´╗┐

Senators

GP: 9 | W: 4 | L: 5 | OTL: 0 | P: 8
GF: 17 | GA: 26 | PP%: 15.38% | PK%: 86.05%
GM : Rob Rosanio | Morale : 50 | Team Overall : 58
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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
1Buddy RobinsonX100.008588786688818664505965706244446850640
2Ales HemskyX100.005240998073393968506072724281845450630
3Joakim NordstromXXX100.007944977469579658435756742566676450630
4Martin FrkX100.007644927171568576256670532552526950630
5Chris TerryXX100.007168797168565371506871646744446850620
6Nikita ScherbakXX100.006942907666657766255868582546466750610
7Emil PetterssonX100.007367866367747762786257635444446350600
8Adam ErneXX100.008175857278576260565464592548486450590
9Kyle CriscuoloX100.006660816260798462785960605744446350590
10Mikhail Vorobyev (R)X100.008176916576666859745756665344446250590
11Daniel PribylX100.008074956374585957715654655144446050570
12Yakov Trenin (R)X100.007976876376504955695551644844445750550
13Ryan MurphyX100.005941788067776970255250672561616050640
14Joakim RyanX100.006541957767717961255248692551516150630
15Michael Kapla (R)X100.007873896573657048254041623944445350570
16Ludwig BystromX100.007064836564656853255041593944445450560
17Robin Norell (R)X100.007470826270727944253439593744445150560
18Macoy Erkamps (R)X100.007671866771677444253339603744445150560
Scratches
1Hampus Gustafsson (R)XX100.008377976277555751644750654844445750550
2Filip Sandberg (R)XX100.007164886264586054684756605344445750540
3Adam Musil (R)X100.007976876676505149614746634444445450530
4Quentin Shore (R)XX100.007769946769555845563846614444445350520
5Vincent Dunn (R)XX100.006670555770555750635244574244445150520
6Dysin MayoX100.007472806572535547253741603944445150540
7Lukas Bengtsson (R)X100.007163916463505052255039603744445350540
TEAM AVERAGE100.00736487677161665747525363424848595058
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3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
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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
1Linus Ullmark100.00678099856672597165643046466750660
2Chris Driedger100.00485366804648505448483044444950520
Scratches
TEAM AVERAGE100.0058678383566055635756304545585059
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Luke Richardson62416665454654CAN491800,000$


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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 Team NamePOS GP 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
1Chris TerrySenators (OTT)LW/RW93470801282131414.29%015116.86134627000011063.64%1100000.9200000200
2Ryan MurphySenators (OTT)D9235-24021790622.22%921123.50213832011036100.00%000000.4700000010
3Nikita ScherbakSenators (OTT)LW/RW9235-120591851111.11%114716.34112333000000140.00%1000000.6800000001
4Ales HemskySenators (OTT)RW9044-200020157140.00%215016.76011327000000040.00%1500000.5300000000
5Adam ErneSenators (OTT)LW/RW9134-21001417158116.67%012313.75112330000050058.33%1200000.6500000000
6Joakim RyanSenators (OTT)D9134-20091060216.67%1319021.18123432000011100.00%000000.4200000001
7Martin FrkSenators (OTT)RW92130003111631512.50%111612.9400000000000110.00%1000000.5200000101
8Mikhail VorobyevSenators (OTT)C9123050201010132107.69%313815.430004240000100153.97%12600000.4300022010
9Buddy RobinsonSenators (OTT)RW9202-780128131815.38%412614.090000111012420071.43%700000.3200000000
10Joakim NordstromSenators (OTT)C/LW/RW9022-6401128430.00%112113.53000170111410052.11%7100000.3300000000
11Emil PetterssonSenators (OTT)C9022-24091710390.00%016117.98011334000040063.07%17600000.2500000000
12Hampus GustafssonSenators (OTT)C/LW9112-22031031733.33%09911.0900000000000053.41%8800000.4000000001
13Ludwig BystromSenators (OTT)D9011-2601116230.00%1218520.60011427000030000.00%000000.1100000000
14Robin NorellSenators (OTT)D9101-480216100100.00%715917.7800006000029000.00%000000.1300000010
15Daniel PribylSenators (OTT)C9101-2604680512.50%110711.90000000000191077.78%2700000.1900000010
16Michael KaplaSenators (OTT)D9000-21001656350.00%1117219.16000627000012000.00%000000.0000000000
17Kyle CriscuoloSenators (OTT)C9000-700475020.00%19710.87000000000220063.77%6900000.0000000000
18Macoy ErkampsSenators (OTT)D9000-31002655200.00%1215917.7300005000030000.00%000000.0000000001
Team Total or Average162172946-4613220181169178441259.55%78262316.19611174532912332994357.56%62200000.3500022345
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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
1Linus UllmarkSenators (OTT)94500.8782.8650300241960000.000090200
2Chris DriedgerSenators (OTT)10000.7783.243700290000.000009000
Team Total or Average104500.8732.8854100262050000.000099200


