Barracuda

GP: 22 | W: 15 | L: 7 | OTL: 0 | P: 30
GF: 85 | GA: 68 | PP%: 58.82% | PK%: 59.52%
GM : Will Clements | Morale : 50 | Team Overall : 56
Next Games vs Falcons
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

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
1Christoph BertschyXX100.007266857166808659745657625444446350600
2C.J. Smith (R)X100.007366907066656664506362645944446550600
3T.J. TynanX100.006658866258838864806857605444446350600
4Ryan Hitchcock (R)XX100.007463996563545264806461645844446450580
5Dominic Toninato (R)X100.006741897663517261605555612548486050570
6Alexander True (R)X100.008079816779575757715654655144446050570
7Antoine Waked (R)X100.007470846770748148504348604644445650550
8Jens Looke (R)XX100.007668936568646851504948624644445650550
9Nick MoutreyXX100.007876836376616449614548624644445550540
10Adam Gilmour (R)XX100.007974926174616549614646634444445550540
11Tyler WotherspoonX100.007878796578687255255243644144445750590
12Aaron NessX100.007166846966697354255241613948485550580
13Patrick SieloffX100.008175946675657145253639633744445250570
14Ludwig BystromX100.007064836564656853255041593944445450560
15Maxime Lajoie (R)X100.007567926567626649254339613744445350560
16Andrew O'BrienX100.007678706278565947253741613944445250550
Scratches
1Mike Vecchione (R)XX99.807468886368666862785862645944446450590
2Tye McGinnX79.407476697176565658505357655455556150580
3Graham Knott (R)X100.007974896274687447504346624444445450540
4Mackenzie MacEachern (R)X100.007672846272626650504451624844445650540
5Matt Buckles (R)X100.008580956280495050635044664244445550540
6Connor Clifton (R)X100.007063876463596345253441573944445150530
TEAM AVERAGE99.05756986667063685450504962464545575057
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
1Mike McKenna100.00586581755760546257563046465850580
2Yann Danis100.00546683685258505853523049495550560
Scratches
1Michael McNiven (R)100.00516986794652505648483044445250540
TEAM AVERAGE100.0054678374525751595352304646555056
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
1C.J. SmithBarracuda (SJ )LW2236427812373533271957210318.46%1550923.14612189270005305146.43%284216063.0611232425
2T.J. TynanBarracuda (SJ )C222945741551452939154499018.83%1351123.251091915270112293060.31%5242416022.8911144153
3Christoph BertschyBarracuda (SJ )C/RW2211283901210292679205213.92%1139317.913473160001132161.68%321245001.9800011120
4Ryan HitchcockBarracuda (SJ )C/LW221821392175271979245522.78%1238117.35448617000050060.00%20277022.0400010320
5Tye McGinnBarracuda (SJ )LW191218301495351375325816.00%827914.70000001011141045.45%11247022.1500001302
6Aaron NessBarracuda (SJ )D22326290472523256236294.84%4658126.42358530011134000.00%0518001.0000122013
7Jens LookeBarracuda (SJ )LW/RW221562162420241879255718.99%1031414.2800000000020066.67%62414001.3400301030
8Patrick SieloffBarracuda (SJ )D220191913222023173418160.00%3342419.29033020000018000.00%0413000.9000202010
9Mike VecchioneBarracuda (SJ )C/RW138614-74230121325111532.00%619615.08112110000000069.23%13124011.4300213101
10Maxime LajoieBarracuda (SJ )D2207734125139231280.00%1630914.060001600001000.00%027000.4500113000
11Justin KloosSharksC/RW415659572125128.33%37218.2401105000020050.00%614001.6400001100
12Matt BucklesBarracuda (SJ )C171453556694611.11%11036.0802218000060050.00%2661000.9700001000
13Andrew O'BrienBarracuda (SJ )D2202264135241710420.00%428813.100000000008000.00%0111000.1400124000
14Dominic ToninatoBarracuda (SJ )C22022-455262450.00%1713.2300000000000057.65%8520000.5600010000
15Tyler WotherspoonBarracuda (SJ )D30112275741510.00%25719.290000300003000.00%000000.3500010000
16Ludwig BystromBarracuda (SJ )D5011920735000.00%38517.050000400004000.00%012000.2300000000
Team Total or Average2811342333677939127530124484432150915.88%184457916.30274168411801231017611259.81%10401991250131.6022131725141614
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
1Thomas GreissSharks43100.8773.98241001613084100.000044001
Team Total or Average43100.8773.98241001613084100.000044001


