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Admirals
GP: 82 | W: 31 | L: 44 | OTL: 7 | P: 69
GF: 262 | GA: 319 | PP%: 20.88% | PK%: 77.49%
DG: Yannick Masse | Morale : 50 | Moyenne d’équipe : 53
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Centre de jeu
Comets
42-31-9, 93pts
4
FINAL
5 Admirals
31-44-7, 69pts
Team Stats
W1StreakW2
22-15-4Home Record17-21-3
20-16-5Away Record14-23-4
6-2-2Last 10 Games4-6-0
3.62Buts par match 3.20
3.45Buts contre par match 3.89
18.46%Pourcentage en avantage numérique20.88%
78.81%Pourcentage en désavantage numérique77.49%
Monarchs
21-55-6, 48pts
4
FINAL
5 Admirals
31-44-7, 69pts
Team Stats
OTL1StreakW2
8-31-2Home Record17-21-3
13-24-4Away Record14-23-4
2-7-1Last 10 Games4-6-0
3.23Buts par match 3.20
4.41Buts contre par match 3.89
11.87%Pourcentage en avantage numérique20.88%
70.18%Pourcentage en désavantage numérique77.49%
Meneurs d'équipe
Buts
Garrett Pilon
43
Passes
Connor Carrick
47
Points
Garrett Pilon
83
Plus/Moins
Kevin Gravel
3
Victoires
Michael Hutchinson
23
Pourcentage d’arrêts
Michael Hutchinson
0.908

Statistiques d’équipe
Buts pour
262
3.20 GFG
Tirs pour
2827
34.48 Avg
Pourcentage en avantage numérique
20.9%
57 GF
Début de zone offensive
39.5%
Buts contre
319
3.89 GAA
Tirs contre
3195
38.96 Avg
Pourcentage en désavantage numérique
77.5%%
61 GA
Début de la zone défensive
40.7%
Informations de l'équipe

Directeur généralYannick Masse
DivisionEst
ConférenceEst
Capitaine
Assistant #1Justin Falk
Assistant #2Mitch Moroz


Informations de l’aréna

Capacité3,000
Assistance2,595
Billets de saison300


Informations de la formation

Équipe Pro19
Équipe Mineure20
Limite contact 39 / 50
Espoirs11


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 moyen
1Joakim NordstromXXX100.008145947371556858355751792469720506102931,250,000$
2Garrett PilonX100.00757085687064646379606364604444050600232850,000$
3Jonny BrodzinskiX100.00634286737858646165555771255353050600281750,000$
4Josh Ho-SangX100.00706485766452496350596462614444050580251850,000$
5Nikita Alexandrov (R)X100.00736688636658585873545762544444050560212830,833$
6Cameron Hillis (R)X100.00686283666253535569475859554444050540213838,333$
7Jack BadiniXX100.00777386687354564860454562434444050530232805,000$
8Nathan Legare (R)X100.00777484647451525150475062484444050530204789,167$
9Jan Mysak (R)XX100.00716598626553564355354459444444050500192850,833$
10D'Artagnan JolyX100.00474782656952644560473347375454050490222650,000$
11Connor CarrickX100.00696969776960615925495166486565050610271750,000$
12Kevin GravelX100.00837893707861654925394168395657050600291750,000$
13Madison BoweyX100.00697360777357585825494963475757050600261825,000$
14Alex BiegaX100.00716975706956595125404265406565050580331750,000$
15Joey KeaneX100.00676865616866705425504358414444050560222809,166$
16Axel Andersson (R)X100.00726587646549504825374359414444050530213772,500$
17Benjamin Mirageas (R)X100.00464582606741572925252644285454050460222525,000$
Rayé
1John Beecher (R)X100.0011111111111111105050204925,000$
MOYENNE D’ÉQUIPE100.0066607864665256504344455841484905053
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 moyen
1David Tendeck (R)100.0044405064454445494545454444050470214783,333$
Rayé
MOYENNE D’ÉQUIPE100.004440506445444549454545444405047
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Garrett PilonAdmirals (Ana)C82434083-1052101662583628321311.88%25177521.6511142580218123112085160.04%239500000.9349110645
2Jonny BrodzinskiAdmirals (Ana)RW81224567-416049161333882606.61%24147618.235914521610224931150.98%10200000.91210000334
3Josh Ho-SangAdmirals (Ana)RW81303262-133001041653241042509.26%18140517.3561016671881011741437.37%19000000.8834000263
4Connor CarrickAdmirals (Ana)D81114758-7631518493163471226.75%140188523.2831316642122136195100.00%000000.6200111220
5Madison BoweyAdmirals (Ana)D8183947-14811520510014843905.41%120165820.4811112641940111182100.00%200000.5700111023
6Kevin GravelAdmirals (Ana)D811823413541015172118367215.25%104168320.7910717592250001202020.00%000000.4900011221
7Nikita AlexandrovAdmirals (Ana)C82192140-25260138205250651737.60%18143717.53268331220002952156.33%163500000.5601000122
8Cameron HillisAdmirals (Ana)C81211738-13235671611774112411.86%15116114.340009240112352354.76%98800000.6501001031
9Alex BiegaAdmirals (Ana)D8192736-1552101377310243438.82%125165520.444711421940221190210.00%000000.4300010112
10Joey KeaneAdmirals (Ana)D8272835-26640154697319489.59%83135416.521011046000166200.00%100000.5200000122
11Nathan LegareAdmirals (Ana)RW82122234-2322013298163431487.36%11114113.92011624000002054.95%9100000.6000000201
12Jan MysakAdmirals (Ana)C/LW82102030-27280637010122819.90%21153918.77279161520002653147.11%22500000.3900000002
13Joakim NordstromAdmirals (Ana)C/LW/RW2491928-3140496310021529.00%1654822.8735811500112661040.38%5200001.0203000311
14Tyler PitlickAnaheimRW20819279200262474173410.81%438019.012461658000010037.04%2700001.4212000201
15Jack BadiniAdmirals (Ana)C/LW82151227-36662014060138448410.87%25158019.274262622710121342041.41%12800000.3400211210
16Dakota JoshuaAnaheimC/RW24712193381086587725619.09%448120.0825716810004600251.17%64100000.7922002112
17Axel AnderssonAdmirals (Ana)D8231215-24380111455718355.26%94129315.7810151900006600100.00%100000.2300000000
18D'Artagnan JolyAdmirals (Ana)RW822810-10208355111233.92%27539.190000110000190150.00%6000000.2700000010
19Benjamin MirageasAdmirals (Ana)D70134-16205743425.00%134256.07000017000027000.00%000000.1900000000
20John BeecherAdmirals (Ana)C23000-1800000000.00%01566.7900000000012000.00%8000000.00%00000000
Statistiques d’équipe totales ou en moyenne1384255446701-2696919519751817281577319179.06%8622379517.1957101158576223251015401798251754.73%661800000.591232567283130
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
1Michael HutchinsonAnaheim57232950.9083.5333520219721300220.65223570550
2David TendeckAdmirals (Ana)2871220.8844.621351001049000000.88992461101
Statistiques d’équipe totales ou en moyenne85304170.9013.844703023013030022328161651


