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Thunderbirds
GP: 26 | W: 15 | L: 9 | OTL: 2 | P: 32
GF: 108 | GA: 96 | PP%: 18.18% | PK%: 81.65%
DG: Francois Prevost | Morale : 45 | Moyenne d’équipe : 68
Prochains matchs #321 vs Marlies
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Centre de jeu
Thunderbirds
15-9-2, 32pts
6
FINAL
4 Americans
11-11-1, 23pts
Team Stats
OTL1SéquenceL2
5-6-1Fiche domicile6-6-0
10-3-1Fiche domicile5-5-1
5-3-2Derniers 10 matchs4-5-1
4.15Buts par match 3.78
3.69Buts contre par match 4.13
18.18%Pourcentage en avantage numérique28.09%
81.65%Pourcentage en désavantage numérique80.37%
Phantoms
9-11-3, 21pts
5
FINAL
4 Thunderbirds
15-9-2, 32pts
Team Stats
OTW1SéquenceOTL1
5-6-1Fiche domicile5-6-1
4-5-2Fiche domicile10-3-1
5-5-0Derniers 10 matchs5-3-2
3.96Buts par match 4.15
4.48Buts contre par match 3.69
22.34%Pourcentage en avantage numérique18.18%
78.65%Pourcentage en désavantage numérique81.65%
Thunderbirds
15-9-2, 32pts
Jour 63
Marlies
13-9-2, 28pts
Statistiques d’équipe
OTL1SéquenceL1
5-6-1Fiche domicile6-4-2
10-3-1Fiche visiteur7-5-0
5-3-210 derniers matchs5-4-1
4.15Buts par match 4.13
3.69Buts contre par match 4.13
18.18%Pourcentage en avantage numérique21.21%
81.65%Pourcentage en désavantage numérique73.12%
Thunderbirds
15-9-2, 32pts
Jour 65
Canucks
14-8-3, 31pts
Statistiques d’équipe
OTL1SéquenceSOL1
5-6-1Fiche domicile6-5-1
10-3-1Fiche visiteur8-3-2
5-3-210 derniers matchs7-2-1
4.15Buts par match 4.52
3.69Buts contre par match 4.52
18.18%Pourcentage en avantage numérique24.75%
81.65%Pourcentage en désavantage numérique86.67%
Icehogs
15-7-1, 31pts
Jour 66
Thunderbirds
15-9-2, 32pts
Statistiques d’équipe
W2SéquenceOTL1
7-4-1Fiche domicile5-6-1
8-3-0Fiche visiteur10-3-1
6-4-010 derniers matchs5-3-2
4.39Buts par match 4.15
3.39Buts contre par match 4.15
25.51%Pourcentage en avantage numérique18.18%
78.64%Pourcentage en désavantage numérique81.65%
Meneurs d'équipe
Buts
Joachim Blichfeld
22
Passes
Rourke Chartier
24
Points
Joachim Blichfeld
39
Plus/Moins
Anthony Richard
11
Victoires
Emil Larmi
12
Pourcentage d’arrêts
Magnus Hellberg
0.881

Statistiques d’équipe
Buts pour
108
4.15 GFG
Tirs pour
844
32.46 Avg
Pourcentage en avantage numérique
18.2%
20 GF
Début de zone offensive
37.4%
Buts contre
96
3.69 GAA
Tirs contre
771
29.65 Avg
Pourcentage en désavantage numérique
81.7%%
20 GA
Début de la zone défensive
36.4%
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
Assistance2,791
Billets de saison300


Informations de la formation

Équipe Pro26
Équipe Mineure20
Limite contact 46 / 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
1Rourke Chartier (R) (A)X100.007633818166837480747775658362594952740231975,000$
2Dylan Sikura (R)X100.007341807677746975727573717552494352720232850,000$
3Joachim Blichfeld (R)X100.006537798465846387757172687853496052720213990,000$
4Anthony Richard (R)X100.007033817572806077777667688157534852710231800,000$
5Trent Frederic (R)X100.006727897171867062727263786749455652700211800,000$
6Artturi LehkonenX100.006833778273706774716771637251504052690242700,000$
7Michael Rasmussen (R)X100.007026786882717169737178586448446652680202850,000$
8Emil Bemstrom (R)X100.006725818160685981657273597542435952680203800,000$
9Paul Cotter (R)X100.007433765874666970697077516845446352660201500,000$
10Rasmus Kupari (R)X100.005834787953615378706268557642427552640191500,000$
11Trey Fix-Wolansky (R)X100.004340677657696282596365617642436852640201500,000$
12Rafael Harvey-Pinard (R)X100.007145847574676661626962537644455519640202500,000$
13Dylan Blujus (C)X100.007537777776707675636870756871543652720251800,000$
14Henri Jokiharju (R)X100.007430897169746966477657825254446252720202825,000$
15Matt Roy (A)X100.006649827374766278597468756060544339720242800,000$
16Frederic Allard (R)X100.006947787464717073527055776248484952690222750,000$
