July 21,
2009
Proposal for Changes in
Computing RPI - Part 3
 Greg
Van Zant, the head coach at West Virginia University, recently
sent the following recommendation to the NCAA Division I
Baseball Committee to change the formula for calculating the
Ratings Percentage Index (RPI).
The Weighting of
Home Wins and Road Wins
Another problem with the RPI in college baseball
is that it doesn't factor in home field advantage. College
baseball is unique because early in the season the vast majority
of teams from the northern part of the country can not play at
home due to the weather. Northern teams do not choose to play
on the road early in the season, they have to play on the road.
No other NCAA sport has this kind of scheduling inequity.
The home team wins approximately 60% of the time
in Division I Baseball (61% in 2008) because of many factors
such as hitting last, knowledge of the home playing field,
supportive fans, knowledge of the umpires, sleeping at home,
etc. The reasons why the home team wins about 60% of the time
could be listed and debated at length. Regardless, it is a
fact, for whatever reason or reasons, the home team wins roughly
60% of the time.
There is a simple solution to this problem,
mathematically remove the home field advantage from the RPI.
Let me explain.
Let's look at the factors or components of the
current RPI;
1. A team's winning percentage against all the
Division I teams on its schedule. This
is the first 25%
of the RPI. This is where it all starts. If a team is 30-10
against
Division I
competition, the RPI for this team is .750 before the other two
factors of
the RPI adjust
this .750 winning percentage up or down based on the strength of
schedule of the 40
opponents this team played.
2. Average Division I winning percentage of all
your opponents when not playing
you. This is 50% of the RPI. This second
factor rewards a team for playing
opponents that have high winning
percentages.
3. A team's opponents, opponents Division I
winning percentage. This counts 25%
and is an effort to make sure your
opponents legitimately earned their winning
percentage by playing good competition.
Factor #2 has a huge bearing on the final RPI of
each team as it counts for 50% of the total. This factor is
based on the winning percentage of your opponents. Factors #1
and #3 also are based on winning percentage. Obviously, winning
percentage is very important.
Suppose we had two identical college baseball
teams playing each other in a 20-game series. These two
hypothetical teams, which I will name Team A and Team B, are
identical in every aspect. This 20-game series will be played
on a neutral field and each team will be the home team 10
times. Over time, each team will win half of the games because
everything is equal. Therefore, each team's win-loss record
will be 10-10.
Now, let's take the same two identical teams and
play all 20 games of the series at one of the team's home
ballparks, Team A's for example. Since over time it has been
shown that the home team wins 60% of the time in college
baseball, the home team will now win 60% of the time in this
series and Team A will finish with a 12-8 record. The visiting
team, Team B, will finish 8-12. Two identical teams but vastly
different win loss percentages simply because the 20-game series
was not played fairly, (i.e. 10 games at home and 10 on the
road).
The RPI that we currently use would rank Team A
much higher than Team B based on the .600 winning percentage of
Team A and the .400 winning percentage of Team B, even though
these two teams are identical in every aspect. So the first 25%
of the RPI for these two identical teams would be vastly
different.
The second factor of the RPI, which is currently
50%, can also unfairly reward Team A and unfairly punish Team B
if Team A is from the south and Team B is from the north. This
is because most of Team A's opponents are also from the south
and they have also beaten northern teams at home, while most of
Team B's opponents are from the north and they have lost to
southern teams on the road.
Factor three of the RPI, the final 25%, magnifies
the geographical bias of having more home games with the home
field advantage even more. Basically, the RPI rewards the teams
that can play the most home games.
This is not just a geographical problem of north
vs. south, it is a problem of trying to accurately measure the
strength of teams from any geographic region. Some northern
teams play big home schedules, however, as we all realize, most
of the time southern teams do play more home games and thus have
a built-in advantage that our current RPI system does not
account for.
My proposal is to use an Adjusted Winning
Percentage in all three factors of the RPI instead of the actual
winning percentage. This Adjusted Winning Percentage would
factor out the advantage of playing at home so that the RPI
could more accurately measure the strength of the teams instead
of measuring who plays the most home games.
Right now in the winning percentage, a win counts
as 1.0 wins whether it is a home win, a road win, or a neutral
win. My proposal will still count a neutral field win as 1.0
wins, but will count a road win as 1.25 wins and a home win as
0.8333333333 wins. This will negate the statistical advantage
of playing at home. This will also eliminate the need for the
RPI bonus and penalty points that we currently have in place.
