Monsters
GP: 80 | W: 39 | L: 33 | OTL: 8 | P: 86
GF: 331 | GA: 330 | PP%: 18.73% | PK%: 81.02%
GM : Yann Laforest | Morale : 42 | Team Overall : 64
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 SPAgeContractSalary
1Emerson Etem (R)X100.007229807372737571677085646750464562700231800,000$
2Andrew GordonX100.006241776478636668667771626975701831680301850,000$
3Matt CalvertX100.006625747274807173636378607462563324680261900,000$
4Justin Florek (R)X100.007431766474736968716873606860593362670251600,000$
5Dominik Simon (R)X100.005740836459755978747071575148486746660212500,000$
6Ondrej Kase (R)X100.007148816966657164667367637141416640660191500,000$
7Mitch Marner (R)X100.006036806353747068878467446040409460650182500,000$
8Bobby FarnhamX100.007669646280628063626563607068663353650261500,000$
9Jared Knight (R)X100.006221726268697165687069616446454148640231600,000$
10Austin Watson (R)X100.006928766266666865666269606246454057630232600,000$
11Maxim Mamin (R)X100.005634726853646661635860535842425932590202500,000$
12Beau Starrett (R)X100.004441594853595451545359364541415249500191500,000$
13Cameron Hughes (R)X100.005026634761565453544847414642426621490192500,000$
14Roman JosiX100.007130857374747774556872726254484031710253900,000$
15Timothy KunesX100.007231677774747274386665755564512420700281900,000$
16Shea Theodore (R)X100.005937857855667675418469764646426359690202950,000$
17Aaron Ness (R)X100.006838747570747270477269685953483552680251500,000$
18David KolomatisX100.006129856971726766536960696363573062670261500,000$
19Dillon Heatherington (R)X100.006624826061677155416047784943425549630202500,000$
Scratches
1Ryan Fitzgerald (R)X70.156243746066666470695766566244455448620212550,000$
2Joakim Nordstrom (R)X100.008145596269637566556564545345454435620231350,000$
3Richard Nejezchleb (R)X100.005245695864646058636269525545444530600211350,000$
4Francis Perron (R)X100.005433655541526564667163345541416430560191500,000$
5Morgan Rielly (R)X100.007032886566787569507771656349436224690211925,000$
6Matt Grzelcyk (R)X100.006126677655606570397047645343435227620213600,000$
TEAM AVERAGE98.81643574656568696659676659595048494264
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
1Thomas Greiss100.00716770687171637368697470652361690
2Eric Comrie100.00677966687070667174705344426155680
Scratches
1Phoenix Copley100.00675863707061506570586653523719630
TEAM AVERAGE100.0068686669706760707166645653404567
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Brent Sutter90646987405956CAN491500,000$


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
1Emerson EtemMonsters (Clb)LW806850118-1254014914538312120917.75%44185623.211420345829611272427252.47%5668928151.272130001452
2Andrew GordonMonsters (Clb)RW67345387345586852275813514.98%38133219.891113244124200031322047.01%1174037011.3129010233
3Shea TheodoreMonsters (Clb)D80116778-1624054155227891014.85%111186323.2941418322731016216000.00%05564000.8400000132
4Dominik SimonMonsters (Clb)C70234164-7300881182076811411.11%25129418.4991019432211123561051.10%15463017010.9904000243
5Matt CalvertMonsters (Clb)LW623527621240108792007011817.50%23108917.577512201821125815244.74%764116011.1459000451
6Christian HansonBlue JacketsC42153752-73956268114386813.16%2886720.6649132113600041211252.80%11061214001.2015000015
7Justin FlorekMonsters (Clb)LW80242852-7280120751955710312.31%25110313.794711101291019604043.94%1323422000.9435000213
8Mitch MarnerMonsters (Clb)RW80153247-52557658162451019.26%17101512.69000149000042368.97%582712010.9300001116
