Admirals

GP: 76 | W: 49 | L: 21 | OTL: 6 | P: 104
GF: 240 | GA: 157 | PP%: 18.34% | PK%: 86.73%
DG: Stéphane Fournier | Morale : 80 | Moyenne d'Équipe : 59
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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 SP
1Peter HollandX100.00685569747568706775626363556464180640
2Jordan SzwarzX100.00625567687669696660626060555050183610
3Marek HrivikX100.00615564717972626150616260555050186600
4Chase Balisy (A)X100.00635565666461726060596060557172183600
5Mike HalmoX100.00605559647568715550555556555050184570
6Greg ChaseX100.00755566617264565550555555556650184560
7Stefan FournierX100.00555556607873645550555555555050178560
8Jaedon Descheneau (R)X100.00655566626662545550555555555050183550
9Sam Anas (R)X100.00605559625859735550555556555050184550
10Linden VeyX100.00555555555555555550555555557168131540
11Jansen Harkins (R)X100.00565555555557565550555555555050126530
12Sam KurkerX100.00565555555555555550555555555050127520
13Travis SanheimX100.00735583906578767825676388557475182740
14Gustav OlofssonX100.00725582738172686825676073555353184660
15John GilmourX100.00755579626381657225626473555353148640
16Dean KukanX100.00665570667971657225626066555353183630
17Emil Johansson (R)X100.00555555605555715525555555555555181550
18Jacob Middleton (R)X100.00555555605555665525555555555353128540
Rayé
1Danny KristoX100.00565555555657575550555555557170120540
2Nick SeelerX100.00725571627776587225626071555353132630
3Philip Larsen (R)X100.00555555605555755525555555556262162560
4Ben Thomas (R)X100.00555555605555725525555555555353155550
5Andrey PedanX100.00555555605555635525555555555353120540
6Dysin MayoX100.00555556605656605625565656555353120540
7Dominik Masin (R)X100.00555555605555715525555555555353120540
8Gus YoungX100.00555555605555595525555555555353119530
MOYENNE D'ÉQUIPE100.0061556263646365603958576055565615758
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
1Marek Langhamer99.0057796963696968696564556263179650
2Mantas Armalis (R)100.0055717080616162616561555860136620
Rayé
1Ryan Miller100.0085828787858485848383559696120820
MOYENNE D'ÉQUIPE99.676677757772717271716955727314570
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Chris Taylor84888185735878CAN465100,000$


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'ÉquipePOS GP 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
1Travis SanheimAdmirals (Nas)D6616536920860111116183551208.74%69154723.451221331392870002346510.00%100000.8900000654
2Peter HollandAdmirals (Nas)C7028275530740951541775513415.82%13135119.3069153620011263003265.76%132600000.8137000533
3Dean KukanAdmirals (Nas)D766434918112101086010232765.88%65134817.7431215682081232237100.00%000000.7301002313
4Jordan SzwarzAdmirals (Nas)RW7620274729711567661584810012.66%9139618.3849132930210152071256.00%15000010.6714101231
5Gustav OlofssonAdmirals (Nas)D681531462088010374107336714.02%50153222.54131326782910111349120.00%000000.6000000056
6John GilmourAdmirals (Nas)D57172643125958861138348112.32%92122321.46101121922271233299110.00%000000.7001001246
7Chase BalisyAdmirals (Nas)C7612203214551549120101348611.88%11101513.3619101212400021163160.70%99500000.6303002123
8Lukas SedlakNashville PredatorsC/LW2114173122300424488234015.91%446322.06459227431491073271.63%42300011.3412000412
9Nick SeelerAdmirals (Nas)D376212716480593253183911.32%3668918.65358341120111150110.00%000000.7800000230
10Stefan FournierAdmirals (Nas)RW6214132793610544478235917.95%793915.1643715195000002272.13%6100000.5700110014
11Marek HrivikAdmirals (Nas)LW761214261562106750112329210.71%4104413.744262818300021214057.97%6900000.5022200232
12Brandon ManningNashville PredatorsD17420242033558244814288.33%1544926.432573168011051110.00%000001.0700001212
13Jaedon DescheneauAdmirals (Nas)RW7310112121575514578155812.82%588812.17101352000032057.14%4900000.4700001221
14Emil JohanssonAdmirals (Nas)D674141824740822421102119.05%3177711.60224463000078100.00%000000.4601000102
15Mike HalmoAdmirals (Nas)LW7661117140055416729698.96%691712.0724681100000831146.38%6900000.3711000020
