Association Québécoise de Hockey Simulé - Twins 

Twins

GP: 20 | W: 6 | L: 13 | OTL: 1 | P: 13
GF: 59 | GA: 85 | PP%: 26.42% | PK%: 62.90%
DG: David Hardy | Morale : 90 | Moyenne d'Équipe : 55
Prochain matchs #313 vs Barracudas
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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
1Jesse YlonenX100.00544595846267456330626358858373090640
2Andreas JohnssonX100.00534587785967405130525063658878090570
3Otto Koivula (R)X100.00524590738850404930485055508471090550
4Marco Kasper (R)X100.00504595785975404530405061507971090550
5Tyler Angle (R)X100.00504595804557404730405465508270090540
6Victor RaskX100.00504595767050404530405055509077090540
7Scott ReedyX100.00504595757350404530405055508471090530
8Alan QuineX100.00504595756850404530405055509077090530
9Owen Beck (R)X100.00504595775950404530405060507966090530
10Lucas WallmarkX100.00504595795550404530405055508875090530
11Nicholas BaptisteX100.00504595757150404530405055508875090530
12Markus NiemelainenX100.00994590776850404530405059508471090600
13Jamie DrysdaleX100.00534592785073404530405066508173090590
14Dillon HeatheringtonX100.00504595747650404530405058508774090580
15Sean Day (R)X100.00504595737650404530405055508572090570
16David Farrance (R)X100.00504595775350404530405055508471090560
17Olli Juolevi (R)X100.00504595785650404530405055508572090560
Rayé
1Connor BunnamanX100.00504595757250404530405055508572090530
2Janne KuokkanenX100.00504595776550404530405055508572090530
3Ivan Chekhovich (R)X100.00504595785550404530405055508471090520
4Valtteri Puustinen (R)X100.00504595785250404530405055508471090520
MOYENNE D'ÉQUIPE100.0053459477635440463042515752857309055
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
1Michael Dipietro (R)100.0070404086656565656565658269090580
Rayé
MOYENNE D'ÉQUIPE100.007040408665656565656565826909058
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Kirk Muller65656565927456CAN5841,000,000$


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
1Tyler AngleTwins (LAK)C206612-240182752163111.54%1729314.68145524000000034.87%304813000.8201000121
2Andreas JohnssonTwins (LAK)RW97512-1801074482615.91%620122.422026240000141144.12%34128001.1901000211
3Marco KasperTwins (LAK)LW20729-200241639132817.95%1332316.184047250001171024.00%25119000.5601000021
4Austin WagnerLos Angeles KingsLW86172001333210818.75%116120.221013220000171040.00%1594000.8701000200
5Victor RaskTwins (LAK)C100771201117118100.00%318918.980221260000120041.90%21034000.7401000000
6Nicholas BaptisteTwins (LAK)RW13246-275714187911.11%619114.76033321000001050.00%1025000.6301001002
7Scott ReedyTwins (LAK)C20415-110011212731414.81%428414.2300003000010039.60%14973000.3500000100
8Alan QuineTwins (LAK)LW12033-940131114750.00%418515.4800000000000040.00%595000.3200000000
9David FarranceTwins (LAK)D20011-1020295130.00%1228614.350000700002000.00%0011000.0700000010
10Olli JuoleviTwins (LAK)D13011-420456000.00%417713.620000000009000.00%028000.1100000000
11Owen BeckTwins (LAK)C12011000221030.00%0534.470000300000000.00%502000.3700000202
12Dillon HeatheringtonTwins (LAK)D20011-135581519650.00%1635517.80000017000016000.00%0121000.0600001000
13Janne KuokkanenTwins (LAK)LW4011-300225030.00%05614.1200001000020050.00%223000.3500000000
14Jamie DrysdaleTwins (LAK)D2000200020000.00%12311.940000200000000.00%010000.0000000000
15Markus NiemelainenTwins (LAK)D7000-26015109100.00%815121.6400012100008000.00%028000.0000000000
16Sean DayTwins (LAK)D20000-131156134520.00%1333916.97000015000012000.00%0222000.0000010001
17Lucas WallmarkTwins (LAK)C13000-100241000.00%1564.3300000000000051.85%2702000.0000000001
Stats d'équipe Total ou en Moyenne223323466-6851151481782878514711.15%109333314.9589172621700011164138.42%78671128000.4006012869
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
1Joel HoferLos Angeles Kings105410.8823.725640135297157010.8336100110
2Michael DipietroTwins (LAK)40300.8184.0420800147742000.0000313020
Stats d'équipe Total ou en Moyenne145710.8693.807730149374199010.83361313130


