Stars

GP: 25 | W: 18 | L: 4 | OTL: 3 | P: 39
GF: 77 | GA: 40 | PP%: 18.87% | PK%: 91.27%
DG: Pierre-Olivier Lefrançois | Morale : 65 | Moyenne d'Équipe : 63
Prochain matchs #407 vs IceHogs
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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
1Peter HollandX100.006338846579949363706261646275687071650
2Dale WeiseXX100.008242807082737666566164656279725175650
3Devante Smith-PellyXX100.008341826379747061566264736573676338640
4T.J. HensickX100.005435956368787262736556575984745171620
5Nick LappinX100.005936926072846958585657595573674871600
6Nikita JevpalovsX100.006637875679939155575454565569656071600
7Nicholas MerkleyX100.005537876269868061706354565863627871600
8Zack MacEwenX100.006143845984777158625957595565635374600
9Isac Lundestrom (R)X100.005435936271746361726253645360628371600
10Stephen GiontaX100.005935936063726258675956645186763571600
11Chris BreenX100.008439835599878153305450614578705538650
12Dylan McIlrathX100.007540795896856856305553724873677138650
13Philippe MyersX100.007839836391856861306258634863625470650
14Mark BarberioX100.005636846277785061306658764877694038640
15Matt IrwinX100.008254796379695762306856645180722771640
16Kevin GravelX100.005636935989776358306153684972674671630
17Timothy LiljegrenX100.006437896073857958305652615360628371620
18Joe HickettsX100.005637885964897058305753684665635338610
19Jake Bean (R)X100.005536916175787160305855574761638571600
Rayé
1Jonathan Dahlen (R)X100.005236926157918659635856526063627360590
2Nikita Popugaev (R)X100.007935945596767054565253615461636460590
3Aaron LuchukX100.005035955657787255575453505463626322550
4Cam Dineen (R)X100.005335945558918654305352515461637060570
MOYENNE D'ÉQUIPE100.00643888607681735949595662547066606162
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
1Josef Korenar100.00797573747877797877797861655371730
2Spencer Martin100.00757270857473757473757467715271720
Rayé
1Martin Ouellette (R)100.00776563697675777675777675814525720
2Felix Sandstrom (R)100.00746462797372747372747363677525690
3Stuart Skinner (R)100.00716563887069717069717061657625680
MOYENNE D'ÉQUIPE100.0075686679747375747375746570604371
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Scott Gordon81788481847863USA5641,000,000$


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
1Dale WeiseStars (Dal)LW/RW251315281756106833108266312.04%451520.6323529770002911039.47%3800001.0915101451
2Isac LundestromStars (Dal)C257182517203428613388.14%443317.341671979000051162.04%54800001.1500000221
3Nick LappinStars (Dal)RW25910191820262456173516.07%642717.104592292000003168.75%3200000.8900000123
4Roope HintzDallas StarsLW157815522036335993911.86%028318.8704411431011380063.79%29000001.0602000032
5Philippe MyersStars (Dal)D255101585210502744163011.36%1650620.273582678000179000.00%000000.5900100210
6Jake BeanStars (Dal)D2531114860181830101810.00%440916.362351885000020000.00%000000.6800000101
7Nicholas MerkleyStars (Dal)RW2548120607544914298.16%243217.2844877800031200055.68%44900000.5611000001
8Peter HollandStars (Dal)C255510512024313294115.63%628811.55000000000682062.65%16600000.6925000101
9Kevin GravelStars (Dal)D25191071201818811212.50%1942216.91000020000107100.00%000000.4700000101
10T.J. HensickStars (Dal)RW253695008193510148.57%11997.9700000000002066.67%1200000.9000000100
11Stephen GiontaStars (Dal)C25358540518365298.33%61997.9800000000001060.00%1500000.8000000000
12Jonathan DahlenStars (Dal)LW1544848071132112412.50%123915.99213644000001050.00%1400000.6701000002
13Zack MacEwenStars (Dal)C252575331537284510324.44%839415.80000000111490153.19%4700000.3500003100
14Timothy LiljegrenStars (Dal)D2515678013152414214.17%2155522.2202215840110107000.00%000000.2200000010
15Matt IrwinStars (Dal)D2514533604412141077.14%2134513.83000411000093100.00%000000.2900000001
16Nikita JevpalovsStars (Dal)RW253140202116358158.57%72339.3300000000000072.73%1100000.3400000100
17Nikita PopugaevStars (Dal)LW151120140186174125.88%115110.1100002000070185.71%700000.2600000010
18Cam DineenStars (Dal)D151010000552720.00%317811.9210144400003100.00%000000.1100000000
Stats d'équipe Total ou en Moyenne410731251981142753540341071518946610.21%130621715.16193352161727123879214460.10%162900000.64414204151514
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
1Josef KorenarStars (Dal)2518430.9301.49152702385410100.87516250232
Stats d'équipe Total ou en Moyenne2518430.9301.49152702385410100.87516250232


