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Blossom Bytes
GP: 60 | W: 42 | L: 14 | OTL: 4 | P: 88
GF: 273 | GA: 207 | PP%: 29.91% | PK%: 73.33%
DG: Gerd | Morale : 99 | Moyenne d’équipe : N/A
Prochains matchs #975 vs Rocket

Centre de jeu
Penguins
33-25-4, 70pts
2
FINAL
3 Blossom Bytes
42-14-4, 88pts
Team Stats
L1SéquenceW2
16-13-1Fiche domicile20-8-2
17-12-3Fiche domicile22-6-2
4-3-3Derniers 10 matchs8-1-1
3.27Buts par match 4.55
3.15Buts contre par match 3.45
28.33%Pourcentage en avantage numérique29.91%
69.43%Pourcentage en désavantage numérique73.33%
Blossom Bytes
42-14-4, 88pts
6
FINAL
4 Rams
34-24-2, 70pts
Team Stats
W2SéquenceL1
20-8-2Fiche domicile13-17-1
22-6-2Fiche domicile21-7-1
8-1-1Derniers 10 matchs8-2-0
4.55Buts par match 3.85
3.45Buts contre par match 3.37
29.91%Pourcentage en avantage numérique31.37%
73.33%Pourcentage en désavantage numérique72.37%
Rocket
24-32-5, 53pts
Jour 137
Blossom Bytes
42-14-4, 88pts
Statistiques d’équipe
W1SéquenceW2
9-19-2Fiche domicile20-8-2
15-13-3Fiche visiteur22-6-2
8-2-010 derniers matchs8-1-1
3.20Buts par match 4.55
4.00Buts contre par match 4.55
27.09%Pourcentage en avantage numérique29.91%
69.69%Pourcentage en désavantage numérique73.33%
Gorillas
26-31-7, 59pts
Jour 140
Blossom Bytes
42-14-4, 88pts
Statistiques d’équipe
L2SéquenceW2
14-13-3Fiche domicile20-8-2
12-18-4Fiche visiteur22-6-2
7-3-010 derniers matchs8-1-1
3.19Buts par match 4.55
3.77Buts contre par match 4.55
25.18%Pourcentage en avantage numérique29.91%
70.97%Pourcentage en désavantage numérique73.33%
Blossom Bytes
42-14-4, 88pts
Jour 142
Crunch
30-24-8, 68pts
Statistiques d’équipe
W2SéquenceL1
20-8-2Fiche domicile17-8-5
22-6-2Fiche visiteur13-16-3
8-1-110 derniers matchs3-6-1
4.55Buts par match 3.37
3.45Buts contre par match 3.37
29.91%Pourcentage en avantage numérique34.36%
73.33%Pourcentage en désavantage numérique73.97%
Meneurs d'équipe
Buts
Julien Gauthier
38
Passes
John Farinacci
50
Points
Julien Gauthier
80
Plus/Moins
Tyrel Bauer
22
Victoires
Arvid Holm
25
Pourcentage d’arrêts
Ales Stezka
0.898

Statistiques d’équipe
Buts pour
273
4.55 GFG
Tirs pour
2215
36.92 Avg
Pourcentage en avantage numérique
29.9%
96 GF
Début de zone offensive
39.8%
Buts contre
207
3.45 GAA
Tirs contre
1932
32.20 Avg
Pourcentage en désavantage numérique
73.3%%
72 GA
Début de la zone défensive
33.6%
Informations de l'équipe

