Admirals

GP: 51 | W: 36 | L: 11 | OTL: 4 | P: 76
GF: 169 | GA: 102 | PP%: 17.74% | PK%: 86.86%
DG: Stéphane Fournier | Morale : 78 | Moyenne d'Équipe : 59
Prochain matchs #758 vs Rampage
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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
1Chandler StephensonXX100.00685567727367697171706679557477169680
2Peter Holland (A)X100.00685569747568706775626363556464185640
3Vladislav KamenevX100.00795560767869736360616260555050185620
4Jordan SzwarzX100.00625567687669696660626060555050187610
5Marek HrivikX100.00615564717972626150616260555050187600
6Chase Balisy (A)X100.00635565666461726060596060557172186600
7Mike HalmoX100.00605559647568715550555556555050185570
8Greg ChaseX100.00755566617264565550555555556650185560
9Stefan FournierX100.00555556607873645550555555555050170560
10Jaedon Descheneau (R)X100.00655566626662545550555555555050181550
11Sam Anas (R)X100.00605559625859735550555556555050185550
12Travis SanheimX100.00735583906578767825676388557475176740
13Gustav OlofssonX100.00725582738172686825676073555353187660
14John GilmourX100.00755579626381657225626473555353140640
15Nick SeelerX100.00725571627776587225626071555353159640
16Dean KukanX100.00665570667971657225626066555353181630
17Philip Larsen (R)X100.00555555605555755525555555556262171560
18Ben Thomas (R)X100.00555555605555725525555555555353165550
19Emil Johansson (R)X100.00555555605555715525555555555555174550
Rayé
1Danny KristoX100.00565555555657575550555555557170121540
2Linden VeyX100.00555555555555555550555555557168125540
3Jansen Harkins (R)X100.00565555555557565550555555555050119530
4Sam KurkerX100.00565555555555555550555555555050120520
5Andrey PedanX100.00555555605555635525555555555353120540
6Dysin MayoX100.00555556605656605625565656555353120540
7Jacob Middleton (R)X100.00555555605555665525555555555353120540
8Dominik Masin (R)X100.00555555605555715525555555555353120540
9Gus YoungX100.00555555605555595525555555555353119530
MOYENNE D'ÉQUIPE100.0062556264656365604158586055575615958
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
1Ryan Miller100.0085828787858485848383559696128830
2Marek Langhamer99.0057796963696968696564556263177650
Rayé
1Mantas Armalis (R)100.0055717080616162616561555860140620
MOYENNE D'ÉQUIPE99.676677757772717271716955727314870
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)D41103646175206358100307210.00%3995923.4061521721650002221310.00%000000.9600000433
2Vladislav KamenevAdmirals (Nas)LW482023432770011758112338417.86%587718.2737102216201141096162.07%11600000.9822000464
3Peter HollandAdmirals (Nas)C5120224224600621031134010117.70%1191117.8858131611711241962266.30%81600000.9224000331
4Dean KukanAdmirals (Nas)D512313319901077415315483.77%3888017.26055311180221145000.00%000000.7501002212
5Gustav OlofssonAdmirals (Nas)D4311223320480704970273515.71%2998522.9210717481670111226120.00%000000.6700000054
6Jordan SzwarzAdmirals (Nas)RW511518332640103843110356313.64%584216.52145151821013751260.42%4800010.7801101221
7Lukas SedlakNashville PredatorsC/LW2114173122300424488234015.91%446322.06459227431491073271.63%42300011.3412000412
8Brandon ManningNashville PredatorsD17420242033558244814288.33%1544926.432573168011051110.00%000001.0700001212
9Nick SeelerAdmirals (Nas)D304182214360512635162911.43%3257519.2025723870111131100.00%000000.7600000220
10Sonny MilanoNashville PredatorsLW/RW14912219220483472174612.50%535725.5304417690116781157.67%18900001.1801000320
11John GilmourAdmirals (Nas)D3210112113315483271162714.08%5369521.73516391071122178110.00%000000.6001001133
12Marek HrivikAdmirals (Nas)LW51981712435403776236611.84%359411.6620213630002213048.57%3500000.5700100132
13Stefan FournierAdmirals (Nas)RW379817113010262436134125.00%551013.81011075000002275.61%4100000.6700110014
14Chase BalisyAdmirals (Nas)C516101613371524636320519.52%451410.090111170001412163.00%45400000.6201002001
15Emil JohanssonAdmirals (Nas)D4249132240038171351730.77%1852512.51224463000049100.00%000000.4901000101
16Jaedon DescheneauAdmirals (Nas)RW483811173753025428297.14%360212.56101348000031065.52%2900000.3600001011
17Ben ThomasAdmirals (Nas)D3427962203911122716.67%1442912.65011218101138000.00%000000.4200000001
18Philip LarsenAdmirals (Nas)D382681826037171031120.00%2248812.85022232112196100.00%000000.3300000020
19Chandler StephensonAdmirals (Nas)C/LW1044836011333352412.12%220420.4812311440001340070.05%19700000.7800000101
20Greg ChaseAdmirals (Nas)C51257124027251862211.11%52695.29000150000241054.82%22800000.5201000010
21Mike HalmoAdmirals (Nas)LW514263200192138173710.53%54578.98000020000531139.53%4300000.2611000010
22Sam AnasAdmirals (Nas)C51101-16096164136.25%01793.530002210000200053.03%6600000.1111000000
23Gus YoungAdmirals (Nas)D11101426022240425.00%718216.5910115000026100.00%000000.1100000000
24Jansen HarkinsAdmirals (Nas)C3000000000000.00%031.10000010000000100.00%100000.0000000000
25Linden VeyAdmirals (Nas)RW5000100210110.00%0244.9500000000000066.67%300000.0000000000
26Dysin MayoAdmirals (Nas)D4000-140302110.00%1276.900000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne886166297463320833651001794123537489713.44%3251301414.694575120376172181119391934331764.15%268900020.71717318303833
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
2Ryan MillerAdmirals (Nas)2316430.9111.71140006404490100.78614230221
3Marek LanghamerAdmirals (Nas)2315710.8912.28139401534880000.83362326111
Stats d'équipe Total ou en Moyenne84602040.9061.86507041315716620300.826238429674


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
Chandler StephensonAdmirals (Nas)C/LW221994-04-22No190 Lbs5 ft11NoNoNo1Contrat 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
Vladislav KamenevAdmirals (Nas)LW201996-08-12No203 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm925,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3123.32192 Lbs6 ft12.39666,742$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Vladislav KamenevJordan Szwarz40122
2Marek HrivikPeter HollandStefan Fournier30122
3Mike HalmoChase BalisyJaedon Descheneau20122
4Greg Chase10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis SanheimGustav Olofsson40122
2John GilmourNick Seeler30122
3Dean KukanBen Thomas20122
4Emil JohanssonTravis Sanheim10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Vladislav KamenevJordan Szwarz60122
2Marek HrivikPeter HollandStefan Fournier40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis SanheimGustav Olofsson60122
2John GilmourNick Seeler40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Peter Holland60122
2Vladislav KamenevJordan Szwarz40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis SanheimGustav Olofsson60122
2John GilmourNick Seeler40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Travis SanheimGustav Olofsson60122
2Peter Holland40122John GilmourNick Seeler40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Peter Holland60122
2Vladislav KamenevJordan Szwarz40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Travis SanheimGustav Olofsson60122
2John GilmourNick Seeler40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Vladislav KamenevJordan SzwarzTravis SanheimGustav Olofsson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Vladislav KamenevJordan SzwarzTravis SanheimGustav Olofsson
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Sam Anas, Chase Balisy, Mike HalmoSam Anas, Chase BalisyMike Halmo
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dean Kukan, Ben Thomas, Emil JohanssonDean KukanBen Thomas, Emil Johansson
Tirs de Pénalité
, Peter Holland, Vladislav Kamenev, Jordan Szwarz, Chase Balisy
Gardien
#1 : Marek Langhamer, #2 :


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
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
1Bears2110000045-1110000003211010000013-220.500471100615447115241144641338301522392015.00%11372.73%0883152258.02%799148853.70%40970957.69%13849911109345602320
2Griffins6510000022715211000006244400000016511100.833223961026154471115241144641338100358910821419.05%36488.89%0883152258.02%799148853.70%40970957.69%13849911109345602320
3Gulls2110000024-2110000001011010000014-320.50024601615447113341144641338231242331715.88%15286.67%0883152258.02%799148853.70%40970957.69%13849911109345602320
4IceHogs7420100024195421010001613332100000862100.7142445690061544711156411446413381494614312735617.14%581082.76%3883152258.02%799148853.70%40970957.69%13849911109345602320
5Monsters1010000004-41010000004-40000000000000.00000000615447118411446413382582418300.00%12375.00%0883152258.02%799148853.70%40970957.69%13849911109345602320
6Moose66000000358274400000025619220000001028121.0003562970061544711227411446413381153310713917952.94%40587.50%2883152258.02%799148853.70%40970957.69%13849911109345602320
7Penguins201000103301010000023-11000001010120.50034701615447114341144641338341134391200.00%17194.12%0883152258.02%799148853.70%40970957.69%13849911109345602320
8Rampage4100111014952000011033021001000116570.8751421350061544711116411446413388318446929724.14%22195.45%1883152258.02%799148853.70%40970957.69%13849911109345602320
9Reign22000000817110000005051100000031241.0008122001615447118041144641338341120461119.09%90100.00%0883152258.02%799148853.70%40970957.69%13849911109345602320
10Stars63101001201193210000096331001001115690.7502039590261544711132411446413381084311413226623.08%48589.58%2883152258.02%799148853.70%40970957.69%13849911109345602320
Total512911033411691026726158011108252302514302231875037760.7451692964650861544711128741144641338102933182710162484417.74%3504686.86%8883152258.02%799148853.70%40970957.69%13849911109345602320
12Wild530002001813522000000835310002001010080.800183250006154471112441144641338129376410532515.63%29582.76%0883152258.02%799148853.70%40970957.69%13849911109345602320
13Wolves833000201918141300000410-6420000201587100.6251931500161544711164411446413381996212416125416.00%53786.79%0883152258.02%799148853.70%40970957.69%13849911109345602320
_Since Last GM Reset512911033411691026726158011108252302514302231875037760.7451692964650861544711128741144641338102933182710162484417.74%3504686.86%8883152258.02%799148853.70%40970957.69%13849911109345602320
_Vs Conference36197033311177740178601110463791911102221714031540.7501172073240561544711844411446413387682415787021683219.05%2463286.99%6883152258.02%799148853.70%40970957.69%13849911109345602320
_Vs Division12136021302923664501110101006910102019136371.5422947760361544711277411446413382568518624053611.32%77988.31%0883152258.02%799148853.70%40970957.69%13849911109345602320

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5176L316929646512871029331827101608
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
5129113341169102
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2615811108252
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2514322318750
Derniers 10 Matchs
WLOTWOTL SOWSOL
531010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2484417.74%3504686.86%8
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
4114464133861544711
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
883152258.02%799148853.70%40970957.69%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
13849911109345602320


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 - 2019-01-15758Rampage-Admirals-
138 - 2019-01-20795Admirals-Moose-
139 - 2019-01-21806Admirals-Moose-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25819Admirals-Monsters-
145 - 2019-01-27841Admirals-Monsters-
148 - 2019-01-30853Admirals-Stars-
150 - 2019-02-01864Admirals-Rampage-
152 - 2019-02-03885Admirals-Rampage-
154 - 2019-02-05889Stars-Admirals-
157 - 2019-02-08906Wolves-Admirals-
158 - 2019-02-09917Griffins-Admirals-
159 - 2019-02-10928Admirals-Wolves-
162 - 2019-02-13934Monsters-Admirals-
165 - 2019-02-16961Griffins-Admirals-
171 - 2019-02-22989IceHogs-Admirals-
172 - 2019-02-23998Admirals-IceHogs-
176 - 2019-02-271023Admirals-IceHogs-
179 - 2019-03-021049Admirals-Wolves-
180 - 2019-03-031055Admirals-Griffins-
183 - 2019-03-061067Rampage-Admirals-
185 - 2019-03-081079Wolves-Admirals-
186 - 2019-03-091091Wild-Admirals-
189 - 2019-03-121106IceHogs-Admirals-
193 - 2019-03-161131Griffins-Admirals-
194 - 2019-03-171149Admirals-IceHogs-



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
12 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
196,811$ 206,690$ 110,440$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 129,261$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 63 1,581$ 99,603$




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
13512911033411691026726158011108252302514302231875037761692964650861544711128741144641338102933182710162484417.74%3504686.86%8883152258.02%799148853.70%40970957.69%13849911109345602320
Total Saison Régulière512911033411691026726158011108252302514302231875037761692964650861544711128741144641338102933182710162484417.74%3504686.86%8883152258.02%799148853.70%40970957.69%13849911109345602320
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