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Connexion

Blossom Bytes
GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0% | PK%: 0%
DG: Gerd | Morale : 99 | Moyenne d’équipe : N/A
Prochains matchs #4 vs Wolf Pack

Wolf Pack
0-0-0, 0pts
Jour 1
Blossom Bytes
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0Buts par match 0
0Buts contre par match 0
0%Pourcentage en avantage numérique0%
0%Pourcentage en désavantage numérique0%
Blossom Bytes
0-0-0, 0pts
Jour 3
Titans
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0Buts par match 0
0Buts contre par match 0
0%Pourcentage en avantage numérique0%
0%Pourcentage en désavantage numérique0%
Admirals
0-0-0, 0pts
Jour 5
Blossom Bytes
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0Buts par match 0
0Buts contre par match 0
0%Pourcentage en avantage numérique0%
0%Pourcentage en désavantage numérique0%
Meneurs d'équipe

Statistiques d’équipe
Informations de l'équipe

Directeur généralGerd
EntraîneurAdam Foote
DivisionAtlantic Division
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité8,500
Assistance
Billets de saison850


Informations de la formation

Équipe Pro33
Équipe Mineure20
Limite contact 53 / 65
Espoirs14


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 SPÂgeContratSalaire
1Noel GunlerXX100.00606060606070706060606060604962099002411,312,500$
2Martin ChromiakXX100.0060606060607070606060606060496209900231866,250$
3Ryder KorczakX100.00606060606070706060606060604962099002311,023,750$
4Jason PolinXX100.0072509367757586636163637365526109900261682,500$
5Riley DuranXXX100.0060606060607070606060606060476009900232800,000$
6Justin RobidasXXX100.0064509373667789658266646965435809900222866,250$
7Vinzenz RohrerXXX100.00606060606070706060606060604760099002121,023,750$
8Hunter HaightXXX100.00625091706677906671666667654358099002121,312,500$
9Michael MilneXX100.0060606060607070606060606060476009900232866,250$
10Nikita GrebenkinXX100.0073548775797886726569676965425709901221650,000$
11Gracyn SawchynXXX100.00606060606070706060606060605259099002021,250,000$
12Ilya ProtasXX100.0060509072868293667866656665445709900192975,000$
13Lukas CormierX100.00606060606070706060606060605965099002321,074,938$
14Henry BrzustewiczX100.00606060606070706060606060605061099001831,850,000$
15Tyrel BauerX100.0060606060607070606060606060486109900231787,500$
16Sean BehrensX100.00606060606070706060606060604760099002221,312,500$
17Dylan AnhornX100.0060606060607070606060606060476009900261682,500$
18Connor KelleyX100.0060606060607070606060606060465909901232800,000$
Rayé
1Alex GaffneyX100.0060606060607070606060606060546309900232700,000$
2John FarinacciXXX100.00606060606070706060606060605565099002421,378,125$
3Noah PowellXX100.0060606060607070606060606060506109900202900,000$
4Julien GauthierXX100.00606060606070706060606060606467099002822,325,000$
5Mack OliphantX100.0060606060607070606060606060526209900232650,000$
6Trey TaylorX100.0060606060607070606060606060485909900233850,000$
7Cameron AllenX100.0060606060607070606060606060465909901201825,000$
8Ty GallagherX100.0060606060607070606060606060545909900221750,000$
9Ty MurchisonX100.0064508062808280622563627365505709900221700,000$
MOYENNE D’ÉQUIPE100.006158666263727461616161626149610990
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 SPÂgeContratSalaire
1Arvid Holm100.0060707060606060606060606873099002711,466,625$
2Hampton Slukynsky100.006070706060606060606060516109900202750,000$
Rayé
1Emmett Croteau100.006070706060606060606060536309900222850,000$
2Ales Stezka100.006070706060606060606060647209900284727,650$
3Isaiah Saville100.006070706060606060606060596509900251909,563$
4Harrison Meneghin100.006070706060606060606060556109900212650,000$
MOYENNE D’ÉQUIPE100.00607070606060606060606058660990
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Adam Foote8076749162671CAN552600,000$


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’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
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


