Comets

GP: 21 | W: 16 | L: 3 | OTL: 2 | P: 34
GF: 81 | GA: 60 | PP%: 16.00% | PK%: 79.41%
GM : Mathieu Turcotte | Morale : 75 | Team Overall : 63
Next Games #364 vs Americans

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
1JJ Peterka (R)0XX100.00593489767286897556717365766268075690
2Ryan Donato0XX100.00715885697281887075686762657168075670
3Nathan Bastian (R)0X100.00827779658780786357646276616870075660
4Adam Edstrom0X100.00864189629976695956576364586566075640
5Cole Guttman (R)0X100.00623883686386826781656662686567075640
6Jiri Kulich (R)0X100.00683888677591826563586462666167075640
7Brendan Perlini0XX100.00774180638695715760596261586870075630
8Matthew Phillips (R)0XX100.00593495656082806461626360646668075630
9Jakob Pelletier (R)0X100.00633687666385766560636261666465075630
10Isaac Ratcliffe (R)0X100.00835069579274815653545558526567075610
11Marco Kasper (R)0X100.00733787597485735860575663596264075610
12Graham Slaggert (R)0X100.00603789586973805760545653556567075590
13Philip Broberg (R)0X100.00753995658979816330675864506365075650
14Matt Irwin0X100.00765383628078845730605668487879075640
15Jordan Gross0X100.00613782656886806330626461536971075630
16Jake Livingstone (R)0X100.00734080648881736330655260486567075630
17Kevin Gravel0X100.00763991608780855830605366477274075630
18Jack Thompson (R)0X100.00673792637584855930625764496264075620
19Tyler Tucker (R)0X100.00726761637880785830625961536466075620
Scratches
1Aliaksei Protas (R)0XX100.00824095679781876966686065626465075670
2Robert Mastrosimone (R)0X100.00553973586481675659575452556365075580
3Dmitry Zlodeyev (R)0X100.00603695556961635456525350556264075570
4Corson Ceulemans (R)0X100.00713991588064705730555356466163075590
5Nicolas Beaudin (R)0X100.00573874636665705730645154466567075590
6Thomas Miller (R)0X100.00683894547765755230535156456567075580
TEAM AVERAGE100.0069438563777978614961596156656707563
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
1Mads Sogaard100.0078858195777678777678776471075680
2Dennis Hildeby (R)100.0071787491706971706971706369075630
Scratches
TEAM AVERAGE100.007582789374737574737574647007566
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Ben Simon66636475696580USA4531,000,000$


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
1JJ PeterkaComets (VAN)LW/RW21161430600849131336112.21%847822.781231966000172252.46%6100001.2500000213
2Jiri KulichComets (VAN)RW217142180018219421677.45%138118.181561457000003048.28%2900001.1000000104
3Cole GuttmanComets (VAN)C2161420800236456245310.71%341519.812241066000050052.54%57100000.9600000021
4Nathan BastianComets (VAN)RW2161218722090388320777.23%442920.450229650000231053.57%2800000.8400000310
5Ryan DonatoComets (VAN)C/LW21891724021438321589.64%436217.251341968000001057.14%3500000.9400000110
6Adam EdstromComets (VAN)C2179168160543147113314.89%1037017.662139340223641046.88%48000000.8600000202
7Philip BrobergComets (VAN)D2141115540442533131912.12%3050624.112131668101255100.00%000000.5900000031
8Aliaksei ProtasComets (VAN)C/LW176814929534386114479.84%230718.0710113380000162152.28%39400000.9100001120
9Kevin GravelComets (VAN)D2139121516032162491912.50%2941719.890221052101142000.00%000000.5700000110
