Monsters

GP: 82 | W: 50 | L: 25 | OTL: 7 | P: 107
GF: 248 | GA: 160 | PP%: 16.85% | PK%: 88.18%
GM : Patrick Auger | Morale : 50 | Team Overall : 63

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
1Brendan LeipsicXX100.007035947069777869636662576873665350640
2Brayden BurkeXXX100.005646796365838866706861596467635250630
3Daniel AudetteX100.005646795864889362666459566169655450610
4David KaseXX100.005535956266727363616161606467655650610
5Jonah GadjovichX100.005842856282677064565863616265637050610
6Max VeronneauX100.005435926176777162576063556271664250610
7Carson Focht (R)X100.006152735871788361685956545861625650590
8Ryan HaggertyXX100.006538785674828754555357565475683650590
9Jake LeschyshynX100.006046805669879254655355525463626850580
10Will ButcherX100.005735957168878270307862595671675650660
11Ty Smith (R)X100.006139857467897873308159625461638450660
12Oliwer KaskiX100.007237905981869158305759634971664250650
13Logan DayX100.007051746479758058306255594873683750630
14Kyle BurroughsX100.007254715973727358306156624871664750620
15Brennan MenellX100.005338876168848063306557625167625350620
16Leon GawankeX100.006639875975768158306154574663625750610
17Josiah DidierX100.007257695481747954305752574675685250610
18Cole Hults (R)X100.006338885472687356305753544665635650580
Scratches
1Dan HamhuisX100.007346816078817762306955775189793350680
2Jeremy RoyX100.006454715573657053305551544567647650570
TEAM AVERAGE100.00634383617378806145625859546965545062
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
1Marcus Hogberg100.00788285947776787776787774785650770
2Filip Gustavsson100.00748581777372747372747365697150720
Scratches
TEAM AVERAGE100.0076848386757476757476757074645075
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Todd McLellan80867787807469CAN5435,000,000$


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 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
1Brayden BurkeMonsters (Clb)C/LW/RW823049792974101081822215815413.57%18163319.931322356036221352367261.37%168800000.97140021023
2Brennan MenellMonsters (Clb)D82155065432202263120498112.50%72160319.56111425843480331312210.00%000000.8100000135
3Brendan LeipsicMonsters (Clb)C/LW82362662282201261532566019414.06%13193223.564151952364404103739157.39%163100110.6415000875
4Ty SmithMonsters (Clb)D8211465741263011010612638818.73%78189023.05918271033880330314100.00%000000.6000123372
5Jonah GadjovichMonsters (Clb)LW822729562334084711936115413.99%10139417.0191524583540000193054.46%10100000.8002000356
6Eric RobinsonColumbus JacketsLW/RW74213455321000181143226511559.29%36171623.1956115532403353082053.89%69400000.6415000574
7David KaseMonsters (Clb)LW/RW82183553232204467210591298.57%11138116.844172153358000025256.76%7400000.7701000443
8Will ButcherMonsters (Clb)D8216324854006574124538312.90%77192523.48101222983890004341620.00%000100.5000000123
9Logan DayMonsters (Clb)D8213324542131251365283364615.66%54154218.8281321563430111266510.00%000000.5800140106
10Daniel AudetteMonsters (Clb)C8225174225210871532487617610.08%15141717.280000000021493159.17%115600010.5911101352
11Max VeronneauMonsters (Clb)RW82122537231402361122361099.84%8154718.873694237111241872054.05%11100000.4824000032
12Ryan HaggertyMonsters (Clb)C/RW82141832288014367175521208.00%13124715.2100007000001159.02%6100000.5100000225
13Kyle BurroughsMonsters (Clb)D82125261170082442911353.45%4389910.9701131500007100.00%000000.5800000002
14Leon GawankeMonsters (Clb)D8201515-118053392311150.00%275767.03011210011040000.00%000000.5200000002
15Josiah DidierMonsters (Clb)D82571213983087293061416.67%4795011.60000000000109000.00%000000.2500204002
16Jeremy RoyMonsters (Clb)D4608823552677200.00%92635.740000000000000.00%000000.6100001000
17Carson FochtMonsters (Clb)C821230206470114.29%01091.341012340000290048.39%6200000.5501000000
18Jake LeschyshynMonsters (Clb)C82022000104320.00%1400.49011222000000080.00%1000000.9900000000
Team Total or Average1432245452697281948110138413152204662154911.12%5322207215.4177141218670369671320322699471158.36%558800220.636235611414752
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
1Filip GustavssonMonsters (Clb)77482270.9121.8646148814316340200.79224770821
Team Total or Average77482270.9121.8646148814316340200.79224770821


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
Brayden BurkeC/LW/RW251997-01-01No165 Lbs5 ft11NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Brendan LeipsicC/LW271994-05-19No180 Lbs5 ft11NoNoNo2RFAPro & Farm500,000$0$0$NoLink / NHL Link
Brennan MenellD241997-05-24No177 Lbs5 ft11NoNoNo1RFAPro & Farm300,000$0$0$NoLink / NHL Link
Carson FochtC222000-02-04Yes180 Lbs6 ft0NoNoNo4ELCPro & Farm300,000$0$0$No
Cole HultsD231998-05-22Yes189 Lbs6 ft0NoNoNo4RFAPro & Farm300,000$0$0$No
Dan HamhuisD391982-12-13No204 Lbs6 ft1NoNoNo2UFAPro & Farm500,000$0$0$NoLink / NHL Link
Daniel AudetteC251996-05-06No176 Lbs5 ft8NoNoNo4RFAPro & Farm300,000$0$0$NoLink / NHL Link
David KaseLW/RW251997-01-28No169 Lbs5 ft11NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Filip GustavssonG231998-06-07No184 Lbs6 ft2NoNoNo1RFAPro & Farm500,000$0$0$NoLink / NHL Link
Jake LeschyshynC231999-03-10No185 Lbs5 ft11NoNoNo3RFAPro & Farm300,000$0$0$NoLink / NHL Link
Jeremy RoyD241997-05-14No195 Lbs6 ft0NoNoNo1RFAPro & Farm500,000$0$0$NoLink / NHL Link
Jonah GadjovichLW231998-10-12No209 Lbs6 ft2NoNoNo2RFAPro & Farm500,000$0$0$NoLink / NHL Link
Josiah DidierD281993-04-08No202 Lbs6 ft2NoNoNo4UFAPro & Farm300,000$0$0$NoLink / NHL Link
Kyle BurroughsD261995-07-12No193 Lbs6 ft0NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Leon GawankeD221999-05-31No186 Lbs6 ft1NoNoNo3ELCPro & Farm300,000$0$0$NoLink / NHL Link
Logan DayD271994-09-19No209 Lbs6 ft1NoNoNo3RFAPro & Farm300,000$0$0$NoLink / NHL Link
Marcus HogbergG271994-11-25No222 Lbs6 ft5NoNoNo1RFAPro & Farm300,000$0$0$NoLink / NHL Link
Max VeronneauRW261995-12-12No193 Lbs6 ft1NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Oliwer KaskiD261995-09-04No190 Lbs6 ft3NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Ryan HaggertyC/RW291993-03-04No200 Lbs6 ft0NoNoNo2UFAPro & Farm300,000$0$0$NoLink / NHL Link
Ty SmithD222000-03-24Yes175 Lbs5 ft11NoNoNo4ELCPro & Farm900,000$0$0$No
Will ButcherD271995-01-06No190 Lbs5 ft10NoNoNo1RFAPro & Farm500,000$0$0$NoLink / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2225.59190 Lbs6 ft02.36381,818$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Brendan LeipsicMax Veronneau40122
2Jonah GadjovichBrayden BurkeDavid Kase30122
3Daniel AudetteRyan Haggerty20122
4Brendan Leipsic10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty SmithWill Butcher40122
2Logan DayBrennan Menell30122
3Kyle BurroughsJosiah Didier20122
4Leon Gawanke10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Brendan LeipsicMax Veronneau60122
2Jonah GadjovichBrayden BurkeDavid Kase40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty SmithWill Butcher60122
2Logan DayBrennan Menell40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Brendan Leipsic60122
2Brayden BurkeMax Veronneau40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty SmithWill Butcher60122
2Logan DayBrennan Menell40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
160122Ty SmithWill Butcher60122
2Brendan Leipsic40122Logan DayBrennan Menell40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Brendan Leipsic60122
2Brayden BurkeMax Veronneau40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty SmithWill Butcher60122
2Logan DayBrennan Menell40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Brendan LeipsicMax VeronneauTy SmithWill Butcher
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Brendan LeipsicMax VeronneauTy SmithWill Butcher
Extra Forwards
Normal PowerPlayPenalty Kill
Carson Focht, Jake Leschyshyn, Daniel AudetteCarson Focht, Jake LeschyshynDaniel Audette
Extra Defensemen
Normal PowerPlayPenalty Kill
Kyle Burroughs, Josiah Didier, Leon GawankeKyle BurroughsJosiah Didier, Leon Gawanke
Penalty Shots
, Brendan Leipsic, Brayden Burke, Max Veronneau, Jonah Gadjovich
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

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
82107W124845570322141793534960138908
All Games
GPWLOTWOTL SOWSOLGFGA
8244253532248160
Home Games
GPWLOTWOTL SOWSOLGFGA
412013232111983
Visitor Games
GPWLOTWOTL SOWSOLGFGA
412412121112977
Last 10 Games
WLOTWOTL SOWSOL
451000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
4577716.85%4064888.18%7
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
767715713428982719
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1469247859.28%1211226453.49%681113360.11%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
227616741741544943502


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
2 - 2021-10-0217Checkers2Monsters1LXBoxScore
4 - 2021-10-0433Wild3Monsters1LBoxScore
6 - 2021-10-0643Monsters5Americans3WBoxScore
8 - 2021-10-0861Monsters2Checkers0WBoxScore
9 - 2021-10-0978IceHogs1Monsters4WBoxScore
12 - 2021-10-1295Monsters2Americans3LXBoxScore
14 - 2021-10-14111Phantoms3Monsters2LBoxScore
16 - 2021-10-16124Monsters3Griffins4LBoxScore
17 - 2021-10-17140Eagles2Monsters3WBoxScore
20 - 2021-10-20162Thunderbirds3Monsters2LBoxScore
21 - 2021-10-21169Monsters3Heat2WBoxScore
23 - 2021-10-23191Monsters4Stars2WBoxScore
26 - 2021-10-26204Palm Springs1Monsters6WBoxScore
27 - 2021-10-27220Monsters1Rocket2LBoxScore
29 - 2021-10-29233Monsters3Thunderbirds0WBoxScore
31 - 2021-10-31249Moose1Monsters6WBoxScore
33 - 2021-11-02269Bears1Monsters3WBoxScore
35 - 2021-11-04283Monsters10IceHogs1WBoxScore
37 - 2021-11-06303Gulls0Monsters3WBoxScore
40 - 2021-11-09316Monsters0Thunderbirds1LBoxScore
42 - 2021-11-11333Phantoms3Monsters2LBoxScore
44 - 2021-11-13349Monsters1Condors0WBoxScore
45 - 2021-11-14354Monsters3Roadrunners2WBoxScore
46 - 2021-11-15368Monsters2Wild4LBoxScore
48 - 2021-11-17382Eagles1Monsters5WBoxScore
51 - 2021-11-20409Reign1Monsters7WBoxScore
54 - 2021-11-23427Senators1Monsters3WBoxScore
56 - 2021-11-25450Monsters6Crunch2WBoxScore
58 - 2021-11-27462Penguins6Monsters1LBoxScore
60 - 2021-11-29482Monsters2Marlies3LBoxScore
61 - 2021-11-30494Griffins2Monsters0LBoxScore
62 - 2021-12-01507Monsters3Penguins4LXXBoxScore
65 - 2021-12-04526Palm Springs1Monsters4WBoxScore
68 - 2021-12-07548Monsters1Comets0WBoxScore
69 - 2021-12-08556IceHogs1Monsters7WBoxScore
71 - 2021-12-10580Wolves2Monsters1LBoxScore
73 - 2021-12-12592Monsters8Eagles0WBoxScore
74 - 2021-12-13610Heat1Monsters5WBoxScore
76 - 2021-12-15622Monsters8Heat2WBoxScore
78 - 2021-12-17640Monsters6Palm Springs1WBoxScore
80 - 2021-12-19654Comets0Monsters1WBoxScore
82 - 2021-12-21675Roadrunners1Monsters6WBoxScore
84 - 2021-12-23693Monsters3Rocket2WBoxScore
86 - 2021-12-25707Barracuda0Monsters1WBoxScore
87 - 2021-12-26715Monsters1Devils3LBoxScore
89 - 2021-12-28731Monsters4Senators1WBoxScore
92 - 2021-12-31751Crunch1Monsters5WBoxScore
95 - 2022-01-03774Thunderbirds4Monsters0LBoxScore
97 - 2022-01-05793Monsters2Griffins1WXBoxScore
99 - 2022-01-07807Bruins4Monsters1LBoxScore
100 - 2022-01-08822Monsters0Gulls4LBoxScore
102 - 2022-01-10839Monsters4Stars2WBoxScore
103 - 2022-01-11846Rampage2Monsters3WXXBoxScore
106 - 2022-01-14870Moose2Monsters6WBoxScore
107 - 2022-01-15883Monsters3Wolf Pack2WXXBoxScore
109 - 2022-01-17901Wolves2Monsters1LXBoxScore
111 - 2022-01-19917Monsters1Comets2LBoxScore
113 - 2022-01-21932Monsters9Reign1WBoxScore
114 - 2022-01-22940Penguins2Monsters0LBoxScore
118 - 2022-01-26967Marlies2Monsters1LXXBoxScore
120 - 2022-01-28989Monsters1Rampage2LBoxScore
121 - 2022-01-29996Monsters3Admirals1WBoxScore
122 - 2022-01-301006Americans2Monsters5WBoxScore
124 - 2022-02-011028Monsters2Admirals1WBoxScore
125 - 2022-02-021039Marlies2Monsters3WXBoxScore
128 - 2022-02-051062Monsters5Americans2WBoxScore
129 - 2022-02-061071Stars2Monsters1LXBoxScore
133 - 2022-02-101095Rocket4Monsters1LBoxScore
135 - 2022-02-121105Monsters5Bears2WBoxScore
137 - 2022-02-141121Monsters2Bruins3LXBoxScore
138 - 2022-02-151132Admirals2Monsters3WXXBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
141 - 2022-02-181149Monsters4Moose3WBoxScore
144 - 2022-02-211168Wild2Monsters3WXBoxScore
145 - 2022-02-221179Monsters1Wolves2LBoxScore
147 - 2022-02-241194Monsters3Checkers1WBoxScore
149 - 2022-02-261206Condors1Monsters3WBoxScore
151 - 2022-02-281228Stars3Monsters2LBoxScore
154 - 2022-03-031243Monsters3Sound Tigers1WBoxScore
155 - 2022-03-041255Monsters0Barracuda4LBoxScore
157 - 2022-03-061270Checkers5Monsters1LBoxScore
160 - 2022-03-091286Monsters0Rampage1LBoxScore
164 - 2022-03-131310Condors4Monsters6WBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance77,46538,433
Attendance PCT94.47%93.74%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
0 2827 - 94.23% 70,567$2,893,237$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
5,086,175$ 84,000$ 0$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 86,179$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 30,812$ 0$




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
Regular Season
12825322021312921741184126120102015187644127100111114187541182925328242901238579251208258688101662505138418105338315.57%5727087.76%91707271062.99%1238224555.14%709116360.96%237217381629547947509
13764621011342421509238211200113115744138259010211277651105242417659112092786820700668676715147144598814065299517.96%4315487.47%61490244360.99%1204208657.72%659104563.06%213515611561528899478
147642220314427115611538231101012137766138191102132134805410327148475511101127775229907587477731757503112314523345416.17%4315687.01%41366241056.68%1321230557.31%640110957.71%204314781655527908469
1582343404325227179484121160111111980394113180321410899988227424651080877856235007557468211907583113714524056516.05%4536685.43%11490259557.42%1305235755.37%645113956.63%218115761808570980504
168244250353224816088412013023211198336412412012111297752107248455703088982719221476771571342179353496013894577716.85%4064888.18%71469247859.28%1211226453.49%681113360.11%227616741741544943502
Total Regular Season39821912401311151612808194611991116405577641400241199108600868963941922052112802312359244889496389287114457673721375031618590257055927509225837416.56%229329487.18%2775221263659.53%62791125755.78%3334558959.65%1100980298396271846792464
Playoff
122016400000491930108200000219121082000002810183249831320601218174660143156146405121392396141149.93%1661093.98%338167356.61%36566654.80%16827960.22%509338516168266131
13514000001012-2211000005323030000059-4210172700053295038263112245807533515.15%36586.11%05813842.03%6416339.26%407652.63%10871129386230
141899000003743-61037000001026-16862000002717101837691060201610945201731271344371222623861071312.15%1161487.93%128158148.36%30161548.94%12625848.84%455313458143242118
Total Playoff43261700000967422221210000003638-221147000006036245296169265080333128101303543093119642887348572813211.39%3182990.88%4720139251.72%730144450.55%33461354.49%10737231104350570280