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Texas Stars
GP: 32 | W: 14 | L: 15 | OTL: 3 | P: 31
GF: 143 | GA: 152 | PP%: 24.05% | PK%: 73.42%
DG: Mathieu DG | Morale : 50 | Moyenne d’équipe : 60
Prochains matchs #550 vs Iowa Wild

Centre de jeu
Texas Stars
14-15-3, 31pts
1
FINAL
3 Calgary Wranglers
24-11-2, 50pts
Team Stats
L5SéquenceW1
8-9-0Fiche domicile11-5-1
6-6-3Fiche domicile13-6-1
1-8-1Derniers 10 matchs4-6-0
4.47Buts par match 5.03
4.75Buts contre par match 4.51
24.05%Pourcentage en avantage numérique30.85%
73.42%Pourcentage en désavantage numérique69.52%
San Diego Gulls
18-16-3, 39pts
7
FINAL
4 Texas Stars
14-15-3, 31pts
Team Stats
W1SéquenceL5
8-6-3Fiche domicile8-9-0
10-10-0Fiche domicile6-6-3
5-4-1Derniers 10 matchs1-8-1
3.70Buts par match 4.47
4.14Buts contre par match 4.75
23.81%Pourcentage en avantage numérique24.05%
72.73%Pourcentage en désavantage numérique73.42%
Iowa Wild
15-15-3, 33pts
Jour 85
Texas Stars
14-15-3, 31pts
Statistiques d’équipe
L1SéquenceL5
8-7-2Fiche domicile8-9-0
7-8-1Fiche visiteur6-6-3
7-3-010 derniers matchs1-8-1
3.88Buts par match 4.47
4.09Buts contre par match 4.47
21.35%Pourcentage en avantage numérique24.05%
71.43%Pourcentage en désavantage numérique73.42%
Texas Stars
14-15-3, 31pts
Jour 88
Tucson Roadrunners
20-16-0, 40pts
Statistiques d’équipe
L5SéquenceW1
8-9-0Fiche domicile12-5-0
6-6-3Fiche visiteur8-11-0
1-8-110 derniers matchs5-5-0
4.47Buts par match 3.83
4.75Buts contre par match 3.83
24.05%Pourcentage en avantage numérique30.49%
73.42%Pourcentage en désavantage numérique84.71%
Texas Stars
14-15-3, 31pts
Jour 90
Coachella Valley Firebirds
23-7-2, 48pts
Statistiques d’équipe
L5SéquenceL1
8-9-0Fiche domicile11-6-0
6-6-3Fiche visiteur12-1-2
1-8-110 derniers matchs8-2-0
4.47Buts par match 5.25
4.75Buts contre par match 5.25
24.05%Pourcentage en avantage numérique32.93%
73.42%Pourcentage en désavantage numérique74.68%
Meneurs d'équipe
Buts
Jake Lucchini
17
Vincent IorioPasses
Vincent Iorio
28
Points
Jake Lucchini
34
Liam OhgrenPlus/Moins
Liam Ohgren
5

Statistiques d’équipe
Buts pour
143
4.47 GFG
Tirs pour
1259
39.34 Avg
Pourcentage en avantage numérique
24.1%
19 GF
Début de zone offensive
39.2%
Buts contre
152
4.75 GAA
Tirs contre
1291
40.34 Avg
Pourcentage en désavantage numérique
73.4%%
21 GA
Début de la zone défensive
41.0%
Informations de l'équipe

Directeur généralMathieu DG
EntraîneurNicklas Lidstrom
DivisionCentral Division
ConférenceWestern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité9,000
Assistance8,725
Billets de saison8,370