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
Aaron LuchukStars (Dal)C221997-04-04No180 Lbs5 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Cam DineenStars (Dal)D211998-06-19Yes183 Lbs5 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
Chris BreenStars (Dal)D301989-06-29No226 Lbs6 ft7NoNoNo1Sans RestrictionPro & Farm300,000$0$0$NoLien
Dale WeiseStars (Dal)LW/RW301988-08-05No206 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm936,481$0$0$NoLien
Devante Smith-PellyStars (Dal)LW/RW271992-06-14No223 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm1,000,000$0$0$NoLien
Dylan McIlrathStars (Dal)D271992-04-20No236 Lbs6 ft5NoNoNo4Avec RestrictionPro & Farm963,777$0$0$NoLien
Felix SandstromStars (Dal)G221997-01-12Yes191 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Isac LundestromStars (Dal)C191999-11-06Yes187 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Jake BeanStars (Dal)D211998-06-09Yes186 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Joe HickettsStars (Dal)D231996-05-04No180 Lbs5 ft8NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Jonathan DahlenStars (Dal)LW211997-12-20Yes176 Lbs5 ft1NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Josef KorenarStars (Dal)G211998-01-31No185 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Kevin GravelStars (Dal)D271992-03-06No211 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm973,000$0$0$NoLien
Mark BarberioStars (Dal)D291990-03-23No200 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm995,999$0$0$NoLien
Martin OuelletteStars (Dal)G271991-12-30Yes160 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Matt IrwinStars (Dal)D311987-11-29No207 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Nicholas MerkleyStars (Dal)RW221997-05-23No194 Lbs5 ft10NoNoNo3Contrat d'EntréePro & Farm900,000$0$0$NoLien
Nick LappinStars (Dal)RW261992-11-01No175 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Nikita JevpalovsStars (Dal)RW241994-09-09No210 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$NoLien
Nikita PopugaevStars (Dal)LW201998-11-20Yes217 Lbs6 ft6NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Peter HollandStars (Dal)C281991-01-14No193 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm915,775$0$0$NoLien
Philippe MyersStars (Dal)D221997-01-25No210 Lbs6 ft5NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Spencer MartinStars (Dal)G241995-06-08No210 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm500,000$0$0$NoLien
Stephen GiontaStars (Dal)C351983-10-09No177 Lbs5 ft7NoNoNo1Sans RestrictionPro & Farm300,000$0$0$NoLien
Stuart SkinnerStars (Dal)G201998-11-01Yes206 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$NoLien
T.J. HensickStars (Dal)RW331985-12-10No190 Lbs5 ft10NoNoNo1Sans RestrictionPro & Farm498,888$0$0$NoLien
Timothy LiljegrenStars (Dal)D201999-04-30No192 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Zack MacEwenStars (Dal)C221996-07-08No205 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2824.79197 Lbs6 ft02.57610,140$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Dale WeiseIsac LundestromNick Lappin40122
2Zack MacEwen30122
3Nicholas MerkleyNikita Jevpalovs20122
4T.J. HensickPeter HollandStephen Gionta10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Timothy LiljegrenPhilippe Myers40122
2Kevin GravelJake Bean30122
3Matt Irwin20122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Dale WeiseIsac LundestromNicholas Merkley60122
2Nick Lappin40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Timothy LiljegrenJake Bean60122
2Philippe Myers40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Nicholas MerkleyDale Weise60122
2Peter Holland40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt IrwinKevin Gravel60122
2Philippe MyersTimothy Liljegren40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Peter Holland60122Matt IrwinKevin Gravel60122
240122Philippe MyersTimothy Liljegren40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Isac Lundestrom60122
2Zack MacEwen40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Timothy LiljegrenJake Bean60122
2Philippe Myers40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Dale WeisePeter HollandNicholas MerkleyMatt IrwinKevin Gravel
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Peter HollandDale WeiseMatt IrwinKevin Gravel
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Peter Holland, Isac Lundestrom, , Nikita JevpalovsZack MacEwen
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Matt Irwin, Kevin Gravel, Timothy LiljegrenMatt IrwinKevin Gravel, Matt Irwin
Tirs de Pénalité
, Dale Weise, Peter Holland, , Nicholas Merkley
Gardien
#1 : Josef Korenar, #2 : Spencer Martin


