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Ohio

Season: 2027 2026 2025 2024 2023 2022 2021 2020 2019 2018
Also known as: Ohio Bobcats
Program History
Coach: Bob Boldon

2015 Team Stats (2 games)

57.5
PPG
59.0
Opp
-1.5
Margin
37.5%
FG%
35.3%
3P%
65.5%
FT%
37.0
RPG
14.0
APG
17.0
TO
-
Est. poss./game
67.3
Adj PPG
55.9
Adj Opp PPG
#58
Scoring Rank

Model Outputs

2014-2015
Catalog

Output is shown as model rating with league rank in parentheses when available.

Model Output Notes
Elo Elo Streaming paired-comparison rating with recency baked into sequential updates. More → 1213 (#72) -
Bradley-Terry Bradley-Terry Static logistic paired-comparison model with one team strength parameter. More → 1255 (#40) -
Bradley-Terry Recency Bradley-Terry Recency Static Bradley-Terry with exponential recency weights on newer games. HCA +86 elo More → 1152 (#23) HCA +86 elo
Margin Margin Linear team-strength model fit on point differential instead of binary wins. HCA +2.9 More → +11.8 (#63) HCA +2.9
Margin Recency Margin Recency Margin regression with exponential recency weights on newer games. HCA +2.7 More → +9.4 (#75) HCA +2.7
Pythagorean Pythagorean Pythagorean win expectation from raw points scored and allowed. More → 0.919 (#18) -
Adjusted Efficiency Adjusted Efficiency Opponent-adjusted efficiency model with separate offensive and defensive components. AdjNet +18.8 More → 0.898 (#61) AdjNet +18.8
Log Adjusted Log Adjusted Log-scale adjusted efficiency model that downweights blowout leverage. AdjNet +19.0 More → 0.901 (#62) AdjNet +19.0
Points Off/Def Points Off/Def Raw points regression with separate offensive and defensive team parameters. AdjO 67.3 | AdjD 55.9 More → 0.738 (#58) AdjO 67.3 | AdjD 55.9
Points Off/Def Recency Points Off/Def Recency Off/def points regression with exponential recency weights. AdjO 64.4 | AdjD 56.8 More → 0.667 (#59) AdjO 64.4 | AdjD 56.8
Core Ensemble Core Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and points off/def. Blend of Elo, BT, Margin, PythLog, PtsOD More → 0.805 (#51) Blend of Elo, BT, Margin, PythLog, PtsOD
Recency Ensemble Recency Ensemble Equal-logit blend of Elo, recency BT, recency margin, log-adjusted pyth, and recency points off/def. Blend of Elo, BT, Margin, PythLog, PtsOD More → 0.794 (#51) Blend of Elo, BT, Margin, PythLog, PtsOD
Dynamic Bradley-Terry Dynamic Bradley-Terry Time-evolving paired-comparison model with latent team strength drift. RD 118 | GP 32 More → 1260 (#36) RD 118 | GP 32

2015 Schedule & Results

Date Vs/At Opponent Result Score
2014-11-14 @ Murray State Racers W 111 - 60
2014-11-17 vs Wofford Terriers W 84 - 37
2014-11-20 vs Detroit Mercy Titans W 60 - 57
2014-11-25 @ Northern Kentucky Norse W 77 - 38
2014-11-30 vs Manhattan Jaspers W 82 - 58
2014-12-03 vs Morehead State Eagles W 87 - 67
2014-12-06 vs East Carolina Pirates L 68 - 76
2014-12-15 vs James Madison Dukes L 62 - 69
2014-12-19 vs La Salle Explorers W 74 - 63
2014-12-20 vs Massachusetts Minutewomen W 59 - 52
2014-12-29 vs Cleveland State Vikings W 71 - 64
2015-01-03 @ Buffalo Bulls W 61 - 50
2015-01-07 @ Western Michigan Broncos L 51 - 61
2015-01-10 vs Toledo Rockets W 65 - 58
2015-01-14 @ Eastern Michigan Eagles W 82 - 59
2015-01-17 vs Central Michigan Chippewas W 71 - 51
2015-01-21 vs Northern Illinois Huskies W 67 - 40
2015-01-24 @ Ball State Cardinals W 60 - 53
2015-01-28 vs Akron Zips W 72 - 60
2015-01-31 @ Central Michigan Chippewas W 74 - 66
2015-02-07 vs Kent State Golden Flashes W 58 - 44
2015-02-11 @ Bowling Green Falcons W 71 - 46
2015-02-14 @ Miami (OH) RedHawks W 67 - 45
2015-02-18 vs Eastern Michigan Eagles L 61 - 73
2015-02-21 @ Akron Zips W 71 - 55
2015-02-25 vs Buffalo Bulls W 78 - 70
2015-02-28 vs Bowling Green Falcons W 67 - 47
2015-03-04 @ Kent State Golden Flashes W 69 - 56
2015-03-07 vs Miami (OH) RedHawks W 75 - 60
2015-03-13 vs Buffalo Bulls W 63 - 55
2015-03-14 vs Eastern Michigan Eagles W 60 - 44
2015-03-21 @ Arizona State Sun Devils L 55 - 74

2015 Roster

Minutes by Position

Each player's share of the team's minutes per game (season minutes over the roster's), placed by position, so every column is one game's minutes. Use the labels or legend to isolate how each player absorbs guard-to-big minutes.

Player Pos GP MIN PTS REB AST STL BLK TO FGA Numbers PM PM GP PM/G PM/40 FG% 3P% FT% RAPM TS% eFG%
K. Black K. Black G 2 29.5 18.5 3.5 2.0 1.0 1.0 2.5 14.0 9.5 211 20 10.6 16.9 39.3 36.8 100.0 3.43 58.7 51.8
Q. Lampkins Q. Lampkins G 2 34.5 9.5 6.0 3.0 1.5 1.0 3.5 9.0 8.5 161 20 8.1 12.4 33.3 0.0 53.8 0.08 40.1 33.3
J. Peppers J. Peppers - 2 36.5 8.5 2.0 2.5 1.5 0.0 2.0 7.0 5.5 159 20 8.0 11.7 35.7 45.5 100.0 -0.5 57.1 53.6
L. Baldwin L. Baldwin F 2 26.0 7.5 3.5 0.5 1.5 2.0 0.5 6.5 8.0 170 20 8.5 16.9 46.2 42.9 0 2.73 57.7 57.7
K. Yelle K. Yelle - 2 24.5 6.5 3.0 2.0 0.5 0.0 1.5 5.5 5.0 158 20 7.9 15.7 54.5 25.0 0 2.43 59.1 59.1
J. Weatherspoon J. Weatherspoon F 2 14.0 3.0 4.0 1.0 0.5 1.5 1.5 1.5 7.0 68 18 3.8 10.5 66.7 0 50.0 1.02 63.0 66.7
M. Harris M. Harris G 2 9.5 2.5 3.0 0.5 0.5 0.0 2.5 2.5 1.5 36 17 2.1 7.3 40.0 50.0 0 -2.21 50.0 50.0
Y. Jenkins Y. Jenkins G 2 16.0 1.5 1.5 2.0 0.0 0.0 0.5 4.0 0.5 101 19 5.3 13.5 12.5 25.0 0 0.56 18.8 18.8
H. Boesinger H. Boesinger F 2 9.0 0.0 3.0 0.5 0.0 0.0 1.0 2.0 0.5 107 20 5.3 14.2 0.0 0.0 0.0 1.51 0.0 0.0
T. Stinson T. Stinson F 1 1.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 45 14 3.2 19.2 0 0 0 0.52 0 0

Numbers/Game vs RAPM

X-axis = Numbers/Game (PTS+REB+AST+STL+BLK-TO-FGA), Y-axis = RAPM.

Advanced: Numbers = PTS+REB+AST+STL+BLK-TO-FGA, PM = total +/-, PM/G = per game, PM/40 = per 40 minutes, RAPM = Regularized Adj Plus-Minus, TS% = True Shooting, eFG% = Effective FG