Crunch

GP: 53 | W: 15 | L: 35 | OTL: 3 | P: 33
GF: 162 | GA: 245 | PP%: 22.45% | PK%: 75.11%
GM : Nick Fournier | Morale : 50 | Team Overall : 64
Next Games #854 vs IceHogs

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# 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
1Matt BoldyX100.006935936980798268626765687262658650660
2Byron FroeseXX100.006637896478757966786264686378754850650
3Reid BoucherX100.005833726471859065746667636875695250650
4Austin CzarnikXX100.005235956467797566746567616877693650640
5Lane PedersonX100.008335956672807167756564626667634250640
6Matt PuempelX100.006946816278788363686564616675686750640
7Brendan PerliniXX100.005935926886727366556361586469658250630
8Karson KuhlmanXX100.008035916769777164656266626571664250630
9Mario KempeXXX100.006243836371807565696658566782733550620
10Christopher Wilkie (R)X100.006357686172787359625764636669645050610
11Mason ShawX100.005735746266687359716058565965666250590
12Chad Yetman (R)X100.005935935968727758526056575561635450580
13Maxime LajoieX100.005335957277817465306358625067645650640
14Wyatt NewpowerX100.007346806282737561305956634867644350630
15Nick EbertX100.006536816074798458305755594773675450620
16Joni TuulolaX100.007445865483889352305353564569654750620
17Lawrence PilutX100.005836906371777162306357645071664250620
18Michael Krutil (R)X100.007638895584677252305453604559596250600
19Ole Bjorgvik-HolmX100.006934835778727759305853564659615750600
20Brandon Crawley (R)X100.007660625678667153305250584567645350590
21Blake HillmanX100.006743835876726755305251544569654850580
Scratches
1Francis PerronX100.005943815768747957615956545769654750580
TEAM AVERAGE100.00664084627576776152605960576966535062
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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
1Logan Thompson100.00798785877877797877797867714350760
2Louis Domingue100.00748681857372747372747377835150740
Scratches
1Oscar Dansk100.00748382847372747372747373776650730
2Kaden Fulcher (R)100.00727169847170727170727165694450700
TEAM AVERAGE100.0075827985747375747375747175515073
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Mike Van Ryn66737071625784CAN4231,000,000$


Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
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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
1Lane PedersonCrunch (Tam)C53382866-2975515221437510721110.13%41112621.2514163096206000004160.32%123500031.1702001624
2Lawrence PilutCrunch (Tam)D53224365-19775128931875910011.76%124118222.311316291382000110117300.00%000001.1011001254
3Antoine RousselTampa LightningLW/RW50203656298220107961814513611.05%11120024.02418223618910162216251.15%56700000.9317220624
4Matt PuempelCrunch (Tam)LW53362056-2770201781092866517812.59%48112121.16119206215110161632358.06%6200021.0012022322
5Joni TuulolaCrunch (Tam)D53173653-241241012678167619410.18%96105819.971011211191710110127200.00%000001.0000002133
6Mason ShawCrunch (Tam)LW53171431-317010981051684411010.12%2872313.6600000000001272.00%5000030.8611101412
7Karson KuhlmanCrunch (Tam)C/RW528142210560797510334897.77%572814.001451046000002057.34%44300000.6000000100
8Maxime LajoieCrunch (Tam)D2044200022140.00%44522.870221900008000.00%000001.7500000010
9Austin CzarnikCrunch (Tam)C/RW22134000273628.57%03718.57011090000400100.00%100001.6200000100
10Byron FroeseCrunch (Tam)C/RW22134003083825.00%13718.6300039000041065.31%4900001.6100000011
11Matt BoldyCrunch (Tam)LW21235002615286.67%04723.7810148000090065.52%2900001.2600000000
12Brandon CrawleyCrunch (Tam)D210110001100100.00%1115.830000000000000.00%000001.7100000000
13Ole Bjorgvik-HolmCrunch (Tam)D2011100000010.00%2115.830000000000000.00%000001.7100000000
14Wyatt NewpowerCrunch (Tam)D21012204121350.00%34422.131011900006000.00%000000.4500000000
15Brendan PerliniCrunch (Tam)LW/RW2000020344110.00%03015.1900000000010050.00%200000.0000000000
16Chad YetmanCrunch (Tam)RW2000000010000.00%021.19000000000000100.00%100000.0000000000
17Christopher WilkieCrunch (Tam)RW2000100012130.00%063.250000000000000.00%000000.0000000000
18Nick EbertCrunch (Tam)D2000020210000.00%22412.280000000002000.00%000000.0000000000
19Mario KempeCrunch (Tam)C/LW/RW2000040132120.00%02814.4400000000000048.15%2700000.0000000000
20Michael KrutilCrunch (Tam)D2000000310110.00%12110.930000000000000.00%000000.0000000000
21Reid BoucherCrunch (Tam)LW2000120007130.00%14321.9800018000180083.33%600000.0000000000
22Blake HillmanCrunch (Tam)D3000040220200.00%1144.780000000000000.00%000000.0000000000
Team Total or Average398165200365-7057070888795151743295810.88%369754918.97557713247110222241367821857.97%247200080.97413347241720
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
1Logan ThompsonCrunch (Tam)22000.9750.50120011400000.000020100
Team Total or Average22000.9750.50120011400000.000020100


