Rampage

GP: 22 | W: 9 | L: 12 | OTL: 1 | P: 19
GF: 66 | GA: 78 | PP%: 74.55% | PK%: 46.00%
GM : Martin Grech | Morale : 50 | Team Overall : 58
Next Games vs Condors
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

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 SP
1David Kampf (R)XX100.006742917672638160906259762550506550620
2Josh LeivoX100.005740887165574477576557702550506350600
3Iiro PakarinenX100.008345947778565957305357712559596250600
4Justin AugerX100.008687856487737855505056685344446250590
5Adam TambelliniX100.007264916464778357715159615644446150580
6Michael Dal ColleX100.007874876074788456505651644844445950580
7Luke Johnson (R)X100.007270766770818856705057615444446050580
8Alex Schoenborn (R)X100.007472786272626648504545604344445350520
9Julius HonkaX100.006541898267627670254747592550505850600
10Andreas EnglundX100.007871947471768446253739623744445450590
11Dillon HeatheringtonX100.008178896578707550254441643944445550590
12Jordan SchmaltzX100.006141867372566563254847562546465650570
13Josh Jacobs (R)X100.007775826275646849254439623744445350570
14Dylan BlujusX100.007673836773545551254542624044445350560
15Josh Wesley (R)X100.007977836577515443253239613744445050540
Scratches
1Slater KoekkoekX100.007543857169577258255051672554556050610
TEAM AVERAGE100.00746286697365715642494964374747585058
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 SP
1Nick Schneider100.0065696577657064686963455555150650
2Zane McIntyre (R)100.00627088796169576665633044446450630
Scratches
1Christopher Gibson100.00575569725762616564633045456050590
2Hunter Miska (R)100.00556784655156556154543044445650560
3Mackenzie Blackwood100.00506379904552505549493044445250550
4Matiss Kivlenieks (R)100.00537493724755505849493044445450550
5Marcus Hogberg (R)100.00505670874852505551513044445250540
6Chris Driedger100.00485366804648505448483044444950520
7Matt Hackett100.00494860664955505455543046465250520
TEAM AVERAGE100.0054627576525854605655324646495057
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Guy Boucher93576484635569CAN4611,000,000$


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 NamePOS GP 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
1Josh LeivoRampage (Col)LW22293362-77526271495110119.46%1145720.80714211129000001057.89%194225062.7100001314
2Julius HonkaRampage (Col)D22134255075162213465669.70%2553324.231110212529000329010.00%01624012.0600010043
3Luke JohnsonRampage (Col)C22142337-34915182894365414.89%1334915.883912715000001054.75%400227012.1201111103
4Michael Dal ColleRampage (Col)LW22122032-25745262079244615.19%1234215.584812515000001165.22%232112001.8700072022
5Justin AugerRampage (Col)RW22121123-13315232386184213.95%1128613.0220234000000042.86%14217011.6100003100
6Andreas EnglundRampage (Col)D2251520-1800191639211712.82%2739618.02448519000417110.00%0323001.0101000001
7Dillon HeatheringtonRampage (Col)D2251520-17242031205926308.47%3538817.65358819000216100.00%0419001.0300211010
8Adam TambelliniRampage (Col)C2212517-275151590325913.33%826612.1211212000001052.87%157186011.2711010100
9Slater KoekkoekRampage (Col)D1331417-47521154520156.67%1630023.09235415000312000.00%01015001.1300100100
10Iiro PakarinenRampage (Col)RW78311-700121043142318.60%413218.9620223000000025.00%8214011.6600000100
11Jordan SchmaltzRampage (Col)D2201010-200472014190.00%1025011.400000000002000.00%047000.8000000000
12Josh JacobsRampage (Col)D22088-4115129171090.00%1727112.340111200000000.00%0111000.5900010000
13Dylan BlujusRampage (Col)D22066-7754219870.00%71496.780111100001000.00%005000.8000010000
14Alex SchoenbornRampage (Col)RW22112-15001453416332.94%21677.6100000000000075.00%4183000.2400000000
15Josh WesleyRampage (Col)D22011-7001444450.00%71396.330000000000000.00%008000.1400000000
Team Total or Average306114207321-9620912525522391235952612.50%205443114.483956957315800012806354.24%6252011760111.451341388813
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
Team Total or Average0.0000.0000.000