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 CONT StatusType Current Salary Salary 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
Aaron NessBarracuda (SJ )D271991-05-18No184 Lbs5 ft10NoNoNo3RFAPro & Farm650,000$650,000$650,000$Link
Adam GilmourBarracuda (SJ )C/RW241994-01-28Yes192 Lbs6 ft4NoNoNo2RFAPro & Farm650,000$650,000$Link
Alexander TrueBarracuda (SJ )C211997-07-17Yes205 Lbs6 ft5NoNoNo2RFAPro & Farm800,000$800,000$Link
Andrew O'BrienBarracuda (SJ )D251992-11-20No208 Lbs6 ft4NoNoNo2RFAPro & Farm650,000$650,000$Link
Antoine WakedBarracuda (SJ )RW221996-05-17Yes194 Lbs6 ft0NoNoNo2RFAPro & Farm800,000$800,000$Link
C.J. SmithBarracuda (SJ )LW231994-12-01Yes185 Lbs5 ft11NoNoNo2RFAPro & Farm925,000$925,000$Link
Christoph BertschyBarracuda (SJ )C/RW241994-04-04No186 Lbs5 ft10NoNoNo1RFAPro & Farm500,000$Link
Connor CliftonBarracuda (SJ )D231995-04-28Yes190 Lbs5 ft11NoNoNo3RFAPro & Farm500,000$500,000$500,000$Link
Dominic ToninatoBarracuda (SJ )C241994-03-09Yes165 Lbs6 ft1NoNoNo3RFAPro & Farm500,000$500,000$500,000$Link
Graham KnottBarracuda (SJ )LW211997-01-13Yes191 Lbs6 ft3NoNoNo3RFAPro & Farm800,000$800,000$800,000$Link
Jens LookeBarracuda (SJ )LW/RW211997-04-11Yes180 Lbs6 ft1NoNoNo3RFAPro & Farm700,000$700,000$700,000$Link
Ludwig BystromBarracuda (SJ )D241994-07-20No175 Lbs6 ft1NoNoNo3RFAPro & Farm650,000$650,000$650,000$Link
Mackenzie MacEachernBarracuda (SJ )LW241994-03-08Yes190 Lbs6 ft2NoNoNo2RFAPro & Farm750,000$750,000$Link
Matt BucklesBarracuda (SJ )C231995-05-05Yes218 Lbs6 ft3NoNoNo1RFAPro & FarmLink
Maxime LajoieBarracuda (SJ )D211997-11-05Yes183 Lbs6 ft1NoNoNo3RFAPro & Farm500,000$500,000$500,000$Link
Michael McNivenBarracuda (SJ )G211997-07-09Yes221 Lbs6 ft1NoNoNo2RFAPro & Farm750,000$750,000$Link
Mike McKennaBarracuda (SJ )LW/RW341984-07-14 7:21:33 PMNo190 Lbs6 ft2NoNoNo2UFAPro & Farm750,000$750,000$Link
Mike VecchioneBarracuda (SJ )C/RW251993-02-25Yes194 Lbs5 ft10NoNoNo1RFAPro & Farm925,000$Link
Nick MoutreyBarracuda (SJ )C/LW231995-06-23No218 Lbs6 ft3NoNoNo1RFAPro & Farm650,000$Link
Patrick SieloffBarracuda (SJ )D241994-05-14No205 Lbs6 ft1NoNoNo3RFAPro & Farm650,000$650,000$650,000$Link
Ryan HitchcockBarracuda (SJ )C/LW221996-03-30Yes176 Lbs5 ft10NoNoNo2RFAPro & Farm900,000$900,000$Link
T.J. TynanBarracuda (SJ )C261992-02-24No165 Lbs5 ft8NoNoNo2RFAPro & Farm650,000$650,000$Link
Tye McGinn (Out of Payroll)Barracuda (SJ )LW271991-07-29No205 Lbs6 ft2NoNoNo1RFAPro & Farm700,000$Link
Tyler WotherspoonBarracuda (SJ )D251993-03-12No207 Lbs6 ft2NoNoNo1RFAPro & Farm850,000$Link
Yann DanisBarracuda (SJ )C361982-06-21No185 Lbs6 ft0NoNoNo2UFAPro & Farm650,000$650,000$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2524.40192 Lbs6 ft12.08674,000$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1C.J. SmithT.J. Tynan40122
2Ryan HitchcockChristoph Bertschy30122
3Jens Looke20122
4T.J. TynanDominic ToninatoC.J. Smith10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Aaron Ness40122
2Patrick Sieloff30122
3Maxime LajoieAndrew O'Brien20122
4Aaron Ness10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1C.J. SmithT.J. Tynan60122
2Ryan HitchcockChristoph Bertschy40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Aaron Ness60122
2Patrick Sieloff40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1T.J. TynanC.J. Smith60122
2Christoph Bertschy40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Aaron Ness60122
2Patrick Sieloff40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1T.J. Tynan60122Aaron Ness60122
2C.J. Smith40122Patrick Sieloff40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1T.J. TynanC.J. Smith60122
2Christoph Bertschy40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Aaron Ness60122
2Patrick Sieloff40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
C.J. SmithT.J. TynanAaron Ness
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
C.J. SmithT.J. TynanAaron Ness
Extra Forwards
Normal PowerPlayPenalty Kill
, , ,
Extra Defensemen
Normal PowerPlayPenalty Kill
Maxime Lajoie, Andrew O'Brien, Patrick SieloffMaxime LajoieAndrew O'Brien, Patrick Sieloff
Penalty Shots
T.J. Tynan, C.J. Smith, , Christoph Bertschy,
Goalie
#1 : , #2 :


