Connexion

Admirals
GP: 82 | W: 46 | L: 30 | OTL: 6 | P: 98
GF: 290 | GA: 259 | PP%: 20.94% | PK%: 82.68%
DG: Yannick Masse | Morale : 50 | Moyenne d’équipe : 54
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Centre de jeu
Monarchs
36-38-8, 80pts
3
FINAL
8 Admirals
46-30-6, 98pts
Team Stats
L3StreakL1
20-17-4Home Record22-15-4
16-21-4Away Record24-15-2
6-4-0Last 10 Games5-4-1
3.38Goals Per Game3.54
3.62Goals Against Per Game3.16
20.08%Power Play Percentage20.94%
77.65%Penalty Kill Percentage82.68%
Admirals
46-30-6, 98pts
4
FINAL
5 Sharks
57-21-4, 118pts
Team Stats
L1StreakW6
22-15-4Home Record33-7-1
24-15-2Away Record24-14-3
5-4-1Last 10 Games8-1-1
3.54Goals Per Game3.88
3.16Goals Against Per Game2.90
20.94%Power Play Percentage23.35%
82.68%Penalty Kill Percentage79.14%
Meneurs d'équipe
Buts
Xavier Ouellet
10
Passes
Oscar Fantenberg
18
Points
Oscar Fantenberg
25
Plus/Moins
Oscar Fantenberg
3
Victoires
Christopher Gibson
46
Pourcentage d’arrêts
Christopher Gibson
0.918

Statistiques d’équipe
Buts pour
290
3.54 GFG
Tirs pour
3036
37.02 Avg
Pourcentage en avantage numérique
20.9%
49 GF
Début de zone offensive
39.5%
Buts contre
259
3.16 GAA
Tirs contre
3075
37.50 Avg
Pourcentage en désavantage numérique
82.7%
53 GA
Début de la zone défensive
41.7%
Information d’équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,565
Billets de saison300


Information formation

Équipe Pro26
Équipe Mineure20
Limite contact 46 / 50
Espoirs8


Historique d'équipe

Saison actuelle46-30-6 (98PTS)
Historique46-30-8 (0.548%)
Apparitions séries éliminatoires
Historique séries éliminatoires (W-L)-


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
1Nicolas DeslauriersXX100.009399707181598359316059712568680506302911,400,000$
2Jordan WealXXX100.006764747164666764806258655561620506102831,400,000$
3Andy AndreoffXX100.00767481707455556075387469706364050600291650,000$
4Garrett PilonX100.00707069687062616780706063574444050600221742,500$
5Dominic TurgeonX100.00797392637368715771515767545353050590241750,000$
6Matthew PecaXXX100.007063868263606159745756635352520505902711,400,000$
7Trent FredericXX100.00809059657758795956525968255050050590221895,000$
8Patrick RussellXX100.00814599627457526033705561255050050580271925,000$
9Nikita Alexandrov (R)X100.00766699646652506379566765644444050580203830,833$
10Tomas JurcoXX100.00654299777052545726615551256263050570271750,000$
11Joshua Ho-Sang (R)X100.006559927664585859495653655244440505702411,000,000$
12Jack Quinn (R)X100.00716584666560615950625161484444050570193925,000$
13Dillon HeatheringtonX100.00747774658171804625383766375354050600251700,000$
14Joey KeaneX100.00807592616868655828584367374444050590213809,166$
15Axel Andersson (R)X100.00746595646556584925384560434444050550204772,500$
16Benjamin Mirageas (R)X100.00484583616744613025272844295454050470213525,000$
17Linus HultstromX100.00394545455536363945393945423230050410271825,000$
18Lukas BengtssonX100.00394545454836363945393945423230050400261742,500$
Rayé
1Jack Badini (R)XX100.00797394637353554556414462424444050520223805,000$
2Cameron Hillis (R)X100.00726296636258624556384658444444050510204838,333$
3Jan Mysak (R)XX100.00756599636557604556384760454444050510183850,833$
4D'Artagnan JolyX100.00494783666956694761513547385454050500213650,000$
5Malte StromwallXX100.00394545455436363945393945423230050400261742,500$
6James Greenway (R)X100.00374343436835353743373743403230050400221700,000$
MOYENNE D’ÉQUIPE100.0067627963675559525149495943484805054
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 SP
1Christopher Gibson100.0061546882656356656261335045050610
2Spencer Martin100.0054537473545651595353304444050550
Rayé
MOYENNE D’ÉQUIPE100.005854717860605462585732474505058
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)C82346195333001512693319123210.27%24176921.58911205718901172657260.49%253100001.07360005411
2Jordan WealAdmirals (Ana)C/LW/RW8134407421340731452868422911.89%36150218.551010204016110192507255.47%50300100.9925000553
3Matthew PecaAdmirals (Ana)C/LW/RW822351742216072175295722287.80%13150918.4121113372041014942356.48%21600100.9845000122
4Joey KeaneAdmirals (Ana)D8264854108420150939239896.52%127181722.1611314391860000242100.00%000000.5900211025
5Trent FredericAdmirals (Ana)C/LW74242650-28020223152249711879.64%14124116.7747114314100051135351.26%103400200.8102103143
6Tomas JurcoAdmirals (Ana)LW/RW82163248-56023105214601307.48%5126115.395510271310003541231.02%21600010.7600000042
7Patrick RussellAdmirals (Ana)LW/RW82173148214559795185701319.19%12109613.370661572000192048.94%9400000.8800000621
8Dominic TurgeonAdmirals (Ana)C821730474420128165206671808.25%29127015.49358178900011192154.83%136600000.7402000320
9Joshua Ho-SangAdmirals (Ana)RW8217294624037136210711518.10%12102912.550001110001304044.44%9900000.8900000022
10Nikita AlexandrovAdmirals (Ana)C822219415140661232026415110.89%2083010.1321357000001158.05%85100000.9900000242
11Jack QuinnAdmirals (Ana)RW82152439-920055100167391188.98%899912.18066748000003128.36%6700000.7800000035
12Xavier OuelletAnaheimD66101525-762101213287326311.49%103136420.67235181190000165100.00%000100.3700020021
13Oscar FantenbergAnaheimD3571825332074497231619.72%6382123.472573090000196200.00%000100.6100000204
14Axel AnderssonAdmirals (Ana)D8281119176751423571294811.27%118156119.04134191300000184120.00%000000.2400000100
15Dillon HeatheringtonAdmirals (Ana)D486111774151162745154213.33%93116624.30224181060001136110.00%000000.2900100031
16Cameron HillisAdmirals (Ana)C375914124061233162816.13%4051914.04000190000240142.86%2800000.5400000001
17Andy AndreoffAdmirals (Ana)C/LW12581377514145419379.26%321718.1011211220002261054.79%7300001.2011010000
18Nicolas DeslauriersAdmirals (Ana)LW/RW127613180443657163812.28%625721.483258230001350034.92%6300001.0101000310
19Jack BadiniAdmirals (Ana)C/LW734812-231567467317635.48%1780611.051015570001590046.67%12000000.3000001000
20Jan MysakAdmirals (Ana)C/LW53257-322029205422233.70%54438.3600004000010046.15%2600000.3200000001
21Benjamin MirageasAdmirals (Ana)D471676200277641016.67%3182217.49000049000076000.00%000000.1700000000
22Linus HultstromAdmirals (Ana)D19044-21203221120.00%1932717.25000017000027000.00%000000.2400000000
23Lukas BengtssonAdmirals (Ana)D321231114038183612.50%1347514.850001700009000.00%000000.1300000000
24James GreenwayAdmirals (Ana)D120225201720220.00%1219516.3200005000018000.00%000000.2000000000
25D'Artagnan JolyAdmirals (Ana)RW2000000001000.00%000.090000000000000.00%000000.0000000000
Statistiques d’équipe totales ou en moyenne14232814967771467177518571852299792522499.38%8232330516.3848911393991888213372045411955.21%728700610.671022445294044
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
1Christopher GibsonAdmirals (Ana)82463050.9183.0848764425030310130.700208201821
2Spencer MartinAdmirals (Ana)30010.9022.5594004410100.0000082000
Statistiques d’équipe totales ou en moyenne85463060.9173.0749704425430720230.7002082821821


