Thunderbird

GP: 62 | W: 23 | L: 36 | OTL: 3 | P: 49
GF: 274 | GA: 379 | PP%: 37.82% | PK%: 45.63%
DG: William Forest | Morale : 43 | Moyenne d'Équipe : 65
Prochain matchs #773 vs Penguins
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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
1Blake ColemanX100.008744727969819574785263776754595667700
2Vinnie HinostrozaXXX100.005941808857789079636262646754524859680
3Ivan BarbashevXX100.006641828570738884675059646853527765670
4Pontus AbergX100.006042817771777675596056696452517348660
5Nicolas Aube-KubelX100.006547586065599960506160606050504460650
6Alexander VolkovX100.006245646072619960505861606150504469610
7Klim KostinX100.006746616081509657505954605450504555600
8Paul Bittner (R)X100.006641756084648156505557605750504464600
Rayé
MOYENNE D'ÉQUIPE100.00674372717168916858575964625252546165
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
1Marek Mazanec100.00666377806874686767666452594260660
Rayé
MOYENNE D'ÉQUIPE100.0066637780687468676766645259426066
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Claude Noel62656979898779can621500,000$


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
1Nicolas Aube-KubelThunderbird (FLA)RW6221486911122056382881151847.29%3497415.71761315300111130047.83%464624001.4200112465
2Klim KostinThunderbird (FLA)RW62102333-155153622201741154.98%972211.6511217000001156.25%324720000.9100010277
3Alexander VolkovThunderbird (FLA)LW22141832-932101618102376913.73%735716.2769151229000093055.00%201513011.7900011340
4Blake ColemanThunderbird (FLA)C101015254140101460293216.67%822122.13681410231013380070.08%37198022.2600000201
5Ivan BarbashevThunderbird (FLA)C/LW767133004654143811.11%213919.923147141012202059.26%27167001.8600000102
6Christian DjoosPanthersD51101140057161096.25%29719.5116741000026000.00%025002.2600000010
7Vinnie HinostrozaThunderbird (FLA)C/LW/RW1011-200217110.00%12020.63011010001100100.00%100000.9700000000
Stats d'équipe Total ou en Moyenne16962122184-14209351291067282804488.52%63253314.99243256491182139896166.00%49713577031.4500133121815
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
Alexander VolkovThunderbird (FLA)LW201997-08-02No191 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Blake ColemanThunderbird (FLA)C251991-11-28No200 Lbs5 ft11NoNoNo3Contrat d'EntréePro & Farm1,800,000$0$0$NoLien
Ivan BarbashevThunderbird (FLA)C/LW211995-12-14No187 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Klim KostinThunderbird (FLA)RW181999-05-05No212 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Marek MazanecThunderbird (FLA)G261991-07-18No187 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Nicolas Aube-KubelThunderbird (FLA)RW211996-05-10No187 Lbs5 ft11NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Paul BittnerThunderbird (FLA)LW201996-11-04Yes214 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Pontus AbergThunderbird (FLA)LW241993-09-23No196 Lbs5 ft11NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Vinnie HinostrozaThunderbird (FLA)C/LW/RW231994-04-03No173 Lbs5 ft9NoNoNo2Contrat d'EntréePro & Farm1,500,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
922.00194 Lbs6 ft11.33950,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
2Nicolas Aube-Kubel30122
3Klim Kostin20122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
4Nicolas Aube-Kubel10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
2Nicolas Aube-Kubel40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
2Nicolas Aube-Kubel40122
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
2Nicolas Aube-Kubel40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Klim Kostin, , Klim Kostin,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , Nicolas Aube-Kubel,
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
1Admirals2110000078-1110000005411010000024-220.5007142100431259795152863864117712822107342.86%11554.55%0471104744.99%497109145.55%578132743.56%12867861461566994457
2Barracuda2010010047-31010000024-21000010023-110.25048120043125979505286386411749151824500.00%9188.89%0471104744.99%497109145.55%578132743.56%12867861461566994457