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


Informations de l’aréna

Capacité8,000
Assistance4,964
Billets de saison800


Informations de la formation

Équipe Pro32
Équipe Mineure22
Limite contact 54 / 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 FarinacciXXX100.00735094707477886383656273654961090002311,312,500$
2Julien GauthierXX100.00785093788577737361677171655863085002732,325,000$
3Jens LookeXX100.00606060606070706060606060606370085002711,783,180$
4Martin ChromiakXX100.0060606060607070606060606060435809000222866,250$
5Jason PolinXX100.0060509367757583626162636765505909000252682,500$
6Nikita NesterenkoX100.0069508870747792696170697065415608600232682,500$
7Hunter HaightXXX100.00606060606070706060606060604156068002011,250,000$
8Michael MilneXX100.0073508867707589626162637165415609100221825,000$
9Nikita GrebenkinXX100.0065508769797588656165646965405508801212650,000$
10Gracyn Sawchyn (R)X100.00606060606070706060606060604655088001931,250,000$
11Ilya Protas (R)XX100.0060606060607070606060606060425509000183975,000$
12Lukas CormierX100.00606060606070706060606060605361076002211,023,750$
13Sean BehrensX100.00606060606070706060606060604156083002111,250,000$
14Dylan AnhornX100.0060606060607070606060606060415609000252682,500$
15Connor KelleyX100.0060606060607070606060606060405508401221650,000$
16Cameron AllenX100.0060606060607070606060606060405509001192825,000$
17Ty Murchison (R)X100.0060606060607070606060606060485506800212700,000$
Rayé
1Alex GaffneyX100.0060606060607070606060606060485909700223700,000$
2Noel GunlerXX100.00606060606070706060606060604358062002321,312,500$
3Ryder KorczakX100.00606060606070706060606060604358042002221,023,750$
4Riley DuranXXX100.0073509362677989616861627365415608700221700,000$
5Justin RobidasX92.0062509471667893647165636765415607400211825,000$
6Vinzenz RohrerXXX100.0060606060607070606060606060415605900201975,000$
7Dylan WendtXXX100.0060606060607070606060606060405504100231650,000$
8Mack OliphantX100.0060606060607070606060606060465809700223650,000$
9Tyrel BauerX100.0060606060607070606060606060425708700222787,500$
10Ty Gallagher (R)X100.0060606060607070606060606060485505600212750,000$
MOYENNE D’ÉQUIPE99.676357696364727561626161636145570790
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
1Hampton Slukynsky (R)99.006070706060606060606060425508300193750,000$
2Harrison Meneghin (R)100.006070706060606060606060465509000203650,000$
Rayé
1Arvid Holm100.0060707060606060606060605664058002621,466,625$
2Ales Stezka48.126070706060606060606060556605800275727,650$
3Isaiah Saville100.006070706060606060606060505906900241866,250$
MOYENNE D’ÉQUIPE89.40607070606060606060606050600720
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
1Julien GauthierBlossom Bytes (SJS)LW/RW523842807343073672467912815.45%2283516.07212243611950000186344.00%755121031.9137141685
2John FarinacciBlossom Bytes (SJS)C/LW/RW602750776372568961817312714.92%20108618.111033433122512371843158.17%7653720001.4223212722
3Nikita NesterenkoBlossom Bytes (SJS)C51273663-5202067702024512413.37%2995518.731118294018910161080146.59%9812512001.3211022443
4Nikita GrebenkinBlossom Bytes (SJS)LW/RW60332659-3352581572087112715.87%1795715.9516173342223000014344.83%583410011.2301230345
5Ilya ProtasBlossom Bytes (SJS)C/LW59222345151417512354117286518.80%24101617.229122124216000007049.47%952420100.8900348131
6Michael MilneBlossom Bytes (SJS)LW/RW60162642-551357039123529613.01%2882613.77610161895000000241.07%56227001.0225241112
7Jason PolinBlossom Bytes (SJS)LW/RW601918371659454654155549012.26%3094215.7110112202201813040.00%802112000.7811324112
8Justin RobidasBlossom Bytes (SJS)C5211243573715355813243728.33%1665912.680113150222561253.38%5324210001.0603012224
9Riley DuranBlossom Bytes (SJS)C/LW/RW531717341659355973110327715.45%2774214.0153884421381641154.15%2531115010.9211223111
10Martin ChromiakBlossom Bytes (SJS)LW/RW5911213276735803796296011.46%1572212.2537101699000002140.54%371713000.8957205052
11Tyrel BauerBlossom Bytes (SJS)D5252025221185088888627385.81%67123223.70426101930001149010%02027000.4101235001
12Sean BehrensBlossom Bytes (SJS)D5942125201739599626617286.06%60119220.223710162150113164000%01429000.4200658101
13Gracyn SawchynBlossom Bytes (SJS)C585182312684075626927427.25%2468311.7900000000012149.52%630414000.6700422020
14Hunter HaightBlossom Bytes (SJS)C/LW/RW19101121102915332063123015.87%629115.33156559000062137.84%3756001.4401201212
15Lukas CormierBlossom Bytes (SJS)D4202020-3704078494811130%4192021.9208891540222117000%0725000.4300242020
16Ty MurchisonBlossom Bytes (SJS)D4021719111147074455022124.00%4689722.4315612139000193100%01622000.4200446001
17Dylan AnhornBlossom Bytes (SJS)D521171811348072506125221.64%66107420.671455620003116000%0723000.3300628000
18Cameron AllenBlossom Bytes (SJS)D60314177744076565522225.45%47104117.36257101180002100000%0919000.3300224000
19Jens LookeBlossom Bytes (SJS)LW/RW336713101810391440122115.00%42898.7601105000031066.67%12610000.9000110001
20Noel GunlerBlossom Bytes (SJS)LW/RW27268220103716269227.69%72669.8810118000030080.00%553000.6000002001
21Connor KelleyBlossom Bytes (SJS)D303584864043343316159.09%3553917.980000200008100%069100.3000215101
22Vinzenz RohrerBlossom Bytes (SJS)C/LW/RW14257753251933248138.33%321115.13000130001360046.29%22943000.6600212002
23Ty GallagherBlossom Bytes (SJS)D251236101352625241134.17%1240816.35123439000032010%0515000.1500222010
24Ryder KorczakBlossom Bytes (SJS)C2000020000000%021.35000000000000100.00%10000000000000
Statistiques d’équipe totales ou en moyenne10792654467111701600890146111592215725124711.96%6461779816.499616225831723136814561551341850.55%3846392345250.801531525075303737
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)3425230.8973.3017812198948559400.818223210320
2Ales StezkaBlossom Bytes (SJS)2011600.8983.4811200065639380310.7147208221
3Hampton SlukynskyBlossom Bytes (SJS)105410.8873.355560031275158101.0002815100
4Harrison MeneghinBlossom Bytes (SJS)71200.8413.49189001169380000027000
Statistiques d’équipe totales ou en moyenne71421440.8943.373648212051931113581316060641


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 Stezka (sur la masse salariale)Blossom Bytes (SJS)G271997-01-06CZENo190 Lbs6 ft4NoNoN/ANoNo5FalseFalsePro & Farm727,650$201,265$72,765$20,126$No727,650$727,650$727,650$727,650$-----727,650$727,650$727,650$727,650$-----NoNoNoNo-----
Alex GaffneyBlossom Bytes (SJS)C222002-06-25USANo176 Lbs5 ft9NoNoAssign ManuallyNoNo32026-03-29FalseFalsePro & Farm700,000$193,617$70,000$19,362$No700,000$700,000$-------700,000$700,000$-------NoNo-------
Arvid HolmBlossom Bytes (SJS)G261998-11-03SWENo214 Lbs6 ft4NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,466,625$405,662$146,662$40,566$No1,466,625$--------1,466,625$--------No--------
Cameron AllenBlossom Bytes (SJS)D192005-01-07CANNo194 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm825,000$228,191$82,500$22,819$No825,000$--------825,000$--------No--------
Connor KelleyBlossom Bytes (SJS)D222002-01-30USANo201 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm650,000$179,787$65,000$17,979$No---------------------------
Dylan AnhornBlossom Bytes (SJS)D251999-01-21CANNo190 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$188,777$68,250$18,878$No682,500$--------682,500$--------No--------
Dylan WendtBlossom Bytes (SJS)C/LW/RW232001-01-09USANo185 Lbs6 ft1NoNoFree AgentNoNo12025-06-11FalseFalsePro & Farm650,000$179,787$65,000$17,979$No---------------------------
Gracyn SawchynBlossom Bytes (SJS)C192005-01-19CANYes154 Lbs5 ft10NoNoProspectNoNo32025-08-21FalseFalsePro & Farm1,250,000$345,745$125,000$34,574$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$207,447$75,000$20,745$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Harrison MeneghinBlossom Bytes (SJS)G202004-09-13CANYes174 Lbs6 ft2NoNoDraftNoNo32025-08-21FalseFalsePro & Farm650,000$179,787$65,000$17,979$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Hunter HaightBlossom Bytes (SJS)C/LW/RW202004-04-04CANNo180 Lbs6 ft7NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$345,745$125,000$34,574$No---------------------------
Ilya ProtasBlossom Bytes (SJS)C/LW182006-07-18BLRYes201 Lbs6 ft3NoNoDraftNoNo32025-08-21FalseFalsePro & Farm975,000$269,681$97,500$26,968$No975,000$975,000$-------975,000$975,000$-------NoNo-------
Isaiah SavilleBlossom Bytes (SJS)G242000-09-21USANo196 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm866,250$239,601$86,625$23,960$No---------------------------
Jason PolinBlossom Bytes (SJS)LW/RW251999-06-17USANo198 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$188,777$68,250$18,878$No682,500$--------682,500$--------No--------
Jens LookeBlossom Bytes (SJS)LW/RW271997-04-11SWENo185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,783,180$493,220$178,318$49,322$No---------------------------
John FarinacciBlossom Bytes (SJS)C/LW/RW232001-02-14USANo197 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,312,500$363,032$131,250$36,303$No---------------------------
Julien Gauthier (contrat à 1 volet)Blossom Bytes (SJS)LW/RW271997-10-15CANNo226 Lbs6 ft4NoNoN/ANoNo3FalseFalsePro & Farm2,325,000$625,000$2,325,000$625,000$No2,325,000$2,325,000$-------2,325,000$2,325,000$-------NoNo-------
Justin Robidas (sur la masse salariale)Blossom Bytes (SJS)C212003-03-13USANo176 Lbs5 ft8NoNoN/ANoNo1FalseFalsePro & Farm825,000$228,191$82,500$22,819$No---------------------------
Lukas CormierBlossom Bytes (SJS)D222002-03-27CANNo185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,023,750$283,165$102,375$28,316$No---------------------------
Mack OliphantBlossom Bytes (SJS)D222002-12-28USANo205 Lbs6 ft1NoNoAssign ManuallyNoNo32026-03-29FalseFalsePro & Farm650,000$179,787$65,000$17,979$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Martin ChromiakBlossom Bytes (SJS)LW/RW222002-08-20SVKNo190 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm866,250$239,601$86,625$23,960$No866,250$--------866,250$--------No--------