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 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
Andy AndreoffAdmirals (Ana)C/LW291991-05-17No203 Lbs6 ft1NoNoNo1Pro & Farm650,000$650,000$0$NoLien
Axel AnderssonAdmirals (Ana)D202000-02-10Yes179 Lbs6 ft0NoNoNo4Pro & Farm772,500$77,250$0$No772,500$772,500$772,500$Lien
Benjamin MirageasAdmirals (Ana)D211999-05-08Yes181 Lbs6 ft1NoNoNo3Pro & Farm525,000$52,500$0$No525,000$525,000$Lien
Cameron HillisAdmirals (Ana)C202000-06-24Yes171 Lbs5 ft10NoNoNo4Pro & Farm838,333$83,833$0$No838,333$838,333$838,333$Lien
Christopher GibsonAdmirals (Ana)G271992-12-27No217 Lbs6 ft2NoNoNo1Pro & Farm800,000$80,000$0$NoLien
D'Artagnan JolyAdmirals (Ana)RW211999-04-07No181 Lbs6 ft3NoNoNo3Pro & Farm650,000$65,000$0$No650,000$650,000$Lien
Dillon HeatheringtonAdmirals (Ana)D251995-05-08No215 Lbs6 ft4NoNoNo1Pro & Farm700,000$70,000$0$NoLien
Dominic TurgeonAdmirals (Ana)C241996-02-25No199 Lbs6 ft2NoNoNo1Pro & Farm750,000$75,000$0$NoLien
Garrett PilonAdmirals (Ana)C221998-04-13No190 Lbs6 ft0NoNoNo1Pro & Farm742,500$74,250$0$NoLien
Jack BadiniAdmirals (Ana)C/LW221998-01-19Yes203 Lbs6 ft0NoNoNo3Pro & Farm805,000$80,500$0$No805,000$805,000$Lien
Jack QuinnAdmirals (Ana)RW192001-09-19Yes176 Lbs6 ft0NoNoNo3Pro & Farm925,000$92,500$0$No925,000$925,000$Lien
James GreenwayAdmirals (Ana)D221998-04-27Yes205 Lbs6 ft4NoNoNo1Pro & Farm700,000$70,000$0$NoLien
Jan MysakAdmirals (Ana)C/LW182002-06-24Yes176 Lbs6 ft0NoNoNo3Pro & Farm850,833$85,083$0$No850,833$850,833$Lien
Joey KeaneAdmirals (Ana)D211999-07-02No187 Lbs6 ft0NoNoNo3Pro & Farm809,166$80,917$0$No809,166$809,166$Lien
Jordan WealAdmirals (Ana)C/LW/RW281992-04-15No181 Lbs5 ft9NoNoNo3Pro & Farm1,400,000$140,000$0$No1,400,000$1,400,000$Lien
Joshua Ho-SangAdmirals (Ana)RW241996-01-22Yes173 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$100,000$0$NoLien
Linus HultstromAdmirals (Ana)D271992-12-09No181 Lbs5 ft10NoNoNo1Pro & Farm825,000$82,500$0$NoLien
Lukas BengtssonAdmirals (Ana)D261994-04-14No168 Lbs5 ft9NoNoNo1Pro & Farm742,500$74,250$0$NoLien
Malte StromwallAdmirals (Ana)LW/RW261994-08-24No180 Lbs5 ft10NoNoNo1Pro & Farm742,500$74,250$0$NoLien
Matthew PecaAdmirals (Ana)C/LW/RW271993-04-27No182 Lbs5 ft8NoNoNo1Pro & Farm1,400,000$140,000$0$NoLien
Nicolas DeslauriersAdmirals (Ana)LW/RW291991-02-22No215 Lbs6 ft1NoNoNo1Pro & Farm1,400,000$1,400,000$0$NoLien
Nikita AlexandrovAdmirals (Ana)C202000-09-16Yes185 Lbs5 ft10NoNoNo3Pro & Farm830,833$83,083$0$No830,833$830,833$Lien
Patrick RussellAdmirals (Ana)LW/RW271993-01-04No203 Lbs6 ft1NoNoNo1Pro & Farm925,000$92,500$0$NoLien
Spencer MartinAdmirals (Ana)G251995-06-08No191 Lbs6 ft1NoNoNo3Pro & Farm750,000$75,000$0$No750,000$750,000$Lien
Tomas JurcoAdmirals (Ana)LW/RW271992-12-27No188 Lbs6 ft2NoNoNo1Pro & Farm750,000$75,000$0$NoLien
Trent FredericAdmirals (Ana)C/LW221998-02-11No203 Lbs6 ft2NoNoNo1Pro & Farm895,000$89,500$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2623.81190 Lbs6 ft01.92853,045$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nicolas DeslauriersJordan WealJack Quinn40122
2Andy AndreoffGarrett PilonMatthew Peca30122
3Trent FredericTomas JurcoJoshua Ho-Sang20122
4Patrick RussellDominic TurgeonNikita Alexandrov10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dillon HeatheringtonJoey Keane40122
2Axel AnderssonBenjamin Mirageas30122
3Linus HultstromLukas Bengtsson20122
4Dillon HeatheringtonJoey Keane10122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nicolas DeslauriersJordan WealJack Quinn60122
2Andy AndreoffGarrett PilonMatthew Peca40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dillon HeatheringtonJoey Keane60122
2Axel AnderssonBenjamin Mirageas40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jordan WealNicolas Deslauriers60122
2Garrett PilonAndy Andreoff40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dillon HeatheringtonJoey Keane60122
2Axel AnderssonBenjamin Mirageas40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jordan Weal60122Dillon HeatheringtonJoey Keane60122
2Garrett Pilon40122Axel AnderssonBenjamin Mirageas40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jordan WealNicolas Deslauriers60122
2Garrett PilonAndy Andreoff40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dillon HeatheringtonJoey Keane60122
2Axel AnderssonBenjamin Mirageas40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nicolas DeslauriersJordan WealJack QuinnDillon HeatheringtonJoey Keane
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nicolas DeslauriersJordan WealJack QuinnDillon HeatheringtonJoey Keane
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Matthew Peca, Trent Frederic, Dominic TurgeonMatthew Peca, Trent FredericMatthew Peca
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Benjamin Mirageas, Linus Hultstrom, Lukas BengtssonBenjamin MirageasBenjamin Mirageas, Linus Hultstrom
Tirs de pénalité
Nicolas Deslauriers, Jordan Weal, Andy Andreoff, Garrett Pilon, Matthew Peca
Gardien
#1 : Christopher Gibson, #2 : Spencer Martin