17Sami Niku (R)X100.005937728062677976457567674455504352670232800,000$
18Calen Addison (R)X100.005730777556526476387555644442426731630191500,000$
Rayé
1Pierre Engvall (R)X74.906841957480897867697768836260475543740232925,000$
2Nathan Smith (R)X100.006040777851575769636267497045445920620211500,000$
3Nicholas Robertson (R)X100.005028717350654976686760497640407820610182500,000$
4Jeremy Lauzon (R)X97.516235848270738078488668786365495439730222850,000$
5Alex Vlasic (R)X100.006822875658665442236546673940408020600182500,000$
MOYENNE D’ÉQUIPE98.80663580756771667361716666675147574468
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
1Magnus Hellberg99.00736465746871686970717369662558690281700,000$
2Emil Larmi100.00736573576181796558756744445658670232600,000$
Rayé
1Arturs Silovs (R)100.00775158727149476266527240407027590182500,000$
MOYENNE D’ÉQUIPE99.6774606568676765656566715150504865
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)RW26221739-12204732128327617.19%1150519.4656113098000003169.23%392512021.5411000523
2Rourke ChartierThunderbirds (Stl)C261124350200433497336011.34%1151419.7948121799000000048.98%733235001.3611000150
3Anthony RichardThunderbirds (Stl)C26717241112036497117359.86%945917.660668780001501052.46%284115001.0501000221
4Dylan SikuraThunderbirds (Stl)RW261011218160392262134316.13%838014.62000130001401066.67%1594111.1100000210
5Emil BemstromThunderbirds (Stl)RW2611920-280291470214515.71%332712.61235978000000055.56%9164001.2200000111
6Jeremy LauzonThunderbirds (Stl)D1621416610015363512135.71%3242126.32112660000162000%01912000.7600000112
7Michael RasmussenThunderbirds (Stl)LW26771411240453236111519.44%1043016.56224996000020054.55%2255000.6500000101
8Henri JokiharjuThunderbirds (Stl)D263101374037482991510.34%4065025.010000700003102000%0526000.4000000011
9Pierre EngvallThunderbirds (Stl)LW256612500342947141412.77%1247619.06000000001902031.71%41512000.5000000001
10Sami NikuThunderbirds (Stl)D262101202401925235118.70%1341515.97224711000004100%0610000.5800000000
11Matt RoyThunderbirds (Stl)D243811120293128121710.71%3043117.98202465000010000%0813000.5100000011
12Trent FredericThunderbirds (Stl)C2628101201740215169.52%736414.01000050000991045.34%31127000.5500000011
13Trey Fix-WolanskyThunderbirds (Stl)RW2682102100151946131817.39%52429.33000001012330036.36%1146000.8200000000
14Artturi LehkonenThunderbirds (Stl)LW2618904029174012222.50%42529.73000040115291025.00%4185000.7100000000
15Rasmus KupariThunderbirds (Stl)C26448-100211033111512.12%42228.5600000000021057.89%7641000.7200000101
16Dylan BlujusThunderbirds (Stl)D263585260364220131415.00%3052120.0700009011167200%0822000.3111000010
17Paul CotterThunderbirds (Stl)LW26448-110038172512916.00%832612.57213478000001020.00%1022000.4900000000
18Calen AddisonThunderbirds (Stl)D120664120172013730%1030425.40011045000027000%048000.3900000010
19Frederic AllardThunderbirds (Stl)D26145080223520565.00%1338814.9400000000175000%0111000.2600000000
20Rafael Harvey-PinardThunderbirds (Stl)LW1000-100010020%088.720000000000000%00100000000000
Statistiques d’équipe totales ou en moyenne46810717428155214056855384425744912.68%260764516.34203050959071231669914149.32%1555175171130.7434000141713
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)2112710.8773.55116720695592702100206000
2Magnus HellbergThunderbirds (Stl)93210.8813.754000025210107110.6673620000
Statistiques d’équipe totales ou en moyenne3015920.8783.60156720947693773232626000


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 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 Non Activé 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 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)D182001-01-01Yes216 Lbs6 ft6NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Anthony RichardThunderbirds (Stl)C231996-01-01Yes163 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm800,000$558,416$0$0$No------------------
