Stars

GP: 48 | W: 25 | L: 19 | OTL: 4 | P: 54
GF: 132 | GA: 110 | PP%: 17.15% | PK%: 85.36%
DG: Pierre-Olivier Lefrançois | Morale : 87 | Moyenne d'Équipe : 58
Prochain matchs #759 vs IceHogs
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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
1Daniel ZaarX98.00605571666262696050606156557375166600
2Nick LappinX98.00625565766662666050606060555050168590
3Hunter Fejes (R)X100.00595571637668545550555559555050149560
4T.J. HensickX100.00595565635859705550555555555758170560
5Chris BrownX98.00565555555758585550555555557373183550
6Vernon FiddlerX100.00555555555555555550555555557374137540
7Matt FrattinX100.00565555555555555550555555555960169540
8Stephen GiontaX100.00555555555555555550555555557372160540
9Roope HintzX100.00565555555555555550555555555050167530
10Nick SchultzX100.00625565708565796525656659559092168660
11Joe HickettsX100.00655566815774706525656063555353139630
12Michal RozsivalX100.00585555605555775525555555558793158590
13Julian MelchioriX100.00555555605555795525555555557170177570
14Nikita TryamkinX100.00555555605555555525555555557272182560
15Timothy Liljegren (R)X100.00555555605555585525555555556262159550
16Chris BreenX100.00555555605555605525555555555353140540
17Ryan JohnstonX100.00555555605555595525555555555353158540
Rayé
1Mike CammalleriXXX100.00665580866762807981806775558075158710
2Drew ShoreX100.00565555555657575550555555556774133540
3Brandon Gignac (R)X100.00565555555758595550555555557366133540
4Nikita JevpalovsX100.00565555555555555550555555555050149530
5Levko Koper (R)X100.00565555555556555550555555555050151530
6Max GortzX100.00565555555555555550555555555050120520
7Nicholas Merkley (R)X100.00555555555555555550555555555050119520
8Zack MacEwen (R)X100.00555555555555555550555555555050124520
9Samuel Girard (R)X100.00755599885582558825766480557574139720
10Colby RobakX100.00605564667965716025606058555353157600
11Mathieu BrodeurX100.00555555605555685525555555555353122540
12Philippe Myers (R)X100.00555555605555555525555555556262146540
MOYENNE D'ÉQUIPE99.7958556062595962584158575755626315257
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
1Spencer Martin100.0063768179656567646865556063155660
Rayé
1Garret Sparks100.0077757785777783837676557069122750
2Jack Flinn100.0054655987595958585959555456153600
MOYENNE D'ÉQUIPE100.006572728467676968686755616314367
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
1Mike CammalleriStars (Dal)C/LW/RW401622382526101363103316115.53%886121.531892618410171994162.50%7200000.8802011533
2Daniel ZaarStars (Dal)RW48181735136064124157539911.46%9109522.831071748200000122186054.23%46100010.6415000123
3Nick LappinStars (Dal)RW481517322555901061476311410.20%14104121.7079163219300081975152.08%14400010.6115001212
4Matt FrattinStars (Dal)RW4117153220320446485265820.00%862615.280113270001452063.10%8400011.0200000171
5Roope HintzStars (Dal)LW4710203021335614996287310.42%1470915.101125240000563054.05%3700000.8500001223
6Chris BrownStars (Dal)C48131427-9575698091287414.29%1293019.3969152220110121293051.23%85100000.5802100221
7Nick SchultzStars (Dal)D2961824622032273772816.22%3151717.854812218901109401100.00%100000.9300000210
8Colby RobakStars (Dal)D3751924444058446114488.20%4382422.2931114471750000171100.00%000000.5800000112
9T.J. HensickStars (Dal)C47815239315516880248010.00%1053411.37044576000091054.20%54800000.8600100113
10Julian MelchioriStars (Dal)D4851722732069266121428.20%5181717.033811411690000141000.00%000000.5400000200
11Timothy LiljegrenStars (Dal)D4831619-153569303511298.57%2767013.97156221030000104000.00%000000.5700001101
12Hunter FejesStars (Dal)LW3651217-128030548230516.10%773220.35336191560220991053.96%13900000.4613000200
13Brandon GignacStars (Dal)C2366121140254038102915.79%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
16Nikita TryamkinStars (Dal)D48189-655566293711222.70%2577916.24044221020000100000.00%000000.2300001001
17Vernon FiddlerStars (Dal)C131671180919144177.14%121616.621233200001190052.88%19100000.6500000000
18Levko KoperStars (Dal)LW36314-416033143817377.89%646112.82011111190000150063.33%3000000.1700000100
19Philippe MyersStars (Dal)D30123-4195248102310.00%92237.4400006000129000.00%000000.2700001000
20Chris BreenStars (Dal)D121123006241225.00%41089.071013110000230136.36%1100000.3701000001
21Nikita JevpalovsStars (Dal)C19022-1802167260.00%720510.810112360000510044.68%4700000.1900000000
22Ryan JohnstonStars (Dal)D2311246015580612.50%61848.01000121000027000.00%000000.2200000000
23Joe HickettsStars (Dal)D11022-21151167470.00%611910.86000626000024000.00%000000.3300001000
24Max GortzStars (Dal)RW5101-3203334233.33%05410.91000160000001100.00%200000.3700000001
25Nicholas MerkleyStars (Dal)C9000000011100.00%0192.1300006000000075.00%400000.0000000000
26Samuel GirardStars (Dal)D1000000012000.00%022.880000000000000.00%000000.0000000000
27Logan ShawDallas StarsC/RW2000-1201474470.00%03718.92000113000000066.67%300000.0000000000
28Stephen GiontaStars (Dal)C35000-200248280.00%1441.2700011000000071.87%3200000.0000000000
Stats d'équipe Total ou en Moyenne8361422443866664250969939127041593711.18%3171301315.574589134386219823532187127753.30%337700130.59419217252225
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 MartinStars (Dal)37211220.9072.32211943828800101.00093612205
2Garret SparksStars (Dal)124620.9192.0769602242980100.7789120401
3Jack FlinnStars (Dal)10100.9092.1428001110000.0000024000
Stats d'équipe Total ou en Moyenne50251940.9102.2628444510711890200.889184836606


