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Admirals
GP: 51 | W: 24 | L: 21 | OTL: 6 | P: 54
GF: 124 | GA: 145 | PP%: 27.36% | PK%: 64.34%
DG: Andrew Welch | Morale : 49 | Moyenne d’équipe : 56
Prochains matchs #807 vs Crunch

Centre de jeu
Admirals
24-21-6, 54pts
2
1 Condors
27-18-7, 61pts
Team Stats
W2SéquenceOTL1
12-12-2Fiche domicile14-10-1
12-9-4Fiche domicile13-8-6
6-3-1Derniers 10 matchs5-2-3
2.43Buts par match 2.67
2.84Buts contre par match 2.27
27.36%Pourcentage en avantage numérique27.36%
64.34%Pourcentage en désavantage numérique72.44%
Crunch
15-28-7, 37pts
2
5 Admirals
24-21-6, 54pts
Team Stats
L3SéquenceW2
10-11-5Fiche domicile12-12-2
5-17-2Fiche domicile12-9-4
4-6-0Derniers 10 matchs6-3-1
2.30Buts par match 2.43
3.12Buts contre par match 2.84
24.37%Pourcentage en avantage numérique27.36%
71.63%Pourcentage en désavantage numérique64.34%
Admirals
24-21-6, 54pts
Jour 64
Crunch
15-28-7, 37pts
Statistiques d’équipe
W2SéquenceL3
12-12-2Fiche domicile10-11-5
12-9-4Fiche visiteur5-17-2
6-3-110 derniers matchs4-6-0
2.43Buts par match 2.30
2.84Buts contre par match 2.30
27.36%Pourcentage en avantage numérique24.37%
64.34%Pourcentage en désavantage numérique71.63%
Phantoms
20-25-6, 46pts
Jour 65
Admirals
24-21-6, 54pts
Statistiques d’équipe
L1SéquenceW2
9-14-3Fiche domicile12-12-2
11-11-3Fiche visiteur12-9-4
3-4-310 derniers matchs6-3-1
2.55Buts par match 2.43
3.14Buts contre par match 2.43
25.00%Pourcentage en avantage numérique27.36%
64.79%Pourcentage en désavantage numérique64.34%
Barracuda
35-12-5, 75pts
Jour 66
Admirals
24-21-6, 54pts
Statistiques d’équipe
W1SéquenceW2
18-7-1Fiche domicile12-12-2
17-5-4Fiche visiteur12-9-4
7-3-010 derniers matchs6-3-1
1.90Buts par match 2.43
1.56Buts contre par match 2.43
24.27%Pourcentage en avantage numérique27.36%
86.54%Pourcentage en désavantage numérique64.34%
Meneurs d'équipe
Buts
Yegor Sidorov
21
Passes
Yegor Sidorov
27
Points
Yegor Sidorov
48
Plus/Moins
Angus Booth
7
Victoires
Dryden McKay
22
Pourcentage d’arrêts
Adam Scheel
0.857

Statistiques d’équipe
Buts pour
124
2.43 GFG
Tirs pour
842
16.51 Avg
Pourcentage en avantage numérique
27.4%
29 GF
Début de zone offensive
33.6%
Buts contre
145
2.84 GAA
Tirs contre
956
18.75 Avg
Pourcentage en désavantage numérique
64.3%%
46 GA
Début de la zone défensive
39.2%
Informations de l'équipe

Directeur généralAndrew Welch
EntraîneurAustin Violette
DivisionDivision 4
ConférenceConference 2
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,916
Billets de saison1,500


Informations de la formation

Équipe Pro23
Équipe Mineure25
Limite contact 48 / 100
Espoirs119


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
1Tye FelhaberX100.0065675668678288635059645860464661706102711,045,000$
2Yegor Sidorov (R)X99.0074679067687174625058636258464561716102131,315,000$
3Joshua Roy (R)XX100.006542957371587559255171572549496457600222835,000$
4Ben Jones (R)X100.0085928770715191634451576725484760726002731,386,000$
5Ethan Keppen (R)XXX100.0078758664764340577149606357454559495602531,339,000$
6Bradley MarekXXX100.0076806464805050536646566153464554505502531,111,000$
7Cameron WrightX100.0070716865715353565049576055454558315502712,000,000$
8C.J. SuessX100.0075708765705556536846556053464557565503212,000,000$
9Matthew SeminoffX100.0073698563706671475044445843464552635402231,041,000$
10Carl BerglundX100.0081769563764949506350456343454552505402631,109,000$
11Ryan Leonard (R)X100.0081739981744951435038446242464551565402131,268,000$
12Cam BergXXX100.0054409981712830582549546325464555595402412,000,000$
13Cam Thiesing (R)XXX100.0071687764685051496347475846454552305302512,000,000$
14Joshua BrownX99.0076874767876166482536396437686948646103211,275,000$
15Artem Duda (R)X100.0075699267705556532549436240464553705802131,289,000$
16Otto Salin (R)X100.0078719981723531532551406337454553495702231,293,000$
17Angus Booth (R)X100.0073717964724849492541425938464549635502131,263,000$
18Jesse Pulkkinen (R)X100.0084839161843634452535396437464548685502131,263,000$
19Chad NychukX100.0073718161714141462537395937454549345202521,065,000$
Rayé
1Jordan Dumais (R)X100.0071619364624947595057576054454559425602131,279,000$
2Ben Harpur (R)X100.0078885662885052462536406138454649375603131,401,000$
MOYENNE D’ÉQUIPE99.90747182677351555343475061434747545456
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
1Dryden McKay100.004440506745904550908145464558785902811,000,000$
2Adam Scheel100.005140508354605559636130444455795702631,140,000$
Rayé
MOYENNE D’ÉQUIPE100.0048405075507550557771384545577958
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Austin Violette40404040404040TUR8111,000,000$


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
1Yegor SidorovAdmirals (NAS)RW51212748-1027257094137366815.33%29115922.747714247811251002335.82%672725010.8357122373
2Tye FelhaberAdmirals (NAS)LW49162743-65715107106103295115.53%15105521.53291112590223494244.26%653225110.8201012522
3Joshua RoyAdmirals (NAS)LW/RW49172037-15005471113386315.04%1395219.4454916601017553327.54%694111000.7825000621
4Ben JonesAdmirals (NAS)C50191433-29155657699255819.19%1798719.7642611490112443141.73%6592812010.6702137313
5Bradley MarekAdmirals (NAS)C/LW/RW5151217-153159864536259.43%1289917.63224459000090041.18%341112000.3800102211
6Artem DudaAdmirals (NAS)D5131316-4292534714114187.32%47116422.8303343310115700100.00%11526000.2700212012
7Jordan DumaisAdmirals (NAS)RW348715-31715374949173616.33%961017.961346330001201053.49%43156000.4902003011
8Carl BerglundAdmirals (NAS)C455101542040442851217.86%261213.62011080000133048.45%161412000.4900000014
9Angus BoothAdmirals (NAS)D5141115713540531981621.05%21104420.48213458000266100%0423100.2900100010
10Joshua BrownAdmirals (NAS)D4921214-1015355103785231133.85%51122825.08145784000162000%01630000.2300236001
11Ryan LeonardAdmirals (NAS)RW5166120171551653092220.00%986016.870223440002490047.46%1181816000.2845030021
12Ethan KeppenAdmirals (NAS)C/LW/RW30448-1612531412772614.81%546815.601232180001191159.34%18255000.3400122000
13Otto SalinAdmirals (NAS)D462573752032104320.00%1262613.6100002000122100%087000.2200001001
14Cameron WrightAdmirals (NAS)RW2004427521166260%726513.2700000000000062.50%814000.3000001000
15C.J. SuessAdmirals (NAS)C493140003830146621.43%24769.73112422000000057.14%3534000.1700000000
16Jesse PulkkinenAdmirals (NAS)D51134-529153862178125.88%2891617.97112574000095000%0317000.0900102000
17Ben HarpurAdmirals (NAS)D39123-6792554611514106.67%2182421.15101343000050000%0415000.0700122000
18Matthew SeminoffAdmirals (NAS)RW510221202776150%33266.3900007000010057.14%702000.1200000000
19Cam BergAdmirals (NAS)C/LW/RW49202000117133515.38%12455.0210113000001020.00%571000.1600000100
20Cam ThiesingAdmirals (NAS)C/LW/RW200111201483110%01386.9400001000010036.36%1120000.1400000010
21Justin GillPredatorsC/LW/RW21013601222550.00%02412.48000000000000100.00%100000.8000000000
22Chad NychukAdmirals (NAS)D22011020242100%21657.500000100007000%011000.1200000000
23Gabe PerreaultPredatorsRW2011000121010%0115.9501100000000045.45%1100001.6800000000
24Cameron ButlerPredatorsRW2000000000000%031.760000000000000%00000000000000
25Brandon HickeyPredatorsD26000-100452010%11606.160000000004000%00000000000000
Statistiques d’équipe totales ou en moyenne940120183303-43654300961104884226746314.25%3071522916.2029437210674634726733201044.89%2065235234230.401122111732202020
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
1Dryden McKayAdmirals (NAS)51222160.8532.73297144135919434220.50020510032
2Adam ScheelAdmirals (NAS)72000.8572.361270053519001.0003051000
Statistiques d’équipe totales ou en moyenne58242160.8532.7130994414095445322235151032