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 NamePOS Age Birthday Rookie Weight Height No Trade Available For Trade Force Waivers CONT StatusType Current Salary Salary Year 2 Salary Year 3 Salary Year 4 Salary Year 5 Salary Year 6 Salary Year 7 Salary Year 8 Salary Year 9 Salary Year 10 Link
Adam TambelliniRampage (Col)C241994-10-31No195 Lbs6 ft4NoNoNo1RFAPro & Farm750,000$Link
Alex SchoenbornRampage (Col)RW221995-12-11Yes196 Lbs6 ft1NoNoNo2RFAPro & Farm750,000$750,000$Link
Andreas EnglundRampage (Col)D221996-01-21No189 Lbs6 ft3NoNoNo2RFAPro & Farm850,000$850,000$Link
Chris DriedgerRampage (Col)D241994-05-18No205 Lbs6 ft4NoNoNo1RFAPro & Farm700,000$Link
Christopher GibsonRampage (Col)C251992-12-27No188 Lbs6 ft1NoNoNo4RFAPro & Farm750,000$750,000$750,000$750,000$Link
David KampfRampage (Col)C/RW231995-01-12Yes191 Lbs6 ft2NoNoNo2RFAPro & Farm1,000,000$1,000,000$Link
Dillon HeatheringtonRampage (Col)D231995-05-08No215 Lbs6 ft4NoNoNo1RFAPro & Farm800,000$Link
Dylan BlujusRampage (Col)D241994-01-22No203 Lbs6 ft3NoNoNo2RFAPro & Farm750,000$750,000$Link
Hunter MiskaRampage (Col)C/LW/RW231995-07-07Yes170 Lbs6 ft1NoNoNo2RFAPro & Farm1,000,000$1,000,000$Link
Iiro PakarinenRampage (Col)RW271991-08-25No209 Lbs6 ft1NoNoNo4RFAPro & Farm1,000,000$1,000,000$1,000,000$1,000,000$Link
Jordan SchmaltzRampage (Col)D251993-10-08No190 Lbs6 ft2NoNoNo1RFAPro & Farm900,000$Link
Josh JacobsRampage (Col)D221996-02-14Yes200 Lbs6 ft2NoNoNo2RFAPro & Farm850,000$850,000$Link
Josh LeivoRampage (Col)LW251993-05-26No205 Lbs6 ft2NoNoNo2RFAPro & Farm750,000$750,000$Link
Josh WesleyRampage (Col)D221996-04-09Yes205 Lbs6 ft3NoNoNo3RFAPro & Farm600,000$600,000$600,000$Link
Julius HonkaRampage (Col)D221995-12-03No195 Lbs5 ft11NoNoNo2RFAPro & Farm1,000,000$1,000,000$Link
Justin AugerRampage (Col)RW241994-05-14No229 Lbs6 ft7NoNoNo2RFAPro & Farm750,000$750,000$Link
Luke JohnsonRampage (Col)C241994-09-18Yes198 Lbs5 ft11NoNoNo2RFAPro & Farm500,000$500,000$Link
Mackenzie BlackwoodRampage (Col)D211996-12-08No224 Lbs6 ft4NoNoNo2RFAPro & Farm850,000$850,000$Link
Marcus HogbergRampage (Col)D231994-11-25Yes209 Lbs6 ft5NoNoNo3RFAPro & Farm700,000$700,000$700,000$Link
Matiss KivlenieksRampage (Col)C/LW/RW221996-08-26Yes184 Lbs6 ft2NoNoNo2RFAPro & Farm1,000,000$1,000,000$Link
Matt HackettRampage (Col)D271991-03-07No171 Lbs6 ft2NoNoNo3RFAPro & Farm750,000$750,000$750,000$Link
Michael Dal ColleRampage (Col)LW221996-06-19No198 Lbs6 ft3NoNoNo2RFAPro & Farm950,000$950,000$Link
Nick SchneiderRampage (Col)LW211997-07-21No181 Lbs6 ft2NoNoNo2RFAPro & Farm750,000$750,000$Link
Slater KoekkoekRampage (Col)D241994-02-17No198 Lbs6 ft2NoNoNo2RFAPro & Farm850,000$850,000$Link
Zane McIntyreRampage (Col)LW/RW261992-08-20Yes206 Lbs6 ft2NoNoNo3RFAPro & Farm750,000$750,000$750,000$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2523.48198 Lbs6 ft22.16812,000$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Josh Leivo40122
2Michael Dal ColleLuke Johnson30122
3Adam TambelliniJustin Auger20122
4Alex Schoenborn10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Julius Honka40122
2Andreas EnglundDillon Heatherington30122
3Josh JacobsJordan Schmaltz20122
4Dylan BlujusJosh Wesley10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Josh Leivo60122
2Michael Dal ColleLuke Johnson40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Julius Honka60122
2Andreas EnglundDillon Heatherington40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
160122
2Josh Leivo40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Julius Honka60122
2Andreas EnglundDillon Heatherington40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
160122Julius Honka60122
240122Andreas EnglundDillon Heatherington40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
160122
2Josh Leivo40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Julius Honka60122
2Andreas EnglundDillon Heatherington40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Josh LeivoJulius Honka
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Josh LeivoJulius Honka
Extra Forwards
Normal PowerPlayPenalty Kill
Justin Auger, Adam Tambellini, Alex SchoenbornJustin Auger, Adam TambelliniAlex Schoenborn
Extra Defensemen
Normal PowerPlayPenalty Kill
Josh Jacobs, Jordan Schmaltz, Dylan BlujusJosh JacobsJordan Schmaltz, Dylan Blujus
Penalty Shots
, , , Josh Leivo, Justin Auger
Goalie
#1 : , #2 :


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
1Bears1010000012-11010000012-10000000000000.0001230034555443138233733493820418000.00%2150.00%018041443.48%14534941.55%21851242.58%502334470182354160
2Checkers10100000610-40000000000010100000610-400.0006111700345554449382337334931126172150.00%3166.67%018041443.48%14534941.55%21851242.58%502334470182354160
3Comets1100000011470000000000011000000114721.000111526003455544513823373349331214172150.00%2150.00%018041443.48%14534941.55%21851242.58%502334470182354160
4Condors4210100031274201010001314-1220000001813560.75031568700345554420838233733491403649668450.00%8362.50%018041443.48%14534941.55%21851242.58%502334470182354160
5Falcons1010000068-2000000000001010000068-200.0006121800345554438382337334943171110000.00%3233.33%018041443.48%14534941.55%21851242.58%502334470182354160
6Griffins10100000711-410100000711-40000000000000.000712190034555444138233733495213171333100.00%110.00%018041443.48%14534941.55%21851242.58%502334470182354160
7Gulls1010000039-61010000039-60000000000000.00036900345554447382337334932760194250.00%5420.00%018041443.48%14534941.55%21851242.58%502334470182354160
8Heat11000000752000000000001100000075221.0007121900345554451382337334945199204250.00%3166.67%018041443.48%14534941.55%21851242.58%502334470182354160
9IceHogs10001000871000000000001000100087121.00081624003455544553823373349361422044100.00%10100.00%018041443.48%14534941.55%21851242.58%502334470182354160
10Monsters1010000057-21010000057-20000000000000.000591400345554451382337334937172163266.67%110.00%018041443.48%14534941.55%21851242.58%502334470182354160
11Pirates11000000642110000006420000000000021.00061117003455544443823373349441641433100.00%20100.00%018041443.48%14534941.55%21851242.58%502334470182354160
12Reign10001000761100010007610000000000021.00071320003455544583823373349401072022100.00%110.00%018041443.48%14534941.55%21851242.58%502334470182354160
Since Last GM Reset2261203001146158-121126020016678-1211460100080800190.43214625740300345554410593823373349881282261367554174.55%502746.00%018041443.48%14534941.55%21851242.58%502334470182354160
Total2261203001146158-121126020016678-1211460100080800190.43214625740300345554410593823373349881282261367554174.55%502746.00%018041443.48%14534941.55%21851242.58%502334470182354160
Vs Conference1851003000127135-8815020005365-1210450100074704160.4441272213480034555448873823373349729230237301493673.47%382242.11%018041443.48%14534941.55%21851242.58%502334470182354160
Vs Division1356010009097-7512010002740-138440000063576120.462901562460034555446303823373349524158197219312167.74%331845.45%018041443.48%14534941.55%21851242.58%502334470182354160
17Wild21100000171341100000014771010000036-320.5001728450034555441103823373349802819338675.00%220.00%018041443.48%14534941.55%21851242.58%502334470182354160
18Wolf Pack1000000167-11000000167-10000000000010.50061218003455544483823373349394101711100.00%5340.00%018041443.48%14534941.55%21851242.58%502334470182354160
19Wolves404000002538-1310100000411-7303000002127-600.0002542670034555441773823373349191574767111090.91%11645.45%018041443.48%14534941.55%21851242.58%502334470182354160

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
2219L3146257403105988128226136700
All Games
GPWLOTWOTL SOWSOLGFGA
226123001146158
Home Games
GPWLOTWOTL SOWSOLGFGA
112620016678
Visitor Games
GPWLOTWOTL SOWSOLGFGA
114610008080
Last 10 Games
WLOTWOTL SOWSOL
450001
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
554174.55%502746.00%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
38233733493455544
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
18041443.48%14534941.55%21851242.58%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
502334470182354160


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
3 - 2018-10-0417Condors6Rampage7WXBoxScore
5 - 2018-10-0630Rampage11Comets4WBoxScore
7 - 2018-10-0846Gulls9Rampage3LBoxScore
9 - 2018-10-1066Griffins11Rampage7LBoxScore
10 - 2018-10-1175Rampage8Wolves10LBoxScore
13 - 2018-10-1494Condors8Rampage6LBoxScore
14 - 2018-10-15107Rampage3Wild6LBoxScore
16 - 2018-10-17117Rampage7Heat5WBoxScore
18 - 2018-10-19134Rampage9Condors7WBoxScore
20 - 2018-10-21148Pirates4Rampage6WBoxScore
22 - 2018-10-23161Rampage5Wolves7LBoxScore
24 - 2018-10-25176Wolves11Rampage4LBoxScore
26 - 2018-10-27193Rampage8IceHogs7WXBoxScore
28 - 2018-10-29208Wild7Rampage14WBoxScore
31 - 2018-11-01227Monsters7Rampage5LBoxScore
33 - 2018-11-03240Rampage8Wolves10LBoxScore
35 - 2018-11-05254Rampage9Condors6WBoxScore
37 - 2018-11-07268Reign6Rampage7WXBoxScore
40 - 2018-11-10290Wolf Pack7Rampage6LXXBoxScore
43 - 2018-11-13306Rampage6Checkers10LBoxScore
45 - 2018-11-15320Rampage6Falcons8LBoxScore
47 - 2018-11-17328Bears2Rampage1LBoxScore
50 - 2018-11-20346Rampage-Heat-
52 - 2018-11-22362IceHogs-Rampage-
54 - 2018-11-24378Rampage-Heat-
56 - 2018-11-26390Moose-Rampage-
59 - 2018-11-29414Rampage-Stars-
60 - 2018-11-30424Rampage-Bruins-
62 - 2018-12-02431Americans-Rampage-
64 - 2018-12-04451Condors-Rampage-
67 - 2018-12-07471Rampage-IceHogs-
68 - 2018-12-08483Rampage-Falcons-
70 - 2018-12-10492Monsters-Rampage-
73 - 2018-12-13515Falcons-Rampage-
76 - 2018-12-16538Wild-Rampage-
79 - 2018-12-19556Rampage-Penguins-
81 - 2018-12-21565Rampage-Wild-
83 - 2018-12-23576Condors-Rampage-
87 - 2018-12-27600Comets-Rampage-
89 - 2018-12-29624Pirates-Rampage-
91 - 2018-12-31634Rampage-Wolves-
94 - 2019-01-03658Rampage-Wild-
95 - 2019-01-04664Stars-Rampage-
99 - 2019-01-08688Stars-Rampage-
101 - 2019-01-10708Rampage-Comets-
103 - 2019-01-12717Admirals-Rampage-
106 - 2019-01-15739Rampage-Marlies-
108 - 2019-01-17749Rampage-Gulls-
109 - 2019-01-18759Comets-Rampage-
111 - 2019-01-20771Rampage-Comets-
114 - 2019-01-23788Rampage-IceCaps-
115 - 2019-01-24796Griffins-Rampage-
118 - 2019-01-27819Rampage-Reign-
119 - 2019-01-28827Wolves-Rampage-
122 - 2019-01-31849Rampage-Reign-
123 - 2019-02-01857Americans-Rampage-
126 - 2019-02-04879Crunch-Rampage-
128 - 2019-02-06892Rampage-Sound Tigers-
131 - 2019-02-09913Heat-Rampage-
133 - 2019-02-11926Rampage-Griffins-
135 - 2019-02-13941Barracuda-Rampage-
137 - 2019-02-15955Rampage-Monsters-
139 - 2019-02-17973Senators-Rampage-
141 - 2019-02-19984Rampage-Admirals-
143 - 2019-02-211002Rampage-Phantoms-
Trade Deadline --- Trades can’t be done after this day is simulated!
144 - 2019-02-221011Rampage-Griffins-
145 - 2019-02-231015Wolves-Rampage-
147 - 2019-02-251029Rampage-Phantoms-
149 - 2019-02-271046Heat-Rampage-
153 - 2019-03-031074Barracuda-Rampage-
156 - 2019-03-061097Wolves-Rampage-
158 - 2019-03-081111Rampage-Barracuda-
162 - 2019-03-121130Gulls-Rampage-
163 - 2019-03-131138Rampage-Admirals-
165 - 2019-03-151152Rampage-Devils-
168 - 2019-03-181169Gulls-Rampage-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance00
Attendance PCT0.00%0.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
27 0 - 0.00% 0$0$3000100

Expenses
Players Total SalariesPlayers Total Average SalariesCoaches Salaries
2,030,000$ 1,640,000$ 0$
Year To Date ExpensesSalary Cap Per DaysSalary Cap To Date
581,182$ 0$ 578,697$

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 122 11,871$ 1,448,262$




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
20182261203001146158-121126020016678-12114601000808001914625740300345554410593823373349881282261367554174.55%502746.00%018041443.48%14534941.55%21851242.58%502334470182354160
Total Regular Season2261203001146158-121126020016678-12114601000808001914625740300345554410593823373349881282261367554174.55%502746.00%018041443.48%14534941.55%21851242.58%502334470182354160