Please rotate your device to landscape mode for a better experience.
Connexion

Blossom Bytes
GP: 3 | W: 3 | L: 0 | OTL: 0 | P: 6
GF: 15 | GA: 4 | PP%: 22.73% | PK%: 86.67%
DG: Gerd | Morale : 99 | Moyenne d’équipe : N/A
Prochains matchs #56 vs Admirals

Centre de jeu
Wolf Pack
1-2-0, 2pts
0
FINAL
4 Blossom Bytes
3-0-0, 6pts
Team Stats
L2SéquenceW3
1-0-0Fiche domicile1-0-0
0-2-0Fiche domicile2-0-0
1-2-0Derniers 10 matchs3-0-0
2.00Buts par match 5.00
3.67Buts contre par match 1.33
16.67%Pourcentage en avantage numérique22.73%
81.25%Pourcentage en désavantage numérique86.67%
Blossom Bytes
3-0-0, 6pts
4
FINAL
1 Senators
0-1-1, 1pts
Team Stats
W3SéquenceL1
1-0-0Fiche domicile0-1-1
2-0-0Fiche domicile0-0-0
3-0-0Derniers 10 matchs0-1-1
5.00Buts par match 2.50
1.33Buts contre par match 4.50
22.73%Pourcentage en avantage numérique30.00%
86.67%Pourcentage en désavantage numérique83.33%
Admirals
0-3-0, 0pts
Jour 8
Blossom Bytes
3-0-0, 6pts
Statistiques d’équipe
L3SéquenceW3
0-2-0Fiche domicile1-0-0
0-1-0Fiche visiteur2-0-0
0-3-010 derniers matchs3-0-0
2.33Buts par match 5.00
6.33Buts contre par match 5.00
14.29%Pourcentage en avantage numérique22.73%
61.54%Pourcentage en désavantage numérique86.67%
Blossom Bytes
3-0-0, 6pts
Jour 10
Titans
1-3-0, 2pts
Statistiques d’équipe
W3SéquenceL1
1-0-0Fiche domicile0-1-0
2-0-0Fiche visiteur1-2-0
3-0-010 derniers matchs1-3-0
5.00Buts par match 2.50
1.33Buts contre par match 2.50
22.73%Pourcentage en avantage numérique8.70%
86.67%Pourcentage en désavantage numérique50.00%
Grisards
3-0-1, 7pts
Jour 12
Blossom Bytes
3-0-0, 6pts
Statistiques d’équipe
OTL1SéquenceW3
2-0-0Fiche domicile1-0-0
1-0-1Fiche visiteur2-0-0
3-0-110 derniers matchs3-0-0
4.25Buts par match 5.00
3.75Buts contre par match 5.00
41.67%Pourcentage en avantage numérique22.73%
60.00%Pourcentage en désavantage numérique86.67%
Meneurs d'équipe
Buts
Nikita Grebenkin
4
Passes
Michael Milne
5
Points
John Farinacci
6
Plus/Moins
Tyrel Bauer
7
Victoires
Arvid Holm
3
Pourcentage d’arrêts
Arvid Holm
0.956

Statistiques d’équipe
Buts pour
15
5.00 GFG
Tirs pour
123
41.00 Avg
Pourcentage en avantage numérique
22.7%
5 GF
Début de zone offensive
36.6%
Buts contre
4
1.33 GAA
Tirs contre
90
30.00 Avg
Pourcentage en désavantage numérique
86.7%%
2 GA
Début de la zone défensive
34.2%
Informations de l'équipe

