NCAA TOURNAMENT: SEEDING THE TEAMS, PART 2

In part 1 of this series, I showed a history-based process for seeding teams into the NCAA Tournament bracket:  pods of 4 #1 seeds, 4 #2 seeds, 4 #3 seeds, and 4 #4 seeds; a pod of additional automatic qualifiers and at large selections to bring the total at large selections to 19; and the remaining automatic qualifiers.  Please refer to part 1 for how the process works.

Using on that process, based on games played through April 11, I come up with the following initial array of teams (not in order within their pods).  (To rank teams within their conferences, for the conferences that played in the Fall, I used the average of their conference regular season and conference tournament finishing positions; and for the conferences that did not play in the Fall, I used their current conference ranks based average points per game played, which means I have disregarded what has happened so far in their conference tournaments.  Once the season is done, I will re-rank them using the system I used for the Fall-playing conferences.  Bold face = actual or most likely automatic qualifier.)

#1 seeds:

ACC, Florida State

ACC, North Carolina

Pac 12, UCLA

SEC, Arkansas

#2 seeds:

ACC, Virginia

Big 10, Penn State

Big 12, TCU

Pac 12, Southern California

#3 seeds:

ACC, Duke

SEC, Texas A&M

SEC, South Carolina

West Coast, Santa Clara

#4 seeds:

ACC, Clemson

Big 10: Ohio State

Big 12: West Virginia

Pac 12: Washington

Pod of most likely at large selections (from the non-automatic qualifiers, three will have to be removed to get the total number of at large selections down to 19):

ACC, Louisville

ACC, Notre Dame

American, South Florida

American, Memphis

Big East, Georgetown 

Big 10, Illinois

Big 10, Indiana

Big 12, Oklahoma State

Big 12, Kansas

Pac 12, Arizona State

Pac 12, Stanford

SEC, Vanderbilt

SEC, Tennessee

West Coast, BYU

Pod of longer shots to displace other potential at large selections:

ACC, Virginia Tech

ACC, Wake Forest

American, SMU

Big East, Butler

Big East, Connecticut

Big 10, Wisconsin

Big 10, Minnesota

Big 10, Rutgers

Big 10, Michigan

Big 12, Baylor

Big 12, Texas

Pac 12, Colorado

Pac 12, Washington State

SEC, Missouri

SEC, Auburn

SEC, Mississippi

West Coast, Pepperdine

Atlantic 10, St. Louis  (included on basis of win over Arkansas)

Conference USA, Rice (included on basis of win over Texas A&M)

The above is my history-based initial array of teams.  Starting there, I need to remove three of the non-automatic qualifiers from the most likely at large selection group and, after that, I need to review the longer shot group to see if I should pick some of them to replace teams remaining in the most likely at large selection group.  To do this, I use the following table.  This table, and the next one, likely will not be readable as you first see it.  To see it clearly, simply click on the table.  That should bring up a readable version.  Then, to return to this article, simply on the black area to either side of the table.

In this table, for each team on the list, I show its numbers of wins, ties, and losses against the initial #1, #2, #3, and #4 seeds, against the most likely at large selection teams (group 5), against the longer shot at large selection teams (group 6), and against other teams it played (group 7).  Then, on the table, I have highlighted in green good results and in orange poor results, in relation to the position the team is competing for.

Using the table as highlighted, I then decided which three teams to remove from the likely at large selection group in order to bring the number of at large selections to 19.  I removed Louisville, Indiana, and Illinois.

Next, I compared teams on the longer shot list to the remaining teams on the likely at large selection list and made two more changes:  I removed Memphis and Kansas from the likely list and added Rutgers and Colorado from the longer shot list.

I then re-created the above table, but with the changes I just made:

I reviewed this table to see if I should make further changes.  Although Notre Dame is a close call to retain as an at large selection, I decided to leave it with a selection.  However, if St. Louis turns out not to be an automatic qualifier, I probably would give it an at large selection and would remove Notre Dame from that group.  I also would consider Rice, although its chances would be smaller.

Once the selections are set, I could use the above table to place in exact order some or possibly even all of the 16 #1 to #4 seeded teams and the additional 11 teams.  Some of the ordering of teams would be clear and some of it would be speculative.  Since the season is not yet over, I am not going to try to do that this week.  I may try to do it once the coming weekend’s final results are in.

