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Monsters
GP: 82 | W: 46 | L: 29 | OTL: 7 | P: 99
GF: 320 | GA: 295 | PP%: 22.82% | PK%: 79.21%
GM : Benoit Toupin | Morale : 50 | Team Overall : 55
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Game Center
Thunder
12-61-9, 33pts
1
FINAL
7 Monsters
46-29-7, 99pts
Team Stats
L7StreakSOL1
4-34-3Home Record23-14-4
8-27-6Away Record23-15-3
0-8-2Last 10 Games5-4-1
2.85Goals Per Game3.90
5.04Goals Against Per Game3.60
19.20%Power Play Percentage22.82%
77.78%Penalty Kill Percentage79.21%
Monsters
46-29-7, 99pts
2
FINAL
3 Caroline
23-48-11, 57pts
Team Stats
SOL1StreakW3
23-14-4Home Record17-19-5
23-15-3Away Record6-29-6
5-4-1Last 10 Games5-3-2
3.90Goals Per Game3.44
3.60Goals Against Per Game4.65
22.82%Power Play Percentage24.23%
79.21%Penalty Kill Percentage71.37%
Team Leaders
Goals
Colin Blackwell
13
Assists
Kurtis MacDermid
27
Points
Kurtis MacDermid
38
Plus/Minus
Colin Blackwell
2
Wins
Braden Holtby
46
Save Percentage
Jean-Francois Berube
0.957

Team Stats
Goals For
320
3.90 GFG
Shots For
3394
41.39 Avg
Power Play Percentage
22.8%
55 GF
Offensive Zone Start
41.1%
Goals Against
295
3.60 GAA
Shots Against
3208
39.12 Avg
Penalty Kill Percentage
79.2%
58 GA
Defensive Zone Start
40.6%
Team Info

General ManagerBenoit Toupin
DivisionNord-Est
ConferenceEst
Captain
Assistant #1
Assistant #2


Arena Info

Capacity3,000
Attendance2,865
Season Tickets300


Roster Info

Pro Team30
Farm Team18
Contract Limit48 / 50
Prospects14


Team History

This Season46-29-7 (99PTS)
History46-29-8 (0.554%)
Playoff Appearances
Playoff Record (W-L)-


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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 SPAgeContractSalary Average
1Melker KarlssonXX100.006543887765588155495557757266690506203021,425,000$
2Benoit-Olivier Groulx (R)X100.00767383677373766278616065574444050610204822,500$
3Cole Caufield (R)X100.00614093805666517025608054254444050610193880,833$
4Tom KuhnhacklXX100.00787388777355546250605770546063050610281600,000$
5Julien GauthierX100.00844686698454705945655862255152050600221925,000$
6Sheldon DriesXX100.00706483746461626176556362604849050590264700,000$
7Dominik Bokk (R)XX100.00756989676961626150566264594444050580204863,333$
8Chad Yetman (R)XX100.00756499646460615670565163484444050560204560,000$
9Tim SoderlundXX100.00766499655857535555554864424444050550223825,834$
10Brandon Coe (R)X100.00797489637459615150524663444444050540184650,000$
11Griffen MolinoXX100.00676488596350484964474462445151050510262900,000$
12Kasper Bjorkqvist (R)XX100.00737288497246464749365362514444050500231700,000$
13Johnathan KovacevicX100.00868686637866625828554569394444050610232792,500$
14Jimmy SchuldtX100.00868097617374715828445669484444050610251825,000$
15Brian LashoffX100.00817986687955584925374169396364050600301775,000$
16Keaton MiddletonX100.00898891618857594925443968374444050590221715,000$
17Connor Mackey (R)X100.00757283607259615525524362414444050570244925,000$
18Adam Ginning (R)X100.00615871627763904025353767395052050570204825,000$
Scratches
1Adam Tambellini (R)XX100.00334343435131313343333343383230050360251560,000$
2Todd Burgess (R)X100.00344040405533333440343440373230050360241650,000$
3Wyatte Wylie (R)X100.00757085617061645125464161394444050560204820,833$
4Nils Lundkvist (R)X100.00484183696169925125464748495050050550204925,000$
5Reece ScarlettX100.00706985606946464725384060394444050520271650,000$
6Jake Christiansen (R)X100.00757198577150543925273761364444050520213925,000$
7Matt Kiersted (R)X100.00776799646745474125283960374444050520222858,750$
8Sergei Boikov (R)X100.00323737376631313237323237343230050360241705,000$
TEAM AVERAGE100.0069638362695559514147486144464605055
Filter Tips
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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
1Braden Holtby100.0059677581595957616459787175050630
2Jean-Francois Berube100.0052648066475352575151335247050540
Scratches
1Cory Schneider100.0047455880474551535148306969050540
2Jakub Skarek (R)100.0048536681464750544747334844050520
TEAM AVERAGE100.005257707750515356535144605905056
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary


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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
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# 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
1Cole CaufieldMonsters (Clb)RW8247479415403516944711933110.51%6151618.507121971201000018231.79%15100011.2402000864
2Tom KuhnhacklMonsters (Clb)LW/RW8230639317580182163375912638.00%35177521.666101650192011122033146.67%16500011.054100001041
3Benoit-Olivier GroulxMonsters (Clb)C82305383284751112152987921610.07%22153918.78215174518511271155159.35%208100101.0805100374
4Sheldon DriesMonsters (Clb)C/LW8225568123315100219307742268.14%18170020.746131955192123132063157.42%198200000.95612100257
5Julien GauthierMonsters (Clb)RW82294776216001761372788222310.43%11154218.818917371730002126344.07%11800000.9901000642
6Dominik BokkMonsters (Clb)LW/RW82244266-1538095125327742277.34%24141817.305914431390004911043.16%9500010.9349000433
7Melker KarlssonMonsters (Clb)C/RW592525501560411462046614912.25%2499416.8611214570002712245.86%68900101.0104000333
8Chad YetmanMonsters (Clb)C/RW82202848-1014070190220591179.09%13123615.080003260002530354.44%153000000.7811000211
9Jimmy SchuldtMonsters (Clb)D761434483106201467116252818.64%120170322.4161016571961122116100.00%000100.5600112003
10Brian LashoffMonsters (Clb)D8213253834601019160110308011.82%139167520.436612371680001173110.00%000100.4500101413
11Kurtis MacDermidColumbusD51112738-24201606112439628.87%97121223.7821012421250002130200.00%000000.6300000014
12Keaton MiddletonMonsters (Clb)D8262531-1011020210436215469.68%105137616.781235320002129100.00%000000.4500301000
13Johnathan KovacevicMonsters (Clb)D5262329136610127657931667.59%94113321.81426381150221123200.00%000000.5100101011
14Tim SoderlundMonsters (Clb)LW/RW82111526-15240808616441926.71%19109813.40011213000101551045.16%12400000.4711000012
15Colin BlackwellColumbusC/LW/RW20131225220126789297414.61%948724.38471119620002672047.07%69900011.0316000300
16Connor MackeyMonsters (Clb)D6171724-145201395059224711.86%9094415.483251350000034100.00%000000.5100000012
17Nils LundkvistMonsters (Clb)D403161915004132681311.54%2676919.24123874000050000.00%000000.4900000031
18Adam GinningMonsters (Clb)D82710170180713649243614.29%139145717.780114131013166020.00%000000.2300000001
19Kasper BjorkqvistMonsters (Clb)LW/RW4975121120412249174614.29%665813.4400000000061244.44%5400000.3600000001
20Griffen MolinoMonsters (Clb)C/LW80189-54024744518372.22%74695.8700001000030054.50%57800000.3800000000
21Brandon CoeMonsters (Clb)RW44268-617535315111343.92%53427.79000020000140045.83%2400000.4700001000
22Jake ChristiansenMonsters (Clb)D5011-240501120.00%511022.0801109000011000.00%000000.1800000000
23Wyatte WylieMonsters (Clb)D1401121001849660.00%1323716.9800012300007000.00%000000.0800000000
24Adam TambelliniMonsters (Clb)C/LW6000000000000.00%0508.3900001000050028.57%700000.0000000000
Team Total or Average14593315869171107857520732047353598824749.36%10272545417.456211317554420584711651952401853.96%829700440.721751816454143
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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
1Braden HoltbyMonsters (Clb)82462770.9103.4148534027630810270.77845820425
2Cory SchneiderMonsters (Clb)30200.9383.43105006970000.0000061010
3Jean-Francois BerubeMonsters (Clb)10000.9571.9431001230000.0000020000
Team Total or Average86462970.9123.4049904028332010270.778458281435