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
Adam ScheelAdmirals (NAS)G261999-05-01USANo200 Lbs6 ft4NoNoN/ANoNo32025-10-17FalseFalsePro & Farm1,140,000$508,929$0$0$No1,140,000$1,140,000$-------1,140,000$1,140,000$-------NoNo-------Lien
Angus BoothAdmirals (NAS)D212004-04-27QCYes190 Lbs6 ft1NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,263,000$563,839$0$0$No1,263,000$1,263,000$-------1,263,000$1,263,000$-------NoNo-------Lien
Artem DudaAdmirals (NAS)D212004-04-08RUSYes187 Lbs6 ft1NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,289,000$575,446$0$0$No1,289,000$1,289,000$-------1,289,000$1,289,000$-------NoNo-------Lien
Ben HarpurAdmirals (NAS)D311995-01-12CANYes231 Lbs6 ft6NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,401,000$625,446$0$0$No1,401,000$1,401,000$-------1,401,000$1,401,000$-------NoNo-------Lien
Ben JonesAdmirals (NAS)C271999-02-26CANYes187 Lbs6 ft0NoNoAssign ManuallyNoNo32025-10-22FalseFalsePro & Farm1,386,000$618,750$0$0$No1,386,000$1,386,000$-------1,386,000$1,386,000$-------NoNo-------Lien
Bradley MarekAdmirals (NAS)C/LW/RW252000-11-13USANo212 Lbs6 ft4NoNoAssign ManuallyNoNo32025-10-17FalseFalsePro & Farm1,111,000$495,982$0$0$No1,111,000$1,111,000$-------1,111,000$1,111,000$-------NoNo-------Lien
C.J. SuessAdmirals (NAS)C321994-03-17USANo194 Lbs6 ft0NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm2,000,000$892,857$0$0$No---------------------------Lien / Lien NHL
Cam BergAdmirals (NAS)C/LW/RW242002-01-29USANo190 Lbs6 ft0NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm2,000,000$892,857$0$0$No---------------------------Lien
Cam ThiesingAdmirals (NAS)C/LW/RW252001-03-26USAYes189 Lbs6 ft0NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm2,000,000$892,857$0$0$No---------------------------Lien
Cameron WrightAdmirals (NAS)RW271998-08-11ONTNo193 Lbs6 ft1NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm2,000,000$892,857$0$0$No---------------------------Lien
Carl BerglundAdmirals (NAS)C262000-01-16SWENo207 Lbs6 ft2NoNoAssign ManuallyNoNo32025-10-17FalseFalsePro & Farm1,109,000$495,089$0$0$No1,109,000$1,109,000$-------1,109,000$1,109,000$-------NoNo-------Lien
Chad NychukAdmirals (NAS)D252001-03-06MANNo194 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm1,065,000$475,446$0$0$No1,065,000$--------1,065,000$--------No--------Lien
Dryden McKayAdmirals (NAS)G281997-11-25USANo183 Lbs6 ft0NoNoAssign ManuallyNoNo12025-12-08FalseFalsePro & Farm1,000,000$446,429$0$0$No---------------------------Lien
Ethan KeppenAdmirals (NAS)C/LW/RW252001-03-20ONYes203 Lbs6 ft2NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,339,000$597,768$0$0$No1,339,000$1,339,000$-------1,339,000$1,339,000$-------NoNo-------Lien
Jesse PulkkinenAdmirals (NAS)D212004-12-27FINYes215 Lbs6 ft6NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,263,000$563,839$0$0$No1,263,000$1,263,000$-------1,263,000$1,263,000$-------NoNo-------Lien
Jordan DumaisAdmirals (NAS)RW212004-04-15CANYes174 Lbs5 ft9NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,279,000$570,982$0$0$No1,279,000$1,279,000$-------1,279,000$1,279,000$-------NoNo-------Lien