16Greg ChaseAdmirals (Nas)C7669153420655157164710.53%86168.110114380000592058.23%54100000.4901000020
17Philip LarsenAdmirals (Nas)D5028101934044211151418.18%2261112.23022232112110910100.00%100000.3300000020
18Ben ThomasAdmirals (Nas)D4828101032052161841111.11%1656811.85011218101144000.00%000000.3500000001
19Chandler StephensonNashville PredatorsC/LW1044836011333352412.12%220420.4812311440001340070.05%19700000.7800000101
20Sam AnasAdmirals (Nas)C76314-412027243911247.69%24145.460002270000401052.22%27000000.1911000000
21Jansen HarkinsAdmirals (Nas)C14033100344330.00%1715.09011212000080083.33%1800000.8400000000
22Danny KristoAdmirals (Nas)LW1211216010683412.50%117314.43000020000140041.67%1200000.2300000000
23Linden VeyAdmirals (Nas)RW22112080551061010.00%01456.6000000000001057.14%700000.2800000010
24Gus YoungAdmirals (Nas)D11101426022240425.00%718216.5910115000026100.00%000000.1100000000
25Sam KurkerAdmirals (Nas)RW11000000002020.00%0121.1700004000000025.00%400000.0000000000
26Dysin MayoAdmirals (Nas)D6000-280414110.00%1376.210000000000000.00%000000.0000000000
27Jacob MiddletonAdmirals (Nas)D19000280321030.00%7874.6200000000028000.00%000000.0000000000
28Dominik MasinAdmirals (Nas)D2000020000000.00%021.370000000002000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne1275204383587308110975133511201702509121711.99%4841871314.6873117190623269391019362822361662.65%419300020.63924418334141
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
1Louis DomingueNashville Predators3829900.9121.69227546647250201.0003383342
2Marek LanghamerAdmirals (Nas)37241120.8882.31223002867660100.714143737112
3Ryan MillerAdmirals (Nas)34201040.9121.77206607616970300.83318340431
4Mantas ArmalisAdmirals (Nas)10001.0000.0015000160000.0000029000
Stats d'équipe Total ou en Moyenne110733060.9041.92658841521122040600.8003510969885


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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Andrey PedanAdmirals (Nas)D231993-07-02No214 Lbs6 ft5NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Ben ThomasAdmirals (Nas)D201996-05-28Yes190 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Chase BalisyAdmirals (Nas)C241992-02-02No170 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Danny KristoAdmirals (Nas)LW261990-06-18No195 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No
Dean KukanAdmirals (Nas)D231993-07-08No209 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Dominik MasinAdmirals (Nas)D201996-02-01Yes189 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Dysin MayoAdmirals (Nas)D201996-08-17No194 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Emil JohanssonAdmirals (Nas)D201996-05-06Yes190 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Greg ChaseAdmirals (Nas)C221995-01-01No189 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm894,000$0$0$No
Gus YoungAdmirals (Nas)D251991-07-10No190 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Gustav OlofssonAdmirals (Nas)D221994-12-01No191 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Jacob MiddletonAdmirals (Nas)D211996-01-01Yes200 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Jaedon DescheneauAdmirals (Nas)RW261990-03-04Yes186 Lbs5 ft9NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Jansen HarkinsAdmirals (Nas)C191997-05-23Yes194 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
John GilmourAdmirals (Nas)D231993-05-16No180 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Jordan SzwarzAdmirals (Nas)RW251991-05-14No200 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Linden VeyAdmirals (Nas)RW251991-07-17No189 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No
Mantas ArmalisAdmirals (Nas)G241992-09-05Yes194 Lbs6 ft4NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Marek HrivikAdmirals (Nas)LW251991-08-28No200 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Marek LanghamerAdmirals (Nas)G221994-07-21No184 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No
