Connexion

Thunderbirds
GP: 58 | W: 35 | L: 22 | OTL: 1 | P: 71
GF: 277 | GA: 218 | PP%: 35.23% | PK%: 72.73%
DG: | Morale : 40 | Moyenne d’équipe : 62
Prochains matchs #936 vs IceHogs
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Centre de jeu
Gulls
29-26-4, 62pts
8
FINAL
2 Thunderbirds
35-22-1, 71pts
Team Stats
L1StreakW1
14-14-1Home Record17-11-1
15-12-3Away Record18-11-0
4-5-1Last 10 Games4-6-0
4.14Buts par match 4.78
3.97Buts contre par match 3.76
28.14%Pourcentage en avantage numérique35.23%
70.81%Pourcentage en désavantage numérique72.73%
Thunderbirds
35-22-1, 71pts
10
FINAL
3 Crunch
21-33-5, 47pts
Team Stats
W1StreakL1
17-11-1Home Record11-16-2
18-11-0Away Record10-17-3
4-6-0Last 10 Games4-6-0
4.78Buts par match 4.80
3.76Buts contre par match 5.90
35.23%Pourcentage en avantage numérique33.77%
72.73%Pourcentage en désavantage numérique60.93%
Thunderbirds
35-22-1, 71pts
2022-10-08
IceHogs
16-37-4, 36pts
Statistiques d’équipe
W1SéquenceL4
17-11-1Fiche domicile11-17-1
18-11-0Fiche visiteur5-20-3
4-6-010 derniers matchs2-8-0
4.78Buts par match 4.86
3.76Buts contre par match 4.86
35.23%Pourcentage en avantage numérique34.64%
72.73%Pourcentage en désavantage numérique53.99%
Wild
34-18-8, 76pts
2022-10-10
Thunderbirds
35-22-1, 71pts
Statistiques d’équipe
SOL1SéquenceW1
16-9-4Fiche domicile17-11-1
18-9-4Fiche visiteur18-11-0
4-3-310 derniers matchs4-6-0
5.12Buts par match 4.78
4.32Buts contre par match 4.78
35.26%Pourcentage en avantage numérique35.23%
72.67%Pourcentage en désavantage numérique72.73%
Thunderbirds
35-22-1, 71pts
2022-10-12
Wolves
26-28-3, 55pts
Statistiques d’équipe
W1SéquenceW1
17-11-1Fiche domicile15-13-2
18-11-0Fiche visiteur11-15-1
4-6-010 derniers matchs7-2-1
4.78Buts par match 4.19
3.76Buts contre par match 4.19
35.23%Pourcentage en avantage numérique35.40%
72.73%Pourcentage en désavantage numérique75.76%
Meneurs d'équipe
Matthew PecaButs
Matthew Peca
30
Passes
Scott Perunovich
67
Points
Scott Perunovich
81
Mackenzie MacEachernPlus/Moins
Mackenzie MacEachern
27
Joel HoferVictoires
Joel Hofer
15
Maxime LagacePourcentage d’arrêts
Maxime Lagace
0.917

Statistiques d’équipe
Buts pour
277
4.78 GFG
Tirs pour
2110
36.38 Avg
Pourcentage en avantage numérique
35.2%
62 GF
Début de zone offensive
38.5%
Buts contre
218
3.76 GAA
Tirs contre
2049
35.33 Avg
Pourcentage en désavantage numérique
72.7%
45 GA
Début de la zone défensive
40.8%
Informations de l'équipe

Directeur général
EntraîneurDrew Bannister
DivisionDivision 4
ConférenceConference 2
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro16
Équipe Mineure21
Limite contact 37 / 20
Espoirs0


