Please rotate your device to landscape mode for a better experience.
Connexion

Sags
GP: 42 | W: 21 | L: 18 | OTL: 3 | P: 45
GF: 122 | GA: 123 | PP%: 20.00% | PK%: 81.46%
DG: Nicolas Gagnon | Morale : 90 | Moyenne d’équipe : 57
Prochains matchs #632 vs Rockets

Centre de jeu
Barracudas
24-13-3, 51pts
5
3 Sags
21-18-3, 45pts
Team Stats
L1SéquenceW1
14-4-1Fiche domicile13-7-0
10-9-2Fiche domicile8-11-3
6-3-1Derniers 10 matchs6-4-0
3.73Buts par match 2.90
3.15Buts contre par match 2.93
16.96%Pourcentage en avantage numérique20.00%
84.07%Pourcentage en désavantage numérique81.46%
Scorpions
19-18-4, 42pts
3
4 Sags
21-18-3, 45pts
Team Stats
L1SéquenceW1
13-5-2Fiche domicile13-7-0
6-13-2Fiche domicile8-11-3
5-5-0Derniers 10 matchs6-4-0
3.20Buts par match 2.90
3.07Buts contre par match 2.93
18.78%Pourcentage en avantage numérique20.00%
83.66%Pourcentage en désavantage numérique81.46%
Sags
21-18-3, 45pts
Jour 50
Rockets
22-18-0, 44pts
Statistiques d’équipe
W1SéquenceW1
13-7-0Fiche domicile13-7-0
8-11-3Fiche visiteur9-11-0
6-4-010 derniers matchs5-5-0
2.90Buts par match 3.63
2.93Buts contre par match 3.63
20.00%Pourcentage en avantage numérique18.32%
81.46%Pourcentage en désavantage numérique84.95%
CoolFm
20-19-2, 42pts
Jour 52
Sags
21-18-3, 45pts
Statistiques d’équipe
L2SéquenceW1
10-9-1Fiche domicile13-7-0
10-10-1Fiche visiteur8-11-3
5-5-010 derniers matchs6-4-0
2.80Buts par match 2.90
3.24Buts contre par match 2.90
13.57%Pourcentage en avantage numérique20.00%
87.69%Pourcentage en désavantage numérique81.46%
Sags
21-18-3, 45pts
Jour 53
Farmers
17-23-1, 35pts
Statistiques d’équipe
W1SéquenceL2
13-7-0Fiche domicile8-12-0
8-11-3Fiche visiteur9-11-1
6-4-010 derniers matchs4-6-0
2.90Buts par match 2.73
2.93Buts contre par match 2.73
20.00%Pourcentage en avantage numérique19.05%
81.46%Pourcentage en désavantage numérique82.25%
Meneurs d'équipe
Brett LeasonButs
Brett Leason
8
Torey KrugPasses
Torey Krug
19
Torey KrugPoints
Torey Krug
24
Torey KrugPlus/Moins
Torey Krug
0
Clay StevensonVictoires
Clay Stevenson
6
Kevin MandolesePourcentage d’arrêts
Kevin Mandolese
0.917

Statistiques d’équipe
Buts pour
122
2.90 GFG
Tirs pour
1091
25.98 Avg
Pourcentage en avantage numérique
20.0%
40 GF
Début de zone offensive
37.0%
Buts contre
123
2.93 GAA
Tirs contre
1388
33.05 Avg
Pourcentage en désavantage numérique
81.5%%
28 GA
Début de la zone défensive
44.2%
Informations de l'équipe

Directeur généralNicolas Gagnon
EntraîneurLane Lambert
DivisionDivision Est
ConférenceConference 2
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance3,000
Billets de saison3,000