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
Adam GinningMonsters (Clb)D202000-01-13Yes206 Lbs6 ft4NoNoNo4Pro & Farm825,000$82,500$0$No825,000$825,000$825,000$
Adam TambelliniMonsters (Clb)C/LW251994-11-01Yes169 Lbs6 ft2NoNoNo1Pro & Farm560,000$56,000$0$NoLink
Benoit-Olivier GroulxMonsters (Clb)C202000-02-05Yes195 Lbs6 ft2NoNoNo4Pro & Farm822,500$82,250$0$No822,500$822,500$822,500$Link
Braden HoltbyMonsters (Clb)G311989-09-16No214 Lbs6 ft2NoNoNo4Pro & Farm4,875,000$487,500$0$No4,875,000$4,875,000$4,875,000$Link
Brandon CoeMonsters (Clb)RW182001-12-01Yes190 Lbs6 ft4NoNoNo4Pro & Farm650,000$65,000$0$No650,000$650,000$650,000$Link
Brian LashoffMonsters (Clb)D301990-07-15No213 Lbs6 ft3NoNoNo1Pro & Farm775,000$77,500$0$NoLink
Chad YetmanMonsters (Clb)C/RW202000-02-18Yes179 Lbs5 ft11NoNoNo4Pro & Farm560,000$56,000$0$No560,000$560,000$560,000$Link
Cole CaufieldMonsters (Clb)RW192001-01-02Yes162 Lbs5 ft7NoNoNo3Pro & Farm880,833$88,083$0$No880,833$880,833$Link
Connor MackeyMonsters (Clb)D241996-09-12Yes190 Lbs6 ft2NoNoNo4Pro & Farm925,000$92,500$0$No925,000$925,000$925,000$Link
Cory SchneiderMonsters (Clb)G341986-03-17No200 Lbs6 ft3NoNoNo2Pro & Farm5,250,000$525,000$0$No5,250,000$Link
Dominik BokkMonsters (Clb)LW/RW202000-02-03Yes181 Lbs6 ft2NoNoNo4Pro & Farm863,333$86,333$0$No863,333$863,333$863,333$Link
Griffen MolinoMonsters (Clb)C/LW261994-01-21No171 Lbs5 ft11NoNoNo2Pro & Farm900,000$90,000$0$No900,000$Link
Jake ChristiansenMonsters (Clb)D211999-09-12Yes194 Lbs6 ft1NoNoNo3Pro & Farm925,000$92,500$0$No925,000$925,000$
Jakub SkarekMonsters (Clb)G201999-11-10Yes202 Lbs6 ft3NoNoNo4Pro & Farm764,167$76,417$0$No764,167$764,167$764,167$Link
Jean-Francois BerubeMonsters (Clb)G291991-07-13No177 Lbs6 ft1NoNoNo1Pro & Farm999,999$100,000$0$NoLink
Jimmy SchuldtMonsters (Clb)D251995-05-11No203 Lbs6 ft0NoNoNo1Pro & Farm825,000$82,500$0$NoLink
Johnathan KovacevicMonsters (Clb)D231997-07-12No207 Lbs6 ft4NoNoNo2Pro & Farm792,500$79,250$0$No792,500$Link
Julien GauthierMonsters (Clb)RW221997-10-15No227 Lbs6 ft4NoNoNo1Pro & Farm925,000$92,500$0$NoLink
Kasper BjorkqvistMonsters (Clb)LW/RW231997-07-10Yes198 Lbs6 ft1NoNoNo1Pro & Farm700,000$70,000$0$NoLink
Keaton MiddletonMonsters (Clb)D221998-02-10No233 Lbs6 ft6NoNoNo1Pro & Farm715,000$71,500$0$NoLink
Matt KierstedMonsters (Clb)D221998-04-14Yes181 Lbs6 ft0NoNoNo2Pro & Farm858,750$85,875$0$No858,750$Link
Melker KarlssonMonsters (Clb)C/RW301990-07-18No182 Lbs5 ft10NoNoNo2Pro & Farm1,425,000$142,500$0$No1,425,000$Link
Nils LundkvistMonsters (Clb)D202000-07-27Yes174 Lbs5 ft10NoNoNo4Pro & Farm925,000$92,500$0$No925,000$925,000$925,000$Link
Reece ScarlettMonsters (Clb)D271993-05-31No185 Lbs6 ft1NoNoNo1Pro & Farm650,000$65,000$0$NoLink
Sergei BoikovMonsters (Clb)D241996-01-24Yes200 Lbs6 ft2NoNoNo1Pro & Farm705,000$70,500$0$NoLink
Sheldon DriesMonsters (Clb)C/LW261994-04-23No180 Lbs5 ft9NoNoNo4Pro & Farm700,000$70,000$0$No700,000$700,000$700,000$Link
Tim SoderlundMonsters (Clb)LW/RW221998-01-23No163 Lbs5 ft9NoNoNo3Pro & Farm825,834$82,583$0$No825,834$825,834$Link
Todd BurgessMonsters (Clb)RW241996-04-03Yes178 Lbs6 ft2NoNoNo1Pro & Farm650,000$65,000$0$NoLink
Tom KuhnhacklMonsters (Clb)LW/RW281992-01-21No196 Lbs6 ft2NoNoNo1Pro & Farm600,000$60,000$0$NoLink
Wyatte WylieMonsters (Clb)D201999-11-02Yes190 Lbs6 ft0NoNoNo4Pro & Farm820,833$82,083$0$No820,833$820,833$820,833$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3023.83191 Lbs6 ft12.471,089,792$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Tom KuhnhacklBenoit-Olivier GroulxCole Caufield40014
2Sheldon DriesMelker KarlssonJulien Gauthier34023
3Dominik BokkChad YetmanBrandon Coe20032
4Tim SoderlundGriffen MolinoKasper Bjorkqvist6122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Johnathan KovacevicBrian Lashoff40122
2Jimmy SchuldtConnor Mackey30032
3Adam GinningKeaton Middleton20023
4Johnathan KovacevicJimmy Schuldt10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Tom KuhnhacklBenoit-Olivier GroulxCole Caufield60005
2Dominik BokkSheldon DriesJulien Gauthier40005
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Jimmy SchuldtBrian Lashoff60005
2Johnathan KovacevicConnor Mackey40014
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Benoit-Olivier GroulxMelker Karlsson60050
2Benoit-Olivier GroulxTom Kuhnhackl40050
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Jimmy SchuldtBrian Lashoff60050
2Keaton MiddletonJohnathan Kovacevic40050
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Benoit-Olivier Groulx60050Jimmy SchuldtBrian Lashoff60050
2Cole Caufield40050Keaton MiddletonJohnathan Kovacevic40050
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Benoit-Olivier GroulxCole Caufield60122
2Tom KuhnhacklJulien Gauthier40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Jimmy SchuldtBrian Lashoff60122
2Keaton MiddletonJohnathan Kovacevic40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Tom KuhnhacklBenoit-Olivier GroulxCole CaufieldJimmy SchuldtJohnathan Kovacevic
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Tom KuhnhacklBenoit-Olivier GroulxMelker KarlssonJohnathan KovacevicBrian Lashoff
Extra Forwards
Normal PowerPlayPenalty Kill
Chad Yetman, Tim Soderlund, Brandon CoeDominik Bokk, Tim SoderlundBrandon Coe
Extra Defensemen
Normal PowerPlayPenalty Kill
Adam Ginning, Johnathan Kovacevic, Brian LashoffAdam GinningJimmy Schuldt, Adam Ginning
Penalty Shots
Benoit-Olivier Groulx, Cole Caufield, Tom Kuhnhackl, Julien Gauthier, Sheldon Dries
Goalie
#1 : Braden Holtby, #2 : Jean-Francois Berube


