Blues

GP: 66 | W: 37 | L: 24 | OTL: 5 | P: 79
GF: 168 | GA: 160 | PP%: 18.12% | PK%: 84.78%
GM : Patrick Resche | Morale : 75 | Team Overall : 69
Next Games #1007 vs Stars

Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Player Name C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SP
1Claude Giroux (C)XX97.005638878469879586839078718279906475750
2Jeff Carter (A)XX98.007341817287838971837477747084754675710
3Jake GuentzelXXX97.008138827768859576597580677868716375710
4Brandon SaadXX99.005836907579839372607377747273706375700
5Artem AnisimovXX100.005436887086819168767176736779725575690
6Thomas VanekXX98.005839817483807873527574567785765675690
7Frans NielsenX100.006738896875828566807267786585793975690
8Erik HaulaXXX100.007338797873815276807478637775684375690
9Adam LowryXX100.009254846591779164836666856471696375690
10Matthew PecaX100.005836946468676262736057685871664775620
11Anthony PelusoXX100.006445795588716354525653575578704775590
12Alex Pietrangelo (A)X100.006438867685918475308174895677867275740
13Dustin ByfuglienXXX97.008553567698916574308568735984753675720
14Jared SpurgeonX100.007137897463919572307973865878703975720
15Brandon MontourX98.007740767073899569307768745669676875690
16John MooreX100.008139796582847464307063785277706675670
17Trevor van RiemsdykX100.005636896679789164307157764875693675650
18Mark BarberioX100.005636846277785061306658764877694075630
Scratches
TEAM AVERAGE99.11684083717982806955736973637773527569
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
1Brian Elliott100.00868280828584868584868584882875710
Scratches
1Thomas Greiss99.00908285878988908988908984883375740
2Cory Schneider100.00848381838382848382848382875075700
TEAM AVERAGE99.6787828284868587868587868388377572
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Bob Boughner83749189403999CAN472550,000$


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
1Claude GirouxBluesC/RW65223153-50011209226801769.73%13135220.807121946223000024054.14%170100000.7825000336
2Jake GuentzelBluesC/LW/RW66212647128011892233631919.01%6131519.93961546237000002148.08%10400000.7157000334
3Jeff CarterBluesC/RW662221436140841092126012910.38%7126719.214101440220000045358.51%9400000.6803000471
4Jared SpurgeonBluesD64736434180649811034726.36%76133620.8831114481840000161200.00%000100.6400000114
5Alex PietrangeloBluesD60122941-41405111712134649.92%89140123.376915731720001168210.00%000010.5800000322
6Dustin ByfuglienBluesLW/RW/D62122537-49410274104168611317.14%15136922.1021214362140000783133.33%11100000.5400011434
7Brandon MontourBluesD6692231-910951885784255810.71%60151422.95591447245000054230.00%000000.4100010311
8Erik HaulaBluesC/LW/RW59111829618080125135441298.15%5110318.7125722187000042153.93%123500000.5314000332
9Brandon SaadBluesLW/RW66151328-4201979211451417.11%7113517.205274522500011526146.67%13500000.4903000213
10Adam LowryBluesC/LW66915240541018410613336966.77%23114617.3815665400082181257.46%36200100.4200110331
11Thomas VanekBluesLW/RW659918-19120346310634658.49%10111517.17224181320002653036.06%20800000.3202000111
12Frans NielsenBluesC6389170402912080206310.00%1582813.1512322800061851053.28%109800000.4100000020
13Trevor van RiemsdykBluesD6631417-1028081465017306.00%55116217.61347351710000172010.00%000000.2900000000
14John MooreBluesD66312156995156464312316.98%59123018.640005390001143000.00%000000.2400000001
15Artem AnisimovBluesC/LW667411-60016819231507.61%7126119.1101146100011142052.10%28600100.1711000012
16Mark BarberioBluesD62088-62807830187110.00%4781613.17000320000189000.00%000000.2000000000
17Matthew PecaBluesC65112-700241206205.00%52934.520000110000400051.78%30900000.1400000000
18Maxime LajoieRampage (STL)D2501102091010140.00%1232513.000001600002000.00%000000.0600000000
19Adam CracknellRampage (STL)RW54011-9008516380.00%13286.0800011000000046.15%2600000.0600000000
20Anthony PelusoBluesLW/RW41011-5201511000.00%01463.5800000000000035.71%2800000.1400000000
21Calle RosenRampage (STL)D5000-200001100.00%2326.420001700001000.00%000000.0000000000
22Eric GrybaRampage (STL)D15000140001010.00%0181.250001400003000.00%000000.0000000000
23Dawson LeedahlRampage (STL)LW6000000200000.00%081.440000000007000.00%100000.0000000000
Team Total or Average1239171296467-665303015031539207161414708.26%5142051116.5550901404802451000211670351452.49%569800310.46925131303132
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
1Brian ElliottBlues2915840.9112.26167222637040200.75082640211
2Thomas GreissBlues28141300.9072.60159343697380010.83362834310
Team Total or Average57292140.9082.4332666513214420210.786145474521