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
1Logan BrownX100.008475806597787967756865656367698240660241750,000$
2Matthew PecaX100.006635946467798465716962606270724440640291750,000$
3Klim KostinX100.008737736887747666726463576363677740640231863,333$
4Dakota JoshuaX100.008553725885778361736263565967685540620261750,000$
5Nathan ToddX97.006138855970928159686060565968703640600261750,000$
6Hugh McGingX100.006137865963778959586159525765675440590231883,750$
7Tanner KaspickX100.006539725975697357605556565365675740590241750,000$
8Niko MikkolaX99.008054756088868263307563765066675440660261787,005$
9Scott PerunovichX100.005636837466836875307463625265677040640231925,000$
10Steven SantiniX100.008638946282818757306754615068706240630272750,000$
11Tommy CrossX100.007543725884788661306561624874794440630321750,000$
12Luke WitkowskiX100.006334875882717859305860594873753240610322750,000$
13Brady LyleX100.006939875679698659305857554864665340600222800,000$
Rayé
1Mackenzie MacEachernX76.867341845779778660636162576169715440620281900,000$
MOYENNE D’ÉQUIPE98.00724382617978816251646160556770554062
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
1Maxime Lagace100.007574767874757675747574718450406302910$
Rayé
1Joel Hofer98.00757574857471747372747363686040620212795,000$
MOYENNE D’ÉQUIPE99.0075757582747375747375746776554063
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Drew Bannister64696971747077CAN481700,000$


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
1Scott PerunovichThunderbirds (STL)D4714678182205390127407511.02%83115824.6642125691102023112100.00%000001.4000000333
2Tommy CrossThunderbirds (STL)D581654702233513984146418910.96%83120020.7091019711180000110310.00%000001.1700001435
3Matthew PecaThunderbirds (STL)C5830386822140401522347516212.82%20103917.9226817611013807217.92124600011.3101000242
4Niko MikkolaThunderbirds (STL)D46154964066014676137426810.95%101111024.1310102075111000088230.00%000011.1500000321
5Dakota JoshuaThunderbirds (STL)C5826346033951641232265818111.50%19105918.27651125540003492018.2765600011.1311100513
6Mackenzie MacEachernThunderbirds (STL)LW532729562710066441925110914.06%11101819.216915341070000214219.217200021.1011000335
7Hugh McGingThunderbirds (STL)LW582529542710026601544312116.23%1792715.9951615600002183115.995800001.1600000231
8Klim KostinThunderbirds (STL)C41222547143601461181744210912.64%1090222.02191024920332782122.02108600011.0400000231
9Nathan ToddThunderbirds (STL)C53222143412039461514911614.57%11108420.474610271260000171120.4715500020.7900000321
10Nathan WalkerBluesLW231722396402462136319812.50%655624.1725716470116702024.1712600011.4000000214
11Brady LyleThunderbirds (STL)D588283611335884443231918.60%6286614.9400005101161100.00%000000.8300001012
12Luke WitkowskiThunderbirds (STL)D5814223612180485473222919.18%5984014.491015110001122114.49200000.8600000012
13Steven SantiniThunderbirds (STL)D4452631-134068547723626.49%6587619.9239123491000177000.00%000000.7100000110
14Tanner KaspickThunderbirds (STL)C5812193122295804512131899.92%1096016.5613419680001210116.5610800000.6500000001
15Logan BrownThunderbirds (STL)C151510255235284566254422.73%1032921.95561112290001394021.9545500021.5200001340
Statistiques d’équipe totales ou en moyenne72826847374118238325115510972057596137113.03%5671393019.1459100159443109944824860341357.21%3964000111.0623103333231
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
1Joel HoferThunderbirds (STL)28151100.8903.89141900928360600.00%02338001
2Maxime LagaceThunderbirds (STL)2815710.9172.73151643698270210.75042710220
Statistiques d’équipe totales ou en moyenne56301810.9033.2929354316116630810.75045048221