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
1Admirals20200000410-61010000013-21010000037-400.00047111011497981999107711191142101682164711218.18%3166.67%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
2Baby Hawks210010001293110000006421000100065141.000121830001149798196810771119114210192251852100.00%9366.67%11799312757.53%1612308952.19%743140053.07%1992137519236061081540
3Bears42100010161422110000066021000010108260.75016274300114979819147107711191142101141363510816531.25%15566.67%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
4Bruins31200000711-41010000027-52110000054120.3337121900114979819991077111911421011284027719111.11%11190.91%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
5Cabaret Lady Mary Ann3300000017892200000012661100000052361.0001731480011497981916610771119114210110228107411218.18%4175.00%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
6Caroline43000001231582200000015872100000187170.8752342650011497981918310771119114210115343517311436.36%16756.25%11799312757.53%1612308952.19%743140053.07%1992137519236061081540
7Chiefs210001005501000010034-11100000021130.75058130011497981969107711191142101531516486116.67%7185.71%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
8Chill211000007701010000035-21100000042220.50071219101149798199010771119114210175271244800.00%6266.67%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
9Comets2020000028-61010000014-31010000014-300.0002350011497981973107711191142101782723456116.67%4175.00%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
10Cougars30300000813-52020000069-31010000024-200.0008162420114979819861077111911421011354024646350.00%7185.71%11799312757.53%1612308952.19%743140053.07%1992137519236061081540
11Crunch330000001367110000004222200000094561.000132437001149798191421077111911421011292545887342.86%140100.00%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
12Heat2110000078-1110000005321010000025-320.50071421001149798197310771119114210179321246500.00%6183.33%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
13Jayhawks200010019901000000145-11000100054130.750914230011497981980107711191142101802427558112.50%6266.67%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
14Las Vegas220000001183110000005321100000065141.00011203100114979819911077111911421011013551547114.29%5180.00%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
15Manchots402000111114-32020000025-32000001199030.3751117280011497981915310771119114210117358581087114.29%13284.62%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
16Marlies31100010862110000004132010001045-140.667811191011497981910210771119114210110436277310220.00%11190.91%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
17Minnesota22000000954110000003211100000063341.00091524001149798199710771119114210174201764500.00%6266.67%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
18Monarchs21100000972110000005141010000046-220.500917260011497981910210771119114210174241047500.00%50100.00%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
19Monsters20200000311-81010000025-31010000016-500.000369001149798196310771119114210188321845400.00%9366.67%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
20Oceanics200001109901000010045-11000001054130.750915240011497981976107711191142101991720476233.33%10190.00%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
21Oil Kings2010000168-21010000023-11000000145-110.25061117001149798196410771119114210165151450800.00%70100.00%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
22Phantoms4310000017116220000009362110000088060.7501731480011497981916410771119114210115835287917529.41%14378.57%11799312757.53%1612308952.19%743140053.07%1992137519236061081540
23Rocket302000101015-51010000026-42010001089-120.33310152510114979819971077111911421011304432666116.67%16381.25%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
24Senators321000001394211000009721100000042240.6671324370011497981913710771119114210110132225611436.36%11372.73%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
25Sharks211000008621010000034-11100000052320.500813210011497981967107711191142101802918404250.00%9188.89%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
26Sound Tigers4110101022184210000101284201010001010060.7502239610011497981917310771119114210116239348611763.64%16568.75%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
27Spiders412000101417-32100001097220200000510-540.5001425391011497981914310771119114210115746289411327.27%13561.54%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
28Stars2010000169-31000000134-11010000035-210.250612180011497981987107711191142101811810404125.00%5180.00%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
29Thunder330000002161522000000144101100000072561.000213859001149798191981077111911421011063516906116.67%8187.50%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
30Wolf Pack4210001013130220000008532010001058-360.7501322350011497981920510771119114210114243268214214.29%130100.00%01799312757.53%1612308952.19%743140053.07%1992137519236061081540
Total82352903285320295254121140022216413925411415030631561560990.604320559879701149798193394107711191142101320894173519362415522.82%2795879.21%41799312757.53%1612308952.19%743140053.07%1992137519236061081540
_Since Last GM Reset82352903285320295254121140022216413925411415030631561560990.604320559879701149798193394107711191142101320894173519362415522.82%2795879.21%41799312757.53%1612308952.19%743140053.07%1992137519236061081540
_Vs Conference4619170117117915821231280012091712023790105188871560.609179310489401149798191955107711191142101176851836710721463725.34%1583180.38%11799312757.53%1612308952.19%743140053.07%1992137519236061081540
_Vs Division287501030116102141460000206142191415010105560-5220.3931162033191011497981911681077111911421011086300260630872731.03%1002773.00%21799312757.53%1612308952.19%743140053.07%1992137519236061081540

