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Blossom Bytes
GP: 62 | W: 44 | L: 14 | OTL: 4 | P: 92
GF: 283 | GA: 211 | PP%: 30.09% | PK%: 73.29%
GM : Gerd | Morale : 99 | Team Overall : N/A
Next Games #1014 vs Crunch

Game Center
Rocket
25-34-5, 55pts
3
FINAL
4 Blossom Bytes
44-14-4, 92pts
Team Stats
L1StreakW4
10-19-2Home Record22-8-2
15-15-3Home Record22-6-2
6-4-0Last 10 Games8-1-1
3.17Goals Per Game4.56
3.97Goals Against Per Game3.40
26.72%Power Play Percentage30.09%
69.09%Penalty Kill Percentage73.29%
Gorillas
26-32-8, 60pts
1
FINAL
6 Blossom Bytes
44-14-4, 92pts
Team Stats
L1StreakW4
14-13-4Home Record22-8-2
12-19-4Home Record22-6-2
5-4-1Last 10 Games8-1-1
3.17Goals Per Game4.56
3.82Goals Against Per Game3.40
25.27%Power Play Percentage30.09%
71.13%Penalty Kill Percentage73.29%
Blossom Bytes
44-14-4, 92pts
Day 142
Crunch
31-24-8, 70pts
Team Stats
W4StreakW1
22-8-2Home Record18-8-5
22-6-2Away Record13-16-3
8-1-1Last 10 Games4-5-1
4.56Goals Per Game3.40
3.40Goals Against Per Game3.40
30.09%Power Play Percentage33.83%
73.29%Penalty Kill Percentage73.66%
Blossom Bytes
44-14-4, 92pts
Day 143
Bears
31-29-7, 69pts
Team Stats
W4StreakL1
22-8-2Home Record14-13-4
22-6-2Away Record17-16-3
8-1-1Last 10 Games4-5-1
4.56Goals Per Game3.25
3.40Goals Against Per Game3.25
30.09%Power Play Percentage28.57%
73.29%Penalty Kill Percentage71.23%
Norsemen
33-21-9, 75pts
Day 145
Blossom Bytes
44-14-4, 92pts
Team Stats
W1StreakW4
16-11-4Home Record22-8-2
17-10-5Away Record22-6-2
5-4-1Last 10 Games8-1-1
3.89Goals Per Game4.56
3.59Goals Against Per Game4.56
29.21%Power Play Percentage30.09%
71.14%Penalty Kill Percentage73.29%
Team Leaders
Goals
Julien Gauthier
41
Assists
John Farinacci
52
Points
Julien Gauthier
84
Plus/Minus
Tyrel Bauer
23
Wins
Arvid Holm
25
Save Percentage
Isaiah Saville
0.96

Team Stats
Goals For
283
4.56 GFG
Shots For
2289
36.92 Avg
Power Play Percentage
30.1%
99 GF
Offensive Zone Start
39.7%
Goals Against
211
3.40 GAA
Shots Against
1986
32.03 Avg
Penalty Kill Percentage
73.3%%
74 GA
Defensive Zone Start
33.9%
Team Info

