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Thunderbirds
GP: 80 | W: 36 | L: 37 | OTL: 7 | P: 79
GF: 321 | GA: 331 | PP%: 20.89% | PK%: 75.30%
DG: Francois Prevost | Morale : 32 | Moyenne d’équipe : 68

Centre de jeu
Canucks
44-29-7, 95pts
1
FINAL
3 Thunderbirds
36-37-7, 79pts
Team Stats
L2SéquenceL1
23-14-3Fiche domicile17-18-5
21-15-4Fiche domicile19-19-2
4-6-0Derniers 10 matchs4-4-2
4.45Buts par match 4.01
3.91Buts contre par match 4.14
24.83%Pourcentage en avantage numérique20.89%
79.88%Pourcentage en désavantage numérique75.30%
Thunderbirds
36-37-7, 79pts
4
FINAL
7 Bears
44-31-5, 93pts
Team Stats
L1SéquenceW1
17-18-5Fiche domicile22-15-3
19-19-2Fiche domicile22-16-2
4-4-2Derniers 10 matchs5-4-1
4.01Buts par match 3.99
4.14Buts contre par match 3.86
20.89%Pourcentage en avantage numérique19.40%
75.30%Pourcentage en désavantage numérique77.25%
Meneurs d'équipe
Buts
Joachim Blichfeld
65
Passes
Rourke Chartier
71
Points
Joachim Blichfeld
123
Plus/Moins
Pierre Engvall
13
Victoires
Emil Larmi
25
Pourcentage d’arrêts
Emil Larmi
0.875

Statistiques d’équipe
Buts pour
321
4.01 GFG
Tirs pour
2576
32.20 Avg
Pourcentage en avantage numérique
20.9%
61 GF
Début de zone offensive
36.0%
Buts contre
331
4.14 GAA
Tirs contre
2542
31.78 Avg
Pourcentage en désavantage numérique
75.3%%
83 GA
Début de la zone défensive
37.0%
Informations de l'équipe

Directeur généralFrancois Prevost
EntraîneurTeemu Selanne
DivisionGunther-Sabetzki
ConférenceLouis-Magnus
CapitaineDylan Blujus
Assistant #1Rourke Chartier
Assistant #2Matt Roy


Informations de l’aréna

Capacité3,000
Assistance2,793
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure20
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
1Pierre Engvall (R)X100.006841957480897867697768836260475543740232925,000$
2Rourke Chartier (R) (A)X100.007633818166837480747775658362594940740231975,000$
3Dylan Sikura (R)X100.007341807677746975727573717552494343720232850,000$
4Joachim Blichfeld (R)X100.006537798465846387757172687853496052720213990,000$
5Anthony Richard (R)X100.007033817572806077777667688157534852710231800,000$
6Artturi LehkonenX100.006833778273706774716771637251504052690242700,000$
7Noah Gregor (R)X100.006633817667686969696978687144465625690211600,000$
8Michael Rasmussen (R)X100.007026786882717169737178586448446642680202850,000$
9Emil Bemstrom (R)X100.006725818160685981657273597542435952680203800,000$
10Paul Cotter (R)X100.007433765874666970697077516845446352660201500,000$
11Rasmus Kupari (R)X100.005834787953615378706268557642427542640191500,000$
12Trey Fix-Wolansky (R)X100.004340677757696282596365617642436852640201500,000$
13Jeremy Lauzon (R)X100.006235848270738078488668786365495428730222850,000$
14Dylan Blujus (C)X100.007537777776707675636870756871543650720251800,000$
15Henri Jokiharju (R)X100.007430897169746966477657825254446232720202825,000$
16Matt Roy (A)X100.006649827374766278597468756060544339720242800,000$
17Frederic Allard (R)X100.006947787464717073527055776248484949690222750,000$
18Sami Niku (R)X100.005937728062677976457567674455504352670232800,000$
Rayé
1Nathan Smith (R)X100.006040777851575769636267497045445920620211500,000$
2Jakob Pelletier (R)X100.004935787045706161808261395440407323610182500,000$
3Nicholas Robertson (R)X100.005028717350654976686760497640407819610182500,000$
4Calen Addison (R)X100.005730777556526476387555644442426712630191500,000$
5Jared McIsaac (R)X100.005532767456576774267452634244425619620191500,000$
6Alex Vlasic (R)X100.006822875658665442236546673940408012600182500,000$
MOYENNE D’ÉQUIPE100.00643579756570667361726665655047583868
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
1Marc-André Fleury100.00717574787069777270707992991541741351900,000$
2Emil Larmi100.00736573576181796558756744445672670232600,000$
Rayé
1Arturs Silovs (R)100.00775158727149476266527240407020590182500,000$
MOYENNE D’ÉQUIPE100.0074646869676668666566735961474467
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Teemu Selanne77697390877445Fin424650,000$


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
1Joachim BlichfeldThunderbirds (Stl)RW80655812315801359039011026016.67%41156819.6017183568253000006350.41%1239825041.57350001338
2Rourke ChartierThunderbirds (Stl)C794471115258012812230311119514.52%28154919.6212273944245000004150.09%22205318011.48140006133
3Anthony RichardThunderbirds (Stl)C80324072123001371322215712114.48%31140217.54311141520010171507149.14%9303717001.0325000374
4Jeremy LauzonThunderbirds (Stl)D63115061-33809713213247488.33%111173827.5971219262120005221000%05948000.7000000234
5Dylan SikuraThunderbirds (Stl)RW7725356010400110772145611611.68%39113614.760002801131202063.64%553511121.0601000521
6Emil BemstromThunderbirds (Stl)RW80222951028095531946014211.34%1699712.47671323201000000146.15%264910001.0211000121
7Pierre EngvallThunderbirds (Stl)LW7313314413009495127456110.24%40157521.58134410401152653147.93%1212032000.5611000001
8Michael RasmussenThunderbirds (Stl)LW80201939774012887105365819.05%26130616.33651120249000080054.05%741419000.6000000111
9Artturi LehkonenThunderbirds (Stl)LW8015203555008755137508210.95%1289411.180000130116813056.00%253519000.7800000022
10Sami NikuThunderbirds (Stl)D8042731344057797425395.41%52124915.62471123281000012110%01828000.5001000000
11Henri JokiharjuThunderbirds (Stl)D795253072201181397725396.49%136194824.6702211780006288000%02266000.3100000013
12Noah GregorThunderbirds (Stl)C62171128-111207288138447512.32%2380312.960003270000801051.38%5433320000.7000000024
13Trey Fix-WolanskyThunderbirds (Stl)RW8018927-63403549120488315.00%147559.45000001013950038.64%44169000.7101000110
14Matt RoyThunderbirds (Stl)D7862026-480851048335387.23%71139617.90303717500003800100.00%12537000.3700000012
15Rasmus KupariThunderbirds (Stl)C80111425-142006443103425910.68%127008.7600001000051045.42%251910000.7111000101
16Dylan BlujusThunderbirds (Stl)D766172310680971219232316.52%88154220.300000200112189200%02761000.3011000111
17Frederic AllardThunderbirds (Stl)D79214168220531025216213.85%64118715.03000020004219000%0537000.2700000001
18Paul CotterThunderbirds (Stl)LW805611-1330085336221198.06%177849.81213496000021042.31%26610000.2800000000
19Jakob PelletierThunderbirds (Stl)LW374711-34012124614228.70%52777.5000002000060050.00%264000.7900000100
20Calen AddisonThunderbirds (Stl)D220101022402633181140%2651423.39022055000046000%0614000.3900000010
21Jared McIsaacThunderbirds (Stl)D32156112093121874.76%2443913.74000230000017000%0311000.2700000100
22Alex VlasicThunderbirds (Stl)D3022-220625300%56421.4400017000011000%001000.6200000000
23Nathan SmithThunderbirds (Stl)C11011002640125.00%01818.9000004000000061.29%3100001.0611000010
24Nicholas RobertsonThunderbirds (Stl)RW3000-140733350%14314.5600000000020050.00%40200000000000
Statistiques d’équipe totales ou en moyenne1484327520847256820173916882721899152612.02%8822389716.106195156243236924641186531849.91%4476576509170.711122000364137
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)60252640.8753.963285202171731820510.733155624102
2Marc-André FleuryThunderbirds (Stl)124600.8564.9362120513531821100119000
Statistiques d’équipe totales ou en moyenne72293240.8714.123907402682084100262156733102


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)D182001-01-01USAYes216 Lbs6 ft6NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Anthony RichardThunderbirds (Stl)C231996-01-01CANYes163 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm800,000$0$0$No---------------------------
Artturi LehkonenThunderbirds (Stl)LW241995-01-01FINNo185 Lbs5 ft11NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm700,000$0$0$No750,000$--------700,000$--------No--------
Arturs SilovsThunderbirds (Stl)G182001-01-01LVAYes203 Lbs6 ft4NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Calen AddisonThunderbirds (Stl)D192000-01-01CANYes173 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Dylan BlujusThunderbirds (Stl)D251994-01-01USANo191 Lbs6 ft2NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm800,000$0$0$No---------------------------