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


Informations de l’aréna

Capacité8,000
Assistance4,855
Billets de saison800


Informations de la formation

Équipe Pro30
Équipe Mineure22
Limite contact 52 / 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
1John FarinacciXXX100.00735094707477886383656273654961099002311,312,500$
2Julien GauthierXX100.00785093788577737361677171655863096002732,325,000$
3Jens LookeXX100.00606060606070706060606060606370097002711,783,180$
4Martin ChromiakXX100.0060606060607070606060606060435809900222866,250$
5Jason PolinXX100.0060509367757583626162636765505909900252682,500$
6Nikita NesterenkoX100.0069508870747792696170697065415609600232682,500$
7Riley DuranXXX100.0073509362677989616861627365415609900221700,000$
8Justin RobidasX100.0062509471667893647165636765415609900211825,000$
9Michael MilneXX100.0073508867707589626162637165415609900221825,000$
10Nikita GrebenkinXX100.0065508769797588656165646965405509901212650,000$
11Gracyn Sawchyn (R)X100.00606060606070706060606060604655099001931,250,000$
12Ilya Protas (R)XX100.0060606060607070606060606060425509900183975,000$
13Lukas CormierX100.00606060606070706060606060605361093002211,023,750$
14Tyrel BauerX100.0060606060607070606060606060425709900222787,500$
15Sean BehrensX100.00606060606070706060606060604156096002111,250,000$
16Dylan AnhornX100.0060606060607070606060606060415609900252682,500$
17Cameron AllenX100.0060606060607070606060606060405509901192825,000$
18Ty Murchison (R)X100.0060606060607070606060606060485509900212700,000$
Rayé
1Noel GunlerXX100.00606060606070706060606060604358096002321,312,500$
2Ryder KorczakX100.00606060606070706060606060604358096002221,023,750$
3Vinzenz RohrerXXX100.0060606060607070606060606060415609600201975,000$
4Hunter HaightXXX100.00606060606070706060606060604156096002011,250,000$
5Dylan WendtXXX100.0060606060607070606060606060405509600231650,000$
6Connor KelleyX100.0060606060607070606060606060405509601221650,000$
7Ty Gallagher (R)X100.0060606060607070606060606060485509600212750,000$
MOYENNE D’ÉQUIPE100.006357706364727562626161636245570970
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 Holm100.0060707060606060606060605664099002621,466,625$
2Ales Stezka100.006070706060606060606060556609900275727,650$
Rayé
1Isaiah Saville100.006070706060606060606060505909800241866,250$
2Hampton Slukynsky (R)100.006070706060606060606060425509800193750,000$
3Harrison Meneghin (R)100.006070706060606060606060465509800203650,000$
MOYENNE D’ÉQUIPE100.00607070606060606060606050600980
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Adam Foote8076687961661CAN543600,000$


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
1John FarinacciBlossom Bytes (SJS)C/LW/RW324630012122916.67%26521.700333150001110050.00%6421001.8400000100
2Michael MilneBlossom Bytes (SJS)LW/RW30553205110260%15016.85033315000000040.00%510001.9800000001
3Nikita GrebenkinBlossom Bytes (SJS)LW/RW341530063145328.57%35016.77202515000000033.33%600001.9900000011
4Lukas CormierBlossom Bytes (SJS)D304471410837110%47625.5800021400009000%002001.0400020010
5Tyrel BauerBlossom Bytes (SJS)D313478051071314.29%07625.5710121500007000%011001.0400000000
6Julien GauthierBlossom Bytes (SJS)LW/RW3303055041861216.67%04916.44202714000011033.33%340001.2200010000
7Nikita NesterenkoBlossom Bytes (SJS)C3033055439250%14916.53022215000000049.06%5310001.2100010000
8Justin RobidasBlossom Bytes (SJS)C32133003661433.33%03511.80000000000111165.00%2023001.6900000100
9Martin ChromiakBlossom Bytes (SJS)LW/RW3022300211020%0248.09000000000000100.00%120001.6500000000
10Riley DuranBlossom Bytes (SJS)C/LW/RW32022003365533.33%34414.73000000000121077.78%921000.9100000000
11Jens LookeBlossom Bytes (SJS)LW/RW3101310100061216.67%0248.030000000000000%101000.8300110001
12Jason PolinBlossom Bytes (SJS)LW/RW3011255169460%24113.94000000002110020.00%500000.4800001000
13Cameron AllenBlossom Bytes (SJS)D3011200242100%04113.880000000026000%010000.4800000000
14Gracyn SawchynBlossom Bytes (SJS)C3011200335230%13110.4500000000000038.71%3100000.6400000000
15Sean BehrensBlossom Bytes (SJS)D3000-11010542000%36020.18000014000113000%01200000011000
16Dylan AnhornBlossom Bytes (SJS)D3000275113120%24013.440000200001000%00000000001000
17Ty MurchisonBlossom Bytes (SJS)D3000-195804000%16220.89000015000111000%01200000001000
18Ilya ProtasBlossom Bytes (SJS)C/LW30000255542320%24816.13000014000000050.00%42000000001000
Statistiques d’équipe totales ou en moyenne5415264140100606258123376512.20%2587316.175813241540007983149.01%2022013000.9400165223
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
1Arvid HolmBlossom Bytes (SJS)33000.9561.331800149047000030110
Statistiques d’équipe totales ou en moyenne33000.9561.33180014904700030110


