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Connexion

Checkers
GP: 11 | W: 8 | L: 3 | OTL: 0 | P: 16
GF: 35 | GA: 19 | PP%: 25.64% | PK%: 85.37%
DG: Alex Loignon | Morale : 70 | Moyenne d’équipe : 65
Prochains matchs #196 vs Firebird

Centre de jeu
Firebird
5-6-0, 10pts
4
6 Checkers
8-3-0, 16pts
Team Stats
L3SéquenceW2
3-3-0Fiche domicile5-1-0
2-3-0Fiche domicile3-2-0
4-6-0Derniers 10 matchs7-3-0
2.82Buts par match 3.18
2.82Buts contre par match 1.73
24.00%Pourcentage en avantage numérique25.64%
78.38%Pourcentage en désavantage numérique85.37%
Checkers
8-3-0, 16pts
4
0 Admirals
7-2-3, 17pts
Team Stats
W2SéquenceOTW1
5-1-0Fiche domicile4-1-1
3-2-0Fiche domicile3-1-2
7-3-0Derniers 10 matchs6-1-3
3.18Buts par match 3.17
1.73Buts contre par match 2.92
25.64%Pourcentage en avantage numérique21.15%
85.37%Pourcentage en désavantage numérique81.58%
Checkers
8-3-0, 16pts
Jour 28
Firebird
5-6-0, 10pts
Statistiques d’équipe
W2SéquenceL3
5-1-0Fiche domicile3-3-0
3-2-0Fiche visiteur2-3-0
7-3-010 derniers matchs4-6-0
3.18Buts par match 2.82
1.73Buts contre par match 2.82
25.64%Pourcentage en avantage numérique24.00%
85.37%Pourcentage en désavantage numérique78.38%
Checkers
8-3-0, 16pts
Jour 29
Roadrunners
3-8-1, 7pts
Statistiques d’équipe
W2SéquenceW1
5-1-0Fiche domicile1-4-1
3-2-0Fiche visiteur2-4-0
7-3-010 derniers matchs3-6-1
3.18Buts par match 2.75
1.73Buts contre par match 2.75
25.64%Pourcentage en avantage numérique11.11%
85.37%Pourcentage en désavantage numérique64.86%
Admirals
7-2-3, 17pts
Jour 32
Checkers
8-3-0, 16pts
Statistiques d’équipe
OTW1SéquenceW2
4-1-1Fiche domicile5-1-0
3-1-2Fiche visiteur3-2-0
6-1-310 derniers matchs7-3-0
3.17Buts par match 3.18
2.92Buts contre par match 3.18
21.15%Pourcentage en avantage numérique25.64%
81.58%Pourcentage en désavantage numérique85.37%
Meneurs d'équipe
Buts
Bradly Nadeau
5
Passes
Theo Lindstein
9
Points
Bradly Nadeau
12
Plus/Moins
Theo Lindstein
10
Victoires
Sergei Murashov
8
Pourcentage d’arrêts
Sergei Murashov
0.925

Statistiques d’équipe
Buts pour
35
3.18 GFG
Tirs pour
297
27.00 Avg
Pourcentage en avantage numérique
25.6%
10 GF
Début de zone offensive
40.3%
Buts contre
19
1.73 GAA
Tirs contre
254
23.09 Avg
Pourcentage en désavantage numérique
85.4%%
6 GA
Début de la zone défensive
38.7%
Informations de l'équipe

Directeur généralAlex Loignon
EntraîneurMark French
DivisionCentral
ConférenceConference Ouest
Capitaine
Assistant #1Bradly Nadeau
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance3,000
Billets de saison300


