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

Blossom Bytes
GP: 30 | W: 25 | L: 3 | OTL: 2 | P: 52
GF: 138 | GA: 93 | PP%: 31.06% | PK%: 70.31%
GM : Gerd | Morale : 99 | Team Overall : N/A
Next Games #493 vs Bears

Game Center
Admirals
12-14-2, 26pts
5
FINAL
3 Blossom Bytes
25-3-2, 52pts
Team Stats
W1StreakW1
4-9-2Home Record12-2-1
8-5-0Home Record13-1-1
4-4-2Last 10 Games9-1-0
3.57Goals Per Game4.60
3.79Goals Against Per Game3.10
24.00%Power Play Percentage31.06%
68.35%Penalty Kill Percentage70.31%
Blossom Bytes
25-3-2, 52pts
3
FINAL
2 White Wolves
15-12-5, 35pts
Team Stats
W1StreakL1
12-2-1Home Record5-7-3
13-1-1Home Record10-5-2
9-1-0Last 10 Games5-3-2
4.60Goals Per Game3.72
3.10Goals Against Per Game3.22
31.06%Power Play Percentage28.48%
70.31%Penalty Kill Percentage74.51%
Bears
16-13-3, 35pts
Day 70
Blossom Bytes
25-3-2, 52pts
Team Stats
W3StreakW1
6-6-3Home Record12-2-1
10-7-0Away Record13-1-1
6-3-1Last 10 Games9-1-0
3.53Goals Per Game4.60
3.38Goals Against Per Game4.60
33.08%Power Play Percentage31.06%
74.31%Penalty Kill Percentage70.31%
Titans
13-17-2, 28pts
Day 74
Blossom Bytes
25-3-2, 52pts
Team Stats
SOL1StreakW1
6-7-2Home Record12-2-1
7-10-0Away Record13-1-1
3-6-1Last 10 Games9-1-0
3.28Goals Per Game4.60
3.50Goals Against Per Game4.60
26.28%Power Play Percentage31.06%
69.05%Penalty Kill Percentage70.31%
Mountaineers
18-9-4, 40pts
Day 78
Blossom Bytes
25-3-2, 52pts
Team Stats
W3StreakW1
10-4-1Home Record12-2-1
8-5-3Away Record13-1-1
6-4-0Last 10 Games9-1-0
3.68Goals Per Game4.60
3.52Goals Against Per Game4.60
30.77%Power Play Percentage31.06%
72.73%Penalty Kill Percentage70.31%
Team Leaders
Goals
Nikita Grebenkin
16
Assists
John Farinacci
24
Points
John Farinacci
38
Plus/Minus
Ilya Protas
13
Wins
Arvid Holm
18
Save Percentage
Arvid Holm
0.905

Team Stats
Goals For
138
4.60 GFG
Shots For
1141
38.03 Avg
Power Play Percentage
31.1%
50 GF
Offensive Zone Start
38.8%
Goals Against
93
3.10 GAA
Shots Against
971
32.37 Avg
Penalty Kill Percentage
70.3%%
38 GA
Defensive Zone Start
34.7%
Team Info

General ManagerGerd
CoachAdam Foote
DivisionAtlantic Division
ConferenceEastern Conference
Captain
Assistant #1
Assistant #2


Arena Info

Capacity8,000
Attendance4,623
Season Tickets800


Roster Info

Pro Team29
Farm Team22
Contract Limit51 / 65
Prospects14


Filter Tips
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
# Player Name C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPAgeContractSalary
1John FarinacciXXX100.00735094707477886383656273654961090002311,312,500$
2Julien GauthierXX100.00785093788577737361677171655863081002732,325,000$
3Noel GunlerXX100.00606060606070706060606060604358093002321,312,500$
4Martin ChromiakXX100.0060606060607070606060606060435809800222866,250$
5Jason PolinXX100.0060509367757583626162636765505909800252682,500$
6Nikita NesterenkoX100.0069508870747792696170697065415607900232682,500$
7Vinzenz RohrerXXX100.0060606060607070606060606060415608900201975,000$
8Hunter HaightXXX100.00606060606070706060606060604156091002011,250,000$
9Michael MilneXX100.0073508867707589626162637165415609200221825,000$
10Nikita GrebenkinXX100.0065508769797588656165646965405509601212650,000$
11Gracyn Sawchyn (R)X100.00606060606070706060606060604655098001931,250,000$
12Ilya Protas (R)XX100.0060606060607070606060606060425509100183975,000$
13Lukas CormierX100.00606060606070706060606060605361080002211,023,750$
14Sean BehrensX100.00606060606070706060606060604156097002111,250,000$
15Dylan AnhornX100.0060606060607070606060606060415608500252682,500$
16Cameron AllenX100.0060606060607070606060606060405508801192825,000$
17Ty Gallagher (R)X100.0060606060607070606060606060485509100212750,000$
18Ty Murchison (R)X100.0060606060607070606060606060485508700212700,000$
Scratches
1Jens LookeXX100.00606060606070706060606060606370078002711,783,180$
2Ryder KorczakX100.00606060606070706060606060604358072002221,023,750$
3Riley DuranXXX100.0073509362677989616861627365415609300221700,000$
4Justin RobidasX100.0062509471667893647165636765415608400211825,000$
5Dylan WendtXXX100.0060606060607070606060606060405507100231650,000$
6Tyrel BauerX100.0060606060607070606060606060425709300222787,500$
7Connor KelleyX100.0060606060607070606060606060405507601221650,000$
TEAM AVERAGE100.006357706364727562626161636245570880
Filter Tips
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
# Goalie Name CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SPAgeContractSalary
1Arvid Holm100.0060707060606060606060605664090002621,466,625$
2Hampton Slukynsky (R)100.006070706060606060606060425509700193750,000$
Scratches
1Isaiah Saville100.006070706060606060606060505908400241866,250$
2Harrison Meneghin (R)100.006070706060606060606060465508400203650,000$
TEAM AVERAGE100.00607070606060606060606049580890
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Adam Foote8076687961661CAN543600,000$


Filter Tips
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
# Player Name Team NamePOSGP 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/RW30142438132204051101396613.86%1159219.7441620141131234852058.32%5111713001.2812211421
2Nikita GrebenkinBlossom Bytes (SJS)LW/RW30161632-21154730107376114.95%1248516.191091928114000011148.48%33144001.3201010042
3Julien GauthierBlossom Bytes (SJS)LW/RW22121830517152128116395510.34%1037216.927101722830000114146.81%47217001.6122021222
4Michael MilneBlossom Bytes (SJS)LW/RW3082028-22915392164244212.50%1646215.43610161895000000154.55%33143001.2111030011
5Nikita NesterenkoBlossom Bytes (SJS)C21131225-1151526308895514.77%1337417.84581320790000140146.40%375115001.3311021310
6Riley DuranBlossom Bytes (SJS)C/LW/RW2913122593725374766215319.70%2045115.555278422134821154.84%155713011.1111122110
7Ilya ProtasBlossom Bytes (SJS)C/LW29111223138745652862133817.74%1251417.73471111108000006052.00%50109000.8900243111
8Jason PolinBlossom Bytes (SJS)LW/RW3010818113725243490374711.11%1447515.840000020210862029.17%48124000.7611104102
9Hunter HaightBlossom Bytes (SJS)C/LW/RW137111810181023144462015.91%620015.42156543000002137.50%1634001.8001101212
10Justin RobidasBlossom Bytes (SJS)C269817955183157183415.79%533412.880111140222551252.97%202197001.0203010212
11Lukas CormierBlossom Bytes (SJS)D1901414103020411924550%2341822.01022369022047000%0315000.6700130020
12Tyrel BauerBlossom Bytes (SJS)D284101412934555655618267.14%4172325.833144106000173010%01519000.3901225001
13Ty MurchisonBlossom Bytes (SJS)D2721214885556035381595.26%3561522.811451188000158100%01017000.4500425001
14Sean BehrensBlossom Bytes (SJS)D2921012697554229359135.71%2958920.3315610109000277000%0717000.4100434100
15Martin ChromiakBlossom Bytes (SJS)LW/RW293697291527133312259.09%62608.9800005000000150.00%643000.6912003002
16Cameron AllenBlossom Bytes (SJS)D3018910363034262312124.35%2349416.49112220000249000%049000.3600123000
17Gracyn SawchynBlossom Bytes (SJS)C282799352541334411224.55%1032911.7800000000000154.07%30735000.5500401020
18Noel GunlerBlossom Bytes (SJS)LW/RW23257316103312226199.09%72269.8310118000020080.00%533000.6200002001
19Dylan AnhornBlossom Bytes (SJS)D22077344302415239100%2241118.70044453000236000%0311000.3400312000
20Vinzenz RohrerBlossom Bytes (SJS)C/LW/RW10145953251523166116.25%214814.89000130001240046.11%16722000.6700212002
21Ty GallagherBlossom Bytes (SJS)D2112378430231922924.55%1134216.33123325000026010%0514000.1800222010
22Connor KelleyBlossom Bytes (SJS)D42021004141250.00%25413.640000000000100%013100.7300000100
23Jens LookeBlossom Bytes (SJS)LW/RW7101110104261416.67%1405.8200000000000075.00%801000.4900110001
24Ryder KorczakBlossom Bytes (SJS)C2000020000000%021.35000000000000100.00%10000000000000
Team Total or Average539134226360139902530743606114135763111.74%331892116.5550871371661187571229739211252.09%1964188188110.81816313342181921
Filter Tips
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
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Arvid HolmBlossom Bytes (SJS)2418220.9053.1212892167705408300.81316226220
2Ales StezkaSharks64000.9012.96345001717196100068011
3Hampton SlukynskyBlossom Bytes (SJS)43100.9052.8119200995450000215000
Team Total or Average3425320.9043.051827219397154940163029231


Filter Tips
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
Player Name Team NamePOS Age Birthday Country Rookie Weight Height No Trade Available For Trade Acquired By Last Trade Date Force Waivers Waiver Possible Contract Contract Signature Date Force UFA Emergency Recall Type Current Salary Salary RemainingSalary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Salary Cap Year 2Salary Cap Year 3Salary Cap Year 4Salary Cap Year 5Salary Cap Year 6Salary Cap Year 7Salary Cap Year 8Salary Cap Year 9Salary Cap Year 10No Trade Year 2No Trade Year 3No Trade Year 4No Trade Year 5No Trade Year 6No Trade Year 7No Trade Year 8No Trade Year 9No Trade Year 10Link
Arvid HolmBlossom Bytes (SJS)G261998-11-03SWENo214 Lbs6 ft4NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,466,625$936,144$146,662$93,614$No1,466,625$--------1,466,625$--------No--------
Cameron AllenBlossom Bytes (SJS)D192005-01-07CANNo194 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm825,000$526,596$82,500$52,660$No825,000$--------825,000$--------No--------
Connor KelleyBlossom Bytes (SJS)D222002-01-30USANo201 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm650,000$414,894$65,000$41,489$No---------------------------
Dylan AnhornBlossom Bytes (SJS)D251999-01-21CANNo190 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$435,638$68,250$43,564$No682,500$--------682,500$--------No--------
Dylan WendtBlossom Bytes (SJS)C/LW/RW232001-01-09USANo185 Lbs6 ft1NoNoFree AgentNoNo12025-06-11FalseFalsePro & Farm650,000$414,894$65,000$41,489$No---------------------------
Gracyn SawchynBlossom Bytes (SJS)C192005-01-19CANYes154 Lbs5 ft10NoNoProspectNoNo32025-08-21FalseFalsePro & Farm1,250,000$797,872$125,000$79,787$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$478,723$75,000$47,872$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Harrison MeneghinBlossom Bytes (SJS)G202004-09-13CANYes174 Lbs6 ft2NoNoDraftNoNo32025-08-21FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Hunter HaightBlossom Bytes (SJS)C/LW/RW202004-04-04CANNo180 Lbs6 ft7NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$797,872$125,000$79,787$No---------------------------
Ilya ProtasBlossom Bytes (SJS)C/LW182006-07-18BLRYes201 Lbs6 ft3NoNoDraftNoNo32025-08-21FalseFalsePro & Farm975,000$622,340$97,500$62,234$No975,000$975,000$-------975,000$975,000$-------NoNo-------
Isaiah SavilleBlossom Bytes (SJS)G242000-09-21USANo196 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm866,250$552,926$86,625$55,293$No---------------------------
Jason PolinBlossom Bytes (SJS)LW/RW251999-06-17USANo198 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$435,638$68,250$43,564$No682,500$--------682,500$--------No--------
Jens LookeBlossom Bytes (SJS)LW/RW271997-04-11SWENo185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,783,180$1,138,200$178,318$113,820$No---------------------------
John FarinacciBlossom Bytes (SJS)C/LW/RW232001-02-14USANo197 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,312,500$837,766$131,250$83,777$No---------------------------
Julien Gauthier (1 Way Contract)Blossom Bytes (SJS)LW/RW271997-10-15CANNo226 Lbs6 ft4NoNoN/ANoNo3FalseFalsePro & Farm2,325,000$1,475,000$2,325,000$1,475,000$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$526,596$82,500$52,660$No---------------------------
Lukas CormierBlossom Bytes (SJS)D222002-03-27CANNo185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,023,750$653,457$102,375$65,346$No---------------------------
Martin ChromiakBlossom Bytes (SJS)LW/RW222002-08-20SVKNo190 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm866,250$552,926$86,625$55,293$No866,250$--------866,250$--------No--------
Michael MilneBlossom Bytes (SJS)LW/RW222002-09-21CANNo185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm825,000$526,596$82,500$52,660$No---------------------------
Nikita GrebenkinBlossom Bytes (SJS)LW/RW212003-05-02RUSNo210 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm650,000$414,894$65,000$41,489$No650,000$--------650,000$--------No--------
Nikita NesterenkoBlossom Bytes (SJS)C232001-09-10USANo195 Lbs6 ft2NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$435,638$68,250$43,564$No682,500$--------682,500$--------No--------
Noel GunlerBlossom Bytes (SJS)LW/RW232001-10-07SWENo176 Lbs6 ft2NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,312,500$837,766$131,250$83,777$No1,312,500$--------1,312,500$--------No--------
Riley DuranBlossom Bytes (SJS)C/LW/RW222002-01-25USANo174 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm700,000$446,809$70,000$44,681$No---------------------------
Ryder KorczakBlossom Bytes (SJS)C222002-09-23CANNo172 Lbs5 ft11NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,023,750$653,457$102,375$65,346$No1,023,750$--------1,023,750$--------No--------
Sean BehrensBlossom Bytes (SJS)D212003-03-31USANo177 Lbs6 ft8NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$797,872$125,000$79,787$No---------------------------
Ty GallagherBlossom Bytes (SJS)D212003-03-06USAYes196 Lbs5 ft10NoNoProspectNoNo22025-08-21FalseFalsePro & Farm750,000$478,723$75,000$47,872$No750,000$--------750,000$--------No--------
Ty MurchisonBlossom Bytes (SJS)D212003-02-02USAYes205 Lbs6 ft0NoNoProspectNoNo22025-08-21FalseFalsePro & Farm700,000$446,809$70,000$44,681$No700,000$--------700,000$--------No--------
Tyrel BauerBlossom Bytes (SJS)D222002-05-23CANNo207 Lbs6 ft3NoNoN/ANoNo22025-09-08FalseFalsePro & Farm787,500$502,660$78,750$50,266$No787,500$--------787,500$--------No--------
Vinzenz RohrerBlossom Bytes (SJS)C/LW/RW202004-09-09AUTNo178 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm975,000$622,340$97,500$62,234$No---------------------------
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2922.07190 Lbs6 ft11.76982,407$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Ilya ProtasVinzenz RohrerHunter Haight28122
2Nikita GrebenkinNikita NesterenkoMichael Milne28122
3Julien GauthierGracyn SawchynJason Polin25122
4Noel GunlerJohn FarinacciMartin Chromiak19122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty GallagherDylan Anhorn28122
2Ty MurchisonSean Behrens28122
3Lukas CormierCameron Allen25122
4Ty MurchisonDylan Anhorn19122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Ilya ProtasNikita NesterenkoHunter Haight50122
2Nikita GrebenkinJohn FarinacciJulien Gauthier50122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Lukas CormierTy Murchison50122
2Ty GallagherSean Behrens50122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Vinzenz RohrerJason Polin50122
2Nikita NesterenkoJohn Farinacci50122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty GallagherDylan Anhorn50122
2Lukas CormierSean Behrens50122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Nikita Grebenkin50122Ty GallagherTy Murchison50122
2Ilya Protas50122Cameron AllenSean Behrens50122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Gracyn SawchynHunter Haight50122
2Vinzenz RohrerJohn Farinacci50122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Lukas CormierTy Murchison50122
2Ty GallagherSean Behrens50122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Gracyn SawchynHunter HaightJulien GauthierLukas CormierDylan Anhorn
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Ilya ProtasGracyn SawchynMartin ChromiakSean BehrensTy Gallagher
Extra Forwards
Normal PowerPlayPenalty Kill
Ilya Protas, Jason Polin, Julien GauthierIlya Protas, Hunter HaightJulien Gauthier
Extra Defensemen
Normal PowerPlayPenalty Kill
Lukas Cormier, Cameron Allen, Ty MurchisonLukas CormierCameron Allen, Ty Murchison
Penalty Shots
Julien Gauthier, Martin Chromiak, Hunter Haight, John Farinacci, Nikita Grebenkin
Goalie
#1 : Hampton Slukynsky, #2 : Arvid Holm


Filter Tips
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
OverallHomeVisitor
# VS Team 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
1Admirals42100010181442110000089-121000010105560.75018274500324951101533543713993214958919829931.03%13376.92%039876252.23%35268151.69%27352152.40%648342597301583284
2Americans11000000321110000003210000000000021.0003580032495110393543713993229103333100.00%40100.00%039876252.23%35268151.69%27352152.40%648342597301583284
3Bears20001100990000000000002000110099030.7509172600324951106135437139932621941538337.50%8537.50%139876252.23%35268151.69%27352152.40%648342597301583284
4Bulldogs11000000431000000000001100000043121.000481200324951104735437139932291828354125.00%4325.00%039876252.23%35268151.69%27352152.40%648342597301583284
5Grisards20101000101001010000067-11000100043120.50010142400324951108235437139932751963429222.22%10370.00%039876252.23%35268151.69%27352152.40%648342597301583284
6Gulls3300000017981100000053222000000126661.000172744003249511010535437139932102369379201050.00%14378.57%239876252.23%35268151.69%27352152.40%648342597301583284
7Octopus11000000523110000005230000000000021.00058130032495110393543713993236154725300.00%6266.67%039876252.23%35268151.69%27352152.40%648342597301583284
8Penguins3200010014122210001009901100000053250.83314264000324951101063543713993210639717716212.50%13561.54%039876252.23%35268151.69%27352152.40%648342597301583284
9Rams11000000532000000000001100000053221.000581300324951105135437139932271021228450.00%3233.33%039876252.23%35268151.69%27352152.40%648342597301583284
10Senators22000000835110000004221100000041341.00081321003249511056354371399326715334813215.38%9188.89%039876252.23%35268151.69%27352152.40%648342597301583284
11Silver Knights11000000514110000005140000000000021.00058130032495110353543713993230935215240.00%5180.00%039876252.23%35268151.69%27352152.40%648342597301583284
12Titans1010000034-1000000000001010000034-100.000358003249511035354371399323088213133.33%4175.00%039876252.23%35268151.69%27352152.40%648342597301583284
13Whalers11000000312000000000001100000031221.000369003249511037354371399323256255240.00%30100.00%039876252.23%35268151.69%27352152.40%648342597301583284
14White Wolves21000010642100000103211100000032141.00061016003249511082354371399325823345410330.00%7271.43%039876252.23%35268151.69%27352152.40%648342597301583284
15Wolf Pack21000010835210000108350000000000041.00081321013249511089354371399324518493510440.00%70100.00%039876252.23%35268151.69%27352152.40%648342597301583284
16Wolves320000102013721000010121021100000083561.00020315100324951101243543713993294292517517529.41%18761.11%239876252.23%35268151.69%27352152.40%648342597301583284
Total301930224013893451592001306850181510102110704327520.86713822636401324951101141354371399329713319047431615031.06%1283870.31%539876252.23%35268151.69%27352152.40%648342597301583284
_Since Last GM Reset301930224013893451592001306850181510102110704327520.86713822636401324951101141354371399329713319047431615031.06%1283870.31%539876252.23%35268151.69%27352152.40%648342597301583284
_Vs Conference25153022301188335127200120554510138102110633825420.8401181923100132495110938354371399328182667606081394431.65%1063071.70%539876252.23%35268151.69%27352152.40%648342597301583284
_Vs Division7920122036211544100110191453510111017710261.85736579300324951102703543713993221764338178391128.21%341070.59%239876252.23%35268151.69%27352152.40%648342597301583284