3Bears310020001914521001000141041000100054161.000193453004312597998528638641176826283114642.86%141028.57%0471104744.99%497109145.55%578132743.56%12867861461566994457
4Blacknight301011001518-31000010067-120101000911-230.500152843004312597968528638641177614264310550.00%14935.71%1471104744.99%497109145.55%578132743.56%12867861461566994457
5Bruins62301000323113110100017143312000001517-260.50032578900431259791785286386411716960507720945.00%251060.00%2471104744.99%497109145.55%578132743.56%12867861461566994457
6Condors20200000511-61010000025-31010000036-300.0005101500431259795952863864117722322287114.29%11736.36%0471104744.99%497109145.55%578132743.56%12867861461566994457
7Crunch220000001411311000000110111100000031241.000142539014312597982528638641173511131412758.33%40100.00%1471104744.99%497109145.55%578132743.56%12867861461566994457
8Devils30300000829-211010000046-220200000423-1900.000815230043125979855286386411716149543812216.67%171323.53%0471104744.99%497109145.55%578132743.56%12867861461566994457
9Gulls22000000844110000005411100000030341.00081523014312597956528638641173611122711436.36%6183.33%0471104744.99%497109145.55%578132743.56%12867861461566994457
10Heat202000001013-31010000057-21010000056-100.000101929004312597959528638641174411144010440.00%7528.57%0471104744.99%497109145.55%578132743.56%12867861461566994457
11Icedogs1010000025-3000000000001010000025-300.000235004312597920528638641172491682150.00%8275.00%0471104744.99%497109145.55%578132743.56%12867861461566994457
12Marlies402011002331-8302001001524-91000100087130.375234366004312597913452863864117145481034416637.50%291451.72%1471104744.99%497109145.55%578132743.56%12867861461566994457
13Moose202000001118-710100000611-51010000057-200.000112132004312597959528638641179327302810330.00%15940.00%0471104744.99%497109145.55%578132743.56%12867861461566994457
14Penguins513010002432-8201010001116-5312000001316-340.40024436700431259791585286386411717252446718633.33%221150.00%1471104744.99%497109145.55%578132743.56%12867861461566994457
15Phantoms402020001424-1020101000611-520101000813-540.50014253900431259791005286386411718178364112325.00%181611.11%0471104744.99%497109145.55%578132743.56%12867861461566994457
16Rampages20200000414-101010000026-41010000028-600.0004812004312597964528638641176528272510110.00%11463.64%1471104744.99%497109145.55%578132743.56%12867861461566994457
17Reigh320010001812621001000121021100000062461.000183553004312597995528638641178320223514750.00%11463.64%1471104744.99%497109145.55%578132743.56%12867861461566994457
18Rocket514000002331-8312000001720-320200000611-520.20023436600431259791485286386411717958565217847.06%281450.00%1471104744.99%497109145.55%578132743.56%12867861461566994457
19Senateurs606000002159-38303000001226-1430300000933-2400.0002136570043125979189528638641172771011237518738.89%433225.58%0471104744.99%497109145.55%578132743.56%12867861461566994457
20Stars1010000019-81010000019-80000000000000.00012300431259792852863864117421614122150.00%7528.57%0471104744.99%497109145.55%578132743.56%12867861461566994457
Total62143609300274379-1053281705200160199-393061904100114180-66490.395274505779024312597918245286386411720907067507472389037.82%32017445.63%9471104744.99%497109145.55%578132743.56%12867861461566994457
22Wolves220000001183110000007521100000043141.000112132004312597943528638641174821202811654.55%10280.00%0471104744.99%497109145.55%578132743.56%12867861461566994457
_Since Last GM Reset62143609300274379-1053281705200160199-393061904100114180-66490.395274505779024312597918245286386411720907067507472389037.82%32017445.63%9471104744.99%497109145.55%578132743.56%12867861461566994457
_Vs Conference3872307100178252-742041104100107127-20183120300071125-54290.382178321499014312597911725286386411713874835074391395438.85%20012040.00%6471104744.99%497109145.55%578132743.56%12867861461566994457
_Vs Division2351502100113153-401338011007284-121027010004169-28150.326113204317014312597973152863864117805278345262833744.58%1297045.74%5471104744.99%497109145.55%578132743.56%12867861461566994457