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
Austin CzarnikC/RW281992-12-12No175 Lbs5 ft9NoNoNo1UFAPro & Farm1,000,000$0$0$NoLink / NHL Link
Blake HillmanD251996-01-26No193 Lbs6 ft1NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Brandon CrawleyD241997-02-02Yes204 Lbs6 ft1NoNoNo1RFAPro & Farm300,000$0$0$No
Brendan PerliniLW/RW251996-04-27No211 Lbs6 ft3NoNoNo3RFAPro & Farm300,000$0$0$NoLink / NHL Link
Byron FroeseC/RW301991-03-12No202 Lbs6 ft1NoNoNo3UFAPro & Farm500,000$0$0$NoLink / NHL Link
Chad YetmanRW212000-02-18Yes179 Lbs5 ft11NoNoNo4ELCPro & Farm300,000$0$0$No
Christopher WilkieRW251996-07-10Yes190 Lbs6 ft0NoNoNo4RFAPro & Farm300,000$0$0$No
Francis PerronLW251996-04-18No166 Lbs6 ft0NoNoNo3RFAPro & Farm300,000$0$0$NoLink / NHL Link
Joni TuulolaD251996-01-01No198 Lbs6 ft3NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Kaden FulcherG231998-09-23Yes201 Lbs6 ft3NoNoNo1RFAPro & Farm300,000$0$0$No
Karson KuhlmanC/RW261995-09-26No190 Lbs5 ft10NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Lane PedersonC241997-08-04No190 Lbs6 ft0NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Lawrence PilutD251995-12-30No194 Lbs5 ft11NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Logan ThompsonG241997-02-25No201 Lbs6 ft4NoNoNo2RFAPro & Farm900,000$0$0$NoLink
Louis DomingueG291992-03-06No208 Lbs6 ft3NoNoNo2UFAPro & Farm750,000$0$0$NoLink / NHL Link
Mario KempeC/LW/RW331988-09-19No185 Lbs6 ft0NoNoNo2UFAPro & Farm300,000$0$0$NoLink / NHL Link
Mason ShawLW221998-11-03No182 Lbs5 ft9NoNoNo2ELCPro & Farm500,000$0$0$NoLink / NHL Link
Matt BoldyLW202001-04-05No196 Lbs6 ft2NoNoNo4ELCPro & Farm900,000$0$0$NoLink
Matt PuempelLW281993-01-24No201 Lbs6 ft1NoNoNo1UFAPro & Farm500,000$0$0$NoLink / NHL Link
Maxime LajoieD231997-11-05No196 Lbs6 ft1NoNoNo1RFAPro & Farm300,000$0$0$NoLink / NHL Link
Michael KrutilD192002-06-03Yes202 Lbs6 ft3NoNoNo1ELCPro & Farm0$0$No
Nick EbertD271994-05-11No200 Lbs6 ft0NoNoNo1RFAPro & Farm500,000$0$0$NoLink / NHL Link
Ole Bjorgvik-HolmD192002-05-23No190 Lbs6 ft2NoNoNo4ELCPro & Farm300,000$0$0$NoLink
Oscar DanskG271994-02-28No204 Lbs6 ft3NoNoNo1RFAPro & Farm500,000$0$0$NoLink / NHL Link
Reid BoucherLW281993-09-08No195 Lbs5 ft10NoNoNo4UFAPro & Farm1,000,000$0$0$NoLink / NHL Link
Wyatt NewpowerD231997-12-09No194 Lbs6 ft3NoNoNo2RFAPro & Farm300,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2624.92194 Lbs6 ft12.19444,231$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Matt BoldyByron FroeseAustin Czarnik40122
2Reid BoucherLane PedersonKarson Kuhlman30122
3Matt PuempelMario KempeBrendan Perlini20122
4Mason ShawMatt BoldyChristopher Wilkie10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Maxime LajoieWyatt Newpower40122
2Joni TuulolaLawrence Pilut30122
3Nick EbertMichael Krutil20122
4Ole Bjorgvik-HolmBrandon Crawley10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Matt BoldyByron FroeseAustin Czarnik60122
2Reid BoucherLane PedersonKarson Kuhlman40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Maxime LajoieWyatt Newpower60122
2Joni TuulolaLawrence Pilut40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Matt BoldyReid Boucher60122
2Byron FroeseAustin Czarnik40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Maxime LajoieWyatt Newpower60122
2Joni TuulolaLawrence Pilut40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Matt Boldy60122Maxime LajoieWyatt Newpower60122
2Reid Boucher40122Joni TuulolaLawrence Pilut40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Matt BoldyReid Boucher60122
2Byron FroeseAustin Czarnik40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Maxime LajoieWyatt Newpower60122
2Joni TuulolaLawrence Pilut40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Matt BoldyByron FroeseAustin CzarnikMaxime LajoieWyatt Newpower
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Matt BoldyByron FroeseAustin CzarnikMaxime LajoieWyatt Newpower
Extra Forwards
Normal PowerPlayPenalty Kill
Chad Yetman, Matt Puempel, Brendan PerliniChad Yetman, Matt PuempelBrendan Perlini
Extra Defensemen
Normal PowerPlayPenalty Kill
Blake Hillman, Nick Ebert, Michael KrutilBlake HillmanNick Ebert, Michael Krutil
Penalty Shots
Matt Boldy, Reid Boucher, Byron Froese, Austin Czarnik, Lane Pederson
Goalie
#1 : Logan Thompson, #2 : Louis Domingue