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
Alan QuineTwins (LAK)LW301993-02-25No203 Lbs6 ft0NoNoNo4Sans RestrictionPro & Farm700,000$0$0$No
Andreas JohnssonTwins (LAK)RW281994-11-21No195 Lbs5 ft10NoNoNo4Sans RestrictionPro & Farm1,000,000$0$0$No
Connor BunnamanTwins (LAK)C251998-04-16No207 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm750,000$0$0$No
David FarranceTwins (LAK)D241999-06-23Yes189 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm700,000$0$0$No
Dillon HeatheringtonTwins (LAK)D281995-05-09No215 Lbs6 ft4NoNoNo1Sans RestrictionPro & Farm750,000$0$0$No
Ivan ChekhovichTwins (LAK)RW241999-01-04Yes185 Lbs5 ft10NoNoNo3Avec RestrictionPro & Farm900,000$0$0$No
Jamie DrysdaleTwins (LAK)D212002-04-08No183 Lbs5 ft11NoNoNo3Avec RestrictionPro & Farm2,000,000$0$0$No
Janne KuokkanenTwins (LAK)LW251998-05-25No193 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm850,000$0$0$No
Jesse YlonenTwins (LAK)RW231999-10-03No188 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm900,000$0$0$No
Lucas WallmarkTwins (LAK)C281995-09-05No178 Lbs6 ft0NoNoNo4Sans RestrictionPro & Farm850,000$0$0$No
Marco KasperTwins (LAK)LW192004-04-08Yes183 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm1,200,000$0$0$No
Markus NiemelainenTwins (LAK)D251998-06-08No190 Lbs6 ft6NoNoNo2Avec RestrictionPro & Farm950,000$0$0$No
Michael DipietroTwins (LAK)G241999-06-09Yes200 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm850,000$0$0$No
Nicholas BaptisteTwins (LAK)RW271995-10-12No205 Lbs6 ft1NoNoNo5Avec RestrictionPro & Farm775,000$0$0$No
Olli JuoleviTwins (LAK)D251998-05-05Yes182 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm900,000$0$0$No
Otto KoivulaTwins (LAK)LW251998-09-01Yes225 Lbs6 ft5NoNoNo1Avec RestrictionPro & Farm750,000$0$0$No
Owen BeckTwins (LAK)C192004-02-03Yes191 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm950,000$0$0$No
Scott ReedyTwins (LAK)C241999-04-04No205 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm1,000,000$0$0$No
Sean DayTwins (LAK)D251998-01-09Yes218 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm850,000$0$0$No
Tyler AngleTwins (LAK)C222000-09-30Yes166 Lbs5 ft10NoNoNo4Avec RestrictionPro & Farm775,000$0$0$No
Valtteri PuustinenTwins (LAK)RW241999-06-04Yes183 Lbs5 ft9NoNoNo2Avec RestrictionPro & Farm900,000$0$0$No
Victor RaskTwins (LAK)C301993-03-01No199 Lbs6 ft2NoNoNo5Sans RestrictionPro & Farm775,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2224.77195 Lbs6 ft13.05912,500$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
135122
2Marco KasperTyler Angle30122
3Scott Reedy25122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
135122
2Dillon HeatheringtonSean Day30122
3David Farrance25122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
155122
2Marco KasperTyler Angle45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
2Dillon HeatheringtonSean Day45122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
155122
2Marco Kasper45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
2Dillon HeatheringtonSean Day45122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