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8299SOL132055987933943208941735193670
All Games
GPWLOTWOTL SOWSOLGFGA
8235293285320295
Home Games
GPWLOTWOTL SOWSOLGFGA
4121140222164139
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4114153063156156
Last 10 Games
WLOTWOTL SOWSOL
540001
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
2415522.82%2795879.21%4
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
107711191142101114979819
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1799312757.53%1612308952.19%743140053.07%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
1992137519236061081540


Last Played Games
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3 - 2021-10-1416Marlies1Monsters4WBoxScore
4 - 2021-10-1522Monsters5Manchots6LXXBoxScore
6 - 2021-10-1735Crunch2Monsters4WBoxScore
10 - 2021-10-2159Admirals3Monsters1LBoxScore
11 - 2021-10-2269Monsters6Caroline4WBoxScore
15 - 2021-10-2694Stars4Monsters3LXXBoxScore
17 - 2021-10-28110Monsters6Baby Hawks5WXBoxScore
18 - 2021-10-29120Sound Tigers4Monsters5WXXBoxScore
20 - 2021-10-31129Monsters2Marlies4LBoxScore
23 - 2021-11-03148Caroline2Monsters6WBoxScore
25 - 2021-11-05165Monsters4Phantoms3WBoxScore
29 - 2021-11-09189Oil Kings3Monsters2LBoxScore
31 - 2021-11-11200Monsters2Chiefs1WBoxScore
32 - 2021-11-12212Heat3Monsters5WBoxScore
35 - 2021-11-15227Las Vegas3Monsters5WBoxScore
37 - 2021-11-17246Monsters5Jayhawks4WXBoxScore
39 - 2021-11-19260Monsters1Monsters6LBoxScore
42 - 2021-11-22273Monsters5Rocket4WXXBoxScore
45 - 2021-11-25297Chiefs4Monsters3LXBoxScore
49 - 2021-11-29322Rocket6Monsters2LBoxScore
51 - 2021-12-01337Cougars4Monsters3LBoxScore
53 - 2021-12-03352Monsters5Oceanics4WXXBoxScore
55 - 2021-12-05369Senators3Monsters2LBoxScore
57 - 2021-12-07384Phantoms2Monsters5WBoxScore
59 - 2021-12-09400Manchots2Monsters1LBoxScore
60 - 2021-12-10410Monsters5Sound Tigers6LBoxScore
63 - 2021-12-13429Jayhawks5Monsters4LXXBoxScore
65 - 2021-12-15444Wolf Pack2Monsters3WBoxScore
67 - 2021-12-17458Monsters5Cabaret Lady Mary Ann2WBoxScore
69 - 2021-12-19469Monsters4Bears3WXXBoxScore
72 - 2021-12-22490Monsters4Manchots3WXXBoxScore
74 - 2021-12-24501Monsters4Senators2WBoxScore
76 - 2021-12-26521Bears3Monsters4WBoxScore
77 - 2021-12-27529Monsters2Cougars4LBoxScore
79 - 2021-12-29541Monarchs1Monsters5WBoxScore
81 - 2021-12-31561Spiders2Monsters3WXXBoxScore
83 - 2022-01-02573Monsters5Sound Tigers4WXBoxScore
87 - 2022-01-06585Monsters6Bears5WBoxScore
89 - 2022-01-08604Baby Hawks4Monsters6WBoxScore
91 - 2022-01-10619Cabaret Lady Mary Ann4Monsters6WBoxScore
