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Connexion

Barons
GP: 64 | W: 29 | L: 29 | OTL: 6 | P: 64
GF: 240 | GA: 244 | PP%: 22.86% | PK%: 77.94%
DG: Jeff Karas | Morale : 43 | Moyenne d’équipe : 58
Prochains matchs #713 vs Aces

Centre de jeu
Fighting Pandas
38-20-9, 85pts
2
FINAL
3 Barons
29-29-6, 64pts
Team Stats
L1SéquenceW1
17-9-6Fiche domicile16-12-4
21-11-3Fiche domicile13-17-2
5-3-2Derniers 10 matchs5-5-0
4.34Buts par match 3.75
3.51Buts contre par match 3.81
27.34%Pourcentage en avantage numérique22.86%
78.98%Pourcentage en désavantage numérique77.94%
Barons
29-29-6, 64pts
6
FINAL
4 Firebirds
22-40-3, 47pts
Team Stats
W1SéquenceL1
16-12-4Fiche domicile12-19-1
13-17-2Fiche domicile10-21-2
5-5-0Derniers 10 matchs1-8-1
3.75Buts par match 3.95
3.81Buts contre par match 4.78
22.86%Pourcentage en avantage numérique23.36%
77.94%Pourcentage en désavantage numérique73.97%
Aces
43-15-6, 92pts
Jour 140
Barons
29-29-6, 64pts
Statistiques d’équipe
SOW2SéquenceW1
23-9-0Fiche domicile16-12-4
20-6-6Fiche visiteur13-17-2
8-1-110 derniers matchs5-5-0
3.77Buts par match 3.75
3.03Buts contre par match 3.75
25.56%Pourcentage en avantage numérique22.86%
79.73%Pourcentage en désavantage numérique77.94%
Barons
29-29-6, 64pts
Jour 141
Canucks
29-29-7, 65pts
Statistiques d’équipe
W1SéquenceL7
16-12-4Fiche domicile16-12-4
13-17-2Fiche visiteur13-17-3
5-5-010 derniers matchs3-7-0
3.75Buts par match 3.92
3.81Buts contre par match 3.92
22.86%Pourcentage en avantage numérique30.20%
77.94%Pourcentage en désavantage numérique76.71%
Firebirds
22-40-3, 47pts
Jour 145
Barons
29-29-6, 64pts
Statistiques d’équipe
L1SéquenceW1
12-19-1Fiche domicile16-12-4
10-21-2Fiche visiteur13-17-2
1-8-110 derniers matchs5-5-0
3.95Buts par match 3.75
4.78Buts contre par match 3.75
23.36%Pourcentage en avantage numérique22.86%
73.97%Pourcentage en désavantage numérique77.94%
Meneurs d'équipe
Parker KellyButs
Parker Kelly
45
Jayden StrublePasses
Jayden Struble
58
Parker KellyPoints
Parker Kelly
97
Matias MaccelliPlus/Moins
Matias Maccelli
5
Ville HussoVictoires
Ville Husso
5
Thatcher DemkoPourcentage d’arrêts
Thatcher Demko
0.907

Statistiques d’équipe
Buts pour
240
3.75 GFG
Tirs pour
1871
29.23 Avg
Pourcentage en avantage numérique
22.9%
32 GF
Début de zone offensive
36.4%
Buts contre
244
3.81 GAA
Tirs contre
2244
35.06 Avg
Pourcentage en désavantage numérique
77.9%%
15 GA
Début de la zone défensive
42.1%
Informations de l'équipe

Directeur généralJeff Karas
EntraîneurNeal Broten
DivisionCentral
ConférenceWestern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro18
Équipe Mineure19
Limite contact 37 / 50
Espoirs27