Mike HalmoAdmirals (Nas)LW251991-05-14No209 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Nick SeelerAdmirals (Nas)D231993-06-02No200 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Peter HollandAdmirals (Nas)C261991-01-13No194 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Philip LarsenAdmirals (Nas)D271989-12-07Yes182 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm450,000$0$0$No
Ryan MillerAdmirals (Nas)G361980-07-16No168 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm8,500,000$0$0$No
Sam AnasAdmirals (Nas)C231993-05-31Yes160 Lbs5 ft8NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Sam KurkerAdmirals (Nas)RW221994-04-08No203 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Stefan FournierAdmirals (Nas)RW241992-04-29No205 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Travis SanheimAdmirals (Nas)D201996-03-29No181 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm900,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2923.48191 Lbs6 ft12.48670,483$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Marek HrivikPeter HollandJordan Szwarz40122
2Mike HalmoChase BalisyStefan Fournier30122
3Peter HollandGreg ChaseJaedon Descheneau20122
4Jordan SzwarzSam AnasLinden Vey10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis SanheimGustav Olofsson40122
2John GilmourDean Kukan30122
3Emil Johansson20122
4Jacob MiddletonTravis Sanheim10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Marek HrivikPeter HollandJordan Szwarz60122
2Mike HalmoChase BalisyStefan Fournier40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis SanheimGustav Olofsson60122
2John GilmourDean Kukan40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Peter HollandJordan Szwarz60122
2Chase BalisyMarek Hrivik40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis SanheimGustav Olofsson60122
2John GilmourDean Kukan40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Peter Holland60122Travis SanheimGustav Olofsson60122
2Jordan Szwarz40122John GilmourDean Kukan40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Peter HollandJordan Szwarz60122
2Chase BalisyMarek Hrivik40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis SanheimGustav Olofsson60122
2John GilmourDean Kukan40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Marek HrivikPeter HollandJordan SzwarzTravis SanheimGustav Olofsson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Marek HrivikPeter HollandJordan SzwarzTravis SanheimGustav Olofsson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jansen Harkins, Sam Kurker, Greg ChaseJansen Harkins, Sam KurkerGreg Chase
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Emil Johansson, Jacob MiddletonEmil Johansson, Jacob Middleton
Tirs de Pénalité
Peter Holland, Jordan Szwarz, Chase Balisy, Marek Hrivik, Mike Halmo
Gardien
#1 : Marek Langhamer, #2 : Mantas Armalis


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
LigueDomicileVisiteur
# 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
1Bears2110000045-1110000003211010000013-220.500471100847769165261267064356301522392015.00%11372.73%01352229258.99%1229222155.34%623106358.61%206514761645521906485
2Griffins1062010103417175120101014955500000020812160.80034619502847769162786126706435617451139190501020.00%59886.44%01352229258.99%1229222155.34%623106358.61%206514761645521906485
3Gulls2110000024-2110000001011010000014-320.50024601847769163361267064356231242331715.88%15286.67%01352229258.99%1229222155.34%623106358.61%206514761645521906485
4IceHogs1292010005028226410100026151165100000241311200.833508513500847769163106126706435625790229235611626.23%981584.69%41352229258.99%1229222155.34%623106358.61%206514761645521906485
5Monsters40300010411-72020000027-52010001024-220.2504590084776916556126706435610030758620210.00%35682.86%01352229258.99%1229222155.34%623106358.61%206514761645521906485
6Moose8700010041103144000000256194300010016412150.93841741150184776916295612670643561494512917129931.03%51688.24%21352229258.99%1229222155.34%623106358.61%206514761645521906485