Artturi LehkonenThunderbirds (Stl)LW241995-01-01No185 Lbs5 ft11NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm700,000$488,614$0$0$No750,000$--------No--------
Arturs SilovsThunderbirds (Stl)G182001-01-01Yes203 Lbs6 ft4NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Calen AddisonThunderbirds (Stl)D192000-01-01Yes173 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Dylan BlujusThunderbirds (Stl)D251994-01-01No191 Lbs6 ft2NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm800,000$558,416$0$0$No------------------
Dylan SikuraThunderbirds (Stl)RW231996-01-01Yes166 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm850,000$593,317$0$0$No950,000$--------No--------
Emil BemstromThunderbirds (Stl)RW201999-01-01Yes193 Lbs6 ft0NoNoFree AgentNoNo32024-08-20FalseFalsePro & Farm800,000$558,416$0$0$No900,000$975,000$-------NoNo-------
Emil LarmiThunderbirds (Stl)G231996-01-01No185 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm600,000$418,812$0$0$No700,000$--------No--------
Frederic AllardThunderbirds (Stl)D221997-01-01Yes179 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm750,000$523,515$0$0$No750,000$--------No--------
Henri JokiharjuThunderbirds (Stl)D201999-01-01Yes200 Lbs6 ft0NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm825,000$575,866$0$0$No975,000$--------No--------
Jeremy LauzonThunderbirds (Stl)D221997-01-01Yes204 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm850,000$593,317$0$0$No850,000$--------No--------
Joachim BlichfeldThunderbirds (Stl)RW211998-01-01Yes187 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm990,000$691,040$0$0$No1,500,000$2,200,000$-------NoNo-------
Magnus HellbergThunderbirds (Stl)G281991-01-01No185 Lbs6 ft5NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm700,000$488,614$0$0$No------------------
Matt RoyThunderbirds (Stl)D241995-01-01No200 Lbs6 ft1NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm800,000$558,416$0$0$No900,000$--------No--------
Michael RasmussenThunderbirds (Stl)LW201999-01-01Yes210 Lbs6 ft6NoNoFree Agent2024-08-09NoNo22024-08-20FalseFalsePro & Farm850,000$593,317$0$0$No900,000$--------No--------
Nathan SmithThunderbirds (Stl)C211998-01-01Yes177 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Nicholas RobertsonThunderbirds (Stl)RW182001-01-01Yes179 Lbs5 ft9NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Paul CotterThunderbirds (Stl)LW201999-01-01Yes212 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Pierre Engvall (sur la masse salariale)Thunderbirds (Stl)LW231996-01-01Yes215 Lbs6 ft5NoNoFree AgentNoNo22024-08-20FalseFalsePro & Farm925,000$645,668$0$0$Yes1,250,000$--------No--------
Rafael Harvey-PinardThunderbirds (Stl)LW201999-01-01Yes183 Lbs6 ft0NoNoTrade2024-08-09NoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Rasmus KupariThunderbirds (Stl)C192000-01-01Yes200 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Rourke ChartierThunderbirds (Stl)C231996-01-01Yes190 Lbs6 ft0NoNoFree AgentNoNo12024-08-20FalseFalsePro & Farm975,000$680,569$0$0$No------------------
Sami NikuThunderbirds (Stl)D231996-01-01Yes176 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm800,000$558,416$0$0$No800,000$--------No--------
Trent FredericThunderbirds (Stl)C211998-01-01Yes203 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm800,000$558,416$0$0$No------------------
Trey Fix-WolanskyThunderbirds (Stl)RW201999-01-01Yes186 Lbs5 ft7NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2621.46191 Lbs6 ft11.69704,423$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael RasmussenRourke ChartierJoachim Blichfeld40122
2Artturi LehkonenAnthony RichardDylan Sikura30122
3Paul CotterTrent FredericEmil Bemstrom20122
4Rafael Harvey-PinardRasmus KupariTrey Fix-Wolansky10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Calen AddisonHenri Jokiharju40122
2Dylan BlujusMatt Roy30122
3Frederic AllardSami Niku20122
4Calen AddisonDylan Blujus10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Michael RasmussenRourke ChartierJoachim Blichfeld60122
2Paul CotterAnthony RichardEmil Bemstrom40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Sami NikuCalen Addison60122
2Matt RoyHenri Jokiharju40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Trent FredericArtturi Lehkonen60122
2Anthony RichardDylan Sikura40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Henri JokiharjuCalen Addison60122
2Dylan BlujusFrederic Allard40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Trent Frederic60122Dylan BlujusHenri Jokiharju60122
2Anthony Richard40122Calen AddisonFrederic Allard40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Rourke ChartierMichael Rasmussen60122
2Anthony RichardArtturi Lehkonen40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Henri JokiharjuDylan Blujus60122
2Matt RoyCalen Addison40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Michael RasmussenRourke ChartierJoachim BlichfeldCalen AddisonSami Niku
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Artturi LehkonenTrent FredericDylan SikuraHenri JokiharjuFrederic Allard
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Rasmus Kupari, Dylan Sikura, Trey Fix-WolanskyTrent Frederic, Artturi LehkonenTrey Fix-Wolansky
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Frederic Allard, Sami Niku, Calen AddisonSami NikuFrederic Allard, Dylan Blujus
Tirs de pénalité
Rourke Chartier, Anthony Richard, Joachim Blichfeld, Trey Fix-Wolansky, Rasmus Kupari
Gardien
#1 : Emil Larmi, #2 : Magnus Hellberg
Lignes d’attaque personnalisées en prolongation
Rourke Chartier, Rafael Harvey-Pinard, Dylan Sikura, Joachim Blichfeld, Anthony Richard, Trent Frederic, Trent Frederic, Artturi Lehkonen, Michael Rasmussen, Emil Bemstrom, Paul Cotter
Lignes de défense personnalisées en prolongation
Calen Addison, 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
1Admirals11000000532000000000001100000053221.000571200313738330289291252152711423200.00%20100.00%029357550.96%26856047.86%20640251.24%566315533246469235
2Americans211000009811010000034-11100000064220.500916250031373836028929125215642226439222.22%13469.23%029357550.96%26856047.86%20640251.24%566315533246469235
3Canucks422000001416-22110000057-22110000099040.5001420340031373831422892912521510544388115320.00%19289.47%029357550.96%26856047.86%20640251.24%566315533246469235
4Checkers1010000035-21010000035-20000000000000.00034710313738336289291252152410414300.00%20100.00%029357550.96%26856047.86%20640251.24%566315533246469235
5Comets1010000015-41010000015-40000000000000.0001230031373833428929125215366623400.00%3166.67%029357550.96%26856047.86%20640251.24%566315533246469235
6Condors1010000024-2000000000001010000024-200.00023510313738329289291252153086265120.00%30100.00%029357550.96%26856047.86%20640251.24%566315533246469235
7Icehogs11000000761000000000001100000076121.0007101700313738340289291252153613424200.00%3166.67%029357550.96%26856047.86%20640251.24%566315533246469235
8Islander31100100710-32110000046-21000010034-130.5007101700313738370289291252159239165915213.33%8275.00%029357550.96%26856047.86%20640251.24%566315533246469235
9Little Stars3300000015781100000052322000000105561.00015243900313738390289291252158128327211327.27%16475.00%029357550.96%26856047.86%20640251.24%566315533246469235
10Phantoms1000010045-11000010045-10000000000010.5004812003137383342892912521536812224125.00%6183.33%029357550.96%26856047.86%20640251.24%566315533246469235
11Punishers42101000181172010100077022000000114760.7501832500031373831382892912521511237329819210.53%16287.50%029357550.96%26856047.86%20640251.24%566315533246469235
12Senators2110000011740000000000021100000117420.50011182900313738359289291252155414243911218.18%12191.67%129357550.96%26856047.86%20640251.24%566315533246469235