Dylan SikuraThunderbirds (Stl)RW231996-01-01CANYes166 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm850,000$0$0$No950,000$--------800,000$--------No--------
Emil BemstromThunderbirds (Stl)RW201999-01-01SWEYes193 Lbs6 ft0NoNoFree AgentNoNo32024-08-20FalseFalsePro & Farm800,000$0$0$No900,000$975,000$-------800,000$800,000$-------NoNo-------
Emil LarmiThunderbirds (Stl)G231996-01-01FINNo185 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm600,000$0$0$No700,000$--------500,000$--------No--------
Frederic AllardThunderbirds (Stl)D221997-01-01CANYes179 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------
Henri JokiharjuThunderbirds (Stl)D201999-01-01FINYes200 Lbs6 ft0NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm825,000$0$0$No975,000$--------825,000$--------No--------
Jakob PelletierThunderbirds (Stl)LW182001-01-01CANYes170 Lbs5 ft9NoNoTrade2025-02-03NoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Jared McIsaacThunderbirds (Stl)D192000-01-01CANYes192 Lbs6 ft1NoNoTrade2025-04-10NoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Jeremy LauzonThunderbirds (Stl)D221997-01-01CANYes204 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm850,000$0$0$No850,000$--------850,000$--------No--------
Joachim BlichfeldThunderbirds (Stl)RW211998-01-01DNKYes187 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm990,000$0$0$No1,500,000$2,200,000$-------850,000$850,000$-------NoNo-------
Marc-André FleuryThunderbirds (Stl)G351984-01-01CANNo180 Lbs6 ft2NoNoFree AgentNoNo12025-03-30FalseFalsePro & Farm900,000$0$0$No---------------------------
Matt RoyThunderbirds (Stl)D241995-01-01USANo200 Lbs6 ft1NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm800,000$0$0$No900,000$--------800,000$--------No--------
Michael RasmussenThunderbirds (Stl)LW201999-01-01CANYes210 Lbs6 ft6NoNoFree Agent2024-08-09NoNo22024-08-20FalseFalsePro & Farm850,000$0$0$No900,000$--------850,000$--------No--------
Nathan SmithThunderbirds (Stl)C211998-01-01USAYes177 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Nicholas RobertsonThunderbirds (Stl)RW182001-01-01USAYes179 Lbs5 ft9NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Noah GregorThunderbirds (Stl)C211998-01-01CANYes185 Lbs6 ft0NoNoTrade2025-04-15NoNo1FalseFalsePro & Farm600,000$0$0$No---------------------------
Paul CotterThunderbirds (Stl)LW201999-01-01USAYes212 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Pierre EngvallThunderbirds (Stl)LW231996-01-01SWEYes215 Lbs6 ft5NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm925,000$0$0$No1,250,000$--------925,000$--------No--------
Rasmus KupariThunderbirds (Stl)C192000-01-01FINYes200 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Rourke ChartierThunderbirds (Stl)C231996-01-01CANYes190 Lbs6 ft0NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm975,000$0$0$No---------------------------
Sami NikuThunderbirds (Stl)D231996-01-01FINYes176 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm800,000$0$0$No800,000$--------600,000$--------No--------
Trey Fix-WolanskyThunderbirds (Stl)RW201999-01-01CANYes186 Lbs5 ft7NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2721.56190 Lbs6 ft11.67696,852$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Pierre EngvallRourke ChartierJoachim Blichfeld40122
2Michael RasmussenAnthony RichardDylan Sikura30122
3Artturi LehkonenNoah GregorEmil Bemstrom20122
4Paul CotterRasmus KupariTrey Fix-Wolansky10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jeremy LauzonHenri Jokiharju40122
2Dylan BlujusMatt Roy30122
3Frederic AllardSami Niku20122
4Jeremy LauzonDylan Blujus10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael RasmussenRourke ChartierJoachim Blichfeld60122