7Penguins201000103301010000023-11000001010120.50034701847769164361267064356341134391200.00%17194.12%01352229258.99%1229222155.34%623106358.61%206514761645521906485
8Rampage822011112319440100111810-2421010001596100.62523376000847769162146126706435617948108149611219.67%53492.45%11352229258.99%1229222155.34%623106358.61%206514761645521906485
9Reign22000000817110000005051100000031241.0008122001847769168061267064356341120461119.09%90100.00%01352229258.99%1229222155.34%623106358.61%206514761645521906485
10Stars85101001261313431000001266420010011477130.8132650760384776916178612670643561415615116738923.68%60690.00%21352229258.99%1229222155.34%623106358.61%206514761645521906485
Total7639210446224015783381814021211178235382170234112375481040.684240417657010847769161948612670643561571504119915244097518.34%5206986.73%91352229258.99%1229222155.34%623106358.61%206514761645521906485
12Wild6310020020173321000001073310002001010080.667203656008477691614061267064356161468012537616.22%36683.33%01352229258.99%1229222155.34%623106358.61%206514761645521906485
13Wolves1237000202529-461500000917-86220002016124100.4172542670184776916270612670643562898917024453815.09%761284.21%01352229258.99%1229222155.34%623106358.61%206514761645521906485
_Since Last GM Reset7639210446224015783381814021211178235382170234112375481040.684240417657010847769161948612670643561571504119915244097518.34%5206986.73%91352229258.99%1229222155.34%623106358.61%206514761645521906485
_Vs Conference5628150434217812355281111021217964152817402221995940770.6881783114890684776916139061267064356120138087711103006120.33%3825186.65%71352229258.99%1229222155.34%623106358.61%206514761645521906485
_Vs Division1620130314135341869021211517-281440102020173561.750355893038477691638361267064356346112232323811012.35%1001486.00%01352229258.99%1229222155.34%623106358.61%206514761645521906485

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
76104W12404176571948157150411991524010
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7639214462240157
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
381814212111782
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
38217234112375
Derniers 10 Matchs
WLOTWOTL SOWSOL
540010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4097518.34%5206986.73%9
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
6126706435684776916
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
1352229258.99%1229222155.34%623106358.61%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
206514761645521906485


Derniers Match 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
4 - 2018-09-0819Admirals6Stars0WSommaire du Match
7 - 2018-09-1128Admirals7Rampage3WSommaire du Match
11 - 2018-09-1548Bears2Admirals3WSommaire du Match
12 - 2018-09-1661Admirals6Wolves2WSommaire du Match
15 - 2018-09-1968Admirals3Reign1WSommaire du Match
17 - 2018-09-2180Admirals1Gulls4LSommaire du Match
19 - 2018-09-2398Admirals2Wolves1WXXSommaire du Match
21 - 2018-09-25101Rampage1Admirals0LXSommaire du Match
24 - 2018-09-28112Monsters4Admirals0LSommaire du Match
25 - 2018-09-29122Moose2Admirals7WSommaire du Match
28 - 2018-10-02136Moose2Admirals5WSommaire du Match
31 - 2018-10-05149IceHogs3Admirals5WSommaire du Match
32 - 2018-10-06159Admirals3Griffins0WSommaire du Match
36 - 2018-10-10174Wolves3Admirals0LSommaire du Match
38 - 2018-10-12188IceHogs5Admirals2LSommaire du Match
40 - 2018-10-14207Admirals3Wolves2WXXSommaire du Match
43 - 2018-10-17221Admirals3Wild4LXSommaire du Match
45 - 2018-10-19232Admirals3Wild1WSommaire du Match
46 - 2018-10-20242Reign0Admirals5WSommaire du Match
50 - 2018-10-24261Wild2Admirals4WSommaire du Match
52 - 2018-10-26267Admirals2Griffins1WSommaire du Match
53 - 2018-10-27280IceHogs3Admirals6WSommaire du Match
59 - 2018-11-02314Stars0Admirals3WSommaire du Match
60 - 2018-11-03326Admirals4IceHogs3WSommaire du Match
64 - 2018-11-07345Admirals2Stars3LXXSommaire du Match
