FanPost

Hoegher's 2016 Previews: NORTHWESTERN

It's hot as the dickens here in Wisconsin, which I am not a fan of. The fiancee gripes about our air conditioning keeping the apartment too cold, but in my opinion: put on a dang sweater. I can only strip off so much before indecency and/or flaying occurs.

More information can be found here: [OTE PRIMER], [DROPBOX]

PREVIOUS ACHIEVEMENTS

Overall Ratings

Off/Def Ratings

W%/Luck Ratings

RECORD COMPARISON, 2006-2015

Tm Rk Gms W L T W%
5 219 159 60 0 73%
10 201 106 95 0 53%
15 173 81 92 0 47%
20 190 67 123 0 35%
25 163 50 113 0 31%
30 162 36 126 0 22%
35 156 38 118 0 24%
40 160 31 129 0 19%
45 142 22 120 0 15%
50 140 17 123 0 12%
55 155 26 129 0 17%
60 135 12 123 0 9%
65 134 17 117 0 13%
70 111 7 104 0 6%
75 121 7 114 0 6%
80 110 6 104 0 5%
85 121 7 114 0 6%
90 116 2 114 0 2%
95 102 1 101 0 1%
100 90 0 90 0 0%
Avg Gms W L T W%
62.8 25 6 19 0 24%

Record vs Top 25

Lo Hi Gms W L T W% +/-
99% 100% 3 3 0 0 100% +0.0
90% 99% 19 18 1 0 95% -0.2
80% 90% 7 5 2 0 71% -0.9
70% 80% 13 12 1 0 92% +2.1
60% 70% 12 9 3 0 75% +1.2
50% 60% 14 6 8 0 43% -1.6
40% 50% 5 2 3 0 40% -0.3
30% 40% 8 3 5 0 38% +0.3
20% 30% 10 2 8 0 20% -0.4
10% 20% 18 7 11 0 39% +4.7
0% 10% 17 3 14 0 18% +2.2
Close Gms 50 31 19 0 62% +6.6

Win Lk Comparison

FUTURE ENDEAVORS

Conf Record C-Rec Tot Rat rk Adj Rat rk Res Rat rk
B10-West 0-0 0-0 0.13 51 0.10 56 0.48 39
# Tms Prj Rec Prj C-Rec Adj Off rk Adj Def rk Prj SOS rk
129 6-6 4-5 0.94 87 0.85 32 0.17 52
Perf W 1 Loss Bowl Ret Off rk Ret Def rk Rec 3yr rk
0.0% 0.1% 63.1% 6 74 5 96 84.74 39

Gm Wk Date H/V Opponent Opp Rk FCS C-Gm Prj Lk
1 2 09/03 H WesternMichigan 84 ~ ~ 67%
2 3 09/10 H Illinois State 130 Y ~ 98%
3 4 09/17 H Duke 62 ~ ~ 56%
4 5 09/24 H Nebraska 39 ~ Y 38%
5 6 10/01 V Iowa 31 ~ Y 34%
6 8 10/15 V MichiganState 10 ~ Y 20%
7 9 10/22 H Indiana 89 ~ Y 68%
8 10 10/29 V OhioState 3 ~ Y 12%
9 11 11/05 H Wisconsin 32 ~ Y 36%
10 12 11/12 V Purdue 70 ~ Y 60%
11 13 11/19 V Minnesota 44 ~ Y 42%
12 14 11/26 H Illinois 92 ~ Y 70%
Opp Rk Team B10 Avg Opp %ile
Top 12 2 1.6 90%
Top 25 2 2.3 80%
Top 51 6 6.0 60%
Bot 25 1 1.3 20%

One of the things I've been trying to highlight during these low-quality previews is a team's record in close games (defined as games with a final margin of 7-pts or less). It's more-or-less accepted wisdom that close games lend themselves to more danger in the result, since it is harder to lose by virtue of a missed field goal when you are already up 21 pts. Generally, the rule-of-thumb is that teams should go 0.500 in the close games they find themselves in, and (while that can be a bit simplistic) justified skepticism can be given toward those teams that far outpace that assumption. Given that it is justNorthwestern week, this is where I note that they went 5-0 in close games during the 2015 season and got apple-cored in their three losses (including the bowl game). That bowl game loss was to Tennessee, a four-loss team that went 2-4 in close games. Just putting that out there for y'all to chew on.

While the 0.500 assumption meets the "eh, good enough" threshold to which I usually aspire, I've tried something a bit different when looking at close games and W/L records. Let's be honest, when Ohio State found themselves in a close games against Indiana and their backup QB, most of us were still betting on the Buckeyes. Putting themselves in that close game territory certainly gave them less room for error (see: pass-interference in the end-zone that went uncalled), but they're still the better team. We'd still expect them to win most of the time.

So consider a game where one team is a 7-pt favorite. I'd say they're probably 70% likely to win (and considering historical Vegas results, that's about right). But that's considering all results, including the 59-0 blowouts (as an example). Limiting the results to those that would be considered close (7-pts or less, in this case), the odds are a bit more compressed, and given a large enough sample size we can come up with a decent model for comparison. Below is a model of how we might apply this (using game results since 1990):

Since a team favored by 30-pts doesn't usually find itself in a close game, the data ges a little wonky at the edges. But we still get a decent enough picture of how to model "close game win likelihood." In case you didn't read the primer above (and I know you didn't, it's okay), the model we're using is a logistic model, using the following form:

W-Lk = 1/(1 + exp(-cf*ExpMOV))

A smaller coefficient lends itself to a flatter curve, hence the relative values above.