Thunderbirds

GP: 25 | W: 7 | L: 18 | OTL: 0 | P: 14
GF: 62 | GA: 113 | PP%: 9.26% | PK%: 74.29%
DG: Yannick Ferland | Morale : 42 | Moyenne d'Équipe : 58
Prochain matchs #403 vs Sound Tigers
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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
1Evgeny Svechnikov (R)XX100.00735574877770697250626362557172166660
2Trevor Smith (R)X100.00765572687468716150636462555757148610
3Anthony PelusoX100.00585566658280545550555560557174156590
4Brendan WoodsX100.00675558668078655550555555556974148590
5Ben HolmstromX100.00615565607770725550555559557475145580
6Jamie DevaneX100.00655558688078685550555556555050156580
7Mason Appleton (R)X100.00745569557566725550555555555050156560
8Adam ChapieX100.00815566637467545550555555555050156560
9Eric TangradiX100.00565555555657575550555555557172129540
10John MitchellX100.00565555555556555550555555557272125540
11Jens Looke (R)X100.00565555555557565550555555555050156530
12Mark ZengerleX100.00565555555555555550555555555050156530
13Reid PetrykX100.00565555555555555550555555555050154530
14Tyler WotherspoonX100.00595559605959755925595959555353143570
15Zbynek MichalekX100.00555555605555555525555555558284126560
16Andrew BodnarchukX100.00555556605656675625565656555353156550
17Zach Trotman (R)X100.00555555605555745525555555555555156550
18Chris CastoX100.00555555605555675525555555555353136540
Rayé
1Steven KampferXHO795572726781596725616071557070113660
MOYENNE D'ÉQUIPE100.0063556162656463574256565755616114657
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 McIntyre100.0077757776797980767676557068155740
2Adam Carlson (R)100.0052496170535252575353555055156540
Rayé
MOYENNE D'ÉQUIPE100.006562697366666667656555606215664
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
1Brendan WoodsThunderbirds (Flo)C25151631-103605785128549211.72%1252721.09538351020002363147.37%3800021.1800000133
2Trevor SmithThunderbirds (Flo)C25141529-926050961284010710.94%2753021.2017832941011551150.38%53000001.0900000133
3Andrej SekeraFlorida PanthersD1651520725524333052216.67%1842026.262461850011062000.00%000000.9500001102
4Ben HolmstromThunderbirds (Flo)C2510919-8135336592306410.87%2335714.30112945000001159.35%31000001.0600010300
5Evgeny SvechnikovThunderbirds (Flo)LW/RW1541014910022264713308.51%130520.341347650111620065.48%8400100.9200000102
6Reid PetrykThunderbirds (Flo)C2510414-234010917310440909.62%3052220.91415431090001182048.00%2500000.5400200211
7Evan RodriguesFlorida PanthersC/LW/RW835844011171851716.67%117622.060334360000420068.12%13800000.9100000001
8Chris CastoThunderbirds (Flo)D7538-31951810216423.81%1513519.33213142600007000.00%000001.1800100000
9Steven KampferThunderbirds (Flo)D1000000410010.00%12222.550000200003000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne1476677143-331732531040656819342711.62%128299720.3916233916253412352877356.00%112500120.95003119712
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 Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Adam CarlsonThunderbirds (Flo)G221994-02-13Yes174 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Adam ChapieThunderbirds (Flo)RW251991-07-05No185 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
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$0$No300,000$
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
Evgeny SvechnikovThunderbirds (Flo)LW/RW201996-10-31Yes212 Lbs6 ft3NoNoNo3Contrat d'EntréePro & Farm900,000$0$0$No900,000$900,000$
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$0$No300,000$300,000$300,000$
John MitchellThunderbirds (Flo)C311985-01-22No204 Lbs6 ft1NoNoNo4Sans RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Mark ZengerleThunderbirds (Flo)C271989-05-12No185 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Mason AppletonThunderbirds (Flo)C201996-01-15Yes201 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Reid PetrykThunderbirds (Flo)C231993-02-02No212 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Steven KampferThunderbirds (Flo)D281988-09-23No192 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Trevor SmithThunderbirds (Flo)C311985-02-07Yes195 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Tyler WotherspoonThunderbirds (Flo)D231993-03-11No210 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$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$0$No300,000$
Zbynek MichalekThunderbirds (Flo)D341982-12-22No210 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm750,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2125.62204 Lbs6 ft22.10378,571$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Reid Petryk40122
2Trevor SmithBrendan Woods30122
3Brendan WoodsBen Holmstrom20122
4Trevor Smith10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
4Reid Petryk10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Reid Petryk60122
2Trevor SmithBrendan Woods40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Trevor Smith60122
2Reid Petryk40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
2Trevor Smith4012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Trevor Smith60122
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, , Brendan WoodsBen Holmstrom, Brendan Woods
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, Trevor Smith, , 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
1Americans1010000037-41010000037-40000000000000.00036900272311119226224258341141617300.00%8362.50%033079441.56%27773737.58%16037742.44%496351736184269115
2Bears20200000110-90000000000020200000110-900.000123002723111412262242583581314301800.00%6266.67%033079441.56%27773737.58%16037742.44%496351736184269115
3Bruins21100000710-321100000710-30000000000020.500712190027231116622622425836416243313215.38%11463.64%033079441.56%27773737.58%16037742.44%496351736184269115
4Checkers11000000523110000005230000000000021.00059140027231115222622425833041230300.00%60100.00%033079441.56%27773737.58%16037742.44%496351736184269115
5Comets10001000431000000000001000100043121.00046100027231113322622425832817201100.00%110.00%033079441.56%27773737.58%16037742.44%496351736184269115
6Crunch1010000025-31010000025-30000000000000.0002460027231112322622425834112162510110.00%8275.00%033079441.56%27773737.58%16037742.44%496351736184269115
7Devils11000000211110000002110000000000021.0002460027231112422622425832298216116.67%4175.00%033079441.56%27773737.58%16037742.44%496351736184269115
8Penguins41300000722-1531200000615-91010000017-620.250712190027231117622622425831504332481500.00%16475.00%133079441.56%27773737.58%16037742.44%496351736184269115
9Phantoms40400000817-92020000028-62020000069-300.0008111900272311193226224258310934356129310.34%14285.71%033079441.56%27773737.58%16037742.44%496351736184269115
10Rocket20200000611-50000000000020200000611-500.000610160027231115522622425835422203018316.67%8275.00%033079441.56%27773737.58%16037742.44%496351736184269115
11Sound Tigers514000001022-1231200000812-420200000210-820.200101424002723111153226224258315442459130310.00%19573.68%033079441.56%27773737.58%16037742.44%496351736184269115
Total256180100062113-511569000004263-211009010002050-30140.280621001620027231117112262242583779215242423162159.26%1052774.29%133079441.56%27773737.58%16037742.44%496351736184269115
13Wolf Pack11000000734110000007340000000000021.0007101700272311176226224258328513176233.33%4175.00%033079441.56%27773737.58%16037742.44%496351736184269115
_Since Last GM Reset256180100062113-511569000004263-211009010002050-30140.280621001620027231117112262242583779215242423162159.26%1052774.29%133079441.56%27773737.58%16037742.44%496351736184269115
_Vs Conference513010001823-52110000089-1302010001014-440.40018314900272311115922622425831534155973538.57%23673.91%033079441.56%27773737.58%16037742.44%496351736184269115

