Admirals

GP: 4 | W: 4 | L: 0 | OTL: 0 | P: 8
GF: 22 | GA: 7 | PP%: 29.17% | PK%: 93.33%
DG: Stéphane Fournier | Morale : 55 | Moyenne d'Équipe : N/A
Prochain matchs #68 vs Reign
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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
1Phillip Di GiuseppeXX100.0079557881757169735067646755656215300
2Evgeny Svechnikov (R) (A)XX100.0073557487777069725062636255717215600
3Greg ChaseX100.0075556661726456555055555555665015600
4Jaedon Descheneau (R)X100.0065556662666254555055555555505015600
5Peter HollandX100.0068556974756870677562636355646415600
6Sam Anas (R)X100.0060555962585973555055555655505015600
7Jordan SzwarzX100.0062556768766969666062606055505015600
8Vladislav KamenevX100.0079556076786973636061626055505015600
9Lukas SedlakXX100.0080557776756870698360617355515115600
10Marek HrivikX100.0061556471797262615061626055505015600
11Mike HalmoX100.0060555964756871555055555655505015600
12Chase Balisy (A)X100.0063556566646172606059606055717215600
13Dean KukanX100.0066557066797165722562606655535315600
14Gustav OlofssonX100.0072558273817268682567607355535315600
15Philip Larsen (R)X100.0055555560555575552555555555626215600
16Travis SanheimX100.0073558390657876782567638855747515000
17Ben Thomas (R)X100.0055555560555572552555555555535315600
18Emil Johansson (R)X100.0055555560555571552555555555555515600
19Gus YoungX100.0055555560555559552555555555535315600
Rayé
1Danny KristoX100.0056555555565757555055555555717014600
2Jansen Harkins (R)X100.0056555555555756555055555555505014600
3Sam KurkerX100.0056555555555555555055555555505014600
4Linden VeyX100.0055555555555555555055555555716814600
5Andrey PedanX100.0055555560555563552555555555535314600
6Dysin MayoX100.0055555660565660562556565655535314600
7Jacob Middleton (R)X100.0055555560555566552555555555535314600
8Dominik Masin (R)X100.0055555560555571552555555555535314600
MOYENNE D'ÉQUIPE100.006355636665626660435858605557561530
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 Langhamer100.005779696369696869656455626315600
2Mantas Armalis (R)100.005571708061616261656155586015600
Rayé
MOYENNE D'ÉQUIPE100.00567570726565656565635560621560
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
1Lukas SedlakAdmirals (Nas)C/LW4448520107143328.57%18822.022135181122221068.00%7500011.8200000200
2Vladislav KamenevAdmirals (Nas)LW434732094152720.00%07117.791233180110100075.00%400001.9700000110
3Peter HollandAdmirals (Nas)C4426300291251233.33%07117.932023180110111177.38%8400001.6700000100
4Evgeny SvechnikovAdmirals (Nas)LW/RW4235420713116718.18%08922.401011180111230060.87%4600001.1200000001
5Ben ThomasAdmirals (Nas)D414556030112100.00%05814.580110210114000.00%000001.7200000000
6Dean KukanAdmirals (Nas)D4044160838040.00%48922.41011417000018000.00%000000.8900000000
7Philip LarsenAdmirals (Nas)D41345409122250.00%34912.3502218112117100.00%000001.6200000020
8Jordan SzwarzAdmirals (Nas)RW421312032102220.00%14611.74000080000000100.00%100001.2800000000
9Emil JohanssonAdmirals (Nas)D4033680541030.00%37418.6901111600007000.00%000000.8000000000
10Chandler StephensonNashville PredatorsC/LW21232203782412.50%02914.99011590000000100.00%300002.0000000001
11Chase BalisyAdmirals (Nas)C41231203442425.00%14812.0300000000080074.36%3900001.2500000000
12Phillip Di GiuseppeAdmirals (Nas)LW/RW4022120365590.00%04310.7700000000000080.00%500000.9300000000
13Greg ChaseAdmirals (Nas)C41121005622550.00%0297.3700000000001079.31%2900001.3600000010
14Gustav OlofssonAdmirals (Nas)D4022-260876340.00%49323.48022518000019000.00%000000.4300000000
15Marek HrivikAdmirals (Nas)LW41121201760316.67%1358.85000000000400100.00%200001.1300000001
16Travis SanheimAdmirals (Nas)D21120601442525.00%24522.551121900016000.00%000000.8900000000
17Jaedon DescheneauAdmirals (Nas)RW4011120442130.00%05914.850001180000000100.00%200000.3400000001
18Mike HalmoAdmirals (Nas)LW4011100135420.00%0297.37000000000000100.00%100000.6800000000
19Sam AnasAdmirals (Nas)C4000000110000.00%0246.1300000000030066.67%600000.0000000000
20Gus YoungAdmirals (Nas)D4000580602010.00%06416.0900001000011000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne76224163446209292118428218.64%20114215.03712193018435861704172.73%29700011.1000000444
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
1Marek LanghamerAdmirals (Nas)44000.8971.75240017680000.000040000
Stats d'équipe Total ou en Moyenne44000.8971.75240017680000.000040000


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 Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 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$0$No300,000$300,000$
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$0$No500,000$500,000$
Dean KukanAdmirals (Nas)D231993-07-08No209 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Dominik MasinAdmirals (Nas)D201996-02-01Yes189 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Dysin MayoAdmirals (Nas)D201996-08-17No194 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Emil JohanssonAdmirals (Nas)D201996-05-06Yes190 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Evgeny SvechnikovAdmirals (Nas)LW/RW201996-10-31Yes212 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm900,000$0$0$No900,000$900,000$
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$0$No300,000$300,000$300,000$
Jacob MiddletonAdmirals (Nas)D211996-01-01Yes200 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Jaedon DescheneauAdmirals (Nas)RW261990-03-04Yes186 Lbs5 ft9NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Jansen HarkinsAdmirals (Nas)C191997-05-23Yes194 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
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$0$No500,000$500,000$
Lukas SedlakAdmirals (Nas)C/LW231993-02-25No198 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Mantas ArmalisAdmirals (Nas)G241992-09-05Yes194 Lbs6 ft4NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Marek HrivikAdmirals (Nas)LW251991-08-28No200 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Marek LanghamerAdmirals (Nas)G221994-07-21No184 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Mike HalmoAdmirals (Nas)LW251991-05-14No209 Lbs5 ft10NoNoNo1Avec 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
Phillip Di GiuseppeAdmirals (Nas)LW/RW231993-10-09No200 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Sam AnasAdmirals (Nas)C231993-05-31Yes160 Lbs5 ft8NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Sam KurkerAdmirals (Nas)RW221994-04-08No203 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Travis SanheimAdmirals (Nas)D201996-03-29No181 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm900,000$0$0$No900,000$900,000$
Vladislav KamenevAdmirals (Nas)LW201996-08-12No203 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm925,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2922.79193 Lbs6 ft12.48429,966$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Phillip Di GiuseppeLukas SedlakEvgeny Svechnikov35112
2Vladislav KamenevPeter HollandJaedon Descheneau30122
3Sam AnasChase BalisyJordan Szwarz20122
4Mike HalmoGreg ChaseMarek Hrivik15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Gustav OlofssonTravis Sanheim40122
2Dean KukanEmil Johansson35122
3Ben ThomasGus Young25122
4Gus YoungGustav Olofsson0122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Evgeny SvechnikovLukas SedlakJordan Szwarz60005
2Vladislav KamenevPeter HollandJaedon Descheneau40005
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Gustav OlofssonTravis Sanheim60113
2Dean KukanEmil Johansson40113
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Evgeny SvechnikovLukas Sedlak60131
2Peter HollandVladislav Kamenev40131
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Gustav OlofssonTravis Sanheim60131
2Philip LarsenDean Kukan40131
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Evgeny Svechnikov60131Gustav OlofssonTravis Sanheim60140
2Lukas Sedlak40131Philip LarsenDean Kukan40140
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Evgeny SvechnikovLukas Sedlak60113
2Peter HollandVladislav Kamenev40113
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Gustav OlofssonTravis Sanheim60122
2Dean KukanEmil Johansson40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Phillip Di GiuseppeLukas SedlakEvgeny SvechnikovGustav OlofssonTravis Sanheim
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Phillip Di GiuseppeLukas SedlakEvgeny SvechnikovGustav OlofssonTravis Sanheim
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Sam Anas, Marek Hrivik, Chase BalisySam Anas, Marek HrivikChase Balisy
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Travis Sanheim, Gustav Olofsson, Gus YoungBen ThomasGustav Olofsson, Gus Young
Tirs de Pénalité
Evgeny Svechnikov, Lukas Sedlak, Peter Holland, Vladislav Kamenev, Marek Hrivik
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
1Bears11000000321110000003210000000000021.00035800958023403741013710218112.50%5260.00%08912770.08%8110577.14%466570.77%1219070234728
2Rampage11000000734000000000001100000073421.0007121900958038403741025312255480.00%60100.00%18912770.08%8110577.14%466570.77%1219070234728
3Stars11000000606000000000001100000060621.0006121801958026403741011322237114.29%100100.00%28912770.08%8110577.14%466570.77%1219070234728
Total440000002271511000000321330000001951481.00022416301958011840374106820629224729.17%30293.33%38912770.08%8110577.14%466570.77%1219070234728
5Wolves11000000624000000000001100000062421.0006121800958031403741019718234125.00%90100.00%08912770.08%8110577.14%466570.77%1219070234728
_Since Last GM Reset440000002271511000000321330000001951481.00022416301958011840374106820629224729.17%30293.33%38912770.08%8110577.14%466570.77%1219070234728
_Vs Conference330000001951400000000000330000001951461.0001936550195809540374105513527116637.50%250100.00%38912770.08%8110577.14%466570.77%1219070234728
_Vs Division12000000624000000000001200000062442.0006121800958031403741019718234125.00%90100.00%08912770.08%8110577.14%466570.77%1219070234728