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 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
Brady LyleThunderbirds (STL)D221999-06-06No203 Lbs6 ft1NoNoNo2Pro & Farm800,000$240,860$0$0$No800,000$Lien / Lien NHL
Dakota JoshuaThunderbirds (STL)C261996-05-15No206 Lbs6 ft3NoNoNo1Pro & Farm750,000$225,806$0$0$NoLien / Lien NHL
Hugh McGingThunderbirds (STL)LW231998-07-11No167 Lbs5 ft8NoNoNo1Pro & Farm883,750$266,075$0$0$NoLien / Lien NHL
Joel HoferThunderbirds (STL)G212000-07-30No179 Lbs6 ft5NoNoNo2Pro & Farm795,000$239,355$0$0$No795,000$Lien / Lien NHL
Klim KostinThunderbirds (STL)C231999-05-05No215 Lbs6 ft3NoNoNo1Pro & Farm863,333$259,928$0$0$NoLien / Lien NHL
Logan BrownThunderbirds (STL)C241998-03-05No218 Lbs6 ft6NoNoNo1Pro & Farm750,000$225,806$0$0$NoLien / Lien NHL
Luke WitkowskiThunderbirds (STL)D321990-04-14No210 Lbs6 ft2NoNoNo2Pro & Farm750,000$225,806$0$0$No750,000$Lien / Lien NHL
Mackenzie MacEachernThunderbirds (STL)LW281994-03-09No193 Lbs6 ft2NoNoNo1Pro & Farm900,000$270,968$0$0$NoLien / Lien NHL
Matthew PecaThunderbirds (STL)C291993-04-27No181 Lbs5 ft10NoNoNo1Pro & Farm750,000$225,806$0$0$NoLien / Lien NHL
Maxime LagaceThunderbirds (STL)G291993-01-12No190 Lbs6 ft2NoNoNo1Pro & Farm0$0$NoLien / Lien NHL
Nathan ToddThunderbirds (STL)C261995-12-02No176 Lbs6 ft0NoNoNo1Pro & Farm750,000$225,806$0$0$NoLien / Lien NHL
Niko MikkolaThunderbirds (STL)D261996-04-27No209 Lbs6 ft4NoNoNo1Pro & Farm787,005$236,948$0$0$NoLien / Lien NHL
Scott PerunovichThunderbirds (STL)D231998-08-18No175 Lbs5 ft10NoNoNo1Pro & Farm925,000$278,495$0$0$NoLien
Steven SantiniThunderbirds (STL)D271995-03-07No205 Lbs6 ft2NoNoNo2Pro & Farm750,000$225,806$0$0$No750,000$Lien / Lien NHL
Tanner KaspickThunderbirds (STL)C241998-01-28No200 Lbs6 ft0NoNoNo1Pro & Farm750,000$225,806$0$0$NoLien / Lien NHL
Tommy CrossThunderbirds (STL)D321989-09-12No205 Lbs6 ft3NoNoNo1Pro & Farm750,000$225,806$0$0$NoLien / Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1625.94196 Lbs6 ft21.25747,131$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nathan Todd40122
2Hugh McGingMatthew PecaTanner Kaspick30122
3Dakota Joshua20122
4Nathan ToddMatthew Peca10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Niko Mikkola40122
2Tommy CrossSteven Santini30122
3Luke WitkowskiBrady Lyle20122
4Niko Mikkola10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nathan Todd60122
2Hugh McGingMatthew PecaTanner Kaspick40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Niko Mikkola60122
2Tommy CrossSteven Santini40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Matthew Peca60122
2Dakota Joshua40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Niko Mikkola60122
2Tommy CrossSteven Santini40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
160122Niko Mikkola60122
2Matthew Peca40122Tommy CrossSteven Santini40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Matthew Peca60122
2Dakota Joshua40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Niko Mikkola60122
2Tommy CrossSteven Santini40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nathan ToddNiko Mikkola
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nathan ToddNiko Mikkola
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Hugh McGing, Tanner Kaspick, Dakota JoshuaHugh McGing, Tanner KaspickDakota Joshua
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Luke Witkowski, Brady Lyle, Tommy CrossLuke WitkowskiBrady Lyle, Tommy Cross
Tirs de pénalité
, Matthew Peca, Dakota Joshua, , Nathan Todd
Gardien
#1 : , #2 :
Lignes d’attaque personnalisées en prolongation
, Matthew Peca, Dakota Joshua, , Nathan Todd, Hugh McGing, Hugh McGing, Tanner Kaspick, , ,
Lignes de défense personnalisées en prolongation
Niko Mikkola, , Tommy Cross, Steven Santini, Luke Witkowski