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 Nouveau joueur Poids Taille Non-échange Disponible pour échange Ballotage forcé Contrat Type Salaire actuel Salaire moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Alex Biega (contrat à 1 volet)Admirals (Ana)D331988-04-04No199 Lbs5 ft10YesNoYes1Pro & Farm750,000$0$0$NoLien
Axel AnderssonAdmirals (Ana)D212000-02-10Yes179 Lbs6 ft0NoNoNo3Pro & Farm772,500$0$0$No772,500$772,500$Lien
Benjamin MirageasAdmirals (Ana)D221999-05-08Yes181 Lbs6 ft1NoNoNo2Pro & Farm525,000$0$0$No525,000$Lien
Cameron HillisAdmirals (Ana)C212000-06-24Yes171 Lbs5 ft10NoNoNo3Pro & Farm838,333$0$0$No838,333$838,333$Lien
Connor Carrick (contrat à 1 volet)Admirals (Ana)D271994-04-13No194 Lbs5 ft11YesNoYes1Pro & Farm750,000$0$0$NoLien
D'Artagnan JolyAdmirals (Ana)RW221999-04-07No181 Lbs6 ft3NoNoNo2Pro & Farm650,000$0$0$No650,000$Lien
David TendeckAdmirals (Ana)G211999-11-25Yes172 Lbs6 ft1NoNoNo4Pro & Farm783,333$0$0$No783,333$783,333$783,333$Lien
Garrett PilonAdmirals (Ana)C231998-04-13No190 Lbs6 ft0NoNoNo2Pro & Farm850,000$0$0$No850,000$Lien
Jack BadiniAdmirals (Ana)C/LW231998-01-19No203 Lbs6 ft0NoNoNo2Pro & Farm805,000$0$0$No805,000$Lien
Jan MysakAdmirals (Ana)C/LW192002-06-24Yes176 Lbs6 ft0NoNoNo2Pro & Farm850,833$0$0$No850,833$Lien
Joakim Nordstrom (contrat à 1 volet)Admirals (Ana)C/LW/RW291992-02-25No194 Lbs6 ft1NoNoYes3Pro & Farm1,250,000$350,000$0$No1,250,000$1,250,000$Lien
Joey KeaneAdmirals (Ana)D221999-07-02No187 Lbs6 ft0NoNoNo2Pro & Farm809,166$0$0$No809,166$Lien
John BeecherAdmirals (Ana)C202001-04-05 08:30:29Yes210 Lbs6 ft3NoNoNo4Pro & Farm925,000$0$0$No925,000$925,000$925,000$
Jonny Brodzinski (contrat à 1 volet)Admirals (Ana)RW281993-06-19No215 Lbs6 ft1YesNoYes1Pro & Farm750,000$0$0$NoLien
Josh Ho-SangAdmirals (Ana)RW251996-01-22No173 Lbs6 ft0NoNoYes1Pro & Farm850,000$0$0$NoLien
Kevin Gravel (contrat à 1 volet)Admirals (Ana)D291992-03-06No205 Lbs6 ft4YesNoYes1Pro & Farm750,000$0$0$NoLien
Madison Bowey (contrat à 1 volet)Admirals (Ana)D261995-04-22No198 Lbs6 ft2YesNoYes1Pro & Farm825,000$0$0$NoLien
Nathan LegareAdmirals (Ana)RW202001-01-11Yes205 Lbs6 ft0NoNoNo4Pro & Farm789,167$0$0$No789,167$789,167$789,167$Lien
Nikita AlexandrovAdmirals (Ana)C212000-09-16Yes176 Lbs6 ft1NoNoNo2Pro & Farm830,833$0$0$No830,833$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1923.79190 Lbs6 ft12.16808,114$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Joakim NordstromGarrett PilonJonny Brodzinski40122
2Jack BadiniNikita AlexandrovJosh Ho-Sang30122
3Jan MysakCameron HillisNathan Legare20122
4Joakim NordstromJan MysakD'Artagnan Joly10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Connor CarrickKevin Gravel40122
2Madison BoweyAlex Biega30122
3Joey KeaneAxel Andersson20122
4Benjamin MirageasConnor Carrick10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Joakim NordstromGarrett PilonJonny Brodzinski60122
2Jack BadiniNikita AlexandrovJosh Ho-Sang40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Connor CarrickKevin Gravel60122
2Madison BoweyAlex Biega40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Garrett PilonJoakim Nordstrom60122
2Nikita AlexandrovJack Badini40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Connor CarrickKevin Gravel60122
2Madison BoweyAlex Biega40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Garrett Pilon60122Connor CarrickKevin Gravel60122
2Nikita Alexandrov40122Madison BoweyAlex Biega40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Garrett PilonJoakim Nordstrom60122
2Nikita AlexandrovJack Badini40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Connor CarrickKevin Gravel60122
2Madison BoweyAlex Biega40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Joakim NordstromGarrett PilonJonny BrodzinskiConnor CarrickKevin Gravel
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Joakim NordstromGarrett PilonJonny BrodzinskiConnor CarrickKevin Gravel
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nikita Alexandrov, Cameron Hillis, Nathan LegareNikita Alexandrov, Cameron HillisNikita Alexandrov
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Joey Keane, Axel Andersson, Benjamin MirageasJoey KeaneJoey Keane, Axel Andersson
Tirs de pénalité
Joakim Nordstrom, Jonny Brodzinski, Garrett Pilon, Josh Ho-Sang, Nikita Alexandrov
Gardien
#1 : , #2 : David Tendeck