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


Arena Info

Capacity8,000
Attendance4,996
Season Tickets800


Roster Info

Pro Team32
Farm Team22
Contract Limit54 / 65
Prospects14


Filter Tips
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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 FarinacciXXX99.00735094707477886383656273654961090002311,312,500$
2Julien GauthierXX99.00785093788577737361677171655863087002732,325,000$
3Jens LookeXX100.00606060606070706060606060606370089002711,783,180$
4Martin ChromiakXX100.0060606060607070606060606060435809000222866,250$
5Jason PolinXX100.0060509367757583626162636765505909100252682,500$
6Nikita NesterenkoX100.0069508870747792696170697065415608800232682,500$
7Vinzenz RohrerXXX100.0060606060607070606060606060415605900201975,000$
8Hunter HaightXXX100.00606060606070706060606060604156069002011,250,000$
9Michael MilneXX100.0073508867707589626162637165415609100221825,000$
10Nikita GrebenkinXX100.0065508769797588656165646965405509001212650,000$
11Gracyn Sawchyn (R)X100.00606060606070706060606060604655088001931,250,000$
12Ilya Protas (R)XX100.0060606060607070606060606060425508900183975,000$
13Lukas CormierX98.00606060606070706060606060605361079002211,023,750$
14Tyrel BauerX100.0060606060607070606060606060425708700222787,500$
15Sean BehrensX100.00606060606070706060606060604156083002111,250,000$
16Connor KelleyX99.0060606060607070606060606060405508601221650,000$
17Cameron AllenX100.0060606060607070606060606060405509101192825,000$
18Ty Murchison (R)X100.0060606060607070606060606060485506800212700,000$
Scratches
1Alex GaffneyX100.0060606060607070606060606060485909600223700,000$
2Noel GunlerXX100.00606060606070706060606060604358062002321,312,500$
3Ryder KorczakX100.00606060606070706060606060604358040002221,023,750$
4Riley DuranXXX100.0073509362677989616861627365415608700221700,000$
5Justin RobidasX100.0062509471667893647165636765415607500211825,000$
6Dylan WendtXXX100.0060606060607070606060606060405503900231650,000$
7Mack OliphantX100.0060606060607070606060606060465809600223650,000$
8Dylan AnhornX98.8160606060607070606060606060415608100252682,500$
9Ty Gallagher (R)X100.0060606060607070606060606060485505400212750,000$
TEAM AVERAGE99.706357696364727561626161636145570790
Filter Tips
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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 Holm100.0060707060606060606060605664059002621,466,625$
2Hampton Slukynsky (R)100.006070706060606060606060425508300193750,000$
Scratches
1Ales Stezka56.126070706060606060606060556605800275727,650$
2Isaiah Saville100.006070706060606060606060505907000241866,250$
3Harrison Meneghin (R)92.826070706060606060606060465508100203650,000$
TEAM AVERAGE89.60607070606060606060606050600700
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
1Julien GauthierBlossom Bytes (SJS)LW/RW544143848343078702568313216.02%2387316.18212344632000000196346.32%955322041.9237141785
2John FarinacciBlossom Bytes (SJS)C/LW/RW622752798392570981877313014.44%21112518.151033433223012371873158.24%7713720001.4023212722
3Nikita NesterenkoBlossom Bytes (SJS)C53283664-3202071742124612713.21%2999018.701118294219310161110146.44%10122612001.2911022453
4Nikita GrebenkinBlossom Bytes (SJS)LW/RW62332760-1352584582107412915.71%1799015.9716173342227000014345.00%603512011.2101230345
5Ilya ProtasBlossom Bytes (SJS)C/LW60222446161417512554117286518.80%24103017.179122124217000007048.96%962420100.8900348131
6Michael MilneBlossom Bytes (SJS)LW/RW62172643-351357142128529813.28%2885313.77610161895000001241.07%56237001.0125241112
7Jason PolinBlossom Bytes (SJS)LW/RW621919381759454855159559511.95%3097615.7510126202201843041.46%822214000.7811324112
8Justin RobidasBlossom Bytes (SJS)C5312243693715366113444728.96%1667512.750113150222561353.52%5404310001.0703012225
9Riley DuranBlossom Bytes (SJS)C/LW/RW541718351859355973115327814.78%2775513.9953884421381641154.20%2621115010.9311223111
10Martin ChromiakBlossom Bytes (SJS)LW/RW61122234872408638101296411.88%1575712.41481218104000002142.11%381715000.9057206052
11Sean BehrensBlossom Bytes (SJS)D60422262017595100636617326.06%63121920.323811162170113167000%01429000.4300658101
12Tyrel BauerBlossom Bytes (SJS)D5352025231185089908728395.75%67124623.52426101930001149010%02028000.4001235001
13Gracyn SawchynBlossom Bytes (SJS)C596182410684076627228448.33%2569711.8310110000013149.77%643414000.6900422020
14Lukas CormierBlossom Bytes (SJS)D44021210825080525013130%4296321.89099111600222119000%0825000.4400352020
15Hunter HaightBlossom Bytes (SJS)C/LW/RW20101121112915352163123115.87%630315.17156559000092137.21%4357001.3801201212
16Cameron AllenBlossom Bytes (SJS)D625162110794582576024258.33%49108217.46369121230002103000%0919000.3900324100
17Ty MurchisonBlossom Bytes (SJS)D4121820111167077455225143.85%4691822.4116712141000196100%01723000.4400446001
18Dylan AnhornBlossom Bytes (SJS)D541171801388077516325231.59%67110420.451455650003118000%0824000.3300628000
19Jens LookeBlossom Bytes (SJS)LW/RW356713112820421444132213.64%43078.7901105000041061.54%13710000.8500211001
20Connor KelleyBlossom Bytes (SJS)D3237107864045393616208.33%3558818.390001700008100%079100.3400215111
21Noel GunlerBlossom Bytes (SJS)LW/RW28268220103717269227.69%72699.6210118000030080.00%553000.5900002001
22Vinzenz RohrerBlossom Bytes (SJS)C/LW/RW15257755252134258138.00%422615.11000140001360046.50%24343000.6200212002
23Ty GallagherBlossom Bytes (SJS)D251236101352625241134.17%1240816.35123439000032010%0515000.1500222010
24Mack OliphantBlossom Bytes (SJS)D1011100002000%21717.180000000000000%000001.1600000000
25Alex GaffneyBlossom Bytes (SJS)C1000000100000%011.63000000000000100.00%10000000000000
26Ryder KorczakBlossom Bytes (SJS)C2000020000000%021.35000000000000100.00%10000000000000
Team Total or Average11152754627371961644920151611932289745129112.01%6591838716.499916826733123626814561580361950.59%3961404356260.801531555177323938
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)3425230.8973.3017812198948559400.818223211320
2Ales StezkaBlossom Bytes (SJS)2011600.8983.4811200065639380310.7147208221
3Hampton SlukynskyBlossom Bytes (SJS)116410.8863.425960034297173101.0002816100
4Isaiah SavilleBlossom Bytes (SJS)11000.9601.00600012513100010000
5Harrison MeneghinBlossom Bytes (SJS)81200.8553.16209001176420000127000
Team Total or Average74441440.8953.333768212091985116791316262641


Filter Tips
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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
Ales Stezka (Out of Payroll)Blossom Bytes (SJS)G271997-01-06CZENo190 Lbs6 ft4NoNoN/ANoNo5FalseFalsePro & Farm727,650$185,783$72,765$18,578$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$178,723$70,000$17,872$No700,000$700,000$-------700,000$700,000$-------NoNo-------
Arvid HolmBlossom Bytes (SJS)G261998-11-03SWENo214 Lbs6 ft4NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,466,625$374,457$146,662$37,446$No1,466,625$--------1,466,625$--------No--------
Cameron AllenBlossom Bytes (SJS)D192005-01-07CANNo194 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm825,000$210,638$82,500$21,064$No825,000$--------825,000$--------No--------
Connor KelleyBlossom Bytes (SJS)D222002-01-30USANo201 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm650,000$165,957$65,000$16,596$No---------------------------
Dylan AnhornBlossom Bytes (SJS)D251999-01-21CANNo190 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$174,255$68,250$17,426$No682,500$--------682,500$--------No--------
Dylan WendtBlossom Bytes (SJS)C/LW/RW232001-01-09USANo185 Lbs6 ft1NoNoFree AgentNoNo12025-06-11FalseFalsePro & Farm650,000$165,957$65,000$16,596$No---------------------------
Gracyn SawchynBlossom Bytes (SJS)C192005-01-19CANYes154 Lbs5 ft10NoNoProspectNoNo32025-08-21FalseFalsePro & Farm1,250,000$319,149$125,000$31,915$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$191,489$75,000$19,149$No750,000$750,000$-------750,000$750,000$-------NoNo-------
Harrison Meneghin (Out of Payroll)Blossom Bytes (SJS)G202004-09-13CANYes174 Lbs6 ft2NoNoDraftNoNo32025-08-21FalseFalsePro & Farm650,000$165,957$65,000$16,596$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Hunter HaightBlossom Bytes (SJS)C/LW/RW202004-04-04CANNo180 Lbs6 ft7NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$319,149$125,000$31,915$No---------------------------
Ilya ProtasBlossom Bytes (SJS)C/LW182006-07-18BLRYes201 Lbs6 ft3NoNoDraftNoNo32025-08-21FalseFalsePro & Farm975,000$248,936$97,500$24,894$No975,000$975,000$-------975,000$975,000$-------NoNo-------
Isaiah SavilleBlossom Bytes (SJS)G242000-09-21USANo196 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm866,250$221,170$86,625$22,117$No---------------------------
Jason PolinBlossom Bytes (SJS)LW/RW251999-06-17USANo198 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$174,255$68,250$17,426$No682,500$--------682,500$--------No--------
Jens LookeBlossom Bytes (SJS)LW/RW271997-04-11SWENo185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm1,783,180$455,280$178,318$45,528$No---------------------------
John FarinacciBlossom Bytes (SJS)C/LW/RW232001-02-14USANo197 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,312,500$335,106$131,250$33,511$No---------------------------
Julien Gauthier (1 Way Contract)Blossom Bytes (SJS)LW/RW271997-10-15CANNo226 Lbs6 ft4NoNoN/ANoNo3FalseFalsePro & Farm2,325,000$575,000$2,325,000$575,000$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$210,638$82,500$21,064$No---------------------------
Lukas CormierBlossom Bytes (SJS)D222002-03-27CANNo185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,023,750$261,383$102,375$26,138$No---------------------------
Mack OliphantBlossom Bytes (SJS)D222002-12-28USANo205 Lbs6 ft1NoNoAssign ManuallyNoNo32026-03-29FalseFalsePro & Farm650,000$165,957$65,000$16,596$No650,000$650,000$-------650,000$650,000$-------NoNo-------
Martin ChromiakBlossom Bytes (SJS)LW/RW222002-08-20SVKNo190 Lbs6 ft0NoNoN/ANoNo22025-09-08FalseFalsePro & Farm866,250$221,170$86,625$22,117$No866,250$--------866,250$--------No--------
Michael MilneBlossom Bytes (SJS)LW/RW222002-09-21CANNo185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm825,000$210,638$82,500$21,064$No---------------------------
Nikita GrebenkinBlossom Bytes (SJS)LW/RW212003-05-02RUSNo210 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm650,000$165,957$65,000$16,596$No650,000$--------650,000$--------No--------
Nikita NesterenkoBlossom Bytes (SJS)C232001-09-10USANo195 Lbs6 ft2NoNoN/ANoNo22025-09-08FalseFalsePro & Farm682,500$174,255$68,250$17,426$No682,500$--------682,500$--------No--------
Noel GunlerBlossom Bytes (SJS)LW/RW232001-10-07SWENo176 Lbs6 ft2NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,312,500$335,106$131,250$33,511$No1,312,500$--------1,312,500$--------No--------
Riley DuranBlossom Bytes (SJS)C/LW/RW222002-01-25USANo174 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm700,000$178,723$70,000$17,872$No---------------------------
Ryder KorczakBlossom Bytes (SJS)C222002-09-23CANNo172 Lbs5 ft11NoNoN/ANoNo22025-09-08FalseFalsePro & Farm1,023,750$261,383$102,375$26,138$No1,023,750$--------1,023,750$--------No--------
Sean BehrensBlossom Bytes (SJS)D212003-03-31USANo177 Lbs6 ft8NoNoN/ANoNo1FalseFalsePro & Farm1,250,000$319,149$125,000$31,915$No---------------------------
Ty GallagherBlossom Bytes (SJS)D212003-03-06USAYes196 Lbs5 ft10NoNoProspectNoNo22025-08-21FalseFalsePro & Farm750,000$191,489$75,000$19,149$No750,000$--------750,000$--------No--------
Ty MurchisonBlossom Bytes (SJS)D212003-02-02USAYes205 Lbs6 ft0NoNoProspectNoNo22025-08-21FalseFalsePro & Farm700,000$178,723$70,000$17,872$No700,000$--------700,000$--------No--------
Tyrel BauerBlossom Bytes (SJS)D222002-05-23CANNo207 Lbs6 ft3NoNoN/ANoNo22025-09-08FalseFalsePro & Farm787,500$201,064$78,750$20,106$No787,500$--------787,500$--------No--------
Vinzenz RohrerBlossom Bytes (SJS)C/LW/RW202004-09-09AUTNo178 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm975,000$248,936$97,500$24,894$No---------------------------
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3222.22190 Lbs6 ft11.94955,233$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Ilya ProtasNikita NesterenkoMichael Milne28122
2Nikita GrebenkinVinzenz RohrerMartin Chromiak28122
3Julien GauthierGracyn SawchynJason Polin25122
4John FarinacciHunter HaightJens Looke19122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Connor KelleyTyrel Bauer28122
2Lukas CormierSean Behrens28122
3Ty MurchisonCameron Allen25122
4Connor KelleySean Behrens19122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Ilya ProtasNikita NesterenkoMartin Chromiak50122
2Nikita GrebenkinGracyn SawchynJulien Gauthier50122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty MurchisonCameron Allen50122
2Lukas CormierSean Behrens50122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Hunter HaightJason Polin50122
2Nikita NesterenkoJohn Farinacci50122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Lukas CormierTyrel Bauer50122
2Ty MurchisonSean Behrens50122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Nikita Nesterenko50122Ty MurchisonLukas Cormier50122
2Julien Gauthier50122Cameron AllenSean Behrens50122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1John FarinacciMartin Chromiak50122
2Vinzenz RohrerJulien Gauthier50122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Cameron AllenTy Murchison50122
2Tyrel BauerSean Behrens50122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Gracyn SawchynNikita NesterenkoJulien GauthierTy MurchisonTyrel Bauer
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Ilya ProtasGracyn SawchynMartin ChromiakSean BehrensConnor Kelley
Extra Forwards
Normal PowerPlayPenalty Kill
Ilya Protas, Jason Polin, Julien GauthierIlya Protas, Martin ChromiakJulien Gauthier
Extra Defensemen
Normal PowerPlayPenalty Kill
Ty Murchison, Cameron Allen, Lukas CormierSean BehrensCameron Allen, Lukas Cormier
Penalty Shots
Julien Gauthier, Martin Chromiak, Michael Milne, John Farinacci, Nikita Grebenkin
Goalie
#1 : Arvid Holm, #2 : Hampton Slukynsky, #3 : 0


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
1Admirals42100010181442110000089-121000010105560.7501827450070102100181537557317815214958919829931.03%13376.92%0794157450.44%679134150.63%531104650.76%133870612236211214594
2Americans11000000321110000003210000000000021.000358007010210018397557317815229103333100.00%40100.00%0794157450.44%679134150.63%531104650.76%133870612236211214594
3Bears402011001416-22020000057-22000110099030.37514253900701021001812475573178152114395810620735.00%14657.14%1794157450.44%679134150.63%531104650.76%133870612236211214594
4Bills11000000514000000000001100000051421.000510150070102100182975573178152276433010220.00%40100.00%0794157450.44%679134150.63%531104650.76%133870612236211214594
5Blood Miners1010000035-2000000000001010000035-200.00035800701021001841755731781522981121500.00%3166.67%0794157450.44%679134150.63%531104650.76%133870612236211214594
6Bulldogs220000001165110000007341100000043141.0001120310070102100188075573178152552861539444.44%13376.92%1794157450.44%679134150.63%531104650.76%133870612236211214594
7Eagles10001000211000000000001000100021121.0002350070102100182875573178152381312254125.00%60100.00%0794157450.44%679134150.63%531104650.76%133870612236211214594
8Gorillas11000000615110000006150000000000021.00061016007010210018367557317815225322214125.00%110.00%0794157450.44%679134150.63%531104650.76%133870612236211214594
9Griffins1010000058-31010000058-30000000000000.0005813007010210018407557317815226153426400.00%7271.43%0794157450.44%679134150.63%531104650.76%133870612236211214594
10Grisards311010001715221100000131211000100043140.6671725420070102100181217557317815211738956412325.00%21671.43%0794157450.44%679134150.63%531104650.76%133870612236211214594
11Gulls55000000271215220000001257330000001578101.0002744710070102100181817557317815215966163124331236.36%24387.50%2794157450.44%679134150.63%531104650.76%133870612236211214594
12Moose3210000013103110000005322110000087140.667132235007010210018109755731781521043237796116.67%11281.82%0794157450.44%679134150.63%531104650.76%133870612236211214594
13Mountaineers1010000012-11010000012-10000000000000.00012300701021001835755731781522451826400.00%40100.00%0794157450.44%679134150.63%531104650.76%133870612236211214594
14Octopus11000000523110000005230000000000021.0005813007010210018397557317815236154725300.00%6266.67%0794157450.44%679134150.63%531104650.76%133870612236211214594
15Penguins5210011022202310001101211121100000109170.700224062007010210018173755731781521786113412323521.74%22863.64%0794157450.44%679134150.63%531104650.76%133870612236211214594
16Phantoms302000101011-1201000106601010000045-120.33310132300701021001811575573178152117331048010440.00%17570.59%0794157450.44%679134150.63%531104650.76%133870612236211214594
17Rams320000011815300000000000320000011815350.8331831490070102100181207557317815210230635921838.10%9455.56%0794157450.44%679134150.63%531104650.76%133870612236211214594
18Reign11000000633000000000001100000063321.0006121800701021001836755731781521979218337.50%20100.00%0794157450.44%679134150.63%531104650.76%133870612236211214594
19Roadrunners1010000024-2000000000001010000024-200.0002351070102100184575573178152361323205120.00%4175.00%0794157450.44%679134150.63%531104650.76%133870612236211214594
20Rocket11000000431110000004310000000000021.00046100070102100183875573178152291022344250.00%6183.33%0794157450.44%679134150.63%531104650.76%133870612236211214594
21Saints10000010651100000106510000000000021.0006713007010210018307557317815233514258225.00%2150.00%0794157450.44%679134150.63%531104650.76%133870612236211214594
22Senators320000101376110000004222100001095461.00013203300701021001891755731781529925437617423.53%14285.71%0794157450.44%679134150.63%531104650.76%133870612236211214594
23Silver Knights11000000514110000005140000000000021.0005813007010210018357557317815230935215240.00%5180.00%0794157450.44%679134150.63%531104650.76%133870612236211214594
24Titans5310010025178210001001073321000001510570.700254065007010210018179755731781521514071113331030.30%21766.67%0794157450.44%679134150.63%531104650.76%133870612236211214594
25Whalers11000000312000000000001100000031221.00036900701021001837755731781523256255240.00%30100.00%0794157450.44%679134150.63%531104650.76%133870612236211214594
26White Wolves21000010642100000103211100000032141.0006101600701021001882755731781525823345410330.00%7271.43%0794157450.44%679134150.63%531104650.76%133870612236211214594
27Wolf Pack311000101312131100010131210000000000040.6671321340170102100181297557317815276331125919842.11%16662.50%0794157450.44%679134150.63%531104650.76%133870612236211214594
28Wolves320000102013721000010121021100000083561.0002031510070102100181247557317815294292517517529.41%18761.11%2794157450.44%679134150.63%531104650.76%133870612236211214594
Total623314033812832117232168002601451133230176031211389840920.7422834627451170102100182289755731781521986659164615163299930.09%2777473.29%6794157450.44%679134150.63%531104650.76%133870612236211214594
_Since Last GM Reset623314033812832117232168002601451133230176031211389840920.7422834627451170102100182289755731781521986659164615163299930.09%2777473.29%6794157450.44%679134150.63%531104650.76%133870612236211214594
_Vs Conference46241002361216165512311600240103861723134021211137934680.7392163505660170102100181695755731781521521499126111142467831.71%2075971.50%5794157450.44%679134150.63%531104650.76%133870612236211214594
_Vs Division1315601331684919664002202825379201111402416421.6156811117900701021001848175573178152406125489333742128.38%621674.19%2794157450.44%679134150.63%531104650.76%133870612236211214594

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
6292W4283462745228919866591646151611
All Games
GPWLOTWOTL SOWSOLGFGA
6233143381283211
Home Games
GPWLOTWOTL SOWSOLGFGA
321680260145113
Visitor Games
GPWLOTWOTL SOWSOLGFGA
30176312113898
Last 10 Games
WLOTWOTL SOWSOL
810001
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
3299930.09%2777473.29%6
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
755731781527010210018
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
794157450.44%679134150.63%531104650.76%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
133870612236211214594


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
70493Bears4Blossom Bytes3LBoxScore
74519Titans5Blossom Bytes4LXBoxScore
78549Mountaineers2Blossom Bytes1LBoxScore
80567Blossom Bytes3Blood Miners5LBoxScore
83582Bulldogs3Blossom Bytes7WBoxScore
85601Blossom Bytes3Moose1WBoxScore
87613Phantoms3Blossom Bytes4WXXBoxScore
90635Blossom Bytes5Moose6LBoxScore
91644Wolf Pack9Blossom Bytes5LBoxScore
94667Blossom Bytes5Titans1WBoxScore
95675Blossom Bytes3Gulls1WBoxScore
97684Moose3Blossom Bytes5WBoxScore
100707Saints5Blossom Bytes6WXXBoxScore
102726Blossom Bytes4Phantoms5LBoxScore
104740Phantoms3Blossom Bytes2LBoxScore
106753Blossom Bytes2Roadrunners4LBoxScore
108766Blossom Bytes5Penguins6LBoxScore
110776Bears3Blossom Bytes2LBoxScore
112793Blossom Bytes5Senators4WXXBoxScore
114804Blossom Bytes6Reign3WBoxScore
115816Gulls2Blossom Bytes7WBoxScore
119842Blossom Bytes2Eagles1WXBoxScore
120848Griffins8Blossom Bytes5LBoxScore
122870Blossom Bytes5Bills1WBoxScore
124878Grisards5Blossom Bytes7WBoxScore
127906Titans2Blossom Bytes6WBoxScore
129920Blossom Bytes7Titans5WBoxScore
131937Blossom Bytes7Rams8LXXBoxScore
132943Penguins2Blossom Bytes3WXXBoxScore
136969Blossom Bytes6Rams4WBoxScore
137975Rocket3Blossom Bytes4WBoxScore
1401000Gorillas1Blossom Bytes6WBoxScore
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 Price4020
Attendance58,006101,855
Attendance PCT72.51%57.87%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
9 4996 - 62.45% 179,017$5,728,536$8000110

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Salaries CapCoaches Salaries
2,406,994$ 2,686,481$ 2,686,481$ 600,000$0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
17,481$ 2,406,994$ 29 2

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
1,611,151$ 48 17,481$ 839,088$




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