NCAA Division 1A Football

Copyright 2004-2016, Paul Kislanko

Analysis Breaks down the computer ranknigs listed on Kenneth Massey's College Football Ratings Comparison pageas ranked ballots using a variety of vote-counting methods.
Top 25 Borda Majority Consensus Pairwise Matrix Correlations Conference Ranks Weighted Violations
Majority Consensus History
Playoff Approval Playoff Watch List Opponents' Rank Distribution
David Wilson's Rankings List describes the rating systems in terms of their attributes.
The 2016 Schedules (July 4, 2016)
The annual "Things should be better than this" whine from someone who remembers the brief period when they were.
Last update 9/2/2016 to update the pre-season computer rankings used to value game-quality.
D1A Schedule Topology part 2 (July 10, 2016)
The games that contribute the most to rankings accuracy/connecting the field.
The Ratings Field (July 17, 2016)
Applies "how far" and "how many" metrics to the games graph I will use to determine ISR and ISOV ratings.
Ratings Trends (October 6, 2016)
Temporal correlations
Rating Trends (October 11, 2016)
The same analysis applied to all ratings as was to the Majority Consensus rating.
How Predictive? (October 17, 2016)
Expectations versus Realities
Week Eight results. Week 10 Week 11 Week 12 Week 13 Week 14 Week 15+Bowls D1 Championships
Playoff Watch List (October 25, 2016)
Who might be in?
The Smith Set and Bad Loss Index (November 10, 2016)
An expanded look at the "watch list"
Surfing the Directed Games Graph (November 17, 2016)
A Good Win Index?
Index to team and conference schedules
Consolidated Schedules and Results
This is a consolidated and indexed version of Dr. Peter Wolfe's schedules and scores pages.
Division 1A (Post-Season)
Division 1AA (Post-Season)
Division 2 (Post-Season)
Division 3 (Post-Season)
NAIA (Post-Season)


Interdivisional Results with scoring analysis

Division 1 schedule by week
Interconference results for FBS Conferences
Upcoming FBS v FBS games sorted by Rank-Based Interest Factor

Division and Conference Affiliations
For all teams, based upon Dr. Wolfe's NCAA and NAIA Divisional and Conference Affiliations page.
College Football Data Warehouse
Where to go when you get old enough that your memory fails or you're too young to remember what happened before you were born.
Well, it was before it adopted advertising practices that even disrespectable websites gave up on long ago. You have to be desperate to use it now.
Splits and situational stats - inside box scores
Boyd Nation's Iterative Strength Rating
Iterated Strength of Victory (ISR with SOV-based adjustments for each game)
Normalized Scoring Stats
Scoring data adjusted by opponents' strength
Directed Games Graph Metrics
Weighted Win Paths
See the WWP definition
The below are not "ratings" per se, but count and make visible all of the shortest "A beat B beat C beat ..." (A⇒) chains in the current games graph.
Second Order Winning Percentage
% of teams that the given team has a shorter or stronger A⇒... chain to other teams than the other way around. (D1A Only D1AA Only D2 D3 NAIA)
by the length and strength of the A⇒ paths to other teams. (D1A Only D1AA Only D2 D3 NAIA)
Often people who are not familiar with the nature and limitations of statistical methods tend to expect too much of the rating system. Ratings provide merely a comparison of performances, no more and no less. The measurement of the performance of an individual is always made relative to the performance of his competitors and both the performance of the player and of his opponents are subject to much the same random fluctuations. The measurement of the rating of an individual might well be compared with the measurement of the position of a cork bobbing up and down on the surface of agitated water with a yard stick tied to a rope and which is swaying in the wind.
Arpad Elo in Chess Life, 1962
In theory, there is no difference between theory and practice; In practice, there is. — Chuck Reid

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