Informations de la formation

Équipe Pro26
Équipe Mineure18
Limite Contrat44 / 50
Espoirs102


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
1Tanner JeannotX100.009969597578558153304759556687750906002842,000,000$
2Tanner LaczynskiX100.00504587756950404730405455508774090530284775,000$
3Adam BoqvistX99.00544587865559426430636455698472090630255900,000$
4Torey KrugX100.005045848951504045304050555093890905803422,250,000$
5Matt KierstedX100.005045927850534047304450625087750905702721,600,000$
6Dysin MayoX100.00504595786050404530405055508674090560293800,000$
7Kyle CapobiancoX100.00504590766450404530405055508775090560283800,000$
8Cole McWard (R)X100.00504595775850404530405055508269090550245800,000$
Rayé
1Brett LeasonX100.006945857785657556305657776785750906402631,250,000$
2Luke EvangelistaX100.005545868656698264306762656983740906402333,000,000$
3Philip TomasinoX100.006945918459657461305765616883730906302411,200,000$
4Craig SmithX100.00674579806857715830536361689583090610362950,000$
5Juha Jaaska (R)X86.856848837769504053305650576687740905702741,550,000$
6Nikita AlexandrovX100.005045907956504045714050555083700905402551,075,000$
7Ben MeyersX100.00564592775950404530405057508673090530262925,000$
8Samuel LabergeX100.00504595757250404530405055508774090530282800,000$
9Rocco GrimaldiX100.00504595786050404530405055509077090530323775,000$
10Aku Raty (R)X100.005045958050504045304050555082710905202451,075,000$
11Matthew Phillips (R)X100.00504595824050404530405055508673090520274775,000$
12Gabriel LandeskogX100.00504595746050404530405055509178090520322900,000$
13Alexander ChmelevskiX100.00504595776050404530405055508471090520264775,000$
14Nathan Smith (R)X100.00504595796050404530405055508471090520263800,000$
15Aidan McDonough (R)X100.00504595776050404530405055508370090520254800,000$
16Parker WotherspoonX100.007745907957756651304952686587790906402853,000,000$
MOYENNE D’ÉQUIPE99.3857468979615449493246535856867509057
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
Rayé
1Clay Stevenson (R)100.0070506087707070707070708572090620265900,000$
2Kevin Mandolese (R)100.0070404083656565656565658270090570255800,000$
MOYENNE D’ÉQUIPE100.007045508568686868686868847109060
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Lane Lambert65656565947352CAN6241,000,000$


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
1Torey KrugSags (CHI)D39519240240733348152810.42%4575919.47369281230000810050.00%200000.6300000441
2Adam BoqvistSags (CHI)D3041620-1280243533172412.12%3061220.42471119104000065000%300000.6501000322
3Parker WotherspoonSags (CHI)D3161218-7440108446917268.70%4671823.19448491320000690150.00%200000.5012000444
4Tanner JeannotSags (CHI)RW397815-560101194367175110.45%659115.1623516620000170046.39%9700000.5122110173
5Matt KierstedSags (CHI)D3331215-39539333112289.68%2866320.1123520990110722025.00%800000.4500001203
6Brett LeasonSags (CHI)LW248614-3160423852103215.38%1049020.43459121080003702128.33%6000010.5701000220
7Luke EvangelistaSags (CHI)RW114711-500132624101916.67%423821.721347520000121043.59%3900000.9200000210
8Craig SmithSags (CHI)RW17538-880362339122512.82%332319.010111061000090057.14%2800000.4900000300
9Ben MeyersSags (CHI)C24268-420747313136.45%740216.752138380000110038.40%40100000.4001000112
10Kyle CapobiancoSags (CHI)D42167-63406627278153.70%4268616.351015390000280020.00%500000.2000000132
11Tanner LaczynskiSags (CHI)C21246-1060639273177.41%433515.950005390000241040.77%39000000.3600000101
12Dysin MayoSags (CHI)D29156-101804021124148.33%2349917.220114250000210034.00%5000000.2400000110
13Landon SlaggertChicago BlackhawksLW8415-2002131661425.00%315919.882028330000222015.38%1300000.6300000101
14Aku RatySags (CHI)RW23314-12042819121915.79%328412.36000115000092054.17%2400000.2801000023
15Nathan SmithSags (CHI)C23224-500838294276.90%1034014.811015330000290040.73%41000000.2302000104
16Rocco GrimaldiSags (CHI)LW16314-2004152411312.50%326216.43000012000072025.00%2800000.3000000011
17Gabriel LandeskogSags (CHI)LW25213-720720249198.33%640016.03000127000060033.33%3600000.1501000010
18Philip TomasinoSags (CHI)LW12123-70020182311194.35%325120.930225560001290028.57%2100000.2400000110
19Cole McWardSags (CHI)D19123-24018913267.69%1422912.09000230000100050.00%400000.2600000110
20Nikita AlexandrovSags (CHI)C13123-22042811149.09%125019.241122470001220056.80%29400000.2400000001
21Juha JaaskaSags (CHI)LW18112-5802218184135.56%324713.750005390000150042.42%3300000.1600000001
22Samuel LabergeSags (CHI)C10101-200114731114.29%116216.20000010000000036.46%19200000.1200000000
23Aidan McDonoughSags (CHI)C4000-300122020%0348.6300000000000025.71%350000000000000
Statistiques d’équipe totales ou en moyenne51167117184-1112471566461264618143910.37%295894317.502737642121167011563912241.33%217500010.41311111293129
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
1Clay StevensonSags (CHI)166910.9152.5893203404700000.8577161431
2Kevin MandoleseSags (CHI)115410.9172.9363501313740000.50041020412
Statistiques d’équipe totales ou en moyenne27111320.9162.7215670471844000112621843