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
1Admirals30300000612-62020000047-31010000025-300.0006915101099174410465571872615892118581516.67%9277.78%01057187556.37%974199048.94%504100750.05%143110311353392706354
2Barrucada220000001459110000006241100000083541.00014264000109917446165571872615782818464250.00%9188.89%01057187556.37%974199048.94%504100750.05%143110311353392706354
3Bruins30300000819-111010000045-120200000414-1000.0008122000109917441176557187261512438106110220.00%5420.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
4Canucks1010000046-21010000046-20000000000000.0004711001099174436655718726154168245120.00%4175.00%11057187556.37%974199048.94%504100750.05%143110311353392706354
5Checkers11000000835110000008350000000000021.0008142200109917443565571872615418420200.00%2150.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
6Chekers1100000011561100000011560000000000021.00011203100109917448665571872615459425100.00%220.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
7Comets11000000651000000000001100000065121.00061218001099174461655718726153660264250.00%000.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
8Condors22000000963110000004311100000053241.0009162500109917447665571872615451112268225.00%5180.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
9Crunch22000000174131100000071611000000103741.00017284500109917447865571872615712610357571.43%40100.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
10Eagles1010000035-21010000035-20000000000000.00034700109917442365571872615265523100.00%000.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
11Griffins220000001037110000005321100000050541.00010203001109917447265571872615581615305120.00%40100.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
12Gulls20200000414-101010000028-61010000026-400.00045900109917445665571872615803522477114.29%11281.82%01057187556.37%974199048.94%504100750.05%143110311353392706354
13Heat2100100014113110000006421000100087141.00014243800109917448165571872615862323435360.00%9544.44%01057187556.37%974199048.94%504100750.05%143110311353392706354
14IceHogs22000000176111100000073411000000103741.00017294600109917448865571872615662110446466.67%4175.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
15Islanders211000009721010000045-11100000052320.5009162500109917447065571872615672510398337.50%5260.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
16Marlies22000000181081100000010551100000085341.0001830480010991744896557187261580186325480.00%3233.33%01057187556.37%974199048.94%504100750.05%143110311353392706354
17Monsters2110000011561100000010191010000014-320.50011203100109917448265571872615782510506350.00%5180.00%11057187556.37%974199048.94%504100750.05%143110311353392706354
18Moose42101000181712100100095421100000912-360.75018335100109917441366557187261515840228711545.45%11463.64%01057187556.37%974199048.94%504100750.05%143110311353392706354
19Penguins1010000015-41010000015-40000000000000.00012300109917443465571872615508822200.00%4175.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
20Phantoms21100000633211000006330000000000020.5006111701109917445865571872615411518414250.00%80100.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
21Reign20200000912-31010000068-21010000034-100.0009162510109917446065571872615762027347342.86%6266.67%01057187556.37%974199048.94%504100750.05%143110311353392706354
22Roadrunners43000100201282100010086222000000126670.87520375700109917441356557187261513738308110330.00%15286.67%11057187556.37%974199048.94%504100750.05%143110311353392706354
23Rocket21100000642110000004131010000023-120.500612180010991744676557187261570178457228.57%40100.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
24Senators11000000202000000000001100000020221.0002460110991744256557187261528108162150.00%30100.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
25Silver Knights11000000312000000000001100000031221.00036900109917442665571872615194616300.00%20100.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
26Stars413000001018-81010000004-4312000001014-420.25010182800109917441306557187261515745379211327.27%12466.67%01057187556.37%974199048.94%504100750.05%143110311353392706354
27Wild3200001017107110000008532100001095461.0001731480010991744137655718726151063316628450.00%8275.00%11057187556.37%974199048.94%504100750.05%143110311353392706354
28Wolf Pack220000001477110000006511100000082641.000142539001099174466655718726157225123010550.00%6350.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
29Wolves1010000023-1000000000001010000023-100.0002460010991744216557187261524151020200.00%5260.00%01057187556.37%974199048.94%504100750.05%143110311353392706354
Total583222021102772185929161101100143108352916110101013411024710.6122774917682310991744211065571872615204959138711751766235.23%1654572.73%41057187556.37%974199048.94%504100750.05%143110311353392706354
_Since Last GM Reset583222021102772185929161101100143108352916110101013411024710.6122774917682310991744211065571872615204959138711751766235.23%1654572.73%41057187556.37%974199048.94%504100750.05%143110311353392706354
_Vs Conference341713021101591401917870110078717179601010816912410.603159281440201099174412356557187261512093392587081023231.37%1072972.90%31057187556.37%974199048.94%504100750.05%143110311353392706354
_Vs Division21108011109180111044011003935411640001052457250.59591161252101099174475365571872615739203138447622032.26%591574.58%21057187556.37%974199048.94%504100750.05%143110311353392706354