9Roman JosiMonsters (Clb)D70132740-3016010214215561688.39%140184126.316612252430225204300.00%04967000.4300000041
10Jared KnightMonsters (Clb)C71132336-552096102103275412.62%20100414.1514571050001161247.60%626818000.7200000142
11Ondrej KaseMonsters (Clb)RW69161733-17209470138448111.59%27102514.87369181991012492247.92%481815000.6411000025
12Aaron NessMonsters (Clb)D7762632-442075928840406.82%72124816.220224133022199010.00%02822000.5101000211
13Timothy KunesMonsters (Clb)D3752328356084717934406.33%5689724.2626816143022296000.00%02823000.6200000121
14Bobby FarnhamMonsters (Clb)RW77101727-63209549100326010.00%1684410.96112448000091222.22%361515000.6400000000
15Austin WatsonMonsters (Clb)LW7613112461808453103256412.62%137169.43000070000390138.10%21812000.6700000010
16Ryan FitzgeraldMonsters (Clb)C80812200260505672275111.11%217829.7900001000040046.55%391812000.5100000000
17Morgan RiellyMonsters (Clb)D644121634076957826365.13%60131320.53101111720114158100.00%02334000.2401000001
18David KolomatisMonsters (Clb)D8021416-24026794820344.17%58108513.57000153011066000.00%01437000.2900000000
19Joakim NordstromMonsters (Clb)LW54459322039172492416.67%33306.120000220001501147.06%5123000.5400000011
20Dillon HeatheringtonMonsters (Clb)D7109928034692912100.00%5579311.18011012000032000.00%0130000.2300000000
21Richard NejezchlebMonsters (Clb)RW51437912011121231333.33%41913.75000011000001033.33%950000.7300000020
22Maxim MaminMonsters (Clb)C64415612010162272018.18%33395.31000020000200042.64%12926000.2900000000
23Matt GrzelcykMonsters (Clb)D51022514017137380.00%143296.450000200005000.00%019000.1200000000
24Beau StarrettMonsters (Clb)C70011-1100791110.00%21712.45000030000210038.10%6300000.1200000000
25Cameron HughesMonsters (Clb)C31000-100000000.00%130.130000200000000.00%000000.0000000000
26Francis PerronMonsters (Clb)LW51000220102010.00%0541.06000040000240037.50%1600000.0000000000
Team Total or Average1705327538865-7760115164417282776917155411.78%8762339713.7267104171312270061117531815321849.87%4991538513190.741448011304037
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
1Thomas GreissMonsters (Clb)54242110.8734.192838201981553793320.800155121100
2Eric ComrieMonsters (Clb)39131380.8733.941996401311029530510.724293049210
3Phoenix CopleyMonsters (Clb)20100.8644.19430032210100.000008000
Team Total or Average95373590.8734.0848776033226041333930.750448178310


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 Type Current Salary Salary RemainingSalary Cap Salary Cap Remaining Exclude from Salary Cap Salary Year 2Salary Year 3Salary Year 4Salary Year 5Salary Year 6Salary Year 7Salary Year 8Salary Year 9Salary Year 10Link
Aaron NessMonsters (Clb)D251990-01-01Yes182 Lbs5 ft10NoNoNo1Pro & Farm500,000$0$0$No
Andrew GordonMonsters (Clb)RW301985-01-01No194 Lbs6 ft0NoNoNo1Pro & Farm850,000$0$0$No
Austin WatsonMonsters (Clb)LW231992-01-01Yes193 Lbs6 ft4NoNoNo2Pro & Farm600,000$0$0$No600,000$
Beau StarrettMonsters (Clb)C191996-01-01Yes215 Lbs6 ft5NoNoNo1Pro & Farm500,000$0$0$No
Bobby FarnhamMonsters (Clb)RW261989-01-01No188 Lbs5 ft10NoNoNo1Pro & Farm500,000$0$0$No
Cameron HughesMonsters (Clb)C191996-01-01Yes195 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
David KolomatisMonsters (Clb)D261989-01-01No196 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Dillon HeatheringtonMonsters (Clb)D201995-01-01Yes185 Lbs6 ft4NoNoNo2Pro & Farm500,000$0$0$No500,000$
