Monsters

GP: 49 | W: 24 | L: 24 | OTL: 1 | P: 49
GF: 181 | GA: 188 | PP%: 17.35% | PK%: 81.15%
GM : Patrick Auger | Morale : 50 | Team Overall : 62
Next Games #786 vs Wolfpack

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
1Justin Brazeau0X99.007143946293888261656260645965674250640
2Pierrick Dube0X100.005538786465956763666164576362644250620
3Anthony Angello0X99.008444705791748058635456605767694750610
4Brayden Burke0X100.005637856165717062666457566166684250600
5David Cotton0X100.007138905880737754615556575566684750590
6Nikita Pavlychev0X100.008642795495736453575455615466684750590
7Aarne Talvitie0X100.006336935572708454625654555964664850580
8Max Veronneau0X100.006737955576736554605852575368703650580
9Ty Smith0X100.006137876968878166307263615463658250650
10Josiah Didier0X100.007242705581658052305453564570755050600
11Darien Kielb0X100.007141745680726654305755564764664350600
12Jack Dougherty0X100.007139895380616452305450554567696150580
Scratches
1Chris Wagner0XX100.008440736073888359655859675674753650640
2Jake Leschyshyn0X92.926637886371768464786559626664666850630
3Jonah Gadjovich0X100.008179606382737459576058575964656850610
4Tommy Cross0X100.007543695684727555305852574674794150620
5Logan Day0X100.007039885679728055305951574569713650610
TEAM AVERAGE99.41714281597975755752595659546769495061
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
1Laurent Brossoit100.00807271867978807978807971845150770
Scratches
TEAM AVERAGE100.0080727186797880797880797184515077
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Bob Boughner75747376787272CAN5261,000,000$


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
1Jake LeschyshynMonsters (Clb)C4729346335220421081785112416.29%1487118.547815289200071633166.23%83800001.4500000463
2Ty SmithMonsters (Clb)D4910475765351348013237787.58%96116523.786814791590110172100.00%000000.9800100425
3Justin BrazeauMonsters (Clb)RW362728553223555761825612814.84%2082622.97312153010711281894165.12%41000011.3300001584
4Anthony AngelloMonsters (Clb)C3628204827810109822446218211.48%3767418.7453848102000002065.92%57800021.4200002323
5Logan DayMonsters (Clb)D3642933034064366021446.67%4872120.0536935860000114100.00%000000.9100000322
6Max VeronneauMonsters (Clb)RW36921301560103584245410.71%1150013.91000000001562064.81%5400011.2000000041
7David CottonMonsters (Clb)C3611182921100131578205614.10%746212.8400000000000068.75%6400001.2500000003
8Nikita PavlychevMonsters (Clb)C36151227166315815491276516.48%445212.5600003000013159.36%47000011.1900102401
9Jonah GadjovichMonsters (Clb)LW2812921198020722581126114.81%752218.6733613730004725050.00%3800000.8000202103
10Jack DoughertyMonsters (Clb)D36215171252051212212239.09%3050313.9900022000052000.00%000000.6800000000
11Darien KielbMonsters (Clb)D2551217-7400632141203612.20%3146118.474483057000069110.00%000000.7400000110
12Tommy CrossMonsters (Clb)D211121344956314215174.76%2146422.100661053011082000.00%000000.5600001020
13Pierrick DubeMonsters (Clb)RW5448500183062413.33%011122.360111110000201068.00%2500001.4300000000
14Josiah DidierMonsters (Clb)D151568160311067116.67%1419813.2200006000011000.00%000000.6100000001
15Aarne TalvitieMonsters (Clb)C36213-2209121951610.53%51213.380115240000140052.63%7600000.4900000000
16Brayden BurkeMonsters (Clb)LW1000100010100.00%022.780000000000000.00%000000.0000000000
Team Total or Average47916026742716752860798598126936690912.61%345806116.8331528328178213420102223464.12%255300051.0600408252726
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
1Laurent BrossoitMonsters (Clb)88000.9371.5048101121900000.000080200
Team Total or Average88000.9371.5048101121900000.000080200


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
Aarne TalvitieC251999-02-11No198 Lbs5 ft11NoNoNo2RFAPro & Farm300,000$0$0$NoLink
Anthony AngelloC271996-03-06No210 Lbs6 ft5NoNoNo3RFAPro & Farm500,000$0$0$NoLink / NHL Link
Brayden BurkeLW271997-01-01No165 Lbs5 ft11NoNoNo4RFAPro & Farm300,000$0$0$NoLink / NHL Link
Chris WagnerC/RW321991-05-27No192 Lbs6 ft0NoNoNo2UFAPro & Farm400,001$0$0$NoLink / NHL Link
Darien KielbD241999-03-18No181 Lbs6 ft3NoNoNo1RFAPro & Farm300,000$0$0$NoLink
David CottonC261997-07-09No200 Lbs6 ft2NoNoNo2RFAPro & Farm300,000$0$0$NoLink
Jack DoughertyD271996-05-25No196 Lbs6 ft2NoNoNo1RFAPro & Farm300,000$0$0$NoLink / NHL Link
Jake Leschyshyn (Out of Payroll)C241999-03-10No195 Lbs5 ft11NoNoNo1RFAPro & Farm300,000$0$0$YesLink / NHL Link
Jonah GadjovichLW251998-10-12No209 Lbs6 ft2NoNoNo3RFAPro & Farm300,000$0$0$NoLink / NHL Link
Josiah DidierD301993-04-08No202 Lbs6 ft2NoNoNo2UFAPro & Farm300,000$0$0$NoLink / NHL Link
Justin BrazeauRW261998-02-02No220 Lbs6 ft5NoNoNo2RFAPro & Farm300,000$0$0$NoLink
Laurent BrossoitG301993-03-23No215 Lbs6 ft3NoNoNo3UFAPro & Farm1,000,000$0$0$NoLink / NHL Link
Logan DayD291994-09-19No209 Lbs6 ft1NoNoNo1UFAPro & Farm300,000$0$0$NoLink / NHL Link
Max VeronneauRW281995-12-12No193 Lbs6 ft1NoNoNo3UFAPro & Farm300,000$0$0$NoLink
Nikita PavlychevC261997-03-23No200 Lbs6 ft7NoNoNo3RFAPro & Farm300,000$0$0$NoLink
Pierrick DubeRW232001-01-07No172 Lbs5 ft9NoNoNo2RFAPro & Farm300,000$0$0$NoLink
Tommy CrossD341989-09-12No205 Lbs6 ft3NoNoNo4UFAPro & Farm500,000$0$0$NoLink / NHL Link
Ty SmithD232000-03-24No180 Lbs5 ft11NoNoNo2RFAPro & Farm900,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
1827.00197 Lbs6 ft22.28400,000$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Justin Brazeau40122
2Anthony Angello30122
3David CottonNikita PavlychevMax Veronneau20122
4Justin BrazeauDavid Cotton10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty Smith40122
230122
3Jack Dougherty20122
4Ty Smith10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Justin Brazeau60122
2Anthony Angello40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty Smith60122
240122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Justin Brazeau60122
240122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty Smith60122
240122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Justin Brazeau60122Ty Smith60122
24012240122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Justin Brazeau60122
240122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ty Smith60122
240122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Justin BrazeauTy Smith
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Justin BrazeauTy Smith
Extra Forwards
Normal PowerPlayPenalty Kill
Aarne Talvitie, Nikita Pavlychev, Max VeronneauAarne Talvitie, Nikita PavlychevMax Veronneau
Extra Defensemen
Normal PowerPlayPenalty Kill
, Jack Dougherty, Jack Dougherty,
Penalty Shots
Justin Brazeau, , , , Anthony Angello
Goalie
#1 : , #2 :
Custom OT Lines Forwards
Justin Brazeau, , , , Anthony Angello, , , Nikita Pavlychev, David Cotton, Max Veronneau, Aarne Talvitie
Custom OT Lines Defensemen
Ty Smith, , , ,


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
4949L11813195001573152046860896711
All Games
GPWLOTWOTL SOWSOLGFGA
4922242100181188
Home Games
GPWLOTWOTL SOWSOLGFGA
2491221008399
Visitor Games
GPWLOTWOTL SOWSOLGFGA
25131200009889
Last 10 Games
WLOTWOTL SOWSOL
541000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1963417.35%2444681.15%2
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
54151951037949512
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
805146454.99%701137151.13%41775255.45%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
12679391130311544279


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
5 - 2023-08-1421Monsters0Phantoms4LBoxScore
6 - 2023-08-1529Monsters3Bears5LBoxScore
11 - 2023-08-2035Crunch5Monsters4LBoxScore
12 - 2023-08-2149Crunch6Monsters4LBoxScore
18 - 2023-08-2779Monsters2Griffins7LBoxScore
19 - 2023-08-2894Monsters4Wolves3WBoxScore
23 - 2023-09-01107Griffins4Monsters1LBoxScore
25 - 2023-09-03114Bruins5Monsters2LBoxScore
26 - 2023-09-04128Bruins3Monsters1LBoxScore
32 - 2023-09-10153Monsters2Senators9LBoxScore
34 - 2023-09-12173Monsters2Senators8LBoxScore
38 - 2023-09-16191Americans9Monsters0LBoxScore
40 - 2023-09-18209Americans5Monsters0LBoxScore
42 - 2023-09-20223Monsters9Checkers1WBoxScore
44 - 2023-09-22231Monsters5Checkers1WBoxScore
46 - 2023-09-24240Marlies0Monsters3WBoxScore
48 - 2023-09-26266Monsters6Marlies1WBoxScore
54 - 2023-10-02292Comets3Monsters4WXBoxScore
55 - 2023-10-03304Comets3Monsters4WBoxScore
58 - 2023-10-06311Monsters3Wolfpack2WBoxScore
60 - 2023-10-08320Monsters2Penguins1WBoxScore
61 - 2023-10-09332Monsters4Bears3WBoxScore
66 - 2023-10-14357Senators6Monsters4LBoxScore
67 - 2023-10-15360Senators2Monsters4WBoxScore
72 - 2023-10-20391Monsters2Americans3LBoxScore
74 - 2023-10-22404Monsters7Crunch3WBoxScore
75 - 2023-10-23418Monsters5Comets2WBoxScore
79 - 2023-10-27428Marlies3Monsters7WBoxScore
82 - 2023-10-30459Monsters7Wolves3WBoxScore
83 - 2023-10-31465Monsters0Griffins3LBoxScore
86 - 2023-11-03471Monsters2Marlies3LBoxScore
88 - 2023-11-05479Monsters2Americans5LBoxScore
89 - 2023-11-06492Americans9Monsters1LBoxScore
95 - 2023-11-12520Monsters2Comets5LBoxScore
96 - 2023-11-13536Monsters10Crunch4WBoxScore
102 - 2023-11-19566Phantoms3Monsters2LXBoxScore
103 - 2023-11-20574Phantoms3Monsters5WBoxScore
107 - 2023-11-24599Marlies3Monsters5WBoxScore
109 - 2023-11-26609Wolfpack6Monsters1LBoxScore
110 - 2023-11-27625Wolfpack5Monsters1LBoxScore
115 - 2023-12-02652Wolves2Monsters6WBoxScore
117 - 2023-12-04668Wolves4Monsters5WXBoxScore
123 - 2023-12-10686Checkers1Monsters8WBoxScore
125 - 2023-12-12711Checkers3Monsters8WBoxScore
127 - 2023-12-14712Griffins6Monsters3LBoxScore
130 - 2023-12-17727Monsters1Griffins3LBoxScore
131 - 2023-12-18740Monsters7Wolves2WBoxScore
132 - 2023-12-19751Monsters8Wolves2WBoxScore
137 - 2023-12-24773Monsters3Bruins6LBoxScore
138 - 2023-12-25786Monsters-Wolfpack-
139 - 2023-12-26799Monsters-Bruins-
142 - 2023-12-29808Marlies-Monsters-
144 - 2023-12-31818Wolves-Monsters-
145 - 2024-01-01829Wolves-Monsters-
147 - 2024-01-03848Griffins-Monsters-
151 - 2024-01-07860Monsters-Rocket-
152 - 2024-01-08869Monsters-Rocket-
Trade Deadline --- Trades can’t be done after this day is simulated!
155 - 2024-01-11891Griffins-Monsters-
160 - 2024-01-16930Penguins-Monsters-
161 - 2024-01-17937Penguins-Monsters-
164 - 2024-01-20950Bears-Monsters-
166 - 2024-01-22964Bears-Monsters-
170 - 2024-01-26989Monsters-Griffins-
173 - 2024-01-291007Americans-Monsters-
177 - 2024-02-021030Monsters-Americans-
179 - 2024-02-041041Monsters-Penguins-
180 - 2024-02-051053Monsters-Phantoms-
185 - 2024-02-101074Rocket-Monsters-
187 - 2024-02-121094Rocket-Monsters-
193 - 2024-02-181123Monsters-Americans-
194 - 2024-02-191130Monsters-Marlies-
195 - 2024-02-201148Monsters-Marlies-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance45,01522,898
Attendance PCT93.78%95.41%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
12 2830 - 94.32% 70,363$1,688,716$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
750,042$ 69,000$ 0$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 47,411$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
844,358$ 58 5,482$ 317,956$




OverallHomeVisitor
Year GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
Regular Season
12825322021312921741184126120102015187644127100111114187541182925328242901238579251208258688101662505138418105338315.57%5727087.76%91707271062.99%1238224555.14%709116360.96%237217381629547947509
12825322021312921741184126120102015187644127100111114187541182925328242901238579251208258688101662505138418105338315.57%5727087.76%91707271062.99%1238224555.14%709116360.96%237217381629547947509
13764621011342421509238211200113115744138259010211277651105242417659112092786820700668676715147144598814065299517.96%4315487.47%61490244360.99%1204208657.72%659104563.06%213515611561528899478
13764621011342421509238211200113115744138259010211277651105242417659112092786820700668676715147144598814065299517.96%4315487.47%61490244360.99%1204208657.72%659104563.06%213515611561528899478
147642220314427115611538231101012137766138191102132134805410327148475511101127775229907587477731757503112314523345416.17%4315687.01%41366241056.68%1321230557.31%640110957.71%204314781655527908469
147642220314427115611538231101012137766138191102132134805410327148475511101127775229907587477731757503112314523345416.17%4315687.01%41366241056.68%1321230557.31%640110957.71%204314781655527908469
1582343404325227179484121160111111980394113180321410899988227424651080877856235007557468211907583113714524056516.05%4536685.43%11490259557.42%1305235755.37%645113956.63%218115761808570980504
1582343404325227179484121160111111980394113180321410899988227424651080877856235007557468211907583113714524056516.05%4536685.43%11490259557.42%1305235755.37%645113956.63%218115761808570980504
16824425035322481608841201302321119833641241201211129775210724845570308089827122140767715713179353496013894577716.85%4064888.18%71469247859.28%1211226453.49%681113360.11%227616741741544943502
16824425035322481608841201302321119833641241201211129775210724845570308089827122140767715713179353496013894577716.85%4064888.18%71469247859.28%1211226453.49%681113360.11%227616741741544943502
177231330242023521322361814013001171071036131901120118106127423541064539092746519800646688633183255482313793658021.92%3326979.22%31131211353.53%1039202751.26%560108751.52%192414161601469816425
177231330242023521322361814013001171071036131901120118106127423541064539092746519800646688633183255482313793658021.92%3326979.22%31131211353.53%1039202751.26%560108751.52%192414161601469816425
1849222402100181188-724912021008399-162513120000098899491813195001179495121573541519510315204686089671963417.35%2444681.15%2805146454.99%701137151.13%41775255.45%12679391130311544279
Total Regular Season989522338032313432321122529594942671680141714141599111348649525517001814201816121139473123932115763897415115791239999830284235419357939089332236467161343818743544294217.31%549477285.95%62181113096258.49%153372793954.89%82051410458.17%2713519832211266688115356059
Playoff
122016400000491930108200000219121082000002810183249831320601218174660143156146405121392396141149.93%1661093.98%338167356.61%36566654.80%16827960.22%509338516168266131
122016400000491930108200000219121082000002810183249831320601218174660143156146405121392396141149.93%1661093.98%338167356.61%36566654.80%16827960.22%509338516168266131
13514000001012-2211000005323030000059-4210172700053295038263112245807533515.15%36586.11%05813842.03%6416339.26%407652.63%10871129386230
13514000001012-2211000005323030000059-4210172700053295038263112245807533515.15%36586.11%05813842.03%6416339.26%407652.63%10871129386230
141899000003743-61037000001026-16862000002717101837691060201610945201731271344371222623861071312.15%1161487.93%128158148.36%30161548.94%12625848.84%455313458143242118
141899000003743-61037000001026-16862000002717101837691060201610945201731271344371222623861071312.15%1161487.93%128158148.36%30161548.94%12625848.84%455313458143242118
Total Playoff8652340000019214844442420000007276-44228140000012072481041923385300160666256202607086186221928576146817145626411.39%6365890.88%81440278451.72%1460288850.55%668122654.49%2147144722087011141561