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Thunderbirds

GP: 81 | W: 30 | L: 47 | OTL: 4 | P: 64
GF: 291 | GA: 411 | PP%: 21.57% | PK%: 73.68%
DG: Jonathan Auger | Morale : 50 | Moyenne d'Équipe : 62
Prochain matchs #1265 vs Bears
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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 SP
1Oskar LindblomX100.00693787677675946553666764636567055660
2Peter HollandX100.00633884657994936370626164627568050650
3David KampfXX100.00623788637876796178666274636764040640
4Max JonesX100.00734079638780656258616266596163050630
5Kevin PorterX100.00583886607291875970625456578279050620
6Pascal LabergeX100.00553981577275695653545956586163050590
7Deven SideroffX100.00523789566777715463575152546362050570
8Nathan NoelX100.00544177555687815455525153526362050560
9Matt Roy (R)X100.00713789657785666430685970526765056650
10Caleb JonesX100.00633788647688676330715765516362050630
11Christian DjoosX100.00563591636874586230725863516965050630
12Christian JarosX100.00804485598477745830665362486563050620
13TJ BrennanX100.00684080608192895930635358517870050620
14Matt TennysonX100.00663789598178665830575359467769050610
15Kyle CumiskeyX100.00533691586882765730605154468273050600
16Lucas CarlssonX100.00593788587293915730585355476362050600
Rayé
MOYENNE D'ÉQUIPE100.0063388661758377604662576154696605062
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 SP
1Chad Johnson100.0078747283777678777678778287050680
2Dustin Tokarski100.0077737175767577767577767884050670
Rayé
1Eamon McAdam100.0073706874727173727173726973050640
2Zachary Fucale100.0071656378706971706971706771050620
3Michael Dipietro100.0064656374636264636264636063050580
MOYENNE D'ÉQUIPE100.007369677772717372717372717605064
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Peter HollandThunderbirds (FLO)C819334127-1538026934466517952813.98%149195624.15137205714020291239262.27%1948000111.30160001044
2Kevin PorterThunderbirds (FLO)C81493584-353551662664921333409.96%89158919.626713501120110327161.93%192300031.0612100656
3Matt TennysonThunderbirds (FLO)D81155368-20460231127192601167.81%132140917.4001146011021132.00%2500000.9700000051
4David KampfThunderbirds (FLO)C/RW3218264418604777214751278.41%2374523.3023516501012283063.16%9500011.1815000422
5Max JonesThunderbirds (FLO)LW32143044371209570188491257.45%1365820.5704419440005190260.38%5300001.3423000352
6Caleb JonesThunderbirds (FLO)D8193342-43201098669214613.04%10495211.75213823000024200.00%000000.8800000012
7Deven SideroffThunderbirds (FLO)RW32920293620193075304912.00%360518.92224841000000068.18%4400000.9600000013
8Pascal LabergeThunderbirds (FLO)C321610266403865110358814.55%853816.8200011000163154.23%60300010.9700000302
9Christian DjoosThunderbirds (FLO)D324212518100283136112611.11%2557918.10123623000027100.00%000000.8600000001
10Nathan NoelThunderbirds (FLO)LW3288161075383178245710.26%653916.87000000000111051.43%3500000.5900001012
11Oskar LindblomThunderbirds (FLO)LW1861016380374210222575.88%941923.310227280004330056.85%24100000.7614000111
12Christian JarosThunderbirds (FLO)D324913720054212892914.29%2144013.780000000001000.00%000000.5900000001
13Derrick PouliotPanthersD162911107538171941910.53%1331919.991121025011026000.00%000000.6900001101
14TJ BrennanThunderbirds (FLO)D3229118803213319136.45%2543713.680000000004000.00%000000.5000000010
15Matt RoyThunderbirds (FLO)D14178820719186215.56%1928320.24101819011023000.00%000000.5600000000
16Kyle CumiskeyThunderbirds (FLO)D32066-5201189440.00%92367.390000000000000.00%000000.5100000000
17Lucas CarlssonThunderbirds (FLO)D32000-100100000.00%1200.6400001000000050.00%200000.0000000000