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
1Baby Hawks31200000711-42110000067-11010000014-320.333710170010385641668935913944691253225619111.11%10190.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
2Bears2020000049-51010000015-41010000034-100.0004711001038564168393591394469101283356800.00%30100.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
3Bruins2020000068-21010000034-11010000034-100.0006915001038564164793591394469833416456116.67%7271.43%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
4Cabaret Lady Mary Ann220000001165110000006331100000053241.000111930001038564161219359139446996231673000.00%7271.43%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
5Caroline2110000067-1110000004311010000024-220.50061016001038564166793591394469792420445240.00%8187.50%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
6Chiefs30300000510-51010000013-22020000047-300.000591410103856416859359139446910432257117317.65%11554.55%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
7Chill3120000011110211000009811010000023-120.33311182900103856416124935913944691333122679111.11%10370.00%11484277953.40%1500286152.43%770139855.08%1911129019896261081540
8Comets41100011161602100001010822010000168-250.6251625410010385641616193591394469153283411015533.33%11372.73%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
9Cougars210001009901000010067-11100000032130.75091625001038564166393591394469912512613266.67%60100.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
10Crunch2010001068-2100000104311010000025-320.5006915001038564166493591394469692116426116.67%8362.50%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
11Heat412001001114-32010010059-42110000065130.375112132001038564161339359139446916249259312325.00%10280.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
12Jayhawks31001001161421000000156-121001000118350.83316284400103856416106935913944691352733746466.67%14471.43%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
13Las Vegas330000001266110000004222200000084461.000122133001038564161069359139446912629356510330.00%14285.71%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
14Manchots21100000330110000002021010000013-220.500347011038564165793591394469601410367114.29%5180.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
15Marlies20200000612-61010000026-41010000046-200.00061117001038564167093591394469752039546116.67%11372.73%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
16Minnesota30100020990200000207521010000024-240.6679142300103856416114935913944699218187411218.18%90100.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
17Monarchs3110100015141201010009901100000065140.667152843001038564161419359139446913633246714535.71%12283.33%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
18Monsters211000004401010000013-21100000031220.500459001038564165093591394469732110424125.00%5180.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
19Monsters30200100815-720200000511-61000010034-110.16781523001038564169493591394469853126678337.50%13376.92%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
20Oceanics302000101214-21000001043120200000811-320.333121931001038564161009359139446912329296410330.00%11372.73%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
21Oil Kings404000001017-72020000058-32020000059-400.000101929101038564161369359139446915648241061218.33%11190.91%21484277953.40%1500286152.43%770139855.08%1911129019896261081540
22Phantoms2010000168-21010000034-11000000134-110.250611170010385641668935913944696917244110330.00%12375.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
23Rocket20200000811-31010000035-21010000056-100.0008132100103856416569359139446963226415120.00%2150.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
24Seattle40400000523-1820200000313-1020200000210-800.0005914001038564161429359139446918960211011516.67%8450.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
25Senators20001001990100010006511000000134-130.750918270010385641687935913944697115164514214.29%6183.33%11484277953.40%1500286152.43%770139855.08%1911129019896261081540
26Sharks413000001620-420200000712-52110000098120.250163046001038564161469359139446915141441151317.69%12375.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
27Sound Tigers210000101082110000004311000001065141.000101727001038564167693591394469723218475240.00%9277.78%11484277953.40%1500286152.43%770139855.08%1911129019896261081540
28Spiders2110000059-41010000006-61100000053220.5005914001038564165293591394469842616398112.50%8362.50%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
29Stars3020100068-21010000013-22010100055020.33361016001038564167493591394469102251768900.00%5260.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
30Thunder22000000514110000003121100000020241.00051015011038564166793591394469581525628225.00%80100.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
31Wolf Pack21100000550110000003211010000023-120.5005712001038564166993591394469791812548112.50%50100.00%01484277953.40%1500286152.43%770139855.08%1911129019896261081540
Total82214404364262319-5741102102251132167-3541112302113130152-22690.42126245171322103856416282793591394469319586869119852735720.88%2716177.49%51484277953.40%1500286152.43%770139855.08%1911129019896261081540
_Since Last GM Reset82214404364262319-5741102102251132167-3541112302113130152-22690.42126245171322103856416282793591394469319586869119852735720.88%2716177.49%51484277953.40%1500286152.43%770139855.08%1911129019896261081540
_Vs Conference35101902022117135-1818510020105771-141759000126064-4300.4291172033200210385641612379359139446913683743388341302519.23%1242778.23%31484277953.40%1500286152.43%770139855.08%1911129019896261081540

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8269W226245171328273195868691198522
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8221444364262319
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4110212251132167
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4111232113130152
Derniers 10 matchs
WLOTWOTL SOWSOL
460000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2735720.88%2716177.49%5
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
93591394469103856416
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
1484277953.40%1500286152.43%770139855.08%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1911129019896261081540


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
6 - 2022-10-129Seattle8Admirals2BLSommaire du match
9 - 2022-10-1532Admirals6Sound Tigers5AWXXSommaire du match
11 - 2022-10-1739Admirals2Wolf Pack3ALSommaire du match
12 - 2022-10-1848Admirals5Spiders3AWSommaire du match
14 - 2022-10-2059Admirals3Bruins4ALSommaire du match
17 - 2022-10-2388Admirals3Cougars2AWSommaire du match
20 - 2022-10-26110Thunder1Admirals3BWSommaire du match
22 - 2022-10-28121Admirals2Las Vegas1AWSommaire du match
24 - 2022-10-30142Marlies6Admirals2BLSommaire du match
26 - 2022-11-01158Admirals5Sharks3AWSommaire du match
28 - 2022-11-03171Admirals2Comets3ALSommaire du match
30 - 2022-11-05188Admirals4Sharks5ALSommaire du match
31 - 2022-11-06192Cabaret Lady Mary Ann3Admirals6BWSommaire du match
34 - 2022-11-09210Minnesota2Admirals3BWXXSommaire du match
37 - 2022-11-12234Baby Hawks5Admirals3BLSommaire du match
40 - 2022-11-15255Cougars7Admirals6BLXSommaire du match
42 - 2022-11-17266Admirals4Oceanics6ALSommaire du match
44 - 2022-11-19282Admirals2Chiefs3ALSommaire du match
46 - 2022-11-21296Admirals2Chiefs4ALSommaire du match
48 - 2022-11-23314Wolf Pack2Admirals3BWSommaire du match
50 - 2022-11-25323Senators5Admirals6BWXSommaire du match
52 - 2022-11-27343Seattle5Admirals1BLSommaire du match
54 - 2022-11-29356Admirals2Chill3ALSommaire du match
56 - 2022-12-01371Admirals3Stars2AWXSommaire du match
58 - 2022-12-03379Admirals2Minnesota4ALSommaire du match
59 - 2022-12-04392Admirals4Oceanics5ALSommaire du match
61 - 2022-12-06410Caroline3Admirals4BWSommaire du match
64 - 2022-12-09433Sharks5Admirals2BLSommaire du match
67 - 2022-12-12451Admirals3Senators4ALXXSommaire du match
68 - 2022-12-13454Admirals4Marlies6ALSommaire du match
70 - 2022-12-15469Admirals5Rocket6ALSommaire du match
72 - 2022-12-17486Admirals2Oil Kings4ALSommaire du match
75 - 2022-12-20516Admirals6Monarchs5AWSommaire du match
76 - 2022-12-21524Minnesota3Admirals4BWXXSommaire du match
78 - 2022-12-23544Heat4Admirals3BLXSommaire du match
83 - 2022-12-28562Las Vegas2Admirals4BWSommaire du match
85 - 2022-12-30574Chill6Admirals5BLSommaire du match
88 - 2023-01-02597Phantoms4Admirals3BLSommaire du match
90 - 2023-01-04611Stars3Admirals1BLSommaire du match
92 - 2023-01-06627Sharks7Admirals5BLSommaire du match