66 - 2018-11-09357Admirals3Stars2WXSommaire du Match
67 - 2018-11-10371Admirals4Rampage3WXSommaire du Match
70 - 2018-11-13381Griffins0Admirals5WSommaire du Match
73 - 2018-11-16398Stars3Admirals4WSommaire du Match
74 - 2018-11-17406Admirals6Griffins1WSommaire du Match
78 - 2018-11-21431Admirals3IceHogs1WSommaire du Match
81 - 2018-11-24452Wolves3Admirals2LSommaire du Match
85 - 2018-11-28469Wolves0Admirals1WSommaire du Match
88 - 2018-12-01493Admirals4Wild5LXSommaire du Match
92 - 2018-12-05516Admirals1IceHogs2LSommaire du Match
95 - 2018-12-08539Admirals1Penguins0WXXSommaire du Match
96 - 2018-12-09549Admirals1Bears3LSommaire du Match
99 - 2018-12-12555Griffins2Admirals1LSommaire du Match
102 - 2018-12-15584Gulls0Admirals1WSommaire du Match
104 - 2018-12-17592Admirals6Moose1WSommaire du Match
106 - 2018-12-19600Admirals4Moose1WSommaire du Match
109 - 2018-12-22622Admirals5Griffins3WSommaire du Match
110 - 2018-12-23635Admirals4Wolves3WSommaire du Match
112 - 2018-12-25644Rampage2Admirals3WXXSommaire du Match
115 - 2018-12-28662Wild1Admirals4WSommaire du Match
116 - 2018-12-29668Moose1Admirals6WSommaire du Match
122 - 2019-01-04690Moose1Admirals7WSommaire du Match
123 - 2019-01-05706IceHogs2Admirals3WXSommaire du Match
127 - 2019-01-09721Stars3Admirals2LSommaire du Match
129 - 2019-01-11728Penguins3Admirals2LSommaire du Match
130 - 2019-01-12734Wolves4Admirals1LSommaire du Match
133 - 2019-01-15758Rampage3Admirals2LXXSommaire du Match
138 - 2019-01-20795Admirals5Moose0WSommaire du Match
139 - 2019-01-21806Admirals1Moose2LXSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25819Admirals2Monsters1WXXSommaire du Match
145 - 2019-01-27841Admirals0Monsters3LSommaire du Match
148 - 2019-01-30853Admirals3Stars2WSommaire du Match
150 - 2019-02-01864Admirals1Rampage2LSommaire du Match
152 - 2019-02-03885Admirals3Rampage1WSommaire du Match
154 - 2019-02-05889Stars0Admirals3WSommaire du Match
157 - 2019-02-08906Wolves3Admirals2LSommaire du Match
158 - 2019-02-09917Griffins2Admirals1LSommaire du Match
159 - 2019-02-10928Admirals0Wolves2LSommaire du Match
162 - 2019-02-13934Monsters3Admirals2LSommaire du Match
165 - 2019-02-16961Griffins4Admirals5WXSommaire du Match
171 - 2019-02-22989IceHogs1Admirals7WSommaire du Match
172 - 2019-02-23998Admirals5IceHogs4WSommaire du Match
176 - 2019-02-271023Admirals6IceHogs2WSommaire du Match
179 - 2019-03-021049Admirals1Wolves2LSommaire du Match
180 - 2019-03-031055Admirals4Griffins3WSommaire du Match
183 - 2019-03-061067Rampage4Admirals3LSommaire du Match
185 - 2019-03-081079Wolves4Admirals3LSommaire du Match
186 - 2019-03-091091Wild4Admirals2LSommaire du Match
189 - 2019-03-121106IceHogs1Admirals3WSommaire du Match
193 - 2019-03-161131Griffins1Admirals2WXXSommaire du Match
194 - 2019-03-171149Admirals5IceHogs1WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
292,578$ 194,440$ 98,190$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 192,536$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 1,518$ 0$




LigueDomicileVisiteur
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
13763921044622401578338181402121117823538217023411237548104240417657010847769161948612670643561571504119915244097518.34%5206986.73%91352229258.99%1229222155.34%623106358.61%206514761645521906485
Total Saison Régulière763921044622401578338181402121117823538217023411237548104240417657010847769161948612670643561571504119915244097518.34%5206986.73%91352229258.99%1229222155.34%623106358.61%206514761645521906485
Séries
121064000003818205320000020515532000001813512387010804161381254878579321056130191501020.00%57787.72%317327363.37%15230050.67%7814155.32%2491772357111758
121064000003818205320000020515532000001813512387010804161381254878579321056130191501020.00%57787.72%317327363.37%15230050.67%7814155.32%2491772357111758
Total Séries2012800000763640106400000401030106400000362610247614021608322616250817417015864201122603821002020.00%1141487.72%634654663.37%30460050.67%15628255.32%498354470142234117