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2514L16210016271177921524242300
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
25618100062113
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
156900004263
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
100910002050
Derniers 10 Matchs
WLOTWOTL SOWSOL
361000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
162159.26%1052774.29%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
22622425832723111
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
33079441.56%27773737.58%16037742.44%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
496351736184269115


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 - 2018-11-17403Thunderbirds-Sound Tigers-
75 - 2018-11-18417Bears-Thunderbirds-
78 - 2018-11-21429Crunch-Thunderbirds-
80 - 2018-11-23440Comets-Thunderbirds-
81 - 2018-11-24459Bruins-Thunderbirds-
87 - 2018-11-30480Sound Tigers-Thunderbirds-
88 - 2018-12-01489Thunderbirds-Crunch-
89 - 2018-12-02499Thunderbirds-Wolf Pack-
94 - 2018-12-07523Thunderbirds-Wolf Pack-
95 - 2018-12-08537Bruins-Thunderbirds-
96 - 2018-12-09547Phantoms-Thunderbirds-
101 - 2018-12-14566Bears-Thunderbirds-
102 - 2018-12-15581Bruins-Thunderbirds-
103 - 2018-12-16588Thunderbirds-Bruins-
106 - 2018-12-19597Thunderbirds-Phantoms-
108 - 2018-12-21607Thunderbirds-Bruins-
109 - 2018-12-22619Thunderbirds-Wolf Pack-
111 - 2018-12-24639Rocket-Thunderbirds-
113 - 2018-12-26646Thunderbirds-Wolf Pack-
115 - 2018-12-28655Thunderbirds-Crunch-
116 - 2018-12-29678Thunderbirds-Bruins-
122 - 2019-01-04687Wolf Pack-Thunderbirds-
123 - 2019-01-05704Comets-Thunderbirds-
127 - 2019-01-09718Bears-Thunderbirds-
129 - 2019-01-11725Thunderbirds-Americans-
130 - 2019-01-12735Thunderbirds-Marlies-
136 - 2019-01-18772Checkers-Thunderbirds-
137 - 2019-01-19788Marlies-Thunderbirds-
138 - 2019-01-20796Thunderbirds-Bruins-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25824Thunderbirds-Wolf Pack-
144 - 2019-01-26831Thunderbirds-Sound Tigers-
150 - 2019-02-01862Wolf Pack-Thunderbirds-
151 - 2019-02-02874Bruins-Thunderbirds-
152 - 2019-02-03882Thunderbirds-Bruins-
157 - 2019-02-08905Thunderbirds-Devils-
158 - 2019-02-09914Wolf Pack-Thunderbirds-
159 - 2019-02-10925Thunderbirds-Bruins-
162 - 2019-02-13935Thunderbirds-Bears-
164 - 2019-02-15944Thunderbirds-Comets-
166 - 2019-02-17969Thunderbirds-Sound Tigers-
171 - 2019-02-22987Devils-Thunderbirds-
172 - 2019-02-231001Rocket-Thunderbirds-
173 - 2019-02-241010Thunderbirds-Penguins-
178 - 2019-03-011031Thunderbirds-Devils-
179 - 2019-03-021047Thunderbirds-Penguins-
183 - 2019-03-061065Wolf Pack-Thunderbirds-
186 - 2019-03-091086Thunderbirds-Checkers-
187 - 2019-03-101097Thunderbirds-Checkers-
192 - 2019-03-151120Sound Tigers-Thunderbirds-
193 - 2019-03-161135Bruins-Thunderbirds-
194 - 2019-03-171143Thunderbirds-Bruins-



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
23 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
394,660$ 74,500$ 71,250$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 23,523$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 5,539$ 675,758$




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
13256180100062113-511569000004263-211009010002050-3014621001620027231117112262242583779215242423162159.26%1052774.29%133079441.56%27773737.58%16037742.44%496351736184269115
Total Saison Régulière256180100062113-511569000004263-211009010002050-3014621001620027231117112262242583779215242423162159.26%1052774.29%133079441.56%27773737.58%16037742.44%496351736184269115