Thunderbirds

GP: 76 | W: 18 | L: 54 | OTL: 4 | P: 40
GF: 187 | GA: 334 | PP%: 9.73% | PK%: 73.07%
DG: Yannick Ferland | Morale : 20 | Moyenne d'Équipe : 57
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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
1Alexander NylanderX100.00805582887365766050606160557070182640
2Trevor Smith (R)X100.00765572687468716150636462555757142610
3Anthony PelusoX100.00585566658280545550555560557174154590
4Brendan WoodsX100.00675558668078655550555555556974136590
5Ben HolmstromX100.00615565607770725550555559557475131580
6Jamie DevaneX100.00655558688078685550555556555050169580
7Mason Appleton (R)X100.00745569557566725550555555555050169560
8Adam ChapieX100.00815566637467545550555555555050169560
9Eric TangradiX100.00565555555657575550555555557172142540
10John MitchellX100.00565555555556555550555555557272138540
11Jens Looke (R)X100.00565555555557565550555555555050169530
12Mark ZengerleX100.00565555555555555550555555555050169530
13Reid PetrykX100.00565555555555555550555555555050146530
14Zbynek MichalekX100.00555555605555555525555555558284139560
15Andrew BodnarchukX100.00555556605656675625565656555353169550
16Zach Trotman (R)X100.00555555605555745525555555555555169550
17Chris CastoX100.00555555605555675525555555555353149540
Rayé
MOYENNE D'ÉQUIPE100.0062556162656363564456565655606115556
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
1Zane McIntyre100.0077757776797980767676557068168740
2Adam Carlson (R)100.0052496170535252575353555055169540
Rayé
MOYENNE D'ÉQUIPE100.006562697366666667656555606216964
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Alain Nasreddine52806849666263CAN4051,000,000$


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'ÉquipePOS GP 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
1Reid PetrykThunderbirds (Flo)C76362561-50971527621933810826910.65%96149919.72135181102720002473251.95%7700000.8100201823
2Brendan WoodsThunderbirds (Flo)C40252550-6715881262047514712.25%1983120.787512501480003705251.61%6200031.2000010343
3Trevor SmithThunderbirds (Flo)C45232649-9520101159237671969.70%6294320.97310135515310121191150.69%94300001.0400000155
4Ben HolmstromThunderbirds (Flo)C76321446-1872201151652507417312.80%56100413.223141767000004159.88%84000010.9200022620
5Haydn FleuryFlorida PanthersD45113142188115545677296514.29%34112324.9610818552220111185200.00%000000.7500021033
6Frank VatranoFlorida PanthersC/LW/RW451710277255244089205519.10%579517.676511282211011443159.15%14200000.6801100312
7Andrej SekeraFlorida PanthersD1651520725524333052216.67%1842026.262461850011062000.00%000000.9500001102
8Evgeny SvechnikovFlorida PanthersLW/RW1541014910022264713308.51%130520.341347650111620065.48%8400100.9200000102
9Alexander NylanderThunderbirds (Flo)LW44410142128041192971813.79%054912.481232390001210057.41%5400000.5100000020
10Evan RodriguesFlorida PanthersC/LW/RW835844011171851716.67%117622.060334360000420068.12%13800000.9100000001
11Chris CastoThunderbirds (Flo)D7538-31951810216423.81%1513519.33213142600007000.00%000001.1800100000
Stats d'équipe Total ou en Moyenne417165174339-2048470774870134040999612.31%307778318.6648479536013062351166418756.28%234000140.8701455231921
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
Stats d'équipe Total ou en Moyenne0.0000.0000.000