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 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
Adam BoqvistSags (CHI)D252000-08-15SWENo189 Lbs6 ft0NoNoTrade2025-01-09NoNo52026-03-08FalseFalsePro & Farm900,000$491,667$0$0$No900,000$900,000$900,000$900,000$-----900,000$900,000$900,000$900,000$-----NoNoNoNo-----Lien NHL
Aidan McDonoughSags (CHI)C251999-11-06USAYes190 Lbs6 ft3NoNoTrade2026-05-28NoNo42026-03-08FalseFalsePro & Farm800,000$437,037$0$0$No800,000$800,000$800,000$------800,000$800,000$800,000$------NoNoNo------Lien NHL
Aku RatySags (CHI)RW242001-07-05FINYes170 Lbs6 ft0NoNoAssign ManuallyNoNo52026-03-20FalseFalsePro & Farm1,075,000$587,269$0$0$No1,075,000$1,075,000$1,075,000$1,075,000$-----1,075,000$1,075,000$1,075,000$1,075,000$-----NoNoNoNo-----Lien NHL
Alexander ChmelevskiSags (CHI)RW261999-06-09USANo188 Lbs6 ft0NoNoN/ANoNo42026-03-08FalseFalsePro & Farm775,000$423,380$0$0$No775,000$775,000$775,000$------775,000$775,000$775,000$------NoNoNo------
Ben MeyersSags (CHI)C261998-11-15USANo194 Lbs5 ft11NoNoN/ANoNo22026-03-08FalseFalsePro & Farm925,000$505,324$0$0$No925,000$--------925,000$--------No--------Lien NHL
Brett LeasonSags (CHI)LW261999-04-30CANNo218 Lbs6 ft5NoNoTrade2026-05-16NoNo32026-03-08FalseFalsePro & Farm1,250,000$682,870$0$0$No1,250,000$1,250,000$-------1,250,000$1,250,000$-------NoNo-------Lien NHL
Clay StevensonSags (CHI)G261999-03-03CANYes195 Lbs6 ft4NoNoProspectNoNo52026-03-08FalseFalsePro & Farm900,000$491,667$0$0$No900,000$900,000$900,000$900,000$-----900,000$900,000$900,000$900,000$-----NoNoNoNo-----Lien NHL
Cole McWardSags (CHI)D242001-06-09USAYes192 Lbs6 ft1NoNoTrade2025-09-11NoNo52026-03-08FalseFalsePro & Farm800,000$437,037$0$0$No800,000$800,000$800,000$800,000$-----800,000$800,000$800,000$800,000$-----NoNoNoNo-----Lien NHL
Craig SmithSags (CHI)RW361989-09-05USANo203 Lbs6 ft1NoNoN/ANoNo22026-03-08FalseFalsePro & Farm950,000$518,981$0$0$No950,000$--------950,000$--------No--------Lien NHL
Dysin MayoSags (CHI)D291996-08-17CANNo183 Lbs6 ft2NoNoAssign ManuallyNoNo32026-03-08FalseFalsePro & Farm800,000$437,037$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien NHL
Gabriel LandeskogSags (CHI)LW321992-11-23SWENo215 Lbs6 ft1NoNoN/ANoNo22026-03-08FalseFalsePro & Farm900,000$491,667$0$0$No900,000$--------900,000$--------No--------Lien NHL
Juha Jaaska (sur la masse salariale)Sags (CHI)LW271998-02-09SWEYes210 Lbs6 ft0NoNoAssign ManuallyNoNo42026-03-08FalseFalsePro & Farm1,550,000$846,759$0$0$Yes1,550,000$1,550,000$1,550,000$------1,550,000$1,550,000$1,550,000$------NoNoNo------Lien NHL
Kevin MandoleseSags (CHI)G252000-08-22CANYes180 Lbs6 ft4NoNoN/ANoNo52026-03-08FalseFalsePro & Farm800,000$437,037$0$0$No800,000$800,000$800,000$800,000$-----800,000$800,000$800,000$800,000$-----NoNoNoNo-----Lien NHL
Kyle CapobiancoSags (CHI)D281997-08-13CANNo201 Lbs6 ft2NoNoAssign ManuallyNoNo32026-03-08FalseFalsePro & Farm800,000$437,037$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien NHL
Luke EvangelistaSags (CHI)RW232002-02-21CANNo183 Lbs6 ft0NoNoTrade2026-04-21NoNo32026-03-08FalseFalsePro & Farm3,000,000$1,638,889$0$0$No3,000,000$3,000,000$-------3,000,000$3,000,000$-------NoNo-------Lien NHL
Matt KierstedSags (CHI)D271998-04-14USANo181 Lbs6 ft0NoNoTrade2025-09-18NoNo22026-03-08FalseFalsePro & Farm1,600,000$874,074$0$0$No1,600,000$--------1,600,000$--------No--------Lien NHL