For the remaining automatic qualifiers that are not covered by the above tables but that will be in the Tournament, I have shown in Part 1 how I would order them for seeding purposes.

Observation.  The point of this is not to show what the Tournament at large selections and seeding should be.  Rather, it is to show a workable system for making the at large selections and doing the seeding.  The system is based on historic and current-year data, allowing for the exercise of some discretion but with pretty clearly defined boundaries.  I believe, the system would produce a relatively credible and defensible bracket given the unique circumstances of this year.

NCAA TOURNAMENT: SEEDING THE TEAMS, PART 1

 In previous articles, I wrote about how the Committee might make at large selections for the NCAA Tournament, if the RPI is not usable.  In those articles, I identified three history-based tiers of teams:

Tier 1 for the most likely Top 16 seeded teams, consisting of automatic qualifiers and at large selections;

Tier 2 for the 14 most likely next teams, consisting of automatic qualifiers and potential competitors for at large selections; and

Tier 3 for next level automatic qualifiers and longer-shot competitors for at large selections.

Based on bracket history since 2013, I assigned tier positions to conferences as shown in this table:

In this article, I will write about how the Committee might seed teams.  And, since the Tournament will be at one site this year, I will cover how the Committee might seed all of the 48 teams in the bracket (with some in pods).

Tier 1 - Top 16 Teams

The above table, in Tier 1, shows the history-based distribution of the 16 seeded teams among conferences:  5 ACC teams, 3 Pac 12 teams, 3 SEC teams, 2 Big 10 teams, 2 Big 12 teams, and 1 West Coast team.  The table, however, does not put the teams in seed order.  The Committee practice has been to have four pods of seeds: four #1s, four #2s, four #3s, and four #4s.  Is there a legitimate way to do that this year?

Here is a table with the history of the #1 seeds, by conference, for the period since 2013;

The table shows the distribution of the #1 seeds each year since 2013, by conference.  The Average column shows the average per year.  Using rounding of the averages, the Awarded column shows the distribution of the #1 seeds most consistent with history:  2 to the ACC, 1 to the Pac 12, and 1 to the SEC.  Thus under a history-based distribution the tentative #1 seeds go to the #1 and #2 ACC teams and the #1 Pac 12 and SEC teams.

Here is a mostly similar table for the #2 seeds:

This table has the same format as the #1 seed table, but adds the two next-to-last columns on the right.  In the Carry Forward column, I have carried forward from the #1 seed table the difference between a conference’s Average #1 seeds and its Awarded seeds.  Thus, for example, the Big East had an Average of 0.1 #1 seeds but did not get a #1 seed, so I carried forward 0.1 to add to its #2 seed Average.  Conversely, the SEC had an Average of 0.6 #1 and got 1 #1 seed, so I carried forward -0.4 to subtract from its #2 seed Average.  The Net column shows the total of the #2 seed Average and the Carry Forward amount.  Based on the Net amounts, the Awarded column shows the history-based distribution of the tentative #2 seeds:  1 each to the ACC, Big 10, Big 12, and Pac 12.  Given the #1 seed assignments, these would be the the #3 ACC team, the #2 Pac 12 team, and the #1 Big 10 and Big 12 teams.

Here is a similar table for the #3 seeds:

The Awarded column shows the history-based distribution of the tentative #3 seeds:  2 to the SEC and 1 each to the ACC and West Coast.  Given the #1 and 2 seed assignments, these would be the the #2 and #3 SEC teams, the #4 ACC team, and the #1 West Coast team.

Here is a similar table for the #4 seeds:

The Awarded column shows the history-based distribution of the tentative #4 seeds:  1 each to the ACC, Big 10, Big 12, and Pac 12.  Given the #1 through #3 seed assignments, these would be the the #5 ACC team, the #2 Big 10 team, the #2 Big 12 team, and the #3 Pac 12 team.

The following table summarizes the tentative assignments of pod positions, by conference (not in order within the pods):

I do not see legitimately being able to put all four of the teams in a pod in order.  The reason for this is simple.  The Big 10 teams have played only conference games.  Therefore, there is no way based on actual game results this season to compare Big 10 teams to the other teams in their seed pods.  Further, the Pac 12 and West Coast teams combined have played a grand total of 4 games outside of the west region, with only 1 against a non-west conference that has teams in the seed group (BYU defeated Missouri).  Therefore, there is no way based on actual game results to compare Pac 12 and West Coast teams to the other teams in their seed pods.  Perhaps conference history and actual game results will support putting some teams in each pod in order, but that probably is the best that will be possible from a strict data-based perspective.

Tier 2 - Most Likely Candidates for Unseeded At Large Positions

Of the 16 Tier 1 seeded teams, 5 are likely to be automatic qualifiers and 11 at large selections.  Of the 14 Tier 2 teams, 3 are likely to be automatic qualifiers and 11 are potential at large selections.  With Tier 1 having 11 at large selections, this means it will be necessary to reduce Tier 2’s 11 potential at large selections down to 8, to get to the total of 19 at large selections for the Tournament.

To get from 11 Tier 2 potential at large selections down to 8, if the RPI is not usable this means the selection method must use the other NCAA-mandated factors to do it: head to head results, results against common opponents, results against highly ranked opponents (meaning, this year, against Tier 1 through Tier 3 opponents), and recent results.  It will be a matter of doing the best one can with a limited set of data.

After eliminating three Tier 2 teams, what about trying to put the remaining Tier 2 automatic qualifiers and at large selection teams in seed order?  For the same reasons that the Committee will not be able to put all the teams within the seed pods in order, it will not be able to put all of the Tier 2 automatic qualifiers and selected teams in order.  It may be able to put some in order in relation to each other, but not all of them.  This also will be true if the Committee drops some teams from Tier 2 and replaces them with Tier 3 teams.

Thus there would be pods of teams in seed order as follows:

#1 seeds: 4 teams, in order only to the extent justified by actual data

#2 seeds: 4 teams, in order only to the extent justified by actual data

#3 seeds: 4 teams, in order only to the extent justified by actual data

#4 seeds: 4 teams, in order only to the extent justified by actual data

Tier 2 automatic qualifiers and unseeded at large selections: 11 teams, in order only to the extent justified by actual data

Remaining Automatic Qualifiers

Finally, after identifying and seeding either individually or in pods the 27 Tier 1 and Tier 2 teams that will be in the bracket, there will be 21 automatic qualifiers to place in the bracket (assuming none of them have moved up into Tier 1 or 2 as part of the process).  What about assigning seed positions to these teams?  A reasonable way to do it is to base the order on the historic ranks of the automatic qualifiers from each conference.  Here is a table that shows what I mean:

This table shows the rank of each conference’s automatic qualifier for each year since 2013.  The Average column shows the average ranks of the conferences’ automatic qualifiers.  The Rank by AQ column shows the rank of each conference in terms of the average rank of its automatic qualifiers.  (Interestingly, as you can see, there is a big drop from the first eight conferences - the highlighted ones in earlier articles - to the remaining conferences.)

For the automatic qualifiers other than those from the first eight conferences (all of which are in Tier 1 or 2), a history-based way to rank them would be to follow the order in the table.  This would assign tentative rank positions to the 21 remaining conference automatic qualifiers as follows:

#28  Conference USA

#29  Colonial

#30  Patriot

#31  Sun Belt

#32  Atlantic 10

#33  Southern

#34  Atlantic Sun

#35  Metro Atlantic

#36  Mid American

#37  Mountain West

#38  Big South

#39  Horizon

#40  Missouri Valley

#41  Southland

#42  WAC

#43  Ohio Valley

#44  Big Sky

#45  America East

#46  Summit

#47  Northeast

#48  Southwestern

Final Steps

The above creates an overall history-based assigned conference position framework for the bracket.  This season’s actual in-conference results then would be the basis for selecting specific teams to fill the assigned conference positions.  This would create a tentative bracket with teams seeded either individually or in pods from top to bottom.

Actual game results data from this season, however, might justify altering any of the tentative seed assignments.  Looking for and making results-based adjustments thus would be the final step of the process.

As one example of a possible results-based adjustment, if St. Louis is the Atlantic 10 conference champion, it has a win over Arkansas.  If Arkansas nevertheless gets a #1 seed, the Committee might elevate St. Louis a significant distance on the seed list.  Indeed, if St. Louis by chance is not the Atlantic 10 automatic qualifier, the Arkansas win might justify the Committee moving St. Louis all the way from not in any of the three tiers into consideration for an at large selection.