13Wolfpack10000010541000000000001000001054121.0005611003137383452892912521535910257342.86%5260.00%029357550.96%26856047.86%20640251.24%566315533246469235
14Wranglers11000000752110000007520000000000021.00071421003137383372892912521539112193133.33%10100.00%029357550.96%26856047.86%20640251.24%566315533246469235
Total261390121010896121246011003946-7149300110695019320.615108174282203137383844289291252157712602165681102018.18%1092081.65%129357550.96%26856047.86%20640251.24%566315533246469235
_Since Last GM Reset261390121010896121246011003946-7149300110695019320.615108174282203137383844289291252157712602165681102018.18%1092081.65%129357550.96%26856047.86%20640251.24%566315533246469235
_Vs Conference17860111063585935010002532-785100110382612210.618639816110313738355528929125215485173138372741317.57%691381.16%029357550.96%26856047.86%20640251.24%566315533246469235
_Vs Division117301000473413522010001716165100000301812160.72747761230031373833702892912521529810910225145817.78%51884.31%029357550.96%26856047.86%20640251.24%566315533246469235

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2632OTL110817428284477126021656820
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
26139121010896
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
124611003946
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
149301106950
Derniers 10 matchs
WLOTWOTL SOWSOL
431200
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1102018.18%1092081.65%1
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
289291252153137383
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
29357550.96%26856047.86%20640251.24%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
566315533246469235


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
63321Thunderbirds-Marlies-
65333Thunderbirds-Canucks-
66338Icehogs-Thunderbirds-
70358Thunderbirds-Rockets-
71364Checkers-Thunderbirds-
76388Firebirds-Thunderbirds-
80410Admirals-Thunderbirds-
82423Thunderbirds-Phantoms-
84434Gulls-Thunderbirds-
87445Thunderbirds-Griffins-
90462Eagles-Thunderbirds-
93477Thunderbirds-Firebirds-
94487Punishers-Thunderbirds-
97498Thunderbirds-Eagles-
99509Thunderbirds-Wranglers-
102517Barracuda-Thunderbirds-
105534Thunderbirds-Little Stars-
107544Rockets-Thunderbirds-
110565Marlies-Thunderbirds-
113578Thunderbirds-Senators-
115590Thunderbirds-Moose-
116596Eagles-Thunderbirds-
119612Thunderbirds-Crunch-
121620Condors-Thunderbirds-
126644Senators-Thunderbirds-
128655Thunderbirds-Wolfpack-
130670Firebirds-Thunderbirds-
133687Thunderbirds-Penguins-
135696Penguins-Thunderbirds-
137710Thunderbirds-Gulls-
138721Bears-Thunderbirds-
142741Islander-Thunderbirds-
144750Thunderbirds-Crunch-
147768Griffins-Thunderbirds-
151792Moose-Thunderbirds-
153800Thunderbirds-Checkers-
156815Wolfpack-Thunderbirds-
159832Thunderbirds-Wolfpack-
161843Penguins-Thunderbirds-
162851Thunderbirds-Barracuda-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
165865Comets-Thunderbirds-
171892Senators-Thunderbirds-
174911Crunch-Thunderbirds-
178935Thunderbirds-Marlies-
179938Thunderbirds-Punishers-
180942Checkers-Thunderbirds-
184964Little Stars-Thunderbirds-
185967Thunderbirds-Punishers-
188984Thunderbirds-Comets-
190992Little Stars-Thunderbirds-
1921000Thunderbirds-Bears-
1941013Thunderbirds-Comets-
1961024Canucks-Thunderbirds-
1981031Thunderbirds-Bears-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance22,33111,159
Assistance PCT93.05%92.99%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
28 2791 - 93.03% 175,834$2,110,007$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
744,222$ 1,739,000$ 1,670,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
8,609$ 541,609$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
4,923,350$ 141 11,827$ 1,667,607$




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