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Connexion

Stars
GP: 82 | W: 56 | L: 20 | OTL: 6 | P: 118
GF: 299 | GA: 191 | PP%: 20.00% | PK%: 87.18%
DG: Julien Desrosiers | Morale : 50 | Moyenne d’équipe : 57
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Centre de jeu
Stars
56-20-6, 118pts
2
FINAL
5 Chiefs
31-39-12, 74pts
Team Stats
W1StreakL1
28-10-3Home Record16-18-7
28-10-3Away Record15-21-5
6-2-2Last 10 Games5-5-0
3.65Buts par match 3.20
2.33Buts contre par match 4.00
20.00%Pourcentage en avantage numérique23.58%
87.18%Pourcentage en désavantage numérique75.70%
Chiefs
31-39-12, 74pts
1
FINAL
6 Stars
56-20-6, 118pts
Team Stats
L1StreakW1
16-18-7Home Record28-10-3
15-21-5Away Record28-10-3
5-5-0Last 10 Games6-2-2
3.20Buts par match 3.65
4.00Buts contre par match 2.33
23.58%Pourcentage en avantage numérique20.00%
75.70%Pourcentage en désavantage numérique87.18%
Meneurs d'équipe
Buts
Nathan Smith
42
Passes
Alexander Holtz
50
Points
Nathan Smith
91
Plus/Moins
Nathan Smith
58
Victoires
Spencer Knight
53
Pourcentage d’arrêts
Spencer Knight
0.93

Statistiques d’équipe
Buts pour
299
3.65 GFG
Tirs pour
3136
38.24 Avg
Pourcentage en avantage numérique
20.0%
50 GF
Début de zone offensive
42.3%
Buts contre
191
2.33 GAA
Tirs contre
2636
32.15 Avg
Pourcentage en désavantage numérique
87.2%%
25 GA
Début de la zone défensive
39.1%
Informations de l'équipe

Directeur généralJulien Desrosiers
DivisionNord
ConférenceOuest
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,998
Billets de saison300


Informations de la formation

Équipe Pro23
Équipe Mineure18
Limite contact 41 / 50
Espoirs16


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 SPÂgeContratSalaire moyen
1Max ComtoisX100.00866975788067797243656262255959050640221792,500$
2Taylor RaddyshXX100.00794595748063766836626869255353050640232750,000$
3Sam SteelXX100.006541918167638163696659682562620506302321,000,000$
4Jordan MartinookXXX100.007944887971597761426259622569710506202921,500,000$
5Tobias RiederXXX100.006241978367587155295156832469700506202811,700,000$
6Nathan SmithX100.00914693707167417474657263254444050620223650,000$
7Alexander Holtz (R)X100.00674292787062627025675569254444050610192925,000$
8Alexander VolkovX100.00714393767255675436586666245960050600241864,167$
9Egor Afanasyev (R)XXX100.00787682707658585873555665534444050580204789,167$
10Filip Cederqvist (R)X100.00535099657768895162464748495858050540214850,000$
11Jake BeanX100.006742888069818066256150777557580506702322,450,000$
12Ty SmithX100.00694289846474836725574966255757050650213863,333$
13Alec Regula (R)X100.00794577707875646725394978254545050640213866,667$
14Thomas Harley (R)X100.00734393787363756125484863254747050610202894,167$
15Zachary Jones (R)X100.00614099706266636125524773754646050600202925,000$
16Louie BelpedioX100.00687064637055565525455159484444050550251750,000$
17Albert Johansson (R)X100.00433699686167924625453844405454050530204820,000$
Rayé
1Liam Hawel (R)X100.00737289627249504964524162414444050520222525,000$
2Linus Karlsson (R)X100.00474481676564854755434154455456050520213700,000$
3Antonio Stranges (R)XX100.00686098626051544558424158414444050500193560,000$
4Niklas Nordgren (R)X100.00474380646336393749353243355050050430213700,000$
5Joni Ikonen (R)X100.00403797636229283349263439385454050400222825,000$
MOYENNE D’ÉQUIPE100.0067498972706067574352516237535305058
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 SPÂgeContratSalaire moyen
1Magnus Chrona (R)100.0045575489394450464243435046050500213560,000$
Rayé
MOYENNE D’ÉQUIPE100.004557548939445046424343504605050
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Nathan SmithStars (Dal)C82424991583801681903679930111.44%16151518.486915301200001767056.91%168500011.2000000797
2Alexander HoltzStars (Dal)RW822450742810041135300842318.00%11152918.66581351198000007229.67%9100110.9701000235
3Alexander VolkovStars (Dal)RW8133326525180601142858619511.58%9125615.521128410000011134.57%8100011.0300000436
4Tobias RiederStars (Dal)C/LW/RW81273764248038138311962028.68%36149018.404711512100003943234.95%18600110.8613000227
5Taylor RaddyshStars (Dal)C/RW652242642380122133226581729.73%25137821.21116174016810171474140.39%164400120.9326000921
6Ty SmithStars (Dal)D82124557263201279014551738.28%104187322.8551823702260000163100.00%000000.6100000321
7Jordan MartinookStars (Dal)C/LW/RW81272855252751261042166019012.50%18155219.164610261990002644143.87%21200000.7100010344
8Egor AfanasyevStars (Dal)C/LW/RW82203454337420147161238641718.40%14131516.040003230001644057.35%95200000.8200112027
9Alec RegulaStars (Dal)D82193453236410212851766910810.80%141180021.954711532060110144310.00%100000.5900002437
10Sam SteelStars (Dal)C/LW79193453-38084194261831927.28%14164520.8377144319800041412156.34%127800100.6416000254
11Max ComtoisStars (Dal)LW53232346214351841111686915413.69%10107420.27639261090110731145.71%28000000.8614010463
12Zachary JonesStars (Dal)D826384434100436610135695.94%102140317.120331481000076110.00%000000.6300000112
13Jake BeanStars (Dal)D3882533516066769535688.42%7595825.2267133799000286100.00%000000.6900000221
14Thomas HarleyStars (Dal)D825212625220112568729655.75%74169620.69134311910002150100.00%000000.3100000010
15Louie BelpedioStars (Dal)D811181927700184364925242.04%78121615.0200017000031100.00%000000.3100000011
16Liam HawelStars (Dal)C762810616104159489284.17%105827.6600001000041049.70%49500000.3400002000
17Filip CederqvistStars (Dal)LW7935812205194114297.32%686110.9000001000030056.14%5700000.1900000001
18Albert JohanssonStars (Dal)D8214524409814437.14%3396911.82000048000038000.00%000000.1000000000
19Linus KarlssonStars (Dal)C60022100252330.00%1971.62000118000010041.94%6200000.4100000000
20Antonio StrangesStars (Dal)C/LW31101-1007342325.00%11093.54000010000190070.00%1000000.1800000000
21Niklas NordgrenStars (Dal)RW2000000101010.00%13517.9100001000000040.00%500000.00%00000000
Statistiques d’équipe totales ou en moyenne14632955298244164705017791783313597522829.41%7792436216.6550951454852156123221384521150.33%703900460.68520136434657
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 KnightDallas76531650.9302.2244166916323180120.833187601293
2Magnus ChronaStars (Dal)113410.9272.5454320233160000.6673682000
Statistiques d’équipe totales ou en moyenne87562060.9292.2549608918626340122182821293


