Stars

GP: 23 | W: 9 | L: 10 | OTL: 4 | P: 22
GF: 51 | GA: 57 | PP%: 18.52% | PK%: 86.58%
DG: Pierre-Olivier Lefrançois | Morale : 65 | Moyenne d'Équipe : 57
Prochain matchs #388 vs Wild
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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 ZaarX100.00605571666262696050606156557375151590
2Nick LappinX100.00625565766662666050606060555050150590
3Hunter Fejes (R)X100.00595571637668545550555559555050147560
4Chris BrownX100.00565555555758585550555555557373159550
5Drew ShoreX100.00565555555657575550555555556774146540
6Brandon Gignac (R)X100.00565555555758595550555555557366145540
7Stephen GiontaX100.00555555555555555550555555557372138540
8Roope HintzX100.00565555555555555550555555555050146530
9Levko Koper (R)X100.00565555555556555550555555555050153530
10Matt FrattinX100.00565555555555555550555555555960150530
11Nick SchultzX100.00625565708565796525656659559092156660
12Colby RobakX100.00605564667965716025606058555353150600
13Michal RozsivalX100.00585555605555775525555555558793157580
14Julian MelchioriX100.00555555605555795525555555557170152570
15Nikita TryamkinX100.00555555605555555525555555557272158550
16Ryan JohnstonX100.00555555605555595525555555555353139540
17Timothy Liljegren (R)X100.00555555605555585525555555556262145540
18Philippe Myers (R)X100.00555555605555555525555555556262148540
Rayé
1Pavel ZachaXX100.00805578878181797978767077557876162730
2Vernon FiddlerX100.00555555555555555550555555557374137540
3Max GortzX100.00565555555555555550555555555050134530
4Zack MacEwen (R)X100.00555555555555555550555555555050140530
5Nicholas Merkley (R)X100.00555555555555555550555555555050130520
6Joe HickettsX100.00655566815774706525656063555353146630
7Chris BreenX100.00555555605555605525555555555353147540
8Mathieu BrodeurX100.00555555605555685525555555555353126540
MOYENNE D'ÉQUIPE100.0058555961605962574157575755636314756
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 Martin100.0063768179656567646865556063149660
2Jack Flinn100.0054655987595958585959555456151600
Rayé
1Garret Sparks100.0077757785777783837676557069133750
MOYENNE D'ÉQUIPE100.006572728467676968686755616314467
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Willie Desjardins75715578765548CAN6151,000,000$


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
1Colby RobakStars (Dal)D231171843002826347312.94%2951022.1911011281120000118100.00%000000.7100000111
2Nick SchultzStars (Dal)D2351116416024172462220.83%2536615.924610156401107001100.00%100000.8700000110
3Daniel ZaarStars (Dal)RW23581342202549549269.26%353823.41145179800031193055.05%19800000.4803000001
4Nick LappinStars (Dal)RW235813-430038395730518.77%551022.20369139700061012058.04%11200000.5103000101
5Hunter FejesStars (Dal)LW233912-322016334420296.82%248821.24123121060220700056.79%8100000.4902000100
6Drew ShoreStars (Dal)C18369-110032282081715.00%128816.0326811650000120054.86%28800000.6200000011
7Chris BrownStars (Dal)C23437-620019252962313.79%243518.9631411931012720050.00%31200000.3202000010
8Michal RozsivalStars (Dal)D23167-4120353176125.88%932214.031121370000069000.00%200000.4300000000
9Julian MelchioriStars (Dal)D23336-16021317101017.65%1329012.612131567000059000.00%000000.4100000100
10Timothy LiljegrenStars (Dal)D23246-3275271365333.33%1227011.78123433000050000.00%000000.4400001100
11Brandon GignacStars (Dal)C18325-78023293061810.00%328015.57000838000001148.78%24600100.3611000011
12Roope HintzStars (Dal)LW23325-11802617385187.89%134314.921124180000431042.86%2100000.2900000010
13Matt FrattinStars (Dal)RW16134-31801121166176.25%324615.430113130001340079.55%4400000.3200000000
14Vernon FiddlerStars (Dal)C5123-31004651520.00%19519.09123219000050047.66%10700000.6300000000
15Chris BreenStars (Dal)D111123006231233.33%4948.63101290000220136.36%1100000.4201000001
16Levko KoperStars (Dal)LW23112-3120127217214.76%224810.800118640000130058.82%1700000.1600000000
17David SchlemkoDallas StarsD11112-2100612103510.00%5999.0810181600003000.00%000000.4000000010
18Joe HickettsStars (Dal)D10022-21151167470.00%611811.84000626000024000.00%000000.3400001000
19Max GortzStars (Dal)RW5101-3203334233.33%05410.91000160000001100.00%200000.3700000001
20Nikita TryamkinStars (Dal)D23101-10260261771514.29%1033314.48000123000038000.00%000000.0600000000
21Ryan JohnstonStars (Dal)D10000-200300010.00%2293.0000003000010000.00%000000.0000000000
22Nicholas MerkleyStars (Dal)C2000000001000.00%021.170000000000000.00%100000.0000000000
23Logan ShawDallas StarsC/RW2000-1201474470.00%03718.92000113000000066.67%300000.0000000000
24Philippe MyersStars (Dal)D17000-61151133100.00%41076.3000000000015000.00%000000.0000001000
25Stephen GiontaStars (Dal)C10000-100001010.00%080.8200011000000050.00%200000.0000000000
Stats d'équipe Total ou en Moyenne4114589134-51323154213664511503339.98%142612214.902344671841065134129558453.11%144800100.44112003677
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)135420.8922.5373501312880001.00041211003
2Garret SparksStars (Dal)114520.9182.1763602232800100.7789110401
3Jack FlinnStars (Dal)10100.9092.1428001110000.0000012000
Stats d'équipe Total ou en Moyenne2591040.9052.36140103555790100.846132323404