Dominik SimonMonsters (Clb)C211994-01-01Yes190 Lbs5 ft11NoNoNo2Pro & Farm500,000$0$0$No500,000$
Emerson EtemMonsters (Clb)LW231992-01-01Yes212 Lbs6 ft1NoNoNo1Pro & Farm800,000$0$0$No
Eric ComrieMonsters (Clb)G201995-01-01No185 Lbs6 ft1NoNoNo3Pro & Farm600,000$0$0$No700,000$800,000$
Francis PerronMonsters (Clb)LW191996-01-01Yes178 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$No
Jared KnightMonsters (Clb)C231992-01-01Yes203 Lbs5 ft11NoNoNo1Pro & Farm600,000$0$0$No
Joakim NordstromMonsters (Clb)LW231992-01-01Yes189 Lbs6 ft1NoNoNo1Pro & Farm350,000$0$0$No
Justin FlorekMonsters (Clb)LW251990-01-01Yes199 Lbs6 ft4NoNoNo1Pro & Farm600,000$0$0$No
Matt CalvertMonsters (Clb)LW261989-01-01No187 Lbs5 ft10NoNoNo1Pro & Farm900,000$0$0$No
Matt GrzelcykMonsters (Clb)D211994-01-01Yes171 Lbs5 ft9NoNoNo3Pro & Farm600,000$0$0$No700,000$800,000$
Maxim MaminMonsters (Clb)C201995-01-01Yes185 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$
Mitch MarnerMonsters (Clb)RW181997-01-01Yes175 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$
Morgan RiellyMonsters (Clb)D211994-01-01Yes200 Lbs6 ft0NoNoNo1Pro & Farm925,000$0$0$No
Ondrej KaseMonsters (Clb)RW191996-01-01Yes186 Lbs5 ft11NoNoNo1Pro & Farm500,000$0$0$No
Phoenix CopleyMonsters (Clb)G231992-01-01No196 Lbs6 ft4NoNoNo1Pro & Farm500,000$0$0$No
Richard NejezchlebMonsters (Clb)RW211994-01-01Yes187 Lbs5 ft11NoNoNo1Pro & Farm350,000$0$0$No
Roman JosiMonsters (Clb)D251990-01-01No198 Lbs6 ft2NoNoNo3Pro & Farm900,000$0$0$No1,000,000$1,000,000$
Ryan Fitzgerald (Out of Payroll)Monsters (Clb)C211994-01-01Yes185 Lbs5 ft10NoNoNo2Pro & Farm550,000$0$0$Yes550,000$
Shea TheodoreMonsters (Clb)D201995-01-01Yes185 Lbs6 ft2NoNoNo2Pro & Farm950,000$0$0$No950,000$
Thomas GreissMonsters (Clb)G291986-01-01No210 Lbs6 ft1NoNoNo2Pro & Farm650,000$0$0$No650,000$
Timothy KunesMonsters (Clb)D281987-01-01No170 Lbs6 ft1NoNoNo1Pro & Farm900,000$0$0$No
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2822.64191 Lbs6 ft11.54611,607$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Emerson EtemDominik SimonMitch Marner40122
2Matt CalvertJared KnightAndrew Gordon30122
3Justin FlorekOndrej Kase20122
4Austin WatsonMaxim MaminBobby Farnham10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Roman JosiTimothy Kunes40122
2Dillon HeatheringtonShea Theodore30122
3Aaron NessDavid Kolomatis20122
4Roman JosiTimothy Kunes10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Emerson EtemDominik SimonAndrew Gordon60122
2Matt CalvertJared KnightOndrej Kase40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Roman JosiTimothy Kunes60122
2Aaron NessShea Theodore40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Emerson EtemAndrew Gordon60122
2Matt CalvertJustin Florek40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Roman JosiTimothy Kunes60122
2David KolomatisShea Theodore40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Emerson Etem60122Roman JosiTimothy Kunes60122
2Andrew Gordon40122David KolomatisShea Theodore40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Emerson EtemAndrew Gordon60122
2Matt CalvertJustin Florek40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Roman JosiTimothy Kunes60122
2Aaron NessShea Theodore40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Emerson EtemDominik SimonAndrew GordonRoman JosiTimothy Kunes
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Emerson EtemDominik SimonAndrew GordonRoman JosiTimothy Kunes
Extra Forwards
Normal PowerPlayPenalty Kill
Beau Starrett, Cameron Hughes, Bobby FarnhamBeau Starrett, Cameron HughesBobby Farnham
Extra Defensemen
Normal PowerPlayPenalty Kill
Aaron Ness, David Kolomatis, Timothy KunesAaron NessDavid Kolomatis, Roman Josi
Penalty Shots
Emerson Etem, Andrew Gordon, Matt Calvert, Justin Florek, Dominik Simon
Goalie
#1 : Thomas Greiss, #2 : Eric Comrie


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
1Admirals62201010302913110100014140311000101615180.66730457500991151061721293694785369204595512734720.59%25772.00%1943186050.70%868178048.76%678135150.19%171394316897631469739
2Barracuda705000112233-1130300000815-7402000111418-430.21422365800991151061724293694785369220754615129620.69%23482.61%0943186050.70%868178048.76%678135150.19%171394316897631469739
3Bears321000001917222000000151141010000046-240.667193251009911510617113936947853698426205311436.36%10280.00%1943186050.70%868178048.76%678135150.19%171394316897631469739
4Checkers3020001089-1201000105501010000034-120.3338122000991151061710393694785369903328671218.33%14192.86%1943186050.70%868178048.76%678135150.19%171394316897631469739
5Comets2010100089-11010000035-21000100054120.5008111910991151061769936947853697220647600.00%30100.00%0943186050.70%868178048.76%678135150.19%171394316897631469739
6Condors42200000191542110000089-121100000116540.5001932510099115106171369369478536912445208819315.79%9188.89%0943186050.70%868178048.76%678135150.19%171394316897631469739
7Crunch201000101112-11010000046-21000001076120.5001118291099115106178193694785369721918349222.22%9188.89%0943186050.70%868178048.76%678135150.19%171394316897631469739
8Devils220000001064110000006331100000043141.0001017270099115106177193694785369651910436116.67%5340.00%1943186050.70%868178048.76%678135150.19%171394316897631469739
9Eagles21000001761110000003121000000145-130.7507111800991151061761936947853696991850800.00%9277.78%0943186050.70%868178048.76%678135150.19%171394316897631469739
10Griffins31001001141132100100010641000000145-150.8331425390099115106178993694785369843216611616.25%8450.00%0943186050.70%868178048.76%678135150.19%171394316897631469739
11Heat20200000610-41010000014-31010000056-100.00069150099115106176293694785369782914333133.33%7185.71%0943186050.70%868178048.76%678135150.19%171394316897631469739
12IceHogs7320011027234320000101798412001001014-490.64327437000991151061723693694785369204724616232825.00%23291.30%1943186050.70%868178048.76%678135150.19%171394316897631469739
13Influenza3110001011110210000108531010000036-340.6671117280099115106171109369478536910735225810220.00%11372.73%0943186050.70%868178048.76%678135150.19%171394316897631469739
14Little Stars210000016511000000123-11100000042230.75061117009911510617689369478536968161848300.00%90100.00%0943186050.70%868178048.76%678135150.19%171394316897631469739
15Moose312000001112-1211000008801010000034-120.33311182900991151061783936947853691053746679111.11%23386.96%0943186050.70%868178048.76%678135150.19%171394316897631469739
16Penguins22000000862110000002111100000065141.0008152300991151061754936947853695616124613323.08%60100.00%0943186050.70%868178048.76%678135150.19%171394316897631469739
17Phantoms32100000171161100000062421100000119240.6671724410099115106171149369478536910539215818527.78%8275.00%0943186050.70%868178048.76%678135150.19%171394316897631469739
18Punishers210000101477100000106511100000082641.000142135009911510617809369478536967206328337.50%30100.00%0943186050.70%868178048.76%678135150.19%171394316897631469739