Joshua BrownAdmirals (NAS)D321994-01-21ONTNo220 Lbs6 ft5NoNoN/ANoNo1FalseFalsePro & Farm1,275,000$569,196$0$0$No---------------------------Lien
Joshua RoyAdmirals (NAS)LW/RW222003-08-06CANYes192 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm835,000$372,768$0$0$No835,000$--------835,000$--------No--------Lien
Matthew SeminoffAdmirals (NAS)RW222003-12-27USANo190 Lbs5 ft11NoNoN/ANoNo32025-05-01FalseFalsePro & Farm1,041,000$464,732$0$0$No1,041,000$1,041,000$-------1,041,000$1,041,000$-------NoNo-------Lien
Otto SalinAdmirals (NAS)D222004-03-07FINYes195 Lbs6 ft0NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,293,000$577,232$0$0$No1,293,000$1,293,000$-------1,293,000$1,293,000$-------NoNo-------Lien
Ryan LeonardAdmirals (NAS)RW212005-01-21USAYes192 Lbs6 ft0NoNoProspectNoNo32025-10-22FalseFalsePro & Farm1,268,000$566,071$0$0$No1,268,000$1,268,000$-------1,268,000$1,268,000$-------NoNo-------Lien
Tye FelhaberAdmirals (NAS)LW271998-08-05CANNo185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,045,000$466,518$0$0$No---------------------------Lien
Yegor SidorovAdmirals (NAS)RW212004-06-18BLRYes184 Lbs6 ft0NoNoDraftNoNo32025-10-22FalseFalsePro & Farm1,315,000$587,054$0$0$No1,315,000$1,315,000$-------1,315,000$1,315,000$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2324.87196 Lbs6 ft12.301,335,522$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cameron WrightTye FelhaberYegor Sidorov40122
2Bradley MarekBen JonesC.J. Suess30122
3Tye FelhaberBen JonesRyan Leonard20122
4Yegor SidorovTye FelhaberBen Jones10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Artem DudaJoshua Brown40122
2Otto SalinAngus Booth30122
3Jesse PulkkinenJoshua Brown20122
4Otto SalinJoshua Brown10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1C.J. SuessTye FelhaberYegor Sidorov60122
2Bradley MarekRyan LeonardBen Jones40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jesse PulkkinenJoshua Brown60122
2Artem DudaAngus Booth40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Tye FelhaberYegor Sidorov60122
2Ben JonesRyan Leonard40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Joshua BrownJesse Pulkkinen60122
2Otto SalinAngus Booth40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Tye Felhaber60122Joshua BrownJesse Pulkkinen60122
2Yegor Sidorov40122Artem DudaAngus Booth40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Tye FelhaberYegor Sidorov60122
2Ben JonesRyan Leonard40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jesse PulkkinenJoshua Brown60122
2Artem DudaAngus Booth40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ben JonesTye FelhaberYegor SidorovArtem DudaJoshua Brown
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ben JonesTye FelhaberYegor SidorovArtem DudaJoshua Brown
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Tye Felhaber, Yegor Sidorov, Ryan LeonardYegor Sidorov, Tye FelhaberRyan Leonard
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jesse Pulkkinen, Angus Booth, Joshua BrownJesse PulkkinenJoshua Brown, Jesse Pulkkinen
Tirs de pénalité
Ryan Leonard, Yegor Sidorov, Ben Jones, Bradley Marek, Tye Felhaber
Gardien
#1 : Dryden McKay, #2 : Adam Scheel