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 moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Albert JohanssonStars (Dal)D202001-01-04Yes168 Lbs6 ft0NoNoNo4Pro & Farm820,000$0$0$No820,000$820,000$820,000$Lien
Alec RegulaStars (Dal)D212000-08-05Yes208 Lbs6 ft4NoNoNo3Pro & Farm866,667$0$0$No866,667$866,667$Lien
Alexander HoltzStars (Dal)RW192002-01-23Yes194 Lbs6 ft0NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Alexander VolkovStars (Dal)RW241997-08-01No195 Lbs6 ft1NoNoYes1Pro & Farm864,167$0$0$NoLien
Antonio StrangesStars (Dal)C/LW192002-02-05Yes168 Lbs5 ft10NoNoNo3Pro & Farm560,000$0$0$No560,000$560,000$Lien
Egor AfanasyevStars (Dal)C/LW/RW202001-01-23Yes203 Lbs6 ft3NoNoNo4Pro & Farm789,167$0$0$No789,167$789,167$789,167$Lien
Filip CederqvistStars (Dal)LW212000-08-23Yes207 Lbs6 ft4NoNoNo4Pro & Farm850,000$0$0$No850,000$850,000$850,000$Lien
Jake BeanStars (Dal)D231998-06-09No186 Lbs6 ft1NoNoNo2Pro & Farm2,450,000$0$0$No2,450,000$Lien
Joni IkonenStars (Dal)C221999-04-14Yes172 Lbs5 ft11NoNoNo2Pro & Farm825,000$0$0$No825,000$Lien
Jordan Martinook (contrat à 1 volet)Stars (Dal)C/LW/RW291992-07-25No196 Lbs6 ft0NoNoYes2Pro & Farm1,500,000$600,000$0$No1,500,000$Lien
Liam HawelStars (Dal)C221999-04-18Yes183 Lbs6 ft5NoNoNo2Pro & Farm525,000$0$0$No525,000$Lien
Linus KarlssonStars (Dal)C211999-11-16Yes179 Lbs6 ft1NoNoNo3Pro & Farm700,000$0$0$No700,000$700,000$Lien
Louie BelpedioStars (Dal)D251996-05-14No197 Lbs5 ft11NoNoYes1Pro & Farm750,000$0$0$NoLien
Magnus ChronaStars (Dal)G212000-08-28Yes216 Lbs6 ft6NoNoNo3Pro & Farm560,000$0$0$No560,000$560,000$Lien
Max ComtoisStars (Dal)LW221999-01-08No215 Lbs6 ft2NoNoNo1Pro & Farm792,500$0$0$NoLien
Nathan SmithStars (Dal)C221998-10-18No190 Lbs6 ft1NoNoNo3Pro & Farm650,000$0$0$No650,000$650,000$Lien
Niklas NordgrenStars (Dal)RW212000-05-04Yes183 Lbs5 ft9NoNoNo3Pro & Farm700,000$0$0$No700,000$700,000$Lien
Sam SteelStars (Dal)C/LW231998-02-03No189 Lbs5 ft11NoNoNo2Pro & Farm1,000,000$0$0$No1,000,000$Lien
Taylor RaddyshStars (Dal)C/RW231998-02-18No216 Lbs6 ft3NoNoNo2Pro & Farm750,000$0$0$No750,000$Lien
Thomas HarleyStars (Dal)D202001-08-18Yes190 Lbs6 ft3NoNoNo2Pro & Farm894,167$0$0$No894,167$Lien
Tobias Rieder (contrat à 1 volet)Stars (Dal)C/LW/RW281993-01-09No186 Lbs5 ft11NoNoYes1Pro & Farm1,700,000$800,000$0$NoLien
Ty SmithStars (Dal)D212000-03-23No175 Lbs5 ft11NoNoNo3Pro & Farm863,333$0$0$No863,333$863,333$Lien
Zachary JonesStars (Dal)D202000-10-18Yes172 Lbs5 ft10NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2322.04191 Lbs6 ft12.39924,348$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Max ComtoisTaylor RaddyshTobias Rieder40122
2Jordan MartinookSam SteelAlexander Holtz30122
3Egor AfanasyevNathan SmithAlexander Volkov20122
4Filip CederqvistMax Comtois10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Albert JohanssonTy Smith40122
2Alec RegulaThomas Harley30122
3Zachary JonesLouie Belpedio20122
4Albert JohanssonTy Smith10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Max ComtoisTaylor RaddyshTobias Rieder60122
2Jordan MartinookSam SteelAlexander Holtz40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Albert JohanssonTy Smith60122
2Alec RegulaThomas Harley40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Max ComtoisTaylor Raddysh60122
2Sam SteelTobias Rieder40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zachary JonesTy Smith60122
2Alec RegulaThomas Harley40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Max Comtois60122Albert JohanssonTy Smith60122
2Taylor Raddysh40122Alec RegulaThomas Harley40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Max ComtoisTaylor Raddysh60122
2Sam SteelTobias Rieder40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Louie BelpedioTy Smith60122
2Alec RegulaThomas Harley40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Max ComtoisTaylor RaddyshTobias RiederAlec RegulaTy Smith
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Max ComtoisTaylor RaddyshTobias RiederAlec RegulaTy Smith
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Nathan Smith, Alexander Volkov, Egor AfanasyevNathan Smith, Alexander VolkovEgor Afanasyev
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Zachary Jones, Louie Belpedio, Albert JohanssonZachary JonesLouie Belpedio, Albert Johansson
Tirs de pénalité
Max Comtois, Taylor Raddysh, Sam Steel, Tobias Rieder, Nathan Smith
Gardien
#1 : , #2 : Magnus Chrona


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
TotalDomicileVisiteur
# 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
1Admirals32000100862210001005501100000031250.8338122000971079061029861033109839742035585240.00%90100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
2Baby Hawks42100001972220000007252010000125-350.62591524119710790613298610331098391353231767114.29%13192.31%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
3Bears21100000743110000005051010000024-220.50071219019710790657986103310983979211244900.00%60100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
4Bruins210001008711000010034-11100000053230.75081624009710790675986103310983962208536350.00%4250.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
5Cabaret Lady Mary Ann2200000015411110000008351100000071641.00015254000971079061339861033109839631614404125.00%70100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
6Caroline2110000078-11010000014-31100000064220.50071320009710790681986103310983956216448225.00%30100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
7Chiefs321000001266110000006152110000065140.66712223401971079061159861033109839762911621218.33%30100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
8Chill422000001112-12110000068-22110000054140.500112132009710790614698610331098391455321897114.29%80100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
9Comets3300000015692200000011471100000042261.0001529440097107906112986103310983910324236913215.38%8187.50%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
10Cougars22000000835110000004221100000041341.00081422009710790660986103310983968151435600.00%7185.71%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
11Crunch20000011880100000103211000000156-130.750814220097107906889861033109839872316586350.00%7271.43%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
12Heat3200010014862200000012571000010023-150.8331426400097107906129986103310983985336726233.33%30100.00%11519299450.73%1408276450.94%625131747.46%2107147617825871074556
13Jayhawks430000101468220000008352100001063381.000142539009710790614298610331098391364229877114.29%11190.91%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
14Las Vegas3300000015691100000052322000000104661.000152540009710790612598610331098398523256813430.77%50100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
15Manchots211000007611010000023-11100000053220.50071118009710790681986103310983946136387114.29%3166.67%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
16Marlies22000000725110000002111100000051441.0007121900971079066998610331098394915144817211.76%7185.71%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
17Minnesota4120001014113211000008532010001066040.5001423370197107906175986103310983913930201001300.00%9455.56%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
18Monarchs3300000017891100000042222000000136761.000173148009710790615498610331098399929108610440.00%50100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
19Monsters21001000312110000001011000100021141.000358019710790665986103310983965171448700.00%7185.71%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
20Monsters431000001688211000008622200000082660.7501629450197107906149986103310983912241207711436.36%9188.89%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
21Oceanics31200000981211000008531010000013-220.33391827009710790610498610331098391142919607114.29%70100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
22Oil Kings321000006601010000014-32200000052340.6676121800971079061079861033109839993314586233.33%6183.33%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
23Phantoms210000018711000000134-11100000053230.7508142200971079066498610331098397218144011327.27%60100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
24Rocket220000001156110000004311100000072541.0001119300097107906679861033109839591912355120.00%5180.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
25Seattle3120000057-21010000013-22110000044020.333591401971079061029861033109839913116518112.50%6183.33%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
26Senators210000101275100000104311100000084441.0001219310097107906759861033109839812814467342.86%7357.14%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
27Sharks321000001156220000009271010000023-140.66711193000971079061219861033109839942512738225.00%50100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
28Sound Tigers2110000067-1110000004311010000024-220.50061117009710790671986103310983976148376116.67%4175.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
29Spiders2020000015-41010000013-21010000002-200.00012310971079067498610331098396623846300.00%3166.67%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
30Thunder22000000514110000002021100000031241.0005712019710790659986103310983953171838700.00%90100.00%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
31Wolf Pack2110000010641010000056-11100000050520.5001019290197107906102986103310983957258438225.00%3166.67%01519299450.73%1408276450.94%625131747.46%2107147617825871074556
Total825120013432991911084126100022115198534125100112214893551180.720299529828299710790631369861033109839263677947817792505020.00%1952587.18%11519299450.73%1408276450.94%625131747.46%2107147617825871074556
_Since Last GM Reset825120013432991911084126100022115198534125100112214893551180.720299529828299710790631369861033109839263677947817792505020.00%1952587.18%11519299450.73%1408276450.94%625131747.46%2107147617825871074556
_Vs Conference4429900132169997021155000108749382314400122825032670.76116930046915971079061717986103310983914044122579321252520.00%1021486.27%11519299450.73%1408276450.94%625131747.46%2107147617825871074556
_Vs Division26810001185582713410001051302113400000134286190.365851532381497107906963986103310983986725615155164914.06%60788.33%01519299450.73%1408276450.94%625131747.46%2107147617825871074556

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
82118W129952982831362636779478177929
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8251201343299191
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
412610022115198
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
412510112214893
Derniers 10 matchs
WLOTWOTL SOWSOL
620002
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2505020.00%1952587.18%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
986103310983997107906
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
1519299450.73%1408276450.94%625131747.46%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2107147617825871074556


Derniers matchs 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
7 - 2022-10-1316Stars3Chill1AWSommaire du match
9 - 2022-10-1535Chill1Stars2BWSommaire du match
11 - 2022-10-1746Oceanics1Stars5BWSommaire du match
14 - 2022-10-2061Stars5Marlies1AWSommaire du match
16 - 2022-10-2279Stars7Rocket2AWSommaire du match
18 - 2022-10-2492Stars8Senators4AWSommaire du match
19 - 2022-10-25100Stars5Bruins3AWSommaire du match
21 - 2022-10-27117Bears0Stars5BWSommaire du match
23 - 2022-10-29127Wolf Pack6Stars5BLSommaire du match
26 - 2022-11-01153Monarchs2Stars4BWSommaire du match
28 - 2022-11-03172Stars2Jayhawks1AWXXSommaire du match
30 - 2022-11-05178Stars2Oil Kings1AWSommaire du match
33 - 2022-11-08204Stars1Oceanics3ALSommaire du match
36 - 2022-11-11223Sharks1Stars4BWSommaire du match
38 - 2022-11-13238Stars5Phantoms3AWSommaire du match
40 - 2022-11-15248Stars3Thunder1AWSommaire du match
42 - 2022-11-17262Stars7Cabaret Lady Mary Ann1AWSommaire du match
44 - 2022-11-19284Sound Tigers3Stars4BWSommaire du match
46 - 2022-11-21298Monsters1Stars4BWSommaire du match
48 - 2022-11-23313Baby Hawks2Stars4BWSommaire du match
50 - 2022-11-25330Oceanics4Stars3BLSommaire du match
51 - 2022-11-26339Stars4Monsters2AWSommaire du match
53 - 2022-11-28350Stars4Chiefs0AWSommaire du match
56 - 2022-12-01371Admirals3Stars2BLXSommaire du match
59 - 2022-12-04393Minnesota0Stars6BWSommaire du match
61 - 2022-12-06409Marlies1Stars2BWSommaire du match
63 - 2022-12-08423Senators3Stars4BWXXSommaire du match
65 - 2022-12-10435Cougars2Stars4BWSommaire du match
67 - 2022-12-12449Stars5Manchots3AWSommaire du match
68 - 2022-12-13456Stars0Spiders2ALSommaire du match
70 - 2022-12-15471Stars2Bears4ALSommaire du match
72 - 2022-12-17487Stars6Caroline4AWSommaire du match
74 - 2022-12-19502Stars2Monsters1AWXSommaire du match
76 - 2022-12-21522Oil Kings4Stars1BLSommaire du match
78 - 2022-12-23541Rocket3Stars4BWSommaire du match
82 - 2022-12-27551Stars2Chill3ALSommaire du match
84 - 2022-12-29569Stars4Minnesota3AWXXSommaire du match
86 - 2022-12-31586Sharks1Stars5BWSommaire du match
89 - 2023-01-03608Stars5Monarchs2AWSommaire du match
90 - 2023-01-04611Stars3Admirals1AWSommaire du match
94 - 2023-01-08637Cabaret Lady Mary Ann3Stars8BWSommaire du match
96 - 2023-01-10653Stars2Sound Tigers4ALSommaire du match