Stats d'équipe Total ou en Moyenne6922503205708123915122012472326671164510.75%6491173116.952830581945213472136927760.72%4969000160.97620102282628
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
1Chad JohnsonThunderbirds (FLO)3221740.9272.22194703729910000.52619320222
Stats d'équipe Total ou en Moyenne3221740.9272.22194703729910000.52619320222


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Caleb JonesThunderbirds (FLO)D211997-06-06No194 Lbs6 ft1NoNoNo2Pro & Farm815,000$0$0$No815,000$Lien / Lien NHL
Chad JohnsonThunderbirds (FLO)G321986-06-10No197 Lbs6 ft3NoNoNo1Pro & Farm1,750,000$0$0$NoLien / Lien NHL
Christian DjoosThunderbirds (FLO)D241994-08-06No169 Lbs6 ft0NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Christian JarosThunderbirds (FLO)D221996-04-02No201 Lbs6 ft3NoNoNo2Pro & Farm801,667$0$0$No801,667$Lien / Lien NHL
David KampfThunderbirds (FLO)C/RW231995-01-12No188 Lbs6 ft2NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Deven SideroffThunderbirds (FLO)RW211997-04-14No171 Lbs5 ft11NoNoNo2Pro & Farm935,833$0$0$No935,833$Lien / Lien NHL
Dustin TokarskiThunderbirds (FLO)G291989-09-16No204 Lbs6 ft0NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Eamon McAdamThunderbirds (FLO)G241994-09-24No200 Lbs6 ft0NoNoNo1Pro & Farm950,000$0$0$NoLien / Lien NHL
Kevin PorterThunderbirds (FLO)C321986-03-12No190 Lbs6 ft0NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Kyle CumiskeyThunderbirds (FLO)D311986-12-02No180 Lbs5 ft11NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Lucas CarlssonThunderbirds (FLO)D211997-07-05No189 Lbs6 ft0NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien / Lien NHL
Matt RoyThunderbirds (FLO)D231995-03-01Yes200 Lbs6 ft1NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Matt TennysonThunderbirds (FLO)D281990-04-23No205 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Max JonesThunderbirds (FLO)LW201998-02-17No220 Lbs6 ft3NoNoNo3Pro & Farm863,333$0$0$No863,333$863,333$Lien / Lien NHL
Michael DipietroThunderbirds (FLO)G191999-06-09No200 Lbs6 ft0NoNoNo4Pro & Farm925,000$0$0$No910,833$910,833$910,833$Lien / Lien NHL
Nathan NoelThunderbirds (FLO)LW211997-06-21No174 Lbs5 ft1NoNoNo2Pro & Farm925,000$0$0$No925,000$Lien / Lien NHL
Oskar LindblomThunderbirds (FLO)LW221996-08-15No191 Lbs6 ft1NoNoNo2Pro & Farm1,137,500$0$0$No1,137,500$Lien / Lien NHL
Pascal LabergeThunderbirds (FLO)C201998-04-09No172 Lbs6 ft1NoNoNo3Pro & Farm863,333$0$0$No863,333$863,333$Lien / Lien NHL
Peter HollandThunderbirds (FLO)C271991-01-14No193 Lbs6 ft2NoNoNo1Pro & Farm675,000$0$0$NoLien / Lien NHL
TJ BrennanThunderbirds (FLO)D291989-04-03No216 Lbs6 ft1NoNoNo2Pro & Farm675,000$0$0$No675,000$Lien / Lien NHL
Zachary FucaleThunderbirds (FLO)G231995-05-28No187 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2124.38192 Lbs6 ft01.71856,746$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Peter HollandDavid Kampf30122
2Max JonesKevin PorterDeven Sideroff30122
3Nathan NoelPascal LabergeMatt Tennyson25122
4Peter HollandDavid Kampf15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
130122
2Christian DjoosCaleb Jones30122
3TJ BrennanChristian Jaros25122
4Matt TennysonKyle Cumiskey15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Peter HollandDavid Kampf60122
2Max JonesKevin PorterDeven Sideroff40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Christian DjoosCaleb Jones40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Peter Holland60122
2David KampfMax Jones40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Christian DjoosCaleb Jones40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
2Peter Holland40122Christian DjoosCaleb Jones40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Peter Holland60122
