Senators

GM : Ondrej Ptacek Morale : 50 Team Overall : 57
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# Player Name C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SP
1Miikka Salomaki (R)XX100.00824683776574686560404268505151051620
2Robby Fabbri (R)XXX100.00655286836077686961464960505353049620
3Sergei PlotnikovXX100.00774666775853676560373860504848048570
4Tom KuhnhacklXX100.00684466705558736460444265504747051570
5Michael McCarron (R)XX100.00769958666056616379394057504545054560
6Viktor TikhonovXXX100.00664366725456606360394160505757048560
7Zack Mitchell (R)X100.00726875625370656169333958564444051550
8Daniel CatenacciXX100.00724477735250606058373857504545051540
9Stefan Noesen (R)XX100.00627663695862625876363460504444048540
10Jordan WealXX100.00564168695050626274373858504545046530
11Tanner Richard (R)X100.00566559625069666074433456504444050530
12Felix Girard (R)X100.00576659605168655565323054504444047500
13Klas DahlbeckX100.00854685757370886125413978505656048650
14Chris WidemanX100.00694281746666856925414373505151051620
15Scott Harrington (R)X100.00724588737262666825393771506060051610
16Dylan Blujus (R)X100.00837395706979785125303262505555049600
17Jakub NakladalX100.00744567676165656925384069504646048580
18Oliver Kylington (R)X100.00596767735758635625323559505555051540
Scratches
1Brian Hart (R)XX100.00607562635648575259253155504444046490
2Mark MacMillan (R)XX100.00566459635053605564313252504444046490
3Danny BiegaX100.00577464715965685825293257504646046530
4Joey LaLeggia (R)X100.00556461725561656625343254504444046530
5Matt Finn (R)X100.00567162645861656625323357504646046530
6Patrick McNally (R)X100.00596967615757635325242758504646046500
TEAM AVERAGE100.0066597069586267614936376150484804956
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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
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
1Jason Kasdorf (R)100.0066686575667965727366485555051660
2Richard Bachman99.0067726470687469716966535959048660
Scratches
1Rasmus Tirronen100.0058707265666864626061495555046610
TEAM AVERAGE99.676470677067746668676450565604864
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Kurt Kleinendorst54616365605860USA555100,000$


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1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Player Name Team Name# POS GP G A P +/- PIM PIM5 HIT SHT OSB OSM SHT% SB MP PPG PPA PPP PKG PKA PKP PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS
1Chris WidemanSenatorsSenators (OTT)D467131020419111131.58%625.:.2401100013000.00%064012.5600
2Robby FabbriSenatorsSenators (OTT)C/LW/RW4641035551451342.86%221.:.24202000140048.00%25254012.3400
3Jakub NakladalSenatorsSenators (OTT)D45499002123641.67%420.:.200000008100.00%026012.2100
4Scott HarringtonSenatorsSenators (OTT)D4178900815766.67%620.:.240000008000.00%027001.9600
5Klas DahlbeckSenatorsSenators (OTT)D434710001683637.50%1425.:.2600000014000.00%015011.3800
6Miikka SalomakiSenatorsSenators (OTT)LW/RW432560051331023.08%215.:.0100000051050.00%2140001.6600
7Michael McCarronSenatorsSenators (OTT)C/RW432555630684937.50%011.:.2900000000062.50%2461012.1800
8Viktor TikhonovSenatorsSenators (OTT)C/LW/RW4235400660333.33%217.:.1901100000041.03%7803001.4400
9Sergei PlotnikovSenatorsSenators (OTT)LW/RW403346088130.00%117.:.2601100000025.00%462000.8600
10Daniel CatenacciSenatorsSenators (OTT)C/LW403340090350.00%011.:.5200000030057.89%1960001.2600
11Zack MitchellSenatorsSenators (OTT)RW42134205222100.00%310.:.2600000000050.00%223001.4400
12Tom KuhnhacklSenatorsSenators (OTT)LW/RW4123620411479.09%116.:.480000001500100.00%1103000.8900
13Tanner RichardSenatorsSenators (OTT)C40228391552110.00%015.:.4700000000041.67%4801000.6300
14Oliver KylingtonSenatorsSenators (OTT)D401132042300.00%414.:.370000000000.00%022000.3400
15Dylan BlujusSenatorsSenators (OTT)D40113101065430.00%213.:.450000000000.00%016000.3600
16Stefan NoesenSenatorsSenators (OTT)LW/RW401145511010.00%010.:.130000000000.00%140000.4900
17Jordan WealSenatorsSenators (OTT)C/RW1000-30010100.00%212.:.4100000010066.67%311000.0000
Team Total or Average65324779891296595110126558625.40%49108316.672359280001862046.38%2078848051.4600445222
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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
1Richard BachmanSenatorsSenators (OTT)422092.6%2.4719400810865200.0%040010
2Jason KasdorfSenatorsSenators (OTT)100087.5%4.00450032415100.0%004000
Team Total or Average52200.9172.76239001113280300.000044010


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1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Player Name POS Age Birthday Rookie Weight Height No Trade Force Waivers Contract Type Current Salary Salary RemainingSalary Year 2 Salary Year 3 Salary Year 4 Salary Year 5 Salary Year 6 Salary Year 7 Salary Year 8 Salary Year 9 Salary Year 10 Link
Brian HartLW/RW2225.11.1993Yes203 Lbs6 ft2NoNo10Farm Only100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Chris WidemanD2607.01.1990 11:24:59No180 Lbs5 ft10NoNo1Pro & Farm1,300,000$0$Link
Daniel CatenacciC/LW2309.03.1993No192 Lbs5 ft9NoNo2Pro & Farm900,000$0$900,000$Link
Danny BiegaD2529.09.1991 15:13:00No205 Lbs6 ft0NoNo1Pro & Farm1,000,000$0$Link
Dylan BlujusD2222.01.1994Yes191 Lbs6 ft3NoNo9Farm Only100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Felix GirardC2209.05.1994Yes185 Lbs5 ft10NoNo9Farm Only100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Jakub NakladalD2829.12.1987No205 Lbs6 ft2NoNo1Pro & Farm1,500,000$0$Link
Jason KasdorfG2408.05.1992 17:28:26Yes178 Lbs6 ft3NoNo9Pro & Farm100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Joey LaLeggiaD2424.06.1992 15:05:47Yes183 Lbs5 ft9NoNo9Pro & Farm100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Jordan WealC/RW2415.04.1992 14:38:36No179 Lbs5 ft10NoNo1Pro & Farm1,000,000$0$Link
Klas DahlbeckD2506.07.1991 11:27:27No207 Lbs6 ft3NoNo1Pro & Farm1,200,000$0$Link
Mark MacMillanC/RW2423.01.1992Yes172 Lbs6 ft0NoNo10Farm Only100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Matt FinnD2224.02.1994Yes199 Lbs6 ft0NoNo9Farm Only100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Michael McCarronC/RW2107.03.1995 15:07:56Yes237 Lbs6 ft5NoNo3Pro & Farm1,200,000$0$1,200,000$1,200,000$Link
Miikka SalomakiLW/RW2309.03.1993 15:09:23Yes198 Lbs5 ft11NoNo2Farm Only900,000$0$900,000$Link
Oliver KylingtonD1919.05.1997 15:04:29Yes181 Lbs6 ft0NoNo9Pro & Farm100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Patrick McNallyD2404.12.1991Yes181 Lbs6 ft2NoNo10Farm Only100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Rasmus TirronenG2509.11.1990 0:01:39No200 Lbs6 ft3NoNo9Farm Only100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Richard BachmanG2925.07.1987No183 Lbs5 ft10NoNo2Pro & Farm900,000$0$900,000$Link
Robby FabbriC/LW/RW2022.01.1996 16:54:46Yes170 Lbs5 ft10NoNo3Pro & Farm1,600,000$0$1,600,000$1,600,000$Link
Scott HarringtonD2301.01.1993 15:15:41Yes201 Lbs6 ft2NoNo1Pro & Farm1,000,000$0$Link
Sergei PlotnikovLW/RW2603.06.1990 3:23:02No205 Lbs6 ft2NoNo1Pro & Farm1,000,000$0$Link
Stefan NoesenLW/RW2312.02.1993Yes205 Lbs6 ft2NoNo9Farm Only100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Tanner RichardC2306.04.1993 11:30:09Yes176 Lbs6 ft0NoNo7Farm Only100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$Link
Tom KuhnhacklLW/RW2421.02.1992 11:31:02No196 Lbs6 ft2NoNo1Pro & Farm1,200,000$0$Link
Viktor TikhonovC/LW/RW2812.05.1988 4:06:53No189 Lbs6 ft2NoNo1Pro & Farm1,100,000$0$Link
Zack MitchellRW2307.01.1993Yes185 Lbs6 ft0NoNo9Farm Only100,000$0$100,000$100,000$100,000$100,000$100,000$100,000$100,000$100,000$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2723.78192 Lbs6 ft15.1481481481481633,333$



5 vs 5 Forward
Line #CenterLeft WingRight WingTime %PHYDFOF
1Viktor TikhonovRobby FabbriSergei Plotnikov40005
2Tanner RichardMiikka SalomakiTom Kuhnhackl30122
3Tanner RichardJordan WealMichael McCarron20131
4Daniel CatenacciStefan NoesenZack Mitchell10230
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Klas DahlbeckChris Wideman43122
2Scott HarringtonJakub Nakladal34122
3Dylan BlujusOliver Kylington23230
4Klas DahlbeckChris Wideman0122
Power Play Forward
Line #CenterLeft WingRight WingTime %PHYDFOF
1Viktor TikhonovSergei PlotnikovRobby Fabbri60005
2Tanner RichardMiikka SalomakiTom Kuhnhackl40113
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Klas DahlbeckChris Wideman60014
2Scott HarringtonJakub Nakladal40032
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Robby FabbriTom Kuhnhackl60122
2Daniel CatenacciMiikka Salomaki40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Klas DahlbeckChris Wideman60122
2Scott HarringtonJakub Nakladal40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Robby Fabbri60122Klas DahlbeckChris Wideman60122
2Michael McCarron40122Scott HarringtonJakub Nakladal40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Robby FabbriTom Kuhnhackl60113
2Viktor TikhonovMiikka Salomaki40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Klas DahlbeckChris Wideman60122
2Scott HarringtonDylan Blujus40122
Last Minutes Offensive
CenterLeft WingRight WingDefenseDefense
Viktor TikhonovRobby FabbriTom KuhnhacklKlas DahlbeckChris Wideman
Last Minutes Defensive
CenterLeft WingRight WingDefenseDefense
Robby FabbriMiikka SalomakiTom KuhnhacklKlas DahlbeckChris Wideman
Extra Forwards
Normal PowerPlayPenalty Kill
Tanner Richard, Michael McCarron, Jordan WealTanner Richard, Michael McCarronJordan Weal
Extra Defensemen
Normal PowerPlayPenalty Kill
Jakub Nakladal, Oliver Kylington, Scott HarringtonJakub NakladalOliver Kylington, Scott Harrington
Penalty Shots
Robby Fabbri, Miikka Salomaki, Tom Kuhnhackl, Viktor Tikhonov, Sergei Plotnikov
Goalie
#1 : Richard Bachman, #2 : Jason Kasdorf


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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
# VS Team 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 GF% SH% SV% PDO PDOBRK
1SenatorsCrunch1010000027-500.00023500121380385231460292028192150.00%4175.00%0275846.55%357844.87%387749.35%825192356531
2SenatorsBears1010000012-100.000123001213802252314604292924100.00%20100.00%0275846.55%357844.87%387749.35%825192356531
3SenatorsMarlies1100000061521.00061117001213803452314603271627000.00%3166.67%0275846.55%357844.87%387749.35%825192356531
4SenatorsHeat110000002412321.000243458001213803552314602913582611100.00%40100.00%0275846.55%357844.87%387749.35%825192356531
Vs Division1100000061521.00061117001213803452314603271627000.00%3166.67%0275846.55%357844.87%387749.35%825192356531
Vs Conference31200000910-120.33391625001213809452314601033673703133.33%9277.78%0275846.55%357844.87%387749.35%825192356531
Since Last GM Reset4220000033112240.50033508300121380129523146013249131964250.00%13284.62%0275846.55%357844.87%387749.35%825192356531
Total4220000033112240.50033508300121380129523146013249131964250.00%13284.62%0275846.55%357844.87%387749.35%825192356531

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
44L2335083129132491319600
All Games
GPWLOTWOTL SOWSOLGFGA
42200003311
Home Games
GPWLOTWOTL SOWSOLGFGA
2200000302
Visitor Games
GPWLOTWOTL SOWSOLGFGA
202000039
Last 10 Games
WLOTWOTL SOWSOL
220000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
4250.00%13284.62%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
5231460121380
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
275846.55%357844.87%387749.35%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
825192356531


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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
DateMatchup Result Detail
Trade Deadline --- Trades can’t be done after this day is simulated!
Fri, Nov 22Senators@SenatorsHeat1,Senators24RECAP
Sat, Nov 23Senators@SenatorsMarlies1,Senators6RECAP
Tue, Nov 26Senators@SenatorsSenators1,Bears2RECAP
Wed, Nov 27Senators@SenatorsSenators2,Crunch7RECAP



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance00
Attendance PCT0.00%0.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
0 0 - 0.00% 0$0$3000100

Expenses
Players Total SalariesPlayers Total Average SalariesCoaches Salaries
1,710,000$ 680,000$ 0$
Year To Date ExpensesSalary Cap Per DaysSalary Cap To Date
0$ 0$ 0$

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 0$ 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