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'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Adam CarlsonThunderbirds (Flo)G221994-02-13Yes174 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Adam ChapieThunderbirds (Flo)RW251991-07-05No185 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Alexander NylanderThunderbirds (Flo)LW181998-07-29No180 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm900,000$0$0$No
Andrew BodnarchukThunderbirds (Flo)D281988-07-10No189 Lbs5 ft10NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Anthony PelusoThunderbirds (Flo)RW271989-04-17No235 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Ben HolmstromThunderbirds (Flo)C291987-04-08No197 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Brendan WoodsThunderbirds (Flo)C241992-06-10No209 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Chris CastoThunderbirds (Flo)D251991-12-27No209 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Eric TangradiThunderbirds (Flo)LW271989-02-10No221 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jamie DevaneThunderbirds (Flo)LW251991-02-20No231 Lbs6 ft5NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jens LookeThunderbirds (Flo)RW191997-04-11Yes181 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
John MitchellThunderbirds (Flo)C311985-01-22No204 Lbs6 ft1NoNoNo4Sans RestrictionPro & Farm300,000$0$0$No
Mark ZengerleThunderbirds (Flo)C271989-05-12No185 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Mason AppletonThunderbirds (Flo)C201996-01-15Yes201 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Reid PetrykThunderbirds (Flo)C231993-02-02No212 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Trevor SmithThunderbirds (Flo)C311985-02-07Yes195 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
Zach TrotmanThunderbirds (Flo)D261990-08-25Yes216 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Zane McIntyreThunderbirds (Flo)G241992-08-20No207 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Zbynek MichalekThunderbirds (Flo)D341982-12-22No210 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm750,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1925.53202 Lbs6 ft22.21376,316$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Reid Petryk40122
230122
3Ben Holmstrom20122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
4Reid Petryk10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Reid Petryk60122
240122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
2Reid Petryk40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
24012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
2Reid Petryk40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Reid Petryk
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Reid Petryk
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Ben Holmstrom, , Ben Holmstrom,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , Reid Petryk,
Gardien
#1 : , #2 :


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
1Americans20200000511-61010000037-41010000024-200.00059140071714144468570972915702222371100.00%11463.64%0884219840.22%856229837.25%457115339.64%14089702331569840357
2Bears604011001131-2030101100914-530300000217-1530.250111627007171414122685709729152155946994249.52%21766.67%0884219840.22%856229837.25%457115339.64%14089702331569840357
3Bruins14113000002667-41716000001534-19707000001133-2220.0712646720071714143196857097291553412913723662914.52%611870.49%0884219840.22%856229837.25%457115339.64%14089702331569840357
4Checkers4300010017134210001009722200000086270.8751732490071714142246857097291516231281071100.00%14192.86%0884219840.22%856229837.25%457115339.64%14089702331569840357
5Comets412010001317-4211000009812010100049-540.500132134007171414129685709729151423749642613.85%11463.64%0884219840.22%856229837.25%457115339.64%14089702331569840357
6Crunch40400000518-132020000049-52020000019-800.000591400717141491685709729151625362712913.45%27966.67%0884219840.22%856229837.25%457115339.64%14089702331569840357
7Devils41200001513-82100000133020200000210-830.3755101500717141488685709729151264630742528.00%15380.00%0884219840.22%856229837.25%457115339.64%14089702331569840357
8Marlies2110000010911010000056-11100000053220.500101828007171414926857097291595371868600.00%9277.78%0884219840.22%856229837.25%457115339.64%14089702331569840357
9Penguins615000001229-1731200000615-930300000614-820.167122032007171414123685709729152215838672400.00%19573.68%1884219840.22%856229837.25%457115339.64%14089702331569840357
10Phantoms606000001125-1430300000210-830300000915-600.000111627007171414140685709729151595174943937.69%26580.77%0884219840.22%856229837.25%457115339.64%14089702331569840357
11Rocket403001001221-920100100610-420200000611-510.1251219310071714141146857097291513446406730516.67%18666.67%0884219840.22%856229837.25%457115339.64%14089702331569840357
12Sound Tigers1018010002047-27513010001318-550500000729-2240.200202949007171414266685709729153111038419657712.28%361266.67%0884219840.22%856229837.25%457115339.64%14089702331569840357
Total76145404301187334-1473892302301107157-50385310200080177-97400.26318731950611717141421356857097291526567697501372401399.73%3238773.07%1884219840.22%856229837.25%457115339.64%14089702331569840357
14Wolf Pack1054010004033753200000231675220100017170120.6004074114117171414383685709729153259712219239717.95%551180.00%0884219840.22%856229837.25%457115339.64%14089702331569840357
_Since Last GM Reset76145404301187334-1473892302301107157-50385310200080177-97400.26318731950611717141421356857097291526567697501372401399.73%3238773.07%1884219840.22%856229837.25%457115339.64%14089702331569840357
_Vs Conference1658012005771-14824002003238-6834010002533-8140.4385799156007171414603685709729156031731573438467.14%631773.02%0884219840.22%856229837.25%457115339.64%14089702331569840357

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7640L318731950621352656769750137211
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7614544301187334
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
389232301107157
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
38531200080177
Derniers 10 Matchs
WLOTWOTL SOWSOL
280000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
401399.73%3238773.07%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
685709729157171414
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
884219840.22%856229837.25%457115339.64%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
14089702331569840357


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
4 - 2018-09-0814Thunderbirds1Penguins7LSommaire du Match
10 - 2018-09-1435Thunderbirds3Phantoms4LSommaire du Match
11 - 2018-09-1552Phantoms3Thunderbirds1LSommaire du Match
12 - 2018-09-1659Bruins7Thunderbirds3LSommaire du Match
17 - 2018-09-2176Thunderbirds2Rocket6LSommaire du Match
18 - 2018-09-2282Thunderbirds4Rocket5LSommaire du Match
25 - 2018-09-29123Bruins3Thunderbirds4WSommaire du Match
26 - 2018-09-30132Wolf Pack3Thunderbirds7WSommaire du Match
31 - 2018-10-05144Sound Tigers3Thunderbirds1LSommaire du Match
32 - 2018-10-06155Thunderbirds0Sound Tigers4LSommaire du Match
38 - 2018-10-12185Thunderbirds3Phantoms5LSommaire du Match
39 - 2018-10-13195Thunderbirds1Bears5LSommaire du Match
43 - 2018-10-17214Penguins2Thunderbirds3WSommaire du Match
45 - 2018-10-19229Americans7Thunderbirds3LSommaire du Match
46 - 2018-10-20244Phantoms5Thunderbirds1LSommaire du Match
52 - 2018-10-26269Penguins6Thunderbirds2LSommaire du Match
53 - 2018-10-27283Crunch5Thunderbirds2LSommaire du Match
54 - 2018-10-28291Thunderbirds2Sound Tigers6LSommaire du Match
57 - 2018-10-31303Sound Tigers6Thunderbirds2LSommaire du Match
60 - 2018-11-03323Thunderbirds0Bears5LSommaire du Match
61 - 2018-11-04333Sound Tigers3Thunderbirds5WSommaire du Match
66 - 2018-11-09349Thunderbirds4Comets3WXSommaire du Match
67 - 2018-11-10368Checkers2Thunderbirds5WSommaire du Match
68 - 2018-11-11377Devils1Thunderbirds2WSommaire du Match
71 - 2018-11-14385Penguins7Thunderbirds1LSommaire du Match
74 - 2018-11-17403Thunderbirds3Sound Tigers5LSommaire du Match
75 - 2018-11-18417Bears4Thunderbirds5WXSommaire du Match
78 - 2018-11-21429Crunch4Thunderbirds2LSommaire du Match
80 - 2018-11-23440Comets4Thunderbirds8WSommaire du Match
81 - 2018-11-24459Bruins3Thunderbirds1LSommaire du Match
87 - 2018-11-30480Sound Tigers3Thunderbirds4WXSommaire du Match
88 - 2018-12-01489Thunderbirds0Crunch4LSommaire du Match
89 - 2018-12-02499Thunderbirds3Wolf Pack5LSommaire du Match
94 - 2018-12-07523Thunderbirds5Wolf Pack3WSommaire du Match
95 - 2018-12-08537Bruins4Thunderbirds2LSommaire du Match
96 - 2018-12-09547Phantoms2Thunderbirds0LSommaire du Match
101 - 2018-12-14566Bears4Thunderbirds3LXSommaire du Match
102 - 2018-12-15581Bruins7Thunderbirds3LSommaire du Match
103 - 2018-12-16588Thunderbirds1Bruins3LSommaire du Match