Matthew PhillipsSags (CHI)LW271998-04-06CANYes160 Lbs5 ft8NoNoN/ANoNo42026-03-08FalseFalsePro & Farm775,000$423,380$0$0$No775,000$775,000$775,000$------775,000$775,000$775,000$------NoNoNo------Lien NHL
Nathan SmithSags (CHI)C261998-10-19USAYes177 Lbs6 ft0NoNoN/ANoNo32026-03-08FalseFalsePro & Farm800,000$437,037$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------
Nikita AlexandrovSags (CHI)C252000-09-16RUSNo177 Lbs6 ft1NoNoAssign ManuallyNoNo52026-03-20FalseFalsePro & Farm1,075,000$587,269$0$0$No1,075,000$1,075,000$1,075,000$1,075,000$-----1,075,000$1,075,000$1,075,000$1,075,000$-----NoNoNoNo-----Lien NHL
Parker WotherspoonSags (CHI)D281997-08-24CANNo195 Lbs6 ft1NoNoTrade2025-12-11NoNo52026-03-08FalseFalsePro & Farm3,000,000$1,638,889$0$0$No3,000,000$3,000,000$3,000,000$3,000,000$-----3,000,000$3,000,000$3,000,000$3,000,000$-----NoNoNoNo-----Lien NHL
Philip TomasinoSags (CHI)LW242001-07-28CANNo179 Lbs6 ft0NoNoTrade2025-12-07NoNo12026-03-08FalseFalsePro & Farm1,200,000$655,556$0$0$No---------------------------Lien NHL
Rocco GrimaldiSags (CHI)LW321993-02-08USANo180 Lbs5 ft6NoNoN/ANoNo32026-03-08FalseFalsePro & Farm775,000$423,380$0$0$No775,000$775,000$-------775,000$775,000$-------NoNo-------Lien NHL
Samuel LabergeSags (CHI)C281997-04-10CANNo206 Lbs6 ft2NoNoN/ANoNo22026-03-08FalseFalsePro & Farm800,000$437,037$0$0$No800,000$--------800,000$--------No--------Lien NHL
Tanner JeannotSags (CHI)RW281997-05-29CANNo220 Lbs6 ft2NoNoTrade2026-01-16NoNo42026-03-08FalseFalsePro & Farm2,000,000$1,092,593$0$0$No2,000,000$2,000,000$2,000,000$------2,000,000$2,000,000$2,000,000$------NoNoNo------Lien NHL
Tanner LaczynskiSags (CHI)C281997-06-01USANo190 Lbs6 ft1NoNoN/ANoNo42026-03-08FalseFalsePro & Farm775,000$423,380$0$0$No775,000$775,000$775,000$------775,000$775,000$775,000$------NoNoNo------Lien NHL
Torey KrugSags (CHI)D341991-04-12USANo194 Lbs5 ft9NoNoTrade2025-06-06NoNo22026-03-08FalseFalsePro & Farm2,250,000$1,229,167$0$0$No2,250,000$--------2,250,000$--------No--------Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2627.27191 Lbs6 ft13.461,202,885$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
135122
2Tanner Laczynski30122
3Tanner Jeannot25122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Adam Boqvist35122
2Torey KrugMatt Kiersted30122
3Dysin MayoKyle Capobianco25122
4Cole McWard10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
155122
2Tanner Laczynski45122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Adam Boqvist55122
2Torey KrugMatt Kiersted45122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
155122
2Tanner Laczynski45122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Adam Boqvist55122
2Torey KrugMatt Kiersted45122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
155122Adam Boqvist55122
2Tanner Laczynski45122Torey KrugMatt Kiersted45122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
155122
2Tanner Laczynski45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Adam Boqvist55122
2Torey KrugMatt Kiersted45122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Adam Boqvist
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tanner LaczynskiTorey KrugMatt Kiersted
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, , Tanner Laczynski,
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dysin Mayo, Kyle Capobianco, Cole McWardDysin MayoDysin Mayo, Kyle Capobianco
Tirs de pénalité
, , Tanner Jeannot, ,
Gardien
#1 : , #2 :