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Ales StezkaBlossom Bytes (SJS)G281997-01-06CZENo190 Lbs6 ft4NoNoN/ANoNo4FalseFalsePro & Farm727,650$727,650$72,765$72,765$No727,650$727,650$727,650$------727,650$727,650$727,650$------NoNoNo------
Alex GaffneyBlossom Bytes (SJS)C232002-06-25USANo176 Lbs5 ft9NoNoAssign ManuallyNoNo22026-03-29FalseFalsePro & Farm700,000$700,000$70,000$70,000$No700,000$--------700,000$--------No--------
Arvid HolmBlossom Bytes (SJS)G271998-11-03SWENo214 Lbs6 ft4NoNoN/ANoNo12025-09-08FalseFalsePro & Farm1,466,625$1,466,625$146,662$146,662$No---------------------------
Cameron AllenBlossom Bytes (SJS)D202005-01-07CANNo194 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm825,000$825,000$82,500$82,500$No---------------------------
Connor KelleyBlossom Bytes (SJS)D232002-01-30USANo201 Lbs6 ft2NoNoN/ANoNo22026-08-02FalseFalsePro & Farm800,000$800,000$80,000$80,000$No800,000$--------800,000$--------No--------
Dylan AnhornBlossom Bytes (SJS)D261999-01-21CANNo190 Lbs6 ft0NoNoN/ANoNo12025-09-08FalseFalsePro & Farm682,500$682,500$68,250$68,250$No---------------------------
Emmett CroteauBlossom Bytes (SJS)G222003-12-07CANNo209 Lbs6 ft2NoNoAssign ManuallyNoNo22026-07-17FalseFalsePro & Farm850,000$850,000$85,000$85,000$No850,000$--------850,000$--------No--------
Gracyn SawchynBlossom Bytes (SJS)C/LW/RW202005-01-19CANNo154 Lbs5 ft10NoNoProspectNoNo22025-08-21FalseFalsePro & Farm1,250,000$1,250,000$125,000$125,000$No1,250,000$--------1,250,000$--------No--------
Hampton SlukynskyBlossom Bytes (SJS)G202005-07-02USANo190 Lbs5 ft11NoNoProspectNoNo22025-08-21FalseFalsePro & Farm750,000$750,000$75,000$75,000$No750,000$--------750,000$--------No--------
Harrison MeneghinBlossom Bytes (SJS)G212004-09-13CANNo174 Lbs6 ft2NoNoDraftNoNo22025-08-21FalseFalsePro & Farm650,000$650,000$65,000$65,000$No650,000$--------650,000$--------No--------
Henry BrzustewiczBlossom Bytes (SJS)D182007-02-09USANo205 Lbs6 ft0NoNoAssign ManuallyNoNo32026-07-17FalseFalsePro & Farm1,850,000$1,850,000$185,000$185,000$No1,850,000$1,850,000$-------1,850,000$1,850,000$-------NoNo-------
Hunter HaightBlossom Bytes (SJS)C/LW/RW212004-04-04CANNo173 Lbs5 ft10NoNoN/ANoNo22026-08-02FalseFalsePro & Farm1,312,500$1,312,500$131,250$131,250$No1,312,500$--------1,312,500$--------No--------
Ilya ProtasBlossom Bytes (SJS)C/LW192006-07-18BLRNo225 Lbs6 ft6NoNoDraftNoNo22025-08-21FalseFalsePro & Farm975,000$975,000$97,500$97,500$No975,000$--------975,000$--------No--------
Isaiah SavilleBlossom Bytes (SJS)G252000-09-21USANo196 Lbs6 ft1NoNoN/ANoNo12026-08-02FalseFalsePro & Farm909,563$909,563$90,956$90,956$No---------------------------
Jason PolinBlossom Bytes (SJS)LW/RW261999-06-17USANo198 Lbs6 ft0NoNoN/ANoNo12025-09-08FalseFalsePro & Farm682,500$682,500$68,250$68,250$No---------------------------
John FarinacciBlossom Bytes (SJS)C/LW/RW242001-02-14USANo197 Lbs5 ft11NoNoN/ANoNo22026-08-02FalseFalsePro & Farm1,378,125$1,378,125$137,812$137,812$No1,378,125$--------1,378,125$--------No--------
Julien Gauthier (contrat à 1 volet)Blossom Bytes (SJS)LW/RW281997-10-15CANNo226 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm2,325,000$2,325,000$2,325,000$2,325,000$No2,325,000$--------2,325,000$--------No--------
Justin RobidasBlossom Bytes (SJS)C/LW/RW222003-03-13USANo176 Lbs5 ft8NoNoN/ANoNo22026-08-02FalseFalsePro & Farm866,250$866,250$86,625$86,625$No866,250$--------866,250$--------No--------
Lukas CormierBlossom Bytes (SJS)D232002-03-27CANNo185 Lbs5 ft11NoNoN/ANoNo22026-08-02FalseFalsePro & Farm1,074,938$1,074,938$107,494$107,494$No1,074,938$--------1,074,938$--------No--------
Mack OliphantBlossom Bytes (SJS)D232002-12-28USANo205 Lbs6 ft1NoNoAssign ManuallyNoNo22026-03-29FalseFalsePro & Farm650,000$650,000$65,000$65,000$No650,000$--------650,000$--------No--------
Martin ChromiakBlossom Bytes (SJS)LW/RW232002-08-20SVKNo190 Lbs6 ft0NoNoN/ANoNo12025-09-08FalseFalsePro & Farm866,250$866,250$86,625$86,625$No---------------------------
Michael MilneBlossom Bytes (SJS)LW/RW232002-09-21CANNo185 Lbs5 ft11NoNoN/ANoNo22026-08-02FalseFalsePro & Farm866,250$866,250$86,625$86,625$No866,250$--------866,250$--------No--------
Nikita GrebenkinBlossom Bytes (SJS)LW/RW222003-05-02RUSNo210 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm650,000$650,000$65,000$65,000$No---------------------------
Noah PowellBlossom Bytes (SJS)LW/RW202005-02-02USANo201 Lbs6 ft0NoNoAssign ManuallyNoNo22026-07-17FalseFalsePro & Farm900,000$900,000$90,000$90,000$No900,000$--------900,000$--------No--------
Noel GunlerBlossom Bytes (SJS)LW/RW242001-10-07SWENo176 Lbs6 ft2NoNoN/ANoNo12025-09-08FalseFalsePro & Farm1,312,500$1,312,500$131,250$131,250$No---------------------------
Riley DuranBlossom Bytes (SJS)C/LW/RW232002-01-25USANo174 Lbs6 ft1NoNoN/ANoNo22026-08-02FalseFalsePro & Farm800,000$800,000$80,000$80,000$No800,000$--------800,000$--------No--------
Ryder KorczakBlossom Bytes (SJS)C232002-09-23CANNo172 Lbs5 ft11NoNoN/ANoNo12025-09-08FalseFalsePro & Farm1,023,750$1,023,750$102,375$102,375$No---------------------------
Sean BehrensBlossom Bytes (SJS)D222003-03-31USANo177 Lbs6 ft8NoNoN/ANoNo22026-08-02FalseFalsePro & Farm1,312,500$1,312,500$131,250$131,250$No1,312,500$--------1,312,500$--------No--------
Trey TaylorBlossom Bytes (SJS)D232002-02-04CANNo190 Lbs6 ft0NoNoAssign ManuallyNoNo32026-08-10FalseFalsePro & Farm850,000$850,000$85,000$85,000$No850,000$850,000$-------850,000$850,000$-------NoNo-------
Ty GallagherBlossom Bytes (SJS)D222003-03-06USANo196 Lbs5 ft10NoNoProspectNoNo12025-08-21FalseFalsePro & Farm750,000$750,000$75,000$75,000$No---------------------------
Ty MurchisonBlossom Bytes (SJS)D222003-02-02USANo212 Lbs6 ft2NoNoProspectNoNo12025-08-21FalseFalsePro & Farm700,000$700,000$70,000$70,000$No---------------------------
Tyrel BauerBlossom Bytes (SJS)D232002-05-23CANNo207 Lbs6 ft3NoNoN/ANoNo12025-09-08FalseFalsePro & Farm787,500$787,500$78,750$78,750$No---------------------------
Vinzenz RohrerBlossom Bytes (SJS)C/LW/RW212004-09-09AUTNo178 Lbs6 ft1NoNoN/ANoNo22026-08-02FalseFalsePro & Farm1,023,750$1,023,750$102,375$102,375$No1,023,750$--------1,023,750$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3322.73192 Lbs6 ft11.76986,914$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Noel GunlerIlya ProtasNikita Grebenkin28113
2Martin ChromiakRyder KorczakJustin Robidas28122
3Jason PolinVinzenz RohrerRiley Duran25122
4Michael MilneHunter HaightGracyn Sawchyn19122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Lukas CormierHenry Brzustewicz28122
2Tyrel BauerSean Behrens28122
3Dylan AnhornConnor Kelley25122
4Lukas CormierHenry Brzustewicz19122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jason PolinJustin RobidasNikita Grebenkin50014
2Martin ChromiakIlya ProtasHunter Haight50113
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Lukas CormierHenry Brzustewicz50122
2Tyrel BauerSean Behrens50113
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Riley DuranNoel Gunler50131
2Justin RobidasMartin Chromiak50131
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Lukas CormierHenry Brzustewicz50122
2Tyrel BauerSean Behrens50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Riley Duran50122Lukas CormierHenry Brzustewicz50122
2Justin Robidas50122Tyrel BauerSean Behrens50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Riley DuranNoel Gunler50122
2Justin RobidasMartin Chromiak50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Lukas CormierHenry Brzustewicz50122
2Tyrel BauerSean Behrens50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nikita GrebenkinRiley DuranJason PolinLukas CormierHenry Brzustewicz
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Noel GunlerRiley DuranVinzenz RohrerLukas CormierHenry Brzustewicz
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Gracyn Sawchyn, Noel Gunler, Martin ChromiakGracyn Sawchyn, Noel GunlerGracyn Sawchyn
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Sean Behrens, Dylan Anhorn, Connor KelleySean BehrensSean Behrens, Dylan Anhorn
Tirs de pénalité
Riley Duran, Justin Robidas, Vinzenz Rohrer, Hunter Haight, Gracyn Sawchyn
Gardien
#1 : Arvid Holm, #2 : Hampton Slukynsky