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
1Parker KellyXX100.00796085666672906963676178506570074660262500,000$
2Fedor Svechkov (R)X100.006456877068727068546668605157590706202210$
3Matias MaccelliX100.004955926866737268506867585061630746202521,000,000$
4Liam Ohgren (R)X100.00685495666866566750635757505557063590222500,000$
5Dalibor DvorskyX100.00493590597450504950504947505457059510203500,000$
6Ozzy WiesblattX100.00503590596650515050505048505861063510233500,000$
7Jan JenikX100.00493590577150504950505047506262049510252500,000$
8Kailer YamamotoX100.00495591576253534950494948517270062510273500,000$
9Grigori DenisenkoX100.00614927577050504950505047506262061500252500,000$
10Oskar OlaussonX100.00493590586550504950494950505658061500231500,000$
11Jayden StrubleX100.00816674657667737150675369626265066650243500,000$
12Mathew DumbaX100.007065696366687867506152695573720556303131,000,000$
13Erik GudbransonX100.007060825780545666506454685579790566203411,250,000$
14Caleb JonesX100.00494184576950525050504950556970057520282500,000$
15Hunter BrzustewiczX100.00515027596950545050505050555559060510213500,000$
Rayé
1Jordan EberleX100.005656837263796576507369636578770196603511,250,000$
MOYENNE D’ÉQUIPE100.0059507962696061595158555753646505957
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
1Thatcher Demko100.00717171746876717069648069700706903011,500,000$
2Ville Husso100.0061666576505754485050506969035570313500,000$
Rayé
MOYENNE D’ÉQUIPE100.006669687559676359605765697005363
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Neal Broten8586997070751USA655500,000$


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
1Parker KellyBarons (MIN)C/LW64455297-52201832633439124813.12%61158224.726915351190113546155.18%199000031.23160001156
2Matias MaccelliBarons (MIN)LW64365793540111103057522711.80%25154724.184913291221014673349.59%12100101.2001000595
3Fedor SvechkovBarons (MIN)C60433982-260651762698618315.99%17132222.04481226950000455150.43%152100031.24340001027
4Liam OhgrenBarons (MIN)LW64294372-64092982224914413.06%24145222.696814271070002525042.60%16900210.9911000474
5Jayden StrubleBarons (MIN)D6485866-283801479377295310.39%118160225.04291128104000041010%200000.8200000265
6Erik GudbransonBarons (MIN)D64123749-34100638278264915.38%119150423.5044817920110522120.00%500000.6500000132
7Ozzy WiesblattBarons (MIN)RW64101626-500759100326310.00%17115017.98011436000090047.78%9000000.4500000012
8Grigori DenisenkoBarons (MIN)LW6471219-8160147568931737.87%9110217.230003280000150059.46%7400000.3400000041
9Jan JenikBarons (MIN)C6411819-14001010973235915.07%9124019.391013230000121048.05%112800000.3100000102
10Hunter BrzustewiczBarons (MIN)D6431619-5280123243214179.38%69138821.700339980000380133.33%300000.2700000120
11Dalibor DvorskyBarons (MIN)RW6471118-172020265563112.73%7128620.1120210990000201142.28%12300000.2824000000
12Mathew DumbaBarons (MIN)D2131215-14026252262413.64%3749223.45011515000090050.00%3200000.6100000011
13Caleb JonesBarons (MIN)D6401313-3201923254220%69144122.520007960000510080.00%500000.1800000001
14Kailer YamamotoBarons (MIN)RW644913100112435102211.43%695614.94000152000040051.47%6800000.2701000000
15Jordan EberleBarons (MIN)RW12718-4206185792712.28%1025621.392021025000071246.67%1500000.6202000102
16Oskar OlaussonBarons (MIN)RW2112340037101110.00%31919.1000004000000050.00%1400000.3100000000
Statistiques d’équipe totales ou en moyenne882226386612-122138093311931792492124312.61%6001851821.0031528321411221239482241151.29%536000370.66719000364038
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
1Dan VladarMinnesota Wild45211830.8933.9024004015614540300.82417436511
2Ville HussoBarons (MIN)85200.8434.3241700301910000081001
3Thatcher DemkoBarons (MIN)233930.9073.17106120565990100.33331351010
Statistiques d’équipe totales ou en moyenne76292960.8923.743879602422244040206458522


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 Plafond 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
Caleb JonesBarons (MIN)D281997-06-06USANo194 Lbs6 ft1NoNoN/ANoNo22024-08-19FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Dalibor DvorskyBarons (MIN)RW202005-06-15SVKNo201 Lbs6 ft1NoNoFree AgentNoNo32025-07-27FalseFalsePro & Farm500,000$50,000$11,667$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Erik GudbransonBarons (MIN)D341992-01-07CANNo222 Lbs6 ft5NoNoAssign ManuallyNoNo12024-08-23FalseFalsePro & Farm1,250,000$125,000$29,167$No---------------------------Lien / Lien NHL
Fedor SvechkovBarons (MIN)C222003-04-05RUSYes187 Lbs6 ft0NoNoProspectNoNo12025-08-05FalseFalsePro & Farm0$0$No---------------------------Lien / Lien NHL
Grigori DenisenkoBarons (MIN)LW252000-06-24RUSNo198 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Hunter BrzustewiczBarons (MIN)D212004-11-29USANo190 Lbs6 ft0NoNoFree AgentNoNo32025-07-27FalseFalsePro & Farm500,000$50,000$11,667$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Jan JenikBarons (MIN)C252000-09-15CZENo199 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Jayden StrubleBarons (MIN)D242001-09-08USANo207 Lbs6 ft0NoNoFree AgentNoNo32024-09-04FalseFalsePro & Farm500,000$50,000$11,667$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Jordan EberleBarons (MIN)RW351990-05-15CANNo180 Lbs5 ft11NoNoAssign ManuallyNoNo12024-08-23FalseFalsePro & Farm1,250,000$125,000$29,167$No---------------------------Lien / Lien NHL
Kailer YamamotoBarons (MIN)RW271998-09-29USANo178 Lbs5 ft9NoNoN/ANoNo32024-08-19FalseFalsePro & Farm500,000$50,000$11,667$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Liam OhgrenBarons (MIN)LW222004-01-28SWEYes187 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Mathew DumbaBarons (MIN)D311994-07-25CANNo185 Lbs6 ft1NoNoN/ANoNo32024-08-19FalseFalsePro & Farm1,000,000$100,000$23,333$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien / Lien NHL
Matias MaccelliBarons (MIN)LW252000-10-14FINNo185 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm1,000,000$100,000$23,333$No1,000,000$--------1,000,000$--------No--------Lien / Lien NHL
Oskar OlaussonBarons (MIN)RW232002-11-10SWENo180 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$11,667$No---------------------------Lien / Lien NHL
Ozzy WiesblattBarons (MIN)RW232002-03-09CANNo183 Lbs5 ft10NoNoFree AgentNoNo32025-07-27FalseFalsePro & Farm500,000$50,000$11,667$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Parker KellyBarons (MIN)C/LW261999-05-14CANNo185 Lbs6 ft1NoNoTrade2025-03-08NoNo2FalseFalsePro & Farm500,000$50,000$11,667$No500,000$--------500,000$--------No--------Lien / Lien NHL
Thatcher DemkoBarons (MIN)G301995-12-08USANo192 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm1,500,000$150,000$35,000$No---------------------------Lien / Lien NHL
Ville HussoBarons (MIN)G311995-02-06FINNo205 Lbs6 ft3NoNoFree AgentNoNo32026-01-27FalseFalsePro & Farm500,000$50,000$11,667$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1826.22192 Lbs6 ft12.11666,667$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Liam OhgrenFedor SvechkovDalibor Dvorsky40122
2Matias MaccelliParker KellyKailer Yamamoto30122
3Grigori DenisenkoJan JenikOzzy Wiesblatt20122
4Matias MaccelliParker KellyOskar Olausson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Caleb JonesErik Gudbranson35122
2Jayden StrubleMathew Dumba30122
3Hunter BrzustewiczErik Gudbranson25122
4Jayden StrubleMathew Dumba10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matias MaccelliParker KellyKailer Yamamoto60122
2Liam OhgrenFedor SvechkovDalibor Dvorsky40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jayden StrubleErik Gudbranson60122
2Caleb JonesHunter Brzustewicz40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Parker KellyMatias Maccelli60122
2Fedor SvechkovLiam Ohgren40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jayden StrubleErik Gudbranson60122
2Caleb JonesHunter Brzustewicz40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Parker Kelly60122Jayden StrubleErik Gudbranson60122
2Fedor Svechkov40122Caleb JonesHunter Brzustewicz40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Parker KellyMatias Maccelli60122
2Fedor SvechkovLiam Ohgren40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jayden StrubleErik Gudbranson60122
2Caleb JonesHunter Brzustewicz40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matias MaccelliParker KellyKailer YamamotoJayden StrubleErik Gudbranson
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matias MaccelliParker KellyOskar OlaussonJayden StrubleErik Gudbranson
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Liam Ohgren, Dalibor Dvorsky, Ozzy WiesblattLiam Ohgren, Dalibor DvorskyLiam Ohgren
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Erik Gudbranson, Caleb Jones, Hunter BrzustewiczErik GudbransonErik Gudbranson, Caleb Jones
Tirs de pénalité
Fedor Svechkov, Parker Kelly, Kailer Yamamoto, Matias Maccelli, Liam Ohgren
Gardien
#1 : Ville Husso, #2 : Thatcher Demko


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
1Aces52100101141222000010135-232100000117460.60014243800897470101206435966034812732106515426.67%3166.67%01034195053.03%1152225951.00%593115151.52%150610471537455840418
2Admirals211000009451010000023-11100000071620.50091322008974701056643596603484210428000%20100.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
3Americiens303000001216-41010000056-120200000710-300.0001222340089747010100643596603481513806311327.27%000%01034195053.03%1152225951.00%593115151.52%150610471537455840418
4Barracuda723001101723-631100010770412001001016-670.50017264300897470101686435966034818268269021419.05%13376.92%01034195053.03%1152225951.00%593115151.52%150610471537455840418
5Broncos30300000916-720200000711-41010000025-300.000916250089747010736435966034867212366116.67%10100.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
6Bruins21100000963110000006151010000035-220.500917260089747010526435966034865150308225.00%000%01034195053.03%1152225951.00%593115151.52%150610471537455840418
7Butter Knives1010000035-2000000000001010000035-200.0003580089747010316435966034832104243133.33%20100.00%11034195053.03%1152225951.00%593115151.52%150610471537455840418
8Canucks521001102222032100000131302000011099070.700223860008974701012264359660348165301053300.00%5340.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
9Fighting Pandas310020001284210010008531000100043161.000122133008974701058643596603489126641400.00%30100.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
10Firebirds2200000012840000000000022000000128441.0001221330089747010756435966034853112298112.50%110.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
11Griffins4310000023194220000001394211000001010060.75023406300897470101616435966034818253148211545.45%7271.43%01034195053.03%1152225951.00%593115151.52%150610471537455840418
12Ice Bats21100000770000000000002110000077020.5007916008974701055643596603487927825500.00%3166.67%01034195053.03%1152225951.00%593115151.52%150610471537455840418
13Lions21100000972211000009720000000000020.50091827008974701080643596603487726833400.00%4175.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
14Lynx2010010047-31000010023-11010000024-210.2504812008974701052643596603485918235100.00%10100.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
15Marlies2020000059-41010000025-31010000034-100.00059140089747010516435966034876186264250.00%30100.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
16Nordiks3200001014953200001014950000000000061.000142337008974701011564359660348172388537228.57%40100.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
17Quacken513000101719-221000010104630300000715-840.4001724410089747010146643596603481615012688112.50%60100.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
18Roadrunners1010000035-21010000035-20000000000000.00036900897470103464359660348328410000%2150.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
19Tomahawks31200000161512110000011921010000056-120.33316264200897470109664359660348147394557228.57%110.00%01034195053.03%1152225951.00%593115151.52%150610471537455840418
20Wombats211000007611010000024-21100000052320.500713200089747010556435966034864190314125.00%000%01034195053.03%1152225951.00%593115151.52%150610471537455840418
21Wranglers512010011621-520100001611-5311010001010050.50016294500897470101716435966034822065168210330.00%7185.71%01034195053.03%1152225951.00%593115151.52%150610471537455840418
Total64222903442240244-432121201232123117632101702210117127-10640.500240408648008974701018716435966034822446221469591403222.86%681577.94%11034195053.03%1152225951.00%593115151.52%150610471537455840418
_Since Last GM Reset64222903442240244-432121201232123117632101702210117127-10640.500240408648008974701018716435966034822446221469591403222.86%681577.94%11034195053.03%1152225951.00%593115151.52%150610471537455840418
_Vs Conference411615013421551541211050013286741220610012106980-11470.57315525741200897470101234643596603481512428116606912123.08%531375.47%01034195053.03%1152225951.00%593115151.52%150610471537455840418
_Vs Division23810013327381-8114300122363421247012103747-10290.630731181910089747010590643596603486671886228647919.15%29872.41%01034195053.03%1152225951.00%593115151.52%150610471537455840418

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6464W12404086481871224462214695900
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6422293442240244
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3212121232123117
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3210172210117127
Derniers 10 matchs
WLOTWOTL SOWSOL
451000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1403222.86%681577.94%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
6435966034889747010
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
1034195053.03%1152225951.00%593115151.52%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
150610471537455840418


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
24Wranglers6Barons2LSommaire du match
310Barons0Barracuda5LSommaire du match
519Barons5Wranglers4WSommaire du match
728Barons2Wranglers4LSommaire du match
942Wranglers5Barons4LXXSommaire du match
1150Barons4Canucks5LXSommaire du match
1463Barracuda2Barons3WXXSommaire du match
1678Barons2Barracuda1WSommaire du match
1885Aces3Barons2LXSommaire du match
21101Nordiks2Barons3WSommaire du match
24115Barons3Aces1WSommaire du match
25121Barons3Quacken4LSommaire du match
27131Broncos5Barons3LSommaire du match
30144Quacken3Barons4WXXSommaire du match
34163Canucks5Barons3LSommaire du match
37178Griffins3Barons4WSommaire du match
39185Barons2Lynx4LSommaire du match
41192Barons2Quacken5LSommaire du match
43200Barons3Ice Bats2WSommaire du match
45210Americiens6Barons5LSommaire du match
47221Barons3Butter Knives5LSommaire du match
49232Marlies5Barons2LSommaire du match
50244Barons7Admirals1WSommaire du match
52254Admirals3Barons2LSommaire du match
54263Barons5Canucks4WXXSommaire du match
56277Nordiks2Barons5WSommaire du match
58290Barons5Wombats2WSommaire du match
60298Canucks4Barons5WSommaire du match
62309Barons4Americiens5LSommaire du match
65322Quacken1Barons6WSommaire du match
67331Barons3Americiens5LSommaire du match
69341Barons2Quacken6LSommaire du match
70349Bruins1Barons6WSommaire du match
74367Nordiks5Barons6WXXSommaire du match
76380Barons4Fighting Pandas3WXSommaire du match
77387Barracuda1Barons2WSommaire du match
80402Barons5Tomahawks6LSommaire du match
82410Griffins6Barons9WSommaire du match
84422Barons2Broncos5LSommaire du match
85432Tomahawks5Barons4LSommaire du match
88440Barons7Griffins5WSommaire du match
91453Barons4Ice Bats5LSommaire du match
92461Fighting Pandas3Barons5WSommaire du match
95470Barons3Bruins5LSommaire du match
97479Roadrunners5Barons3LSommaire du match
98491Barons4Barracuda5LXSommaire du match
101503Lynx3Barons2LXSommaire du match
103514Barons3Griffins5LSommaire du match
104522Wombats4Barons2LSommaire du match
107538Tomahawks4Barons7WSommaire du match
108548Barons3Marlies4LSommaire du match
111560Aces2Barons1LXXSommaire du match
112570Barons6Aces1WSommaire du match
114579Barons3Wranglers2WXSommaire du match
116588Lions5Barons3LSommaire du match
120606Barracuda4Barons2LSommaire du match
122616Barons2Aces5LSommaire du match
123627Canucks4Barons5WSommaire du match
125634Barons4Barracuda5LSommaire du match
127649Broncos6Barons4LSommaire du match
131667Lions2Barons6WSommaire du match
133676Barons6Firebirds4WSommaire du match
136692Fighting Pandas2Barons3WXSommaire du match
137697Barons6Firebirds4WSommaire du match
140713Aces-Barons-
141718Barons-Canucks-
145734Firebirds-Barons-
147747Barons-Lions-
148756Barons-Wranglers-
149761Ice Bats-Barons-
152778Barons-Roadrunners-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
154784Ice Bats-Barons-
157801Quacken-Barons-
160812Barons-Nordiks-
162823Broncos-Barons-
163830Barons-Tomahawks-
167844Wranglers-Barons-
168851Barons-Roadrunners-
171866Butter Knives-Barons-
174878Barons-Lions-
176887Wranglers-Barons-
177893Barons-Nordiks-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
9 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,292,593$ 1,200,000$ 1,200,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
1,200,000$ 909,343$ 18 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 42 9,444$ 396,648$




Barons 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

Barons 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

Barons 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

Barons 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

Barons 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