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)G271997-01-06CZENo190 Lbs6 ft4NoNoN/ANoNo5FalseFalsePro & Farm727,650$700,557$72,765$70,056$No727,650$727,650$727,650$727,650$-----727,650$727,650$727,650$727,650$-----NoNoNoNo-----
Arvid HolmBlossom Bytes (SJS)G261998-11-03SWENo214 Lbs6 ft4NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,466,625$1,412,017$146,662$141,201$No1,466,625$--------1,466,625$--------No--------
Cameron AllenBlossom Bytes (SJS)D192005-01-07CANNo194 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm825,000$794,282$82,500$79,428$No825,000$--------825,000$--------No--------
Connor KelleyBlossom Bytes (SJS)D222002-01-30USANo201 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm650,000$625,798$65,000$62,580$No---------------------------
Dylan AnhornBlossom Bytes (SJS)D251999-01-21CANNo190 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$657,088$68,250$65,709$No682,500$--------682,500$--------No--------
Dylan WendtBlossom Bytes (SJS)C/LW/RW232001-01-09USANo185 Lbs6 ft1NoNoFree AgentNoNo12025-06-11FalseFalsePro & Farm650,000$625,798$65,000$62,580$No---------------------------
Gracyn SawchynBlossom Bytes (SJS)C192005-01-19CANYes154 Lbs5 ft10NoNoProspectNoNo32025-08-21FalseFalsePro & Farm1,250,000$1,203,457$125,000$120,346$No1,250,000$1,250,000$-------1,250,000$1,250,000$-------NoNo-------
Hampton SlukynskyBlossom Bytes (SJS)G192005-07-02USAYes190 Lbs5 ft11NoNoProspectNoNo32025-08-21FalseFalsePro & Farm750,000$722,074$75,000$72,207$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Harrison MeneghinBlossom Bytes (SJS)G202004-09-13CANYes174 Lbs6 ft2NoNoDraftNoNo32025-08-21FalseFalsePro & Farm650,000$625,798$65,000$62,580$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Hunter HaightBlossom Bytes (SJS)C/LW/RW202004-04-04CANNo180 Lbs6 ft7NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$1,203,457$125,000$120,346$No---------------------------
Ilya ProtasBlossom Bytes (SJS)C/LW182006-07-18BLRYes201 Lbs6 ft3NoNoDraftNoNo32025-08-21FalseFalsePro & Farm975,000$938,697$97,500$93,870$No975,000$975,000$-------975,000$975,000$-------NoNo-------
Isaiah SavilleBlossom Bytes (SJS)G242000-09-21USANo196 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm866,250$833,996$86,625$83,400$No---------------------------
Jason PolinBlossom Bytes (SJS)LW/RW251999-06-17USANo198 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$657,088$68,250$65,709$No682,500$--------682,500$--------No--------
Jens LookeBlossom Bytes (SJS)LW/RW271997-04-11SWENo185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,783,180$1,716,785$178,318$171,678$No---------------------------
John FarinacciBlossom Bytes (SJS)C/LW/RW232001-02-14USANo197 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,312,500$1,263,630$131,250$126,363$No---------------------------
Julien Gauthier (contrat à 1 volet)Blossom Bytes (SJS)LW/RW271997-10-15CANNo226 Lbs6 ft4NoNoN/ANoNo3FalseFalsePro & Farm2,325,000$2,237,500$2,325,000$2,237,500$No2,325,000$2,325,000$-------2,325,000$2,325,000$-------NoNo-------
Justin RobidasBlossom Bytes (SJS)C212003-03-13USANo176 Lbs5 ft8NoNoN/ANoNo1FalseFalsePro & Farm825,000$794,282$82,500$79,428$No---------------------------
Lukas CormierBlossom Bytes (SJS)D222002-03-27CANNo185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,023,750$985,632$102,375$98,563$No---------------------------
Martin ChromiakBlossom Bytes (SJS)LW/RW222002-08-20SVKNo190 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm866,250$833,996$86,625$83,400$No866,250$--------866,250$--------No--------
Michael MilneBlossom Bytes (SJS)LW/RW222002-09-21CANNo185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm825,000$794,282$82,500$79,428$No---------------------------