15512255122
245122Dillon HeatheringtonSean Day45122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
155122
2Marco Kasper45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
155122
2Dillon HeatheringtonSean Day45122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Scott Reedy, , Scott Reedy
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
David Farrance, , Dillon HeatheringtonDavid Farrance, Dillon Heatherington
Tirs de Pénalité
, , Marco Kasper, , Tyler Angle
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
1Bandits1010000029-7000000000001010000029-700.00023500172913027123181166744103512200.00%10550.00%013131042.26%14036338.57%13631143.73%446293454155304149
2Barracudas2020000037-41010000023-11010000014-300.000369001729130321231811667411110176116.67%5180.00%013131042.26%14036338.57%13631143.73%446293454155304149
3Bayou20200000411-71010000016-51010000035-200.00047110017291305012318116675112446600.00%20100.00%013131042.26%14036338.57%13631143.73%446293454155304149
4CoolFm1010000034-1000000000001010000034-100.0003580017291302912318116672694112150.00%220.00%113131042.26%14036338.57%13631143.73%446293454155304149
5Farmers1010000048-4000000000001010000048-400.000471100172913014123181166743182492150.00%7357.14%013131042.26%14036338.57%13631143.73%446293454155304149
6Outlaws321000001082211000006511100000043140.6671014240117291306412318116678629124410440.00%7271.43%013131042.26%14036338.57%13631143.73%446293454155304149
7Predateurs22000000972110000006511100000032141.00091524001729130541231811667782718368112.50%9277.78%013131042.26%14036338.57%13631143.73%446293454155304149
8Thugs1010000027-51010000027-50000000000000.00024600172913025123181166733172513400.00%5260.00%013131042.26%14036338.57%13631143.73%446293454155304149
Total20613000015985-261037000002939-101036000013046-16130.325591021611117291304711231811667573186172280531426.42%622362.90%113131042.26%14036338.57%13631143.73%446293454155304149
10Vandals22000000945110000005231100000042241.000916250017291305512318116675411143111100.00%7357.14%013131042.26%14036338.57%13631143.73%446293454155304149
11Vipers30200001913-42020000058-31000000145-110.16791726001729130721231811667702120439444.44%5260.00%013131042.26%14036338.57%13631143.73%446293454155304149
12Wolves1010000024-2000000000001010000024-200.000246101729130241231811667201349200.00%20100.00%013131042.26%14036338.57%13631143.73%446293454155304149
13Xpress1010000023-11010000023-10000000000000.0002460017291302512318116672782911100.00%110.00%013131042.26%14036338.57%13631143.73%446293454155304149
_Since Last GM Reset20613000015985-261037000002939-101036000013046-16130.325591021611117291304711231811667573186172280531426.42%622362.90%113131042.26%14036338.57%13631143.73%446293454155304149
_Vs Conference1669000014861-13936000002736-9733000012125-4130.40648831311117291303761231811667433141107239461123.91%421271.43%013131042.26%14036338.57%13631143.73%446293454155304149
_Vs Division1568000014654-8835000002529-4733000012125-4130.4334679125111729130351123181166740012482226421126.19%371072.97%013131042.26%14036338.57%13631143.73%446293454155304149

