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Thunderbirds
GP: 16 | W: 8 | L: 7 | OTL: 1 | P: 17
GF: 64 | GA: 64 | PP%: 23.26% | PK%: 78.43%
DG: Francois Prevost | Morale : 40 | Moyenne d’équipe : 66
Prochains matchs #204 vs Canucks

Centre de jeu
Thunderbirds
8-7-1, 17pts
2
4 Comets
9-3-2, 20pts
Team Stats
L2SéquenceW1
4-3-0Fiche domicile5-2-1
4-4-1Fiche domicile4-1-1
6-4-0Derniers 10 matchs6-3-1
4.00Buts par match 5.00
4.00Buts contre par match 4.00
23.26%Pourcentage en avantage numérique30.43%
78.43%Pourcentage en désavantage numérique60.00%
Thunderbirds
8-7-1, 17pts
4
8 Americans
9-7-0, 18pts
Team Stats
L2SéquenceW1
4-3-0Fiche domicile4-4-0
4-4-1Fiche domicile5-3-0
6-4-0Derniers 10 matchs8-2-0
4.00Buts par match 4.50
4.00Buts contre par match 4.63
23.26%Pourcentage en avantage numérique16.67%
78.43%Pourcentage en désavantage numérique78.57%
Canucks
9-4-3, 21pts
Jour 34
Thunderbirds
8-7-1, 17pts
Statistiques d’équipe
OTW2SéquenceL2
5-2-1Fiche domicile4-3-0
4-2-2Fiche visiteur4-4-1
6-3-110 derniers matchs6-4-0
4.06Buts par match 4.00
3.50Buts contre par match 4.00
20.97%Pourcentage en avantage numérique23.26%
87.76%Pourcentage en désavantage numérique78.43%
Thunderbirds
8-7-1, 17pts
Jour 36
Bears
9-5-1, 19pts
Statistiques d’équipe
L2SéquenceOTW1
4-3-0Fiche domicile4-3-1
4-4-1Fiche visiteur5-2-0
6-4-010 derniers matchs6-4-0
4.00Buts par match 4.13
4.00Buts contre par match 4.13
23.26%Pourcentage en avantage numérique15.09%
78.43%Pourcentage en désavantage numérique56.52%
Marlies
9-5-2, 20pts
Jour 38
Thunderbirds
8-7-1, 17pts
Statistiques d’équipe
W1SéquenceL2
6-2-0Fiche domicile4-3-0
3-3-2Fiche visiteur4-4-1
6-3-110 derniers matchs6-4-0
4.50Buts par match 4.00
4.31Buts contre par match 4.00
15.22%Pourcentage en avantage numérique23.26%
76.47%Pourcentage en désavantage numérique78.43%
Meneurs d'équipe
Buts
Robert Thomas
12
Passes
Anthony Richard
11
Points
Robert Thomas
20
Plus/Moins
Emil Bemstrom
8
Victoires
Emil Larmi
6
Pourcentage d’arrêts
Arturs Silovs
0.893

Statistiques d’équipe
Buts pour
64
4.00 GFG
Tirs pour
524
32.75 Avg
Pourcentage en avantage numérique
23.3%
10 GF
Début de zone offensive
33.8%
Buts contre
64
4.00 GAA
Tirs contre
521
32.56 Avg
Pourcentage en désavantage numérique
78.4%%
11 GA
Début de la zone défensive
37.2%
Informations de l'équipe

Directeur généralFrancois Prevost
EntraîneurTeemu Selanne
DivisionJohn-Ahearne
ConférenceRobert-Lebel
CapitaineAnthony Richard
Assistant #1Matt Roy
Assistant #2Sami Niku