Nikita GrebenkinBlossom Bytes (SJS)LW/RW212003-05-02RUSNo210 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm650,000$625,798$65,000$62,580$No650,000$--------650,000$--------No--------
Nikita NesterenkoBlossom Bytes (SJS)C232001-09-10USANo195 Lbs6 ft2NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$657,088$68,250$65,709$No682,500$--------682,500$--------No--------
Noel GunlerBlossom Bytes (SJS)LW/RW232001-10-07SWENo176 Lbs6 ft2NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,312,500$1,263,630$131,250$126,363$No1,312,500$--------1,312,500$--------No--------
Riley DuranBlossom Bytes (SJS)C/LW/RW222002-01-25USANo174 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm700,000$673,936$70,000$67,394$No---------------------------
Ryder KorczakBlossom Bytes (SJS)C222002-09-23CANNo172 Lbs5 ft11NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,023,750$985,632$102,375$98,563$No1,023,750$--------1,023,750$--------No--------
Sean BehrensBlossom Bytes (SJS)D212003-03-31USANo177 Lbs6 ft8NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$1,203,457$125,000$120,346$No---------------------------
Ty GallagherBlossom Bytes (SJS)D212003-03-06USAYes196 Lbs5 ft10NoNoProspectNoNo22025-08-21FalseFalsePro & Farm750,000$722,074$75,000$72,207$No750,000$--------750,000$--------No--------
Ty MurchisonBlossom Bytes (SJS)D212003-02-02USAYes205 Lbs6 ft0NoNoProspectNoNo22025-08-21FalseFalsePro & Farm700,000$673,936$70,000$67,394$No700,000$--------700,000$--------No--------
Tyrel BauerBlossom Bytes (SJS)D222002-05-23CANNo207 Lbs6 ft3NoNoN/ANoNo22025-09-08FalseFalsePro & Farm787,500$758,178$78,750$75,818$No787,500$--------787,500$--------No--------
Vinzenz RohrerBlossom Bytes (SJS)C/LW/RW202004-09-09AUTNo178 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm975,000$938,697$97,500$93,870$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3022.23190 Lbs6 ft11.87973,915$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ilya ProtasNikita NesterenkoJulien Gauthier28122
2Nikita GrebenkinJohn FarinacciMichael Milne28122
3Riley DuranGracyn SawchynJason Polin25122
4Jens LookeJustin RobidasMartin Chromiak19122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Lukas CormierTyrel Bauer28122
2Ty MurchisonSean Behrens28122
3Dylan AnhornCameron Allen25122
4Lukas CormierTyrel Bauer19122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ilya ProtasNikita NesterenkoJulien Gauthier50122
2Nikita GrebenkinJohn FarinacciMichael Milne50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Lukas CormierTyrel Bauer50122
2Ty MurchisonSean Behrens50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Justin RobidasJason Polin50122
2Riley DuranJohn Farinacci50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Lukas CormierTyrel Bauer50122
2Ty MurchisonSean Behrens50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Nikita Grebenkin50122Lukas CormierTyrel Bauer50122
2Julien Gauthier50122Ty MurchisonSean Behrens50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Gracyn SawchynJulien Gauthier50122
2Nikita NesterenkoJohn Farinacci50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Lukas CormierTyrel Bauer50122
2Ty MurchisonSean Behrens50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Gracyn SawchynNikita NesterenkoJulien GauthierLukas CormierTyrel Bauer
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ilya ProtasJustin RobidasJulien GauthierLukas CormierRiley Duran
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Ilya Protas, Jason Polin, Justin RobidasIlya Protas, Julien GauthierJustin Robidas
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dylan Anhorn, Cameron Allen, Ty MurchisonDylan AnhornCameron Allen, Ty Murchison
Tirs de pénalité
Justin Robidas, Julien Gauthier, Nikita Nesterenko, John Farinacci, Nikita Grebenkin
Gardien
#1 : Arvid Holm, #2 : Ales Stezka