Michael MilneBlossom Bytes (SJS)LW/RW222002-09-21CANNo185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm825,000$228,191$82,500$22,819$No---------------------------
Nikita GrebenkinBlossom Bytes (SJS)LW/RW212003-05-02RUSNo210 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm650,000$179,787$65,000$17,979$No650,000$--------650,000$--------No--------
Nikita NesterenkoBlossom Bytes (SJS)C232001-09-10USANo195 Lbs6 ft2NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$188,777$68,250$18,878$No682,500$--------682,500$--------No--------
Noel GunlerBlossom Bytes (SJS)LW/RW232001-10-07SWENo176 Lbs6 ft2NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,312,500$363,032$131,250$36,303$No1,312,500$--------1,312,500$--------No--------
Riley DuranBlossom Bytes (SJS)C/LW/RW222002-01-25USANo174 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm700,000$193,617$70,000$19,362$No---------------------------
Ryder KorczakBlossom Bytes (SJS)C222002-09-23CANNo172 Lbs5 ft11NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,023,750$283,165$102,375$28,316$No1,023,750$--------1,023,750$--------No--------
Sean BehrensBlossom Bytes (SJS)D212003-03-31USANo177 Lbs6 ft8NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$345,745$125,000$34,574$No---------------------------
Ty GallagherBlossom Bytes (SJS)D212003-03-06USAYes196 Lbs5 ft10NoNoProspectNoNo22025-08-21FalseFalsePro & Farm750,000$207,447$75,000$20,745$No750,000$--------750,000$--------No--------
Ty MurchisonBlossom Bytes (SJS)D212003-02-02USAYes205 Lbs6 ft0NoNoProspectNoNo22025-08-21FalseFalsePro & Farm700,000$193,617$70,000$19,362$No700,000$--------700,000$--------No--------
Tyrel BauerBlossom Bytes (SJS)D222002-05-23CANNo207 Lbs6 ft3NoNoN/ANoNo22025-09-08FalseFalsePro & Farm787,500$217,819$78,750$21,782$No787,500$--------787,500$--------No--------
Vinzenz RohrerBlossom Bytes (SJS)C/LW/RW202004-09-09AUTNo178 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm975,000$269,681$97,500$26,968$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3222.22190 Lbs6 ft11.94955,233$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ilya ProtasNikita NesterenkoMichael Milne28122
2Nikita GrebenkinMartin Chromiak28122
3Julien GauthierGracyn SawchynJason Polin25122
4John FarinacciHunter HaightJens Looke19122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Connor KelleyDylan Anhorn28122
2Lukas CormierSean Behrens28122
3Ty MurchisonCameron Allen25122
4Connor KelleySean Behrens19122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Ilya ProtasNikita NesterenkoMartin Chromiak50122
2Nikita GrebenkinJohn FarinacciJulien Gauthier50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ty MurchisonCameron Allen50122
2Lukas CormierSean Behrens50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Hunter HaightJason Polin50122
2Nikita NesterenkoJohn Farinacci50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Lukas CormierDylan Anhorn50122
2Ty MurchisonSean Behrens50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Hunter Haight50122Ty MurchisonLukas Cormier50122
2Julien Gauthier50122Cameron AllenSean Behrens50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Gracyn SawchynMartin Chromiak50122
2Julien Gauthier50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Cameron AllenTy Murchison50122
2Dylan AnhornSean Behrens50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Gracyn SawchynNikita NesterenkoJulien GauthierTy MurchisonDylan Anhorn
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Ilya ProtasGracyn SawchynMartin ChromiakSean BehrensDylan Anhorn
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Ilya Protas, Jason Polin, Julien GauthierIlya Protas, Martin ChromiakJulien Gauthier
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ty Murchison, Cameron Allen, Lukas CormierSean BehrensCameron Allen, Lukas Cormier
Tirs de pénalité
Julien Gauthier, Martin Chromiak, Michael Milne, John Farinacci, Nikita Grebenkin
Gardien
#1 : Hampton Slukynsky, #2 : Harrison Meneghin


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
1Admirals42100010181442110000089-121000010105560.75018274500709993181537367107475214958919829931.03%13376.92%0771153250.33%656129450.70%517102050.69%129468311886021172573
2Americans11000000321110000003210000000000021.0003580070999318397367107475229103333100.00%40100.00%0771153250.33%656129450.70%517102050.69%129468311886021172573
3Bears402011001416-22020000057-22000110099030.375142539007099931812473671074752114395810620735.00%14657.14%1771153250.33%656129450.70%517102050.69%129468311886021172573
4Bills11000000514000000000001100000051421.0005101500709993182973671074752276433010220.00%40100.00%0771153250.33%656129450.70%517102050.69%129468311886021172573
5Blood Miners1010000035-2000000000001010000035-200.000358007099931841736710747522981121500.00%3166.67%0771153250.33%656129450.70%517102050.69%129468311886021172573
6Bulldogs220000001165110000007341100000043141.00011203100709993188073671074752552861539444.44%13376.92%1771153250.33%656129450.70%517102050.69%129468311886021172573
7Eagles10001000211000000000001000100021121.00023500709993182873671074752381312254125.00%60100.00%0771153250.33%656129450.70%517102050.69%129468311886021172573
8Griffins1010000058-31010000058-30000000000000.00058130070999318407367107475226153426400.00%7271.43%0771153250.33%656129450.70%517102050.69%129468311886021172573
9Grisards311010001715221100000131211000100043140.66717254200709993181217367107475211738956412325.00%21671.43%0771153250.33%656129450.70%517102050.69%129468311886021172573
10Gulls55000000271215220000001257330000001578101.00027447100709993181817367107475215966163124331236.36%24387.50%2771153250.33%656129450.70%517102050.69%129468311886021172573
11Moose3210000013103110000005322110000087140.6671322350070999318109736710747521043237796116.67%11281.82%0771153250.33%656129450.70%517102050.69%129468311886021172573
12Mountaineers1010000012-11010000012-10000000000000.000123007099931835736710747522451826400.00%40100.00%0771153250.33%656129450.70%517102050.69%129468311886021172573
13Octopus11000000523110000005230000000000021.00058130070999318397367107475236154725300.00%6266.67%0771153250.33%656129450.70%517102050.69%129468311886021172573
14Penguins5210011022202310001101211121100000109170.7002240620070999318173736710747521786113412323521.74%22863.64%0771153250.33%656129450.70%517102050.69%129468311886021172573
15Phantoms302000101011-1201000106601010000045-120.333101323007099931811573671074752117331048010440.00%17570.59%0771153250.33%656129450.70%517102050.69%129468311886021172573
16Rams320000011815300000000000320000011815350.83318314900709993181207367107475210230635921838.10%9455.56%0771153250.33%656129450.70%517102050.69%129468311886021172573
17Reign11000000633000000000001100000063321.00061218007099931836736710747521979218337.50%20100.00%0771153250.33%656129450.70%517102050.69%129468311886021172573
18Roadrunners1010000024-2000000000001010000024-200.00023510709993184573671074752361323205120.00%4175.00%0771153250.33%656129450.70%517102050.69%129468311886021172573
19Saints10000010651100000106510000000000021.00067130070999318307367107475233514258225.00%2150.00%0771153250.33%656129450.70%517102050.69%129468311886021172573
20Senators320000101376110000004222100001095461.000132033007099931891736710747529925437617423.53%14285.71%0771153250.33%656129450.70%517102050.69%129468311886021172573
21Silver Knights11000000514110000005140000000000021.00058130070999318357367107475230935215240.00%5180.00%0771153250.33%656129450.70%517102050.69%129468311886021172573
22Titans5310010025178210001001073321000001510570.7002540650070999318179736710747521514071113331030.30%21766.67%0771153250.33%656129450.70%517102050.69%129468311886021172573
23Whalers11000000312000000000001100000031221.000369007099931837736710747523256255240.00%30100.00%0771153250.33%656129450.70%517102050.69%129468311886021172573
24White Wolves21000010642100000103211100000032141.00061016007099931882736710747525823345410330.00%7271.43%0771153250.33%656129450.70%517102050.69%129468311886021172573
25Wolf Pack311000101312131100010131210000000000040.66713213401709993181297367107475276331125919842.11%16662.50%0771153250.33%656129450.70%517102050.69%129468311886021172573
26Wolves320000102013721000010121021100000083561.00020315100709993181247367107475294292517517529.41%18761.11%2771153250.33%656129450.70%517102050.69%129468311886021172573
Total603114033812732076630148002601351092630176031211389840880.73327344671911709993182215736710747521932646160214613219629.91%2707273.33%6771153250.33%656129450.70%517102050.69%129468311886021172573
_Since Last GM Reset603114033812732076630148002601351092630176031211389840880.73327344671911709993182215736710747521932646160214613219629.91%2707273.33%6771153250.33%656129450.70%517102050.69%129468311886021172573
_Vs Conference46241002361216165512311600240103861723134021211137934680.73921635056601709993181695736710747521521499126111142467831.71%2075971.50%5771153250.33%656129450.70%517102050.69%129468311886021172573
_Vs Division1215601331644618564002202422279201111402416421.75064105169007099931844373671074752377115467299701927.14%561573.21%2771153250.33%656129450.70%517102050.69%129468311886021172573