2David KampfMax Jones40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
2Christian DjoosCaleb Jones40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Peter HollandDavid Kampf
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Peter HollandDavid Kampf
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Pascal Laberge, Nathan Noel, Kevin PorterPascal Laberge, Nathan NoelKevin Porter
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Lucas Carlsson, TJ Brennan, Christian JarosLucas CarlssonTJ Brennan, Christian Jaros
Tirs de Pénalité
, Peter Holland, David Kampf, Max Jones, Kevin Porter
Gardien
#1 : Chad Johnson, #2 : Dustin Tokarski


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
LigueDomicileVisiteur
# 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
1Admirals20200000614-81010000035-21010000039-600.00069150012390766701103111010653313339638000.00%20100.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
2Americans413000001020-102110000079-220200000311-820.250101727001239076616011031110106533206606928225.00%3166.67%01448274552.75%1348277648.56%740143351.64%189313932055521940459
3Barracuda2020000017-61010000015-41010000002-200.0001230012390766661103111010653380211332700.00%4175.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
4Bears20200000216-1410100000110-91010000016-500.00024600123907665811031110106533116391145200.00%3166.67%01448274552.75%1348277648.56%740143351.64%189313932055521940459
5Bruins41300000924-1521100000711-420200000213-1120.25091524001239076612011031110106533199392210310220.00%9366.67%01448274552.75%1348277648.56%740143351.64%189313932055521940459
6Checkers30300000517-121010000027-520200000310-700.0005914001239076611711031110106533156401266500.00%4175.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
7Comets211000001055110000007161010000034-120.500101727001239076612711031110106533732585611100.00%4175.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
8Condors22000000197121100000010191100000096341.00019325100123907661221103111010653389236562150.00%20100.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
9Crunch404000001039-2920200000320-1720200000719-1200.000101727001239076610311031110106533310832060400.00%10370.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
10Devils33000000187111100000071622000000116561.00018325000123907661871103111010653311733657100.00%3166.67%01448274552.75%1348277648.56%740143351.64%189313932055521940459
11Eagles20200000115-141010000017-61010000008-800.00012300123907665611031110106533117358424125.00%4250.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
12Griffins413000001017-720200000410-62110000067-120.2501016261012390766177110311101065331865210949333.33%5180.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
13Gulls20100001411-71010000017-61000000134-110.250481200123907665911031110106533111254532150.00%20100.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
14Heat220000001275110000005231100000075241.0001218300012390766139110311101065336213648200.00%3166.67%11448274552.75%1348277648.56%740143351.64%189313932055521940459
15IceHogs21100000871110000005231010000035-220.5008152300123907665911031110106533671963711327.27%3166.67%01448274552.75%1348277648.56%740143351.64%189313932055521940459
16Marlies431000001113-22110000049-52200000074360.7501120310012390766127110311101065331895222828225.00%10280.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
17Monsters302000101419-51010000079-220100010710-320.333142034101239076681110311101065331554212508337.50%6266.67%01448274552.75%1348277648.56%740143351.64%189313932055521940459
18Moose22000000177101100000076111000000101941.0001730470012390766119110311101065338525845000.00%4175.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
19Penguins3210000018171211000001214-21100000063340.6671832500012390766135110311101065331605414844125.00%7271.43%11448274552.75%1348277648.56%740143351.64%189313932055521940459
20Phantoms311000101011-120100010711-41100000030340.667101727011239076613611031110106533130226546233.33%3166.67%01448274552.75%1348277648.56%740143351.64%189313932055521940459
21Rampage2020000047-31010000023-11010000024-200.00048120012390766761103111010653368164407114.29%20100.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
22Reign2020000069-31010000035-21010000034-100.000610160012390766611103111010653390258352150.00%4325.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
23Roadrunners20100001514-910100000311-81000000123-110.250571200123907666011031110106533110384402150.00%20100.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
24Rocket412000011318-52010000159-42110000089-130.37513213400123907661431103111010653313863259410110.00%7271.43%11448274552.75%1348277648.56%740143351.64%189313932055521940459
25Senators440000003512232200000018612220000001761181.0003561960112390766281110311101065331874081067342.86%40100.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
26Sound Tigers30300000427-231010000009-920200000418-1400.0004610001239076694110311101065331583210661119.09%6350.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
27Stars22000000141131100000010821100000043141.000142236001239076614411031110106533107291258100.00%6183.33%01448274552.75%1348277648.56%740143351.64%189313932055521940459
Total81284700024291411-12040142400011152217-6541142300013139194-55640.39529149278322123907663291110311101065333860108130117641533321.57%1333573.68%31448274552.75%1348277648.56%740143351.64%189313932055521940459
29Wild20200000614-81010000016-51010000058-300.00069150012390766671103111010653386298395120.00%4175.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
30Wolf Pack31200000816-821100000811-31010000005-520.33381422001239076698110311101065331265445410220.00%20100.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
31Wolves2010000113-21010000012-11000000101-110.2501230012390766491103111010653349141238400.00%50100.00%01448274552.75%1348277648.56%740143351.64%189313932055521940459
_Since Last GM Reset81284700024291411-12040142400011152217-6541142300013139194-55640.39529149278322123907663291110311101065333860108130117641533321.57%1333573.68%31448274552.75%1348277648.56%740143351.64%189313932055521940459
_Vs Conference46182600011163242-79239120001188128-40239140000075114-39390.424163282445021239076618861103111010653322656361741019871719.54%752172.00%21448274552.75%1348277648.56%740143351.64%189313932055521940459
_Vs Division235150001079130-511137000104472-281228000003558-23120.2617913421311123907669061103111010653311183167547647919.15%341167.65%11448274552.75%1348277648.56%740143351.64%189313932055521940459

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8164W2291492783329138601081301176422
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8128470024291411
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4014240011152217
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4114230013139194
Derniers 10 Matchs
WLOTWOTL SOWSOL
730000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1533321.57%1333573.68%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
1103111010653312390766
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
1448274552.75%1348277648.56%740143351.64%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
189313932055521940459


Derniers Match 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