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
1Admirals52100101121203100010167-12110000065160.6001221330034221841302472382392313328619924625.00%28485.71%043676556.99%39570456.11%20233660.12%671484553176305156
2Barracuda10000010321100000103210000000000021.000347003422184212472382392323314134125.00%70100.00%043676556.99%39570456.11%20233660.12%671484553176305156
3Condors11000000514000000000001100000051421.000591400342218449247238239232596163133.33%30100.00%043676556.99%39570456.11%20233660.12%671484553176305156
4Griffins330000001468110000006242200000084461.0001424380034221848624723823923481427519444.44%10370.00%143676556.99%39570456.11%20233660.12%671484553176305156
5IceHogs220000001129110000007161100000041341.00011203100342218410124723823923369103710110.00%50100.00%043676556.99%39570456.11%20233660.12%671484553176305156
6Moose11000000413110000004130000000000021.0004711003422184342472382392324589400.00%40100.00%043676556.99%39570456.11%20233660.12%671484553176305156
7Rampage531000011284210000016513210000063370.700122032003422184112247238239231163568992827.14%26388.46%043676556.99%39570456.11%20233660.12%671484553176305156
8Reign11000000716000000000001100000071621.00071421003422184512472382392311210235480.00%50100.00%043676556.99%39570456.11%20233660.12%671484553176305156
Total2515400132774037136200122362214129200010411823390.78077130207023422184730247238239235411392954511062018.87%1261191.27%143676556.99%39570456.11%20233660.12%671484553176305156
10Wild41100020752311000103211000001043160.7507916013422184962472382392390265564900.00%25196.00%043676556.99%39570456.11%20233660.12%671484553176305156
11Wolves211000002201010000012-11100000010120.5002240134221845024723823923358364010110.00%130100.00%043676556.99%39570456.11%20233660.12%671484553176305156
_Since Last GM Reset2515400132774037136200122362214129200010411823390.78077130207023422184730247238239235411392954511062018.87%1261191.27%143676556.99%39570456.11%20233660.12%671484553176305156
_Vs Conference2213400122633627115200112291910118200010341717330.7506310516802342218462424723823923483129263406931516.13%1101190.00%143676556.99%39570456.11%20233660.12%671484553176305156

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2539W17713020773054113929545102
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2515401327740
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
136201223622
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
129200104118
Derniers 10 Matchs
WLOTWOTL SOWSOL
420112
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1062018.87%1261191.27%1
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
247238239233422184
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
43676556.99%39570456.11%20233660.12%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
671484553176305156


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 - 2019-09-045Griffins2Stars6WSommaire du Match
4 - 2019-09-0519Admirals2Stars3WSommaire du Match
10 - 2019-09-1139Stars4Wild3WXXSommaire du Match
11 - 2019-09-1250Stars4IceHogs1WSommaire du Match
15 - 2019-09-1665Stars4Griffins1WSommaire du Match
17 - 2019-09-1878Wild1Stars0LSommaire du Match
18 - 2019-09-1991Wild0Stars1WSommaire du Match
24 - 2019-09-25113Wolves2Stars1LSommaire du Match
25 - 2019-09-26127Barracuda2Stars3WXXSommaire du Match
31 - 2019-10-02151Stars7Reign1WSommaire du Match
32 - 2019-10-03166Stars5Condors1WSommaire du Match
39 - 2019-10-10201Rampage1Stars3WSommaire du Match
40 - 2019-10-11208Stars4Rampage1WSommaire du Match
43 - 2019-10-14220Moose1Stars4WSommaire du Match
45 - 2019-10-16231IceHogs1Stars7WSommaire du Match
52 - 2019-10-23273Stars2Rampage1WSommaire du Match
53 - 2019-10-24287Rampage4Stars3LXXSommaire du Match
54 - 2019-10-25295Stars0Rampage1LSommaire du Match
59 - 2019-10-30314Stars1Admirals2LSommaire du Match
60 - 2019-10-31325Stars4Griffins3WSommaire du Match
61 - 2019-11-01336Stars1Wolves0WSommaire du Match
64 - 2019-11-04345Admirals2Stars1LXSommaire du Match
66 - 2019-11-06357Admirals3Stars2LXXSommaire du Match
71 - 2019-11-11388Wild1Stars2WXXSommaire du Match
73 - 2019-11-13398Stars5Admirals3WSommaire du Match
74 - 2019-11-14407Stars-IceHogs-
77 - 2019-11-17422Stars-Wolves-
80 - 2019-11-20444Rampage-Stars-
81 - 2019-11-21460Stars-Rampage-
86 - 2019-11-26474Rampage-Stars-
88 - 2019-11-28496Reign-Stars-
89 - 2019-11-29502Stars-Rampage-
94 - 2019-12-04526Moose-Stars-
95 - 2019-12-05541Moose-Stars-
99 - 2019-12-09557Condors-Stars-
101 - 2019-12-11569IceHogs-Stars-
102 - 2019-12-12583Wild-Stars-
106 - 2019-12-16604Stars-Gulls-
108 - 2019-12-18614Stars-Barracuda-
109 - 2019-12-19628Stars-Heat-
111 - 2019-12-21642Stars-Roadrunners-
113 - 2019-12-23651Stars-Roadrunners-
115 - 2019-12-25664Heat-Stars-
116 - 2019-12-26680Gulls-Stars-
121 - 2019-12-31682Griffins-Stars-
127 - 2020-01-06721Stars-Admirals-
130 - 2020-01-09742Stars-Moose-
131 - 2020-01-10750Stars-Moose-
133 - 2020-01-12759Stars-IceHogs-
136 - 2020-01-15777Roadrunners-Stars-
137 - 2020-01-16790Roadrunners-Stars-
140 - 2020-01-19807Stars-Wild-
142 - 2020-01-21814Stars-Wolves-
143 - 2020-01-22820Stars-Griffins-
145 - 2020-01-24844Stars-Wolves-
148 - 2020-01-27853Admirals-Stars-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29863Wolves-Stars-
151 - 2020-01-30877Wolves-Stars-
154 - 2020-02-02889Stars-Admirals-
155 - 2020-02-03891Stars-Griffins-
158 - 2020-02-06919Stars-Rampage-
159 - 2020-02-07929Rampage-Stars-
162 - 2020-02-10940Stars-Moose-
164 - 2020-02-12951Stars-Moose-
166 - 2020-02-14970Stars-IceHogs-
169 - 2020-02-17982Griffins-Stars-
171 - 2020-02-19990Wolves-Stars-
172 - 2020-02-201004Griffins-Stars-
176 - 2020-02-241024Moose-Stars-
178 - 2020-02-261034Stars-Wild-
179 - 2020-02-271046Stars-Wild-
185 - 2020-03-041080IceHogs-Stars-
186 - 2020-03-051094IceHogs-Stars-
190 - 2020-03-091110Rampage-Stars-
192 - 2020-03-111124Stars-Rampage-
193 - 2020-03-121138Rampage-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
25 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
442,090$ 170,840$ 21,320$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 65,798$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 121 6,035$ 730,235$




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
1425154001327740371362001223622141292000104118233977130207023422184730247238239235411392954511062018.87%1261191.27%143676556.99%39570456.11%20233660.12%671484553176305156
Total Saison Régulière25154001327740371362001223622141292000104118233977130207023422184730247238239235411392954511062018.87%1261191.27%143676556.99%39570456.11%20233660.12%671484553176305156