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
1Bandits11000000633000000000001100000063321.000612180042394033538435934118409830200.00%4325.00%1531126042.14%692150446.01%28464144.31%9726731049301511257
2Barracudas20200000511-61010000035-21010000026-400.0005914104239403553843593411887214517114.29%2150.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
3Chiwawa22000000835110000002021100000063341.00081523014239403533843593411859129399333.33%20100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
4CoolFm21100000660000000000002110000066020.5006111700423940340384359341184814163311327.27%8362.50%0531126042.14%692150446.01%28464144.31%9726731049301511257
5Farmers11000000211110000002110000000000021.0002460042394032438435934118286893133.33%40100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
6Goons1010000015-4000000000001010000015-400.0001230042394033338435934118194828200.00%40100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
7Grizzlies31200000770211000006511010000012-120.333712190042394031043843593411810724628714214.29%15286.67%0531126042.14%692150446.01%28464144.31%9726731049301511257
8Hunters41300000917-820200000210-82110000077020.25091827014239403104384359341181735026952514.00%11372.73%0531126042.14%692150446.01%28464144.31%9726731049301511257
9Husky320000011073110000003122100000176150.83310203000423940397384359341187824386618527.78%18477.78%0531126042.14%692150446.01%28464144.31%9726731049301511257
10Igloos1010000035-2000000000001010000035-200.000358004239403223843593411845131220100.00%6266.67%0531126042.14%692150446.01%28464144.31%9726731049301511257
11Marlies1010000035-21010000035-20000000000000.00035800423940318384359341183296177114.29%3233.33%0531126042.14%692150446.01%28464144.31%9726731049301511257
12Marmots21100000541110000004221010000012-120.50051015004239403453843593411841510369222.22%5260.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
13Outlaws1000010034-1000000000001000010034-110.5003690042394032238435934118491612253266.67%6183.33%0531126042.14%692150446.01%28464144.31%9726731049301511257
14Raptors11000000422110000004220000000000021.0004812004239403363843593411839141427300.00%70100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
15Rockets413000001016-62110000057-22020000059-420.2501017270042394031033843593411817049438719631.58%19478.95%0531126042.14%692150446.01%28464144.31%9726731049301511257
16Scorpions22000000752110000004311100000032141.000714210042394037038435934118592112527228.57%5180.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
17Smirnoff Ice11000000202110000002020000000000021.0002460142394031638435934118135418300.00%20100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
18Snowbirds21100000532110000003031010000023-120.5005712014239403373843593411854136374125.00%30100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
19Spartans220000001257110000008351100000042241.00012223400423940360384359341186720225316531.25%110100.00%1531126042.14%692150446.01%28464144.31%9726731049301511257
20Supreme1000010034-1000000000001000010034-110.500358004239403333843593411833842012216.67%10100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
21TigersCats1010000013-2000000000001010000013-200.00012300423940315384359341184014920600.00%20100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
22Twins21000010312110000002111000001010141.000336014239403273843593411834148279111.11%40100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
23Vipers11000000422110000004220000000000021.00048120042394032638435934118411212243133.33%50100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
24Xpress1010000034-11010000034-10000000000000.000358004239403163843593411832910247114.29%40100.00%0531126042.14%692150446.01%28464144.31%9726731049301511257
Total42201800211122123-120137000006051922711002116272-10450.53612222434615423940310913843593411813883863639252004020.00%1512881.46%2531126042.14%692150446.01%28464144.31%9726731049301511257
_Since Last GM Reset42201800211122123-120137000006051922711002116272-10450.53612222434615423940310913843593411813883863639252004020.00%1512881.46%2531126042.14%692150446.01%28464144.31%9726731049301511257
_Vs Conference1610300210544014871000003016148320021024240240.750549715113423940341938435934118522151103355731824.66%46393.48%1531126042.14%692150446.01%28464144.31%9726731049301511257
_Vs Division10810010039221755000000218135310010018144170.8503971110024239403289384359341183118867228511325.49%29196.55%1531126042.14%692150446.01%28464144.31%9726731049301511257