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 Hawks311001001013-31000010045-12110000068-230.500101929001138284169399997010177213141527711436.36%14192.86%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
2Bears2010010046-21000010023-11010000023-110.2504711001138284165699997010177268181458700.00%7185.71%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
3Bruins20200000410-61010000046-21010000004-400.00048121011382841664999970101772912810503133.33%4250.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
4Cabaret Lady Mary Ann220000001358110000008531100000050541.00013233601113828416100999970101772802113449333.33%4250.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
5Caroline220000001055110000003121100000074341.0001017270011382841678999970101772693220484250.00%90100.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
6Chiefs30300000310-71010000003-32020000037-400.0003580011382841670999970101772103273362800.00%12191.67%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
7Chill32100000752110000003032110000045-140.6677132001113828416809999701017729125176411218.18%60100.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
8Comets4020101017170201000108802010100099040.5001730470011382841612199997010177216837301238112.50%15566.67%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
9Cougars2010000148-41010000036-31000000112-110.250481200113828416589999701017725923144811218.18%7185.71%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
10Crunch20001010862100010004311000001043141.000811190011382841610599997010177265178589222.22%4250.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
11Heat412001001316-320200000610-42100010076130.3751322350011382841615099997010177214741301031119.09%15566.67%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
12Jayhawks412010001116-52100100086220200000310-740.5001117280011382841615799997010177216528551098112.50%18477.78%21595291954.64%1700308555.11%775138755.88%1975135719356091067531
13Las Vegas421000011512320100001710-32200000082650.6251527420111382841617199997010177213050391001200.00%15193.33%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
14Manchots211000009811010000034-11100000064220.500916250011382841682999970101772782122443133.33%10280.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
15Marlies2010100045-1100010003211010000013-220.5004711001138284165799997010177260221234500.00%5180.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
16Minnesota311000101376211000009451000001043140.667131932001138284161379999701017721153020766350.00%80100.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
17Monarchs54000010271512330000001991021000010862101.00027487500113828416226999970101772143354510719526.32%20670.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
18Monsters220000001046110000007341100000031241.0001020300011382841668999970101772991922473133.33%11281.82%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
19Monsters30201000812-4100010005412020000038-520.33381321001138284169799997010177211537325411218.18%14285.71%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
20Oceanics320001001192210001007701100000042250.833111829001138284161149999701017721363220628225.00%9188.89%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
21Oil Kings4220000011110211000003302110000088040.5001119301011382841614199997010177213441278913323.08%10190.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
22Phantoms2010100034-11010000024-21000100010120.5003690111382841682999970101772982512428112.50%6183.33%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
23Rocket211000007701010000046-21100000031220.50071219101138284166899997010177298253156300.00%11281.82%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
24Senators22000000523110000002111100000031241.00058130011382841684999970101772602529348112.50%80100.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
25Sharks404000001318-52020000069-32020000079-200.0001326390011382841611399997010177216438459710330.00%19478.95%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
26Sound Tigers2110000067-11010000025-31100000042220.500611170011382841664999970101772792927617228.57%11281.82%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
27Spiders22000000826110000006151100000021141.000814220011382841673999970101772692018569222.22%80100.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
28Stars3200001012752200000010641000001021161.000122032001138284161159999701017721104220755240.00%90100.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
29Thunder220000001174110000005321100000064241.000112031001138284161279999701017727619184811100.00%9277.78%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
30Wolf Pack220000001358110000007251100000063341.0001322350011382841685999970101772741318463133.33%8275.00%01595291954.64%1700308555.11%775138755.88%1975135719356091067531
Total823530064522902593141171504311160139214118150214113012010980.598290506796341138284163036999970101772307586175319722344920.94%3065382.68%21595291954.64%1700308555.11%775138755.88%1975135719356091067531
_Since Last GM Reset823530064522902593141171504311160139214118150214113012010980.598290506796341138284163036999970101772307586175319722344920.94%3065382.68%21595291954.64%1700308555.11%775138755.88%1975135719356091067531
_Vs Conference37201202210135107281910601200785919181060101057489480.64913524437912113828416137599997010177213863693298501052321.90%1412681.56%01595291954.64%1700308555.11%775138755.88%1975135719356091067531