Using my proposed system in the example that I
used earlier, both teams would get 1.0 wins for each win at the
neutral site and both would have a .500 Adjusted Winning
Percentage for having 10 wins in 20 games. However, when the
series was switched to all 20 games at one site and the home
team was 12-8 due to home field advantage, this team would still
have a .500 Adjusted Winning Percentage (12 wins x .8333333333 =
10 wins in 20 games). Furthermore, the visiting team for all 20
games that went 8-12 would also have a .500 Adjusted Winning
Percentage (8 wins x 1.25 = 10 wins in 20 games).
The Adjusted Winning Percentage will more
accurately reflect the strength of teams when they are not equal
as well. For example if Team C is a better team than Team D and
Team C plays all 20 games of their series with Team D at home
and wins 15 of 20, Team C's winning percentage is .750 but their
Adjusted Winning Percentage will be 15 x .8333333333 =
12.5 wins in 20 games = .625. Team D's winning percentage is 5
wins in 20 games = .250 but their Adjusted Winning Percentage
will be 5 x 1.25 = 6.25 wins in 20 games= .3125.
Currently some schools play almost their entire
non-conference schedule at home. In the current RPI system,
this is a huge advantage for these teams. A 56-game schedule
with 27 conference games leaves 29 games out of conference.
Assuming all 29 non-conference games were played at home, and 15
of the 27 league games were also at home, this school could play
44 home games. For this example, let’s say this team goes 39-5
at home and 5-7 on the road. This team would have a .7857
winning percentage (44/56) in the current RPI system but would
have a .692 Adjusted Winning Percentage. ( 39 home wins x
.8333333333 + 5 road wins x 1.25) = 32.5 + 6.25 = 38.75/56 =
.692.
Since a road win will be worth 1.25 wins using
the Adjusted Winning Percentage, some coaches may try to
schedule easy road wins against weak teams. This may help in
the first 25% of the RPI but the remaining 75% of the RPI,
factors #2 and #3, will penalize teams that try this tactic.
However, it could help college baseball for some teams to play
on the road once in awhile.
Imagine what an advantage a conference could have
if all of the teams in the conference played the majority of
their non-conference games at home. In a conference of 12 teams
that plays 30 conference games, each team could play 26
non-conference games (12 x 26 = 312 games.) Suppose the
conference as a whole played 300 of those games at home and 12
on the road and the win-loss record in these games was 265-35 at
home and 6-6 on the road. The current RPI formula would assign
a non-conference winning percentage of 271/312 = .8686 while the
Adjusted Winning Percentage would be .7318 (265 home wins x
.8333333333 + 6 road wins x 1.25) = 220.83 + 7.5 = 228.33/312 =
.7318.
Average teams in conferences that can play most
of their non-conference games at home tend to be ranked higher
in the RPI team rankings due to the compounding effect of the
winning percentages in the RPI once these conference teams start
playing each other. These teams are disproportionally bumped up
in the RPI rankings due to the advantages the current system
gives to teams playing at home.
The current RPI system in baseball also favors
conferences that are geographically located adjacent to
conferences that play more home games. This is because the RPI
rewards teams that play other teams with winning records. As
has been noted, a certain percentage of these wins are based on
home field advantage.
The ranking of the conferences using the RPI
seems to be a critical factor in the amount of at-large teams
selected for the NCAA Tournament. Usually, when a conference is
ranked high in the RPI, more teams are picked out of that
conference for the play-offs.
In my opinion, this ranking is based mainly on
how well each conference performs in their non-conference
games. This is because the RPI is based on winning percentage
and every conference will always have a .500 winning percentage
in conference games because if State wins, Tech loses.
For example, if Conference X has 10 teams and
each team plays 30 conference games and 26 non-conference games,
Conference X will play a total of 260 games against the other
conferences. These non-conference games are the ones that
matter. If non-conference games were not allowed, each
conference's winning percentage would be .500.
Let's assume that Conference Y, a very similar
league to Conference X, also has 10 teams and plays 260 total
non-conference games. However, Conference X plays 200 of the
260 games at home while Conference Y plays 130 of the 260 at
home. It doesn't take a rocket scientist to figure out who has
the home field advantage and who will most likely have a higher
RPI but it does take a better RPI to figure out who is the best.
Using the Adjusted Winning Percentage in the RPI
formula will allow the RPI to more accurately measure the
strength of each team and each conference.
Part
1 - Overview
Part
2 - The Weighting of Three RPI Factors
Part
4 - Exempt Contests vs. Non-Division I Teams; Bonus
& Penalty System
(photo by Jimmy Jones)
|