Informations de la formation

Équipe Pro17
Équipe Mineure20
Limite contact 37 / 60
Espoirs14


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
1Jake LucchiniX100.00554370686374706561636158656253050630301775,000$
2Liam OhgrenX100.00644074697273646440616162655550050630212886,667$
3Ville KoivunenX100.00574362675862616243696059635050050620221805,833$
4Noah OstlundX100.00614168685761596142605964625050050610212886,667$
5Viktor NeuchevX100.00574072675760576143605556615050050590221870,000$
6Alex DoucetX100.00604267646363615742565356585150050580231870,000$
7Justin ErtelX100.00614167626260585740555459575050050580222867,500$
8Marc-Edouard VlasicX100.006041837277848571406565736994840507303817,000,000$
9Vincent IorioX100.00664270666863616340595568615050050630231814,167$
10Samuel JohannessonX100.00554068645863626240625661615150050600251870,000$
11Seamus CaseyX100.00584067675859576040595561615050050600212950,000$
12Alec RegulaX100.00614257576357555540545261555150050580252775,000$
13Travis MitchellX100.00585358606765636040545555595250050580261775,000$
Rayé
1Sammy WalkerXXX100.005443717054686663446457576354500506102600$
MOYENNE D’ÉQUIPE100.0059426866636563624360576161555305061
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
1Ales Stezka100.00716667666868706668696356510506202810$
Rayé
1Jan Bednar100.00625757656159605861595450500505602300$
2Jared Moe100.00524848575046454444504452500504602600$
MOYENNE D’ÉQUIPE100.006257576360585856585954535005055
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Nicklas Lidstrom1111111SWE5551$


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
1Jake LucchiniTexas Stars (DAL)C32171734-61004094144209211.81%1161219.1343717460001470154.59%92500001.1123000202
2Noah OstlundTexas Stars (DAL)C3213193201203775103296812.62%843513.61101150001161245.18%52900001.4700000421
3Vincent IorioTexas Stars (DAL)D3242832-1110078525920436.78%7170622.091892966000058100%000000.9100000112
4Marc-Edouard VlasicTexas Stars (DAL)D2291625-1320333882273810.98%3950823.1265113943000025100%100000.9800000211
5Seamus CaseyTexas Stars (DAL)D3261723-1812035416316429.52%4959818.694593266000057000%100000.7700000002
6Viktor NeuchevTexas Stars (DAL)LW3281523-412057609219708.70%1154717.121231146000031046.15%5200100.8411000112
7Justin ErtelTexas Stars (DAL)LW32101121-1240605696276210.42%857517.9700000000000041.86%4300000.7300000030
8Alec RegulaTexas Stars (DAL)D3251217-17180742645153711.11%4159018.441452965000156000%000100.5801000111
9Alex DoucetTexas Stars (DAL)LW1841317-1195131536142211.11%223112.8501101000041144.44%1800001.4713010110
10Isak RosenDallas StarsRW14581338031376711437.46%726919.240007300000140041.67%2400000.9700000112
11Liam OhgrenTexas Stars (DAL)LW75611540151336102913.89%217024.420003150000160075.00%1200001.2911000002
12Ville KoivunenTexas Stars (DAL)RW11617-100262335122117.14%319417.70000417000090056.25%1600000.7200000101
Statistiques d’équipe totales ou en moyenne29692163255-75111549953085822056710.72%252544018.3818284617240700033095450.71%162100200.9459010141116
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


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Alec RegulaTexas Stars (DAL)D252000-08-06USANo218 Lbs6 ft4NoNoFantasy DraftNoNo22025-06-29FalseFalsePro & Farm775,000$407,203$0$0$No775,000$--------775,000$--------No--------Lien NHL
Ales StezkaTexas Stars (DAL)G281997-01-06CZENo203 Lbs6 ft5NoNoAssign ManuallyNoNo12025-11-09FalseFalsePro & Farm0$0$No---------------------------Lien NHL
Alex DoucetTexas Stars (DAL)LW232002-01-12CANNo187 Lbs6 ft0NoNoFantasy DraftNoNo12025-05-26FalseFalsePro & Farm870,000$457,119$0$0$No---------------------------Lien NHL
Jake LucchiniTexas Stars (DAL)C301995-05-09CANNo174 Lbs6 ft0NoNoFantasy DraftNoNo12025-05-26FalseFalsePro & Farm775,000$407,203$0$0$No---------------------------
Jan BednarTexas Stars (DAL)G232002-08-26CZENo201 Lbs6 ft4NoNoFantasy DraftNoNo02025-07-22FalseFalsePro & Farm0$0$No---------------------------
Jared MoeTexas Stars (DAL)G261999-07-22USANo220 Lbs6 ft4NoNoFantasy DraftNoNo02025-07-22FalseFalsePro & Farm0$0$No---------------------------Lien NHL
Justin ErtelTexas Stars (DAL)LW222003-05-27CANNo187 Lbs6 ft2NoNoFantasy DraftNoNo22025-05-26FalseFalsePro & Farm867,500$455,805$0$0$No867,500$--------867,500$--------No--------
Liam OhgrenTexas Stars (DAL)LW212004-01-28SWENo187 Lbs6 ft0NoNoAssign ManuallyNoNo22025-05-26FalseFalsePro & Farm886,667$465,876$0$0$No886,667$--------886,667$--------No--------Lien NHL
Marc-Edouard VlasicTexas Stars (DAL)D381987-03-30CANNo205 Lbs6 ft1NoNoTrade2025-12-28NoYes12025-05-26FalseFalsePro & Farm7,000,000$3,677,966$0$0$No---------------------------Lien NHL
Noah OstlundTexas Stars (DAL)C212004-03-11SWENo165 Lbs5 ft11NoNoAssign ManuallyNoNo22025-05-26FalseFalsePro & Farm886,667$465,876$0$0$No886,667$--------886,667$--------No--------
Sammy WalkerTexas Stars (DAL)C/LW/RW261999-06-07USANo141 Lbs5 ft10NoNoFantasy DraftNoNo02025-07-22FalseFalsePro & Farm0$0$No---------------------------Lien NHL
Samuel JohannessonTexas Stars (DAL)D252000-12-27SWENo176 Lbs5 ft11NoNoFantasy DraftNoNo12025-05-26FalseFalsePro & Farm870,000$457,119$0$0$No---------------------------
Seamus CaseyTexas Stars (DAL)D212004-01-08USANo172 Lbs5 ft10NoNoAssign ManuallyNoNo22025-05-26FalseFalsePro & Farm950,000$499,153$0$0$No950,000$--------950,000$--------No--------
Travis MitchellTexas Stars (DAL)D261999-11-25USANo205 Lbs6 ft4NoNoFantasy DraftNoNo12025-07-22FalseFalsePro & Farm775,000$407,203$0$0$No---------------------------Lien NHL
Viktor NeuchevTexas Stars (DAL)LW222003-10-25RUSNo165 Lbs5 ft11NoNoFantasy DraftNoNo12025-05-26FalseFalsePro & Farm870,000$457,119$0$0$No---------------------------Lien NHL
Ville KoivunenTexas Stars (DAL)RW222003-06-13FINNo168 Lbs6 ft0NoNoAssign ManuallyNoNo12025-05-26FalseFalsePro & Farm805,833$423,404$0$0$No---------------------------
Vincent IorioTexas Stars (DAL)D232002-11-14CANNo205 Lbs6 ft4NoNoAssign ManuallyNoNo12025-05-26FalseFalsePro & Farm814,167$427,783$0$0$No---------------------------Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1724.82187 Lbs6 ft11.121,008,578$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
130122
2Viktor NeuchevJake Lucchini30122
3Noah OstlundJustin Ertel25122
4Justin Ertel15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Vincent Iorio30122
2Seamus CaseyAlec Regula30122
325122
4Vincent Iorio15122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
150122
2Viktor NeuchevJake Lucchini50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Vincent Iorio50122
2Seamus CaseyAlec Regula50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
150122
2Jake Lucchini50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Vincent Iorio50122
2Seamus CaseyAlec Regula50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
150122Vincent Iorio50122
250122Seamus CaseyAlec Regula50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
150122
2Jake Lucchini50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Vincent Iorio50122
2Seamus CaseyAlec Regula50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Vincent Iorio
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Vincent Iorio
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Noah Ostlund, , Noah Ostlund,
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Seamus Casey, Alec Regula, Vincent IorioSeamus CaseyAlec Regula, Vincent Iorio
Tirs de pénalité
, , Jake Lucchini, ,
Gardien
#1 : , #2 :
Lignes d’attaque personnalisées en prolongation
, , Jake Lucchini, , , Noah Ostlund, Viktor Neuchev, , Justin Ertel,
Lignes de défense personnalisées en prolongation
Vincent Iorio, , Seamus Casey, Alec Regula,


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
1Bakersfield Condors1010000045-1000000000001010000045-100.000461000474546737401439405262710917400.00%20100.00%0578116549.61%597121948.97%29758650.68%755537791229405193
2Belleville Senators11000000321000000000001100000032121.00035800474546735401439405263584304125.00%20100.00%0578116549.61%597121948.97%29758650.68%755537791229405193
3Bridgeport Islanders220000001064110000005321100000053241.000101626004745467914014394052687248554250.00%4175.00%0578116549.61%597121948.97%29758650.68%755537791229405193
4Calgary Wranglers303000001016-620200000913-41010000013-200.000101828004745467131401439405261433316681100.00%7357.14%0578116549.61%597121948.97%29758650.68%755537791229405193
5Chicago Wolves412000101920-1201000101011-12110000099040.5001933520047454671594014394052617545301149222.22%14564.29%0578116549.61%597121948.97%29758650.68%755537791229405193
6Colorado Eagles211000001110121100000111010000000000020.500111930004745467644014394052662176384375.00%3233.33%0578116549.61%597121948.97%29758650.68%755537791229405193
7Henderson Silver Knights1010000027-5000000000001010000027-500.00024600474546736401439405263212223000%110.00%0578116549.61%597121948.97%29758650.68%755537791229405193
8Hershey Bears11000000642110000006420000000000021.0006101600474546744401439405265119628200.00%3166.67%0578116549.61%597121948.97%29758650.68%755537791229405193
9Iowa Wild10000010541100000105410000000000021.000571200474546723401439405264717422000%20100.00%0578116549.61%597121948.97%29758650.68%755537791229405193
10Lehigh Valley Phantoms1000010056-1000000000001000010056-110.500510150047454674140143940526561712274250.00%60100.00%0578116549.61%597121948.97%29758650.68%755537791229405193
11Manitoba Moose10001000871000000000001000100087121.0008142200474546736401439405263912428000%220.00%0578116549.61%597121948.97%29758650.68%755537791229405193
12Ontario Reign2200000011652200000011650000000000041.000112132004745467964014394052688210566233.33%000%0578116549.61%597121948.97%29758650.68%755537791229405193
13Rockford IceHogs310001101513211000000532200001101010050.833152742004745467114401439405261022912665240.00%6183.33%0578116549.61%597121948.97%29758650.68%755537791229405193
14San Diego Gulls20200000711-420200000711-40000000000000.000712190047454679040143940526702064811327.27%40100.00%0578116549.61%597121948.97%29758650.68%755537791229405193
15San Jose Barracuda30200100813-51010000024-22010010069-310.1678152300474546710640143940526121413175700.00%13192.31%0578116549.61%597121948.97%29758650.68%755537791229405193
16Springfield Thunderbirds10000010761000000000001000001076121.0007121900474546738401439405264914642200.00%3166.67%0578116549.61%597121948.97%29758650.68%755537791229405193
17Toronto Marlies1010000024-21010000024-20000000000000.00024600474546736401439405263572313000%4175.00%0578116549.61%597121948.97%29758650.68%755537791229405193
18Tucson Roadrunners1010000056-1000000000001010000056-100.0005914004745467504014394052640114245120.00%220.00%0578116549.61%597121948.97%29758650.68%755537791229405193
19Utica Comets1010000056-11010000056-10000000000000.000510150047454673240143940526321022911100.00%10100.00%0578116549.61%597121948.97%29758650.68%755537791229405193
Total3291501340143152-91769000207879-11536013206573-8310.4841432523950047454671259401439405261291367185803791924.05%792173.42%0578116549.61%597121948.97%29758650.68%755537791229405193
_Since Last GM Reset3291501340143152-91769000207879-11536013206573-8310.4841432523950047454671259401439405261291367185803791924.05%792173.42%0578116549.61%597121948.97%29758650.68%755537791229405193
_Vs Conference2451301230105118-131347000206062-21116012104556-11200.41710518529000474546794240143940526946268124579621320.97%561769.64%0578116549.61%597121948.97%29758650.68%755537791229405193
_Vs Division934011305146542200020211745120111030291150.8335188139004745467325401439405263391003622016637.50%18855.56%0578116549.61%597121948.97%29758650.68%755537791229405193

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
3231L51432523951259129136718580300
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
329151340143152
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
176900207879
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
153613206573
Derniers 10 matchs
WLOTWOTL SOWSOL
180100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
791924.05%792173.42%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
401439405264745467
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
578116549.61%597121948.97%29758650.68%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
755537791229405193


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
314Chicago Wolves6Texas Stars4LSommaire du match
423Texas Stars2San Jose Barracuda3LXSommaire du match
741Iowa Wild4Texas Stars5WXXSommaire du match
1167Rockford IceHogs3Texas Stars5WSommaire du match
1486Texas Stars4San Jose Barracuda6LSommaire du match
1699Texas Stars5Chicago Wolves4WSommaire du match
18107Calgary Wranglers8Texas Stars6LSommaire du match
21132Colorado Eagles6Texas Stars4LSommaire du match
25160Texas Stars5Rockford IceHogs6LXSommaire du match
26169San Diego Gulls4Texas Stars3LSommaire du match
29192Ontario Reign5Texas Stars7WSommaire du match
32209Texas Stars8Manitoba Moose7WXSommaire du match
34225Ontario Reign1Texas Stars4WSommaire du match
37248Texas Stars5Bridgeport Islanders3WSommaire du match
38258Chicago Wolves5Texas Stars6WXXSommaire du match
41276Texas Stars7Springfield Thunderbirds6WXXSommaire du match
43289Hershey Bears4Texas Stars6WSommaire du match
48321Toronto Marlies4Texas Stars2LSommaire du match
50333Texas Stars3Belleville Senators2WSommaire du match
52347Texas Stars5Rockford IceHogs4WXXSommaire du match
53357Bridgeport Islanders3Texas Stars5WSommaire du match
56369Texas Stars4Chicago Wolves5LSommaire du match
58385Texas Stars2Henderson Silver Knights7LSommaire du match
59394San Jose Barracuda4Texas Stars2LSommaire du match
62405Texas Stars4Bakersfield Condors5LSommaire du match
64420Texas Stars5Lehigh Valley Phantoms6LXSommaire du match
65431Colorado Eagles4Texas Stars7WSommaire du match
70457Utica Comets6Texas Stars5LSommaire du match
72474Texas Stars5Tucson Roadrunners6LSommaire du match
74488Calgary Wranglers5Texas Stars3LSommaire du match
79512Texas Stars1Calgary Wranglers3LSommaire du match
80522San Diego Gulls7Texas Stars4LSommaire du match
85550Iowa Wild-Texas Stars-
88568Texas Stars-Tucson Roadrunners-
90581Texas Stars-Coachella Valley Firebirds-
91588Bakersfield Condors-Texas Stars-
95613Milwaukee Admirals-Texas Stars-
97625Texas Stars-Iowa Wild-
101647Bakersfield Condors-Texas Stars-
103662Texas Stars-Laval Rocket-
105675Texas Stars-Abbotsford Canucks-
107684Hartford Wolf Pack-Texas Stars-
110711Rockford IceHogs-Texas Stars-
112724Texas Stars-Rochester Americans-
114739Texas Stars-Wilkes-Barre Penguins-
116747Tucson Roadrunners-Texas Stars-
120773Coachella Valley Firebirds-Texas Stars-
124801Manitoba Moose-Texas Stars-
126815Texas Stars-San Jose Barracuda-
129834Henderson Silver Knights-Texas Stars-
131849Texas Stars-Providence Bruins-
132857Texas Stars-Colorado Eagles-
135871Syracuse Crunch-Texas Stars-
137888Texas Stars-Iowa Wild-
139902Texas Stars-Abbotsford Canucks-
140908Charlotte Checkers-Texas Stars-
144931Texas Stars-Henderson Silver Knights-
145939Grand Rapids Griffins-Texas Stars-
149964Milwaukee Admirals-Texas Stars-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
151977Texas Stars-Colorado Eagles-
155996Abbotsford Canucks-Texas Stars-
1561006Texas Stars-San Diego Gulls-
1601028Coachella Valley Firebirds-Texas Stars-
1611036Texas Stars-Milwaukee Admirals-
1641050Texas Stars-Ontario Reign-
1651057Texas Stars-Manitoba Moose-
1671072Tucson Roadrunners-Texas Stars-
1711094Manitoba Moose-Texas Stars-
1721101Texas Stars-Cleveland Monsters-
1731103Texas Stars-Milwaukee Admirals-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité60003000
Prix des billets5025
Assistance98,98949,330
Assistance PCT97.05%96.73%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
18 8725 - 96.94% 436,426$7,419,240$9000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
570,384$ 1,714,584$ 1,714,584$ 1$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 568,109$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
7,855,666$ 93 9,687$ 900,891$




Texas Stars Leaders statistiques des joueurs (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

Texas 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

Texas 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

Texas Stars Leaders statistiques des joueurs (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

Texas 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