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
Brandon GignacStars (Dal)C191997-11-07Yes172 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm300,000$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
Colby RobakStars (Dal)D261990-04-24No194 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Daniel ZaarStars (Dal)RW221994-04-24No167 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Drew ShoreStars (Dal)C251991-01-29No205 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Garret SparksStars (Dal)G231993-06-28No200 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No
Hunter FejesStars (Dal)LW221994-05-31Yes190 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Jack FlinnStars (Dal)G211995-12-20No223 Lbs6 ft8NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Joe HickettsStars (Dal)D201996-05-04No175 Lbs5 ft8NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
Julian MelchioriStars (Dal)D251991-12-06No214 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Levko KoperStars (Dal)LW261990-10-05Yes190 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Mathieu BrodeurStars (Dal)D261990-06-20No215 Lbs6 ft6NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Matt FrattinStars (Dal)RW291988-01-02No205 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm500,000$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
Mike CammalleriStars (Dal)C/LW/RW341982-06-07No190 Lbs5 ft9NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Nicholas MerkleyStars (Dal)C191997-05-23Yes194 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$No
Nick LappinStars (Dal)RW241992-11-01No174 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Nick SchultzStars (Dal)D341982-08-24No203 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm1,000,000$0$0$No
Nikita JevpalovsStars (Dal)C221994-09-09No207 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No
Nikita TryamkinStars (Dal)D261990-03-04No240 Lbs6 ft8NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No
Philippe MyersStars (Dal)D191997-01-25Yes209 Lbs6 ft5NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Roope HintzStars (Dal)LW201996-11-16No198 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Ryan JohnstonStars (Dal)D241992-02-14No176 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Samuel GirardStars (Dal)D181998-05-12Yes161 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$No
Spencer MartinStars (Dal)G211995-06-07No200 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm894,000$0$0$No
Stephen GiontaStars (Dal)C331983-10-08No185 Lbs5 ft7NoNoNo2Sans RestrictionPro & Farm300,000$0$0$No
T.J. HensickStars (Dal)C311985-12-09No190 Lbs5 ft10NoNoNo2Sans RestrictionPro & Farm498,888$0$0$No
Timothy LiljegrenStars (Dal)D171999-04-30Yes190 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm0$0$No
Vernon FiddlerStars (Dal)C361980-05-08No205 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Zack MacEwenStars (Dal)C201996-07-08Yes205 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3224.84198 Lbs6 ft12.50427,903$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris BrownDaniel Zaar40122
2T.J. HensickNick Lappin30122
3Roope HintzMatt Frattin20122
4Daniel ZaarStephen GiontaNick Lappin10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julian Melchiori40122
2Nikita TryamkinTimothy Liljegren30122
320122
4Julian Melchiori10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Chris BrownDaniel Zaar60122
2T.J. HensickNick Lappin40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julian Melchiori60122
2Nikita TryamkinTimothy Liljegren40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Daniel ZaarNick Lappin60122
2Chris Brown40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julian Melchiori60122
2Nikita TryamkinTimothy Liljegren40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Daniel Zaar60122Julian Melchiori60122
2Nick Lappin40122Nikita TryamkinTimothy Liljegren40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Daniel ZaarNick Lappin60122
2Chris Brown40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Julian Melchiori60122
2Nikita TryamkinTimothy Liljegren40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris BrownDaniel ZaarJulian Melchiori
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Chris BrownDaniel ZaarJulian Melchiori
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , Nikita Tryamkin, Nikita Tryamkin
Tirs de Pénalité
Daniel Zaar, Nick Lappin, , Chris Brown, T.J. Hensick
Gardien
#1 : Spencer Martin, #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
1Admirals613001101120-930100110511-63120000069-350.41711193000524233610839538439031132357011748510.42%26676.92%0745139553.41%761153749.51%36469652.30%11738161161349577289
2Barracuda210000016601000000112-11100000054130.75069150052423363939538439031491240345240.00%13376.92%0745139553.41%761153749.51%36469652.30%11738161161349577289
3Condors211000004311010000001-11100000042220.500471100524233648395384390314218313914214.29%12283.33%0745139553.41%761153749.51%36469652.30%11738161161349577289
4Griffins421001001064220000008262010010024-250.62510182801524233685395384390319219558020315.00%25292.00%0745139553.41%761153749.51%36469652.30%11738161161349577289
5Gulls2020000038-51010000025-31010000013-200.0003690052423363639538439031541633461600.00%14285.71%0745139553.41%761153749.51%36469652.30%11738161161349577289
6Heat220000001239110000005231100000071641.00012203200524233662395384390315221126210660.00%5180.00%0745139553.41%761153749.51%36469652.30%11738161161349577289
7IceHogs40301000510-52020000026-42010100034-120.250591400524233685395384390319527448625312.00%21480.95%0745139553.41%761153749.51%36469652.30%11738161161349577289
8Moose55000000286223300000016313220000001239101.00028528002524233622639538439031129456313817741.18%27196.30%1745139553.41%761153749.51%36469652.30%11738161161349577289
9Rampage93500010141404210001011835140000036-380.444142438015242336195395384390311915016316164914.06%62887.10%0745139553.41%761153749.51%36469652.30%11738161161349577289
10Reign2200000014311110000007161100000072541.000142741005242336873953843903145824547228.57%12283.33%1745139553.41%761153749.51%36469652.30%11738161161349577289
11Roadrunners21100000541000000000002110000054120.500581301524233646395384390315519135010220.00%40100.00%0745139553.41%761153749.51%36469652.30%11738161161349577289
Total48201902232132110222411700132705515249120210062557540.563132234366055242336118239538439031121335368510192744717.15%2804185.36%2745139553.41%761153749.51%36469652.30%11738161161349577289
13Wild522000101315-242100010121201010000013-260.6001323360052423361053953843903114946938024416.67%41685.37%0745139553.41%761153749.51%36469652.30%11738161161349577289
14Wolves30101001712-51000000112-120101000610-430.50071219005242336603953843903112837447214214.29%18477.78%0745139553.41%761153749.51%36469652.30%11738161161349577289
_Since Last GM Reset48201902232132110222411700132705515249120210062557540.563132234366055242336118239538439031121335368510192744717.15%2804185.36%2745139553.41%761153749.51%36469652.30%11738161161349577289
_Vs Conference351116022317683-71876001314444017410021003239-7350.50076132208025242336748395384390318812535126972193415.53%2103384.29%0745139553.41%761153749.51%36469652.30%11738161161349577289

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4854W413223436611821213353685101905
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4820192232132110
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2411701327055
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2491221006255
Derniers 10 Matchs
WLOTWOTL SOWSOL
820000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2744717.15%2804185.36%2
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
395384390315242336
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
745139553.41%761153749.51%36469652.30%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
11738161161349577289


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 - 2019-01-15759Stars-IceHogs-
136 - 2019-01-18777Roadrunners-Stars-
137 - 2019-01-19790Roadrunners-Stars-
140 - 2019-01-22807Stars-Wild-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
142 - 2019-01-24814Stars-Wolves-
143 - 2019-01-25820Stars-Griffins-
145 - 2019-01-27844Stars-Wolves-
148 - 2019-01-30853Admirals-Stars-
150 - 2019-02-01863Wolves-Stars-
151 - 2019-02-02877Wolves-Stars-
154 - 2019-02-05889Stars-Admirals-
155 - 2019-02-06891Stars-Griffins-
158 - 2019-02-09919Stars-Rampage-
159 - 2019-02-10929Rampage-Stars-
162 - 2019-02-13940Stars-Moose-
164 - 2019-02-15951Stars-Moose-
166 - 2019-02-17970Stars-IceHogs-
169 - 2019-02-20982Griffins-Stars-
171 - 2019-02-22990Wolves-Stars-
172 - 2019-02-231004Griffins-Stars-
176 - 2019-02-271024Moose-Stars-
178 - 2019-03-011034Stars-Wild-
179 - 2019-03-021046Stars-Wild-
185 - 2019-03-081080IceHogs-Stars-
186 - 2019-03-091094IceHogs-Stars-
190 - 2019-03-131110Rampage-Stars-
192 - 2019-03-151124Stars-Rampage-
193 - 2019-03-161138Rampage-Stars-



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
14 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
581,101$ 136,929$ 104,336$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 88,782$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 63 3,283$ 206,829$




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
134820190223213211022241170013270551524912021006255754132234366055242336118239538439031121335368510192744717.15%2804185.36%2745139553.41%761153749.51%36469652.30%11738161161349577289
Total Saison Régulière4820190223213211022241170013270551524912021006255754132234366055242336118239538439031121335368510192744717.15%2804185.36%2745139553.41%761153749.51%36469652.30%11738161161349577289
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