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
1Americans30300000613-70000000000030300000613-700.0006101600264641186921129131745791958646116.67%9277.78%029768243.55%36279545.53%26855348.46%8492979425861311634
2Barracuda1010000002-2000000000001010000002-200.00000000264641181321129131745111728200.00%10100.00%029768243.55%36279545.53%26855348.46%8492979425861311634
3Bears1000000123-1000000000001000000123-110.500224002646411826211291317452484152150.00%20100.00%029768243.55%36279545.53%26855348.46%8492979425861311634
4Canucks22000000734110000004221100000031241.000710170026464118322112913174533623264375.00%4175.00%029768243.55%36279545.53%26855348.46%8492979425861311634
5Checkers50201020910-13020100047-32000002053260.60091221002646411877211291317457326101105700.00%13653.85%029768243.55%36279545.53%26855348.46%8492979425861311634
6Comets2020000027-51010000004-41010000023-100.0002460026464118352112913174542174143200.00%8450.00%029768243.55%36279545.53%26855348.46%8492979425861311634
7Condors2010100023-11010000002-21000100021120.5002350026464118222112913174537113127200.00%8275.00%029768243.55%36279545.53%26855348.46%8492979425861311634
8Crunch11000000523110000005230000000000021.00057120026464118172112913174574515200.00%000%029768243.55%36279545.53%26855348.46%8492979425861311634
9Eagles421000101816210000010761321000001110160.750182947002646411877211291317458724587910550.00%191047.37%229768243.55%36279545.53%26855348.46%8492979425861311634
10Griffins1010000024-2000000000001010000024-200.00022410264641181021129131745207121022100.00%110.00%029768243.55%36279545.53%26855348.46%8492979425861311634
11Gulls1010000013-21010000013-20000000000000.000112002646411862112913174515529100.00%10100.00%029768243.55%36279545.53%26855348.46%8492979425861311634
12Heat5210110016142311010009902100010075270.70016254100264641188321129131745115331149312541.67%17758.82%029768243.55%36279545.53%26855348.46%8492979425861311634
13IceHogs20000011220100000101011000000112-130.750224012646411823211291317451912737300.00%110.00%029768243.55%36279545.53%26855348.46%8492979425861311634
14Marlies1000010034-11000010034-10000000000010.500358002646411822211291317451332210400.00%10100.00%029768243.55%36279545.53%26855348.46%8492979425861311634
15Monsters11000000101000000000001100000010121.0001230126464118162112913174550518600.00%000%029768243.55%36279545.53%26855348.46%8492979425861311634
16Moose52201000161603020100058-322000000118360.60016233900264641181132112913174593324610412216.67%13469.23%029768243.55%36279545.53%26855348.46%8492979425861311634
17Penguins32100000910-12110000047-31100000053240.6679152400264641184421129131745551746678337.50%13376.92%029768243.55%36279545.53%26855348.46%8492979425861311634
18Roadrunners1010000026-41010000026-40000000000000.0002350026464118142112913174539155283133.33%000%029768243.55%36279545.53%26855348.46%8492979425861311634
19Rocket10001000101100010001010000000000021.0001120126464118122112913174591220100.00%10100.00%029768243.55%36279545.53%26855348.46%8492979425861311634
20Senators30100101812-41000000134-12010010058-320.3338101810264641184621129131745682711538450.00%3166.67%029768243.55%36279545.53%26855348.46%8492979425861311634
21Stars41102000862210010005142010100035-260.7508111901264641185521129131745662729723266.67%7271.43%029768243.55%36279545.53%26855348.46%8492979425861311634
22Thunderbirds1010000025-31010000025-30000000000000.000235002646411814211291317453411818200.00%4175.00%029768243.55%36279545.53%26855348.46%8492979425861311634
23Wolves1010000024-21010000024-20000000000000.000235002646411816211291317451212120400.00%3166.67%129768243.55%36279545.53%26855348.46%8492979425861311634
Total51132107343124145-2126512051215874-162589022226671-5540.5291241833072426464118842211291317459563076589611062927.36%1294664.34%329768243.55%36279545.53%26855348.46%8492979425861311634
_Since Last GM Reset51132107343124145-2126512051215874-162589022226671-5540.5291241833072426464118842211291317459563076589611062927.36%1294664.34%329768243.55%36279545.53%26855348.46%8492979425861311634
_Vs Conference349140523193107-141738041104153-121766011215254-2370.54493140233112646411860421129131745698222503665712230.99%993663.64%229768243.55%36279545.53%26855348.46%8492979425861311634
_Vs Division8911051301624-843604010615-9465011201091352.1881626420126464118137211291317451384311716322418.18%26869.23%129768243.55%36279545.53%26855348.46%8492979425861311634