2Pierre EngvallAnthony RichardEmil Bemstrom40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sami NikuJeremy Lauzon60122
2Matt RoyHenri Jokiharju40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Noah GregorPierre Engvall60122
2Anthony RichardDylan Sikura40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Henri JokiharjuJeremy Lauzon60122
2Dylan BlujusFrederic Allard40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Noah Gregor60122Dylan BlujusHenri Jokiharju60122
2Anthony Richard40122Jeremy LauzonFrederic Allard40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Rourke ChartierMichael Rasmussen60122
2Anthony RichardPierre Engvall40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Henri JokiharjuDylan Blujus60122
2Matt RoyJeremy Lauzon40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Pierre EngvallRourke ChartierJoachim BlichfeldJeremy LauzonSami Niku
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Artturi LehkonenNoah GregorPierre EngvallHenri JokiharjuFrederic Allard
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Rasmus Kupari, Dylan Sikura, Trey Fix-WolanskyNoah Gregor, Artturi LehkonenTrey Fix-Wolansky
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Frederic Allard, Sami Niku, Jeremy LauzonSami NikuFrederic Allard, Dylan Blujus
Tirs de pénalité
Rourke Chartier, Anthony Richard, Joachim Blichfeld, Trey Fix-Wolansky, Rasmus Kupari
Gardien
#1 : Emil Larmi, #2 : Marc-André Fleury
Lignes d’attaque personnalisées en prolongation
Rourke Chartier, Pierre Engvall, Dylan Sikura, Joachim Blichfeld, Anthony Richard, Noah Gregor, Artturi Lehkonen, Michael Rasmussen, Emil Bemstrom, Paul Cotter
Lignes de défense personnalisées en prolongation
Jeremy Lauzon, Henri Jokiharju, Dylan Blujus, 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
1Admirals211000001112-11010000069-31100000053220.5001117280084128102126188590576936512114435120.00%7442.86%0865173449.88%870178148.85%653129750.35%174898716427411447723
2Americans211000009811010000034-11100000064220.500916250084128102126088590576936642226439222.22%13469.23%0865173449.88%870178148.85%653129750.35%174898716427411447723
3Barracuda2010010068-21000010045-11010000023-110.250611170084128102126888590576936632710404125.00%50100.00%0865173449.88%870178148.85%653129750.35%174898716427411447723
4Bears3210000016115110000007342110000098140.667162642008412810212114885905769369125266311436.36%13284.62%0865173449.88%870178148.85%653129750.35%174898716427411447723
5Canucks633000001923-432100000880312000001115-460.50019284700841281021219088590576936163675412323417.39%27388.89%0865173449.88%870178148.85%653129750.35%174898716427411447723
6Checkers4220000015141312000001112-11100000042240.500152237108412810212126885905769361074022691417.14%12558.33%0865173449.88%870178148.85%653129750.35%174898716427411447723
7Comets404000001222-1020200000713-62020000059-400.00012203210841281021212388590576936159363478700.00%18477.78%0865173449.88%870178148.85%653129750.35%174898716427411447723
8Condors2110000045-1110000002111010000024-220.50046101084128102127288590576936632314518225.00%7185.71%0865173449.88%870178148.85%653129750.35%174898716427411447723
9Crunch30300000712-51010000035-22020000047-300.00071320008412810212988859057693698402461400.00%12466.67%0865173449.88%870178148.85%653129750.35%174898716427411447723
10Eagles3210000016972200000012481010000045-140.667162339008412810212948859057693610928206314535.71%10280.00%0865173449.88%870178148.85%653129750.35%174898716427411447723
11Firebirds30300000615-92020000049-51010000026-400.00069150084128102129188590576936953818777228.57%9366.67%0865173449.88%870178148.85%653129750.35%174898716427411447723
12Griffins21100000101001010000035-21100000075220.500101828008412810212708859057693665181439500.00%7528.57%0865173449.88%870178148.85%653129750.35%174898716427411447723
13Gulls21000010862100000103211100000054141.000813210084128102127088590576936592618496116.67%9188.89%0865173449.88%870178148.85%653129750.35%174898716427411447723