Filter Tips
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
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
1Admirals10100000811-310100000811-30000000000000.00081018004765544403143452956441671444100.00%10100.00%021737657.71%16930555.41%28953154.43%510324421185395193
2Comets11000000954000000000001100000095421.0009172600476554457314345295625121716000.00%10100.00%021737657.71%16930555.41%28953154.43%510324421185395193
3Falcons21100000151411100000083510100000711-420.500152035004765544823143452956812561425120.00%3166.67%021737657.71%16930555.41%28953154.43%510324421185395193
4Griffins1010000089-1000000000001010000089-100.0008132100476554457314345295632137127457.14%10100.00%021737657.71%16930555.41%28953154.43%510324421185395193
5Gulls3210000013103110000005232110000088040.667132336004765544119314345295685163947200.00%70100.00%021737657.71%16930555.41%28953154.43%510324421185395193
6Heat1100000010550000000000011000000105521.0001017270047655444931434529564312311133100.00%30100.00%021737657.71%16930555.41%28953154.43%510324421185395193
7IceCaps220000001961322000000196130000000000041.000193251004765544903143452956541868432150.00%4250.00%021737657.71%16930555.41%28953154.43%510324421185395193
8IceHogs3200001026141221000010201191100000063361.00026447000476554414731434529561194428505480.00%4325.00%121737657.71%16930555.41%28953154.43%510324421185395193
9Moose211000001718-110100000510-511000000128420.500172845004765544783143452956833753336466.67%4250.00%021737657.71%16930555.41%28953154.43%510324421185395193
10Penguins11000000844000000000001100000084421.0008142200476554431314345295632417113266.67%10100.00%021737657.71%16930555.41%28953154.43%510324421185395193
11Phantoms11000000954000000000001100000095421.000915240047655444031434529562310012000.00%000.00%021737657.71%16930555.41%28953154.43%510324421185395193
12Reign11000000853110000008530000000000021.0008142200476554451314345295639932226350.00%10100.00%021737657.71%16930555.41%28953154.43%510324421185395193
Since Last GM Reset221370101016813137116400010856817117301000836320300.6821682764440047655449573143452956760256429377513058.82%421759.52%121737657.71%16930555.41%28953154.43%510324421185395193
14Stars20101000111101010000056-11000100065120.500111627004765544653143452956622557574250.00%6350.00%021737657.71%16930555.41%28953154.43%510324421185395193
Total221370101016813137116400010856817117301000836320300.6821682764440047655449573143452956760256429377513058.82%421759.52%121737657.71%16930555.41%28953154.43%510324421185395193
Vs Conference168601010115981784300010615298430100054468200.6251151873020047655447183143452956568187291278402357.50%331360.61%121737657.71%16930555.41%28953154.43%510324421185395193
17Wolves10100000714-710100000714-70000000000000.0007132000476554451314345295638151274250.00%660.00%021737657.71%16930555.41%28953154.43%510324421185395193

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
2230L116827644495776025642937700
All Games
GPWLOTWOTL SOWSOLGFGA
221371010168131
Home Games
GPWLOTWOTL SOWSOLGFGA
116400108568
Visitor Games
GPWLOTWOTL SOWSOLGFGA
117310008363
Last 10 Games
WLOTWOTL SOWSOL
730000
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
513058.82%421759.52%1
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
31434529564765544
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
21737657.71%16930555.41%28953154.43%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
510324421185395193


