Mystery

GP: 6 | W: 4 | L: 2 | OTL: 0 | P: 8
GF: 18 | GA: 12 | PP%: 31.03% | PK%: 85.71%
GM : Cédric De Niverville | Morale : 84 | Team Overall : 62
Next Games #78 vs Oil Kings
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
1Blake ComeauXX100.00924684787473956140625987758081082700
2Jordan MartinookXXX100.00894686827368996156617176256565082690
3Kyle BrodziakX100.00785486727761936188545985258184082670
4Connor BrownXX100.00634193786866996038715981256465082670
5Lee StempniakX100.00757086767054526950646375608284082660
6Jujhar KhairaXX100.00867879788163826147705775255656082660
7Chris TerryXX100.00746985716979826850636768645454082650
8Barclay GoodrowXX100.00809074708059836180605973256465075640
9Sheldon DriesXX100.00824481746554845760585872254747082610
10Tyler GaudetXX100.00787780687772765974585665534545081610
11Travis BoydXX100.00594196636755796053735969254950082610
12Taylor LeierX100.00716682696667696150556262594444082600
13Connor MurphyX100.00884678748079816125525090256868082720
14Jonathan EricssonX100.00845781718372845625444887257579082700
15Ilya Lyubushkin (R)X100.00996189707763635825504769254747082630
16Calle RosenX100.00706581706575796225624664445555078630
17Jordan SchmaltzX100.00654296737258665425504763254949082600
18Jesse GrahamX100.00726783636761654825404160394747081560
Scratches
1Markus HannikainenXX100.00794498717254616325575970254949076600
2Nathan WalkerX100.00656272646271746250596259594445076590
3Garrett Pilon (R)X100.00726394676377825771575361504444074590
4Joseph CramarossaXX100.00637048657071775150504656444646074550
5Ty Dellandrea (R)X100.00757185697156585164465161484444074550
6Matheson IacopelliXX100.00777680677659624750434661444444074540
7Hayden Verbeek (R)XX100.00736591586567734860434760454444074540
8Justin HollX100.00714293636660575725494754254646076560
TEAM AVERAGE100.0076608470716576584756556939555607962
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
1Curtis McElhinney100.0074555680777268738275656364082710
2Josef Korenar (R)100.0060627870606657656463304444082610
Scratches
1Garret Sparks100.0062615983665755606962454747074610
2Kevin Boyle100.0059708878586152625655304444074600
TEAM AVERAGE100.006462707865645865686443505007863
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Dave Hakstol70778181635671USA495300,000$


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
1Jujhar KhairaMystery (MEM)C/LW635836017482437.50%09515.88134119000022028.57%700001.6800000111
2Lee StempniakMystery (MEM)RW62463402591922.22%08514.28224515000000042.86%700001.4000000000
3Kyle BrodziakMystery (MEM)C6145310021512348.33%011619.450222150001270065.88%8500000.8600000010
4Jordan MartinookMystery (MEM)C/LW/RW64152801210123733.33%111318.841125191012371159.38%9600000.8800000200
5Chris TerryMystery (MEM)LW/RW61342204555820.00%09816.4502207000090057.14%700000.8100000100
6Connor MurphyMystery (MEM)D61341806545425.00%514223.70134421000031000.00%000000.5600000002
7Barclay GoodrowMystery (MEM)C/LW40331407210040.00%04812.1601110000070080.00%500001.2300000000
8Connor BrownMystery (MEM)LW/RW61232001961816.67%010617.721123190110300042.31%2600000.5600000010
9Jordan SchmaltzMystery (MEM)D621328054201100.00%29415.8110114000012100.00%000000.6300000000
10Ilya LyubushkinMystery (MEM)D61120100172102100.00%312220.39011016000032000.00%000000.3300000001
11Justin SchultzGothiquesD3112-1000430233.33%66923.0311229000022000.00%000000.5800000000
12Travis BoydMystery (MEM)C/RW61121002672514.29%08914.86101140000110052.63%7600000.4500000000
13Jonathan EricssonMystery (MEM)D6011160633320.00%213823.13000319000033000.00%000000.1400000010
14Calle RosenMystery (MEM)D3011200202030.00%16421.5201128000019000.00%000000.3100000000
15Blake ComeauMystery (MEM)LW/RW6011-112013159570.00%014223.720002180001330060.32%6300000.1400000000
16Nathan WalkerMystery (MEM)LW2000-100100010.00%052.600000200000000.00%000000.0000000000
17Jesse GrahamMystery (MEM)D40001100900010.00%05914.930000100005000.00%000000.0000000000
18Sheldon DriesMystery (MEM)C/LW6000-260323110.00%0366.0900000000010039.39%3300000.0000000000
19Taylor LeierMystery (MEM)LW6000-220210020.00%0335.620000000000000.00%000000.0000000000
20Tyler GaudetMystery (MEM)C/LW4000000000010.00%000.170000000000000.00%000000.0000000000
21Justin HollMystery (MEM)D2000020610000.00%03015.130000000003000.00%000000.0000000000
22Markus HannikainenMystery (MEM)LW/RW2000000111120.00%02713.960000100000000.00%200000.0000000000
Team Total or Average108183250179801189497327818.56%20172115.94918273220611243244156.02%40700000.5800000444
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
1Curtis McElhinneyMystery (MEM)64200.8931.9936200121120000.000060000
Team Total or Average64200.8931.9936200121120000.000060000


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 Contract StatusType Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Link
Barclay GoodrowMystery (MEM)C/LW261993-02-26No210 Lbs6 ft2NoNoNo2RFAPro & Farm700,000$0$0$NoLink / NHL Link
Blake Comeau (1 Way Contract)Mystery (MEM)LW/RW331986-02-17No202 Lbs6 ft1NoNoNo3UFAPro & Farm3,150,000$1,292,500$1,193,767$NoLink / NHL Link
Calle RosenMystery (MEM)D251994-02-02No176 Lbs6 ft0NoNoNo2RFAPro & Farm925,000$0$0$NoLink
Chris TerryMystery (MEM)LW/RW301989-04-07No195 Lbs5 ft10NoNoNo2UFAFarm Only700,000$0$0$NoLink / NHL Link
Connor Brown (1 Way Contract)Mystery (MEM)LW/RW251994-01-14No185 Lbs6 ft0NoNoNo2RFAPro & Farm2,100,000$100,000$92,361$NoLink
Connor Murphy (1 Way Contract)Mystery (MEM)D261993-03-26No212 Lbs6 ft4NoNoNo1RFAPro & Farm3,850,000$1,850,000$1,708,681$NoLink / NHL Link
Curtis McElhinney (1 Way Contract)Mystery (MEM)G361983-05-22No200 Lbs6 ft3NoNoNo1UFAPro & Farm999,999$0$0$NoLink / NHL Link
Garret Sparks (1 Way Contract)Mystery (MEM)G261993-06-28No210 Lbs6 ft3NoNoNo1RFAPro & Farm750,000$0$0$NoLink
Garrett PilonMystery (MEM)C211998-04-13Yes175 Lbs5 ft10NoNoNo3ELCFarm Only792,500$0$0$NoLink
Hayden VerbeekMystery (MEM)C/LW211997-10-17Yes183 Lbs5 ft10NoNoNo1ELCPro & Farm700,000$0$0$NoLink
Ilya Lyubushkin (1 Way Contract)Mystery (MEM)D251994-04-06Yes209 Lbs6 ft2NoNoNo2RFAPro & Farm700,000$0$0$NoLink
Jesse GrahamMystery (MEM)D251994-05-13No184 Lbs6 ft0NoNoNo1RFAPro & Farm700,000$0$0$NoLink
Jonathan Ericsson (1 Way Contract)Mystery (MEM)D351984-03-02No220 Lbs6 ft4NoNoNo2UFAPro & Farm3,100,000$1,100,000$1,015,972$NoLink / NHL Link