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
6249L22745057791824209070675074702
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
6214369300274379
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
328175200160199
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
306194100114180
Derniers 10 Matchs
WLOTWOTL SOWSOL
162100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2389037.82%32017445.63%9
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
5286386411743125979
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
471104744.99%497109145.55%578132743.56%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12867861461566994457


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
3 - 2018-10-118Crunch0Thunderbird11WSommaire du Match
6 - 2018-10-1422Thunderbird4Senateurs17LSommaire du Match
11 - 2018-10-1937Rocket3Thunderbird10WSommaire du Match
13 - 2018-10-2142Thunderbird2Rocket4LSommaire du Match
18 - 2018-10-2657Bruins4Thunderbird8WSommaire du Match
21 - 2018-10-2976Thunderbird9Penguins6WSommaire du Match
22 - 2018-10-3083Marlies8Thunderbird7LSommaire du Match
26 - 2018-11-0399Senateurs12Thunderbird7LSommaire du Match
27 - 2018-11-04107Thunderbird10Bruins7WSommaire du Match
29 - 2018-11-06116Thunderbird8Marlies7WXSommaire du Match
32 - 2018-11-09131Penguins9Thunderbird3LSommaire du Match
35 - 2018-11-12147Bears6Thunderbird7WXSommaire du Match
36 - 2018-11-13153Thunderbird3Crunch1WSommaire du Match
40 - 2018-11-17171Senateurs6Thunderbird1LSommaire du Match
43 - 2018-11-20183Thunderbird2Devils15LSommaire du Match
45 - 2018-11-22190Thunderbird1Phantoms7LSommaire du Match
48 - 2018-11-25200Barracuda4Thunderbird2LSommaire du Match
50 - 2018-11-27207Thunderbird2Devils8LSommaire du Match
54 - 2018-12-01224Rampages6Thunderbird2LSommaire du Match
60 - 2018-12-07244Thunderbird1Senateurs8LSommaire du Match
61 - 2018-12-08250Phantoms4Thunderbird5WXSommaire du Match
64 - 2018-12-11258Thunderbird2Rampages8LSommaire du Match
68 - 2018-12-15273Condors5Thunderbird2LSommaire du Match
70 - 2018-12-17287Thunderbird1Penguins6LSommaire du Match
73 - 2018-12-20296Devils6Thunderbird4LSommaire du Match
78 - 2018-12-25319Reigh5Thunderbird6WSommaire du Match
81 - 2018-12-28337Moose11Thunderbird6LSommaire du Match
83 - 2018-12-30345Thunderbird4Senateurs8LSommaire du Match
87 - 2019-01-03362Bears4Thunderbird7WSommaire du Match
89 - 2019-01-05375Thunderbird2Barracuda3LXSommaire du Match
92 - 2019-01-08386Gulls4Thunderbird5WSommaire du Match
97 - 2019-01-13408Thunderbird7Phantoms6WXSommaire du Match
98 - 2019-01-14413Senateurs8Thunderbird4LSommaire du Match
101 - 2019-01-17423Thunderbird4Blacknight7LSommaire du Match
104 - 2019-01-20435Thunderbird5Heat6LSommaire du Match
105 - 2019-01-21440Blacknight7Thunderbird6LXSommaire du Match
109 - 2019-01-25459Bruins6Thunderbird7WXSommaire du Match
113 - 2019-01-29477Thunderbird5Blacknight4WXSommaire du Match
115 - 2019-01-31484Heat7Thunderbird5LSommaire du Match
117 - 2019-02-02492Thunderbird3Gulls0WSommaire du Match
120 - 2019-02-05506Wolves5Thunderbird7WSommaire du Match
122 - 2019-02-07511Thunderbird6Reigh2WSommaire du Match
128 - 2019-02-13532Rocket9Thunderbird5LSommaire du Match
130 - 2019-02-15540Thunderbird3Bruins6LSommaire du Match
132 - 2019-02-17555Marlies9Thunderbird2LSommaire du Match
134 - 2019-02-19566Thunderbird5Moose7LSommaire du Match
136 - 2019-02-21572Thunderbird3Penguins4LSommaire du Match
138 - 2019-02-23582Penguins7Thunderbird8WXSommaire du Match
144 - 2019-03-01603Rocket8Thunderbird2LSommaire du Match
147 - 2019-03-04619Thunderbird4Wolves3WSommaire du Match
149 - 2019-03-06629Bruins4Thunderbird2LSommaire du Match
152 - 2019-03-09647Thunderbird2Icedogs5LSommaire du Match
153 - 2019-03-10653Stars9Thunderbird1LSommaire du Match
157 - 2019-03-14674Reigh5Thunderbird6WXSommaire du Match
159 - 2019-03-16678Thunderbird2Admirals4LSommaire du Match
163 - 2019-03-20697Admirals4Thunderbird5WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
167 - 2019-03-24714Thunderbird4Rocket7LSommaire du Match
168 - 2019-03-25722Phantoms7Thunderbird1LSommaire du Match
171 - 2019-03-28734Thunderbird5Bears4WXSommaire du Match
175 - 2019-04-01745Marlies7Thunderbird6LXSommaire du Match
178 - 2019-04-04755Thunderbird2Bruins4LSommaire du Match
180 - 2019-04-06759Thunderbird3Condors6LSommaire du Match
183 - 2019-04-09773Penguins-Thunderbird-
186 - 2019-04-12788Thunderbird-Rocket-
188 - 2019-04-14796Monsters-Thunderbird-
193 - 2019-04-19817Monsters-Thunderbird-
196 - 2019-04-22826Thunderbird-Sound Tigers-
200 - 2019-04-26842Sound Tigers-Thunderbird-
206 - 2019-05-02865Sound Tigers-Thunderbird-
208 - 2019-05-04875Thunderbird-Sound Tigers-
212 - 2019-05-08889Devils-Thunderbird-
213 - 2019-05-09891Thunderbird-Crunch-
215 - 2019-05-11904Thunderbird-Marlies-
218 - 2019-05-14914Crunch-Thunderbird-
220 - 2019-05-16926Thunderbird-Monsters-
222 - 2019-05-18937Icedogs-Thunderbird-
223 - 2019-05-19939Thunderbird-Stars-
225 - 2019-05-21948Thunderbird-Marlies-
230 - 2019-05-26961Crunch-Thunderbird-
231 - 2019-05-27962Thunderbird-Bears-
232 - 2019-05-28968Thunderbird-Crunch-
233 - 2019-05-29973Thunderbird-Monsters-



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
9 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
986,824$ 855,000$ 855,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 607,103$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 57 5,717$ 325,869$




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
262143609300274379-1053281705200160199-393061904100114180-6649274505779024312597918245286386411720907067507472389037.82%32017445.63%9471104744.99%497109145.55%578132743.56%12867861461566994457
Total Saison Régulière62143609300274379-1053281705200160199-393061904100114180-6649274505779024312597918245286386411720907067507472389037.82%32017445.63%9471104744.99%497109145.55%578132743.56%12867861461566994457