Bengals

GP: 6 | W: 3 | L: 2 | OTL: 1 | P: 7
GF: 16 | GA: 16 | PP%: 25.00% | PK%: 85.37%
GM : Charles-André Jutras | Morale : 79 | Team Overall : 62
Next Games #77 vs Jets
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
1Paul ByronXXX100.00855590855868866436747869806767080700
2Christian DvorakX100.00714396867168676993705963256161080660
3James NealXX100.00694386748168847438656058637882080660
4Matt PuempelXX100.00777581727578826750626669635555080650
5Chase De LeoX100.00736593626580846680656267595454080640
6Brendan GaunceXX100.00787974717967686580596370606060080640
7Josh LeivoXX100.00675787717867648037617156635959080640
8Tomas NosekXX100.00764491697963856263616273255455080640
9Dmytro TimashovX100.00726979676980856350635865555252080630
10Teddy BluegerX100.00846784686959576052627281254646080630
11Justin BaileyX100.00714493757943745625595562255252080590
12Maxim Letunov (R)X100.00777190627162635873535864554444080580
13Joel EdmundsonX100.00856671828278846025524885256465080710
Scratches
1Justin KirklandX100.00727077647080875450564861464545074580
2JC LiponX100.00606744656776815850535756544747074580
3Nikita Popugaev (R)XX100.00878395668353535450465768544444074580
4Graham KnottXX100.00777387627373805063474664445050074570
5Jens LookeXX100.00746692656671765250465362504747074570
6Nikita KorostelevX100.00797295657266695450564764454444074570
7Justin AugerX100.00868784648757595050385767544545074560
8Adam ClendeningX100.00637143677162636125634261405555067590
TEAM AVERAGE100.0075658270746874615258586648535407762
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
1Martin Jones100.0062918781566860666262956567075670
2Oscar Dansk100.0060617679606259666261304444080610
Scratches
1Michal Neuvirth100.0057506377615850595756306465074590
TEAM AVERAGE100.006067757959635664606052585907662
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Jim Playfair30303030303030CAN513300,000$


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
1Paul ByronBengals (TBS)C/LW/RW62460208171021420.00%413422.391342170000291048.18%13700000.8900000100
2James NealBengals (TBS)LW/RW6325000211103730.00%612420.762243180000301044.44%900000.8000000010
3Josh LeivoBengals (TBS)LW/RW614502025169136.25%09916.5812342000000000.00%300001.0100000100
4Chase De LeoBengals (TBS)C62241403162533.33%19315.5300000000000065.00%2000000.8600000100
5Teddy BluegerBengals (TBS)C613411002643425.00%09716.2112341800000000.00%000000.8200000000
6Matt PuempelBengals (TBS)LW/RW60440601099320.00%011919.970223200000240066.67%600000.6700000001
7Tomas NosekBengals (TBS)C/LW613410031153520.00%29115.2400005000030066.67%900000.8800000010
8Christian DvorakBengals (TBS)C6033-180212107120.00%012220.350221200000230070.59%11900000.4900000000
9Brendan GaunceBengals (TBS)C/LW612318013992711.11%210116.9600017000090063.16%7600000.5900000000
10Joel EdmundsonBengals (TBS)D6303-480125103530.00%1312721.29202821000018000.00%000000.4700000010
11Maxim LetunovBengals (TBS)C602231401110010.00%59215.46000060000110066.67%600000.4300000001
12Justin BaileyBengals (TBS)RW6112-1205271614.29%09215.42011117000001050.00%200000.4300000000
13Dmytro TimashovBengals (TBS)LW61010804452120.00%110417.4100021900000000.00%000000.1900000000
14Adam ClendeningBengals (TBS)D3000-140130000.00%35518.48000010000012000.00%000000.0000000000
Team Total or Average8116304607607896101408215.84%37145617.99714212920200001643059.43%38700000.6300000332
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
1Martin JonesBengals (TBS)63210.8672.5433100141050010.000060001
2Oscar DanskBengals (TBS)10000.8572.142800170000.000006000
Team Total or Average73210.8662.5036000151120010.000066001