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
3052W1138226364114197133190474301
All Games
GPWLOTWOTL SOWSOLGFGA
30193224013893
Home Games
GPWLOTWOTL SOWSOLGFGA
159201306850
Visitor Games
GPWLOTWOTL SOWSOLGFGA
1510121107043
Last 10 Games
WLOTWOTL SOWSOL
910000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1615031.06%1283870.31%5
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
3543713993232495110
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
39876252.23%35268151.69%27352152.40%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
648342597301583284


Last Played Games
Filter Tips
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
DayGame Visitor Team Score Home Team Score ST OT SO RI Link
12Blossom Bytes7Admirals3WBoxScore
430Wolf Pack0Blossom Bytes4WBoxScore
536Blossom Bytes4Senators1WBoxScore
856Admirals4Blossom Bytes5WBoxScore
1071Blossom Bytes3Titans4LBoxScore
1286Grisards7Blossom Bytes6LBoxScore
1395Blossom Bytes8Gulls3WBoxScore
15109Blossom Bytes5Bears6LXBoxScore
17125Penguins5Blossom Bytes4LXBoxScore
18134Blossom Bytes5Rams3WBoxScore
21159Wolves3Blossom Bytes4WXXBoxScore
23168Blossom Bytes4Gulls3WBoxScore
26184Penguins4Blossom Bytes5WBoxScore
29211Blossom Bytes4Bears3WXBoxScore
31220Gulls3Blossom Bytes5WBoxScore
35246Wolf Pack3Blossom Bytes4WXXBoxScore
38267Americans2Blossom Bytes3WBoxScore
40280Blossom Bytes4Grisards3WXBoxScore
43303Wolves7Blossom Bytes8WBoxScore
45313Blossom Bytes8Wolves3WBoxScore
47325Blossom Bytes3Admirals2WXXBoxScore
49339Senators2Blossom Bytes4WBoxScore
51360Blossom Bytes3Whalers1WBoxScore
53370Octopus2Blossom Bytes5WBoxScore
56396Silver Knights1Blossom Bytes5WBoxScore
57410Blossom Bytes4Bulldogs3WBoxScore
60427White Wolves2Blossom Bytes3WXXBoxScore
62445Blossom Bytes5Penguins3WBoxScore
65461Admirals5Blossom Bytes3LBoxScore
68478Blossom Bytes3White Wolves2WBoxScore
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-
Trade Deadline --- Trades can’t be done after this day is simulated!
1691214Blossom Bytes-Americans-
1721227Blossom Bytes-Norsemen-
1741238Whalers-Blossom Bytes-
1781261Rams-Blossom Bytes-
1811280Blossom Bytes-Wolf Pack-
1831292Blossom Bytes-Norsemen-
1861306Rams-Blossom Bytes-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity25005500
Ticket Price4525
Attendance25,97043,379
Attendance PCT69.25%52.58%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
26 4623 - 57.79% 180,250$2,703,750$8000110

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Salaries CapCoaches Salaries
1,157,032$ 2,616,481$ 2,616,481$ 600,000$0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
17,109$ 1,157,032$ 28 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
4,686,500$ 120 17,109$ 2,053,080$




Blossom Bytes Players Stat Leaders (Regular Season)

# Player Name 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 Goalies Stat Leaders (Regular Season)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Blossom Bytes Career Team Stats

OverallHomeVisitor
Year 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 Players Stat Leaders (Play-Off)

# Player Name 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 Goalies Stat Leaders (Play-Off)

# Goalie Name GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA