March Madness 2008 starts in just a few weeks. As I mentioned in Tournament Trends Analysis Part I, seeding is by far the most important factor in a team's tournament success, but I have made it my goal to find out which other factors determine who advances and who doesn't in the NCAA Tournament. In Part I, I analyzed seeding, a team's record in the last ten games, record against the RPI Top 50, road/neutral record and the impact of conference tournaments.

In this analysis, I tested theories on tournament success based on each team's statistics, including field goal percentage, rebounding and turnovers. I used team statistical data from the years 1998-2007 to test my theories. I limited my analysis to games in which the seed differential between the two teams was between 0 and 3 because in those cases the team with better seed won only 52% of the time. In cases where the seed differential was between 4 and 9, the team with the better seed won 75% of the time and because the team with the superior seed tends to have the superior statistics, an analysis of games between teams with seed differentials above 3 would be biased. The following is a list of my theories and a synopsis of my findings.

Disclaimer

Let me start by saying that this site does not support or encourage gambling. I have provided this information for the amusement of college basketball fans and more specifically, stat junkies like myself. If this helps you to fill out your brackets, that's great, but I would never advise anyone to gamble with money that they cannot afford to lose. The beauty of the office pool is that it is very low risk with possible high reward and the tournament is much more interesting when you have someone to root for. The following information is based on trends in the tournament for the past eight to twelve years. There is no guarantee that these trends will continue this season. More importantly, even if these trends do hold true, they give you only a slight edge. Most of what happens in the tourney is pure chance and it takes a lot of luck to do well in your NCAA pool. Please feel free to email me and let me know what you think about the results. However, if you complain to me because you used these trends and they did not work, I will not listen. Use this information at your own risk. Now on to the results.

Theory 1 - The better shooting team will win the majority of the time

My first theory was that good shooting teams (teams with high field goal percentages during the season) would have much more success in the tournament. The way that I see it, defensive intensity increases at tournament time so outside shots will be that much tougher to make. A good shooter (or in this case good shooting team) is much better equipped to overcome tight defensive pressure than a poor shooting team. Because it didn't make sense to compare situations where one team's shooting efficiency was only fractionally better than their opponent, I limited the analysis to situations where one team had an average field goal percentage at least two percentage points better than their tournament opponent. I found 107 such matchups between 1998 and 2007. My theory proved accurate as the team with the higher field goal percentage was 66-41 (62%). When I limited the analysis to matchups between teams with field goal percentages three or more percentage points apart, the better shooting team was 41-26 (61%). Even with the small sample, this is fairly strong evidence that the better shooting team has a distinct advantage in matchups of similarly seeded teams.

Theory 2 - The team with the better field goal percentage defense will win the majority of the games

Again I started with the 2% rule. That is, I only analyzed games in which one team's average field goal percentage defense (in other words, their opponent's field goal percentage) was at least two percentage points better than the other team's field goal percentage defense. Unfortunately, this theory did not prove to be as strong as the previous one. In 88 games, the team with the lower opposition field goal percentage was 48-40 (55%).

Theory 3 - Teams that consistently make their free throws will win more often than not

Anyone who has watched college basketball over the years has seen many games lost because one team was not able to make their free throws. The question is: does data from the NCAA Tournament support this? I felt like this would be one of the critical measures for judging who will win games between evenly matched teams. I rarely pick a poor free throw shooting team to beat a similarly-seeded team that shoots a solid percentage from the charity stripe. Obviously, the close games are much more likely to be decided at the free throw line. This time, I limited my data set to matchups between teams with free throw percentages at least 3 percentage points apart. I came up with 110 occurrences and the team with the better free throw percentage was 62-48 (56%). However, in 79 instances where the difference was 4% or more, the better free throw shooting team won only 37 times (47%). This was very surprising so I looked more closely at the data and found that only 35 of the 110 games analyzed in the first case were decided by four points or less. The better free throw shooting team won only 15 of those 35 games (43%). This data does not support my theory. In fact, it is the exact opposite of what I expected.

Theory 4 - The better rebounding teams will have more success in the Tournament

My theory is that teams will be playing much better defense in the tournament and therefore more shots will be missed. Given more missed shots, there will be more rebounds. With more available rebounds, the better rebounding teams will be at much more of an advantage. At least that is how I see it. I started analyzing this data by calculating a defensive rebounding percentage and an offensive rebounding percentage. A team's defensive rebounding percentage is their average defensive rebounds divided by the sum of their average defensive rebounds and their opponent's average offensive rebounds. In other words, the percentage of available rebounds that the team was able to collect on the defensive end. Offensive rebounding percentage was calculated similarly.

DEFENSIVE REBOUNDING PERCENTAGE = DEFENSIVE REBOUNDS / (DEFENSIVE REBOUNDS + OPPONENTS OFFENSIVE REBOUNDS)

OFFENSIVE REBOUNDING PERCENTAGE = OFFENSIVE REBOUNDS / (OFFENSIVE REBOUNDS + OPPONENTS DEFENSIVE REBOUNDS)

I chose this method rather than actual total rebounds because total rebounds is more a function of shooting percentage. In other words, a team that holds its opponents to a very low shooting percentage will grab more defensive rebounds, but this does not make them a good defensive rebounding team. To test this theory, I again applied the 2% differential rule (at least two percentage points difference between the two teams). In those games, the team with the better defensive rebounding percentage was 61-51 (54%). Using the same analysis for offensive rebounding prowess, I found that the better offensive rebounding team was 69-66 (51%). When I increased the minimum difference to 3%, the results are: better defensive rebounding team, 46-33 (58%) and better offensive rebounding team 51-47 (52%). Again, the data would suggest that the better rebounding team has a better chance to win, but the results are hardly overwhelming.

Theory 5 - The team with the better turnover margin will win the majority of games

Turnover margin is defined as the difference between a team's average number of opponent turnovers forced and the average number of turnovers committed. A positive number indicates that a team takes better care of the ball than their opponent which is critical during tournament time, especially given that single-elimination stress and tighter defense will result in an increased number of turnovers. I started by simply looking at all games where one team's average turnover margin was better than their opponent's average, regardless of whether both were positive or negative. I found that the team with the better turnover margin (minimum difference in turnover margin of 2.0 turnovers per game) was 54-58 (48%). Clearly, these are disappointing results.

Other Analysis

Please take a look at my March Madness Analysis Part I page. There you will find analysis based on a variety of team variables including:

• RPI Ranking
• Conference Winning Pct
• Road/Neutral Court Record
• Winning Pct Against the RPI Top 50
• Experience
• and more

Conclusions

Based on the data, the two most important statistical factors affecting who will win NCAA Tournament games between similarly seeded teams are field goal percentage, defensive field goal percentage and defensive rebounding. Still, the advantages are slight and the sample size (the number of applicable games to analyze) is relatively small. As I have mentioned before, knowing your seeds and good old fashioned luck is required to win a large NCAA Tournament pool. The statistics above must also be taken with caution because not all conferences are created equal. For example, a team with a 45% team field goal percentage that plays in the defensive-minded Big East is probably a better shooting team than a school that averages 47% from the field in a mediocre defensive conference like the Pac Ten. I think some important knowledge can be gleaned from these statistics, but conference affiliation must be considered when examining these statistics.

If you would like to take a look at these team stats in greater depth, I suggest visiting the college basketball page at StatFox.com.