Informations de l’aréna

Capacité3,000
Assistance2,814
Billets de saison300


Informations de la formation

Équipe Pro25
Équipe Mineure22
Limite contact 47 / 250
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
1Robert Thomas (R)X100.006735817371788080869080616556496345740213975,000$
2Anthony Richard (R) (C)X100.007233827676836377787870708263574444730241900,000$
3Michael Rasmussen (R)X100.007426807282757572757380616753466044710211900,000$
4Emil Bemstrom (R)X100.007225828266736583677475617747455444710212900,000$
5Noah Gregor (R)X100.007033837871727272717179717347485144710222750,000$
6Artturi LehkonenX100.007133788276737073726972657353513744700251750,000$
7Rasmus Kupari (R)X100.006434798060676080726671587843446844680203650,000$
8Paul Cotter (R)X100.007633796376697273727278567048465844680213650,000$
9Trey Fix-Wolansky (R)X100.004840707961726683626768647845456244670213650,000$
10Jakob Pelletier (R)X100.005038807146716264828363425641416544630191500,000$
11Nicholas Robertson (R)X100.005229727453675177716962547841416934630191500,000$
12Luke Evangelista (R)X100.006142776263666766686165525940407336610182500,000$
13Matt Roy (A)X100.006649837375756477617669776264563944720251900,000$
14Frederic Allard (R)X100.006947797765717273517256786453504544700231750,000$
15Calen Addison (R)X100.005833807858546677397757664643435932650203650,000$
16Louis Crevier (R)X100.006628836563586848336739744243427044630192500,000$
17Alex Vlasic (R)X100.007025885960675545256649704141417138620191500,000$
18Jamie Drysdale (R)X100.007037755446676465326370515840408225600182500,000$
Rayé
1Dylan Sikura (R)X100.007141817877767177737775727755513923730241950,000$
2Brendan Brisson (R)X100.005336726746596071816563414741436224600192500,000$
3Sean Farrell (R)X100.005536735744646563667365405040408024580182500,000$
4Sami Niku (R) (A)X100.006137748163698078487767684660523944690241800,000$
MOYENNE D’ÉQUIPE100.00643579726469677263726761634846593967
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
1Emil Larmi100.00736877646583816963787051475148710241700,000$
2Arturs Silovs100.00795260747351516469537441416348620191500,000$
Rayé
1Joel Blomqvist (R)100.00625575474569705545735840407532570182500,000$
MOYENNE D’ÉQUIPE100.0071587162616867635968674443634363
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Teemu Selanne77697390877445Fin433650,000$


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
1Robert ThomasThunderbirds (Stl)C1612820220332945213326.67%629118.24527846000052054.96%262125111.3700000202
2Anthony RichardThunderbirds (Stl)C1671118460334049133214.29%632320.212133352025431050.41%36747001.1100000121
3Emil BemstromThunderbirds (Stl)RW168816880222055183714.55%725916.211341038000001053.85%13104011.2300000200
4Michael RasmussenThunderbirds (Stl)LW169615-4100252360163715.00%530519.08314532000040150.00%18134100.9800000020
5Trey Fix-WolanskyThunderbirds (Stl)RW165813-300161736133113.89%424115.071232310003202114.29%782101.0800000101
6Noah GregorThunderbirds (Stl)C166511160261439122815.38%421113.200110140003190049.56%11363001.0400000010
7Artturi LehkonenThunderbirds (Stl)LW164610810032164410169.09%324215.18000010000191142.86%1481000.8200000101
8Rasmus KupariThunderbirds (Stl)C16549-42018133381915.15%318211.43000000000110045.88%85116000.9800000000
9Sami NikuThunderbirds (Stl)D150777601720163130%1631621.1202213800001000%068000.4401000011
10Alex VlasicThunderbirds (Stl)D120775401520208110%1330425.36022336000031000%016000.4600000000
11Nicholas RobertsonThunderbirds (Stl)RW16347-100782091215.00%71449.01000020000010100.00%132000.9700000010
12Calen AddisonThunderbirds (Stl)D142460201715116318.18%1927819.92112227000042000%0414000.4300000000
13Matt RoyThunderbirds (Stl)D16156-28023231810175.56%2737623.54000126000130000%01210000.3200000000
14Paul CotterThunderbirds (Stl)LW16336-4802981372223.08%321013.16011036000001055.56%946000.5700000001
15Luke EvangelistaThunderbirds (Stl)RW905526014624110%417619.57000000110200053.33%1508000.5700000000
16Frederic AllardThunderbirds (Stl)D1605541002027161290%1227617.2600000000029000%029000.3600000000
17Louis CrevierThunderbirds (Stl)D16044-4608187220%1120312.6900001000011000%006000.3900000000
18Jamie DrysdaleThunderbirds (Stl)D17123-11402525105510.00%1834520.34000037011034000%017000.1700000000
19Dylan SikuraThunderbirds (Stl)RW7123-52089253114.00%212017.16000000000170060.00%584000.5000000010
20Jakob PelletierThunderbirds (Stl)LW16112-2404420465.00%21469.1700000000000066.67%632000.2700000000
21Henri JokiharjuBluesD4000-6004113520%610225.5500006000012000%00400000000000
Statistiques d’équipe totales ou en moyenne302681051735114039636654218935712.55%178505916.7513162935414224123589351.15%915116118320.6801000787
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
1Emil LarmiThunderbirds (Stl)136510.8734.0974901514001892000133101
2Arturs SilovsThunderbirds (Stl)42200.8933.702110013121780000313000
Statistiques d’équipe totales ou en moyenne178710.8774.0096001645212672001616101