19Rampage613001012130-9312000001217-530100101913-440.33321365700991151061721493694785369197814612720630.00%23673.91%0943186050.70%868178048.76%678135150.19%171394316897631469739
20Reign31200000710-3110000003212020000048-420.3337121900991151061784936947853691002520511200.00%10280.00%0943186050.70%868178048.76%678135150.19%171394316897631469739
21Rocket312000001415-11010000056-12110000099020.333142539109911510617120936947853698530266321628.57%14471.43%0943186050.70%868178048.76%678135150.19%171394316897631469739
22Senators210000101183110000008621000001032141.0001118290099115106176693694785369783620417228.57%11281.82%0943186050.70%868178048.76%678135150.19%171394316897631469739
23Sound Tigers321000001091110000005232110000057-240.66710182800991151061710793694785369922949442827.14%18477.78%0943186050.70%868178048.76%678135150.19%171394316897631469739
24Thunderbirds302001001117-620100100611-51010000056-110.167112132009911510617112936947853691074614648112.50%7185.71%0943186050.70%868178048.76%678135150.19%171394316897631469739
25Wolfpack211000009901010000046-21100000053220.50091423009911510617729369478536964151438500.00%7185.71%1943186050.70%868178048.76%678135150.19%171394316897631469739
Total80283303385331330140171502141169162740111801244162168-6860.538331541872309911510617275993694785369259786361116533476518.73%2955681.02%6943186050.70%868178048.76%678135150.19%171394316897631469739
_Since Last GM Reset80283303385331330140171502141169162740111801244162168-6860.538331541872309911510617275993694785369259786361116533476518.73%2955681.02%6943186050.70%868178048.76%678135150.19%171394316897631469739
_Vs Conference48182102142201196523127020201078918256140012294107-13510.53120132752810991151061716469369478536915145043879832394518.83%1823879.12%3943186050.70%868178048.76%678135150.19%171394316897631469739
_Vs Division2059011317985-693401010393811125001214047-7200.5007912420300991151061769093694785369628206147440952122.11%711381.69%2943186050.70%868178048.76%678135150.19%171394316897631469739

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8086L133154187227592597863611165330
All Games
GPWLOTWOTL SOWSOLGFGA
8028333385331330
Home Games
GPWLOTWOTL SOWSOLGFGA
4017152141169162
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4011181244162168
Last 10 Games
WLOTWOTL SOWSOL
330121
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
3476518.73%2955681.02%6
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
936947853699911510617
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
943186050.70%868178048.76%678135150.19%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
171394316897631469739


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 - 2020-10-107IceHogs5Monsters8WBoxScore
4 - 2020-10-1219Monsters3IceHogs2WBoxScore
7 - 2020-10-1535Barracuda6Monsters3LBoxScore
9 - 2020-10-1747Monsters3Barracuda4LBoxScore
10 - 2020-10-1853Monsters3Rampage5LBoxScore
13 - 2020-10-2170Monsters2Barracuda5LBoxScore
14 - 2020-10-2276Rampage3Monsters8WBoxScore
17 - 2020-10-2591Admirals4Monsters5WXBoxScore
19 - 2020-10-27103Monsters7Admirals6WXXBoxScore
23 - 2020-10-31124Influenza3Monsters5WBoxScore
24 - 2020-11-01133Monsters3IceHogs6LBoxScore
27 - 2020-11-04147Monsters4Sound Tigers3WBoxScore
28 - 2020-11-05153Barracuda6Monsters3LBoxScore
31 - 2020-11-08171IceHogs2Monsters3WXXBoxScore
35 - 2020-11-12192Monsters2IceHogs3LBoxScore
37 - 2020-11-14202Condors4Monsters7WBoxScore
40 - 2020-11-17215Devils3Monsters6WBoxScore