94 - 2023-01-08644Bruins4Admirals3BLSommaire du match
97 - 2023-01-11660Oil Kings5Admirals3BLSommaire du match
99 - 2023-01-13675Spiders6Admirals0BLSommaire du match
102 - 2023-01-16700Admirals1Manchots3ALSommaire du match
103 - 2023-01-17705Admirals3Phantoms4ALXXSommaire du match
105 - 2023-01-19717Admirals3Monsters1AWSommaire du match
107 - 2023-01-21732Admirals2Crunch5ALSommaire du match
110 - 2023-01-24763Admirals5Jayhawks3AWSommaire du match
112 - 2023-01-26776Admirals3Monsters4ALXSommaire du match
114 - 2023-01-28796Jayhawks6Admirals5BLXXSommaire du match
123 - 2023-02-06811Admirals2Stars3ALSommaire du match
124 - 2023-02-07818Admirals1Baby Hawks4ALSommaire du match
127 - 2023-02-10831Manchots0Admirals2BWSommaire du match
129 - 2023-02-12849Admirals6Las Vegas3AWSommaire du match
132 - 2023-02-15868Crunch3Admirals4BWXXSommaire du match
134 - 2023-02-17882Monarchs5Admirals4BLSommaire du match
137 - 2023-02-20902Admirals5Cabaret Lady Mary Ann3AWSommaire du match
138 - 2023-02-21908Admirals2Thunder0AWSommaire du match
140 - 2023-02-23920Admirals3Bears4ALSommaire du match
142 - 2023-02-25939Admirals2Caroline4ALSommaire du match
144 - 2023-02-27957Baby Hawks2Admirals3BWSommaire du match
146 - 2023-03-01973Bears5Admirals1BLSommaire du match
148 - 2023-03-03987Rocket5Admirals3BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
152 - 2023-03-071021Admirals1Seattle4ALSommaire du match
153 - 2023-03-081024Admirals4Comets5ALXXSommaire du match
155 - 2023-03-101037Admirals2Heat3ALSommaire du match
157 - 2023-03-121060Chill2Admirals4BWSommaire du match
160 - 2023-03-151079Sound Tigers3Admirals4BWSommaire du match
162 - 2023-03-171094Monsters3Admirals1BLSommaire du match
164 - 2023-03-191114Comets4Admirals5BWSommaire du match
166 - 2023-03-211131Heat5Admirals2BLSommaire du match
168 - 2023-03-231146Oceanics3Admirals4BWXXSommaire du match
170 - 2023-03-251164Chiefs3Admirals1BLSommaire du match
172 - 2023-03-271174Monsters7Admirals2BLSommaire du match
175 - 2023-03-301198Admirals1Seattle6ALSommaire du match
177 - 2023-04-011216Admirals3Oil Kings5ALSommaire du match
178 - 2023-04-021225Admirals4Heat2AWSommaire du match
181 - 2023-04-051242Oil Kings3Admirals2BLSommaire du match
184 - 2023-04-081260Admirals6Jayhawks5AWXSommaire du match
185 - 2023-04-091274Monsters4Admirals3BLSommaire du match
187 - 2023-04-111294Comets4Admirals5BWXXSommaire du match
189 - 2023-04-131310Monarchs4Admirals5BWXSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3520
Assistance79,02427,371
Assistance PCT96.37%66.76%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2595 - 86.50% 80,811$3,313,260$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,395,386$ 2,277,916$ 2,277,916$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
11,989$ 1,395,386$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 11,989$ 0$




Admirals Leaders statistiques (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 (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