Stars

GP: 8 | W: 2 | L: 5 | OTL: 1 | P: 5
GF: 12 | GA: 18 | PP%: 9.52% | PK%: 89.19%
DG: DISPONIBLE | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #93 vs Wolves
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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
1Alex Dostie (R)X100.00716096636059605771456364605555625000
2Justin DowlingXXX100.00734390706657706852605969255152645000
3Warren FoegeleXX100.00734385677265905941707171255960714700
4Adam ErneXX100.00904685727761786557555666756061645000
5Tom KuhnhacklXX100.00764497777359565825606074256063655000
6Tomas NosekXX100.00794590697959855974606272256062675000
7Victor Rask (C)XXX100.00674395727556646266656258366767645000
8Dominik Simon (A)XX100.00734393776967856237686056256364655000
9Matthew Strome (R)X100.00827892557861644950454864464444565000
10Remi ElieX100.00817790607757585650476066574747615000
11Alex Petrovic (R)X100.00838186628160635125474065384444545000
12Connor HobbsX100.00726980596955584525324161395353505000
13Christian Folin (A)X100.00898877757864585825454869256465594700
14Joseph Cecconi (R)X100.00817691617652544425343963374444515000
Rayé
MOYENNE D'ÉQUIPE100.0078608967745967574552556638555661500
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
1Michael Hutchinson100.0053616181574850555853785959555000
2Joey Daccord (R)100.0060607577626455646160304444605000
Rayé
MOYENNE D'ÉQUIPE100.005761687960565360605754525258500
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Derek Lalonde83807985735884USA4631,250,000$


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'ÉquipePOSGP 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
1Tom KuhnhacklStars (DAL)LW/RW806630051177160.00%215919.940221270000190016.67%600000.7500000001
2Warren FoegeleStars (DAL)LW/RW8325-3408131821516.67%118022.552026320000280148.00%7500000.5501000001
3Adam ErneStars (DAL)LW/RW850531202512164631.25%113617.03101429000021120.00%500000.7300000110
4Victor RaskStars (DAL)C/LW/RW814500031811669.09%215519.391122280001200058.99%13900000.6400000100
5Christian FolinStars (DAL)D803311402668170.00%817121.40011530000126000.00%100000.3500000000
6Tomas NosekStars (DAL)C/LW8123-2201522144107.14%016220.260225320000210067.27%16500000.3701000000
7Alex PetrovicStars (DAL)D8022240761050.00%216720.91011130000030000.00%000000.2400000001
8Dominik SimonStars (DAL)LW/RW8112-22061411449.09%217421.820111340001310030.77%1300000.2301000000
9Matthew StromeStars (DAL)LW8022-41552041310.00%813216.53000050000000100.00%100000.3000100000
10Alex DostieStars (DAL)C8011-69561114270.00%212816.0500019000030072.00%2500000.1600010000
11Connor HobbsStars (DAL)D8000-2100710220.00%315219.08000029000023000.00%100000.0000000000
12Justin DowlingStars (DAL)C/LW/RW8000-54091516560.00%113917.410004140002160047.19%8900000.0000000000
13Remi ElieStars (DAL)LW8000-713511812210.00%213116.410001130000120062.50%800000.0000100000
14Joseph CecconiStars (DAL)D8000-2100631030.00%315118.93000030000022000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne112112334-24991515414413042898.46%37214119.1248123134900052601257.01%52800000.3203210213
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
1Michael HutchinsonStars (DAL)82510.9092.0546901161760000.667380111
2Joey DaccordStars (DAL)10000.8004.621300150000.000008000
Stats d'équipe Total ou en Moyenne92510.9062.1248201171810000.667388111


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 Type Salaire Actuel Salaire RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Adam ErneStars (DAL)LW/RW251995-04-20No214 Lbs6 ft1NoNoNo1Pro & Farm894,167$800,424$894,167$800,424$0$0$NoLien
Alex DostieStars (DAL)C231997-04-13Yes165 Lbs5 ft10NoNoNo3Pro & Farm925,000$828,024$925,000$828,024$0$0$No925,000$925,000$
Alex PetrovicStars (DAL)D281992-03-03Yes216 Lbs6 ft4NoNoNo1Pro & Farm1,050,000$939,919$1,050,000$939,919$0$0$NoLien
Christian FolinStars (DAL)D291991-02-09No204 Lbs6 ft3NoNoNo2Pro & Farm1,700,000$1,521,774$1,700,000$1,521,774$0$0$No1,700,000$Lien
Connor HobbsStars (DAL)D231997-01-04No187 Lbs6 ft1NoNoNo1Pro & Farm720,000$644,516$720,000$644,516$0$0$NoLien
Dominik SimonStars (DAL)LW/RW251994-08-08No190 Lbs5 ft11NoNoNo4Pro & Farm750,000$671,371$750,000$671,371$0$0$No750,000$750,000$750,000$Lien
Joey DaccordStars (DAL)G231996-08-19Yes196 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$895,161$1,000,000$895,161$0$0$NoLien
Joseph CecconiStars (DAL)D231997-05-23Yes209 Lbs6 ft2NoNoNo3Pro & Farm1,293,750$1,158,115$1,293,750$1,158,115$0$0$No1,293,750$1,293,750$
Justin DowlingStars (DAL)C/LW/RW291990-10-01No185 Lbs5 ft10NoNoNo1Pro & Farm650,000$581,855$650,000$581,855$0$0$NoLien
Matthew StromeStars (DAL)LW211999-01-05Yes206 Lbs6 ft4NoNoNo3Pro & Farm879,167$786,996$879,167$786,996$0$0$No879,167$879,167$
Michael HutchinsonStars (DAL)G301990-03-01No202 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$895,161$1,000,000$895,161$0$0$NoLien
Remi ElieStars (DAL)LW251995-04-15No210 Lbs6 ft1NoNoNo3Pro & Farm450,000$402,823$450,000$402,823$0$0$No450,000$450,000$Lien
Tom KuhnhacklStars (DAL)LW/RW281992-01-21No196 Lbs6 ft2NoNoNo2Pro & Farm700,000$626,613$700,000$626,613$0$0$No700,000$Lien
Tomas NosekStars (DAL)C/LW271992-08-31No210 Lbs6 ft3NoNoNo2Pro & Farm962,500$861,593$962,500$861,593$0$0$No962,500$Lien
Victor RaskStars (DAL)C/LW/RW271993-03-01No200 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$895,161$1,000,000$895,161$0$0$NoLien
Warren FoegeleStars (DAL)LW/RW241996-04-01No190 Lbs6 ft2NoNoNo1Pro & Farm746,667$668,387$746,667$668,387$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1625.63199 Lbs6 ft21.88920,078$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Warren FoegeleTomas NosekDominik Simon35122
2Tom KuhnhacklVictor RaskAdam Erne30122
3Remi ElieJustin DowlingAlex Dostie25122
4Matthew StromeAlex DostieWarren Foegele10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinAlex Petrovic35122
2Joseph CecconiConnor Hobbs30122
3Matthew Strome25122
4Christian FolinAlex Petrovic10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Warren FoegeleTomas NosekDominik Simon60122
2Tom KuhnhacklVictor RaskAdam Erne40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinAlex Petrovic60122
2Joseph CecconiConnor Hobbs40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Warren FoegeleDominik Simon60122
2Tomas NosekTom Kuhnhackl40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinAlex Petrovic60122
2Joseph CecconiConnor Hobbs40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Warren Foegele60122Christian FolinAlex Petrovic60122
2Dominik Simon40122Joseph CecconiConnor Hobbs40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Warren FoegeleDominik Simon60122
2Tomas NosekTom Kuhnhackl40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Christian FolinAlex Petrovic60122
2Joseph CecconiConnor Hobbs40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Warren FoegeleTomas NosekDominik SimonChristian FolinAlex Petrovic
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Warren FoegeleTomas NosekDominik SimonChristian FolinAlex Petrovic
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Justin Dowling, Remi Elie, Victor RaskJustin Dowling, Remi ElieVictor Rask
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Joseph Cecconi, Connor Hobbs, Christian FolinJoseph CecconiConnor Hobbs, Christian Folin
Tirs de Pénalité
Warren Foegele, Dominik Simon, Tomas Nosek, Tom Kuhnhackl, Victor Rask
Gardien
#1 : Michael Hutchinson, #2 : Joey Daccord


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
Total825000011218-65130000147-331200000811-350.3131223350143501364945423181391011604249.52%37489.19%011519259.90%13323556.60%5510552.38%1841241986210249
_Since Last GM Reset825000011218-65130000147-331200000811-350.3131223350143501364945423181391011604249.52%37489.19%011519259.90%13323556.60%5510552.38%1841241986210249
_Vs Conference724000011217-54120000146-231200000811-350.3571223350143501184945423156329514037410.81%34488.24%011519259.90%13323556.60%5510552.38%1841241986210249
_Vs Division724000011217-54120000146-231200000811-350.3571223350143501184945423156329514037410.81%34488.24%011519259.90%13323556.60%5510552.38%1841241986210249

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
85L11223351361813910116001
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
82500011218
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
513000147
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3120000811
Derniers 10 Matchs
WLOTWOTL SOWSOL
250001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4249.52%37489.19%0
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
49454234350
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
11519259.90%13323556.60%5510552.38%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1841241986210249


