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Connexion

Checkers
GP: 77 | W: 32 | L: 32 | OTL: 13 | P: 77
GF: 168 | GA: 201 | PP%: 26.49% | PK%: 69.51%
DG: Mikkel Aagaard | Morale : 36 | Moyenne d’équipe : 58
Prochains matchs #1217 vs Phantoms

Centre de jeu
Silver Knights
32-31-15, 79pts
2
0 Checkers
32-32-13, 77pts
Team Stats
L1SéquenceL2
20-13-7Fiche domicile20-12-7
12-18-8Fiche domicile12-20-6
4-4-2Derniers 10 matchs4-4-2
2.29Buts par match 2.18
2.90Buts contre par match 2.61
31.17%Pourcentage en avantage numérique26.49%
69.86%Pourcentage en désavantage numérique69.51%
Checkers
32-32-13, 77pts
3
5 Roadrunners
39-30-10, 88pts
Team Stats
L2SéquenceW7
20-12-7Fiche domicile20-14-5
12-20-6Fiche domicile19-16-5
4-4-2Derniers 10 matchs8-2-0
2.18Buts par match 3.94
2.61Buts contre par match 3.81
26.49%Pourcentage en avantage numérique24.88%
69.51%Pourcentage en désavantage numérique71.32%
Phantoms
37-31-9, 83pts
Jour 99
Checkers
32-32-13, 77pts
Statistiques d’équipe
W2SéquenceL2
18-17-4Fiche domicile20-12-7
19-14-5Fiche visiteur12-20-6
7-3-010 derniers matchs4-4-2
2.57Buts par match 2.18
2.73Buts contre par match 2.18
27.17%Pourcentage en avantage numérique26.49%
66.67%Pourcentage en désavantage numérique69.51%
Eagles
25-35-16, 66pts
Jour 102
Checkers
32-32-13, 77pts
Statistiques d’équipe
W3SéquenceL2
15-18-7Fiche domicile20-12-7
10-17-9Fiche visiteur12-20-6
5-4-110 derniers matchs4-4-2
2.24Buts par match 2.18
2.95Buts contre par match 2.18
33.15%Pourcentage en avantage numérique26.49%
71.91%Pourcentage en désavantage numérique69.51%
Checkers
32-32-13, 77pts
Jour 103
Thunderbirds
63-10-6, 132pts
Statistiques d’équipe
L2SéquenceW3
20-12-7Fiche domicile31-4-4
12-20-6Fiche visiteur32-6-2
4-4-210 derniers matchs7-1-2
2.18Buts par match 4.77
2.61Buts contre par match 4.77
26.49%Pourcentage en avantage numérique30.77%
69.51%Pourcentage en désavantage numérique79.38%
Meneurs d'équipe
Buts
Aleksanteri Kaskimaki
32
Passes
Aleksanteri Kaskimaki
40
Points
Aleksanteri Kaskimaki
72
Lane PedersonPlus/Moins
Lane Pederson
11
Victoires
Matthew Murray
22
Pourcentage d’arrêts
Matthew Murray
0.877

Statistiques d’équipe
Buts pour
168
2.18 GFG
Tirs pour
1171
15.21 Avg
Pourcentage en avantage numérique
26.5%
40 GF
Début de zone offensive
34.4%
Buts contre
201
2.61 GAA
Tirs contre
1412
18.34 Avg
Pourcentage en désavantage numérique
69.5%%
50 GA
Début de la zone défensive
39.4%
Informations de l'équipe

Directeur généralMikkel Aagaard
EntraîneurBob Murray
DivisionDivision 4
ConférenceConference 2
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,118
Billets de saison1,500