98 - 2023-01-12663Stars5Wolf Pack0AWSommaire du match
100 - 2023-01-14677Heat2Stars6BWSommaire du match
102 - 2023-01-16699Stars4Las Vegas2AWSommaire du match
104 - 2023-01-18716Stars2Sharks3ALSommaire du match
105 - 2023-01-19729Stars8Monarchs4AWSommaire du match
107 - 2023-01-21740Jayhawks2Stars5BWSommaire du match
109 - 2023-01-23753Crunch2Stars3BWXXSommaire du match
111 - 2023-01-25769Caroline4Stars1BLSommaire du match
113 - 2023-01-27785Spiders3Stars1BLSommaire du match
123 - 2023-02-06811Admirals2Stars3BWSommaire du match
125 - 2023-02-08820Minnesota5Stars2BLSommaire du match
128 - 2023-02-11837Thunder0Stars2BWSommaire du match
131 - 2023-02-14861Bruins4Stars3BLXSommaire du match
134 - 2023-02-17880Stars2Minnesota3ALSommaire du match
135 - 2023-02-18887Monsters0Stars1BWSommaire du match
139 - 2023-02-22918Baby Hawks0Stars3BWSommaire du match
142 - 2023-02-25944Stars6Las Vegas2AWSommaire du match
144 - 2023-02-27955Comets2Stars5BWSommaire du match
146 - 2023-03-01970Jayhawks1Stars3BWSommaire du match
147 - 2023-03-02980Stars1Baby Hawks3ALSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2023-03-04997Monsters5Stars4BLSommaire du match
151 - 2023-03-061008Heat3Stars6BWSommaire du match
154 - 2023-03-091025Stars5Crunch6ALXXSommaire du match
156 - 2023-03-111049Stars3Seattle4ALSommaire du match
158 - 2023-03-131063Stars1Seattle0AWSommaire du match
159 - 2023-03-141073Stars4Comets2AWSommaire du match
161 - 2023-03-161086Stars3Oil Kings1AWSommaire du match
163 - 2023-03-181105Stars2Heat3ALXSommaire du match
166 - 2023-03-211130Seattle3Stars1BLSommaire du match
168 - 2023-03-231143Manchots3Stars2BLSommaire du match
170 - 2023-03-251158Comets2Stars6BWSommaire du match
173 - 2023-03-281182Stars1Baby Hawks2ALXXSommaire du match
176 - 2023-03-311203Stars4Jayhawks2AWSommaire du match
177 - 2023-04-011212Stars4Monsters0AWSommaire du match
179 - 2023-04-031227Chill7Stars4BLSommaire du match
182 - 2023-04-061252Phantoms4Stars3BLXXSommaire du match
184 - 2023-04-081269Las Vegas2Stars5BWSommaire du match
186 - 2023-04-101280Stars4Cougars1AWSommaire du match
188 - 2023-04-121296Stars2Chiefs5ALSommaire du match
189 - 2023-04-131307Chiefs1Stars6BWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets205
Assistance81,92841,000
Assistance PCT99.91%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2998 - 99.94% 44,965$1,843,560$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,747,852$ 1,806,001$ 1,806,001$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,505$ 1,747,852$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 9,505$ 0$




Stars Leaders statistiques (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Stars Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Stars Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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

Stars Leaders statistiques (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Stars Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA