Stars

GP: 76 | W: 36 | L: 34 | OTL: 6 | P: 78
GF: 210 | GA: 206 | PP%: 16.11% | PK%: 82.73%
DG: Pierre-Olivier Lefrançois | Morale : 83 | Moyenne d'Équipe : 71
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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
1Chris BrownX100.00565555555758585550555555557373180550
2Drew ShoreX100.00565555555657575550555555556774127540
3Vernon FiddlerX100.00555555555555555550555555557374144540
4Colby RobakX100.00605564667965716025606058555353151600
5Michal RozsivalX100.00585555605555775525555555558793165590
6Chris BreenX100.00555555605555605525555555555353147540
Rayé
1Alex OvechkinXX100.00945584979698989850899988559595167870
2Patrice BergeronX100.00805587929594849398909299559595167860
3Tyler SeguinXX100.00815582969191979695899593558884168860
4Mathew Barzal (R)X100.00675583978190929677988286557977167830
5Patrik LaineXX100.00885588969192959558819884558180157830
6Clayton Keller (R)XXX100.00605582977690929371908379557672167800
7Jason ZuckerXX100.00695587907986859158839185557466168790
8Justin AbdelkaderXX100.00985583879595878374787388558277164780
9Derek RyanX100.00675588798282828295797588557273167750
10Kyle BrodziakX100.00845587778787677889797092558682164750
11Jesper Bratt (R)XX100.00715582917082848364787474557070167740
12Matt CalvertX100.00765573787578777860737186558683159730
13Matt FrattinX100.00565555555555555550555555555960152530
14Max GortzX100.00565555555555555550555555555050120520
15Levko Koper (R)X100.00565555555556555550555555555050123520
16Duncan KeithX100.00755592979294999625876295559999164860
17Jacob TroubaX100.00855582939190989125846494558078167830
18Ryan EllisX100.00745598928893979425877394558481154830
19Christopher TanevX100.00725596859386877425686497558382165790
20Josh MorrisseyX100.00885583906387538925756792558082153770
21Matt IrwinX100.00855592768973797425646381558479131730
22Samuel Girard (R)X100.00755599885582558825766480557574121720
23Mathieu BrodeurX100.00555555605555685525555555555353120540
MOYENNE D'ÉQUIPE100.0071557678757777775073697755757515471
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
1Jack Flinn100.0054655987595958585959555456138600
Rayé
1Darcy Kuemper100.0082898883858584758975558075159800
2Carey Price100.0082748080818281828287559393166800
MOYENNE D'ÉQUIPE100.007376768375757472777455767515473
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ken Hitchcock70878085957638CAN665500,000$


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
1Nick LappinDallas StarsRW692830581382101221732419918911.62%38143920.861112236828300082837351.89%18500010.8116002425
2Daniel ZaarDallas StarsRW6927275426001051912437816911.11%19153522.2613132679294000132957051.75%62800010.7016000353
3Chris BrownStars (Dal)C76282654-1484101391582096916513.40%30146719.311314276831311261826049.90%148300000.7413200623
4T.J. HensickDallas StarsC6818274516415701171605013911.25%1983912.35291125168000093053.41%90800011.0711100244
5Mike CammalleriDallas StarsC/LW/RW401622382526101363103316115.53%886121.531892618410171994162.50%7200000.8802011533
6Matt FrattinStars (Dal)RW51201737203205780120377116.67%1877315.170113270001452057.61%9200010.9600000183
7Roope HintzDallas StarsLW57122436214157871122381009.84%1686315.151125240000563055.81%4300000.8300001225
8Timothy LiljegrenDallas StarsD694222648410107484717428.51%4196113.94156261210110113000.00%000000.5400002201
9Nick SchultzDallas StarsD2961824622032273772816.22%3151717.854812218901109401100.00%100000.9300000210
10Colby RobakStars (Dal)D3751924444058446114488.20%4382422.2931114471750000171100.00%000000.5800000112
11Hunter FejesDallas StarsLW3651217-128030548230516.10%773220.35336191560220991053.96%13900000.4613000200
12Nikita TryamkinDallas StarsD69214161935107505214273.85%40107515.58055251201011111000.00%000000.3000001011
13Brandon GignacDallas StarsC2366121140254038102915.79%335615.520001046000001249.85%32300100.6711000112
14Drew ShoreStars (Dal)C234610-2180415331101912.90%138116.5936917860000150053.67%39500000.5200000111
15Michal RozsivalStars (Dal)D29279-2240496237158.70%1445515.701121790000092000.00%200000.4000000000
16Vernon FiddlerStars (Dal)C131671180919144177.14%121616.621233200001190052.88%19100000.6500000000
17Levko KoperStars (Dal)LW36314-416033143817377.89%646112.82011111190000150063.33%3000000.1700000100
18Philippe MyersDallas StarsD30123-4195248102310.00%92237.4400006000129000.00%000000.2700001000
19Chris BreenStars (Dal)D121123006241225.00%41089.071013110000230136.36%1100000.3701000001
20Nikita JevpalovsDallas StarsC19022-1802167260.00%720510.810112360000510044.68%4700000.1900000000
21Ryan JohnstonDallas StarsD2311246015580612.50%61848.01000121000027000.00%000000.2200000000
22Joe HickettsDallas StarsD11022-21151167470.00%611910.86000626000024000.00%000000.3300001000
23Max GortzStars (Dal)RW5101-3203334233.33%05410.91000160000001100.00%200000.3700000001
24Nicholas MerkleyDallas StarsC9000000011100.00%0192.1300006000000075.00%400000.0000000000
25Samuel GirardStars (Dal)D1000000012000.00%022.880000000000000.00%000000.0000000000
26Logan ShawDallas StarsC/RW2000-1201474470.00%03718.92000113000000066.67%300000.0000000000
27Stephen GiontaDallas StarsC56000-220268280.00%1510.9200011000000066.67%4200000.0000000000
Stats d'équipe Total ou en Moyenne9621912924838577765117112531675552124811.40%3681477015.3558101159485245335838196535952.10%460100140.65623319333135
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
1Spencer MartinDallas Stars57312040.9132.3233306312914830410.929145612227
2Garret SparksDallas Stars124620.9192.0769602242980100.7789120401
3Jack FlinnStars (Dal)10100.9092.1428001110000.0000024000
Stats d'équipe Total ou en Moyenne70352760.9142.2840556515417920510.870236836628


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
Alex OvechkinStars (Dal)LW/RW311985-09-16No239 Lbs6 ft3NoNoNo2Sans RestrictionPro & Farm6,500,000$0$0$No
Carey PriceStars (Dal)G291987-08-16No216 Lbs6 ft3NoNoNo4Sans RestrictionPro & Farm2,000,000$0$0$No
Chris BreenStars (Dal)D271989-06-29No224 Lbs6 ft7NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Chris BrownStars (Dal)C251991-02-03No215 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Christopher TanevStars (Dal)D271989-12-20No185 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm2,500,000$0$0$No
Clayton KellerStars (Dal)C/LW/RW181998-06-25Yes168 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$No
Colby RobakStars (Dal)D261990-04-24No194 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Darcy KuemperStars (Dal)G261990-05-05No205 Lbs6 ft5NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No
Derek RyanStars (Dal)C301986-12-29No170 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm300,000$0$0$No
Drew ShoreStars (Dal)C251991-01-29No205 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Duncan KeithStars (Dal)D331983-07-16No192 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm6,500,000$0$0$No
Jack FlinnStars (Dal)G211995-12-20No223 Lbs6 ft8NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Jacob TroubaStars (Dal)D221994-02-26No200 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm2,500,000$0$0$No
Jason ZuckerStars (Dal)LW/RW241992-01-16No188 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm2,500,000$0$0$No
Jesper BrattStars (Dal)LW/RW181998-07-30Yes174 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Josh MorrisseyStars (Dal)D211995-03-28No195 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm900,000$0$0$No
Justin AbdelkaderStars (Dal)LW/RW291987-02-25No218 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm2,700,000$0$0$No
Kyle BrodziakStars (Dal)C321984-05-25No212 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm500,000$0$0$No
Levko KoperStars (Dal)LW261990-10-05Yes190 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Mathew BarzalStars (Dal)C191997-05-26Yes187 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$No
Mathieu BrodeurStars (Dal)D261990-06-20No215 Lbs6 ft6NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Matt CalvertStars (Dal)LW271989-12-23No187 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm1,000,000$0$0$No
Matt FrattinStars (Dal)RW291988-01-02No205 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Matt IrwinStars (Dal)D291987-11-28No210 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm1,000,000$0$0$No
Max GortzStars (Dal)RW231993-01-28No196 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Michal RozsivalStars (Dal)D381978-09-02No210 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm800,000$0$0$No
Patrice BergeronStars (Dal)C311985-07-23No194 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm6,500,000$0$0$No
Patrik LaineStars (Dal)LW/RW181998-04-19No206 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm900,000$0$0$No
Ryan EllisStars (Dal)D261991-01-02No175 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm3,500,000$0$0$No
Samuel GirardStars (Dal)D181998-05-12Yes161 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$No
Tyler SeguinStars (Dal)C/RW241992-01-30No200 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm6,300,000$0$0$No
Vernon FiddlerStars (Dal)C361980-05-08No205 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3226.06199 Lbs6 ft22.471,681,250$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris Brown40122
230122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris Brown60122
240122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
2Chris Brown40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
24012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
2Chris Brown40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris Brown
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris Brown
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , Chris Brown,
Gardien
#1 : , #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
1Admirals815001101326-1340200110714-741300000612-650.31313213400816657814162563962646178519414960610.00%38976.32%01082213650.66%1155253245.62%534111248.02%171911991999555887424
2Barracuda210000016601000000112-11100000054130.75069150081665783962563962646491240345240.00%13376.92%01082213650.66%1155253245.62%534111248.02%171911991999555887424
3Condors211000004311010000001-11100000042220.500471100816657848625639626464218313914214.29%12283.33%01082213650.66%1155253245.62%534111248.02%171911991999555887424
4Griffins85100110281414430000101578421001001376130.81328437101816657819462563962646213569516834823.53%39489.74%01082213650.66%1155253245.62%534111248.02%171911991999555887424
5Gulls2020000038-51010000025-31010000013-200.0003690081665783662563962646541633461600.00%14285.71%01082213650.66%1155253245.62%534111248.02%171911991999555887424
6Heat220000001239110000005231100000071641.00012203200816657862625639626465221126210660.00%5180.00%01082213650.66%1155253245.62%534111248.02%171911991999555887424
7IceHogs825010002024-4413000001114-341201000910-160.375203858008166578227625639626462508510216138410.53%431272.09%11082213650.66%1155253245.62%534111248.02%171911991999555887424
8Moose862000003615214310000017894310000019712120.750366399028166578299625639626462156899195391230.77%43686.05%11082213650.66%1155253245.62%534111248.02%171911991999555887424
9Rampage1439001102038-18723001101518-371600000520-1590.3212034540181665782846256396264639489213260911010.99%861681.40%01082213650.66%1155253245.62%534111248.02%171911991999555887424
10Reign2200000014311110000007161100000072541.000142741008166578876256396264645824547228.57%12283.33%11082213650.66%1155253245.62%534111248.02%171911991999555887424
11Roadrunners421001001091210001005502110000054150.62510162601816657810462563962646105354310117317.65%19194.74%01082213650.66%1155253245.62%534111248.02%171911991999555887424
Total7630340244221020643815140034210498638152002100106108-2780.513210357567158166578191362563962646218262199815674166716.11%4177282.73%31082213650.66%1155253245.62%534111248.02%171911991999555887424
13Wild834000102633-74210001012120413000001421-780.500264773008166578234625639626462817411412940820.00%49883.67%01082213650.66%1155253245.62%534111248.02%171911991999555887424
14Wolves824010011824-64120000179-2412010001115-470.4381826441081665781586256396264630488981694548.89%44686.36%01082213650.66%1155253245.62%534111248.02%171911991999555887424
_Since Last GM Reset7630340244221020643815140034210498638152002100106108-2780.513210357567158166578191362563962646218262199815674166716.11%4177282.73%31082213650.66%1155253245.62%534111248.02%171911991999555887424
_Vs Conference58192902341141165-24291012002417277-529917021006988-19540.466141236377128166578134862563962646171448275911373324814.46%3165881.65%11082213650.66%1155253245.62%534111248.02%171911991999555887424

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7678L321035756719132182621998156715
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7630342442210206
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
381514034210498
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3815202100106108
Derniers 10 Matchs
WLOTWOTL SOWSOL
280000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4166716.11%4177282.73%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
625639626468166578
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
1082213650.66%1155253245.62%534111248.02%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
171911991999555887424


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
3 - 2018-09-075Griffins0Stars3WSommaire du Match
4 - 2018-09-0819Admirals6Stars0LSommaire du Match
10 - 2018-09-1439Stars1Wild3LSommaire du Match
11 - 2018-09-1550Stars3IceHogs2WXSommaire du Match
15 - 2018-09-1965Stars1Griffins2LSommaire du Match
17 - 2018-09-2178Wild5Stars0LSommaire du Match
18 - 2018-09-2291Wild1Stars3WSommaire du Match
24 - 2018-09-28113Wolves2Stars1LXXSommaire du Match
25 - 2018-09-29127Barracuda2Stars1LXXSommaire du Match
31 - 2018-10-05151Stars7Reign2WSommaire du Match
32 - 2018-10-06166Stars4Condors2WSommaire du Match
39 - 2018-10-13201Rampage1Stars3WSommaire du Match
40 - 2018-10-14208Stars0Rampage1LSommaire du Match
43 - 2018-10-17220Moose0Stars7WSommaire du Match
45 - 2018-10-19231IceHogs4Stars2LSommaire du Match
52 - 2018-10-26273Stars1Rampage2LSommaire du Match
53 - 2018-10-27287Rampage5Stars4LSommaire du Match
54 - 2018-10-28295Stars2Rampage0WSommaire du Match
59 - 2018-11-02314Stars0Admirals3LSommaire du Match
60 - 2018-11-03325Stars1Griffins2LXSommaire du Match
61 - 2018-11-04336Stars2Wolves7LSommaire du Match
64 - 2018-11-07345Admirals2Stars3WXXSommaire du Match
66 - 2018-11-09357Admirals3Stars2LXSommaire du Match
71 - 2018-11-14388Wild4Stars6WSommaire du Match
73 - 2018-11-16398Stars3Admirals4LSommaire du Match
74 - 2018-11-17407Stars0IceHogs2LSommaire du Match
77 - 2018-11-20422Stars4Wolves3WXSommaire du Match
80 - 2018-11-23444Rampage1Stars2WXXSommaire du Match
81 - 2018-11-24460Stars0Rampage1LSommaire du Match
86 - 2018-11-29474Rampage1Stars2WSommaire du Match
88 - 2018-12-01496Reign1Stars7WSommaire du Match
89 - 2018-12-02502Stars0Rampage2LSommaire du Match
94 - 2018-12-07526Moose1Stars4WSommaire du Match
95 - 2018-12-08541Moose2Stars5WSommaire du Match
99 - 2018-12-12557Condors1Stars0LSommaire du Match
101 - 2018-12-14569IceHogs2Stars0LSommaire du Match
102 - 2018-12-15583Wild2Stars3WXXSommaire du Match
106 - 2018-12-19604Stars1Gulls3LSommaire du Match
108 - 2018-12-21614Stars5Barracuda4WSommaire du Match
109 - 2018-12-22628Stars7Heat1WSommaire du Match
111 - 2018-12-24642Stars3Roadrunners4LSommaire du Match
113 - 2018-12-26651Stars2Roadrunners0WSommaire du Match
115 - 2018-12-28664Heat2Stars5WSommaire du Match
116 - 2018-12-29680Gulls5Stars2LSommaire du Match
121 - 2019-01-03682Griffins2Stars5WSommaire du Match
127 - 2019-01-09721Stars3Admirals2WSommaire du Match
130 - 2019-01-12742Stars9Moose3WSommaire du Match
131 - 2019-01-13750Stars3Moose0WSommaire du Match
133 - 2019-01-15759Stars4IceHogs3WSommaire du Match
136 - 2019-01-18777Roadrunners1Stars2WSommaire du Match
137 - 2019-01-19790Roadrunners4Stars3LXSommaire du Match
140 - 2019-01-22807Stars5Wild2WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
142 - 2019-01-24814Stars1Wolves3LSommaire du Match
143 - 2019-01-25820Stars6Griffins1WSommaire du Match
145 - 2019-01-27844Stars4Wolves2WSommaire du Match
148 - 2019-01-30853Admirals3Stars2LSommaire du Match
150 - 2019-02-01863Wolves1Stars0LSommaire du Match
151 - 2019-02-02877Wolves2Stars3WSommaire du Match
154 - 2019-02-05889Stars0Admirals3LSommaire du Match
155 - 2019-02-06891Stars5Griffins2WSommaire du Match
158 - 2019-02-09919Stars1Rampage3LSommaire du Match
159 - 2019-02-10929Rampage2Stars1LXSommaire du Match
162 - 2019-02-13940Stars5Moose1WSommaire du Match
164 - 2019-02-15951Stars2Moose3LSommaire du Match
166 - 2019-02-17970Stars2IceHogs3LSommaire du Match
169 - 2019-02-20982Griffins3Stars4WXXSommaire du Match
171 - 2019-02-22990Wolves4Stars3LSommaire du Match
172 - 2019-02-231004Griffins2Stars3WSommaire du Match
176 - 2019-02-271024Moose5Stars1LSommaire du Match
178 - 2019-03-011034Stars4Wild9LSommaire du Match
179 - 2019-03-021046Stars4Wild7LSommaire du Match
185 - 2019-03-081080IceHogs5Stars4LSommaire du Match
186 - 2019-03-091094IceHogs3Stars5WSommaire du Match
190 - 2019-03-131110Rampage3Stars1LSommaire du Match
192 - 2019-03-151124Stars1Rampage11LSommaire du Match
193 - 2019-03-161138Rampage5Stars2LSommaire 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
823,917$ 538,000$ 330,165$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 169,161$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 5,351$ 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
137630340244221020643815140034210498638152002100106108-278210357567158166578191362563962646218262199815674166716.11%4177282.73%31082213650.66%1155253245.62%534111248.02%171911991999555887424
Total Saison Régulière7630340244221020643815140034210498638152002100106108-278210357567158166578191362563962646218262199815674166716.11%4177282.73%31082213650.66%1155253245.62%534111248.02%171911991999555887424
Séries
12201280000053467116500000292729630000024195245399152001420154513132177154504661482814381501812.00%1211290.08%033464351.94%33666150.83%17030855.19%536367499169274142
12201280000053467116500000292729630000024195245399152001420154513132177154504661482814381501812.00%1211290.08%033464351.94%33666150.83%17030855.19%536367499169274142
Total Séries402416000001069214221210000005854418126000004838104810619830400284030810262643543081009322965628763003612.00%2422490.08%0668128651.94%672132250.83%34061655.19%1073735998339549284