2 - 2019-10-035Thunderbirds5Crunch9LSommaire du Match
4 - 2019-10-0521Crunch9Thunderbirds1LSommaire du Match
7 - 2019-10-0836Checkers7Thunderbirds2LSommaire du Match
10 - 2019-10-1158Thunderbirds1Americans3LSommaire du Match
11 - 2019-10-1268Thunderbirds3Sound Tigers9LSommaire du Match
13 - 2019-10-1480Thunderbirds7Devils5WSommaire du Match
17 - 2019-10-18107Eagles7Thunderbirds1LSommaire du Match
18 - 2019-10-19121Thunderbirds3Admirals9LSommaire du Match
21 - 2019-10-22135Penguins12Thunderbirds4LSommaire du Match
23 - 2019-10-24153Thunderbirds7Heat5WSommaire du Match
26 - 2019-10-27170Thunderbirds9Condors6WSommaire du Match
27 - 2019-10-28178Thunderbirds3Comets4LSommaire du Match
29 - 2019-10-30192Thunderbirds0Eagles8LSommaire du Match
32 - 2019-11-02209Griffins7Thunderbirds3LSommaire du Match
37 - 2019-11-07238Bears10Thunderbirds1LSommaire du Match
39 - 2019-11-09252Thunderbirds1Sound Tigers9LSommaire du Match
40 - 2019-11-10263Thunderbirds0Wolf Pack5LSommaire du Match
42 - 2019-11-12272Thunderbirds0Bruins10LSommaire du Match
44 - 2019-11-14288Moose6Thunderbirds7WSommaire du Match
46 - 2019-11-16306Wolf Pack9Thunderbirds3LSommaire du Match
49 - 2019-11-19319Phantoms9Thunderbirds4LSommaire du Match
51 - 2019-11-21334Gulls7Thunderbirds1LSommaire du Match
53 - 2019-11-23357Thunderbirds1Checkers6LSommaire du Match
54 - 2019-11-24362Americans6Thunderbirds2LSommaire du Match
57 - 2019-11-27383Thunderbirds1Bears6LSommaire du Match
60 - 2019-11-30409Admirals5Thunderbirds3LSommaire du Match
63 - 2019-12-03426Wild6Thunderbirds1LSommaire du Match
67 - 2019-12-07458Monsters9Thunderbirds7LSommaire du Match
68 - 2019-12-08464Barracuda5Thunderbirds1LSommaire du Match
70 - 2019-12-10473Crunch11Thunderbirds2LSommaire du Match
72 - 2019-12-12489Sound Tigers9Thunderbirds0LSommaire du Match
74 - 2019-12-14510Bruins8Thunderbirds3LSommaire du Match
76 - 2019-12-16519Senators5Thunderbirds8WSommaire du Match
80 - 2019-12-20548Stars8Thunderbirds10WSommaire du Match
81 - 2019-12-21560Thunderbirds2Checkers4LSommaire du Match
83 - 2019-12-23572Thunderbirds2Crunch10LSommaire du Match
88 - 2019-12-28596Griffins3Thunderbirds1LSommaire du Match
89 - 2019-12-29608Rocket4Thunderbirds1LSommaire du Match
91 - 2019-12-31619Thunderbirds3Monsters7LSommaire du Match
93 - 2020-01-02632Thunderbirds8Senators6WSommaire du Match
95 - 2020-01-04645Thunderbirds2Americans8LSommaire du Match
96 - 2020-01-05654Thunderbirds6Penguins3WSommaire du Match
98 - 2020-01-07664Roadrunners11Thunderbirds3LSommaire du Match
100 - 2020-01-09681Comets1Thunderbirds7WSommaire du Match
103 - 2020-01-12707Marlies7Thunderbirds1LSommaire du Match
107 - 2020-01-16729Reign5Thunderbirds3LSommaire du Match
109 - 2020-01-18749Thunderbirds1Griffins4LSommaire du Match
111 - 2020-01-20760Thunderbirds5Wild8LSommaire du Match
112 - 2020-01-21765Thunderbirds3IceHogs5LSommaire du Match
123 - 2020-02-01794Thunderbirds4Rocket2WSommaire du Match
125 - 2020-02-03809Thunderbirds3Marlies1WSommaire du Match
126 - 2020-02-04818Thunderbirds4Monsters3WXXSommaire du Match
128 - 2020-02-06830Wolves2Thunderbirds1LSommaire du Match
130 - 2020-02-08848Penguins2Thunderbirds8WSommaire du Match
132 - 2020-02-10861Thunderbirds3Phantoms0WSommaire du Match
133 - 2020-02-11868Thunderbirds4Devils1WSommaire du Match
135 - 2020-02-13883Phantoms2Thunderbirds3WXXSommaire du Match
137 - 2020-02-15898Condors1Thunderbirds10WSommaire du Match
139 - 2020-02-17915Thunderbirds0Barracuda2LSommaire du Match
141 - 2020-02-19930Thunderbirds3Gulls4LXXSommaire du Match
142 - 2020-02-20940Thunderbirds3Reign4LSommaire du Match
144 - 2020-02-22957Thunderbirds0Wolves1LXXSommaire du Match
147 - 2020-02-25979Thunderbirds2Roadrunners3LXXSommaire du Match