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2013L65910216147157318617228011
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2061300015985
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
103700002939
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
103600013046
Derniers 10 Matchs
WLOTWOTL SOWSOL
190000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
531426.42%622362.90%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
12318116671729130
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
13131042.26%14036338.57%13631143.73%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
446293454155304149


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
1 - 2024-04-066Twins3Bayou5LSommaire du Match
3 - 2024-04-0826Outlaws5Twins2LSommaire du Match
4 - 2024-04-0939Twins2Wolves4LSommaire du Match
6 - 2024-04-1148Twins4Vipers5LXXSommaire du Match
7 - 2024-04-1261Bayou6Twins1LSommaire du Match
9 - 2024-04-1484Outlaws0Twins4WSommaire du Match
10 - 2024-04-15102Predateurs5Twins6WSommaire du Match
11 - 2024-04-16105Twins4Outlaws3WSommaire du Match
12 - 2024-04-17121Twins4Vandals2WSommaire du Match
13 - 2024-04-18133Twins3Predateurs2WSommaire du Match
15 - 2024-04-20151Barracudas3Twins2LSommaire du Match
16 - 2024-04-21170Twins1Barracudas4LSommaire du Match
17 - 2024-04-22178Twins4Farmers8LSommaire du Match
18 - 2024-04-23186Vandals2Twins5WSommaire du Match
21 - 2024-04-26216Vipers4Twins2LSommaire du Match
23 - 2024-04-28239Xpress3Twins2LSommaire du Match
24 - 2024-04-29249Twins3CoolFm4LSommaire du Match
25 - 2024-04-30262Twins2Bandits9LSommaire du Match
26 - 2024-05-01279Vipers4Twins3LSommaire du Match
29 - 2024-05-04301Thugs7Twins2LSommaire du Match
30 - 2024-05-05313Twins-Barracudas-
31 - 2024-05-06330Grizzlies-Twins-
32 - 2024-05-07346Twins-Marlies-
34 - 2024-05-09356Marlies-Twins-
35 - 2024-05-10378Twins-Smirnoff Ice-
37 - 2024-05-12392Supreme-Twins-
38 - 2024-05-13403Twins-Vipers-
40 - 2024-05-15424CoolFm-Twins-
42 - 2024-05-17442Farmers-Twins-
43 - 2024-05-18458Twins-Predateurs-
44 - 2024-05-19463Twins-Chiwawa-
46 - 2024-05-21486Igloos-Twins-
47 - 2024-05-22503Twins-Marmots-
48 - 2024-05-23515Twins-Hunters-
49 - 2024-05-24523Raptors-Twins-
51 - 2024-05-26544Husky-Twins-
52 - 2024-05-27562Twins-Saguenéens-
53 - 2024-05-28573Twins-Wolves-
55 - 2024-05-30588Warriors-Twins-
56 - 2024-05-31598Twins-Spartans-
58 - 2024-06-02620TigersCats-Twins-
60 - 2024-06-04632Twins-Igloos-
61 - 2024-06-05648Bayou-Twins-
63 - 2024-06-07672Twins-TigersCats-
64 - 2024-06-08679Predateurs-Twins-
66 - 2024-06-10697Twins-Husky-
67 - 2024-06-11711Scorpions-Twins-
69 - 2024-06-13733Snowbirds-Twins-
70 - 2024-06-14749Twins-Warriors-
71 - 2024-06-15760Wolves-Twins-
72 - 2024-06-16781Twins-Vandals-
73 - 2024-06-17794Smirnoff Ice-Twins-
74 - 2024-06-18806Twins-Snowbirds-
76 - 2024-06-20827Outlaws-Twins-
77 - 2024-06-21843Twins-Rockets-
78 - 2024-06-22852Twins-Xpress-
79 - 2024-06-23867Spartans-Twins-
81 - 2024-06-25883Twins-Outlaws-
83 - 2024-06-27895Chiwawa-Twins-
85 - 2024-06-29919Barracudas-Twins-
87 - 2024-07-01935Twins-Supreme-
88 - 2024-07-02951Twins-Thugs-
89 - 2024-07-03959Wolves-Twins-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
91 - 2024-07-05979Marmots-Twins-
92 - 2024-07-06999Bandits-Twins-
94 - 2024-07-081020Twins-Grizzlies-
95 - 2024-07-091021Twins-Goons-
96 - 2024-07-101042Hunters-Twins-
99 - 2024-07-131061Twins-Farmers-
100 - 2024-07-141076Goons-Twins-
103 - 2024-07-171100Saguenéens-Twins-
105 - 2024-07-191120Rockets-Twins-
106 - 2024-07-201128Twins-Bayou-
108 - 2024-07-221144Twins-Raptors-
110 - 2024-07-241159Vandals-Twins-
111 - 2024-07-251167Twins-Scorpions-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance19,9559,981
Assistance PCT99.78%99.81%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
28 2994 - 99.79% 101,777$1,017,768$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
794,275$ 2,007,500$ 2,007,500$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 530,545$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
2,849,750$ 84 26,615$ 2,235,660$




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
4582244704700219277-5841132301400112138-2641112403300107139-326321940061921477197417914426386991220286797839992103114.76%2516374.90%6581124846.55%650134648.29%571124046.05%2069148317685921106537
4682294204412232265-3341151704212118126-841142500200114139-25742324326641035911018192245764380433206269566410732384318.07%2246969.20%9694136350.92%641131748.67%604125947.97%2280168115485791120552
4720613000015985-261037000002939-101036000013046-1613591021611117291304711231811667573186172280531426.42%622362.90%113131042.26%14036338.57%13631143.73%446293454155304149
Total Saison Régulière18459102081113510627-11792314705612259303-4492285503501251324-73150510934144442991912111241841022146216695246631560161923525018817.56%53715571.14%161406292148.13%1431302647.29%1311281046.65%479634583770132825311238