10Brendan PerliniComets (VAN)LW/RW174711560341427132914.81%526115.39112425000091038.89%1800000.8400000003
11Jakob PelletierComets (VAN)LW21561162013303793313.51%328813.75000000112592041.67%10800000.7600000002
12Jordan GrossComets (VAN)D1828101740916227139.09%1827815.451231034000032000.00%000000.7200000020
13Matthew PhillipsComets (VAN)C/RW212685205244216304.76%427413.0600000000000050.00%2000000.5800000000
14Tyler TuckerComets (VAN)D2126841955217195810.53%1834516.4601126000013000.00%000000.4600001010
15Jack ThompsonComets (VAN)D211454801020145117.14%2735616.9700001000127100.00%000000.2800000000
16Jake LivingstoneComets (VAN)D17235-32086204100.00%71136.680000000003100.00%000000.8800000000
17Matt IrwinComets (VAN)D21055540105219198100.00%2443920.92011217000042000.00%000000.2300011010
18Marco KasperComets (VAN)C210222201119154110.00%21567.470111180001270051.78%19700000.2500000000
19Graham SlaggertComets (VAN)C7000000000000.00%000.09000000000000100.00%100000.0000000000
20Isaac RatcliffeComets (VAN)LW21000000001010.00%000.030000000000000.00%000000.0000000000
Team Total or Average391811472281131762051849081023358410.00%199618515.821224361386222351143116350.31%194200000.7400013111516
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
1Mads SogaardComets (VAN)2116320.9072.85119962576140000.0000210211
2Dennis HildebyComets (VAN)20000.9461.8864002370010.0000021000
Team Total or Average2316320.9092.80126462596510010.00002121211


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
Adam EdstromC232000-10-12No234 Lbs6 ft7NoNoNo3RFAPro & Farm999,999$0$0$NoLink
Aliaksei Protas (1 Way Contract)C/LW232001-01-06Yes225 Lbs6 ft6NoNoNo1RFAPro & Farm1,160,000$1,160,000$834,490$NoLink / NHL Link
Brendan PerliniLW/RW281996-04-27No211 Lbs6 ft3NoNoNo2UFAPro & Farm800,000$0$0$NoLink / NHL Link
Cole GuttmanC251999-04-06Yes167 Lbs5 ft9NoNoNo2RFAPro & Farm950,000$0$0$NoLink / NHL Link
Corson CeulemansD212003-05-05Yes198 Lbs6 ft2NoNoNo2RFAPro & Farm950,000$0$0$NoLink / NHL Link
Dennis HildebyG232001-08-19Yes209 Lbs6 ft5NoNoNo2RFAPro & Farm950,000$0$0$NoLink / NHL Link
Dmitry ZlodeyevC222002-02-15Yes185 Lbs5 ft11NoNoNo3RFAPro & Farm950,000$0$0$No
Graham SlaggertC251999-04-06Yes183 Lbs5 ft11NoNoNo2RFAPro & Farm950,000$0$0$NoLink / NHL Link
Isaac RatcliffeLW251999-02-15Yes200 Lbs6 ft6NoNoNo2RFAPro & Farm800,000$0$0$NoLink / NHL Link
JJ PeterkaLW/RW222002-01-14Yes189 Lbs6 ft0NoNoNo1RFAPro & Farm950,000$0$0$NoLink / NHL Link
Jack ThompsonD222002-04-19Yes189 Lbs6 ft1NoNoNo2RFAPro & Farm950,000$0$0$NoLink / NHL Link
Jake LivingstoneD251999-04-16Yes205 Lbs6 ft3NoNoNo3RFAPro & Farm950,000$0$0$No
Jakob PelletierLW232001-03-07Yes170 Lbs5 ft9NoNoNo1RFAPro & Farm950,000$0$0$NoLink / NHL Link
Jiri KulichRW202004-04-14Yes186 Lbs6 ft1NoNoNo2RFAPro & Farm950,000$0$0$NoLink / NHL Link
Jordan GrossD291995-05-09No190 Lbs5 ft10NoNoNo2UFAPro & Farm836,000$0$0$NoLink / NHL Link
Kevin GravelD321992-03-06No205 Lbs6 ft4NoNoNo2UFAPro & Farm999,999$0$0$NoLink / NHL Link
Mads SogaardG232000-12-13No196 Lbs6 ft7NoNoNo3RFAPro & Farm964,000$0$0$NoLink / NHL Link
Marco KasperC202004-04-08Yes183 Lbs6 ft1NoNoNo3RFAPro & Farm950,000$0$0$No
Matt IrwinD361987-11-29No200 Lbs6 ft2NoNoNo2UFAPro & Farm999,999$0$0$NoLink / NHL Link