Informations de la formation

Équipe Pro29
Équipe Mineure19
Limite Contrat48 / 99
Espoirs61


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
1Adam Beckman0XX100.0066589969748583675569726366656561706702521,699,000$
2Jamieson Rees0XX100.0082725972707379677970656665676654706702541,740,000$
3Jansen Harkins0XXX100.007843857177788265816766636571705870670291994,000$
4Jacob Peterson0XX100.0045199968748186666262726369727141706602731,215,000$
5Bradly Nadeau (A)0XXX100.006660847370728268486271646660586970660212900,000$
6Aleksanteri Kaskimaki (R)0X100.005832717061747668626968656962687870660222900,000$
7Ryan Suzuki0XX100.0072659166746374657969686465676558706502521,382,000$
8Matvei Gridin (R)0XX100.006032766862778167467265637164658270650203900,000$
9Mackie Samoskevich0XX100.0074688965736671676165666461626168706402331,365,000$
10Ozzy Wiesblatt0XXX100.007263856870788565496260645865667570640241900,000$
11Danila Klimovich0XX100.0064638961776581566558596563626055706102331,139,000$
12Egor Afanasyev0XXX100.0082479263807090545445556759686855706102521,190,000$
13Shakir Mukhamadullin0X100.006840947482897071257262695867657870690241900,000$
14Joe Hicketts0X100.0062259962707287562539469925686843706903011,800,000$
15Zayne Parekh (R)0X100.006032777062798363466758745664677770670203900,000$
16Theo Lindstein (R)0X100.006232777064778360456658765564677670670213900,000$
17Santeri Hatakka0X100.0050219965757368713080596756696841706602521,253,000$
18Kirill Kirsanov (R)0X100.006738826668808458456353745066667170660242900,000$
Rayé
1Benjamin Kindel (R)0XX100.005830766760727065466666636964658270630193900,000$
2Cole Eiserman (R)0X100.005935716260667065467662606658628270620203900,000$
3Samuel Huo0X100.006740706268677361456958705357587070620251900,000$
4Alexandre Loignon0XX100.00544976658162705055505062606363777057N2262575,000$
5Calen Addison0X100.0041209965747277573055496354757757706202611,085,000$
6Michael Vukojevic0X100.0057418459806977583059506147727254706202511,029,000$
7Gustav Stjernberg (R)0X100.006750635866677356456358665055586970610242590,000$
MOYENNE D’ÉQUIPE100.00644383667173786350646167596566657064
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
1Sergei Murashov (R)0100.00707574767678767678777563677470730222900,000$
2Arsenii Sergeev (R)0100.00706968677070707070696764637070680232900,000$
Rayé
1Roddy Ross0100.006971706769696968696866606267706702611,225,000$
2Scott Ratzlaff (R)0100.00706867637068686970676660627170660213900,000$
MOYENNE D’ÉQUIPE100.0070717068717171717270696264717069
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Mark French64859157929845CAN551500,000$


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
1Bradly NadeauCheckers (FLO)C/LW/RW1157128408203481914.71%123621.522139340000312131.82%2200001.0100000111
2Jansen HarkinsCheckers (FLO)C/LW/RW115712860212725101820.00%120418.60112734000002060.26%22900001.1700000111
3Theo LindsteinCheckers (FLO)D112911100018141231016.67%1321719.73156827000037000%000001.0100000101
4Santeri HatakkaCheckers (FLO)D11268360716141614.29%1222420.43011733000014000%000000.7100000010
5Zayne ParekhCheckers (FLO)D1117801601811147197.14%823121.011561027000030100%000000.6900000000
6Jacob PetersonCheckers (FLO)C/LW11437-20001024131616.67%019117.422138290000112042.86%2100000.7300000101
7Kirill KirsanovCheckers (FLO)D111678100151061316.67%1017616.0400003000034000%000000.7900000001
8Adam BeckmanCheckers (FLO)LW/RW114268207104410219.09%220919.011121134000011073.33%1500000.5700000020
9Aleksanteri KaskimakiCheckers (FLO)C112463206181362315.38%213111.981344290001280045.39%15200000.9100000100
10Matvei GridinCheckers (FLO)LW/RW11246-200492810227.14%217916.33123112900000009.09%1100000.6700000001
11Mackie SamoskevichCheckers (FLO)C/RW11145360781051010.00%112611.5000000000020157.14%700000.7900000001
12Ryan SuzukiCheckers (FLO)C/LW11314400811146721.43%112711.5800011000000052.21%11300100.6300000100
13Jamieson ReesCheckers (FLO)C/LW11123-21003131195125.26%118616.99000000002350058.72%21800000.3200000000
14Shakir MukhamadullinCheckers (FLO)D1103321801613118220%1023221.1500043500003000%000000.2600000000
15Ozzy WiesblattCheckers (FLO)C/LW/RW1111234051172614.29%212311.250000000000000%600000.3200000000
16Joe HickettsCheckers (FLO)D1102210014198460%1323421.2900000000030000%000000.1700000000
17Danila KlimovichCheckers (FLO)LW/RW111012000090411.11%0726.5600000000000050.00%400000.2800000000
18Egor AfanasyevCheckers (FLO)C/LW/RW11000300665330%111310.35000000000400050.00%80000000000000
Statistiques d’équipe totales ou en moyenne19835681036084019124429710222711.78%80322016.261020308032100033048253.60%80600100.6400000657
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
1Sergei MurashovCheckers (FLO)118300.9251.73658231925400000110310
Statistiques d’équipe totales ou en moyenne118300.9251.7365823192540000110310


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 ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer UFA Rappel d'urgence Type Salaire actuel Plafond 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
Adam BeckmanCheckers (FLO)LW/RW252001-05-10CANNo191 Lbs6 ft2NoNoN/ANoNo22025-05-25FalseFalsePro & Farm1,699,000$0$0$No1,699,000$--------1,699,000$--------No--------
Aleksanteri KaskimakiCheckers (FLO)C222004-02-06FINYes192 Lbs6 ft0NoNoProspectNoNo22026-06-11FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Alexandre LoignonCheckers (FLO)C/RW262000-07-27CANNo226 Lbs6 ft4YesNoN/ANoNo2FalseFalsePro & Farm575,000$0$0$No575,000$--------575,000$--------Yes--------
Arsenii SergeevCheckers (FLO)G232002-12-16RUSYes194 Lbs6 ft3NoNoProspectNoNo22026-06-11FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Benjamin KindelCheckers (FLO)C/RW192007-04-19CANYes181 Lbs5 ft11NoNoProspectNoNo32026-09-20FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Bradly NadeauCheckers (FLO)C/LW/RW212005-05-05CANNo175 Lbs5 ft11NoNoTrade2025-06-14NoNo22025-05-23FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Calen AddisonCheckers (FLO)D262000-04-11CANNo194 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,085,000$0$0$No---------------------------
Cole EisermanCheckers (FLO)LW202006-08-29USAYes201 Lbs6 ft0NoNoProspectNoNo32026-09-20FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Danila KlimovichCheckers (FLO)LW/RW232003-01-09BLRNo214 Lbs6 ft2NoNoN/ANoNo32026-05-31FalseFalsePro & Farm1,139,000$0$0$No1,139,000$1,139,000$-------1,139,000$1,139,000$-------NoNo-------
Egor AfanasyevCheckers (FLO)C/LW/RW252001-01-23RUSNo216 Lbs6 ft4NoNoN/ANoNo22025-05-25FalseFalsePro & Farm1,190,000$0$0$No1,190,000$--------1,190,000$--------No--------
Gustav StjernbergCheckers (FLO)D242002-10-12SWEYes209 Lbs6 ft4NoNoTrade2026-06-26NoNo22026-06-24FalseFalsePro & Farm590,000$0$0$No590,000$--------590,000$--------No--------
Jacob PetersonCheckers (FLO)C/LW271999-07-19SWENo191 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm1,215,000$0$0$No1,215,000$1,215,000$-------1,215,000$1,215,000$-------NoNo-------
Jamieson ReesCheckers (FLO)C/LW252001-02-26CANNo176 Lbs5 ft11NoNoFree AgentNoNo42025-06-02FalseFalsePro & Farm1,740,000$0$0$No1,740,000$1,740,000$1,740,000$------1,740,000$1,740,000$1,740,000$------NoNoNo------
Jansen HarkinsCheckers (FLO)C/LW/RW291997-05-23CANNo203 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm994,000$0$0$No---------------------------
Joe HickettsCheckers (FLO)D301996-05-04CANNo191 Lbs5 ft8NoNoN/ANoNo1FalseFalsePro & Farm1,800,000$0$0$No---------------------------
Kirill KirsanovCheckers (FLO)D242002-09-19RUSYes220 Lbs6 ft2NoNoProspectNoNo22026-06-11FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Mackie SamoskevichCheckers (FLO)C/RW232002-11-15USANo195 Lbs5 ft11NoNoFree AgentNoNo32026-05-31FalseFalsePro & Farm1,365,000$0$0$No1,365,000$1,365,000$-------1,365,000$1,365,000$-------NoNo-------
Matvei GridinCheckers (FLO)LW/RW202006-03-01RUSYes190 Lbs6 ft1NoNoProspectNoNo32026-06-11FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Michael VukojevicCheckers (FLO)D252001-06-08CANNo226 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm1,029,000$0$0$No---------------------------
Ozzy WiesblattCheckers (FLO)C/LW/RW242002-03-09CANNo186 Lbs5 ft10NoNoFree AgentNoNo12025-06-21FalseFalsePro & Farm900,000$0$0$No---------------------------
Roddy RossCheckers (FLO)G262000-07-04CANNo183 Lbs6 ft3NoNoProspectNoNo12026-06-11FalseFalsePro & Farm1,225,000$0$0$No---------------------------
Ryan SuzukiCheckers (FLO)C/LW252001-05-28CANNo197 Lbs6 ft1NoNoN/ANoNo22025-05-25FalseFalsePro & Farm1,382,000$0$0$No1,382,000$--------1,382,000$--------No--------
Samuel HuoCheckers (FLO)C252001-07-13CANNo209 Lbs6 ft5NoNoFree AgentNoNo12026-07-04FalseFalsePro & Farm900,000$0$0$No---------------------------
Santeri HatakkaCheckers (FLO)D252001-01-15FINNo198 Lbs6 ft1NoNoTrade2025-09-10NoNo22025-05-25FalseFalsePro & Farm1,253,000$0$0$No1,253,000$--------1,253,000$--------No--------
Scott RatzlaffCheckers (FLO)G212005-03-09CANYes176 Lbs6 ft1NoNoProspectNoNo32026-06-11FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Sergei MurashovCheckers (FLO)G222004-04-01RUSYes189 Lbs6 ft2NoNoFree AgentNoNo22025-05-29FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Shakir MukhamadullinCheckers (FLO)D242002-01-10RUSNo183 Lbs6 ft4NoNoFree AgentNoNo12025-05-30FalseFalsePro & Farm900,000$0$0$No---------------------------
Theo LindsteinCheckers (FLO)D212005-01-05SWEYes192 Lbs6 ft0NoNoProspectNoNo32026-06-11FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Zayne ParekhCheckers (FLO)D202006-02-15CANYes187 Lbs6 ft0NoNoProspectNoNo32026-06-11FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2923.79196 Lbs6 ft12.101,064,862$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Adam BeckmanJansen HarkinsBradly Nadeau40113
2Jacob PetersonJamieson ReesMatvei Gridin34122
3Ozzy WiesblattRyan SuzukiMackie Samoskevich18122
4Egor AfanasyevAleksanteri KaskimakiDanila Klimovich8122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joe HickettsShakir Mukhamadullin40122
2Santeri HatakkaZayne Parekh34122
3Kirill KirsanovTheo Lindstein19122
4Joe HickettsTheo Lindstein7122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Adam BeckmanJansen HarkinsBradly Nadeau60104
2Jacob PetersonAleksanteri KaskimakiMatvei Gridin40104
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Santeri HatakkaShakir Mukhamadullin53104
2Theo LindsteinZayne Parekh47104
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jamieson ReesEgor Afanasyev55140
2Aleksanteri KaskimakiBradly Nadeau45140
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joe HickettsTheo Lindstein55140
2Zayne ParekhKirill Kirsanov45140
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Egor Afanasyev54050Joe HickettsTheo Lindstein54140
2Jamieson Rees46050Zayne ParekhKirill Kirsanov46140
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jansen HarkinsAdam Beckman57113
2Jamieson ReesBradly Nadeau43113
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joe HickettsShakir Mukhamadullin56122
2Santeri HatakkaZayne Parekh44122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Adam BeckmanJansen HarkinsBradly NadeauSanteri HatakkaShakir Mukhamadullin
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jamieson ReesAleksanteri KaskimakiEgor AfanasyevJoe HickettsShakir Mukhamadullin
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Adam Beckman, Ryan Suzuki, Aleksanteri KaskimakiAdam Beckman, Ryan SuzukiEgor Afanasyev
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Zayne Parekh, Theo Lindstein, Santeri HatakkaZayne ParekhTheo Lindstein, Santeri Hatakka
Tirs de pénalité
Aleksanteri Kaskimaki, Adam Beckman, Ryan Suzuki, Bradly Nadeau, Jacob Peterson
Gardien
#1 : Sergei Murashov, #2 : Arsenii Sergeev


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
TotalDomicile Visiteur
# 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 RI
1Admirals11000000404000000000001100000040421.000481201141110029104101920274621100.00%30100.00%016632551.08%17631256.41%9016953.25%2611792568114270
2Firebird11000000642110000006420000000000021.00061218001411100361041019202868184250.00%4250.00%016632551.08%17631256.41%9016953.25%2611792568114270
3IceHogs22000000624110000003031100000032141.0006121801141110049104101920391112307114.29%50100.00%016632551.08%17631256.41%9016953.25%2611792568114270
4Moose2020000036-31010000012-11010000024-200.00036900141110052104101920451016348337.50%8362.50%016632551.08%17631256.41%9016953.25%2611792568114270
5Roadrunners11000000101110000001010000000000021.000123011411100341041019202368165120.00%40100.00%016632551.08%17631256.41%9016953.25%2611792568114270
6Stars22000000844110000004221100000042241.0008142200141110050104101920401516396233.33%80100.00%016632551.08%17631256.41%9016953.25%2611792568114270
7Wild21100000734110000006151010000012-120.5007142100141110047104101920522820338112.50%9188.89%016632551.08%17631256.41%9016953.25%2611792568114270
Total11830000035191665100000219125320000014104160.72735681030314111002971041019202548086191391025.64%41685.37%016632551.08%17631256.41%9016953.25%2611792568114270
_Since Last GM Reset11830000035191665100000219125320000014104160.72735681030314111002971041019202548086191391025.64%41685.37%016632551.08%17631256.41%9016953.25%2611792568114270
_Vs Conference11830000035191665100000219125320000014104160.72735681030314111002971041019202548086191391025.64%41685.37%016632551.08%17631256.41%9016953.25%2611792568114270

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1116W23568103297254808619103
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
118300003519
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
6510000219
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
53200001410
Derniers 10 matchs
WLOTWOTL SOWSOL
730000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
391025.64%41685.37%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
1041019201411100
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
16632551.08%17631256.41%9016953.25%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2611792568114270


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
215Checkers4Stars2WSommaire du match
430Roadrunners0Checkers1WSommaire du match
537Checkers3IceHogs2WSommaire du match
755IceHogs0Checkers3WSommaire du match
1068Checkers2Moose4LSommaire du match
1494Wild1Checkers6WSommaire du match
16113Moose2Checkers1LSommaire du match
20133Stars2Checkers4WSommaire du match
21145Checkers1Wild2LSommaire du match
24165Firebird4Checkers6WSommaire du match
25173Checkers4Admirals0WSommaire du match
28196Checkers-Firebird-
29200Checkers-Roadrunners-
32220Admirals-Checkers-
34234Checkers-Hammers-
36247Checkers-Bears-
37255Penguins-Checkers-
41275Senators-Checkers-
43293Checkers-Gulls-
45308Checkers-Stars-
46318Marlies-Checkers-
49335Checkers-Americans-
50347Hammers-Checkers-
53367Checkers-Canucks-
55378Monsters-Checkers-
58388Checkers-Marlies-
61409Crunch-Checkers-
63427Checkers-Thunderbirds-
65440Griffins-Checkers-
68465Stars-Checkers-
72491Moose-Checkers-
77520IceHogs-Checkers-
79534Checkers-Eagles-
81549Comets-Checkers-
83569Checkers-Moose-
85580Rockets-Checkers-
87596Checkers-Comets-
89608Checkers-Admirals-
90622Wild-Checkers-
93644Checkers-Wolves-
96656Wranglers-Checkers-
98674Checkers-Reign-
100688Wolf Pack-Checkers-
102704Checkers-Penguins-
104718Checkers-Bruins-
105726Bears-Checkers-
109753Thunderbirds-Checkers-
112776Phantoms-Checkers-
115785Checkers-Griffins-
118810Silver Knight-Checkers-
120823Checkers-Monsters-
123841Wolves-Checkers-
124855Checkers-Phantoms-
127874Firebird-Checkers-
129891Checkers-Rockets-
130905Roadrunners-Checkers-
134927Checkers-Wranglers-
136938Eagles-Checkers-
141965Barracuda-Checkers-
143983Checkers-Roadrunners-
145995Condors-Checkers-
1461007Checkers-Condors-
1481013Checkers-Firebird-
1501031Checkers-Silver Knight-
1511037Canucks-Checkers-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1541053Checkers-Wolf Pack-
1571071Reign-Checkers-
1591090Checkers-Senators-
1611099Checkers-Barracuda-
1631109Bruins-Checkers-
1651123Checkers-Wild-
1671134Checkers-Crunch-
1691148Admirals-Checkers-
1701160Checkers-IceHogs-
1741179Gulls-Checkers-
1841215Americans-Checkers-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3616
Assistance12,0006,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
32 3000 - 100.00% 131,120$786,720$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
995,996$ 6,176,200$ 6,176,200$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 923,015$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
4,195,840$ 158 36,088$ 5,701,904$




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