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
5871W127749176821102049591387117523
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
5832222110277218
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2916111100143108
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2916111010134110
Derniers 10 matchs
WLOTWOTL SOWSOL
460000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1766235.23%1654572.73%4
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
6557187261510991744
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
1057187556.37%974199048.94%504100750.05%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
143110311353392706354


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
3 - 2022-06-0213Penguins5Thunderbirds1BLSommaire du match
5 - 2022-06-0430Thunderbirds3Bruins5ALSommaire du match
7 - 2022-06-0645Phantoms3Thunderbirds2BLSommaire du match
8 - 2022-06-0755Thunderbirds6Stars3AWSommaire du match
11 - 2022-06-1074Thunderbirds7Roadrunners3AWSommaire du match
13 - 2022-06-1285Thunderbirds10IceHogs3AWSommaire du match
15 - 2022-06-1493Stars4Thunderbirds0BLSommaire du match
17 - 2022-06-16111Thunderbirds2Stars6ALSommaire du match
18 - 2022-06-17121Roadrunners3Thunderbirds6BWSommaire du match
21 - 2022-06-20144Eagles5Thunderbirds3BLSommaire du match
23 - 2022-06-22156Thunderbirds5Moose4AWSommaire du match
26 - 2022-06-25179Thunderbirds4Wild1AWSommaire du match
28 - 2022-06-27190Admirals4Thunderbirds3BLSommaire du match
30 - 2022-06-29205Thunderbirds2Wolves3ALSommaire du match
32 - 2022-07-01220Condors3Thunderbirds4BWSommaire du match
36 - 2022-07-05242Wild5Thunderbirds8BWSommaire du match
38 - 2022-07-07264Thunderbirds5Griffins0AWSommaire du match
40 - 2022-07-09271Thunderbirds8Barrucada3AWSommaire du match
41 - 2022-07-10285Rocket1Thunderbirds4BWSommaire du match
44 - 2022-07-13307Wolf Pack5Thunderbirds6BWSommaire du match
46 - 2022-07-15320Thunderbirds5Wild4AWXXSommaire du match
48 - 2022-07-17338Heat4Thunderbirds6BWSommaire du match
50 - 2022-07-19354Thunderbirds5Islanders2AWSommaire du match
53 - 2022-07-22374Checkers3Thunderbirds8BWSommaire du match
55 - 2022-07-24386Thunderbirds8Marlies5AWSommaire du match
57 - 2022-07-26406Crunch1Thunderbirds7BWSommaire du match
59 - 2022-07-28423Thunderbirds5Roadrunners3AWSommaire du match
61 - 2022-07-30433Admirals3Thunderbirds1BLSommaire du match
63 - 2022-08-01448Thunderbirds4Moose8ALSommaire du match
65 - 2022-08-03467Moose3Thunderbirds4BWXSommaire du match
68 - 2022-08-06485Thunderbirds1Bruins9ALSommaire du match
71 - 2022-08-09502Marlies5Thunderbirds10BWSommaire du match
75 - 2022-08-13528Chekers5Thunderbirds11BWSommaire du match
78 - 2022-08-16547Thunderbirds8Heat7AWXSommaire du match
79 - 2022-08-17559Reign8Thunderbirds6BLSommaire du match
82 - 2022-08-20579Thunderbirds3Silver Knights1AWSommaire du match
83 - 2022-08-21589Moose2Thunderbirds5BWSommaire du match