Jordan Martinook (1 Way Contract)Mystery (MEM)C/LW/RW261992-07-24No204 Lbs6 ft0NoNoNo1RFAPro & Farm2,000,000$0$0$NoLink / NHL Link
Jordan SchmaltzMystery (MEM)D251993-10-08No190 Lbs6 ft2NoNoNo1RFAPro & Farm925,000$0$0$NoLink / NHL Link
Josef KorenarMystery (MEM)G211998-01-31Yes185 Lbs6 ft1NoNoNo3ELCFarm Only760,000$0$0$NoLink
Joseph CramarossaMystery (MEM)LW/RW261992-10-26No192 Lbs6 ft0NoNoNo1RFAFarm Only724,500$0$0$NoLink
Jujhar Khaira (1 Way Contract)Mystery (MEM)C/LW241994-08-13No214 Lbs6 ft4NoNoNo1RFAPro & Farm1,200,000$0$0$NoLink
Justin Holl (1 Way Contract)Mystery (MEM)D271992-01-30No170 Lbs6 ft2NoNoNo3RFAPro & Farm700,000$0$0$NoLink
Kevin BoyleMystery (MEM)G271992-05-29No200 Lbs6 ft2NoNoNo1RFAPro & Farm700,000$0$0$NoLink
Kyle Brodziak (1 Way Contract)Mystery (MEM)C351984-05-25No209 Lbs6 ft2NoNoNo1UFAPro & Farm950,000$0$0$NoLink / NHL Link
Lee Stempniak (1 Way Contract)Mystery (MEM)RW361983-02-03No195 Lbs5 ft11NoNoNo1UFAFarm Only2,500,000$500,000$461,806$NoLink / NHL Link
Markus HannikainenMystery (MEM)LW/RW261993-03-25No190 Lbs6 ft2NoNoNo1RFAPro & Farm700,000$0$0$NoLink
Matheson IacopelliMystery (MEM)LW/RW251994-05-15No207 Lbs6 ft2NoNoNo2RFAFarm Only742,500$0$0$NoLink
Nathan WalkerMystery (MEM)LW251994-02-06No175 Lbs5 ft9NoNoNo3RFAPro & Farm700,000$0$0$NoLink
Sheldon DriesMystery (MEM)C/LW251994-04-23No185 Lbs5 ft9NoNoNo2RFAPro & Farm700,000$0$0$NoLink
Taylor LeierMystery (MEM)LW251994-02-14No180 Lbs5 ft11NoNoNo2RFAFarm Only700,000$0$0$NoLink
Travis BoydMystery (MEM)C/RW251993-09-14No185 Lbs5 ft11NoNoNo1RFAPro & Farm700,000$0$0$NoLink
Ty DellandreaMystery (MEM)C182000-07-21Yes190 Lbs6 ft1NoNoNo3ELCFarm Only925,000$0$0$NoLink
Tyler GaudetMystery (MEM)C/LW261993-03-04No205 Lbs6 ft3NoNoNo1RFAFarm Only700,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3026.53195 Lbs6 ft11.701,183,150$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Blake ComeauJordan MartinookConnor Brown30122
2Jujhar KhairaKyle BrodziakLee Stempniak30122
3Chris TerryTravis BoydBarclay Goodrow25122
4Taylor LeierSheldon DriesBlake Comeau15122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Connor MurphyJonathan Ericsson30122
2Calle RosenIlya Lyubushkin30122
3Jordan SchmaltzJesse Graham25122
4Connor MurphyJonathan Ericsson15122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Blake ComeauJordan MartinookConnor Brown55122
2Jujhar KhairaKyle BrodziakLee Stempniak45122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Connor MurphyJonathan Ericsson55122
2Calle RosenIlya Lyubushkin45122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Blake ComeauJordan Martinook55122
2Connor BrownKyle Brodziak45122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Connor MurphyJonathan Ericsson55122
2Calle RosenIlya Lyubushkin45122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Blake Comeau55122Connor MurphyJonathan Ericsson55122
2Jordan Martinook45122Calle RosenIlya Lyubushkin45122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Blake ComeauJordan Martinook55122
2Connor BrownKyle Brodziak45122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Connor MurphyJonathan Ericsson55122
2Calle RosenIlya Lyubushkin45122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Blake ComeauJordan MartinookConnor BrownConnor MurphyJonathan Ericsson
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Blake ComeauJordan MartinookConnor BrownConnor MurphyJonathan Ericsson
Extra Forwards
Normal PowerPlayPenalty Kill
Blake Comeau, Chris Terry, Travis BoydBlake Comeau, Chris TerryTravis Boyd
Extra Defensemen
Normal PowerPlayPenalty Kill
Jordan Schmaltz, Connor Murphy, Calle RosenJordan SchmaltzJonathan Ericsson, Calle Rosen
Penalty Shots
Blake Comeau, Jordan Martinook, Connor Brown, Kyle Brodziak, Lee Stempniak
Goalie
#1 : Curtis McElhinney, #2 : Josef Korenar


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
1Oil Kings2200000010460000000000022000000104641.0001019290010521384830181363223613753.85%11190.91%07714353.85%9316556.36%589660.42%14498141457638
2Olympic1010000014-3000000000001010000014-300.00012300105211548301812761822300.00%9277.78%07714353.85%9316556.36%589660.42%14498141457638
3Redhawks10001000211100010002110000000000021.00022400105211148301811452421300.00%12191.67%17714353.85%9316556.36%589660.42%14498141457638
4Sun Devils11000000413110000004130000000000021.0004711001052118483018111416176116.67%8187.50%07714353.85%9316556.36%589660.42%14498141457638
Total63201000181263110100074332100000118380.6671832500010521974830181112209811829931.03%49785.71%17714353.85%9316556.36%589660.42%14498141457638
6Winterhawks1010000012-11010000012-10000000000000.000123001052115483018124218224125.00%9277.78%07714353.85%9316556.36%589660.42%14498141457638
_Since Last GM Reset63201000181263110100074332100000118380.6671832500010521974830181112209811829931.03%49785.71%17714353.85%9316556.36%589660.42%14498141457638
_Vs Conference63201000181263110100074332100000118380.6671832500010521974830181112209811829931.03%49785.71%17714353.85%9316556.36%589660.42%14498141457638
_Vs Division31101000761210010006241010000014-340.667711180010521444830181521558601218.33%29486.21%17714353.85%9316556.36%589660.42%14498141457638

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
68W118325097112209811800
All Games
GPWLOTWOTL SOWSOLGFGA
63210001812
Home Games
GPWLOTWOTL SOWSOLGFGA
311100074
Visitor Games
GPWLOTWOTL SOWSOLGFGA
3210000118
Last 10 Games
WLOTWOTL SOWSOL
420000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
29931.03%49785.71%1
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
483018110521
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
7714353.85%9316556.36%589660.42%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
14498141457638


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
1 - 2019-10-074Redhawks1Mystery2WXR1BoxScore
3 - 2019-10-0918Mystery1Olympic4LBoxScore
4 - 2019-10-1021Mystery6Oil Kings3WBoxScore
7 - 2019-10-1343Sun Devils1Mystery4WBoxScore
8 - 2019-10-1453Winterhawks2Mystery1LBoxScore
10 - 2019-10-1662Mystery4Oil Kings1WBoxScore
12 - 2019-10-1878Mystery-Oil Kings-
13 - 2019-10-1987Bengals-Mystery-
15 - 2019-10-21100Surfers-Mystery-
17 - 2019-10-23114Mystery-Aeros-
20 - 2019-10-26127Devil Dogs-Mystery-
21 - 2019-10-27137Mystery-Redhawks-
23 - 2019-10-29150Aeros-Mystery-