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 LowryBluesC/LW261993-03-29No210 Lbs6 ft5NoNoNo5RFAPro & Farm2,916,666$2,916,666$580,197$NoLink / NHL Link
Alex PietrangeloBluesD291990-01-18No210 Lbs6 ft3NoNoNo2UFAPro & Farm7,000,000$7,000,000$1,392,473$NoLink / NHL Link
Anthony PelusoBluesLW/RW301989-04-18No225 Lbs6 ft3NoNoNo2UFAPro & Farm700,000$700,000$139,247$NoLink / NHL Link
Artem AnisimovBluesC/LW311988-05-24No198 Lbs6 ft4NoNoNo1UFAPro & Farm4,550,000$4,550,000$905,108$NoLink / NHL Link
Brandon MontourBluesD251994-04-11No193 Lbs6 ft0NoNoNo5RFAPro & Farm3,387,500$3,387,500$673,858$NoLink / NHL Link
Brandon SaadBluesLW/RW261992-10-27No206 Lbs6 ft1NoNoNo2RFAPro & Farm5,750,000$5,750,000$1,143,817$NoLink / NHL Link
Brian ElliottBluesG341985-04-09No209 Lbs6 ft2NoNoNo5UFAPro & Farm3,250,000$3,250,000$646,505$NoLink / NHL Link
Claude GirouxBluesC/RW311988-01-12No185 Lbs5 ft11NoNoNo2UFAPro & Farm9,000,000$9,000,000$1,790,323$NoLink / NHL Link
Cory SchneiderBluesG331986-03-18No200 Lbs6 ft3NoNoNo5UFAPro & Farm2,225,000$2,225,000$442,608$NoLink / NHL Link
Dustin ByfuglienBluesLW/RW/D341985-03-27No260 Lbs6 ft5NoNoNo5UFAPro & Farm7,600,000$7,600,000$1,511,828$NoLink / NHL Link
Erik HaulaBluesC/LW/RW281991-03-23No193 Lbs6 ft0NoNoNo1UFAPro & Farm950,000$950,000$188,978$NoLink / NHL Link
Frans NielsenBluesC351984-04-24No188 Lbs6 ft1NoNoNo1UFAPro & Farm3,500,000$3,500,000$696,237$NoLink / NHL Link
Jake GuentzelBluesC/LW/RW241994-10-06No180 Lbs5 ft11NoNoNo1RFAPro & Farm734,167$734,167$146,044$NoLink / NHL Link
Jared SpurgeonBluesD291989-11-29No167 Lbs5 ft9NoNoNo1UFAPro & Farm3,600,000$3,600,000$716,129$NoLink / NHL Link
Jeff CarterBluesC/RW341985-01-01No219 Lbs6 ft3NoNoNo4UFAPro & Farm5,272,727$5,272,727$1,048,876$NoLink / NHL Link
John MooreBluesD281990-11-19No210 Lbs6 ft2NoNoNo5UFAPro & Farm2,750,000$2,750,000$547,043$NoLink / NHL Link
Mark BarberioBluesD291990-03-23No200 Lbs6 ft1NoNoNo2UFAPro & Farm800,000$800,000$159,140$NoLink / NHL Link
Matthew PecaBluesC261993-04-27No182 Lbs5 ft9NoNoNo2RFAPro & Farm650,000$650,000$129,301$NoLink / NHL Link
Thomas GreissBluesG331986-01-29No232 Lbs6 ft2NoNoNo2UFAPro & Farm2,000,000$2,000,000$397,849$NoLink / NHL Link
Thomas VanekBluesLW/RW351984-01-19No214 Lbs6 ft2NoNoNo3UFAPro & Farm2,000,000$2,000,000$397,849$NoLink / NHL Link
Trevor van RiemsdykBluesD281991-07-24No192 Lbs6 ft2NoNoNo5UFAPro & Farm2,300,000$2,300,000$457,527$NoLink / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2129.90203 Lbs6 ft12.903,377,908$

Sum Year 1 Salary Sum Year 2 Salary Sum Year 3 Salary Sum Year 4 Salary Sum Year 5 Salary
70,936,060$57,601,893$31,701,893$29,701,893$24,429,166$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Dustin ByfuglienClaude GirouxThomas Vanek40122
2Jake GuentzelErik HaulaJeff Carter35122
3Artem AnisimovFrans NielsenBrandon Saad23122
4Dustin ByfuglienAdam LowryBrandon Saad2122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Alex PietrangeloBrandon Montour40122
2John MooreJared Spurgeon35122
3Mark BarberioTrevor van Riemsdyk20122
4Jared SpurgeonBrandon Montour5122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Jake GuentzelClaude GirouxJeff Carter60005
2Thomas VanekErik HaulaBrandon Saad40005
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Dustin ByfuglienBrandon Montour60005
2Alex PietrangeloJared Spurgeon40005
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Adam LowryDustin Byfuglien60122
2Frans NielsenBrandon Saad40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Alex PietrangeloJared Spurgeon60122
2John MooreTrevor van Riemsdyk40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Adam Lowry60122Alex PietrangeloJared Spurgeon60122
2Frans Nielsen40122John MooreTrevor van Riemsdyk40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Claude GirouxJake Guentzel60122
2Erik HaulaJeff Carter40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Alex PietrangeloTrevor van Riemsdyk60122
2Jared SpurgeonBrandon Montour40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Jake GuentzelClaude GirouxDustin ByfuglienAlex PietrangeloJared Spurgeon
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Adam LowryJeff CarterBrandon SaadAlex PietrangeloJared Spurgeon
Extra Forwards
Normal PowerPlayPenalty Kill
Claude Giroux, Jake Guentzel, Jeff CarterBrandon Saad, Claude GirouxArtem Anisimov
Extra Defensemen
Normal PowerPlayPenalty Kill
Alex Pietrangelo, Brandon Montour, Jared SpurgeonBrandon MontourJared Spurgeon, Mark Barberio
Penalty Shots
Claude Giroux, Jake Guentzel, Artem Anisimov, Jeff Carter, Brandon Saad
Goalie
#1 : , #2 : Brian Elliott
Custom OT Lines Forwards
Claude Giroux, Jake Guentzel, Erik Haula, Jeff Carter, Artem Anisimov, Dustin Byfuglien, Dustin Byfuglien, Brandon Saad, Thomas Vanek, Adam Lowry,
Custom OT Lines Defensemen
Alex Pietrangelo, Jared Spurgeon, Brandon Montour, Trevor van Riemsdyk, John Moore


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
6679L116828845619761706504526147115
All Games
GPWLOTWOTL SOWSOLGFGA
6629244342168160
Home Games
GPWLOTWOTL SOWSOLGFGA
3317921228470
Visitor Games
GPWLOTWOTL SOWSOLGFGA
33121522208490
Last 10 Games
WLOTWOTL SOWSOL
550000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
2765018.12%2303584.78%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
6616626294766494513
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1263237753.13%1116209653.24%53997355.40%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
165611571502480845426


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 - 2019-10-022Capitals3Blues5WBoxScore
4 - 2019-10-0524Stars1Blues3WBoxScore
6 - 2019-10-0734Blues3Maple Leafs5LBoxScore
9 - 2019-10-1051Blues4Senators3WXXBoxScore
11 - 2019-10-1266Blues4Canadiens3WXBoxScore
13 - 2019-10-1481Blues4Islanders2WBoxScore
16 - 2019-10-17101Canucks1Blues3WBoxScore
18 - 2019-10-19114Canadiens3Blues1LBoxScore
20 - 2019-10-21131Avalanche2Blues3WBoxScore
23 - 2019-10-24149Kings2Blues1LXXBoxScore
25 - 2019-10-26162Blues1Bruins3LBoxScore
26 - 2019-10-27171Blues4Red Wings1WBoxScore
29 - 2019-10-30190Wild2Blues1LBoxScore
31 - 2019-11-01200Blue Jackets1Blues2WBoxScore
32 - 2019-11-02213Blues2Wild4LBoxScore
35 - 2019-11-05232Blues0Canucks3LBoxScore
36 - 2019-11-06236Blues4Oilers1WBoxScore
39 - 2019-11-09261Blues3Flames2WBoxScore
42 - 2019-11-12275Coyotes2Blues4WBoxScore
45 - 2019-11-15297Blues1Blue Jackets2LXBoxScore
46 - 2019-11-16309Ducks5Blues2LBoxScore
49 - 2019-11-19324Lightning2Blues1LBoxScore
51 - 2019-11-21338Flames1Blues2WXXBoxScore
53 - 2019-11-23358Predators5Blues4LBoxScore
55 - 2019-11-25370Blues3Predators0WBoxScore
57 - 2019-11-27380Blues1Lightning3LBoxScore
59 - 2019-11-29402Blues2Stars1WXBoxScore
60 - 2019-11-30412Penguins1Blues2WXXBoxScore
62 - 2019-12-02422Blues2Blackhawks3LBoxScore
64 - 2019-12-04435Blues3Penguins4LBoxScore
67 - 2019-12-07454Maple Leafs0Blues2WBoxScore
70 - 2019-12-10472Blues1Sabres2LBoxScore
72 - 2019-12-12492Golden Knights2Blues3WXBoxScore
74 - 2019-12-14513Blackhawks1Blues2WXBoxScore
76 - 2019-12-16522Avalanche2Blues3WBoxScore
78 - 2019-12-18537Oilers3Blues2LXXBoxScore
81 - 2019-12-21564Blues2Sharks4LBoxScore
83 - 2019-12-23581Blues3Kings4LXBoxScore
87 - 2019-12-27588Blues5Jets3WBoxScore
89 - 2019-12-29602Jets0Blues5WBoxScore
91 - 2019-12-31625Blues3Coyotes2WBoxScore
93 - 2020-01-02634Blues3Avalanche5LBoxScore
95 - 2020-01-04644Blues6Golden Knights4WBoxScore
98 - 2020-01-07670Sharks1Blues3WBoxScore
100 - 2020-01-09683Sabres4Blues1LBoxScore
102 - 2020-01-11698Rangers2Blues3WBoxScore
104 - 2020-01-13713Ducks1Blues2WBoxScore
106 - 2020-01-15726Flyers5Blues2LBoxScore
109 - 2020-01-18744Blues1Avalanche3LBoxScore
118 - 2020-01-27772Blues3Canucks2WBoxScore
119 - 2020-01-28775Blues4Flames3WXXBoxScore
122 - 2020-01-31790Blues0Oilers2LBoxScore
123 - 2020-02-01795Blues3Jets2WBoxScore
126 - 2020-02-04820Hurricanes2Blues3WBoxScore
128 - 2020-02-06834Jets3Blues2LXBoxScore
130 - 2020-02-08852Stars0Blues1WBoxScore
133 - 2020-02-11876Blues1Ducks5LBoxScore
135 - 2020-02-13889Blues5Golden Knights3WBoxScore
137 - 2020-02-15896Predators2Blues5WBoxScore
138 - 2020-02-16910Blues1Predators3LBoxScore
140 - 2020-02-18924Devils3Blues5WBoxScore
142 - 2020-02-20938Coyotes3Blues0LBoxScore
143 - 2020-02-21944Blues2Stars0WBoxScore
145 - 2020-02-23964Blues0Wild3LBoxScore
147 - 2020-02-25976Blackhawks1Blues3WBoxScore
149 - 2020-02-27990Islanders4Blues3LBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
151 - 2020-02-291007Stars-Blues-
154 - 2020-03-031021Blues-Rangers-
157 - 2020-03-061043Blues-Devils-
159 - 2020-03-081062Blues-Blackhawks-
161 - 2020-03-101075Panthers-Blues-
164 - 2020-03-131094Sharks-Blues-
166 - 2020-03-151111Senators-Blues-
168 - 2020-03-171125Blues-Flyers-
170 - 2020-03-191140Blues-Hurricanes-
172 - 2020-03-211156Blues-Panthers-
175 - 2020-03-241181Blues-Capitals-
178 - 2020-03-271200Kings-Blues-
180 - 2020-03-291220Wild-Blues-
182 - 2020-03-311233Red Wings-Blues-
184 - 2020-04-021250Bruins-Blues-
186 - 2020-04-041258Blues-Avalanche-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2Level 3Level 4Luxury
Arena Capacity7825390049001900975
Ticket Price20015010090300
Attendance104,45160,43964,68036,64219,977
Attendance PCT40.45%46.96%40.00%58.44%62.09%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
8 8672 - 44.47% 1,752,735$57,840,242$19500100

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches SalariesSpecial Salary Cap Value
58,150,836$ 70,936,060$ 64,836,060$ 0$ 0$
Salary Cap Per DaysSalary Cap To DateLuxury Taxe TotalPlayers In Salary CapPlayers Out of Salary Cap
70,936,060$ 57,710,255$ 0$ 21 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
14,021,877$ 37 384,334$ 14,220,358$

Team Total Estimate
Estimated Season ExpensesEstimated Season Salary CapCurrent Bank AccountProjected Bank Account
14,613,224$ 70,936,060$ 32,878,448$ 32,801,051$



Depth Chart

Left WingCenterRight Wing
Dustin ByfuglienAGE:34PO:36OV:72
Jake GuentzelAGE:24PO:63OV:71
Brandon SaadAGE:26PO:63OV:70
Adam LowryAGE:26PO:63OV:69
Thomas VanekAGE:35PO:56OV:69
Artem AnisimovAGE:31PO:55OV:69
Erik HaulaAGE:28PO:43OV:69
Carsen TwarynskiAGE:21PO:63OV:59
Steven LorentzAGE:23PO:62OV:59
Tom SestitoAGE:31PO:53OV:59
Anthony PelusoAGE:30PO:47OV:59
Mason ShawAGE:20PO:64OV:58
Dawson LeedahlAGE:23PO:62OV:56
Ryan KuffnerAGE:23PO:48OV:56
Claude GirouxAGE:31PO:64OV:75
Jake GuentzelAGE:24PO:63OV:71
Jeff CarterAGE:34PO:46OV:71
Adam LowryAGE:26PO:63OV:69
Artem AnisimovAGE:31PO:55OV:69
Erik HaulaAGE:28PO:43OV:69
Frans NielsenAGE:35PO:39OV:69
Matthew PecaAGE:26PO:47OV:62
*Ryan MacInnisAGE:23PO:69OV:59
Anthony RichardAGE:22PO:61OV:59
Brad MorrisonAGE:22PO:63OV:58
Tanner MacMasterAGE:23PO:46OV:58
Stephen PerfettoAGE:28PO:43OV:57
Matthew LaneAGE:25PO:51OV:56
Claude GirouxAGE:31PO:64OV:75
Dustin ByfuglienAGE:34PO:36OV:72
Jake GuentzelAGE:24PO:63OV:71
Jeff CarterAGE:34PO:46OV:71
Brandon SaadAGE:26PO:63OV:70
Thomas VanekAGE:35PO:56OV:69
Erik HaulaAGE:28PO:43OV:69
Adam CracknellAGE:34PO:39OV:62
Jonathon MartinAGE:24PO:61OV:60
Sergei ShumakovAGE:25PO:61OV:60
Anthony PelusoAGE:30PO:47OV:59
Tony CalderoneAGE:24PO:60OV:58

Defense #1Defense #2Goalie
Alex PietrangeloAGE:29PO:72OV:74
Jared SpurgeonAGE:29PO:39OV:72
Dustin ByfuglienAGE:34PO:36OV:72
Brandon MontourAGE:25PO:68OV:69
John MooreAGE:28PO:66OV:67
Trevor van RiemsdykAGE:28PO:36OV:65
Maxime LajoieAGE:21PO:58OV:63
Mark BarberioAGE:29PO:40OV:63
Calle RosenAGE:25PO:51OV:62
Eric GrybaAGE:31PO:52OV:61
Joe HickettsAGE:23PO:53OV:59
Sergei BoikovAGE:23PO:68OV:58
Connor HobbsAGE:22PO:63OV:58
Matt TaorminaAGE:32PO:52OV:58
Thomas GregoireAGE:21PO:53OV:57
Thomas GreissAGE:33PO:33OV:74
Brian ElliottAGE:34PO:28OV:71
Cory SchneiderAGE:33PO:50OV:70
Chris NellAGE:25PO:51OV:63
Angus RedmondAGE:23PO:52OV:60
Ryan FaragherAGE:29PO:44OV:59

Prospects

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
Prospect Team NameDraft Year Overall Pick Information Lien
Aleski HeponiemiBlues
Alex NewhookBlues201917
Anthony FlorentinoBlues
Brad BoyesBlues
Brogan O'BrienBlues8167
Christoph BertschyBlues
Daniel KrejciBlues
Daniil MiromanovBlues8197
Dante FabbroBlues817
David CottonBlues
Griffin LuceBlues8137
Jaret Anderson-DolanBlues
Jason SalvaggioBlues
Jay McClementBlues
Jean-Christophe BeaudinBlues
Joseph GarreffaBlues
Jussi JokinenBlues
Lucas MichaudBlues
Maksim ZhukovBlues
Mark CundariBlues
Maxim ShalunovBlues
Mike RibeiroBlues
Milos RomanBlues2018104
Peter QuennevilleBlues
Phil McRaeBlues
Ryan LarkinBlues
Steve MasonBlues
Teddy PurcellBlues
Tyson StrachanBlues

Draft Picks

Year R1R2R3R4R5R6R7
2020STL STL SJS STL PHI TBL STL STL PHI STL PHI ARI
2021STL STL STL STL STL STL STL
2022STL STL STL STL STL STL STL
2023STL STL STL STL STL STL STL
2024STL STL STL STL STL STL STL



[2020-02-16 08:46:04] - TRADE : From Blues to Canadiens : Y:2020-RND:5-BOS, Y:2020-RND:7-STL.
[2020-02-16 08:46:04] - TRADE : From Canadiens to Blues : Thomas Vanek (69).
[2020-01-01 07:39:57] - Kyle Copobianco has been deleted from Blues.
[2019-11-16 08:09:29] - TRADE : From Blues to Lightning : Henrik Lundqvist (74).
[2019-11-16 08:09:29] - TRADE : From Lightning to Blues : Thomas Greiss (72).
[2019-09-10 19:42:53] - TRADE : From Coyotes to Blues : Matthew Peca (62).
[2019-09-10 19:42:53] - TRADE : From Blues to Coyotes : Trevor Daley (66).
[2019-09-04 15:31:27] - Jonathon Martin was added to Blues.
[2019-09-04 15:31:17] - Dawson Leedahl was added to Blues.
[2019-09-04 15:31:02] - Matthew Lane was added to Blues.
[2019-09-04 15:30:50] - Sergei Boikov was added to Blues.
[2019-09-04 15:30:30] - Eric Gryba was added to Blues.
[2019-09-04 15:29:08] - Tom Sestito was added to Blues.
[2019-09-04 15:29:05] - Tony Calderone was added to Blues.
[2019-09-04 15:28:58] - Tanner MacMaster was added to Blues.
[2019-09-04 15:28:47] - Steven Lorentz was added to Blues.
[2019-09-04 15:28:45] - Stephen Perfetto was added to Blues.
[2019-09-04 15:28:38] - Sergei Shumakov was added to Blues.
[2019-09-04 15:28:35] - Ryan Faragher was added to Blues.
[2019-09-04 15:28:11] - Chris Nell was added to Blues.
[2019-09-04 15:28:05] - Angus Redmond was added to Blues.
[2019-09-04 13:40:51] - Ryan MacInnis was added to Blues.
[2019-09-04 13:29:09] - Rampage hired Trent Cull for 350,000$ for 2 year(s).
[2019-09-04 13:28:11] - Blues hired Bob Boughner for 550,000$ for 2 year(s).
[2019-09-04 12:50:08] - Rampage fired Trent Cull.
[2019-09-04 12:50:08] - Blues fired Bob Boughner.
[2019-09-04 12:45:56] - Team Name Change : Rampage changed name to Rampage
[2019-08-20 22:12:12] - TRADE : From Blues to Bruins : Loui Eriksson (67).
[2019-08-20 22:12:12] - TRADE : From Bruins to Blues : Y:2020-RND:5-BOS.



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
201782421908724251199524123604521117813641191304203134118168425141566666401188315242170989078859235974669116433789124.07%3246280.86%41103186059.30%1010182155.46%609106956.97%174294516907891542786
2018823628045272031949412380421311981384113200031484113-29722033685712573695512236973677682568206060255516102945117.35%2403485.83%01472280052.57%1351258852.20%657118055.68%2079145918545871046535
20196629240434216816083317902122847014331215022208490-6791682884561566494513197666166262947170650452614712765018.12%2303584.78%01263237753.13%1116209653.24%53997355.40%165611571502480845426
Total Regular Season230107710161581362255369115632301085632023288115444806737302321-1923562210711693916179236183406766210623282242174612518521772472494819220.25%79413183.50%43838703754.54%3477650553.45%1805322256.02%547835625048185834331748
Playoff
2017126600000322846330000014113633000001817112325385024151304361271371225040912992279641218.75%371170.27%022237459.36%19833459.28%10817661.36%309179275123242126
2018514000001015-52110000045-130300000610-421018280036011434154444155445111620525.00%15193.33%08117346.82%8617748.59%348440.48%11879122396633
Total Playoff17710000004243-18440000018162936000002427-31442711130272113157916819116654564173143395841720.24%521276.92%030354755.39%28451155.58%14226054.62%427259398163309159