Filter Tips
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1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
5333W21622454071582177253553087911
All Games
GPWLOTWOTL SOWSOLGFGA
5313351211162245
Home Games
GPWLOTWOTL SOWSOLGFGA
26618010179122
Visitor Games
GPWLOTWOTL SOWSOLGFGA
27717111083123
Last 10 Games
WLOTWOTL SOWSOL
440110
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
2455522.45%2295775.11%2
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
539474564137237515
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
648154641.91%597151639.38%36685942.61%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
11388181472358583273


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 - 2021-10-015Rampage3Crunch2LBoxScore
3 - 2021-10-0324Crunch3Heat4LXBoxScore
5 - 2021-10-0537Crunch2Marlies7LBoxScore
6 - 2021-10-0645Crunch5Heat8LBoxScore
8 - 2021-10-0862Americans6Crunch4LBoxScore
10 - 2021-10-1086Thunderbirds4Crunch0LBoxScore
13 - 2021-10-13103Rocket5Crunch2LBoxScore
15 - 2021-10-15118Crunch1Americans6LBoxScore
16 - 2021-10-16129Crunch1Admirals2LBoxScore
18 - 2021-10-18147Crunch3Rocket4LBoxScore
19 - 2021-10-19159Bears6Crunch4LBoxScore
22 - 2021-10-22179Crunch4Checkers8LBoxScore
23 - 2021-10-23190Rampage5Crunch4LXXBoxScore
26 - 2021-10-26212Condors5Crunch3LBoxScore
29 - 2021-10-29230Crunch0Wolves7LBoxScore
30 - 2021-10-30244Comets3Crunch5WBoxScore
32 - 2021-11-01253Crunch7IceHogs3WBoxScore
34 - 2021-11-03276Crunch2Bruins3LBoxScore
35 - 2021-11-04284Wild4Crunch1LBoxScore
38 - 2021-11-07307Wolves5Crunch1LBoxScore
41 - 2021-11-10328Condors3Crunch6WBoxScore
43 - 2021-11-12340Crunch0Devils4LBoxScore
45 - 2021-11-14352Crunch8Palm Springs7WXBoxScore
47 - 2021-11-16374Wolf Pack5Crunch1LBoxScore
49 - 2021-11-18392Crunch7Marlies1WBoxScore
50 - 2021-11-19405Heat5Crunch7WBoxScore
54 - 2021-11-23428Eagles2Crunch5WBoxScore
56 - 2021-11-25450Monsters6Crunch2LBoxScore
58 - 2021-11-27465Crunch3Wolf Pack2WBoxScore
60 - 2021-11-29481Crunch3Palm Springs4LBoxScore
61 - 2021-11-30493Admirals5Crunch1LBoxScore
63 - 2021-12-02513Crunch2Admirals8LBoxScore
65 - 2021-12-04523Comets9Crunch3LBoxScore
67 - 2021-12-06547Griffins6Crunch5LBoxScore
69 - 2021-12-08557Crunch3Eagles2WBoxScore
71 - 2021-12-10579Gulls6Crunch4LBoxScore
72 - 2021-12-11588Crunch3Barracuda6LBoxScore
74 - 2021-12-13605Crunch3Phantoms5LBoxScore
75 - 2021-12-14618Bruins6Crunch2LBoxScore
78 - 2021-12-17639Crunch1Comets6LBoxScore
80 - 2021-12-19655Penguins5Crunch2LBoxScore
82 - 2021-12-21673Crunch1Wild9LBoxScore
83 - 2021-12-22685Griffins2Crunch3WBoxScore
86 - 2021-12-25706Crunch2Americans3LBoxScore
88 - 2021-12-27719Senators3Crunch4WBoxScore
90 - 2021-12-29738Rampage4Crunch1LBoxScore
92 - 2021-12-31751Crunch1Monsters5LBoxScore
93 - 2022-01-01763Crunch6IceHogs5WXXBoxScore
95 - 2022-01-03775Crunch4Roadrunners3WBoxScore
96 - 2022-01-04787Americans5Crunch4LXBoxScore
99 - 2022-01-07810Rocket4Crunch3LBoxScore
101 - 2022-01-09834Crunch3Eagles0WBoxScore
102 - 2022-01-10842Crunch5Moose1WBoxScore
104 - 2022-01-12854IceHogs-Crunch-
106 - 2022-01-14868Crunch-Wild-
107 - 2022-01-15882Marlies-Crunch-
109 - 2022-01-17899Crunch-Reign-
111 - 2022-01-19912Phantoms-Crunch-
113 - 2022-01-21927Crunch-Rampage-
115 - 2022-01-23946Crunch-Rocket-
116 - 2022-01-24952Thunderbirds-Crunch-
118 - 2022-01-26971Crunch-Thunderbirds-
119 - 2022-01-27985Palm Springs-Crunch-
121 - 2022-01-29998Crunch-Heat-
122 - 2022-01-301015Checkers-Crunch-
124 - 2022-02-011029Crunch-Stars-
126 - 2022-02-031043Crunch-Sound Tigers-
127 - 2022-02-041053Barracuda-Crunch-
128 - 2022-02-051066Crunch-Wolves-
131 - 2022-02-081084Devils-Crunch-
133 - 2022-02-101094Crunch-Heat-
135 - 2022-02-121106Crunch-Condors-
136 - 2022-02-131118Reign-Crunch-
139 - 2022-02-161134Crunch-Griffins-
Trade Deadline --- Trades can’t be done after this day is simulated!
141 - 2022-02-181150Sound Tigers-Crunch-
143 - 2022-02-201158Crunch-Checkers-
145 - 2022-02-221183Roadrunners-Crunch-
147 - 2022-02-241193Crunch-Marlies-
149 - 2022-02-261214Stars-Crunch-
154 - 2022-03-031248Moose-Crunch-
157 - 2022-03-061273Bears-Crunch-
163 - 2022-03-121303Stars-Crunch-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance49,17524,353
Attendance PCT94.57%93.67%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
15 2828 - 94.27% 70,617$1,836,050$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
687,676$ 115,500$ 0$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 69,513$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
1,059,260$ 63 6,761$ 425,943$




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
12824224045432491727741221102132129824741201302411120903010824944669511101008259220907137227491711511139218355107414.51%5767287.50%41584255661.97%1364233558.42%730118261.76%225316091733575989519
137638250452221917247381615023111108723382210022111098524952193866051120747960194205796916561716532120416284426314.25%5016287.62%71315230057.17%1227222855.07%613109256.14%199214051686539920480
14764024032432331409338221000141125656038181403102108753399233426659210090756122100746698748171852895914343385716.86%3784288.89%51375243956.38%1220228353.44%609108756.03%199214231706527906471
158243250363225618769412290342113479554121160021112210814106256469725180967975252208318448261834508102713824586313.76%4096185.09%71643275559.64%1282226256.68%716121059.17%223116161760567974508
1653133501211162245-83266180010179122-43277170111083123-403316224540711723751515825394745641317725355308792455522.45%2295775.11%2648154641.91%597151639.38%36685942.61%11388181472358583273
Total Regular Season36917613301520141111199162031848863071010657743514218588700810455424816144111191972309164272397366260104655393343351929928751261451127158199331215.65%209329485.95%2565651159656.61%56901062453.56%3034543055.87%960868738358256943742254
Playoff
1151400000616-102020000017-63120000059-4261218000051810203427125301361233425.88%57984.21%06714446.53%9817655.68%366654.55%10566132406229
1251400000515-102110000055030300000010-10251015010113810262628145358913016212.50%38781.58%07513256.82%9217054.12%356553.85%10063138376329
1412750000024195541000001073734000001412214244165020104734901039487330981252479477.45%54590.74%024049348.68%21547545.26%8018942.33%34723937211218390
15514000001319-62020000049-531200000910-12132336010355134040484612429598327725.93%26773.08%06516439.63%5112341.46%277237.50%11378124376230
Total Playoff271017000004869-211156000002028-816511000002841-1320488613404014151664501892021887241924095831711810.53%1752884.00%044793347.91%45694448.31%17839245.41%666447767227371179