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
Alex VlasicThunderbirds (Stl)D192001-01-01USAYes216 Lbs6 ft6NoNoAssign ManuallyNoNo12024-07-10FalseFalsePro & Farm500,000$405,325$0$0$No---------------------------Lien
Anthony RichardThunderbirds (Stl)C241996-01-01CANYes163 Lbs5 ft10NoNoFree AgentNoNo12025-08-28FalseFalsePro & Farm900,000$729,586$0$0$No---------------------------Lien
Artturi LehkonenThunderbirds (Stl)LW251995-01-01FINNo185 Lbs5 ft11NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm750,000$607,988$0$0$No---------------------------Lien
Arturs SilovsThunderbirds (Stl)G192001-01-01LVANo203 Lbs6 ft4NoNoAssign ManuallyNoNo12024-07-10FalseFalsePro & Farm500,000$405,325$0$0$No---------------------------Lien
Brendan BrissonThunderbirds (Stl)C192001-01-01USAYes179 Lbs5 ft11NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------
Calen AddisonThunderbirds (Stl)D202000-01-01CANYes173 Lbs5 ft11NoNoFree AgentNoNo32025-08-28FalseFalsePro & Farm650,000$526,923$0$0$No750,000$850,000$-------750,000$850,000$-------NoNo-------Lien
Dylan SikuraThunderbirds (Stl)RW241996-01-01CANYes166 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm950,000$770,118$0$0$No---------------------------Lien
Emil BemstromThunderbirds (Stl)RW211999-01-01SWEYes193 Lbs6 ft0NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm900,000$729,586$0$0$No975,000$--------800,000$--------No--------Lien
Emil LarmiThunderbirds (Stl)G241996-01-01FINNo185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm700,000$567,456$0$0$No---------------------------Lien
Frederic AllardThunderbirds (Stl)D231997-01-01CANYes179 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm750,000$607,988$0$0$No---------------------------Lien
Jakob PelletierThunderbirds (Stl)LW192001-01-01CANYes170 Lbs5 ft9NoNoTrade2025-02-03NoNo12024-07-10FalseFalsePro & Farm500,000$405,325$0$0$No---------------------------Lien
Jamie DrysdaleThunderbirds (Stl)D182002-01-01CANYes170 Lbs5 ft11NoNoTrade2025-12-02NoNo22025-07-16FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------
Joel BlomqvistThunderbirds (Stl)G182002-01-01FINYes178 Lbs6 ft1NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------
Louis CrevierThunderbirds (Stl)D192001-01-01CANYes228 Lbs6 ft8NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------
Luke EvangelistaThunderbirds (Stl)RW182002-01-01CANYes175 Lbs5 ft11NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------
Matt RoyThunderbirds (Stl)D251995-01-01USANo200 Lbs6 ft1NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm900,000$729,586$0$0$No---------------------------Lien
Michael RasmussenThunderbirds (Stl)LW211999-01-01CANYes210 Lbs6 ft6NoNoFree Agent2024-08-09NoNo12024-08-20FalseFalsePro & Farm900,000$729,586$0$0$No---------------------------Lien
Nicholas RobertsonThunderbirds (Stl)RW192001-01-01USAYes179 Lbs5 ft9NoNoAssign ManuallyNoNo12024-07-10FalseFalsePro & Farm500,000$405,325$0$0$No---------------------------Lien
Noah GregorThunderbirds (Stl)C221998-01-01CANYes185 Lbs6 ft0NoNoFree Agent2025-04-15NoNo22025-08-28FalseFalsePro & Farm750,000$607,988$0$0$No850,000$--------850,000$--------No--------Lien
Paul CotterThunderbirds (Stl)LW211999-01-01USAYes212 Lbs6 ft2NoNoFree AgentNoNo32025-08-28FalseFalsePro & Farm650,000$526,923$0$0$No750,000$850,000$-------750,000$850,000$-------NoNo-------Lien
Rasmus KupariThunderbirds (Stl)C202000-01-01FINYes200 Lbs6 ft2NoNoFree AgentNoNo32025-08-28FalseFalsePro & Farm650,000$526,923$0$0$No750,000$850,000$-------750,000$850,000$-------NoNo-------Lien
Robert ThomasThunderbirds (Stl)C211999-01-01CANYes218 Lbs6 ft0NoNoTrade2025-11-20NoNo32024-08-21FalseFalsePro & Farm975,000$790,385$0$0$No2,500,000$3,750,000$-------925,000$925,000$-------NoNo-------Lien
Sami NikuThunderbirds (Stl)D241996-01-01FINYes176 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm800,000$648,521$0$0$No---------------------------Lien
Sean FarrellThunderbirds (Stl)LW182002-01-01USAYes175 Lbs5 ft9NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------
Trey Fix-WolanskyThunderbirds (Stl)RW211999-01-01CANYes186 Lbs5 ft7NoNoFree AgentNoNo32025-08-28FalseFalsePro & Farm650,000$526,923$0$0$No750,000$850,000$-------750,000$850,000$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2520.88188 Lbs6 ft01.72675,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael RasmussenRobert ThomasLuke Evangelista40122
2Artturi LehkonenAnthony RichardEmil Bemstrom30122
3Paul CotterRasmus KupariTrey Fix-Wolansky20122
4Jakob PelletierNoah GregorNicholas Robertson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Matt RoyAlex Vlasic40122
2Frederic AllardCalen Addison30122
3Louis CrevierJamie Drysdale20122
4Jamie DrysdaleCalen Addison10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Paul CotterRobert ThomasEmil Bemstrom60122
2Michael RasmussenAnthony RichardTrey Fix-Wolansky40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Calen AddisonAlex Vlasic60122
2Matt RoyJamie Drysdale40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Anthony RichardLuke Evangelista60122
2Noah GregorTrey Fix-Wolansky40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alex VlasicJamie Drysdale60122
2Matt RoyFrederic Allard40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Anthony Richard60122Jamie DrysdaleAlex Vlasic60122
2Noah Gregor40122Matt RoyFrederic Allard40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Robert ThomasMichael Rasmussen60122
2Noah GregorArtturi Lehkonen40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Alex VlasicCalen Addison60122
2Matt RoyJamie Drysdale40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Michael RasmussenRobert ThomasLuke EvangelistaJamie DrysdaleCalen Addison
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Artturi LehkonenNoah GregorTrey Fix-WolanskyAlex VlasicFrederic Allard
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Trey Fix-Wolansky, Luke Evangelista, Jakob PelletierNicholas Robertson, Artturi LehkonenLuke Evangelista
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Frederic Allard, Calen Addison, Jamie DrysdaleCalen AddisonFrederic Allard, Louis Crevier
Tirs de pénalité
Anthony Richard, Nicholas Robertson, Rasmus Kupari, Trey Fix-Wolansky, Emil Bemstrom
Gardien
#1 : Emil Larmi, #2 : Arturs Silovs
Lignes d’attaque personnalisées en prolongation
Noah Gregor, Trey Fix-Wolansky, Robert Thomas, Anthony Richard, Paul Cotter, Emil Bemstrom, Artturi Lehkonen, Michael Rasmussen, Nicholas Robertson, Jakob Pelletier
Lignes de défense personnalisées en prolongation
Calen Addison, Alex Vlasic, Louis Crevier, Frederic Allard, Matt Roy


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
1Admirals2020000069-31010000035-21010000034-100.0006111700192123177218146159168204438112.50%20100.00%015230450.00%17733552.84%13226150.57%350204331141279143
2Americans21100000911-2110000005321010000048-420.5009142300192123161218146159164208538225.00%4175.00%115230450.00%17733552.84%13226150.57%350204331141279143
3Barracuda11000000752000000000001100000075221.000712190019212313121814615913061224300.00%6266.67%015230450.00%17733552.84%13226150.57%350204331141279143
4Bears43100000161332110000059-422000000114760.75016223800192123113421814615911273934857342.86%17194.12%115230450.00%17733552.84%13226150.57%350204331141279143
5Comets1010000024-2000000000001010000024-200.0002240019212313421814615913212018100.00%000%015230450.00%17733552.84%13226150.57%350204331141279143
6Condors2110000067-11010000025-31100000042220.50061218001921231672181461591762612525120.00%6183.33%015230450.00%17733552.84%13226150.57%350204331141279143
7Gulls1000010034-1000000000001000010034-110.500369001921231302181461591266821300.00%40100.00%015230450.00%17733552.84%13226150.57%350204331141279143
8Islander11000000505110000005050000000000021.000571201192123124218146159119142245120.00%10100.00%015230450.00%17733552.84%13226150.57%350204331141279143
9Moose10001000651100010006510000000000021.00061117001921231362181461591431381911100.00%4325.00%015230450.00%17733552.84%13226150.57%350204331141279143
10Senators1010000046-2000000000001010000046-200.0004711001921231302181461591361012272150.00%7357.14%015230450.00%17733552.84%13226150.57%350204331141279143
Total16770110064640733010002627-19440010038371170.531641041680119212315242181461591521166100366431023.26%511178.43%215230450.00%17733552.84%13226150.57%350204331141279143
_Since Last GM Reset16770110064640733010002627-19440010038371170.531641041680119212315242181461591521166100366431023.26%511178.43%215230450.00%17733552.84%13226150.57%350204331141279143
_Vs Conference13660100052511733010002627-16330000026242140.5385284136011921231429218146159143314280303361027.78%41978.05%215230450.00%17733552.84%13226150.57%350204331141279143
_Vs Division844000002829-1413000001019-9431000001810880.5002845730019212312782181461591271855018020525.00%25292.00%115230450.00%17733552.84%13226150.57%350204331141279143

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1617L26410416852452116610036601
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
167711006464
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
73310002627
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
94401003837
Derniers 10 matchs
WLOTWOTL SOWSOL
640000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
431023.26%511178.43%2
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
21814615911921231
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
15230450.00%17733552.84%13226150.57%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
350204331141279143


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
212Condors5Thunderbirds2LSommaire du match
531Bears6Thunderbirds1LSommaire du match
639Thunderbirds4Condors2WSommaire du match
857Moose5Thunderbirds6WXSommaire du match
1065Thunderbirds3Gulls4LXSommaire du match
1170Thunderbirds3Admirals4LSommaire du match
1387Thunderbirds4Bears2WSommaire du match
1598Bears3Thunderbirds4WSommaire du match
18113Admirals5Thunderbirds3LSommaire du match
20125Thunderbirds4Senators6LSommaire du match
22137Islander0Thunderbirds5WSommaire du match
24150Thunderbirds7Bears2WSommaire du match
26163Thunderbirds7Barracuda5WSommaire du match
28175Americans3Thunderbirds5WSommaire du match
30185Thunderbirds2Comets4LSommaire du match
32198Thunderbirds4Americans8LSommaire du match
34204Canucks-Thunderbirds-
36219Thunderbirds-Bears-
38231Marlies-Thunderbirds-
40244Thunderbirds-Wolfpack-
42252Gulls-Thunderbirds-
44268Thunderbirds-Wranglers-
45277Moose-Thunderbirds-
48291Thunderbirds-Penguins-
50306Firebirds-Thunderbirds-
52320Thunderbirds-Condors-
54328Thunderbirds-Islander-
55335Icehogs-Thunderbirds-
58355Griffins-Thunderbirds-
61377Admirals-Thunderbirds-
63389Thunderbirds-Americans-
65404Roadrunners-Thunderbirds-
67417Thunderbirds-Crunch-
69431Crunch-Thunderbirds-
71445Thunderbirds-Firebirds-
72454Admirals-Thunderbirds-
77480Punishers-Thunderbirds-
79497Checkers-Thunderbirds-
81506Thunderbirds-Checkers-
83518Thunderbirds-Barracuda-
85530Little Stars-Thunderbirds-
87547Thunderbirds-Condors-
89557Roadrunners-Thunderbirds-
91575Canucks-Thunderbirds-
93583Thunderbirds-Roadrunners-
95599Thunderbirds-Comets-
97608Comets-Thunderbirds-
99619Thunderbirds-Gulls-
101633Eagles-Thunderbirds-
103649Thunderbirds-Gulls-
104660Islander-Thunderbirds-
107674Thunderbirds-Roadrunners-
108685Americans-Thunderbirds-
111699Thunderbirds-Admirals-
113711Comets-Thunderbirds-
115727Thunderbirds-Moose-
117737Thunderbirds-Senators-
118745Bears-Thunderbirds-
121758Thunderbirds-Griffins-
122768Penguins-Thunderbirds-
125786Thunderbirds-Rockets-
126796Wranglers-Thunderbirds-
130814Thunderbirds-Eagles-
131820Thunderbirds-Admirals-
132828Wolfpack-Thunderbirds-
135849Eagles-Thunderbirds-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
138867Icehogs-Thunderbirds-
139877Thunderbirds-Canucks-
142894Bears-Thunderbirds-
144905Thunderbirds-Marlies-
147918Rockets-Thunderbirds-
149935Thunderbirds-Little Stars-
151946Senators-Thunderbirds-
154962Thunderbirds-Little Stars-
155975Condors-Thunderbirds-
156977Thunderbirds-Icehogs-
160995Barracuda-Thunderbirds-
1631014Thunderbirds-Punishers-
1651025Condors-Thunderbirds-
1661034Thunderbirds-Punishers-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance13,2896,411
Assistance PCT94.92%91.59%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
33 2814 - 93.81% 178,001$1,246,004$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
444,815$ 1,687,500$ 1,687,500$ 650,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,985$ 321,743$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
5,874,019$ 137 13,831$ 1,894,847$




Thunderbirds 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

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 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

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