14Icehogs211000001012-21010000036-31100000076120.500101626008412810212738859057693676318537114.29%5180.00%0865173449.88%870178148.85%653129750.35%174898716427411447723
15Islander421001001414032100000111011000010034-150.6251422360084128102121008859057693613445207721314.29%10370.00%0865173449.88%870178148.85%653129750.35%174898716427411447723
16Little Stars63100110272163100011013103321000001411390.75027426900841281021218888590576936184606814423521.74%34779.41%0865173449.88%870178148.85%653129750.35%174898716427411447723
17Marlies302010001316-31000100054120200000812-420.3331319320084128102129988590576936843430679222.22%15566.67%1865173449.88%870178148.85%653129750.35%174898716427411447723
18Moose2110000010821010000045-11100000063320.5001016260084128102126788590576936721712499222.22%6183.33%0865173449.88%870178148.85%653129750.35%174898716427411447723
19Penguins302001001015-52010010069-31010000046-210.167101727008412810212103885905769369331207213323.08%10460.00%0865173449.88%870178148.85%653129750.35%174898716427411447723
20Phantoms20100100510-51000010045-11010000015-410.25059140084128102126688590576936762418489111.11%9277.78%0865173449.88%870178148.85%653129750.35%174898716427411447723
21Punishers7210210130246301011001112-14200100119127100.71430518100841281021223888590576936198676215935617.14%31777.42%0865173449.88%870178148.85%653129750.35%174898716427411447723
22Rockets210000101174110000006331000001054141.0001117280084128102126088590576936692226398337.50%13284.62%0865173449.88%870178148.85%653129750.35%174898716427411447723
23Senators514000002324-120200000912-3312000001412220.20023365900841281021214288590576936155475810417317.65%29872.41%1865173449.88%870178148.85%653129750.35%174898716427411447723
24Wolfpack421000101717011000000532311000101214-260.7501726430084128102121368859057693614654348616637.50%17476.47%1865173449.88%870178148.85%653129750.35%174898716427411447723
25Wranglers220000001284110000007521100000053241.0001220320084128102126788590576936681716398337.50%8187.50%0865173449.88%870178148.85%653129750.35%174898716427411447723
Total80293703641321331-1040131802520157164-740161901121164167-3790.494321513834308412810212257688590576936254286066617362926120.89%3368375.30%3865173449.88%870178148.85%653129750.35%174898716427411447723
_Since Last GM Reset80293703641321331-1040131802520157164-740161901121164167-3790.494321513834308412810212257688590576936254286066617362926120.89%3368375.30%3865173449.88%870178148.85%653129750.35%174898716427411447723
_Vs Conference50182302421189197-8261011013109898024812011119199-8490.490189299488208412810212160188590576936157753140210721883920.74%2034876.35%1865173449.88%870178148.85%653129750.35%174898716427411447723
_Vs Division19850221176688932012103230210530100144386250.6587612119700841281021261688590576936545194184426811518.52%921781.52%0865173449.88%870178148.85%653129750.35%174898716427411447723

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8079L132151383425762542860666173630
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8029373641321331
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4013182520157164
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4016191121164167
Derniers 10 matchs
WLOTWOTL SOWSOL
241111
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2926120.89%3368375.30%3
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
885905769368412810212
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
865173449.88%870178148.85%653129750.35%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
174898716427411447723


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
28Thunderbirds6Punishers2WR1Sommaire du match
414Thunderbirds4Canucks5LSommaire du match
624Islander2Thunderbirds3WSommaire du match
838Thunderbirds6Little Stars4WSommaire du match
1047Little Stars2Thunderbirds5WSommaire du match
1467Punishers4Thunderbirds3LR1Sommaire du match