149 - 2020-02-27987Marlies2Thunderbirds3WSommaire du Match
151 - 2020-02-291002IceHogs2Thunderbirds5WSommaire du Match
152 - 2020-03-011012Heat2Thunderbirds5WSommaire du Match
156 - 2020-03-051035Bruins3Thunderbirds4WSommaire du Match
158 - 2020-03-071055Rocket5Thunderbirds4LXXSommaire du Match
161 - 2020-03-101075Thunderbirds2Rampage4LSommaire du Match
163 - 2020-03-121090Thunderbirds4Stars3WSommaire du Match
165 - 2020-03-141102Devils1Thunderbirds7WSommaire du Match
167 - 2020-03-161121Thunderbirds5Griffins3WSommaire du Match
168 - 2020-03-171128Thunderbirds10Moose1WSommaire du Match
170 - 2020-03-191138Americans3Thunderbirds5WSommaire du Match
172 - 2020-03-211156Rampage3Thunderbirds2LSommaire du Match
174 - 2020-03-231170Thunderbirds4Marlies3WSommaire du Match
175 - 2020-03-241182Thunderbirds9Senators0WSommaire du Match
177 - 2020-03-261192Thunderbirds4Rocket7LSommaire du Match
179 - 2020-03-281207Thunderbirds2Bruins3LSommaire du Match
181 - 2020-03-301225Wolf Pack2Thunderbirds5WSommaire du Match
184 - 2020-04-021243Senators1Thunderbirds10WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
186 - 2020-04-041265Bears-Thunderbirds-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
1 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,847,439$ 1,799,166$ 1,797,749$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,847,439$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 3 9,621$ 28,863$




LigueDomicileVisiteur
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
Saison Régulière
2823824043672612144741191003135133103304119140123212811117762614587192493847420259182686886180232766486016173756818.13%3515983.19%61497278353.79%1371263652.01%694130953.02%2038138818766231090556
38240300215423020327411717011321131121412313010221179126802303966263996636410253188680780664244968593316603386619.53%3796582.85%21317273648.14%1279282945.21%606120150.46%2059142018596051055536
482294101272193202-9411521001311009914114200114193103-105819332651937676157122173699693760632716774152819075109618.82%5929084.80%61295262749.30%1487311547.74%535115246.44%1933128919976481043518
5823636002352222061641191900012117991841171700223105107-272222387609288879524251886583880041263277752919592143918.22%2254978.22%01288256250.27%1174279142.06%580122147.50%2014143619405631007506
68257300130195587-3924123700020111303-192413360011084284-200101953285230074615752686897877891285233142528822011803418.89%1374467.88%0760250630.33%849313727.06%394149926.28%146410122539566935404
782284502043266420-15441142101032137194-5741142401011129226-97562664817470310492648302610251006957664604134232220471873619.25%1543875.32%21386272250.92%1347326041.32%642145444.15%163111522372560953433
881284700024291411-12040142400011152217-6541142300013139194-556429149278322123907663291110311101065333860108130117641533321.57%1333573.68%31448274552.75%1348277648.56%740143351.64%189313932055521940459
Total Saison Régulière573204296099302516582243-58528610014905316138631127-26428710414704614127951116-32141616582868452612336455304446518816630161996140375238216748476113155195737219.01%197138080.72%1989911868148.13%88552054443.10%4191926945.22%13034909314641408970263414
Séries
2211380000066501611650000030273107300000362313266612118712282314166221521420924661200193368781721.79%751284.00%141275054.93%32968747.89%15831949.53%535366480153276145
3624000001014-43030000049-53210000065141018281114411685447589170555310127622.22%24387.50%08819844.44%8621340.38%348340.96%13790153507937
Total Séries271512000007664121468000003436-21394000004228143076139215232927182830269261267338312552464691052321.90%991584.85%150094852.74%41590046.11%19240247.76%672457634203355183