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8298L129050679630363075861753197234
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8235306452290259
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4117154311160139
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4118152141130120
Derniers 10 matchs
WLOTWOTL SOWSOL
540100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2344920.94%3065382.68%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
999970101772113828416
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
1595291954.64%1700308555.11%775138755.88%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1975135719356091067531


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
2 - 2021-10-1312Jayhawks1Admirals2WSommaire du match
4 - 2021-10-1528Sharks5Admirals3LSommaire du match
7 - 2021-10-1840Admirals1Cougars2LXXSommaire du match
9 - 2021-10-2050Admirals6Manchots4WSommaire du match
10 - 2021-10-2159Admirals3Monsters1WSommaire du match
13 - 2021-10-2478Admirals0Bruins4LSommaire du match
15 - 2021-10-2696Crunch3Admirals4WXSommaire du match
17 - 2021-10-28112Caroline1Admirals3WSommaire du match
19 - 2021-10-30128Heat5Admirals4LSommaire du match
21 - 2021-11-01138Admirals2Chill4LSommaire du match
23 - 2021-11-03152Admirals2Stars1WXXSommaire du match
25 - 2021-11-05168Admirals1Monsters2LSommaire du match
26 - 2021-11-06176Admirals4Las Vegas0WSommaire du match
28 - 2021-11-08187Oceanics5Admirals4LXSommaire du match
31 - 2021-11-11202Comets5Admirals4LSommaire du match
33 - 2021-11-13219Baby Hawks5Admirals4LXSommaire du match
35 - 2021-11-15233Minnesota3Admirals2LSommaire du match
40 - 2021-11-20269Oil Kings1Admirals2WSommaire du match
42 - 2021-11-22278Cougars6Admirals3LSommaire du match
44 - 2021-11-24292Sharks4Admirals3LSommaire du match
46 - 2021-11-26309Admirals1Chiefs2LSommaire du match
48 - 2021-11-28316Admirals2Bears3LSommaire du match
51 - 2021-12-01334Admirals5Cabaret Lady Mary Ann0WSommaire du match
53 - 2021-12-03355Admirals6Thunder4WSommaire du match
55 - 2021-12-05372Sound Tigers5Admirals2LSommaire du match
57 - 2021-12-07386Admirals2Jayhawks5LSommaire du match
59 - 2021-12-09392Oceanics2Admirals3WSommaire du match
62 - 2021-12-12423Monarchs1Admirals3WSommaire du match
66 - 2021-12-16451Bears3Admirals2LXSommaire du match
68 - 2021-12-18463Admirals4Oceanics2WSommaire du match
70 - 2021-12-20476Admirals4Minnesota3WXXSommaire du match
72 - 2021-12-22497Monarchs5Admirals8WSommaire du match
74 - 2021-12-24503Wolf Pack2Admirals7WSommaire du match
77 - 2021-12-27528Admirals1Phantoms0WXSommaire du match
78 - 2021-12-28535Admirals2Spiders1WSommaire du match
81 - 2021-12-31553Admirals4Sound Tigers2WSommaire du match
82 - 2022-01-01565Admirals6Wolf Pack3WSommaire du match
87 - 2022-01-06591Las Vegas5Admirals4LXXSommaire du match
89 - 2022-01-08610Phantoms4Admirals2LSommaire du match
91 - 2022-01-10615Admirals4Las Vegas2WSommaire du match
93 - 2022-01-12636Admirals1Jayhawks5LSommaire du match
96 - 2022-01-15658Chill0Admirals3WSommaire du match
98 - 2022-01-17674Monsters3Admirals7WSommaire du match
100 - 2022-01-19687Stars3Admirals5WSommaire du match
102 - 2022-01-21699Admirals1Baby Hawks5LSommaire du match
104 - 2022-01-23713Admirals2Chiefs5LSommaire du match
107 - 2022-01-26735Admirals2Chill1WSommaire du match
108 - 2022-01-27741Admirals7Caroline4WSommaire du match
118 - 2022-02-06773Admirals3Sharks4LSommaire du match
120 - 2022-02-08778Jayhawks5Admirals6WXSommaire du match
122 - 2022-02-10791Thunder3Admirals5WSommaire du match
123 - 2022-02-11804Admirals5Monarchs4WXXSommaire du match
126 - 2022-02-14819Admirals3Senators1WSommaire du match
128 - 2022-02-16828Admirals3Rocket1WSommaire du match
129 - 2022-02-17839Admirals1Marlies3LSommaire du match
131 - 2022-02-19856Admirals4Crunch3WXXSommaire du match
133 - 2022-02-21876Chiefs3Admirals0LSommaire du match
135 - 2022-02-23890Heat5Admirals2LSommaire du match
138 - 2022-02-26909Admirals4Comets5LSommaire du match
139 - 2022-02-27916Admirals3Heat1WSommaire du match
141 - 2022-03-01930Cabaret Lady Mary Ann5Admirals8WSommaire du match
143 - 2022-03-03947Monsters4Admirals5WXSommaire du match
145 - 2022-03-05965Las Vegas5Admirals3LSommaire du match
147 - 2022-03-07980Oil Kings2Admirals1LSommaire du match
150 - 2022-03-10998Manchots4Admirals3LSommaire du match
152 - 2022-03-121015Spiders1Admirals6WSommaire du match
154 - 2022-03-141025Admirals5Baby Hawks3WSommaire du match
155 - 2022-03-151031Admirals2Monsters6LSommaire du match
157 - 2022-03-171048Marlies2Admirals3WXSommaire du match
159 - 2022-03-191063Minnesota1Admirals7WSommaire du match
161 - 2022-03-211078Senators1Admirals2WSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
165 - 2022-03-251099Admirals3Monarchs2WSommaire du match
166 - 2022-03-261112Rocket6Admirals4LSommaire du match
169 - 2022-03-291136Bruins6Admirals4LSommaire du match
171 - 2022-03-311151Comets3Admirals4WXXSommaire du match
174 - 2022-04-031174Admirals5Oil Kings3WSommaire du match
176 - 2022-04-051187Admirals4Heat5LXSommaire du match
179 - 2022-04-081215Admirals5Comets4WXSommaire du match
180 - 2022-04-091221Admirals3Oil Kings5LSommaire du match
183 - 2022-04-121241Stars3Admirals5WSommaire du match
185 - 2022-04-141256Monarchs3Admirals8WSommaire du match
186 - 2022-04-151271Admirals4Sharks5LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3520
Assistance78,05127,099
Assistance PCT95.18%66.10%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2565 - 85.49% 79,848$3,273,765$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,606,055$ 4,062,916$ 4,062,916$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
21,727$ 2,606,055$ 26 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 21,727$ 0$




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