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6088W2273446719221519326461602146111
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6031143381273207
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
301480260135109
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
30176312113898
Derniers 10 matchs
WLOTWOTL SOWSOL
810001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3219629.91%2707273.33%6
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
7367107475270999318
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
771153250.33%656129450.70%517102050.69%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
129468311886021172573


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
856Admirals4Blossom Bytes5WSommaire du match
1071Blossom Bytes3Titans4LSommaire du match
1286Grisards7Blossom Bytes6LSommaire du match
1395Blossom Bytes8Gulls3WSommaire du match
15109Blossom Bytes5Bears6LXSommaire du match
17125Penguins5Blossom Bytes4LXSommaire du match
18134Blossom Bytes5Rams3WSommaire du match
21159Wolves3Blossom Bytes4WXXSommaire du match
23168Blossom Bytes4Gulls3WSommaire du match
26184Penguins4Blossom Bytes5WSommaire du match
29211Blossom Bytes4Bears3WXSommaire du match
31220Gulls3Blossom Bytes5WSommaire du match
35246Wolf Pack3Blossom Bytes4WXXSommaire du match
38267Americans2Blossom Bytes3WSommaire du match
40280Blossom Bytes4Grisards3WXSommaire du match
43303Wolves7Blossom Bytes8WSommaire du match
45313Blossom Bytes8Wolves3WSommaire du match
47325Blossom Bytes3Admirals2WXXSommaire du match
49339Senators2Blossom Bytes4WSommaire du match
51360Blossom Bytes3Whalers1WSommaire du match
53370Octopus2Blossom Bytes5WSommaire du match
56396Silver Knights1Blossom Bytes5WSommaire du match
57410Blossom Bytes4Bulldogs3WSommaire du match
60427White Wolves2Blossom Bytes3WXXSommaire du match
62445Blossom Bytes5Penguins3WSommaire du match
65461Admirals5Blossom Bytes3LSommaire du match
68478Blossom Bytes3White Wolves2WSommaire du match
70493Bears4Blossom Bytes3LSommaire du match
74519Titans5Blossom Bytes4LXSommaire du match
78549Mountaineers2Blossom Bytes1LSommaire du match
80567Blossom Bytes3Blood Miners5LSommaire du match
83582Bulldogs3Blossom Bytes7WSommaire du match
85601Blossom Bytes3Moose1WSommaire du match
87613Phantoms3Blossom Bytes4WXXSommaire du match
90635Blossom Bytes5Moose6LSommaire du match
91644Wolf Pack9Blossom Bytes5LSommaire du match
94667Blossom Bytes5Titans1WSommaire du match
95675Blossom Bytes3Gulls1WSommaire du match
97684Moose3Blossom Bytes5WSommaire du match
100707Saints5Blossom Bytes6WXXSommaire du match
102726Blossom Bytes4Phantoms5LSommaire du match
104740Phantoms3Blossom Bytes2LSommaire du match
106753Blossom Bytes2Roadrunners4LSommaire du match
108766Blossom Bytes5Penguins6LSommaire du match
110776Bears3Blossom Bytes2LSommaire du match
112793Blossom Bytes5Senators4WXXSommaire du match
114804Blossom Bytes6Reign3WSommaire du match
115816Gulls2Blossom Bytes7WSommaire du match
119842Blossom Bytes2Eagles1WXSommaire du match
120848Griffins8Blossom Bytes5LSommaire du match
122870Blossom Bytes5Bills1WSommaire du match
124878Grisards5Blossom Bytes7WSommaire du match
127906Titans2Blossom Bytes6WSommaire du match
129920Blossom Bytes7Titans5WSommaire du match
131937Blossom Bytes7Rams8LXXSommaire du match
132943Penguins2Blossom Bytes3WXXSommaire du match
136969Blossom Bytes6Rams4WSommaire du match
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 billets4020
Assistance53,99894,920
Assistance PCT72.00%57.53%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
11 4964 - 62.05% 178,990$5,369,712$8000110

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,337,509$ 2,668,981$ 2,668,981$ 600,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
17,388$ 2,337,509$ 29 2

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,968,894$ 52 17,388$ 904,176$




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