25 - 2019-10-31161Mystery-Pitbulls-
27 - 2019-11-02170Olympic-Mystery-
29 - 2019-11-04184Gamblers-Mystery-
31 - 2019-11-06198Mystery-Sun Devils-
33 - 2019-11-08206Mystery-Bengals-
35 - 2019-11-10219Mystery-Pitbulls-
38 - 2019-11-13233Mystery-Olympic-
39 - 2019-11-14238Rivercats-Mystery-
42 - 2019-11-17258Pitbulls-Mystery-
43 - 2019-11-18266Mystery-Sun Devils-
45 - 2019-11-20280Oil Kings-Mystery-
48 - 2019-11-23294Mystery-Aces-
49 - 2019-11-24302Jets-Mystery-
51 - 2019-11-26317Mystery-Jets-
53 - 2019-11-28329Redhawks-Mystery-
55 - 2019-11-30338Mystery-Gators-
56 - 2019-12-01351Gators-Mystery-
58 - 2019-12-03363Mystery-Surfers-
60 - 2019-12-05375Gamblers-Mystery-
62 - 2019-12-07388Mystery-Rhinos-
64 - 2019-12-09400Mystery-Bengals-
65 - 2019-12-10406Citadels-Mystery-
68 - 2019-12-13423Aeros-Mystery-
70 - 2019-12-15440Mystery-Devil Dogs-
71 - 2019-12-16447Mystery-Redhawks-
73 - 2019-12-18458Surfers-Mystery-
74 - 2019-12-19471Boys-Mystery-
76 - 2019-12-21487Mystery-Indians-
77 - 2019-12-22495Broncos-Mystery-
79 - 2019-12-24511Boys-Mystery-
81 - 2019-12-26521Mystery-Jets-
83 - 2019-12-28531Mystery-Gators-
84 - 2019-12-29543Mystery-Gamblers-
86 - 2019-12-31552Aces-Mystery-
88 - 2020-01-02566Sun Devils-Mystery-
89 - 2020-01-03577Mystery-Citadels-
92 - 2020-01-06593Liberty-Mystery-
94 - 2020-01-08606Mystery-Boys-
96 - 2020-01-10617Blazers-Mystery-
98 - 2020-01-12635Broncos-Mystery-
99 - 2020-01-13648Devil Dogs-Mystery-
101 - 2020-01-15659Mystery-Citadels-
102 - 2020-01-16673Olympic-Mystery-
103 - 2020-01-17680Mystery-Boys-
105 - 2020-01-19689Mystery-Gamblers-
107 - 2020-01-21701Mystery-Rivercats-
108 - 2020-01-22713Winterhawks-Mystery-
110 - 2020-01-24729Bengals-Mystery-
113 - 2020-01-27745Mystery-Winterhawks-
115 - 2020-01-29755Blazers-Mystery-
Trade Deadline --- Trades can’t be done after this day is simulated!
117 - 2020-01-31769Mystery-Cobras-
119 - 2020-02-02781Mystery-Broncos-
120 - 2020-02-03786Aces-Mystery-
122 - 2020-02-05802Cobras-Mystery-
123 - 2020-02-06814Mystery-Blazers-
125 - 2020-02-08826Mystery-Rivercats-
126 - 2020-02-09833Cobras-Mystery-
128 - 2020-02-11848Rhinos-Mystery-
131 - 2020-02-14866Rhinos-Mystery-
134 - 2020-02-17884Mystery-Blazers-
135 - 2020-02-18890Mystery-Broncos-
137 - 2020-02-20894Mystery-Liberty-
138 - 2020-02-21906Indians-Mystery-
139 - 2020-02-22913Mystery-Liberty-
142 - 2020-02-25925Indians-Mystery-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3010
Attendance5,9102,752
Attendance PCT98.50%91.73%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
36 2887 - 96.24% 68,273$204,820$300090

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
102,296$ 1,079,560$ 1,081,410$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
7,510$ 79,526$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
2,457,840$ 133 9,580$ 1,274,140$




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
201963201000181263110100074332100000118381832500010521974830181112209811829931.03%49785.71%17714353.85%9316556.36%589660.42%14498141457638
Total Regular Season63201000181263110100074332100000118381832500010521974830181112209811829931.03%49785.71%17714353.85%9316556.36%589660.42%14498141457638