106 - 2018-12-19597Thunderbirds3Phantoms6LSommaire du Match
108 - 2018-12-21607Thunderbirds2Bruins4LSommaire du Match
109 - 2018-12-22619Thunderbirds5Wolf Pack4WXSommaire du Match
111 - 2018-12-24639Rocket5Thunderbirds4LXSommaire du Match
113 - 2018-12-26646Thunderbirds1Wolf Pack0WSommaire du Match
115 - 2018-12-28655Thunderbirds1Crunch5LSommaire du Match
116 - 2018-12-29678Thunderbirds1Bruins5LSommaire du Match
122 - 2019-01-04687Wolf Pack3Thunderbirds6WSommaire du Match
123 - 2019-01-05704Comets4Thunderbirds1LSommaire du Match
127 - 2019-01-09718Bears6Thunderbirds1LSommaire du Match
129 - 2019-01-11725Thunderbirds2Americans4LSommaire du Match
130 - 2019-01-12735Thunderbirds5Marlies3WSommaire du Match
136 - 2019-01-18772Checkers5Thunderbirds4LXSommaire du Match
137 - 2019-01-19788Marlies6Thunderbirds5LSommaire du Match
138 - 2019-01-20796Thunderbirds0Bruins5LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25824Thunderbirds3Wolf Pack5LSommaire du Match
144 - 2019-01-26831Thunderbirds2Sound Tigers6LSommaire du Match
150 - 2019-02-01862Wolf Pack3Thunderbirds0LSommaire du Match
151 - 2019-02-02874Bruins4Thunderbirds0LSommaire du Match
152 - 2019-02-03882Thunderbirds2Bruins5LSommaire du Match
157 - 2019-02-08905Thunderbirds1Devils8LSommaire du Match
158 - 2019-02-09914Wolf Pack3Thunderbirds7WSommaire du Match
159 - 2019-02-10925Thunderbirds1Bruins6LSommaire du Match
162 - 2019-02-13935Thunderbirds1Bears7LSommaire du Match
164 - 2019-02-15944Thunderbirds0Comets6LSommaire du Match
166 - 2019-02-17969Thunderbirds0Sound Tigers8LSommaire du Match
171 - 2019-02-22987Devils2Thunderbirds1LXXSommaire du Match
172 - 2019-02-231001Rocket5Thunderbirds2LSommaire du Match
173 - 2019-02-241010Thunderbirds3Penguins4LSommaire du Match
178 - 2019-03-011031Thunderbirds1Devils2LSommaire du Match
179 - 2019-03-021047Thunderbirds2Penguins3LSommaire du Match
183 - 2019-03-061065Wolf Pack4Thunderbirds3LSommaire du Match
186 - 2019-03-091086Thunderbirds4Checkers3WSommaire du Match
187 - 2019-03-101097Thunderbirds4Checkers3WSommaire du Match
192 - 2019-03-151120Sound Tigers3Thunderbirds1LSommaire du Match
193 - 2019-03-161135Bruins6Thunderbirds2LSommaire du Match
194 - 2019-03-171143Thunderbirds4Bruins5LSommaire du Match



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
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,072,511$ 71,500$ 68,250$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 72,525$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 5,523$ 0$




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
1376145404301187334-1473892302301107157-50385310200080177-974018731950611717141421356857097291526567697501372401399.73%3238773.07%1884219840.22%856229837.25%457115339.64%14089702331569840357
Total Saison Régulière76145404301187334-1473892302301107157-50385310200080177-974018731950611717141421356857097291526567697501372401399.73%3238773.07%1884219840.22%856229837.25%457115339.64%14089702331569840357