Matthew PhillipsC/RW261998-04-06Yes160 Lbs5 ft8NoNoNo2RFAPro & Farm900,000$0$0$NoLink / NHL Link
Nathan BastianRW261997-12-06Yes205 Lbs6 ft4NoNoNo1RFAPro & Farm850,000$0$0$NoLink / NHL Link
Nicolas BeaudinD241999-10-07Yes168 Lbs5 ft11NoNoNo2RFAPro & Farm825,000$0$0$NoLink / NHL Link
Philip BrobergD232001-06-25Yes212 Lbs6 ft4NoNoNo1RFAPro & Farm950,000$0$0$NoLink / NHL Link
Robert MastrosimoneLW232001-01-24Yes170 Lbs5 ft10NoNoNo3RFAPro & Farm950,000$0$0$No
Ryan DonatoC/LW281996-04-09No190 Lbs6 ft0NoNoNo2UFAPro & Farm999,999$0$0$NoLink / NHL Link
Thomas MillerD251999-03-06Yes181 Lbs6 ft2NoNoNo2RFAPro & Farm950,000$0$0$NoLink / NHL Link
Tyler TuckerD242000-03-01Yes204 Lbs6 ft1NoNoNo2RFAPro & Farm868,000$0$0$NoLink / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2724.67193 Lbs6 ft22.04937,148$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1JJ PeterkaCole GuttmanNathan Bastian35122
2Brendan PerliniJakob PelletierJiri Kulich30122
3Ryan DonatoAdam EdstromMatthew Phillips25122
4Ryan DonatoMarco KasperJJ Peterka10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Philip BrobergMatt Irwin40122
2Kevin GravelJake Livingstone30122
3Tyler TuckerJack Thompson30122
4Philip BrobergMatt Irwin0122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1JJ PeterkaCole GuttmanNathan Bastian60122
2Adam EdstromMarco KasperJiri Kulich40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Philip BrobergRyan Donato60122
2Kevin GravelMatt Irwin40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Adam EdstromJJ Peterka60140
2Marco KasperNathan Bastian40140
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Philip BrobergMatt Irwin60122
2Kevin GravelTyler Tucker40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1JJ Peterka60122Philip BrobergMatt Irwin60122
2Ryan Donato40122Kevin GravelJack Thompson40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1JJ PeterkaRyan Donato60122
2Adam EdstromNathan Bastian40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Philip BrobergMatt Irwin60122
2Kevin GravelJack Thompson40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
JJ PeterkaRyan DonatoNathan BastianPhilip BrobergMatt Irwin
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
JJ PeterkaRyan DonatoNathan BastianPhilip BrobergMatt Irwin
Extra Forwards
Normal PowerPlayPenalty Kill
Marco Kasper, Cole Guttman, Adam EdstromMarco Kasper, Cole GuttmanAdam Edstrom
Extra Defensemen
Normal PowerPlayPenalty Kill
Tyler Tucker, Jack Thompson, Kevin GravelTyler TuckerJack Thompson, Kevin Gravel
Penalty Shots
JJ Peterka, Ryan Donato, Adam Edstrom, Nathan Bastian, Jiri Kulich
Goalie
#1 : Mads Sogaard, #2 : Dennis Hildeby
Custom OT Lines Forwards
JJ Peterka, Ryan Donato, Jakob Pelletier, Nathan Bastian, Jiri Kulich, Cole Guttman, Cole Guttman, Adam Edstrom, Marco Kasper, Matthew Phillips, Brendan Perlini
Custom OT Lines Defensemen
Philip Broberg, Matt Irwin, Kevin Gravel, Jake Livingstone, Tyler Tucker


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
2134OTL18114722881065219918251812
All Games
GPWLOTWOTL SOWSOLGFGA
2115312008160
Home Games
GPWLOTWOTL SOWSOLGFGA
118111004428
Visitor Games
GPWLOTWOTL SOWSOLGFGA
107201003732
Last 10 Games
WLOTWOTL SOWSOL
720100
