Senators

GP: 82 | W: 30 | L: 48 | OTL: 4 | P: 64
GF: 267 | GA: 322 | PP%: 18.15% | PK%: 75.15%
GM : Olivier Paquin | Morale : 50 | Team Overall : 44
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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
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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
1Ross Johnston (R)X100.00655647608550375335485860483734050540
2Jiri SekacXX100.00543583676753444635474560463633050520
3Anton Blidh (R)XX100.00493586646955354435414657483734050500
4Luke AdamXX100.00453574667244303939354260424540050480
5Kevin Rooney (R)X100.00533581686457353543353559483734050480
6Alexandre GrenierX100.00543590657151333335333365473734050470
7Carl KlingbergXX100.00443592667238294035314753454138050470
8Alex Broadhurst (R)X100.00473573685451353535353554483532050460
9Cam Morrison (R)X100.00454545457445454545454545453230050460
10Maxwell ReinhartXX100.00443592666938293135313161453734050450
11Christian DjoosX100.00493590725051484535474367483532050540
12Matt DonovanX100.00513584616750314135453567453937050530
13Jaycob Megna (R)X100.00513590607559363535383268483734050530
14Brady AustinX100.00513576597949333035293173473532050520
15Victor Antipin (R)X100.00483585695252434135493264483532050520
16Roland McKeown (R)X100.00514356666350353435363268483532050510
17Evan McEnenyX100.00473594676748333035293168473532050510
18Vojtech MozikX100.00493579596643312935283069463532050490
Scratches
1Dillon Dube (R)X100.00454545456145454545454545453230050450
2Bogdan YakimovX100.00423592598443293149313162453532050450
3Graham Knott (R)X100.00434545456842424345434345443230050450
4Griffen MolinoXX100.00423594735048333335333351473532050450
5Jansen Harkins (R)X100.00434545456742424345434345443230050450
6Nikita Jevpalovs (R)XX100.00434545457342424345434345443230050450
7Paul Bittner (R)X100.00434545457242424345434345443230050450
8Alex Formenton (R)X100.00463595624945353535353554483532050440
9Jayce Hawryluk (R)XX100.00414545456039394145414145433230050430
10Jeremy Bracco (R)X100.00414343436040404143414143423230050430
11James Lodge (R)X100.00394343434837373943393943413230050410
12Fredrik Olofsson (R)X100.00384040407137373840383840393230050410
13Max Gortz (R)X100.00353737376835353537353537363230050390
14Yaroslav Kosov (R)XX100.00333737377733333337333337353230050380
15Scott GlennieX100.00549030337129353135313133453532050370
16Spencer Watson (R)X100.00333737374933333337333337353230050370
17Mike RibeiroX100.00202020202020202020202020202020050240
18Alexander UrbomX100.00358337497229473135313153454138050450
19Mathew BodieX100.00414545455339394145414145433230050430
20Jani Hakanpaa (R)X100.00364040407035353640363640383230050410
21Jan Kostalek (R)X100.00364040405635353640363640383230050400
22Robin Norell (R)X100.00364040406035353640363640383230050400
23Nicholas Boka (R)X100.00373737376437373737373737373230050400
TEAM AVERAGE100.0044416153644336373837375143343205045
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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 CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Ken Appleby (R)100.0050454580474545454565453532050490
2Niklas Svedberg100.0047457163454444434356553734050470
Scratches
1Filip Gustavsson (R)100.0045454568454545454545453230050460
2Kasimir Kaskisuo (R)100.0045454572454545454545453230050460
3Roman Will100.0043454371424141414159583532050450
4Mason McDonald (R)100.0043454366424141414141403230050430
5Stephen Michalek (R)100.0036373673363535353535353230050400
6Niklas Backstrom100.0020202020202020202020202020050220
7Scott Clemmensen (R)100.0020202020202020202020202020050220
TEAM AVERAGE100.003939415938373737374340312905040
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary


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 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
1Jiri SekacSenators (Ott)LW/RW782940697200871042284416112.72%24152719.58315184124700021633144.38%16000010.9015000451
2Ross JohnstonSenators (Ott)LW78372966-212630268832967619712.50%16152019.49581360228022102114247.66%25600010.8715222663
3Matt DonovanSenators (Ott)D78154156-1062011675115256313.04%94159820.5071219662240111204210.00%000000.7000000233
4Tyler EnnisOttawaLW/RW382429532316037961904911612.63%1484522.2437102511511271225245.45%31900011.2513000374
5Nikolay GoldobinOttawaLW/RW46242953212015611606010915.00%1490919.778715431600002711247.44%7800001.1703000434
6Victor AntipinSenators (Ott)D78113849-2400609777266214.29%64156820.116713462230110210000.00%000000.6211000111
7Anton BlidhSenators (Ott)LW/RW78192948-910016621744211510.92%6134817.294610362431011452238.83%10300000.7104000224
8Jaycob MegnaSenators (Ott)D7893544-166001077711428577.89%77171321.9741216552440000220100.00%000000.5100000023
9Brady AustinSenators (Ott)D7882836-17600936269285311.59%87142018.22358321780000146000.00%200000.5100000111
10Kevin RooneySenators (Ott)C7892736-62956314211332747.96%8128416.4727928230000072049.57%150100000.5601100302
11Luke AdamSenators (Ott)C/LW78102434-22410459312330618.13%13115814.85268161201014681147.64%118600000.5900200012
12Alexandre GrenierSenators (Ott)RW82141933-232556882137318110.22%25125615.32145139400011001044.90%9800000.5300001111
13Patrick SharpOttawaLW/RW162010301860263795166221.05%934621.6751617480003632164.46%16600011.7303000531
14Carl KlingbergSenators (Ott)LW/RW8220929-13401947130339515.38%1186810.5920210360001371145.07%7100010.6700000111
15Brett HowdenOttawaC4892029-25351158084265010.71%483617.43291118160000051052.62%104900100.6923100112
16Roland McKeownSenators (Ott)D7362228-10355827351183811.76%90112515.42112966000189100.00%000000.5001001111
17Brendan LemieuxOttawaLW6151924-14755163355625338.93%3691615.0301118000030131.58%1900000.5200100010
18Christian DjoosSenators (Ott)D178122054032154091520.00%2235020.594152449000054200.00%000001.1400000301
19Max JonesOttawaLW5751520-9375101399021735.56%476113.350114230000910061.70%4700000.5303010002
20Alex BroadhurstSenators (Ott)C33628-96028514982212.24%444813.601011100001150044.47%43400000.3600000000
21Matt TennysonOttawaD5156-2407593611.11%411322.71011421011013000.00%000001.0600000001
22Evan McEnenySenators (Ott)D24235-6801315195810.53%2332413.5100023000022100.00%000000.3100000001
23Vojtech MozikSenators (Ott)D24044-580101310430.00%62048.530000500003000.00%000000.3900000000
24Cam MorrisonSenators (Ott)LW23011-43353512252160.00%029312.7500023000050052.94%1700000.0700001000
25Vladislav KamenevOttawaC/LW20011-6006129760.00%01819.10011140000290050.40%12500000.1100000000
26Alexander UrbomSenators (Ott)D2000300011020.00%03316.750001400004000.00%000000.0000000000
27Maxwell ReinhartSenators (Ott)C/LW3000-100110000.00%0227.4400003000020046.15%1300000.0000000000
Team Total or Average1356291491782-9174775161314702464648157811.81%6552297916.95631121755552760369342013301448.99%564400150.68632735383939
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
1Niklas SvedbergSenators (Ott)47182020.8584.0224472116411580300.786144424010
2Ken ApplebySenators (Ott)2471520.8873.44136162786930110.80010240110
3Eric ComrieOttawa30200.8723.6499006470000.0000013000
Team Total or Average74253740.8693.8139088324818980410.792246837120


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
Alex BroadhurstSenators (Ott)C241993-03-07Yes178 Lbs6 ft0NoNoNo2RFAPro & Farm660,000$66,000$0$NoLink
Alex FormentonSenators (Ott)LW181999-09-13Yes165 Lbs6 ft2NoNoNo4ELCPro & Farm742,500$74,250$0$NoLink
Alexander UrbomSenators (Ott)D261990-12-20No215 Lbs6 ft4NoNoNo3RFAPro & Farm750,000$75,000$0$NoLink
Alexandre GrenierSenators (Ott)RW261991-09-05No200 Lbs6 ft5NoNoNo2RFAPro & Farm585,000$58,500$0$NoLink
Anton BlidhSenators (Ott)LW/RW221995-03-14Yes201 Lbs6 ft0NoNoNo3RFAPro & Farm792,000$79,200$0$NoLink
Bogdan YakimovSenators (Ott)C231994-10-04No232 Lbs6 ft5NoNoNo1RFAPro & Farm792,000$79,200$0$NoLink
Brady AustinSenators (Ott)D241993-06-16No230 Lbs6 ft4NoNoNo5RFAPro & Farm850,000$85,000$0$NoLink
Cam MorrisonSenators (Ott)LW191998-08-27Yes212 Lbs6 ft3NoNoNo4ELCPro & Farm825,000$82,500$0$NoLink
Carl KlingbergSenators (Ott)LW/RW261991-01-28No205 Lbs6 ft3NoNoNo3RFAPro & Farm1,282,300$128,230$0$NoLink
Christian DjoosSenators (Ott)D231994-08-06No169 Lbs6 ft0NoNoNo3RFAPro & Farm525,000$525,000$0$NoLink
Dillon DubeSenators (Ott)C191998-07-20Yes190 Lbs5 ft11NoNoNo4ELCPro & Farm742,500$74,250$0$NoLink
Evan McEnenySenators (Ott)D231994-05-22No203 Lbs6 ft2NoNoNo5RFAPro & Farm1,154,888$115,489$0$NoLink
Filip GustavssonSenators (Ott)G191998-06-07Yes185 Lbs6 ft2NoNoNo4ELCPro & Farm742,500$74,250$0$NoLink
Fredrik OlofssonSenators (Ott)LW211996-05-27Yes204 Lbs6 ft2NoNoNo3ELCPro & Farm650,000$65,000$0$NoLink
Graham KnottSenators (Ott)LW201997-01-13Yes195 Lbs6 ft4NoNoNo3ELCPro & Farm825,000$82,500$0$NoLink
Griffen MolinoSenators (Ott)C/LW231994-01-21No171 Lbs5 ft11NoNoNo5RFAPro & Farm900,000$90,000$0$NoLink
James LodgeSenators (Ott)C221995-05-05Yes166 Lbs6 ft0NoNoNo2RFAPro & Farm700,000$70,000$0$NoLink
Jan KostalekSenators (Ott)D221995-02-17Yes181 Lbs6 ft0NoNoNo2RFAPro & Farm660,000$66,000$0$NoLink
Jani HakanpaaSenators (Ott)D251992-05-31Yes211 Lbs6 ft4NoNoNo2RFAPro & Farm650,000$65,000$0$NoLink
Jansen HarkinsSenators (Ott)C201997-05-23Yes195 Lbs6 ft2NoNoNo3ELCPro & Farm825,000$82,500$0$NoLink
Jayce HawrylukSenators (Ott)C/RW211996-01-01Yes190 Lbs5 ft10NoNoNo2ELCPro & Farm925,000$92,500$0$NoLink
Jaycob MegnaSenators (Ott)D241992-12-10Yes219 Lbs6 ft6NoNoNo5RFAPro & Farm969,006$96,901$0$NoLink
Jeremy BraccoSenators (Ott)RW201997-03-17Yes190 Lbs5 ft10NoNoNo3ELCPro & Farm700,000$70,000$0$NoLink
Jiri SekacSenators (Ott)LW/RW251992-06-10No195 Lbs6 ft2NoNoNo1RFAPro & Farm925,000$92,500$0$NoLink
Kasimir KaskisuoSenators (Ott)G241993-10-02Yes194 Lbs6 ft3NoNoNo4RFAPro & Farm925,000$92,500$0$NoLink
Ken ApplebySenators (Ott)G221995-04-10Yes210 Lbs6 ft4NoNoNo4RFAPro & Farm635,000$63,500$0$NoLink
Kevin RooneySenators (Ott)C241993-05-21Yes190 Lbs6 ft2NoNoNo5RFAPro & Farm850,000$85,000$0$NoLink
Luke AdamSenators (Ott)C/LW271990-06-18No206 Lbs6 ft2NoNoNo3RFAPro & Farm500,000$50,000$0$NoLink
Mason McDonaldSenators (Ott)G211996-04-23Yes178 Lbs6 ft4NoNoNo2ELCPro & Farm792,000$79,200$0$NoLink
Mathew BodieSenators (Ott)D271990-03-07No175 Lbs6 ft0NoNoNo2RFAPro & Farm825,000$82,500$0$NoLink
Matt DonovanSenators (Ott)D271990-05-09No205 Lbs6 ft1NoNoNo1RFAPro & Farm600,000$60,000$0$NoLink
Max GortzSenators (Ott)RW241993-01-28Yes196 Lbs6 ft2NoNoNo3RFAPro & Farm525,000$52,500$0$NoLink
Maxwell ReinhartSenators (Ott)C/LW251992-02-04No190 Lbs6 ft1NoNoNo2RFAPro & Farm600,000$60,000$0$NoLink
Mike Ribeiro (1 Way Contract)Senators (Ott)LW371980-02-10No179 Lbs6 ft0NoNoNo1UFAPro & Farm2,500,000$2,500,000$0$NoLink
Nicholas BokaSenators (Ott)D201997-09-08Yes197 Lbs6 ft1NoNoNo4ELCPro & Farm525,000$52,500$0$NoLink
Nikita JevpalovsSenators (Ott)LW/RW231994-09-09Yes210 Lbs6 ft1NoNoNo3RFAPro & Farm825,000$82,500$0$NoLink
Niklas BackstromSenators (Ott)G391978-02-13No192 Lbs6 ft2NoNoNo1UFAPro & Farm1,000,000$100,000$0$NoLink
Niklas SvedbergSenators (Ott)G281989-09-04No176 Lbs6 ft0YesNoNo4UFAPro & Farm870,000$87,000$0$NoLink
Paul BittnerSenators (Ott)LW201996-11-04Yes205 Lbs6 ft4NoNoNo3ELCPro & Farm825,000$82,500$0$NoLink
Robin NorellSenators (Ott)D221995-02-18Yes189 Lbs5 ft11NoNoNo2RFAPro & Farm650,000$65,000$0$NoLink
Roland McKeownSenators (Ott)D211996-01-20Yes195 Lbs6 ft1NoNoNo2ELCPro & Farm718,000$71,800$0$NoLink
Roman WillSenators (Ott)G251992-05-22No195 Lbs6 ft1NoNoNo3RFAPro & Farm750,000$75,000$0$NoLink
Ross JohnstonSenators (Ott)LW231994-02-18Yes235 Lbs6 ft5NoNoNo5RFAPro & Farm850,000$85,000$0$NoLink
Scott Clemmensen (1 Way Contract)Senators (Ott)G411976-07-23 12:42:12Yes200 Lbs6 ft2YesNoNo1UFAPro & Farm985,000$985,000$0$NoLink
Scott GlennieSenators (Ott)RW261991-02-22No204 Lbs6 ft1NoNoNo3RFAPro & Farm450,000$45,000$0$NoLink
Spencer WatsonSenators (Ott)RW221995-04-25Yes170 Lbs5 ft9NoNoNo2RFAPro & Farm525,000$52,500$0$NoLink
Stephen MichalekSenators (Ott)G241993-08-06Yes196 Lbs6 ft2NoNoNo3RFAPro & Farm525,000$52,500$0$NoLink
Victor AntipinSenators (Ott)D241992-12-06Yes175 Lbs5 ft11NoNoNo4RFAPro & Farm925,000$92,500$0$NoLink
Vojtech MozikSenators (Ott)D241992-12-26No200 Lbs6 ft3NoNoNo2RFAPro & Farm667,000$66,700$0$NoLink
Yaroslav KosovSenators (Ott)LW/RW241993-07-05Yes220 Lbs6 ft3NoNoNo2RFAPro & Farm525,000$52,500$0$NoLink
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
5023.98196 Lbs6 ft22.90790,794$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Ross JohnstonLuke AdamJiri Sekac40122
2Anton BlidhKevin RooneyAlexandre Grenier30122
3Carl KlingbergAlex BroadhurstCam Morrison20122
4Cam MorrisonRoss Johnston10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Christian DjoosJaycob Megna40122
2Matt DonovanVictor Antipin30122
3Brady AustinEvan McEneny20122
4Roland McKeownVojtech Mozik10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Ross JohnstonLuke AdamJiri Sekac60122
2Anton BlidhKevin RooneyAlexandre Grenier40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Christian DjoosJaycob Megna60122
2Matt DonovanVictor Antipin40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Ross JohnstonJiri Sekac60122
2Anton BlidhLuke Adam40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Christian DjoosJaycob Megna60122
2Matt DonovanVictor Antipin40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Ross Johnston60122Christian DjoosJaycob Megna60122
2Jiri Sekac40122Matt DonovanVictor Antipin40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Ross JohnstonJiri Sekac60122
2Anton BlidhLuke Adam40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Christian DjoosJaycob Megna60122
2Matt DonovanVictor Antipin40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Ross JohnstonLuke AdamJiri SekacChristian DjoosJaycob Megna
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Ross JohnstonLuke AdamJiri SekacChristian DjoosJaycob Megna
Extra Forwards
Normal PowerPlayPenalty Kill
Carl Klingberg, Alex Broadhurst, Carl Klingberg, Alex Broadhurst
Extra Defensemen
Normal PowerPlayPenalty Kill
Brady Austin, Evan McEneny, Roland McKeownBrady AustinEvan McEneny, Roland McKeown
Penalty Shots
Ross Johnston, Jiri Sekac, Anton Blidh, Luke Adam, Kevin Rooney
Goalie
#1 : Ken Appleby, #2 : Niklas Svedberg


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
1Admirals20200000611-51010000034-11010000037-400.00061117001128663115880084567043811627417114.29%11281.82%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
2Baby Hawks2020000048-41010000035-21010000013-200.000461000112866311508008456704359161235700.00%6350.00%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
3Bears30200100811-32010010068-21010000023-110.167814220011286631172800845670431063324669222.22%12191.67%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
4Bruins41201000910-12110000034-12010100066040.5009162500112866311115800845670438923187315213.33%9188.89%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
5Cabaret Lady Mary Ann412001001318-521100000910-12010010048-430.3751324370011286631114080084567043152424810317423.53%24675.00%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
6Caroline32100000121202110000078-11100000054140.66712223400112866311131800845670437924208117211.76%8275.00%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
7Chiefs2020000036-31010000023-11010000013-200.0003690011286631131800845670435091643300.00%8362.50%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
8Chill21100000910-11010000025-31100000075220.50091625001128663117580084567043521714396350.00%7271.43%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
9Comets2020000057-21010000034-11010000023-100.0005712001128663115280084567043571314334125.00%7185.71%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
10Cougars404000001424-1020200000912-320200000512-700.000142539001128663111318008456704313543499423417.39%221150.00%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
11Crunch421010001394220000007252010100067-160.750132336011128663111038008456704310720416817211.76%18477.78%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
12Heat2010000148-41000000134-11010000014-310.25047110011286631152800845670435513445800.00%2150.00%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
13Jayhawks2010001079-2100000105411010000025-320.50071118001128663116280084567043461714437114.29%7185.71%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
14Las Vegas2110000078-1110000004311010000035-220.50071421001128663116380084567043761524405240.00%11463.64%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
15Manchots3110001012111210000108621010000045-140.667121931001128663117280084567043632930661000.00%13469.23%11156238848.41%1141242946.97%675145646.36%1950129718826351122567
16Marlies413000001318-520200000710-32110000068-220.25013233610112866311918008456704316451408219526.32%20670.00%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
17Minnesota211000009541010000034-11100000061520.500917260011286631160800845670434113202910440.00%10370.00%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
18Monarchs21100000963110000006241010000034-120.50091524001128663116880084567043421023519333.33%9277.78%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
19Monsters312000001012-22110000078-11010000034-120.3331019290011286631166800845670439524334219210.53%13561.54%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
20Monsters20200000613-71010000017-61010000056-100.00061117001128663114080084567043611422421119.09%9188.89%11156238848.41%1141242946.97%675145646.36%1950129718826351122567
21Oceanics20200000310-71010000023-11010000017-600.00035800112866311358008456704365271242600.00%6266.67%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
22Oil Kings21100000752110000005231010000023-120.50071421001128663115380084567043591740386116.67%6183.33%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
23Phantoms30200100712-51010000045-12010010037-410.16771118001128663117180084567043772620639111.11%9188.89%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
24Rocket431000001073211000006602200000041360.75010172701112866311112800845670437721305827414.81%14285.71%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
25Sharks2100001013103100000106511100000075241.000132336001128663116980084567043922027485240.00%11372.73%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
26Sound Tigers32100000990110000003122110000068-240.667918270011286631175800845670436923226311218.18%11190.91%11156238848.41%1141242946.97%675145646.36%1950129718826351122567
27Spiders312000001316-31010000057-22110000089-120.3331325380011286631185800845670439929506515320.00%14192.86%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
28Stars20200000411-71010000036-31010000015-400.00047110011286631165800845670436116204211327.27%10550.00%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
29Thunder412000101212020100010910-12110000032140.500121931011128663111058008456704311541366811436.36%18194.44%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
Total82244802341267322-5541132200141149164-1541112602200118158-40640.39026747674313112866311232980084567043242867777716723366118.15%3348375.15%31156238848.41%1141242946.97%675145646.36%1950129718826351122567
31Wolf Pack3210000016142110000008622110000088040.667163147001128663111278008456704310415276912216.67%9366.67%01156238848.41%1141242946.97%675145646.36%1950129718826351122567
_Since Last GM Reset82244802341267322-5541132200141149164-1541112602200118158-40640.39026747674313112866311232980084567043242867777716723366118.15%3348375.15%31156238848.41%1141242946.97%675145646.36%1950129718826351122567
_Vs Conference43132401230149172-2321611001307984-522713011007088-18360.4191492654141111286631111848008456704313133844038781633219.63%1723579.65%21156238848.41%1141242946.97%675145646.36%1950129718826351122567

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
8264W126747674323292428677777167213
All Games
GPWLOTWOTL SOWSOLGFGA
8224482341267322
Home Games
GPWLOTWOTL SOWSOLGFGA
4113220141149164
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4111262200118158
Last 10 Games
WLOTWOTL SOWSOL
460000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
3366118.15%3348375.15%3
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
80084567043112866311
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1156238848.41%1141242946.97%675145646.36%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
1950129718826351122567


Last Played Games
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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
DayGame Visitor Team Score Home Team Score ST OT SO RI Link
2 - 2018-10-049Baby Hawks5Senators3LBoxScore
4 - 2018-10-0620Senators2Marlies5LBoxScore
6 - 2018-10-0832Senators5Bruins4WXBoxScore
8 - 2018-10-1042Phantoms5Senators4LBoxScore
11 - 2018-10-1359Monarchs2Senators6WBoxScore
13 - 2018-10-1576Stars6Senators3LBoxScore
18 - 2018-10-20107Rocket3Senators2LBoxScore
21 - 2018-10-23125Bruins1Senators3WBoxScore
24 - 2018-10-26147Senators5Monsters6LBoxScore
26 - 2018-10-28163Senators3Las Vegas5LBoxScore
28 - 2018-10-30175Senators2Jayhawks5LBoxScore
30 - 2018-11-01183Crunch2Senators3WBoxScore
32 - 2018-11-03195Senators4Crunch3WXBoxScore
33 - 2018-11-04207Thunder5Senators3LBoxScore
35 - 2018-11-06218Spiders7Senators5LBoxScore
37 - 2018-11-08231Las Vegas3Senators4WBoxScore
39 - 2018-11-10247Senators1Thunder2LBoxScore
40 - 2018-11-11254Senators1Cabaret Lady Mary Ann4LBoxScore
44 - 2018-11-15281Cougars7Senators5LBoxScore
46 - 2018-11-17296Manchots3Senators4WBoxScore
48 - 2018-11-19312Cabaret Lady Mary Ann4Senators5WBoxScore
50 - 2018-11-21327Senators6Minnesota1WBoxScore
52 - 2018-11-23345Senators1Stars5LBoxScore
55 - 2018-11-26365Senators4Wolf Pack5LBoxScore
56 - 2018-11-27368Senators2Phantoms3LXBoxScore
58 - 2018-11-29384Wolf Pack6Senators8WBoxScore
60 - 2018-12-01395Sharks5Senators6WXXBoxScore
63 - 2018-12-04421Senators2Rocket0WBoxScore
65 - 2018-12-06433Rocket3Senators4WBoxScore
67 - 2018-12-08447Manchots3Senators4WXXBoxScore
68 - 2018-12-09456Bruins3Senators0LBoxScore
70 - 2018-12-11471Senators7Chill5WBoxScore
73 - 2018-12-14490Senators3Cougars5LBoxScore
74 - 2018-12-15496Senators2Rocket1WBoxScore
76 - 2018-12-17515Chill5Senators2LBoxScore
80 - 2018-12-21542Senators5Spiders4WBoxScore
81 - 2018-12-22554Bears4Senators3LBoxScore
87 - 2018-12-28581Senators4Sound Tigers3WBoxScore
88 - 2018-12-29589Bears4Senators3LXBoxScore
90 - 2018-12-31605Senators3Monsters4LBoxScore
92 - 2019-01-02615Comets4Senators3LBoxScore
95 - 2019-01-05637Minnesota4Senators3LBoxScore
96 - 2019-01-06645Caroline5Senators3LBoxScore
99 - 2019-01-09670Senators3Admirals7LBoxScore
100 - 2019-01-10682Senators3Monarchs4LBoxScore
102 - 2019-01-12696Senators7Sharks5WBoxScore
106 - 2019-01-16721Monsters7Senators1LBoxScore
108 - 2019-01-18736Senators5Caroline4WBoxScore
109 - 2019-01-19742Senators1Chiefs3LBoxScore
112 - 2019-01-22761Jayhawks4Senators5WXXBoxScore
122 - 2019-02-01784Senators4Manchots5LBoxScore
123 - 2019-02-02793Cougars5Senators4LBoxScore
127 - 2019-02-06821Senators4Marlies3WBoxScore
128 - 2019-02-07829Admirals4Senators3LBoxScore
130 - 2019-02-09844Oceanics3Senators2LBoxScore
133 - 2019-02-12867Caroline3Senators4WBoxScore
135 - 2019-02-14879Senators2Cougars7LBoxScore
137 - 2019-02-16896Senators1Oceanics7LBoxScore
139 - 2019-02-18912Senators1Baby Hawks3LBoxScore
142 - 2019-02-21931Senators3Spiders5LBoxScore
143 - 2019-02-22940Monsters5Senators2LBoxScore
145 - 2019-02-24960Heat4Senators3LXXBoxScore
147 - 2019-02-26971Senators2Bears3LBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
149 - 2019-02-28987Oil Kings2Senators5WBoxScore
151 - 2019-03-021004Senators2Thunder0WBoxScore
152 - 2019-03-031013Senators3Cabaret Lady Mary Ann4LXBoxScore
154 - 2019-03-051021Senators2Sound Tigers5LBoxScore
156 - 2019-03-071035Sound Tigers1Senators3WBoxScore
158 - 2019-03-091051Senators1Bruins2LBoxScore
160 - 2019-03-111067Senators1Phantoms4LBoxScore
163 - 2019-03-141086Chiefs3Senators2LBoxScore
165 - 2019-03-161105Marlies5Senators4LBoxScore
169 - 2019-03-201134Senators2Comets3LBoxScore
170 - 2019-03-211144Senators1Heat4LBoxScore
172 - 2019-03-231153Senators2Oil Kings3LBoxScore
175 - 2019-03-261181Crunch0Senators4WBoxScore
177 - 2019-03-281192Cabaret Lady Mary Ann6Senators4LBoxScore
179 - 2019-03-301206Marlies5Senators3LBoxScore
181 - 2019-04-011224Thunder5Senators6WXXBoxScore
183 - 2019-04-031239Senators4Wolf Pack3WBoxScore
184 - 2019-04-041242Senators2Crunch4LBoxScore
186 - 2019-04-061260Monsters3Senators5WBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price5020
Attendance61,80430,711
Attendance PCT75.37%74.90%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
0 2256 - 75.22% 90,352$3,704,420$3000100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
3,847,942$ 4,077,970$ 4,026,470$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
21,807$ 3,847,942$ 50 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 21,807$ 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
201882244802341267322-5541132200141149164-1541112602200118158-406426747674313112866311232980084567043242867777716723366118.15%3348375.15%31156238848.41%1141242946.97%675145646.36%1950129718826351122567
Total Regular Season82244802341267322-5541132200141149164-1541112602200118158-406426747674313112866311232980084567043242867777716723366118.15%3348375.15%31156238848.41%1141242946.97%675145646.36%1950129718826351122567