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 - 2018-10-025Falcons3Barracuda8WBoxScore
5 - 2018-10-0635Barracuda5Gulls2WBoxScore
6 - 2018-10-0742Barracuda6Stars5WXBoxScore
8 - 2018-10-0958Stars6Barracuda5LBoxScore
10 - 2018-10-1176Reign5Barracuda8WBoxScore
13 - 2018-10-1496IceCaps4Barracuda10WBoxScore
15 - 2018-10-16110Barracuda7Falcons11LBoxScore
18 - 2018-10-19128Barracuda3Gulls6LBoxScore
19 - 2018-10-20137IceHogs7Barracuda8WXXBoxScore
22 - 2018-10-23159Gulls2Barracuda5WBoxScore
25 - 2018-10-26185Wolves14Barracuda7LBoxScore
27 - 2018-10-28199Barracuda10Heat5WBoxScore
28 - 2018-10-29207Barracuda9Phantoms5WBoxScore
31 - 2018-11-01223IceCaps2Barracuda9WBoxScore
34 - 2018-11-04246Barracuda8Penguins4WBoxScore
36 - 2018-11-06257Moose10Barracuda5LBoxScore
38 - 2018-11-08277Barracuda9Comets5WBoxScore
40 - 2018-11-10286Admirals11Barracuda8LBoxScore
42 - 2018-11-12304Barracuda12Moose8WBoxScore
44 - 2018-11-14312Barracuda6IceHogs3WBoxScore
46 - 2018-11-16326IceHogs4Barracuda12WBoxScore
48 - 2018-11-18334Barracuda8Griffins9LBoxScore
51 - 2018-11-21356Barracuda-Falcons-
52 - 2018-11-22364Griffins-Barracuda-
55 - 2018-11-25386Gulls-Barracuda-
58 - 2018-11-28405Barracuda-Reign-
59 - 2018-11-29416Comets-Barracuda-
62 - 2018-12-02435Barracuda-Condors-
64 - 2018-12-04448Marlies-Barracuda-
66 - 2018-12-06463Barracuda-Griffins-
68 - 2018-12-08478Wolf Pack-Barracuda-
70 - 2018-12-10494Barracuda-Admirals-
72 - 2018-12-12506Barracuda-Monsters-
73 - 2018-12-13516Comets-Barracuda-
76 - 2018-12-16537Sound Tigers-Barracuda-
78 - 2018-12-18552Barracuda-Phantoms-
80 - 2018-12-20560Barracuda-Americans-
82 - 2018-12-22573Barracuda-Checkers-
84 - 2018-12-24584Wolves-Barracuda-
86 - 2018-12-26597Barracuda-IceCaps-
88 - 2018-12-28613Wolves-Barracuda-
90 - 2018-12-30629Barracuda-Heat-
92 - 2019-01-01642IceCaps-Barracuda-
94 - 2019-01-03656Barracuda-Gulls-
96 - 2019-01-05674Reign-Barracuda-
100 - 2019-01-09698Wolves-Barracuda-
105 - 2019-01-14728Monsters-Barracuda-
108 - 2019-01-17747Barracuda-Reign-
109 - 2019-01-18761Falcons-Barracuda-
113 - 2019-01-22782Monsters-Barracuda-
115 - 2019-01-24798Barracuda-Bears-
117 - 2019-01-26813Heat-Barracuda-
119 - 2019-01-28830Barracuda-Stars-
121 - 2019-01-30842Barracuda-Wolves-
123 - 2019-02-01852Condors-Barracuda-
125 - 2019-02-03872Barracuda-Wolf Pack-
127 - 2019-02-05882Bruins-Barracuda-
129 - 2019-02-07899Barracuda-Wolves-
131 - 2019-02-09912Crunch-Barracuda-
133 - 2019-02-11925Barracuda-Falcons-
135 - 2019-02-13941Barracuda-Rampage-
136 - 2019-02-14949Stars-Barracuda-
138 - 2019-02-16966Barracuda-Wild-
140 - 2019-02-18982Wild-Barracuda-
143 - 2019-02-211003Condors-Barracuda-
Trade Deadline --- Trades can’t be done after this day is simulated!
145 - 2019-02-231014Barracuda-Senators-
148 - 2019-02-261035Wild-Barracuda-
150 - 2019-02-281054Barracuda-Wolves-
152 - 2019-03-021068Stars-Barracuda-
153 - 2019-03-031074Barracuda-Rampage-
156 - 2019-03-061095Barracuda-Devils-
157 - 2019-03-071103Barracuda-Admirals-
158 - 2019-03-081111Rampage-Barracuda-
161 - 2019-03-111126Barracuda-Wild-
164 - 2019-03-141146Pirates-Barracuda-
169 - 2019-03-191175Reign-Barracuda-



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
27 0 - 0.00% 0$0$3000100

Expenses
Players Total SalariesPlayers Total Average SalariesCoaches Salaries
1,615,000$ 1,395,000$ 0$
Year To Date ExpensesSalary Cap Per DaysSalary Cap To Date
491,960$ 0$ 488,322$

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 122 9,444$ 1,152,168$




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
2018221370101016813137116400010856817117301000836320301682764440047655449573143452956760256429377513058.82%421759.52%121737657.71%16930555.41%28953154.43%510324421185395193
Total Regular Season221370101016813137116400010856817117301000836320301682764440047655449573143452956760256429377513058.82%421759.52%121737657.71%16930555.41%28953154.43%510324421185395193