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
751216.00%681479.41%2
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
26930423253627171
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
43685351.11%36772550.62%17435748.74%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
533374460152271138


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
6 - 2024-10-099Wranglers4Comets5WXBoxScore
8 - 2024-10-1122Phantoms2Comets3WBoxScore
12 - 2024-10-1548Comets5Crunch2WBoxScore
14 - 2024-10-1765Comets3Checkers2WBoxScore
16 - 2024-10-1982Comets3Phantoms2WBoxScore
19 - 2024-10-22100Comets4IceHogs1WBoxScore
23 - 2024-10-26133Penguins5Comets4LXBoxScore
25 - 2024-10-28146Wolves3Comets5WBoxScore
27 - 2024-10-30159Devils3Comets6WBoxScore
30 - 2024-11-02184Comets3Barracuda5LBoxScore
33 - 2024-11-05203Comets4Gulls3WBoxScore
35 - 2024-11-07218Comets4Reign3WBoxScore
37 - 2024-11-09235Condors0Comets3WBoxScore
40 - 2024-11-12250Wranglers1Comets4WBoxScore
42 - 2024-11-14265Sound Tigers1Comets4WBoxScore
44 - 2024-11-16283IceHogs5Comets1LBoxScore
45 - 2024-11-17285Admirals4Comets6WBoxScore
47 - 2024-11-19300Wolf Pack0Comets3WBoxScore
51 - 2024-11-23323Comets3Senators6LBoxScore
54 - 2024-11-26345Comets5Bruins4WBoxScore
55 - 2024-11-27354Comets3Penguins4LXBoxScore
57 - 2024-11-29364Comets-Americans-
59 - 2024-12-01388Comets-Griffins-
61 - 2024-12-03402Comets-Wild-
64 - 2024-12-06422Monsters-Comets-
66 - 2024-12-08437Crunch-Comets-
68 - 2024-12-10455Thunderbirds-Comets-
70 - 2024-12-12471Checkers-Comets-
72 - 2024-12-14486Bruins-Comets-
74 - 2024-12-16496Eagles-Comets-
76 - 2024-12-18510Comets-Roadrunners-
77 - 2024-12-19519Comets-Silver Knights-
79 - 2024-12-21537Senators-Comets-
81 - 2024-12-23555Barracuda-Comets-
86 - 2024-12-28567Firebirds-Comets-
89 - 2024-12-31600Comets-Wranglers-
91 - 2025-01-02613Comets-Firebirds-
92 - 2025-01-03619Admirals-Comets-
95 - 2025-01-06638Comets-Rocket-
97 - 2025-01-08650Comets-Bears-
99 - 2025-01-10666Comets-Wolves-
100 - 2025-01-11672Comets-Marlies-
103 - 2025-01-14702Comets-Moose-
105 - 2025-01-16719Reign-Comets-
107 - 2025-01-18735Condors-Comets-
110 - 2025-01-21755Americans-Comets-
112 - 2025-01-23768Comets-Condors-
114 - 2025-01-25786Bears-Comets-
116 - 2025-01-27796Comets-Thunderbirds-
118 - 2025-01-29810Comets-Admirals-
120 - 2025-01-31823Comets-Stars-
122 - 2025-02-02842Griffins-Comets-
124 - 2025-02-04855Eagles-Comets-
126 - 2025-02-06870Comets-Barracuda-
128 - 2025-02-08884Marlies-Comets-
142 - 2025-02-22905Comets-Silver Knights-
143 - 2025-02-23915Comets-Roadrunners-
146 - 2025-02-26932Comets-Reign-
147 - 2025-02-27944Comets-Gulls-
149 - 2025-03-01960Comets-Firebirds-
153 - 2025-03-05986Gulls-Comets-
155 - 2025-03-071000Wild-Comets-
157 - 2025-03-091019Stars-Comets-
159 - 2025-03-111032Rocket-Comets-
160 - 2025-03-121037Comets-Wranglers-
163 - 2025-03-151065IceHogs-Comets-
164 - 2025-03-161071Roadrunners-Comets-
166 - 2025-03-181086Moose-Comets-
168 - 2025-03-201095Comets-Thunderbirds-
170 - 2025-03-221104Comets-Wolf Pack-
172 - 2025-03-241125Comets-Devils-
174 - 2025-03-261139Comets-Sound Tigers-
176 - 2025-03-281155Comets-Monsters-
Trade Deadline --- Trades can’t be done after this day is simulated!