Informations de la formation

Équipe Pro25
Équipe Mineure26
Limite contact 51 / 100
Espoirs85


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
1Aatu Raty (R)X99.008946887674579159926171592551516766640231902,500$
2Brian PinhoX100.0078719569717780658161666563464765486403112,000,000$
3Aleksanteri Kaskimaki (R)X99.0078709569737478637563616354474760686302231,340,000$
4Brayden LowX100.0067438980767462438872676165464650396203212,000,000$
5Graeme ClarkeX99.0075708568725554625060626058474759545902521,260,000$
6Josiah SlavinX99.0078748865747581555048596153474757675902721,065,000$
7Lane PedersonX100.0071707064714845647961646160474659465802811,172,000$
8C.J. Smith (R)XXX100.0073669165665857617860576154464660375803112,000,000$
9Brett HarrisonX100.0078729266746264536851516148474655335702231,106,000$
10Tyce ThompsonX100.0068715965717682515049495548474752605602621,007,000$
11Jake Schmaltz (R)XXX100.0075728682744848516538616058474656425602531,354,000$
12Jack Beck (R)X100.0073649982663531515055436042464652485402331,273,000$
13Lucas Mercuri (R)X100.0082828681834749435537436242454552295402431,338,000$
14Ty Nelson (R)X100.0072698068718087542549465940474753696102231,309,000$
15Topi NiemelaX100.0074679267697177532549426038474752516002431,342,000$
16Vsevolod Komarov (R)X100.0075786666807684512544435738474750596002231,286,000$
17Ryan Mast (R)X100.0082828664845558452535386137464649425702331,285,000$
18Jack Peart (R)X100.0075718364736469452537395837474747615702331,275,000$
19Brendan LessX100.0078709980703230402527385937464547285302812,000,000$
Rayé
1Trevor Janicke (R)X100.0079729560723836465043446242444451205002500$
2Matt Anderson (R)X100.0072707780703432472539395937444450205402700$
3Christian Krygier (R)X100.0075767761763634472538385937464547215202631,322,000$
MOYENNE D’ÉQUIPE99.82766985707358605251495160464746544658
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
1Matthew Murray99.006440507470677175747230464663806402811,000,000$
2Damian Clara (R)100.004540508946884348888145454560346002131,291,000$
Rayé
1Jesper Vikman (R)100.00444050724589454890814545445947590242858,000$
MOYENNE D’ÉQUIPE99.6751405078548153578478404545615461
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bob Murray81745567646067CAN6911,000,000$


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
1Aleksanteri KaskimakiCheckers (FLO)C7732407224440811291795111617.88%26174322.6461117261122025454660.58%2083625010.8311251677
2Josiah SlavinCheckers (FLO)LW77221840-275040116140109266220.18%30166021.568513169811261224242.77%5052324000.4847224363
3Lane PedersonCheckers (FLO)C711722391158101008176355922.37%16120316.951345530000222259.20%2011215000.6501101223
4Brian PinhoCheckers (FLO)C591325381115157610098325313.27%10100917.112810457000005159.02%6542817000.7503111324
5Graeme ClarkeCheckers (FLO)RW77122638-21392510812914039898.57%27156920.384812271100113723048.51%1343517000.4849032324
6Matias MaccelliPanthersLW/RW31101727320313654163918.52%559019.041346270000203047.84%2551711000.9100000321
7Vsevolod KomarovCheckers (FLO)D7771926-19923012911665252610.77%54192024.94551011129000182100%01643000.2700231100
8Ty NelsonCheckers (FLO)D7751924-1053251121287935356.33%83197325.63549161310222126110%03355000.2400104001
9Topi NiemelaCheckers (FLO)D7751823-12915891395920228.47%63184423.952245760000122010%02045000.2500012201
10Aatu RatyCheckers (FLO)C4361319-3181058406320449.52%573617.1425711410221242160.95%169237000.5200002101
11Tyce ThompsonCheckers (FLO)RW7761117-14722014412843112513.95%20134817.5125712960334950046.62%4291420000.2527211020
12Jack PeartCheckers (FLO)D7721517-749151271244116184.88%62182423.69134389000183000%01148000.1900003002
13Jake SchmaltzCheckers (FLO)C/LW/RW72791691210423432182021.88%75577.751234200000150157.69%208143000.5702002012
14Brett HarrisonCheckers (FLO)C666713-142010947238113515.79%18109816.6400004000001050.00%601817000.2400020101
15C.J. SmithCheckers (FLO)C/LW/RW599211-1140666239122023.08%387514.830004121011322050.00%16187000.2500000040
16Brayden LowCheckers (FLO)LW59527-40054523991712.82%968911.6800000101451250.00%121610000.2001000130
17Christian KrygierCheckers (FLO)D36022-329512203010%544912.49000114000023000%016000.0900100000
18Lucas MercuriCheckers (FLO)C59022-40016144110%11933.28022225000000046.15%3903000.2100000000
19Daylan KueflerPanthersLW18011-3207140030%21649.140000100001000%220000.1200000000
20Jack BeckCheckers (FLO)LW681011005630233.33%01131.680000000000000%121000.1800000001
21Brett DavisPanthersLW9000000311000%0556.210000000002000%00000000000000
22Brandon GignacPanthersC16000-100310000%0140.9100000000000050.00%20000000000000
23Luke HenmanPanthersC18000-3001491120%01096.1000000000000046.15%260000000000000
24Samuel LabergePanthersLW18000-220330000%0482.67000000000000100.00%10000000000000
25Ryan MastCheckers (FLO)D61000-54029365100%974812.2700002000021000%04500000000000
26Brendan LessCheckers (FLO)D500001008100100%23767.540000000001000%00300000000000
27Dominik BadinkaPanthersD18000000130000%11025.680000000001000%00100000000000
Statistiques d’équipe totales ou en moyenne1447165268433-10460427015281627117138068914.09%4582302215.9140661061531107591428925291752.46%2922343383010.381131121824263131
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
1Matthew MurrayCheckers (FLO)52222180.8772.18308127112907486110.54522520412
2Damian ClaraCheckers (FLO)206740.8203.2310790058322149000.66761823000
3Jesper VikmanCheckers (FLO)103410.8692.63479012116088100.3333740010
4Dylan GarandPanthers21000.8645.463300322110000014000
Statistiques d’équipe totales ou en moyenne843232130.8632.49467328194141173421317777422


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 Pays 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 Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 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
Aatu RatyCheckers (FLO)C232002-11-14FINYes190 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm902,500$112,812$0$0$No---------------------------Lien
Aleksanteri KaskimakiCheckers (FLO)C222004-02-06FINYes193 Lbs6 ft0NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,340,000$167,500$0$0$No1,340,000$1,340,000$-------1,340,000$1,340,000$-------NoNo-------Lien
Brayden LowCheckers (FLO)LW321994-05-08CANNo209 Lbs6 ft2NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm2,000,000$250,000$0$0$No---------------------------Lien
Brendan LessCheckers (FLO)D281998-04-24USANo190 Lbs6 ft0NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm2,000,000$250,000$0$0$No---------------------------Lien
Brett HarrisonCheckers (FLO)C222003-06-07CANNo190 Lbs6 ft2NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,106,000$138,250$0$0$No1,106,000$1,106,000$-------1,106,000$1,106,000$-------NoNo-------Lien
Brian PinhoCheckers (FLO)C311995-05-11USANo190 Lbs6 ft1NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm2,000,000$250,000$0$0$No---------------------------Lien / Lien NHL
C.J. SmithCheckers (FLO)C/LW/RW311994-12-01USAYes183 Lbs5 ft11NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm2,000,000$250,000$0$0$No---------------------------Lien
Christian KrygierCheckers (FLO)D262000-05-05USAYes201 Lbs6 ft3NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,322,000$165,250$0$0$No1,322,000$1,322,000$-------1,322,000$1,322,000$-------NoNo-------Lien
Damian ClaraCheckers (FLO)G212005-01-13ITAYes214 Lbs6 ft5NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,291,000$161,375$0$0$No1,291,000$1,291,000$-------1,291,000$1,291,000$-------NoNo-------Lien
Graeme ClarkeCheckers (FLO)RW252001-04-24USANo190 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm1,260,000$157,500$0$0$No1,260,000$--------1,260,000$--------No--------Lien
Jack BeckCheckers (FLO)LW232003-04-12ONYes174 Lbs6 ft0NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,273,000$159,125$0$0$No1,273,000$1,273,000$-------1,273,000$1,273,000$-------NoNo-------Lien
Jack PeartCheckers (FLO)D232003-05-15USAYes195 Lbs6 ft0NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,275,000$159,375$0$0$No1,275,000$1,275,000$-------1,275,000$1,275,000$-------NoNo-------Lien
Jake SchmaltzCheckers (FLO)C/LW/RW252001-04-24USAYes190 Lbs6 ft2NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,354,000$169,250$0$0$No1,354,000$1,354,000$-------1,354,000$1,354,000$-------NoNo-------Lien
Jesper VikmanCheckers (FLO)G242002-03-11SWEYes179 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm858,000$107,250$0$0$No858,000$--------858,000$--------No--------Lien
Josiah SlavinCheckers (FLO)LW271998-12-31USANo197 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm1,065,000$133,125$0$0$No1,065,000$--------1,065,000$--------No--------Lien
Lane PedersonCheckers (FLO)C281997-08-04CANNo190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,172,000$146,500$0$0$No---------------------------Lien / Lien NHL
Lucas MercuriCheckers (FLO)C242002-03-07CANYes220 Lbs6 ft3NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,338,000$167,250$0$0$No1,338,000$1,338,000$-------1,338,000$1,338,000$-------NoNo-------Lien
Matt AndersonCheckers (FLO)D271999-04-11USAYes194 Lbs6 ft0NoNoProspectNoNo02025-10-16FalseFalsePro & Farm0$0$No---------------------------Lien
Matthew MurrayCheckers (FLO)G281998-02-02ABNo194 Lbs6 ft1NoNoAssign ManuallyNoNo12026-02-12FalseFalsePro & Farm1,000,000$125,000$0$0$No---------------------------Lien
Ryan MastCheckers (FLO)D232003-01-14USAYes217 Lbs6 ft5NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,285,000$160,625$0$0$No1,285,000$1,285,000$-------1,285,000$1,285,000$-------NoNo-------Lien
Topi NiemelaCheckers (FLO)D242002-03-25FINNo181 Lbs6 ft0NoNoN/ANoNo32025-10-22FalseFalsePro & Farm1,342,000$167,750$0$0$No1,342,000$1,342,000$-------1,342,000$1,342,000$-------NoNo-------Lien
Trevor JanickeCheckers (FLO)RW252000-12-25USAYes200 Lbs5 ft11NoNoProspectNoNo02025-10-16FalseFalsePro & Farm0$0$No---------------------------Lien
Ty NelsonCheckers (FLO)D222004-03-30CANYes198 Lbs5 ft10NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,309,000$163,625$0$0$No1,309,000$1,309,000$-------1,309,000$1,309,000$-------NoNo-------Lien
Tyce ThompsonCheckers (FLO)RW261999-07-12CANNo193 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm1,007,000$125,875$0$0$No1,007,000$--------1,007,000$--------No--------Lien
Vsevolod KomarovCheckers (FLO)D222004-01-11RUSYes208 Lbs6 ft4NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,286,000$160,750$0$0$No1,286,000$1,286,000$-------1,286,000$1,286,000$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2525.28195 Lbs6 ft12.041,231,420$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Aleksanteri KaskimakiBrian PinhoAatu Raty40122
2Graeme ClarkeJosiah SlavinBrayden Low30122
3Josiah SlavinTyce ThompsonAleksanteri Kaskimaki20122
4Brayden LowAleksanteri KaskimakiGraeme Clarke10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ty NelsonVsevolod Komarov40122
2Topi NiemelaJack Peart30122
3Jack PeartTopi Niemela20122
4Ty NelsonVsevolod Komarov10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Aleksanteri KaskimakiAatu RatyGraeme Clarke60122
2Josiah SlavinBrian PinhoTyce Thompson40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ty NelsonVsevolod Komarov60122
2Jack PeartTopi Niemela40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Tyce ThompsonJosiah Slavin60122
2Aleksanteri KaskimakiGraeme Clarke40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ty NelsonTopi Niemela60122
2Vsevolod KomarovJack Peart40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Graeme Clarke60122Topi NiemelaJack Peart60122
2Aleksanteri Kaskimaki40122Ty NelsonVsevolod Komarov40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Aleksanteri KaskimakiJosiah Slavin60122
2Graeme ClarkeTyce Thompson40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Vsevolod KomarovTy Nelson60122
2Jack PeartTopi Niemela40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Josiah SlavinGraeme ClarkeAleksanteri KaskimakiTy NelsonVsevolod Komarov
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Josiah SlavinGraeme ClarkeAleksanteri KaskimakiTy NelsonVsevolod Komarov
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Aleksanteri Kaskimaki, Graeme Clarke, Josiah SlavinAleksanteri Kaskimaki, Graeme ClarkeGraeme Clarke
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jack Peart, Ty Nelson, Vsevolod KomarovVsevolod KomarovVsevolod Komarov, Jack Peart
Tirs de pénalité
Josiah Slavin, Graeme Clarke, Tyce Thompson, Brian Pinho, Aleksanteri Kaskimaki
Gardien
#1 : Matthew Murray, #2 : Damian Clara


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
1Admirals5200010210912000000235-23200010074370.7001019290133596618733293834404977225910513646.15%70100.00%052198952.68%597113452.65%41575554.97%128343614158781979978
2Americans42001001141133200000110821000100043170.875142438003359661885329383440499435416811218.18%8187.50%152198952.68%597113452.65%41575554.97%128343614158781979978
3Barracuda2110000045-11010000013-21100000032120.50048120033596618393293834404953142639500.00%8362.50%052198952.68%597113452.65%41575554.97%128343614158781979978
4Bears20200000411-71010000005-51010000046-200.000481210335966182832938344049591810413266.67%5180.00%052198952.68%597113452.65%41575554.97%128343614158781979978
5Bruins21100000440110000003121010000013-220.50046100033596618413293834404940181248000%6350.00%052198952.68%597113452.65%41575554.97%128343614158781979978
6Canucks11000000633110000006330000000000021.00069150033596618293293834404924910174125.00%000%052198952.68%597113452.65%41575554.97%128343614158781979978
7Comets211000005321010000002-21100000051420.500571200335966181632938344049271119393266.67%2150.00%152198952.68%597113452.65%41575554.97%128343614158781979978
8Condors2020000025-31010000024-21010000001-100.0002350033596618233293834404944101347200.00%4175.00%052198952.68%597113452.65%41575554.97%128343614158781979978
9Crunch21100000321110000003031010000002-220.5003360133596618293293834404924122141300.00%3166.67%052198952.68%597113452.65%41575554.97%128343614158781979978
10Eagles4210100013112210010008442110000057-260.750131932003359661858329383440496212217112433.33%8537.50%052198952.68%597113452.65%41575554.97%128343614158781979978
11Griffins1010000025-3000000000001010000025-300.0002350033596618163293834404923124255120.00%2150.00%052198952.68%597113452.65%41575554.97%128343614158781979978
12Gulls11000000523110000005230000000000021.0005813003359661815329383440492131323200.00%4175.00%152198952.68%597113452.65%41575554.97%128343614158781979978
13Heat400011201311230001110121111000001010170.875131932013359661851329383440496015487710330.00%9366.67%152198952.68%597113452.65%41575554.97%128343614158781979978
14IceHogs2010100045-11010000013-21000100032120.5004610003359661837329383440492571033300.00%5420.00%052198952.68%597113452.65%41575554.97%128343614158781979978
15Islanders2020000027-51010000013-21010000014-300.0002240033596618413293834404950171532600.00%5340.00%052198952.68%597113452.65%41575554.97%128343614158781979978
16Marlies21100000330110000002021010000013-220.5003580133596618213293834404927226434250.00%8187.50%052198952.68%597113452.65%41575554.97%128343614158781979978
17Monsters21100000321110000003121010000001-120.5003580033596618183293834404920843622100.00%20100.00%052198952.68%597113452.65%41575554.97%128343614158781979978
18Moose51300001410-6210000013303030000017-630.300448013359661859329383440496920311101119.09%13469.23%052198952.68%597113452.65%41575554.97%128343614158781979978
19Penguins512010011115-42010100056-13110000169-350.5001118290133596618773293834404978296212710330.00%11645.45%052198952.68%597113452.65%41575554.97%128343614158781979978
20Phantoms2110000056-11010000024-21100000032120.50059140033596618303293834404942249373133.33%20100.00%052198952.68%597113452.65%41575554.97%128343614158781979978
21Reign3120000010100110000008442020000026-420.33310172700335966185032938344049923921469555.56%8362.50%052198952.68%597113452.65%41575554.97%128343614158781979978
22Roadrunners2010100078-1100010004311010000035-220.500712190033596618443293834404972710345120.00%5260.00%052198952.68%597113452.65%41575554.97%128343614158781979978
23Rocket3000020147-31000010012-12000010135-230.500471100335966184632938344049351214562150.00%2150.00%052198952.68%597113452.65%41575554.97%128343614158781979978
24Senators2010001045-1100000103211010000013-220.5004590033596618263293834404921161835200.00%4250.00%152198952.68%597113452.65%41575554.97%128343614158781979978
25Silver Knights2010010003-31010000002-21000010001-110.2500000033596618223293834404931111939000%2150.00%052198952.68%597113452.65%41575554.97%128343614158781979978
26Stars51300100918-92010010014-331200000814-630.3009142300335966187432938344049822022928225.00%11190.91%052198952.68%597113452.65%41575554.97%128343614158781979978
27Thunderbirds1010000048-41010000048-40000000000000.00047110033596618183293834404937611206116.67%3166.67%052198952.68%597113452.65%41575554.97%128343614158781979978
28Wild3120000046-2211000004401010000002-220.3334590033596618623293834404999332961400.00%120100.00%052198952.68%597113452.65%41575554.97%128343614158781979978
29Wolf Pack21000100541110000002021000010034-130.750581301335966181732938344049168229200.00%20100.00%052198952.68%597113452.65%41575554.97%128343614158781979978
30Wolves21001000422110000001011000100032141.00048120133596618263293834404988657100.00%30100.00%052198952.68%597113452.65%41575554.97%128343614158781979978
Total77223207736168201-333914120432498971388200341270104-34770.5001682684361833596618117132938344049141245860615281514026.49%1645069.51%552198952.68%597113452.65%41575554.97%128343614158781979978
_Since Last GM Reset77223207736168201-333914120432498971388200341270104-34770.5001682684361833596618117132938344049141245860615281514026.49%1645069.51%552198952.68%597113452.65%41575554.97%128343614158781979978
_Vs Conference47122005325111143-322366042146368-524614011114875-27460.4891111802911533596618725329383440499242783909281163429.31%1053269.52%252198952.68%597113452.65%41575554.97%128343614158781979978
_Vs Division1999043253950-11942032141421-71057011112529-4381.0003965104133359661825332938344049300123127398301033.33%321165.63%152198952.68%597113452.65%41575554.97%128343614158781979978