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
5154W212418330784295630765896124
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
5113217343124145
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2651251215874
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
258922226671
Derniers 10 matchs
WLOTWOTL SOWSOL
630100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1062927.36%1294664.34%3
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
2112913174526464118
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
29768243.55%36279545.53%26855348.46%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
8492979425861311634


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
17Heat5Admirals6WSommaire du match
223Admirals6Eagles5WSommaire du match
442Stars0Admirals3WSommaire du match
661Admirals5Penguins3WSommaire du match
774Moose1Admirals2WXSommaire du match
994Checkers2Admirals3WXSommaire du match
10113Admirals2Bears3LXXSommaire du match
11128Eagles6Admirals7WXXSommaire du match
12138Admirals0Stars3LSommaire du match
13147Admirals1Americans3LSommaire du match
15166Checkers3Admirals1LSommaire du match
16188Moose3Admirals1LSommaire du match
17199Admirals5Moose4WSommaire du match
18214Admirals3Eagles1WSommaire du match
19225Admirals5Senators6LXSommaire du match
20242Penguins5Admirals0LSommaire du match
21256Admirals1Americans2LSommaire du match
23274Moose4Admirals2LSommaire du match
25294Checkers2Admirals0LSommaire du match
27311Admirals3Checkers2WXXSommaire du match
28323Roadrunners6Admirals2LSommaire du match
29341Admirals2Eagles4LSommaire du match
30353Rocket0Admirals1WXSommaire du match
31368Admirals3Canucks1WSommaire du match
32388Condors2Admirals0LSommaire du match
34405Admirals1IceHogs2LXXSommaire du match
35420Gulls3Admirals1LSommaire du match
36437Admirals0Barracuda2LSommaire du match
37447Senators4Admirals3LXXSommaire du match
38471Wolves4Admirals2LSommaire du match
40483Admirals4Americans8LSommaire du match
41503Canucks2Admirals4WSommaire du match
42513Admirals3Stars2WXSommaire du match
43533Marlies4Admirals3LXSommaire du match
44550Admirals1Monsters0WSommaire du match
45563Penguins2Admirals4WSommaire du match
46580Admirals2Checkers1WXXSommaire du match
47594Admirals2Griffins4LSommaire du match
48606Heat2Admirals0LSommaire du match
49624IceHogs0Admirals1WXXSommaire du match
50639Admirals2Comets3LSommaire du match
51648Admirals4Heat1WSommaire du match
52664Stars1Admirals2WXSommaire du match
53683Admirals0Senators2LSommaire du match
54696Comets4Admirals0LSommaire du match
56715Admirals6Moose4WSommaire du match
57726Heat2Admirals3WXSommaire du match
58748Thunderbirds5Admirals2LSommaire du match
59761Admirals3Heat4LXSommaire du match
61775Admirals2Condors1WXSommaire du match
62786Crunch2Admirals5WSommaire du match
64807Admirals-Crunch-
65817Phantoms-Admirals-
66838Barracuda-Admirals-
67850Admirals-Phantoms-
68861Admirals-Bruins-
70880Eagles-Admirals-
71891Admirals-Thunderbirds-
73911Wolf Pack-Admirals-
74928Admirals-Reign-
75939Admirals-Wolves-
76952Wild-Admirals-
78971Islanders-Admirals-
80986Admirals-Gulls-
811001Wolf Pack-Admirals-
821018Admirals-Wolf Pack-
831030Admirals-Silver Knights-
841044Griffins-Admirals-
851052Admirals-Rocket-
861071Admirals-Roadrunners-
881083Monsters-Admirals-
891103Bruins-Admirals-
901112Admirals-Islanders-
911132Roadrunners-Admirals-
941159Bears-Admirals-
961186Stars-Admirals-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
981211Americans-Admirals-
1001226Admirals-Marlies-
1011243Silver Knights-Admirals-
1021248Admirals-Penguins-
1051276Reign-Admirals-
1061285Admirals-Wild-
1071294Admirals-Rocket-
1081306Admirals-Penguins-
1101318Americans-Admirals-
1111333Admirals-Wild-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets304
Assistance49,83425,989
Assistance PCT95.83%99.96%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
17 2916 - 97.21% 91,634$2,382,475$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,124,576$ 3,071,700$ 3,071,700$ 1,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
27,426$ 1,553,078$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,557,772$ 50 36,354$ 1,817,700$




Admirals 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

Admirals 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

Admirals 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

Admirals 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

Admirals 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