583635025105772843144298112.50%20100.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
18Thunderbirds11000000422000000000001100000042221.00047110082495834050251057728277818500.00%30100.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
19Wolf Pack440000001679330000009451100000073481.0001629450082495831155025105772812522247612216.67%9277.78%0877168951.92%861164252.44%43984152.20%11748111097359638324
20Wolves11000000633110000006330000000000021.00061016008249583295025105772831610132150.00%5180.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
21Wranglers11000000431000000000001100000043121.000481200824958332502510577281669133266.67%2150.00%0877168951.92%861164252.44%43984152.20%11748111097359638324
Total4827140020518915237241660010110378252411800104867412610.63518933752611824958316015025105772813984163167401544126.62%1132280.53%0877168951.92%861164252.44%43984152.20%11748111097359638324
_Since Last GM Reset4827140020518915237241660010110378252411800104867412610.63518933752611824958316015025105772813984163167401544126.62%1132280.53%0877168951.92%861164252.44%43984152.20%11748111097359638324
_Vs Conference4022130010415212626221560000194722218770010358544490.61315227142311824958313095025105772811533502536321303526.92%951683.16%0877168951.92%861164252.44%43984152.20%11748111097359638324

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4861W11893375261601139841631674011
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4827140205189152
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
24166010110378
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%1132280.53%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
502510577288249583
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
877168951.92%861164252.44%43984152.20%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
11748111097359638324


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 - 2023-12-09785PenguinsF-Checkers-
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
Assistance45,99622,919
Assistance PCT95.83%95.50%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
17 2871 - 95.72% 112,475$2,699,397$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,510,797$ 2,645,000$ 2,645,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,452,589$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,912,073$ 76 15,082$ 1,146,232$




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