1569Thunderbirds5Wolfpack4WXXSommaire du match
1887Thunderbirds5Senators6LSommaire du match
20101Checkers5Thunderbirds3LSommaire du match
22114Thunderbirds5Punishers2WR1Sommaire du match
24125Canucks2Thunderbirds3WSommaire du match
26129Thunderbirds5Canucks4WSommaire du match
29151Islander4Thunderbirds1LSommaire du match
31160Thunderbirds4Little Stars1WSommaire du match
34176Thunderbirds6Senators1WSommaire du match
35181Canucks5Thunderbirds2LSommaire du match
39201Comets5Thunderbirds1LSommaire du match
43221Thunderbirds5Admirals3WSommaire du match
46230Punishers3Thunderbirds4WXR1Sommaire du match
48243Thunderbirds7Icehogs6WSommaire du match
50254Thunderbirds3Islander4LXSommaire du match
51259Wranglers5Thunderbirds7WSommaire du match
54274Thunderbirds2Condors4LSommaire du match
56284Americans4Thunderbirds3LSommaire du match
59298Thunderbirds6Americans4WSommaire du match
61310Phantoms5Thunderbirds4LXSommaire du match
63321Thunderbirds4Marlies5LSommaire du match
65333Thunderbirds2Canucks6LSommaire du match
66338Icehogs6Thunderbirds3LSommaire du match
70358Thunderbirds5Rockets4WXXSommaire du match
71364Checkers2Thunderbirds4WSommaire du match
76388Firebirds4Thunderbirds2LSommaire du match
80410Admirals9Thunderbirds6LSommaire du match
82423Thunderbirds1Phantoms5LSommaire du match
84434Gulls2Thunderbirds3WXXSommaire du match
87445Thunderbirds7Griffins5WSommaire du match
90462Eagles2Thunderbirds8WSommaire du match
93477Thunderbirds2Firebirds6LSommaire du match
94487Punishers5Thunderbirds4LXR1Sommaire du match
97498Thunderbirds4Eagles5LSommaire du match
99509Thunderbirds5Wranglers3WSommaire du match
102517Barracuda5Thunderbirds4LXSommaire du match
105534Thunderbirds4Little Stars6LSommaire du match
107544Rockets3Thunderbirds6WSommaire du match
110565Marlies4Thunderbirds5WXSommaire du match
113578Thunderbirds3Senators5LSommaire du match
115590Thunderbirds6Moose3WSommaire du match
116596Eagles2Thunderbirds4WSommaire du match
119612Thunderbirds2Crunch4LSommaire du match
121620Condors1Thunderbirds2WSommaire du match
126644Senators6Thunderbirds4LSommaire du match
128655Thunderbirds3Wolfpack7LSommaire du match
130670Firebirds5Thunderbirds2LSommaire du match
133687Thunderbirds4Penguins6LSommaire du match
135696Penguins4Thunderbirds3LXSommaire du match
137710Thunderbirds5Gulls4WSommaire du match
138721Bears3Thunderbirds7WSommaire du match
142741Islander4Thunderbirds7WSommaire du match
144750Thunderbirds2Crunch3LSommaire du match
147768Griffins5Thunderbirds3LSommaire du match
151792Moose5Thunderbirds4LSommaire du match
153800Thunderbirds4Checkers2WSommaire du match
156815Wolfpack3Thunderbirds5WSommaire du match
159832Thunderbirds4Wolfpack3WSommaire du match
161843Penguins5Thunderbirds3LSommaire du match
162851Thunderbirds2Barracuda3LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
165865Comets8Thunderbirds6LSommaire du match
171892Senators6Thunderbirds5LSommaire du match
174911Crunch5Thunderbirds3LSommaire du match
178935Thunderbirds4Marlies7LSommaire du match
179938Thunderbirds2Punishers3LXXR1Sommaire du match
180942Checkers5Thunderbirds4LSommaire du match
184964Little Stars5Thunderbirds4LXSommaire du match
185967Thunderbirds6Punishers5WXR1Sommaire du match
188984Thunderbirds2Comets3LSommaire du match
190992Little Stars3Thunderbirds4WXXSommaire du match
1921000Thunderbirds5Bears1WSommaire du match
1941013Thunderbirds3Comets6LSommaire du match
1961024Canucks1Thunderbirds3WSommaire du match
1981031Thunderbirds4Bears7LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance74,42737,300
Assistance PCT93.03%93.25%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2793 - 93.11% 175,925$7,036,986$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,498,296$ 1,881,500$ 1,881,500$ 650,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,314$ 1,830,607$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 12,532$ 0$




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