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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 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 ErneSenators (OTT)LW/RW241995-04-20No210 Lbs6 ft1NoNoNo1ELCPro & Farm850,000$0$0$NoLink
Adam MusilSenators (OTT)C251994-03-26Yes202 Lbs6 ft3NoNoNo3ELCPro & Farm650,000$0$0$NoLink
Ales HemskySenators (OTT)RW351983-08-12No185 Lbs6 ft0NoNoNo1UFAPro & Farm1,200,000$0$0$NoLink
Buddy RobinsonSenators (OTT)RW271991-09-30No232 Lbs6 ft6NoNoNo1RFAPro & Farm650,000$0$0$NoLink
Chris DriedgerSenators (OTT)G241994-05-18No205 Lbs6 ft4NoNoNo3ELCPro & Farm725,000$0$0$NoLink
Chris TerrySenators (OTT)LW/RW301989-04-07No195 Lbs5 ft10NoNoNo1UFAPro & Farm650,000$0$0$NoLink
Daniel PribylSenators (OTT)C261992-12-17No192 Lbs6 ft4NoNoNo1ELCPro & Farm950,000$0$0$NoLink
Dysin MayoSenators (OTT)D221996-08-16No195 Lbs6 ft2NoNoNo2ELCPro & Farm500,000$0$0$NoLink
Emil PetterssonSenators (OTT)C251994-01-14No164 Lbs6 ft2NoNoNo2ELCPro & Farm1,500,000$0$0$NoLink
Filip SandbergSenators (OTT)C/RW241994-07-23Yes181 Lbs5 ft9NoNoNo1ELCPro & Farm900,000$0$0$NoLink
Hampus GustafssonSenators (OTT)C/LW251993-10-26Yes205 Lbs6 ft4NoNoNo1ELCPro & Farm1,500,000$0$0$NoLink
Joakim NordstromSenators (OTT)C/LW/RW271992-02-25No189 Lbs6 ft1NoNoNo2RFAPro & Farm1,250,000$0$0$NoLink
Joakim RyanSenators (OTT)D251993-06-17No185 Lbs5 ft11NoNoNo1ELCPro & Farm500,000$0$0$NoLink
Kyle CriscuoloSenators (OTT)C271992-05-05No170 Lbs5 ft8NoNoNo1RFAPro & Farm655,000$0$0$NoLink
Linus UllmarkSenators (OTT)G251993-07-31No221 Lbs6 ft4NoNoNo1ELCPro & Farm500,000$0$0$NoLink
Ludwig BystromSenators (OTT)D241994-07-20No175 Lbs6 ft1NoNoNo4ELCPro & Farm650,000$0$0$NoLink
Lukas BengtssonSenators (OTT)D251994-04-13Yes172 Lbs5 ft11NoNoNo1ELCPro & Farm750,000$0$0$NoLink
Macoy ErkampsSenators (OTT)D241995-02-02Yes196 Lbs6 ft0NoNoNo1ELCPro & Farm650,000$0$0$NoLink
Martin FrkSenators (OTT)RW251993-10-04No194 Lbs6 ft1NoNoNo2ELCPro & Farm1,200,000$0$0$NoLink
Michael KaplaSenators (OTT)D241994-09-19Yes200 Lbs6 ft0NoNoNo1ELCPro & Farm900,000$0$0$NoLink
Mikhail VorobyevSenators (OTT)C221997-01-05Yes207 Lbs6 ft2NoNoNo3ELCPro & Farm925,000$0$0$NoLink
Nikita ScherbakSenators (OTT)LW/RW231995-12-29No190 Lbs6 ft2NoNoNo1ELCPro & Farm900,000$0$0$NoLink
Quentin ShoreSenators (OTT)C/RW241994-05-25Yes183 Lbs6 ft2NoNoNo2ELCPro & Farm500,000$0$0$NoLink
Robin NorellSenators (OTT)D241995-02-17Yes192 Lbs5 ft11NoNoNo2ELCPro & Farm600,000$0$0$NoLink
Ryan MurphySenators (OTT)D261993-03-30No185 Lbs5 ft11NoNoNo2ELCPro & Farm725,000$0$0$NoLink
Vincent DunnSenators (OTT)C/LW231995-09-14Yes190 Lbs6 ft0NoNoNo3ELCPro & Farm500,000$0$0$NoLink
Yakov TreninSenators (OTT)C221997-01-13Yes201 Lbs6 ft2NoNoNo3ELCPro & Farm800,000$0$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2725.07193 Lbs6 ft11.74817,778$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Chris TerryJoakim NordstromBuddy Robinson40122
2Nikita ScherbakEmil PetterssonMartin Frk30122
3Adam ErneKyle CriscuoloAles Hemsky20122
4Buddy RobinsonMikhail VorobyevMartin Frk10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan MurphyJoakim Ryan40122
2Michael KaplaRobin Norell30122
3Ludwig BystromMacoy Erkamps20122
4Ryan MurphyJoakim Ryan10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Chris TerryJoakim NordstromBuddy Robinson60122
2Nikita ScherbakEmil PetterssonMartin Frk40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan MurphyJoakim Ryan60122
2Michael KaplaRobin Norell40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Buddy RobinsonMartin Frk60122
2Ales HemskyJoakim Nordstrom40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan MurphyJoakim Ryan60122
2Michael KaplaRobin Norell40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Buddy Robinson60122Ryan MurphyJoakim Ryan60122
2Martin Frk40122Michael KaplaRobin Norell40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Buddy RobinsonMartin Frk60122
2Ales HemskyJoakim Nordstrom40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Ryan MurphyJoakim Ryan60122
2Michael KaplaRobin Norell40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Chris TerryJoakim NordstromBuddy RobinsonRyan MurphyJoakim Ryan
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Chris TerryJoakim NordstromBuddy RobinsonRyan MurphyJoakim Ryan
Extra Forwards
Normal PowerPlayPenalty Kill
Daniel Pribyl, Yakov Trenin, Adam ErneDaniel Pribyl, Yakov TreninAdam Erne
Extra Defensemen
Normal PowerPlayPenalty Kill
Ludwig Bystrom, Macoy Erkamps, Michael KaplaLudwig BystromMacoy Erkamps, Michael Kapla
Penalty Shots
Buddy Robinson, Martin Frk, Ales Hemsky, Joakim Nordstrom, Chris Terry
Goalie
#1 : Linus Ullmark, #2 : Chris Driedger


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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
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
1Phantoms541000001112-1220000006423210000058-380.8001119300074511126655561137547011618422.22%22386.36%112724452.05%15525261.51%7612660.32%2201532116110958
2Reign40400000614-82020000059-42020000015-400.00061016007451666655561682462652129.52%21385.71%012724452.05%15525261.51%7612660.32%2201532116110958
Total945000001726-9422000001113-252300000613-780.44417294600745117866555612057813218139615.38%43686.05%112724452.05%15525261.51%7612660.32%2201532116110958
_Since Last GM Reset945000001726-9422000001113-252300000613-780.44417294600745117866555612057813218139615.38%43686.05%112724452.05%15525261.51%7612660.32%2201532116110958
_Vs Conference945000001726-9422000001113-252300000613-780.44417294600745117866555612057813218139615.38%43686.05%112724452.05%15525261.51%7612660.32%2201532116110958
_Vs Division541000001112-1220000006423210000058-380.8001119300074511126655561137547011618422.22%22386.36%112724452.05%15525261.51%7612660.32%2201532116110958

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
98L41729461782057813218100
All Games
GPWLOTWOTL SOWSOLGFGA
94500001726
Home Games
GPWLOTWOTL SOWSOLGFGA
42200001113
Visitor Games
GPWLOTWOTL SOWSOLGFGA
5230000613
Last 10 Games
WLOTWOTL SOWSOL
351000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
39615.38%43686.05%1
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
66555617451
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
12724452.05%15525261.51%7612660.32%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
2201532116110958


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
1 - 2018-10-021Senators2Phantoms1WXBoxScore
3 - 2018-10-049Senators1Phantoms6LBoxScore
5 - 2018-10-0617Phantoms3Senators4WBoxScore
7 - 2018-10-0825Phantoms1Senators2WBoxScore
9 - 2018-10-1033Senators2Phantoms1WBoxScore
15 - 2018-10-1657Senators1Reign3LBoxScore
17 - 2018-10-1861Senators0Reign2LBoxScore
19 - 2018-10-2065Reign3Senators2LBoxScore
21 - 2018-10-2269Reign6Senators3LBoxScore



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
34 0 - 0.00% 0$0$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
0$ 2,208,000$ 2,202,167$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
0$ 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
2018945000001726-9422000001113-252300000613-7817294600745117866555612057813218139615.38%43686.05%112724452.05%15525261.51%7612660.32%2201532116110958
Total Playoff945000001726-9422000001113-252300000613-7817294600745117866555612057813218139615.38%43686.05%112724452.05%15525261.51%7612660.32%2201532116110958