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
1 - 2020-09-273Soldiers1Stars0LSommaire du Match
2 - 2020-09-2815Stars2Soldiers5LSommaire du Match
4 - 2020-09-3026Stars2Soldiers3LSommaire du Match
5 - 2020-10-0139Soldiers3Stars1LSommaire du Match
6 - 2020-10-0249Rampage0Stars2WSommaire du Match
9 - 2020-10-0566Soldiers2Stars1LXXSommaire du Match
10 - 2020-10-0670Stars4Soldiers3WSommaire du Match
12 - 2020-10-0886Penguins1Stars0LSommaire du Match
14 - 2020-10-1093Stars-Wolves-
16 - 2020-10-12102Stars-Soldiers-
18 - 2020-10-14111Stars-Rampage-
20 - 2020-10-16128Admirals-Stars-
22 - 2020-10-18143Wolves-Stars-
23 - 2020-10-19154Stars-Wolves-
24 - 2020-10-20159Stars-Monsters-
25 - 2020-10-21171Moose-Stars-
27 - 2020-10-23180Stars-IceHogs-
28 - 2020-10-24189Sharks-Stars-
30 - 2020-10-26204Condors-Stars-
32 - 2020-10-28211Stars-Rampage-
34 - 2020-10-30226Stars-Soldiers-
36 - 2020-11-01231Senators-Stars-
38 - 2020-11-03243Stars-Moose-
40 - 2020-11-05256Wolves-Stars-
42 - 2020-11-07266Stars-IceHogs-
44 - 2020-11-09276Stars-Moose-
45 - 2020-11-10284Wolves-Stars-
46 - 2020-11-11298Rampage-Stars-
48 - 2020-11-13314Rampage-Stars-
49 - 2020-11-14319Stars-Wolves-
50 - 2020-11-15326Stars-Flames-
51 - 2020-11-16340Soldiers-Stars-
52 - 2020-11-17346Stars-Monarchs-
54 - 2020-11-19364Stars-IceHogs-
55 - 2020-11-20369Soldiers-Stars-
56 - 2020-11-21380Stars-Soldiers-
57 - 2020-11-22392Rampage-Stars-
59 - 2020-11-24409Monsters-Stars-
60 - 2020-11-25421Stars-Wolf Pack-
61 - 2020-11-26430Monarchs-Stars-
64 - 2020-11-29443Stars-Rampage-
65 - 2020-11-30454IceHogs-Stars-
66 - 2020-12-01463Stars-Wolves-
67 - 2020-12-02473Monsters-Stars-
68 - 2020-12-03485Stars-Monsters-
70 - 2020-12-05493Stars-Griffins-
71 - 2020-12-06503IceHogs-Stars-
72 - 2020-12-07514Stars-Marlies-
74 - 2020-12-09525Admirals-Stars-
75 - 2020-12-10539Stars-Penguins-
77 - 2020-12-12545Griffins-Stars-
79 - 2020-12-14561Wolves-Stars-
80 - 2020-12-15573Stars-Sound Tigers-
81 - 2020-12-16581Stars-Rocket-
83 - 2020-12-18595Sound Tigers-Stars-
85 - 2020-12-20605Stars-Monarchs-
86 - 2020-12-21614Phantoms-Stars-
87 - 2020-12-22628Sharks-Stars-
89 - 2020-12-24640Stars-Bruins-
91 - 2020-12-26650Stars-Rampage-
92 - 2020-12-27660Bruins-Stars-
94 - 2020-12-29672Wolf Pack-Stars-
95 - 2020-12-30686Crunch-Stars-
96 - 2020-12-31693Stars-IceHogs-
97 - 2021-01-01706Stars-Soldiers-
98 - 2021-01-02716Moose-Stars-
99 - 2021-01-03722Stars-Senators-
101 - 2021-01-05738Condors-Stars-
103 - 2021-01-07752Marlies-Stars-
104 - 2021-01-08766Stars-Flames-
105 - 2021-01-09774Flames-Stars-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10783Stars-Sharks-
108 - 2021-01-12796Stars-Phantoms-
109 - 2021-01-13806Stars-Condors-
110 - 2021-01-14811Soldiers-Stars-
112 - 2021-01-16828Stars-Crunch-
113 - 2021-01-17834Rocket-Stars-
115 - 2021-01-19846Stars-Moose-
116 - 2021-01-20853Stars-Admirals-
117 - 2021-01-21859IceHogs-Stars-
119 - 2021-01-23878Senators-Stars-
122 - 2021-01-26895IceHogs-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
36 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
285,389$ 1,472,126$ 1,472,126$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 154,336$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 111 21,953$ 2,436,783$




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
2020825000011218-65130000147-331200000811-351223350143501364945423181391011604249.52%37489.19%011519259.90%13323556.60%5510552.38%1841241986210249
Total Saison Régulière825000011218-65130000147-331200000811-351223350143501364945423181391011604249.52%37489.19%011519259.90%13323556.60%5510552.38%1841241986210249