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
TotalDomicileVisiteur
# 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
Total00000000000000000000000000000000000.000000000000000000000000%000%0000%000%000%000000

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
00N/A0000000000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 matchs
WLOTWOTL SOWSOL
000000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
000%000%0
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
00000000
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
000%000%000%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
000000


Derniers matchs 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
14Wolf Pack-Blossom Bytes-
319Blossom Bytes-Titans-
536Admirals-Blossom Bytes-
863Blossom Bytes-Gulls-
1080Pens-Blossom Bytes-
1185Blossom Bytes-Rams-
13100Blossom Bytes-Bears-
15118Wolf Pack-Blossom Bytes-
17136White Wolves-Blossom Bytes-
21163Admirals-Blossom Bytes-
23176Blossom Bytes-Bears-
25186Blossom Bytes-Gulls-
27198Blossom Bytes-Americans-
29213Blossom Bytes-Griffins-
30221Pens-Blossom Bytes-
33244Moose-Blossom Bytes-
35262Blossom Bytes-Norsemen-
37270Blossom Bytes-Moose-
39284Blossom Bytes-Eagles-
40293Saints-Blossom Bytes-
42315Norsemen-Blossom Bytes-
46340Blossom Bytes-Whalers-
47348Wolf Pack-Blossom Bytes-
50370Blossom Bytes-Titans-
51382Admirals-Blossom Bytes-
54395Blossom Bytes-Bears-
56408Blossom Bytes-Crunch-
57416Silver Knights-Blossom Bytes-
60442Blossom Bytes-Titans-
61447Americans-Blossom Bytes-
64472Phantoms-Blossom Bytes-
66484Blossom Bytes-Mountaineers-
68504Gorillas-Blossom Bytes-
70521Blossom Bytes-Octopus-
72536Blood Miners-Blossom Bytes-
74547Blossom Bytes-Grisards-
77569Blossom Bytes-Wolves-
78576Bears-Blossom Bytes-
81601Sens-Blossom Bytes-
83616Blossom Bytes-Reign-
86636Bears-Blossom Bytes-
88648Blossom Bytes-Roadrunners-
90664Pens-Blossom Bytes-
92677Blossom Bytes-Norsemen-
94696Grisards-Blossom Bytes-
96709Blossom Bytes-Wolf Pack-
98724Blossom Bytes-Rams-
99732Gulls-Blossom Bytes-
102751Blossom Bytes-Rams-
103762Blossom Bytes-Bills-
104768Sens-Blossom Bytes-
107795Grisards-Blossom Bytes-
112825Moose-Blossom Bytes-
114844Blossom Bytes-Sens-
116856Redhawks-Blossom Bytes-
120881Bulldogs-Blossom Bytes-
124912White Wolves-Blossom Bytes-
126926Blossom Bytes-Whalers-
128940Gulls-Blossom Bytes-
131967Wolves-Blossom Bytes-
133980Blossom Bytes-Phantoms-
135994Blossom Bytes-Admirals-
1361007Whalers-Blossom Bytes-
1391030Rams-Blossom Bytes-
1411044Blossom Bytes-Gulls-
1441060Blossom Bytes-Wolf Pack-
1451073Wolves-Blossom Bytes-
1491095Titans-Blossom Bytes-
1521118Blossom Bytes-Griffins-
1531128Titans-Blossom Bytes-
1561148Blossom Bytes-Pens-
1581158Rams-Blossom Bytes-
1601172Blossom Bytes-Rocket-
1611178Blossom Bytes-Americans-
1651194Phantoms-Blossom Bytes-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1681217Bulldogs-Blossom Bytes-
1701229Blossom Bytes-Admirals-
1711234Blossom Bytes-Pens-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité35005000
Prix des billets3515
Assistance0%0%
Assistance PCT0%0%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
39 0 - 0%0$0$8500100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
0$ 3,024,315$ 3,024,315$ 600,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
20,829$ 0$ 32 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 174 20,829$ 3,624,246$




Blossom Bytes Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Blossom Bytes Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Blossom Bytes Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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

Blossom Bytes Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Blossom Bytes Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA