Crunch

GP: 7 | W: 0 | L: 6 | OTL: 1 | P: 1
GF: 9 | GA: 31 | PP%: 7.69% | PK%: 78.79%
GM : Nick Fournier | Morale : 50 | Team Overall : 63
Next Games #112 vs Wolfpack

Filter Tips
PriorityTypeDescription
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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 #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
1Miles Wood0X100.007245697379778168566662726374714950670
2Jesse Puljujarvi0X100.008140836790817765586263646769707650650
3Zachary L'Heureux0X100.007661556772818568646565636662648050650
4Drake Caggiula0X100.006839726567838162696461636272733450640
5Marat Khusnutdinov0X100.006734916968807763756160715962637650640
6Reid Schaefer0X100.008654746095807561596260646163647750640
7Lane Pederson0X100.006441776373847562716362606168703650630
8Marc Gatcomb0X100.007939866479778562656063616466674250630
9Stephen Halliday0X100.007740806286827561736557625963656150630
10Rutger McGroarty0X100.006939836678887264626560626461638450630
11Max Willman0X100.006636916471818263665862596470724750630
12Justin Robidas0X100.006335956466857363716261606562645650620
13Oliver Kapanen0X100.005536956479776163716260665561626750620
14Jett Luchanko0X100.006539756668816163726050646560628750600
15Nathan Gaucher0X100.007650695885738455625657595862648250600
16Adam Sykora0X100.005935955766828656605856595561636850590
17Nikolas Brouillard0X100.007052656064718659306455564870723550610
18Topias Vilen0X100.006738906076658158306452574662645850610
19Wyatt Newpower0X100.007345635882657357305653594668703650610
20Mike Benning0X100.005738796066758359306257554863656250600
21Blake Hillman0X100.006738945776638056305553544569714050600
Scratches
1Adam Erne0X100.007169825880737257525653595570726250590
2Brendan Lemieux0X100.007874535880776757545659555871706350590
3Gavin Brindley0X100.005536865964796958625554575661637750580
4Ole Bjorgvik-Holm0X100.006941705578646854305253564563655750580
5Angus Booth0X100.006139765570646854305753564561635950570
TEAM AVERAGE100.00694479627576766055605861576567605062
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
1Oscar Dansk100.00728378847170727170727172856150720
Scratches
1Isaac Poulter100.00758379757473757473757464714350720
2Sergei Murashov100.00747571757372747372747361656050700
TEAM AVERAGE100.0074807678737274737274736674555071
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Ben Simon66636475696580USA4671,000,000$


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
1Drake CaggiulaCrunch (Tam)LW7325-710022192691611.54%316123.09000627000000030.77%1300000.6200000000
2Marat KhusnutdinovCrunch (Tam)C7213-960521163712.50%113118.8200000000000060.87%4600000.4600000000
3Lane PedersonCrunch (Tam)C3112-2208882512.50%05618.71112411000000047.27%5500000.7100000010
4Max LajoieTampa LightningD5022-616010810230.00%611723.570009150000700100.00%200000.3400000000
5Reid SchaeferCrunch (Tam)LW7112-13100202178414.29%315121.6100000000020046.74%9200000.2600000000
6Stephen HallidayCrunch (Tam)C7011-720779250.00%214220.3400003000000052.00%5000000.1400000000
7Max WillmanCrunch (Tam)C7011-118010134230.00%514721.1300000000000051.35%3700000.1400000000
8Mike BenningCrunch (Tam)D7000-860785140.00%613319.0400000000040020.00%500000.0000000000
Team Total or Average507916-63600891058529478.24%26104220.8511219580000140049.67%30000000.3100000010
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
Team Total or Average0.0000.0000.000


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 NamePOS Age Birthday Rookie Weight Height No Trade Available For Trade Force Waivers Contract StatusType Current Salary Salary Cap Salary Cap Remaining Exclude from Salary Cap Link
Adam ErneLW301995-04-20No215 Lbs6 ft1NoNoNo2UFAPro & Farm1,000,000$0$0$NoLink / NHL Link
Adam SykoraLW212004-09-07No179 Lbs5 ft10NoNoNo3ELCPro & Farm500,000$0$0$NoLink / NHL Link
Angus BoothD212004-04-27No177 Lbs6 ft0NoNoNo4ELCPro & Farm300,000$0$0$NoLink
Blake HillmanD291996-01-26No193 Lbs6 ft1NoNoNo4UFAPro & Farm500,000$0$0$NoLink / NHL Link
Brendan LemieuxLW291996-03-15No215 Lbs6 ft1NoNoNo2UFAPro & Farm500,000$0$0$NoLink / NHL Link
Drake CaggiulaLW311994-06-20No179 Lbs5 ft10NoNoNo2UFAPro & Farm500,000$0$0$NoLink / NHL Link
Gavin BrindleyC212004-10-05No175 Lbs5 ft9NoNoNo4ELCPro & Farm900,000$0$0$NoLink
Isaac PoulterG242001-09-12No174 Lbs6 ft2NoNoNo3RFAPro & Farm500,000$0$0$NoLink / NHL Link
Jesse PuljujarviRW271998-05-07No216 Lbs6 ft4NoNoNo4UFAPro & Farm500,000$0$0$NoLink / NHL Link
Jett LuchankoC192006-08-21No180 Lbs5 ft11NoNoNo4ELCPro & Farm900,000$0$0$NoLink
Justin RobidasC222003-03-13No176 Lbs5 ft8NoNoNo4ELCPro & Farm300,000$0$0$NoLink
Lane PedersonC281997-08-04No192 Lbs6 ft0NoNoNo1UFAPro & Farm300,000$0$0$NoLink / NHL Link
Marat KhusnutdinovC232002-07-17No176 Lbs5 ft11NoNoNo3RFAPro & Farm500,000$0$0$NoLink / NHL Link
Marc GatcombRW261999-07-22No195 Lbs6 ft2NoNoNo2RFAPro & Farm300,000$0$0$NoLink / NHL Link
Max WillmanC301995-02-13No184 Lbs6 ft0NoNoNo2UFAPro & Farm500,000$0$0$NoLink / NHL Link
Mike BenningD232002-01-05No185 Lbs5 ft9NoNoNo3RFAPro & Farm500,000$0$0$NoLink / NHL Link
Miles WoodLW301995-09-13No195 Lbs6 ft2NoNoNo4UFAPro & Farm500,000$0$0$NoLink / NHL Link
Nathan GaucherC212003-11-06No207 Lbs6 ft3NoNoNo3ELCPro & Farm900,000$0$0$NoLink / NHL Link
Nikolas BrouillardD301995-02-07No168 Lbs5 ft10NoNoNo2UFAPro & Farm500,000$0$0$NoLink / NHL Link
Ole Bjorgvik-HolmD232002-05-23No190 Lbs6 ft2NoNoNo4RFAPro & Farm300,000$0$0$NoLink
Oliver KapanenC222003-07-29No194 Lbs6 ft2NoNoNo4ELCPro & Farm300,000$0$0$NoLink
Oscar DanskG311994-02-28No204 Lbs6 ft3NoNoNo2UFAPro & Farm750,000$0$0$NoLink / NHL Link
Reid SchaeferLW222003-09-21No226 Lbs6 ft5NoNoNo3ELCPro & Farm900,000$0$0$NoLink / NHL Link
Rutger McGroartyRW212004-03-30No203 Lbs6 ft1NoNoNo4ELCPro & Farm900,000$0$0$NoLink
Sergei MurashovG212004-04-01No175 Lbs6 ft2NoNoNo4ELCPro & Farm300,000$0$0$NoLink
Stephen HallidayC232002-07-02No213 Lbs6 ft3NoNoNo3RFAPro & Farm500,000$0$0$NoLink / NHL Link
Topias VilenD222003-04-01No194 Lbs6 ft1NoNoNo3ELCPro & Farm300,000$0$0$NoLink / NHL Link
Wyatt NewpowerD271997-12-09No194 Lbs6 ft3NoNoNo1UFAPro & Farm300,000$0$0$NoLink / NHL Link
Zachary L'HeureuxLW222003-05-15No197 Lbs5 ft11NoNoNo3ELCPro & Farm900,000$0$0$NoLink / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2924.79192 Lbs6 ft13.00546,552$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Drake Caggiula40122
230122
3Max Willman20122
4Drake CaggiulaMarat Khusnutdinov10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
140122
230122
3Mike Benning20122
410122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Drake Caggiula60122
240122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
160122
240122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
160122
240122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
160122
240122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
16012260122
24012240122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
160122
240122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
160122
240122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Drake Caggiula
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Drake Caggiula
Extra Forwards
Normal PowerPlayPenalty Kill
, Reid Schaefer, Stephen Halliday, Reid SchaeferStephen Halliday
Extra Defensemen
Normal PowerPlayPenalty Kill
, Mike Benning, Mike Benning,
Penalty Shots
, , , ,
Goalie
#1 : , #2 :


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
71L591322114229557312200
All Games
GPWLOTWOTL SOWSOLGFGA
7060100931
Home Games
GPWLOTWOTL SOWSOLGFGA
201010047
Visitor Games
GPWLOTWOTL SOWSOLGFGA
5050000524
Last 10 Games
WLOTWOTL SOWSOL
060100
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
3937.69%33778.79%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
33453604230
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
7217940.22%7020234.65%5111245.54%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
13085204548537


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
8 - 2025-08-221Crunch1Comets5LBoxScore
9 - 2025-08-2313Senators4Crunch3LXBoxScore
15 - 2025-08-2934Crunch0Rocket3LBoxScore
16 - 2025-08-3044Crunch2Rocket6LBoxScore
17 - 2025-08-3160Crunch1Senators4LBoxScore
22 - 2025-09-0572Penguins3Crunch1LBoxScore
23 - 2025-09-0685Crunch1Penguins6LBoxScore
29 - 2025-09-12112Wolfpack-Crunch-
30 - 2025-09-13124Senators-Crunch-
34 - 2025-09-17142Crunch-Wolfpack-
37 - 2025-09-20160Monsters-Crunch-
41 - 2025-09-24185Crunch-Senators-
43 - 2025-09-26192Rocket-Crunch-
44 - 2025-09-27205Crunch-Comets-
50 - 2025-10-03229Comets-Crunch-
51 - 2025-10-04247Bears-Crunch-
55 - 2025-10-08263Senators-Crunch-
57 - 2025-10-10273Crunch-Americans-
58 - 2025-10-11281Americans-Crunch-
62 - 2025-10-15302Rocket-Crunch-
64 - 2025-10-17310Crunch-Monsters-
65 - 2025-10-18321Crunch-Monsters-
69 - 2025-10-22345Crunch-Senators-
71 - 2025-10-24353Bears-Crunch-
72 - 2025-10-25365Comets-Crunch-
76 - 2025-10-29391Crunch-Americans-
78 - 2025-10-31402Crunch-Americans-
85 - 2025-11-07430Crunch-Rocket-
86 - 2025-11-08438Crunch-Rocket-
90 - 2025-11-12466Crunch-Marlies-
92 - 2025-11-14471Senators-Crunch-
93 - 2025-11-15485Phantoms-Crunch-
97 - 2025-11-19503Crunch-Comets-
99 - 2025-11-21510Marlies-Crunch-
100 - 2025-11-22525Americans-Crunch-
104 - 2025-11-26548Bruins-Crunch-
106 - 2025-11-28558Crunch-Islanders-
107 - 2025-11-29571Crunch-Bruins-
109 - 2025-12-01588Comets-Crunch-
113 - 2025-12-05603Islanders-Crunch-
114 - 2025-12-06616Monsters-Crunch-
120 - 2025-12-12652Crunch-Americans-
121 - 2025-12-13662Americans-Crunch-
127 - 2025-12-19677Comets-Crunch-
128 - 2025-12-20695Crunch-Bears-
132 - 2025-12-24712Crunch-Marlies-
134 - 2025-12-26725Crunch-Americans-
135 - 2025-12-27735Crunch-Phantoms-
141 - 2026-01-02769Marlies-Crunch-
142 - 2026-01-03782Rocket-Crunch-
148 - 2026-01-09815Penguins-Crunch-
149 - 2026-01-10828Americans-Crunch-
150 - 2026-01-11840Crunch-Comets-
Trade Deadline --- Trades can’t be done after this day is simulated!
155 - 2026-01-16861Crunch-Comets-
157 - 2026-01-18886Crunch-Penguins-
160 - 2026-01-21892Comets-Crunch-
162 - 2026-01-23902Thunderbirds-Crunch-
163 - 2026-01-24917Crunch-Thunderbirds-
169 - 2026-01-30949Crunch-Phantoms-
170 - 2026-01-31963Americans-Crunch-
176 - 2026-02-06991Comets-Crunch-
177 - 2026-02-071004Americans-Crunch-
178 - 2026-02-081019Crunch-Americans-
181 - 2026-02-111030Crunch-Senators-
183 - 2026-02-131039Marlies-Crunch-
184 - 2026-02-141051Crunch-Marlies-
188 - 2026-02-181074Crunch-Comets-
190 - 2026-02-201080Phantoms-Crunch-
191 - 2026-02-211095Rocket-Crunch-
195 - 2026-02-251113Crunch-Bears-
197 - 2026-02-271126Crunch-Comets-
198 - 2026-02-281141Comets-Crunch-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance3,8641,901
Attendance PCT96.60%95.05%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
34 2883 - 96.08% 72,053$144,105$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
151,592$ 158,500$ 158,500$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 21,592$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
2,449,785$ 174 5,792$ 1,007,808$




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
14764024032432331409338221000141125656038181403102108753399233426659210090756122100746698748171852895914343385716.86%3784288.89%51375243956.38%1220228353.44%609108756.03%199214231706527906471
14764024032432331409338221000141125656038181403102108753399233426659210090756122100746698748171852895914343385716.86%3784288.89%51375243956.38%1220228353.44%609108756.03%199214231706527906471
158243250363225618769412290342113479554121160021112210814106256469725180967975252208318448261834508102713824586313.76%4096185.09%71643275559.64%1282226256.68%716121059.17%223116161760567974508
158243250363225618769412290342113479554121160021112210814106256469725180967975252208318448261834508102713824586313.76%4096185.09%71643275559.64%1282226256.68%716121059.17%223116161760567974508
1682333902323272299-2741171900212145149-441162002111127150-2380272441713150112718525420832773913243573490513734128620.87%3867381.09%61317254051.85%1113237146.94%634130348.66%195614222079553920450
177233280212629026426361812000241521312136151602102138133581290441731130123798426320851832927238771270312803476017.29%2946577.89%11186228052.02%946219343.14%608118851.18%168612591905470774367
1872106100100169412-243365310000086195-109365300010083217-1342116932149010073435319540637601716324290166612302853512.28%2507171.60%4709184738.39%802238633.61%451118338.12%11217512432517766310
1970125200222149345-196357250011181165-84355270011168180-1123214928343221054464717780554589626277882171412053174112.93%3016678.07%1819186943.82%839228636.70%405107537.67%12228392254500748313
2070600100931-222010010047-350500000524-19191322004230114334536022955731223937.69%33778.79%07217940.22%7020234.65%5111245.54%13085204548537
Total Regular Season8533743570273630292568248979425195162010192415135011691814281791950171761412181320-10292725684547711515784100078672124845338111802684832332068661058815739428265915.39%429366484.53%52144132639854.60%125852537449.60%67511281652.68%208031487820935593098724913
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