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
Brandon GignacStars (Dal)C191997-11-07Yes172 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Chris BreenStars (Dal)D271989-06-29No224 Lbs6 ft7NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Chris BrownStars (Dal)C251991-02-03No215 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
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$0$No300,000$300,000$300,000$
Drew ShoreStars (Dal)C251991-01-29No205 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Garret SparksStars (Dal)G231993-06-28No200 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No500,000$
Hunter FejesStars (Dal)LW221994-05-31Yes190 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Jack FlinnStars (Dal)G211995-12-20No223 Lbs6 ft8NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Joe HickettsStars (Dal)D201996-05-04No175 Lbs5 ft8NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Julian MelchioriStars (Dal)D251991-12-06No214 Lbs6 ft5NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Levko KoperStars (Dal)LW261990-10-05Yes190 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Mathieu BrodeurStars (Dal)D261990-06-20No215 Lbs6 ft6NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
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$0$No800,000$
Nicholas MerkleyStars (Dal)C191997-05-23Yes194 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$No900,000$900,000$900,000$
Nick LappinStars (Dal)RW241992-11-01No174 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Nick SchultzStars (Dal)D341982-08-24No203 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm1,000,000$0$0$No1,000,000$1,000,000$
Nikita TryamkinStars (Dal)D261990-03-04No240 Lbs6 ft8NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No500,000$
Pavel ZachaStars (Dal)C/LW191997-04-06No210 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm900,000$0$0$No900,000$900,000$
Philippe MyersStars (Dal)D191997-01-25Yes209 Lbs6 ft5NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Roope HintzStars (Dal)LW201996-11-16No198 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Ryan JohnstonStars (Dal)D241992-02-14No176 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
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$0$No300,000$
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$0$No300,000$300,000$300,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2924.45199 Lbs6 ft22.55427,379$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Hunter FejesDrew ShoreDaniel Zaar40122
2Levko KoperChris BrownNick Lappin30122
3Roope HintzBrandon GignacMatt Frattin20122
4Daniel ZaarDrew ShoreNick Lappin10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nick SchultzColby Robak40122
2Michal RozsivalJulian Melchiori30122
3Nikita TryamkinNick Schultz20122
4Nick SchultzTimothy Liljegren10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Hunter FejesDrew ShoreDaniel Zaar60122
2Levko KoperChris BrownNick Lappin40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nick SchultzColby Robak60122
2Michal RozsivalJulian Melchiori40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Daniel ZaarNick Lappin60122
2Hunter FejesChris Brown40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nick SchultzColby Robak60122
2Michal RozsivalJulian Melchiori40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Daniel Zaar60122Nick SchultzColby Robak60122
2Nick Lappin40122Michal RozsivalJulian Melchiori40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Daniel ZaarNick Lappin60122
2Hunter FejesDrew Shore40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nick SchultzColby Robak60122
2Michal RozsivalJulian Melchiori40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Hunter FejesNick LappinDaniel ZaarNick SchultzColby Robak
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Hunter FejesNick LappinDaniel ZaarNick SchultzColby Robak
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brandon Gignac, Drew Shore, Matt FrattinBrandon Gignac, Drew ShoreMatt Frattin
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nikita Tryamkin, Nick Schultz, Colby RobakNikita TryamkinColby Robak, Nick Schultz
Tirs de Pénalité
Daniel Zaar, Nick Lappin, Hunter Fejes, Brandon Gignac, Chris Brown
Gardien
#1 : Spencer Martin, #2 : Jack Flinn