This week, I am not discussing which teams will fill assigned conference positions (I will do that elsewhere strictly for fun).  I likewise am not looking at actual game results to see changes they might justify to the tentative bracket.  Next week, I will add those step to show how the process, in its entirety, will work.

NCAA TOURNAMENT: KEEPING THE RPI HONEST, PART 7

 In Parts 1 and 2 of this series, I described a test to see if this year’s RPI will be usable.  The test compares the Top 60 and Top 30 in the RPI rankings to baselines for the Top 60 and Top 30 derived from 2013 to the present.  It looks at two groups of conferences: a highlighted group consisting of the eight conferences that have had at least one team in the Top 60 every year since 2013 (ACC, American, Big East, Big 10, Big 12, Pac 12, SEC, West Coast) and a not-highlighted group consisting of all the other conferences.  The test shows the average number of teams and the high and low number of teams each group has had in the Top 60 and Top 30 since 2013.  It asks the question of how the numbers for the RPI ranks this year compare to the test period numbers.

Top 60 Test:  The RPI Top 60 should include roughly 49 teams from the highlighted conferences and 11 teams from the not-highlighted conferences.  The actual numbers can range on either side of these test numbers, but 45 teams should be the minimum from the highlighted group and 15 the maximum from the not-highlighted group.

Top 30 Test:  The RPI Top 30 should include roughly 28 teams from the highlighted conferences and 2 teams from the not-highlighted conferences.  The actual numbers can range on either side of these test numbers, but 27 teams should be the minimum from the highlighted group and 3 the maximum from the not-highlighted group.

Here are three different looks at how these tests apply to the current season, for games played through Sunday, April 4.

 ACTUAL RPI, TO DATE

The following table shows conference representation in the RPI Top 60 and Top 30, plus totals for the highlighted and not-highlighted conferences at the bottom.  The left portion of the table is based on actual RPI ranks, to date, and the right portion of the table has the historic baseline test numbers.

The following table is similar but for regional playing pools:

ACTUAL RPI, TO DATE, CONFERENCES PLAYING SOME NON-CONFERENCE GAMES

Here are similar tables, but for this year’s RPI Top 60 and Top 30 if I consider only conferences playing at least some non-conference games.  I include these tables because it is indisputable that for conferences that play no non-conference games, the RPI cannot rank their teams in relation to teams from other conferences.

SIMULATED RPI, USING ACTUAL RESULTS TO DATE

Here are similar tables, but based on the entire season, including conference tournaments.  Their underlying data are the actual results of games played through April 4 plus simulated results of future games.  These should give a pretty reliable picture of what the end-of-season numbers will look like.

COMMENT

As the above tables show, the RPI is going to greatly underrate teams from stronger conferences and regions and greatly overrate teams from weaker conferences and regions.  This is due to teams not playing enough total games, not playing enough non-conference games, and not playing enough out-of-region games.  Further, it is true even if one considers only teams from conferences that are allowing members to play non-conference games.

As we get closer to the end of the season, this does not seem to be changing.

NCAA TOURNAMENT: HOW IN THE WORLD IS THE COMMITTEE GOING TO MAKE AT LARGE SELECTIONS? PART 4 - AS OF MARCH 28

In the three preceding articles of this series, I discussed the problems with the RPI this year and an alternative way for the Committee to make its 19 at large selections for the NCAA Tournament without using the RPI.  The alternative goes through the following steps:

Allocates the 16 seed positions -- Tier 1 -- to conferences based on the average numbers of seeds they have had over the years since 2013 (the year of completion of the most recent major conference realignment).

For the next 16 positions -- Tier 2 -- allocates them to conferences based on the average number of first round home games their unseeded teams have had over the years since 2013.  (This results in more teams in Tiers 1 and 2 combined than will be needed to fill the 19 at large positions, even after taking Tier 1 and 2 automatic qualifiers into consideration.)

Creates a third group -- Tier 3 -- allocated to conferences to bring them up to the maximum number of teams they have had either seeded or unseeded but with first round home games over the years since 2013 -- as distinguished from the average number of teams.

With the three tiers in place with their assigned conference slots, the next step is to do an initial fill of the slots with teams from the conferences.  For each conference, the basis for initially filling the slots is team actual in-conference results during the current season.  To do this initial fill, I assign each team a rank in its conference, based on where it finished in its conference regular season and where it finished in its conference tournament, with those two finishing positions weighted 50-50.  If the conference does not have a tournament, then I assign the team the rank it had in its conference regular-season competition.  Due to there being so many canceled games this season, I do the conference regular season rankings based on points per game.  Once I have the assigned ranks of teams within their conferences, I then fill the conference tier slots starting with Tier 1, then Tier 2, then Tier 3.

I then look to see if any Tier 3 teams should trade places with any Tier 2 teams.  Any replacement must be based exclusively on team results this season.  After completing that step, I look to see if any Tier 2 teams should trade places with any Tier 1 teams, again based exclusively on team results this season.

When I have finalized Tiers 1 and 2, then the Tier 1 teams will be the 16 seeded teams.  I count the number of Tier 1 teams that are not automatic qualifers and subract that number from 19 to tell me the number of automatic qualifiers that will come from Tier 2.  Most likely, this will be 3 fewer than the number of Tier 2 teams that are not themselves automatic qualifiers.  This means I will have to eliminate 3 of the Tier 2 teams.  This elimination must be based exclusively on team results this season.

When I am done, I have selected 19 at large teams and they, together with the 29 automatic qualifiers, will make up the tournament field.

This process, applied to the actual results of games played through Sunday, March 28, combined with simulated results for all games not yet played including simulated conference tournaments, produces the following initial tiers of teams.  As future actual results replace simulated results, the teams in the tiers will change.  (The simulated results are right roughly two-thirds of the time.)  Thus it is best to view the current three tiers as illustrating an historically appropriate distribution of slots among conferences, rather than focusing on the particular teams currently in those slots.  In addition, since these are only the initial tiers, they would be subject to the review and potential trading of teams between tiers process I have described above.  The yellow highlighted teams are actual or simulated automatic qualifiers.

I will update this table weekly over the closing weeks of the season.

NCAA TOURNAMENT: KEEPING THE RPI HONEST, PART 6

In Parts 1 and 2 of this series, I described a test to see if this year’s RPI will be usable.  The test compares the Top 60 and Top 30 in the RPI rankings to baselines for the Top 60 and Top 30 derived from 2013 to the present.  It looks at two groups of conferences: a highlighted group consisting of the eight conferences that have had at least one team in the Top 60 every year since 2013 (ACC, American, Big East, Big 10, Big 12, Pac 12, SEC, West Coast) and a not-highlighted group consisting of all the other conferences.  The test shows the average number of teams and the high and low number of teams each group has had in the Top 60 and Top 30 since 2013.  It asks the question of how the numbers for the RPI ranks this year compare to the test period numbers.

Top 60 Test:  The RPI Top 60 should include roughly 49 teams from the highlighted conferences and 11 teams from the not-highlighted conferences.  The actual numbers can range on either side of these test numbers, but 45 teams should be the minimum from the highlighted group and 15 the maximum from the not-highlighted group.

Top 30 Test:  The RPI Top 30 should include roughly 28 teams from the highlighted conferences and 2 teams from the not-highlighted conferences.  The actual numbers can range on either side of these test numbers, but 27 teams should be the minimum from the highlighted group and 3 the maximum from the not-highlighted group.

Here are three different looks at how these tests apply to the current season, for games played through Sunday, March 28.

 ACTUAL RPI, TO DATE

The following table shows conference representation in the RPI Top 60 and Top 30, plus totals for the highlighted and not-highlighted conferences at the bottom.  The left portion of the table is based on actual RPI ranks, to date, and the right portion of the table has the historic baseline test numbers.

The following table is similar but for regional playing pools:

ACTUAL RPI, TO DATE, CONFERENCES PLAYING SOME NON-CONFERENCE GAMES

Here are similar tables, but for this year’s RPI Top 60 and Top 30 if I consider only conferences playing at least some non-conference games.  I include these tables because it is indisputable that for conferences that play no non-conference games, the RPI cannot rank their teams in relation to teams from other conferences.

SIMULATED RPI, USING ACTUAL RESULTS TO DATE

Here are similar tables, but based on the entire season, including conference tournaments.  Their underlying data are the actual results of games played through March 28 plus simulated results of future games.  These should give a pretty reliable picture of what the end-of-season numbers will look like.

COMMENT

As the above tables show, the RPI is going to greatly underrate teams from stronger conferences and regions and greatly overrate teams from weaker conferences and regions.  This is due to teams not playing enough total games, not playing enough non-conference games, and not playing enough out-of-region games.  Further, it is true even if one considers only teams from conferences that are allowing members to play non-conference games.

NCAA TOURNAMENT: HOW IN THE WORLD IS THE COMMITTEE GOING TO MAKE AT LARGE SELECTIONS? PART 1 - RPI OR NO RPI?

The Women’s Soccer Committee will face major challenges this year in making the 19 at large selections for the NCAA Tournament.

Two NCAA requirements that apply to normal years may create big problems this year:

Policy Against Using Past Years’ Performance.  The NCAA has a policy that the Committee cannot consider past years’ performance in making at large selections.  Rather, selections must be based only on teams’ performance this year.

Use of the RPI.  The only statistical rating system the Committee is allowed to consider is the RPI.  In addition, it cannot consider polls.

These requirements create a problem: The RPI depends on teams playing enough games and sufficient proportions of non-conference and out-of-region games.  Teams this year likely will play neither enough games nor sufficient proportions of non-conference and out-of-region games for the RPI to work.  If that happens, what is the Committee to do?

Here are some thoughts on this question:

Conference-Only Conferences.  Seven conferences are playing conference-only schedules:  Big Ten, Horizon, Metro Atlantic, Mid American, Mountain West, Ohio Valley, and Patriot (except for Navy, which played three Fall non-conference games, 2 against Pittsburgh and 1 against Virginia Tech).  The problem with this is: If a conference has a conference-only schedule, it is impossible for any statistical rating system to rate the conference’s teams in relation to the teams of other conferences.  Thus the RPI rankings for teams from these conferences will be meaningless in relation to the rankings of teams from other conferences.

Given this, if you cannot refer to history, you have no way to know where the teams of a conference-only conference fit in comparison to teams from other conferences.

What if you refer to history regarding this year’s conference-only conferences?

Based on past seasons since 2013, 6 of the 7 conference-only conferences are not strong enough to get any at large selections, as they have gotten no at large selections to the NCAA Tournament: Horizon, Metro Atlantic, Mid American, Mountain West, Ohio Valley, and Patriot.

The Big Ten, however, is different.  Since 2013 it has had a minimum of 5 and a maximum of 11 teams in the RPI Top 60 with an average of 7.7, of which 1 each year has been an automatic qualifier.  And, it has had a minimum of 0 and a maximum of 2 at large teams seeded, with an average of 1, which means it has had these numbers in the Committee’s actual Top 16.

Of course, regarding the conference-only conferences, the Committee could decide: If your conference went conference-only for this season, then you get only your automatic qualifier in the Tournament; you get no at large positions.  The only real alternative would be to decide: We are going to refer to past history; and you will get roughly the number of at large positions that past history indicates is appropriate for your conference.

To summarize for conference-only conferences, the Committee’s dilemma is this:  Either it gives conference-only conferences no at large positions, which will not be consistent with true conference strength so far as the Big Ten is concerned; or it uses past history as its basis for at large selections.

Conferences Playing Non-Conference Opponents.  What about teams from conferences that are playing non-conference opponents?  If you think about them as first having played all their conference games, at that point they will be in the same position as the conference-only conferences as described above.  Then, as you add non-conference games, their ratings and rankings adjust in relation to those of teams from other conferences playing non-conference opponents.  The more non-conference games you add, the more accurate the adjustments.

In a normal season, 56.0% of games are conference games and 44.0% are non-conference.  It would be better if the proportion of non-conference games were higher, but these proportions are workable given that the Committee supplements the RPI with other data-based considerations such as head to head results and results against common opponents.  This year, however, according to the schedule as of March 21, 83.3% of games will be conference and only 16.7% will be non-conference.  Or, limiting consideration to conferences playing non-conference opponents, 78.6% will be conference and 21.4% non-conference.  Thus the opportunity for ratings and ranks to adjust in relation to teams from other conferences will be less than half what it is in a normal year.  This will cause the RPI to greatly underrate teams from strong conferences and overrate teams from weak conferences.

Here again, the Committee could decide that notwithstanding the problem it is going to use the RPI ranks in the at large selection process.  If it does this, however, it is going to end up with at large selections that obiously will be not consistent with true team strength.  Alternatively, the Committee can decide the RPI is not usable and use past history as a basis for allocating at large positions to conferences and then choose teams from each conference based on their performance this year.

Regional Playing Pools.  Based on historical scheduling patterns, the Division I conferences play in four regional playing pools.  They are:

Middle: Horizon, Mid American, Missouri Valley, and Summit

Northeast: America East, Atlantic 10, Big East, Colonial, Metro Atlantic, Northeast, and Patriot [and Ivy]

South: ACC, American, Atlantic Sun, Big South, Big 10, Big 12, Conference USA, Ohio Valley, SEC, Southern, Southland, Southwestern, and Sun Belt

West: Big Sky, Mountain West, Pac 12, WAC, and West Coast [and Big West]

The situation is the same for regions as for conferences.  If you think about regions as first having played all their in-region games, at that point they will be in the same position as the conference-only conferences as described above -- there will be no way to know how each region’s teams rank in relation to teams from other regions.  Then, as you add out-of-region games, a region’s teams’ ratings and rankings adjust in relation to those of teams from other regions.  The more out-of-region games you add, the more accurate the adjustments.

In a normal year, the Middle plays 33.0% of its games out-of-region, the Northeast 17.8%, the South 14.6%, and the West 17.4%  This year, however, based on the schedule as of March 21, the Middle will play 6.0% of its games out-of-region, the Northeast 16.0%, the South 6.9%, and the West 4.4%.  These proportions of out-of-region games are not enough to allow the RPI to rank the teams from any one region in relation to the teams from the other regions.

Here again, the Committee could decide that notwithstanding the problem it is going to use the RPI ranks in the at large selection process.  If it does this, however, it is going to end up with at large selections that are not consistent with true region strength.  Alternatively, the Committee can use past history as a basis for assuring the distribution of at large allocations among regions is appropriate.

If the Committee is going to use past history to be sure it has appropriate conference and region representation in its at large selections, how can it do it?  I will address that in my next article.

NCAA TOURNAMENT: HOW IN THE WORLD IS THE COMMITTEE GOING TO MAKE AT LARGE SELECTIONS? PART 2 - THE TOP 16 TEAMS

In my preceding article, I questioned the Committee’s ability to use the RPI in this year’s at large selection process.  It may have to turn instead to past history to assure appropriate representation of conferences and regions in its selections.  In this article and the next, I will show how the Committee could make its 19 at large selections using past history to set the overall outlines of the bracket and then use specific teams’ performance this year to fill in the details.

Here are the steps the Committee could go through:

Step 1:  Decide on a group of the Top 16 teams.  These will be tentatively seeded teams, subject to changes if appropriate based on the details of this year’s game results.

For each past year, we know the teams that the Committee ranked within the Top 16 because the Committee seeded them.  The following tables shows the conference distribution of the Top 16 -- the seeds -- since 2013. The first table is for seeded automatic qualifiers, the second is for seeded at large teams, and the third combines the seeded automatic qualifiers and at large teams:

In this table, the highlighted conferences are ones that have had at least one at large selection every year since 2013.  As the table shows, on average the highlighted conferences have had roughly 5 automatic qualifiers that are seeded and the other conferences have had roughly none.  As outside limits, one would expect the highlighted conferences to have no fewer than 4 automatic qualifers seeded and no more than 7; and one would expect the other conferences to have at most 1.

As this table shows, on average the highlighted conferences have had roughly 10 to 11 at large teams that are seeded and the other conferences have had none.  As outside limits, one would expect the highlighted conferences to have no fewer than 8 at large teams seeded and no more than 12; and one would expect the other conferences to have none.

 As this table shows, on average the highlighted conferences have had all of the seeds and the other conferences have had none.  At most, the other conferences have had 1 seeded team and that happened only once.  In other words, history indicates one should expect that the Committee’s Top 16 teams all should come from the highlighted conferences, but with possibly one coming from the other conferences.

The above tables show the reasonably expected distributions of at large selections among the highlighted group and not highlighted group of conferences.  In addition, they show the historic distributions among the particular conferences.  For the conferences grouped together as highlighted, the totals are very good representations of what should be the case this year.  For the particular conferences and regions, the totals should be good, though not as good, representations of what should be the case.  This reflects the fact that although individual team strength varies from year to year, conference and region strength changes only slowly over time and highlighted group strength changes, at most, very slowly.

Thus the tables, in addition to providing a very good tentative picture of what the highlighted and not highlighted group representations should be among the 16 seeds, also provide a good tentative picture of what the individual conference representations should be.  With that in mind, here is what the tentative conference representations should be among the 16 seeds (using rounded off numbers from the above tables as needed):

ACC:  1 automatic qualifier plus 4 at large selections, but with the possibility of the at large selections ranging between 2 and 6

Big 10:  1 automatic qualifier plus 1 at large selection, but with the possibility of no automatic qualifier and of the at large selections ranging between 0 and 3

 Big 12:  1 automatic qualifier plus 1 at large selection, but with the possibility of no automatic qualifier and of the at large selections ranging between 0 and 3

Pac 12:  1 automatic qualifer plus 2 at large selections, but with the possibility of the at large selections ranging between 0 and 3

SEC:  1 automatic qualifier plus 2 at large selections, but with the possibility of no automatic qualifier and of the at large selections ranging between 0 and 4

 American:  no automatic qualifier and no at large selection, but with the possibility of 1 automatic qualifer or 1 at at large selection

Big East:  no automatic qualifier and no at large selection as the baseline, but with the possibility of 1 automatic qualifer or 1 at at large selection

 Summit:  no automatic qualifier and no at large selection, but with the possibility of 1 automatic qualifer or 1 at at large selection

West Coast:  1 automatic qualifier or 1 at large selection, but with the possibility of no automatic qualifier and no at large selection

These allocations set the tentative conference representation for the 16 seeds.  The next step is to use this year’s actual in-conference game data to decide which teams from each conference fill its seed slots.  The data to be used come from three sets of games: (a) conference regular season games that count in the conference standings, (b) conference tournament games for the conferences with tournaments, and (c) any other in-conference games.

To illustrate how filling the conference seed slots can work, I will use a simple method to rank teams within their conferences.  The teams already have their in-conference regular season ranks.  For their conference tournament ranks, I will assign the champion a rank of 1, the runner-up a rank of 2, the losing semi-finalists a rank of 3.5 (the average of the #3 and #4 positions), and other tournament participants ranks determined by the same method.  For teams not participating in the tournament, I will assign them tournament ranks the same as their regular season ranks.  I then will average the regular season and tournament ranks to get each team’s tentative rank for NCAA Tournament selection purposes.  I then will review teams’ conference games that were not counting regular season or conference tournament games and make rank changes they indicate are appropriate, if any.

Since the season still is underway, I am going to simulate where teams will be at the end of the season to show how this system would work.  For the simulation I will use the actual results of games played through March 21 and simulated results of games not yet played (including conference tournament games).  This will produce simulated conference regular season standings, conference tournament results, and other conference game results that I will use to fill the team slots allocated to each conference.  The simulated results of games, of course, may turn out to be wrong, so I am doing this only to illustrate how the process will work.  (The simulated results will be right about 2/3 of the time.)  This results in the following 16 tentative seeds (not in seed order), which I am calling the Tier 1 teams:

The yellow highlighted teams are ones that either already are or that my simulation indicates will be conference automatic qualifiers.  These tentative teams for the 16 seed positions and those I identify as automatic qualifiers may change as actual results replace my simulated results.

In addition, while the above baseline is based on history so far as the conferences are concerned, it also ought to be consistent with history in terms of regional playing pools I described in my preceding article.  The following three tables are the same as the three conference tables above, but are for the regional playing pools:

As the last table shows, on average the highlighted (South and West) regions have had 15 or 16 seeds and the other regions (Middle and Northeast) have had 1 or none.  At a minimum the highlighted regions have had 14 seeds and at a maximum the other regions have had 2.  In other words, history indicates one should expect that the Committee’s Top 16 teams will come almost entirely from the South and West playing pools with perhaps 1 and a maximum of 2 coming from the Middle and Northeast pools.

Looking at the tentative Top 16 teams list above, 12 teams are from the South region and 4 from the West.  This is consistent with the above region tables.  The tables suggest that if I were to decide to revise the tentative team list in order to seed a team from the Middle or Northeast region (which would mean from the American, Big East, or Summit conference), it likely should replace one of the teams from the South region rather than from the West.

In my next article, I will discuss the additional steps needed to finalize the seeds and make the remaining at large selections.