178 - 2025-03-301172Comets-Moose-
181 - 2025-04-021196Firebirds-Comets-
184 - 2025-04-051212Gulls-Comets-
185 - 2025-04-061229Silver Knights-Comets-
187 - 2025-04-081242Comets-Stars-
189 - 2025-04-101256Comets-Eagles-
191 - 2025-04-121273Wild-Comets-
193 - 2025-04-141290Barracuda-Comets-
195 - 2025-04-161305Silver Knights-Comets-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price2515
Attendance21,82110,896
Attendance PCT99.19%99.05%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
-1 2974 - 99.14% 80,564$886,206$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
958,100$ 2,414,300$ 2,414,300$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 677,490$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
-80,564$ 141 17,420$ 2,456,220$




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
580343503224279275440151702114149144540191801110130131-184279464743140831048728150899988913253692578122032075526.57%1825072.53%7848162552.18%728143850.63%660131950.04%161678417559481731872
6803532054222632323140201305200139974240151900222124135-11902634276900110571009923580702801836229679755721912032914.29%1623479.01%4801155051.68%735152248.29%543117146.37%1569742353819051736875
776392606410263204593818130430011610412382113021101471004796263430693150601128425660780951814228374252520092014723.38%1543179.87%9861157054.84%865160653.86%620118252.45%156479714307461583805
876402204253304229753823802131160111493817140212214411826103304500804350861129727340902938881241582071621622246328.13%1752983.43%41051183557.28%950171055.56%668116557.34%160584814737421525762
980322504106330026634401611026501501292140161402413150137139730048978931083108993030010241066922243084844224811863518.82%1713181.87%31071192455.67%894164954.21%629119552.64%176296315137751585779
108042210226726521055402190115313596394021120111413011416109265432697380639210227200826908946241180466620761957236.92%2265675.22%8951177753.52%891178649.89%618112754.84%164483515358131690832
11803828043522512213040181302142128101274020150221012312039925142667704049104892978093910091004237878566923782346226.50%2385576.89%4995193951.32%903171352.71%594112752.71%175694614827871608786
127638220237426521649381911022311301012938191100143135115201012654336981205110996280908621002903260484968620482235424.22%2166271.30%2925182150.80%953185351.43%566111650.72%162786414927511501749
138041180865228919891402780122014983664014100743214011525116289484773120751188330860100510351007255887241821252095526.32%1613677.64%41021199651.15%909176851.41%553111649.55%174393915137741599798
148038230562626820662402080431414210141401815013121261052110226844871634084997827960967926874263392662420422105325.24%1913979.58%5947183651.58%966180853.43%611111754.70%166585815607851633824
1580263206475210219-9401715022131211174409170426289102-138721033454437037778321490581753778264893125817201725833.72%933958.06%2801156251.28%853169350.38%521101351.43%152969015907891757929
1676223106359183208-253813140421498104-6389170214585104-197818332450721060535919720669674594227267640413992614718.01%1723281.40%11170224852.05%1305252651.66%612116252.67%1785121418525781002499
178036320322520718918401719011029496-24019130212311393208920737157832057727323320744773796239271345215412725319.49%2023085.15%11299261849.62%1304266748.89%548119245.97%1926132218735951039523
18762731022410171210-393813160101789113-24381415012338297-157817130447516057604819460626664626250774162716621782815.73%2733985.71%21067221948.08%1434283550.58%565115548.92%1696112819325881009482
1982314102350202226-244117200013098100-241142102220104126-227920236656823075685220670673709676228566133514081743520.11%1492483.89%01140230749.41%1195247648.26%593126646.84%1965134819045901080545