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
1Admirals40200110514-930100110511-61010000003-330.375581300191812268162151153218926528733412.12%20195.00%034963255.22%38976450.92%17532653.68%549371571172281141
2Barracuda1000000112-11000000112-10000000000010.50011200191812218162151153212281814010.00%3166.67%034963255.22%38976450.92%17532653.68%549371571172281141
3Condors11000000422000000000001100000042221.0004711001918122241621511532128920165240.00%9277.78%034963255.22%38976450.92%17532653.68%549371571172281141
4Griffins31100100541110000003032010010024-230.5005101501191812262162151153215811335915320.00%140100.00%034963255.22%38976450.92%17532653.68%549371571172281141
5IceHogs2010100056-11010000024-21000100032120.500591400191812242162151153215512224214321.43%11281.82%034963255.22%38976450.92%17532653.68%549371571172281141
6Moose11000000707110000007070000000000021.00071421011918122361621511532124614315360.00%70100.00%134963255.22%38976450.92%17532653.68%549371571172281141
7Rampage523000001091211000007613120000033040.4001018280119181221151621511532111030949639615.38%35585.71%034963255.22%38976450.92%17532653.68%549371571172281141
8Reign11000000725000000000001100000072521.0007132000191812230162151153211951622200.00%8275.00%134963255.22%38976450.92%17532653.68%549371571172281141
Total23710012125157-61244001122931-21136011002226-4220.4785194145031918122474162151153215791613704531352518.52%1492086.58%234963255.22%38976450.92%17532653.68%549371571172281141
10Wild3120000049-52110000036-31010000013-220.333481200191812249162151153219627734114214.29%32487.50%034963255.22%38976450.92%17532653.68%549371571172281141
11Wolves2010000139-61000000112-11010000027-510.2503690019181223016215115321782728458112.50%10370.00%034963255.22%38976450.92%17532653.68%549371571172281141
_Since Last GM Reset23710012125157-61244001122931-21136011002226-4220.4785194145031918122474162151153215791613704531352518.52%1492086.58%234963255.22%38976450.92%17532653.68%549371571172281141
_Vs Conference20510012113653-171034001112129-81026011001524-9170.4253666102021918122390162151153215141423223861282116.41%1311787.02%034963255.22%38976450.92%17532653.68%549371571172281141

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2322OTL1519414547457916137045303
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2371012125157
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
124401122931
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
113611002226
Derniers 10 Matchs
WLOTWOTL SOWSOL
250210
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1352518.52%1492086.58%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
162151153211918122
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
34963255.22%38976450.92%17532653.68%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
549371571172281141


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 - 2018-11-14388Wild-Stars-
73 - 2018-11-16398Stars-Admirals-
74 - 2018-11-17407Stars-IceHogs-
77 - 2018-11-20422Stars-Wolves-
80 - 2018-11-23444Rampage-Stars-
81 - 2018-11-24460Stars-Rampage-
86 - 2018-11-29474Rampage-Stars-
88 - 2018-12-01496Reign-Stars-
89 - 2018-12-02502Stars-Rampage-
94 - 2018-12-07526Moose-Stars-
95 - 2018-12-08541Moose-Stars-
99 - 2018-12-12557Condors-Stars-
101 - 2018-12-14569IceHogs-Stars-
102 - 2018-12-15583Wild-Stars-
106 - 2018-12-19604Stars-Gulls-
108 - 2018-12-21614Stars-Barracuda-
109 - 2018-12-22628Stars-Heat-
111 - 2018-12-24642Stars-Roadrunners-
113 - 2018-12-26651Stars-Roadrunners-
115 - 2018-12-28664Heat-Stars-
116 - 2018-12-29680Gulls-Stars-
121 - 2019-01-03682Griffins-Stars-
127 - 2019-01-09721Stars-Admirals-
130 - 2019-01-12742Stars-Moose-
131 - 2019-01-13750Stars-Moose-
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
26 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
273,858$ 123,940$ 93,016$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 44,430$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 127 5,794$ 735,838$




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
1323710012125157-61244001122931-21136011002226-4225194145031918122474162151153215791613704531352518.52%1492086.58%234963255.22%38976450.92%17532653.68%549371571172281141
Total Saison Régulière23710012125157-61244001122931-21136011002226-4225194145031918122474162151153215791613704531352518.52%1492086.58%234963255.22%38976450.92%17532653.68%549371571172281141
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