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
1Admirals11000000734000000000001100000073421.00071219003750433641460381243277228.57%4175.00%0387451.35%366952.17%255942.37%673556295628
2Senators11000000413000000000001100000041321.000461000375029364146037812219111.11%6183.33%0387451.35%366952.17%255942.37%673556295628
3Wolf Pack11000000404110000004040000000000021.000481201375051364146015545146233.33%50100.00%0387451.35%366952.17%255942.37%673556295628
Total33000000154111100000040422000000114761.000152641013750123364146090251006222522.73%15286.67%0387451.35%366952.17%255942.37%673556295628
_Since Last GM Reset33000000154111100000040422000000114761.000152641013750123364146090251006222522.73%15286.67%0387451.35%366952.17%255942.37%673556295628
_Vs Conference33000000154111100000040422000000114761.000152641013750123364146090251006222522.73%15286.67%0387451.35%366952.17%255942.37%673556295628
_Vs Division12000000413010000000001100000041342.000461000375029364146037812219111.11%6183.33%0387451.35%366952.17%255942.37%673556295628

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
36W315264112390251006201
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
3300000154
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
110000040
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
2200000114
Derniers 10 matchs
WLOTWOTL SOWSOL
300000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
22522.73%15286.67%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
36414603750
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
387451.35%366952.17%255942.37%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
673556295628


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
12Blossom Bytes7Admirals3WSommaire du match
430Wolf Pack0Blossom Bytes4WSommaire du match
536Blossom Bytes4Senators1WSommaire du match
856Admirals-Blossom Bytes-
1071Blossom Bytes-Titans-
1286Grisards-Blossom Bytes-
1395Blossom Bytes-Gulls-
15109Blossom Bytes-Bears-
17125Penguins-Blossom Bytes-
18134Blossom Bytes-Rams-
21159Wolves-Blossom Bytes-
23168Blossom Bytes-Gulls-
26184Penguins-Blossom Bytes-
29211Blossom Bytes-Bears-
31220Gulls-Blossom Bytes-
35246Wolf Pack-Blossom Bytes-
38267Americans-Blossom Bytes-
40280Blossom Bytes-Grisards-
43303Wolves-Blossom Bytes-
45313Blossom Bytes-Wolves-
47325Blossom Bytes-Admirals-
49339Senators-Blossom Bytes-
51360Blossom Bytes-Whalers-
53370Octopus-Blossom Bytes-
56396Silver Knights-Blossom Bytes-
57410Blossom Bytes-Bulldogs-
60427White Wolves-Blossom Bytes-
62445Blossom Bytes-Penguins-
65461Admirals-Blossom Bytes-
68478Blossom Bytes-White Wolves-
70493Bears-Blossom Bytes-
74519Titans-Blossom Bytes-
78549Mountaineers-Blossom Bytes-
80567Blossom Bytes-Blood Miners-
83582Bulldogs-Blossom Bytes-
85601Blossom Bytes-Moose-
87613Phantoms-Blossom Bytes-
90635Blossom Bytes-Moose-
91644Wolf Pack-Blossom Bytes-
94667Blossom Bytes-Titans-
95675Blossom Bytes-Gulls-
97684Moose-Blossom Bytes-
100707Saints-Blossom Bytes-
102726Blossom Bytes-Phantoms-
104740Phantoms-Blossom Bytes-
106753Blossom Bytes-Roadrunners-
108766Blossom Bytes-Penguins-
110776Bears-Blossom Bytes-
112793Blossom Bytes-Senators-
114804Blossom Bytes-Reign-
115816Gulls-Blossom Bytes-
119842Blossom Bytes-Eagles-
120848Griffins-Blossom Bytes-
122870Blossom Bytes-Bills-
124878Grisards-Blossom Bytes-
127906Titans-Blossom Bytes-
129920Blossom Bytes-Titans-
131937Blossom Bytes-Rams-
132943Penguins-Blossom Bytes-
136969Blossom Bytes-Rams-
137975Rocket-Blossom Bytes-
1401000Gorillas-Blossom Bytes-
1421014Blossom Bytes-Crunch-
1431023Blossom Bytes-Bears-
1451038Norsemen-Blossom Bytes-
1481061Blossom Bytes-Admirals-
1491069Gorillas-Blossom Bytes-
1531096Grisards-Blossom Bytes-
1551109Blossom Bytes-Crunch-
1571128Redhawks-Blossom Bytes-
1581136Blossom Bytes-Wolf Pack-
1621159Whalers-Blossom Bytes-
1631168Blossom Bytes-Americans-
1661191Admirals-Blossom Bytes-
1671197Blossom Bytes-Senators-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1691214Blossom Bytes-Americans-
1721227Blossom Bytes-Norsemen-
1741238Whalers-Blossom Bytes-
1781261Rams-Blossom Bytes-
1811280Blossom Bytes-Wolf Pack-
1831292Blossom Bytes-Norsemen-
1861306Rams-Blossom Bytes-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité25005500
Prix des billets4525
Assistance1,7243,131
Assistance PCT68.96%56.93%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
40 4855 - 60.69% 187,026$187,026$8000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
122,472$ 2,689,246$ 2,689,246$ 600,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
17,496$ 122,472$ 29 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
7,481,040$ 181 17,496$ 3,166,776$




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