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 ClendeningBengals (TBS)D261992-10-26No196 Lbs6 ft0NoNoNo2RFAPro & Farm700,000$0$0$NoLink / NHL Link
Brendan GaunceBengals (TBS)C/LW251994-03-25No217 Lbs6 ft2NoNoNo2RFAPro & Farm700,000$0$0$NoLink / NHL Link
Chase De LeoBengals (TBS)C231995-10-25No185 Lbs5 ft9NoNoNo1ELCPro & Farm765,000$0$0$NoLink
Christian DvorakBengals (TBS)C231996-02-02No195 Lbs6 ft0NoNoNo1ELCPro & Farm892,500$0$0$NoLink
Dmytro TimashovBengals (TBS)LW221996-09-30No195 Lbs5 ft10NoNoNo1ELCPro & Farm730,000$0$0$NoLink
Graham KnottBengals (TBS)C/LW221997-01-13No191 Lbs6 ft3NoNoNo2ELCPro & Farm742,500$0$0$NoLink
JC LiponBengals (TBS)RW251993-07-10No183 Lbs6 ft0NoNoNo2RFAPro & Farm700,000$0$0$NoLink / NHL Link
James Neal (1 Way Contract)Bengals (TBS)LW/RW311987-09-03No221 Lbs6 ft2NoNoNo1UFAPro & Farm5,000,000$3,000,000$2,770,833$NoLink / NHL Link
Jens LookeBengals (TBS)LW/RW221997-04-11No180 Lbs5 ft11NoNoNo2ELCPro & Farm817,500$0$0$NoLink
Joel Edmundson (1 Way Contract)Bengals (TBS)D261993-06-28No215 Lbs6 ft4NoNoNo1RFAPro & Farm1,050,000$0$0$NoLink / NHL Link
Josh Leivo (1 Way Contract)Bengals (TBS)LW/RW261993-05-26No210 Lbs6 ft2NoNoNo2RFAPro & Farm925,000$0$0$NoLink
Justin AugerBengals (TBS)RW251994-05-14No229 Lbs6 ft7NoNoNo2RFAPro & Farm700,000$0$0$NoLink
Justin BaileyBengals (TBS)RW231995-07-01No214 Lbs6 ft3NoNoNo1ELCPro & Farm700,000$0$0$NoLink
Justin KirklandBengals (TBS)LW221996-08-02No183 Lbs6 ft3NoNoNo1ELCPro & Farm742,500$0$0$NoLink
Martin Jones (1 Way Contract)Bengals (TBS)G291990-01-10No195 Lbs6 ft4NoNoNo1UFAPro & Farm3,000,000$1,000,000$923,611$NoLink / NHL Link
Matt PuempelBengals (TBS)LW/RW261993-01-24No205 Lbs6 ft1NoNoNo2RFAPro & Farm725,000$0$0$NoLink
Maxim LetunovBengals (TBS)C231996-02-19Yes180 Lbs6 ft4NoNoNo3ELCPro & Farm700,000$0$0$NoLink
Michal Neuvirth (1 Way Contract)Bengals (TBS)G311988-03-22No209 Lbs6 ft1NoNoNo1UFAPro & Farm2,500,000$500,000$461,806$NoLink / NHL Link
Nikita KorostelevBengals (TBS)RW221997-02-08No195 Lbs6 ft1NoNoNo2ELCPro & Farm700,000$0$0$NoLink
Nikita PopugaevBengals (TBS)LW/RW201998-11-19Yes217 Lbs6 ft6NoNoNo3ELCFarm Only700,000$0$0$NoLink
Oscar DanskBengals (TBS)G251994-02-28No195 Lbs6 ft3NoNoNo2RFAPro & Farm700,000$0$0$NoLink
Paul Byron (1 Way Contract)Bengals (TBS)C/LW/RW301989-04-26No162 Lbs5 ft9NoNoNo5UFAPro & Farm1,166,667$0$0$NoLink / NHL Link
Teddy BluegerBengals (TBS)C241994-08-14No185 Lbs6 ft0NoNoNo1RFAPro & Farm742,500$0$0$NoLink
Tomas Nosek (1 Way Contract)Bengals (TBS)C/LW261992-08-31No210 Lbs6 ft3NoNoNo2RFAPro & Farm962,500$0$0$NoLink / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2424.88199 Lbs6 ft21.791,127,569$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1James NealPaul ByronMatt Puempel30122
2Josh LeivoChristian DvorakJustin Bailey30122
3Tomas NosekBrendan GaunceChase De Leo25122
4Dmytro TimashovChase De LeoPaul Byron15122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Joel Edmundson30122
2Teddy BluegerDmytro Timashov30122
3Maxim Letunov25122
4Joel Edmundson15122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1James NealPaul ByronMatt Puempel55122
2Josh LeivoChristian DvorakJustin Bailey45122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Joel Edmundson55122
2Teddy BluegerDmytro Timashov45122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Paul ByronJames Neal55122
2Christian DvorakMatt Puempel45122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Joel Edmundson55122
245122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Paul Byron55122Joel Edmundson55122
2James Neal4512245122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Paul ByronJames Neal55122
2Christian DvorakMatt Puempel45122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Joel Edmundson55122
245122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
James NealPaul ByronMatt PuempelJoel Edmundson
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
James NealPaul ByronMatt PuempelJoel Edmundson
Extra Forwards
Normal PowerPlayPenalty Kill
Brendan Gaunce, Tomas Nosek, Maxim LetunovBrendan Gaunce, Tomas NosekMaxim Letunov
Extra Defensemen
Normal PowerPlayPenalty Kill
Joel Edmundson, , Joel Edmundson,
Penalty Shots
Paul Byron, James Neal, Christian Dvorak, Matt Puempel, Josh Leivo
Goalie
#1 : Martin Jones, #2 : Oscar Dansk


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
1Aeros1010000013-2000000000001010000013-200.00012310844013313436012416169111.11%8275.00%08413960.43%8916155.28%578765.52%13794151437135
2Oil Kings11000000422110000004220000000000021.0004610008440193134360207187400.00%9188.89%08413960.43%8916155.28%578765.52%13794151437135
3Olympic11000000312000000000001100000031221.00036900844021313436025118153133.33%40100.00%08413960.43%8916155.28%578765.52%13794151437135
4Redhawks1010000026-41010000026-40000000000000.000246008440113134360229161111100.00%8275.00%08413960.43%8916155.28%578765.52%13794151437135
5Rhinos11000000413110000004130000000000021.00048120084401931343601744127228.57%20100.00%08413960.43%8916155.28%578765.52%13794151437135
6Surfers1000010023-1000000000001000010023-110.50024600844018313436017320184250.00%10190.00%08413960.43%8916155.28%578765.52%13794151437135
Total63200100161603210000010913110010067-170.583163046108440101313436011338827928725.00%41685.37%08413960.43%8916155.28%578765.52%13794151437135
_Since Last GM Reset63200100161603210000010913110010067-170.583163046108440101313436011338827928725.00%41685.37%08413960.43%8916155.28%578765.52%13794151437135
_Vs Conference63200100161603210000010913110010067-170.583163046108440101313436011338827928725.00%41685.37%08413960.43%8916155.28%578765.52%13794151437135
_Vs Division2110000057-21010000026-41100000031220.50051015008440323134360472024264250.00%12283.33%08413960.43%8916155.28%578765.52%13794151437135

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
67L116304610111338827910
All Games
GPWLOTWOTL SOWSOLGFGA
63201001616
Home Games
GPWLOTWOTL SOWSOLGFGA
3210000109
Visitor Games
GPWLOTWOTL SOWSOLGFGA
311010067
Last 10 Games
WLOTWOTL SOWSOL
320100
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
28725.00%41685.37%0
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
31343608440
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
8413960.43%8916155.28%578765.52%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
13794151437135


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 - 2019-10-076Bengals2Surfers3LXBoxScore
2 - 2019-10-0815Oil Kings2Bengals4WBoxScore
4 - 2019-10-1029Bengals1Aeros3LBoxScore
7 - 2019-10-1339Bengals3Olympic1WBoxScore
8 - 2019-10-1448Rhinos1Bengals4WBoxScore
10 - 2019-10-1665Redhawks6Bengals2LBoxScore
12 - 2019-10-1877Bengals-Jets-
13 - 2019-10-1987Bengals-Mystery-
15 - 2019-10-2193Citadels-Bengals-
17 - 2019-10-23108Bengals-Devil Dogs-
19 - 2019-10-25122Oil Kings-Bengals-
21 - 2019-10-27135Winterhawks-Bengals-
23 - 2019-10-29148Olympic-Bengals-
25 - 2019-10-31162Bengals-Surfers-
27 - 2019-11-02171Bengals-Gamblers-
29 - 2019-11-04182Bengals-Sun Devils-
31 - 2019-11-06196Aeros-Bengals-
33 - 2019-11-08206Mystery-Bengals-
36 - 2019-11-11221Bengals-Citadels-
38 - 2019-11-13232Gamblers-Bengals-
39 - 2019-11-14242Bengals-Sun Devils-
42 - 2019-11-17255Sun Devils-Bengals-
44 - 2019-11-19269Jets-Bengals-
45 - 2019-11-20281Bengals-Redhawks-
47 - 2019-11-22291Sun Devils-Bengals-
49 - 2019-11-24303Bengals-Surfers-
51 - 2019-11-26315Bengals-Olympic-
53 - 2019-11-28327Winterhawks-Bengals-
55 - 2019-11-30335Bengals-Winterhawks-
56 - 2019-12-01350Aces-Bengals-
58 - 2019-12-03364Bengals-Redhawks-
60 - 2019-12-05374Citadels-Bengals-
61 - 2019-12-06384Bengals-Pitbulls-
64 - 2019-12-09400Mystery-Bengals-
65 - 2019-12-10411Bengals-Aces-
67 - 2019-12-12418Bengals-Cobras-
69 - 2019-12-14431Gamblers-Bengals-
71 - 2019-12-16448Rhinos-Bengals-
73 - 2019-12-18463Bengals-Boys-
74 - 2019-12-19472Broncos-Bengals-
76 - 2019-12-21486Bengals-Boys-
77 - 2019-12-22494Bengals-Rhinos-
79 - 2019-12-24505Olympic-Bengals-
81 - 2019-12-26520Aces-Bengals-
83 - 2019-12-28529Bengals-Indians-
85 - 2019-12-30545Broncos-Bengals-
86 - 2019-12-31556Bengals-Gators-
88 - 2020-01-02567Liberty-Bengals-
89 - 2020-01-03580Bengals-Liberty-
91 - 2020-01-05589Bengals-Jets-
92 - 2020-01-06599Redhawks-Bengals-
95 - 2020-01-09614Pitbulls-Bengals-
97 - 2020-01-11627Bengals-Devil Dogs-
98 - 2020-01-12638Indians-Bengals-
100 - 2020-01-14651Bengals-Indians-
101 - 2020-01-15662Gators-Bengals-
103 - 2020-01-17675Bengals-Oil Kings-
104 - 2020-01-18686Blazers-Bengals-
106 - 2020-01-20695Bengals-Cobras-
108 - 2020-01-22709Bengals-Blazers-
109 - 2020-01-23718Cobras-Bengals-
110 - 2020-01-24729Bengals-Mystery-
112 - 2020-01-26742Liberty-Bengals-
114 - 2020-01-28752Bengals-Aeros-
Trade Deadline --- Trades can’t be done after this day is simulated!
116 - 2020-01-30763Oil Kings-Bengals-
118 - 2020-02-01776Bengals-Rivercats-
120 - 2020-02-03787Rivercats-Bengals-
121 - 2020-02-04798Bengals-Rivercats-
123 - 2020-02-06813Pitbulls-Bengals-
124 - 2020-02-07820Bengals-Gamblers-
126 - 2020-02-09836Blazers-Bengals-
127 - 2020-02-10842Bengals-Broncos-
130 - 2020-02-13860Gators-Bengals-
131 - 2020-02-14863Bengals-Blazers-
133 - 2020-02-16876Bengals-Broncos-
135 - 2020-02-18888Boys-Bengals-
139 - 2020-02-22912Devil Dogs-Bengals-
142 - 2020-02-25931Surfers-Bengals-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price289
Attendance5,8742,770
Attendance PCT97.90%92.33%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
36 2881 - 96.04% 63,134$189,402$300090

Expenses
Year To Date ExpensesPlayers Total SalariesPlayers Total Average SalariesCoaches Salaries
99,044$ 996,600$ 996,600$ 0$
Salary Cap Per DaysSalary Cap To DatePlayers In Salary CapPlayers Out of Salary Cap
6,921$ 76,131$ 0 0

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
2,272,824$ 133 9,004$ 1,197,532$




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
201963200100161603210000010913110010067-17163046108440101313436011338827928725.00%41685.37%08413960.43%8916155.28%578765.52%13794151437135
Total Regular Season63200100161603210000010913110010067-17163046108440101313436011338827928725.00%41685.37%08413960.43%8916155.28%578765.52%13794151437135