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
48W42241631186820629201
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4400000227
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
110000032
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3300000195
Derniers 10 Matchs
WLOTWOTL SOWSOL
400000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
24729.17%30293.33%3
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
40374109580
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
8912770.08%8110577.14%466570.77%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1219070234728


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 - 2018-09-1968Admirals-Reign-
17 - 2018-09-2180Admirals-Gulls-
19 - 2018-09-2398Admirals-Wolves-
21 - 2018-09-25101Rampage-Admirals-
24 - 2018-09-28112Monsters-Admirals-
25 - 2018-09-29122Moose-Admirals-
28 - 2018-10-02136Moose-Admirals-
31 - 2018-10-05149IceHogs-Admirals-
32 - 2018-10-06159Admirals-Griffins-
36 - 2018-10-10174Wolves-Admirals-
38 - 2018-10-12188IceHogs-Admirals-
40 - 2018-10-14207Admirals-Wolves-
43 - 2018-10-17221Admirals-Wild-
45 - 2018-10-19232Admirals-Wild-
46 - 2018-10-20242Reign-Admirals-
50 - 2018-10-24261Wild-Admirals-
52 - 2018-10-26267Admirals-Griffins-
53 - 2018-10-27280IceHogs-Admirals-
59 - 2018-11-02314Stars-Admirals-
60 - 2018-11-03326Admirals-IceHogs-
64 - 2018-11-07345Admirals-Stars-
66 - 2018-11-09357Admirals-Stars-
67 - 2018-11-10371Admirals-Rampage-
70 - 2018-11-13381Griffins-Admirals-
73 - 2018-11-16398Stars-Admirals-
74 - 2018-11-17406Admirals-Griffins-
78 - 2018-11-21431Admirals-IceHogs-
81 - 2018-11-24452Wolves-Admirals-
85 - 2018-11-28469Wolves-Admirals-
88 - 2018-12-01493Admirals-Wild-
92 - 2018-12-05516Admirals-IceHogs-
95 - 2018-12-08539Admirals-Penguins-
96 - 2018-12-09549Admirals-Bears-
99 - 2018-12-12555Griffins-Admirals-
102 - 2018-12-15584Gulls-Admirals-
104 - 2018-12-17592Admirals-Moose-
106 - 2018-12-19600Admirals-Moose-
109 - 2018-12-22622Admirals-Griffins-
110 - 2018-12-23635Admirals-Wolves-
112 - 2018-12-25644Rampage-Admirals-
115 - 2018-12-28662Wild-Admirals-
116 - 2018-12-29668Moose-Admirals-
122 - 2019-01-04690Moose-Admirals-
123 - 2019-01-05706IceHogs-Admirals-
127 - 2019-01-09721Stars-Admirals-
129 - 2019-01-11728Penguins-Admirals-
130 - 2019-01-12734Wolves-Admirals-
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
37 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
15,902$ 124,690$ 57,440$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 8,692$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 180 1,158$ 208,440$




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
134400000022715110000003213300000019514822416301958011840374106820629224729.17%30293.33%38912770.08%8110577.14%466570.77%1219070234728
Total Saison Régulière4400000022715110000003213300000019514822416301958011840374106820629224729.17%30293.33%38912770.08%8110577.14%466570.77%1219070234728
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