44 - 2020-11-21236Comets5Monsters3LBoxScore
47 - 2020-11-24257Monsters5Wolfpack3WBoxScore
49 - 2020-11-26264Monsters1Reign3LBoxScore
51 - 2020-11-28274Reign2Monsters3WBoxScore
54 - 2020-12-01292Phantoms2Monsters6WBoxScore
56 - 2020-12-03303Monsters4Devils3WBoxScore
58 - 2020-12-05311Monsters3Rampage4LXXBoxScore
60 - 2020-12-07324Eagles1Monsters3WBoxScore
64 - 2020-12-11343Monsters8Punishers2WBoxScore
65 - 2020-12-12352Condors5Monsters1LBoxScore
68 - 2020-12-15361Monsters4Phantoms6LBoxScore
70 - 2020-12-17372Monsters4Griffins5LXXBoxScore
72 - 2020-12-19382Checkers2Monsters3WXXBoxScore
75 - 2020-12-22399Barracuda3Monsters2LBoxScore
77 - 2020-12-24409Monsters4Condors5LBoxScore
79 - 2020-12-26420Monsters3Moose4LBoxScore
81 - 2020-12-28428Monsters5Heat6LBoxScore
83 - 2020-12-30437Moose5Monsters4LBoxScore
85 - 2021-01-01453Monsters5Comets4WXBoxScore
87 - 2021-01-03461Little Stars3Monsters2LXXBoxScore
89 - 2021-01-05470Monsters2IceHogs3LXBoxScore
91 - 2021-01-07481Monsters3Reign5LBoxScore
93 - 2021-01-09493Griffins4Monsters7WBoxScore
95 - 2021-01-11504Monsters5Rocket3WBoxScore
97 - 2021-01-13513Monsters7Phantoms3WBoxScore
99 - 2021-01-15520Griffins2Monsters3WXBoxScore
104 - 2021-01-20541Sound Tigers2Monsters5WBoxScore
106 - 2021-01-22548Monsters7Crunch6WXXBoxScore
109 - 2021-01-25564Monsters4Eagles5LXXBoxScore
110 - 2021-01-26571Moose3Monsters4WBoxScore
113 - 2021-01-29592Heat4Monsters1LBoxScore
115 - 2021-01-31605Monsters4Little Stars2WBoxScore
118 - 2021-02-03618Senators6Monsters8WBoxScore
122 - 2021-02-07640Monsters3Rampage4LXBoxScore
124 - 2021-02-09646Rampage8Monsters3LBoxScore
127 - 2021-02-12668Penguins1Monsters2WBoxScore
129 - 2021-02-14674Monsters1Sound Tigers4LBoxScore
131 - 2021-02-16683Monsters4Rocket6LBoxScore
133 - 2021-02-18696Bears6Monsters8WBoxScore
137 - 2021-02-22720Rampage6Monsters1LBoxScore
139 - 2021-02-24728Monsters3Senators2WXXBoxScore
143 - 2021-02-28745IceHogs2Monsters6WBoxScore
147 - 2021-03-04765Monsters6Penguins5WBoxScore
149 - 2021-03-06771Punishers5Monsters6WXXBoxScore
152 - 2021-03-09793Admirals7Monsters3LBoxScore
154 - 2021-03-11797Monsters3Influenza6LBoxScore
157 - 2021-03-14808Monsters5Thunderbirds6LBoxScore
159 - 2021-03-16824Bears5Monsters7WBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
162 - 2021-03-19841Monsters3Checkers4LBoxScore
164 - 2021-03-21849Rocket6Monsters5LBoxScore
166 - 2021-03-23858Monsters4Bears6LBoxScore
169 - 2021-03-26877Crunch6Monsters4LBoxScore
174 - 2021-03-31898Wolfpack6Monsters4LBoxScore
175 - 2021-04-01904Monsters3Barracuda2WXXBoxScore
178 - 2021-04-04921Monsters6Barracuda7LXXBoxScore
180 - 2021-04-06927Influenza2Monsters3WXXBoxScore
186 - 2021-04-12952Monsters5Admirals3WBoxScore
187 - 2021-04-13958Thunderbirds5Monsters1LBoxScore
190 - 2021-04-16975Monsters4Admirals6LBoxScore
192 - 2021-04-18985Thunderbirds6Monsters5LXBoxScore
194 - 2021-04-20996Monsters7Condors1WBoxScore
197 - 2021-04-231012Admirals3Monsters6WBoxScore
201 - 2021-04-271030Checkers3Monsters2LBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price4020
Attendance54,14427,389
Attendance PCT67.68%68.47%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
0 2038 - 67.94% 71,230$2,849,217$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
2,227,748$ 1,657,500$ 1,637,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
8,085$ 1,718,112$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 10,524$ 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