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
4245W11222243461091138838636392515
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
4220180211122123
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2013700006051
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2271102116272
Derniers 10 matchs
WLOTWOTL SOWSOL
640000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2004020.00%1512881.46%2
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
384359341184239403
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
531126042.14%692150446.01%28464144.31%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
9726731049301511257


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
112Hunters6Sags2LSommaire du match
227Sags2Rockets4LSommaire du match
335Sags5CoolFm4WSommaire du match
554Rockets4Sags5WSommaire du match
671Sags1Goons5LSommaire du match
782Marmots2Sags4WSommaire du match
9102Sags3Husky1WSommaire du match
10112Rockets3Sags0LSommaire du match
11120Sags1TigersCats3LSommaire du match
12142Smirnoff Ice0Sags2WSommaire du match
14163Marlies5Sags3LSommaire du match
15175Sags1CoolFm2LSommaire du match
16181Sags1Hunters7LSommaire du match
17203Grizzlies2Sags1LSommaire du match
18214Sags1Twins0WXXSommaire du match
19232Farmers1Sags2WSommaire du match
20245Sags3Rockets5LSommaire du match
22265Raptors2Sags4WSommaire du match
23278Sags6Chiwawa3WSommaire du match
24292Sags4Husky5LXXSommaire du match
25306Husky1Sags3WSommaire du match
27324Spartans3Sags8WSommaire du match
28336Sags1Grizzlies2LSommaire du match
29348Sags6Hunters0WSommaire du match
30365Grizzlies3Sags5WSommaire du match
31381Sags3Outlaws4LXSommaire du match
33397Hunters4Sags0LSommaire du match
34414Sags1Marmots2LSommaire du match
35426Twins1Sags2WSommaire du match
36437Sags3Supreme4LXSommaire du match
37456Snowbirds0Sags3WSommaire du match
39476Sags2Snowbirds3LSommaire du match
40486Sags2Barracudas6LSommaire du match
41494Xpress4Sags3LSommaire du match
42517Chiwawa0Sags2WSommaire du match
43528Sags4Spartans2WSommaire du match
44547Vipers2Sags4WSommaire du match
45554Sags3Igloos5LSommaire du match
46573Sags3Scorpions2WSommaire du match
47584Sags6Bandits3WSommaire du match
48596Barracudas5Sags3LSommaire du match
49617Scorpions3Sags4WSommaire du match
50632Sags-Rockets-
52649CoolFm-Sags-
53669Sags-Farmers-
54675Sags-Marlies-
55689Goons-Sags-
56703Sags-Warriors-
57715Bandits-Sags-
58739Supreme-Sags-
59756Sags-Xpress-
60763Sags-Twins-
61778Marlies-Sags-
63802Vandals-Sags-
64812Sags-Raptors-
65826Sags-Smirnoff Ice-
66837TigersCats-Sags-
68857Sags-Raptors-
69866Igloos-Sags-
70887Sags-Vandals-
71897Smirnoff Ice-Sags-
73917Sags-Warriors-
74926Rockets-Sags-
76948Sags-Wolves-
77959Igloos-Sags-
79991Bandits-Sags-
80999Sags-TigersCats-
821021Warriors-Sags-
831043Bayou-Sags-
841053Sags-Vipers-
861068Sags-Predateurs-
871083Thugs-Sags-
891101Sags-Bayou-
901114Outlaws-Sags-
921131Sags-Goons-
931146Farmers-Sags-
951170Sags-Xpress-
961177Marmots-Sags-
991206Wolves-Sags-
1011217Sags-Thugs-
1031239Predateurs-Sags-
1081271Wolves-Sags-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets8030
Assistance40,00020,000
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
21 3000 - 100.00% 228,000$4,560,000$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,816,080$ 3,127,500$ 3,127,500$ 1,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,358,047$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
4,788,000$ 59 38,218$ 2,254,862$




Sags 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

Sags 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

Sags 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

Sags 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

Sags 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