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7777L216826843611711412458606152818
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7722327736168201
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
39141243249897
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
38820341270104
Derniers 10 matchs
WLOTWOTL SOWSOL
440200
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1514026.49%1645069.51%5
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
3293834404933596618
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
52198952.68%597113452.65%41575554.97%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
128343614158781979978


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
18Checkers1Moose3LSommaire du match
217Heat5Checkers4LXSommaire du match
435Checkers3Penguins4LXXSommaire du match
547Americans4Checkers6WSommaire du match
772Eagles2Checkers5WSommaire du match
994Checkers2Admirals3LXSommaire du match
10106Checkers1Stars3LSommaire du match
11120Stars2Checkers0LSommaire du match
12131Penguins3Checkers4WXSommaire du match
13156Eagles2Checkers3WXSommaire du match
15166Checkers3Admirals1WSommaire du match
16191Heat3Checkers4WXXSommaire du match
17196Checkers1Penguins5LSommaire du match
18219Islanders3Checkers1LSommaire du match
19234Checkers0Eagles4LSommaire du match
20246Checkers2Rocket3LXSommaire du match
22257Wild3Checkers2LSommaire du match
24284Roadrunners3Checkers4WXSommaire du match
25294Checkers2Admirals0WSommaire du match
27311Admirals3Checkers2LXXSommaire du match
28326Checkers4Americans3WXSommaire du match
29345Condors4Checkers2LSommaire du match
30356Checkers1Senators3LSommaire du match
31372IceHogs3Checkers1LSommaire du match
32381Checkers5Eagles3WSommaire du match
33396Checkers2Reign3LSommaire du match
34416Crunch0Checkers3WSommaire du match
35427Checkers3IceHogs2WXSommaire du match
36444Checkers1Marlies3LSommaire du match
37459Phantoms4Checkers2LSommaire du match
39476Bears5Checkers0LSommaire du match
40494Monsters1Checkers3WSommaire du match
41511Checkers0Moose2LSommaire du match
42525Thunderbirds8Checkers4LSommaire du match
43538Checkers4Bears6LSommaire du match
44552Checkers1Bruins3LSommaire du match
45570Checkers0Moose2LSommaire du match
46580Admirals2Checkers1LXXSommaire du match
47599Bruins1Checkers3WSommaire du match
49622Checkers5Stars4WSommaire du match
50636Canucks3Checkers6WSommaire du match
51656Wolf Pack0Checkers2WSommaire du match
53673Checkers0Condors1LSommaire du match
54690Rocket2Checkers1LXSommaire du match
55707Checkers3Barracuda2WSommaire du match
56719Checkers0Monsters1LSommaire du match
57728Wild1Checkers2WSommaire du match
59750Checkers0Silver Knights1LXSommaire du match
60763Moose3Checkers2LXXSommaire du match
61781Checkers3Wolves2WXSommaire du match
62790Heat3Checkers4WXSommaire du match
64809Comets2Checkers0LSommaire du match
65828Checkers5Comets1WSommaire du match
66839Checkers0Wild2LSommaire du match
68852Marlies0Checkers2WSommaire du match
69868Checkers2Penguins0WSommaire du match
70883Reign4Checkers8WSommaire du match
72903Checkers2Griffins5LSommaire du match
73912Penguins3Checkers1LSommaire du match
74935Americans3Checkers2LXXSommaire du match
76951Checkers1Islanders4LSommaire du match
77965Gulls2Checkers5WSommaire du match
79979Checkers1Rocket2LXXSommaire du match
80995Checkers0Crunch2LSommaire du match
811004Wolves0Checkers1WSommaire du match
831028Americans1Checkers2WSommaire du match
841040Checkers2Stars7LSommaire du match
851057Stars2Checkers1LXSommaire du match
861067Checkers0Reign3LSommaire du match
881087Senators2Checkers3WXXSommaire du match
891100Checkers3Phantoms2WSommaire du match
901119Barracuda3Checkers1LSommaire du match
921142Checkers1Heat0WXXSommaire du match
931151Moose0Checkers1WSommaire du match
951169Checkers3Wolf Pack4LXSommaire du match
961183Silver Knights2Checkers0LSommaire du match
981203Checkers3Roadrunners5LSommaire du match
991217Phantoms-Checkers-
1021245Eagles-Checkers-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1031254Checkers-Thunderbirds-
1041274Silver Knights-Checkers-
1051279Checkers-Gulls-
1071298Checkers-Canucks-
1081304Griffins-Checkers-
1091314Checkers-Americans-
1101326Checkers-Heat-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance53,44429,156
Assistance PCT68.52%74.76%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
4 2118 - 70.60% 88,173$3,438,744$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
3,483,507$ 3,078,550$ 3,078,550$ 1,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
27,487$ 2,577,437$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
352,692$ 14 36,416$ 509,824$




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