93 - 2022-01-12627Monsters2Bruins3LBoxScore
95 - 2022-01-14642Sharks4Monsters3LBoxScore
97 - 2022-01-16662Monsters4Monarchs6LBoxScore
98 - 2022-01-17674Monsters3Admirals7LBoxScore
100 - 2022-01-19688Monsters5Sharks2WBoxScore
102 - 2022-01-21700Monsters6Las Vegas5WBoxScore
105 - 2022-01-24719Bruins7Monsters2LBoxScore
107 - 2022-01-26733Caroline6Monsters9WBoxScore
109 - 2022-01-28751Spiders5Monsters6WBoxScore
110 - 2022-01-29758Monsters4Wolf Pack3WXXBoxScore
113 - 2022-02-01766Oceanics5Monsters4LXBoxScore
123 - 2022-02-11792Monsters3Crunch2WBoxScore
124 - 2022-02-12807Monsters3Rocket5LBoxScore
126 - 2022-02-14818Cabaret Lady Mary Ann2Monsters6WBoxScore
129 - 2022-02-17841Cougars5Monsters3LBoxScore
130 - 2022-02-18851Monsters5Monsters2LBoxScore
132 - 2022-02-20863Thunder3Monsters7WBoxScore
135 - 2022-02-23880Monsters6Crunch2WBoxScore
136 - 2022-02-24893Wolf Pack3Monsters5WBoxScore
138 - 2022-02-26912Monsters2Spiders5LBoxScore
140 - 2022-02-28920Monsters4Phantoms5LBoxScore
142 - 2022-03-02936Phantoms1Monsters4WBoxScore
144 - 2022-03-04955Monsters4Chill2WBoxScore
146 - 2022-03-06967Senators4Monsters7WBoxScore
147 - 2022-03-07978Monsters6Minnesota3WBoxScore
150 - 2022-03-10995Minnesota2Monsters3WBoxScore
152 - 2022-03-121013Comets4Monsters1LBoxScore
155 - 2022-03-151030Monsters2Heat5LBoxScore
158 - 2022-03-181058Monsters4Oil Kings5LXXBoxScore
159 - 2022-03-191064Monsters1Comets4LBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
163 - 2022-03-231088Manchots3Monsters1LBoxScore
165 - 2022-03-251105Chill5Monsters3LBoxScore
167 - 2022-03-271118Monsters3Bruins1WBoxScore
170 - 2022-03-301141Bears3Monsters2LBoxScore
172 - 2022-04-011155Monsters2Marlies1WXXBoxScore
174 - 2022-04-031171Monsters3Spiders5LBoxScore
175 - 2022-04-041178Monsters1Wolf Pack5LBoxScore
178 - 2022-04-071199Monsters7Thunder2WBoxScore
179 - 2022-04-081212Monsters3Stars5LBoxScore
181 - 2022-04-101226Sound Tigers4Monsters7WBoxScore
184 - 2022-04-131249Thunder1Monsters7WBoxScore
185 - 2022-04-141255Monsters2Caroline3LXXBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Capacity20001000
Ticket Price3515
Attendance78,19939,270
Attendance PCT95.36%95.78%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueCapacityTeam Popularity
0 2865 - 95.50% 81,122$3,326,015$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
3,134,039$ 3,269,374$ 3,269,374$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
17,483$ 3,134,039$ 30 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 17,483$ 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