87 - 2022-08-25615Phantoms0Thunderbirds4BWSommaire du match
89 - 2022-08-27631Thunderbirds3Reign4ALSommaire du match
92 - 2022-08-30646Thunderbirds2Senators0AWSommaire du match
93 - 2022-08-31653Islanders5Thunderbirds4BLSommaire du match
96 - 2022-09-03678Thunderbirds5Condors3AWSommaire du match
98 - 2022-09-05686Barrucada2Thunderbirds6BWSommaire du match
100 - 2022-09-07711Canucks6Thunderbirds4BLSommaire du match
102 - 2022-09-09723Thunderbirds8Wolf Pack2AWSommaire du match
106 - 2022-09-13746Monsters1Thunderbirds10BWSommaire du match
108 - 2022-09-15765Thunderbirds2Admirals5ALSommaire du match
110 - 2022-09-17776Roadrunners3Thunderbirds2BLXSommaire du match
112 - 2022-09-19793Thunderbirds1Monsters4ALSommaire du match
114 - 2022-09-21807IceHogs3Thunderbirds7BWSommaire du match
115 - 2022-09-22820Thunderbirds2Rocket3ALSommaire du match
117 - 2022-09-24838Griffins3Thunderbirds5BWSommaire du match
119 - 2022-09-26850Thunderbirds2Gulls6ALSommaire du match
121 - 2022-09-28870Bruins5Thunderbirds4BLSommaire du match
123 - 2022-09-30885Thunderbirds6Comets5AWSommaire du match
125 - 2022-10-02898Thunderbirds2Stars5ALSommaire du match
127 - 2022-10-04908Gulls8Thunderbirds2BLSommaire du match
129 - 2022-10-06920Thunderbirds10Crunch3AWSommaire du match
131 - 2022-10-08936Thunderbirds-IceHogs-
133 - 2022-10-10951Wild-Thunderbirds-
135 - 2022-10-12964Thunderbirds-Wolves-
137 - 2022-10-14980Wolves-Thunderbirds-
139 - 2022-10-16993Thunderbirds-Eagles-
141 - 2022-10-181009Penguins-Thunderbirds-
143 - 2022-10-201019Thunderbirds-Eagles-
145 - 2022-10-221041Condors-Thunderbirds-
146 - 2022-10-231048Thunderbirds-Canucks-
149 - 2022-10-261070Thunderbirds-Phantoms-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
151 - 2022-10-281081Senators-Thunderbirds-
153 - 2022-10-301100Thunderbirds-Chekers-
155 - 2022-11-011109Thunderbirds-Admirals-
156 - 2022-11-021118Stars-Thunderbirds-
159 - 2022-11-051141Eagles-Thunderbirds-
161 - 2022-11-071151Thunderbirds-Penguins-
163 - 2022-11-091169Thunderbirds-Bears-
165 - 2022-11-111181Comets-Thunderbirds-
166 - 2022-11-121194Thunderbirds-American-
168 - 2022-11-141209Silver Knights-Thunderbirds-
173 - 2022-11-191239American-Thunderbirds-
174 - 2022-11-201245Thunderbirds-Checkers-
178 - 2022-11-241273Bears-Thunderbirds-
184 - 2022-11-301309IceHogs-Thunderbirds-



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
12 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,332,377$ 1,195,408$ 1,195,408$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
6,427$ 843,167$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 56 10,190$ 570,640$




Thunderbirds 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

Thunderbirds 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

Thunderbirds 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

Thunderbirds 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

Thunderbirds 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