208252220222228120972412510021211451014441271200101136108281162815137942100919888288908681039971247273562818953448625.00%2724184.93%21648307853.54%1514276854.70%671129951.66%2040140518336081075553
2182363501514285297-1241152101301141155-14412114002131441422852855147992408792104322701078106910643559104355022152324619.83%2474780.97%11311308542.50%1397348540.09%559131042.67%181212662164581978467
2282283708414285303-1841141803402143147-441141905012142156-1482285513798530102849032320110610121060328296454320142284218.42%2344979.06%21499313047.89%1447320745.12%628138145.47%1901134020595821010489
238236360190032531213412217002001691482141141901700156164-883325576901211351018813246107010701090163206100570920122344017.09%2707472.59%01614317550.83%1529321647.54%742143751.64%1944139020045741001489
202282412903540418350684120160221019716433412113013302211863510141875211704017611711893588117712041178453311100551219952306026.09%2296870.31%31583313950.43%1468316546.38%710153446.28%1886134520565711009488
20238245310141034530045411820012001641604412711002101811404198345605950031281141013338511421118110820298284256620562666323.68%2385178.57%41643327250.21%1457293649.63%716143150.03%2038144218695701033524
202421153012008160211181011004428161072001003732534811472281236271718102693042325652199182518751216.00%681479.41%243685351.11%36772550.62%17435748.74%533374460152271138
Total Regular Season1695772612079877372574051406008483962980434333352901250040184737631403644403728392640199200757409852155924388475161619861525587353658189471992515751561121788311850421504758109523.01%432393178.46%70246824855950.83%240644855249.56%131012617250.06%376172284938898158142846614218
Playoff
7624000001919031200000981312000001011-14192948000478194054657522784181575240.00%10370.00%17412957.36%5612744.09%508360.24%116601245511859
8514000001518-331200000111012020000048-421524390004381800595762188813313120210.00%9188.89%06010855.56%6713250.76%397651.32%1095899489651
9404000001219-720200000712-52020000057-201222340005611610526049166502010317529.41%9188.89%06111851.69%7912364.23%326847.06%854886377135
1024159000008369141192000003923161367000004446-230831352180001933298980294325269956304204588481225.00%652364.62%430862349.44%32863851.41%18736451.37%496261502236478239
111257000003239-75320000017170725000001522-710325890000714843801341571335071699735020315.00%42880.95%013827849.64%16231451.59%9217652.27%253135257115226113
1213760000037334633000002016474300000171701437619810011111551901821841495171786635527933.33%23865.22%016032848.78%18735352.97%11820557.56%281153272124251126
13624000001819-13120000098131200000911-241833511004772180717869218885015615640.00%25868.00%08015850.63%7315148.34%418448.81%130701135611655
14241410000008073713103000004232101147000003841-32880142222000233122943032529730386728495725471123.40%41782.93%030864048.13%26956447.70%18536350.96%528297476229461226
171257000002729-25140000079-27430000020200102748750107125338090117944441179422643613.95%47882.98%020341449.03%21949344.42%8418645.16%2972043269716477
20514000001316-33120000078-12020000068-221323360003641600445362168515812422627.27%22768.18%09317453.45%8319841.92%489252.17%12283116366635
23514000001323-102020000049-531200000914-521324370006611680536748175603011417317.65%15380.00%08918448.37%7917445.40%429245.65%11883117356331
2022624000002427-3321000001512330300000915-642444680099602177771654213484014519421.05%18572.22%012124349.79%10420351.23%3910437.50%13995147458039
202313760000051474633000002020074300000312741451891400024151205011621701561345213798332351234.29%401075.00%127251952.41%24445353.86%11622551.56%3182203089517184
Total Playoff135627300000424431-7653530000002071842370274300000217247-301244247321156213311715410849352391599168113305098165190335063358124.18%3669274.86%61967391650.23%1950392349.71%1073211850.66%299817712947121623661174