Algebracket was created in 2015 by Peter Rifel and Adam Wilcox, two Michigan State Alumni with the goal of taking the madn... stress out of March. Our site will generate a unique bracket based on the statistics you deem most important to a team's success. We aren't trying to sell you on a bunch of unique formulas developed by a team of statisticians over months of work in a dimly lit basement. We went to MSU. We use simple, straightforward stats, and have just made the process of applying them more user friendly.

Welcome to Algebracket! This site allows you to create a customized bracket based on the stats that you deem most important to a team’s success. The sliders are used to weight the individual stats, which determines a team’s overall score. The farther you slide a stat bar, the greater weight you give that stat and the more influence that stat has in a team’s overall score. If you don’t want a certain stat to effect your formula, leave the slider at 0. The “Clear” button will drop all the stat-weights back to zero.

We have integrated data and results from past years so that you can test what combinations of stat-weights would work best for those years. When you find a combination you like, change the year using the drop down menu at the top of the page. This will transfer the stat-weights you picked to that year.

The "Correct" counter tells you how many correct picks your weights have chosen. This is different from the "Score" counter, which calculates a score based on correct picks in the different rounds being worth the following:

- Round 1 - 1 pts
- Round 2 - 2 pts
- Round 3 - 4 pts
- Final Four - 8 pts
- Final - 16 pts
- Champion - 32 pts

A team's overall score is determined by the stat-weights you apply with the sliders. When two team’s are matched up in the bracket, the team with the highest overall score wins and advances to the next round until that team is ultimately beaten by a team with a higher overall score. The team that the algorithm picks to win the bracket, is the team with the highest overall score out of all the teams in that given year.

To account for the fact that each stat is measured on different scales, a method called Feature Scaling was used to normalize the individual stats to put them in a range of 0 to 1. A team with the best value for a given stat will have a 1 where the team with the worst value will have a 0. Stats where lower values are better than higher values are normalized inversely (Seed, Defensive Rating, Opp Pts / Game, Defense Rating, Opp. True Shoot %, Turnover %, and Opp. FT / FGA).

x’ = (x - min(x)) / (max(x) - min(x)) x’ = normalized value x = original team stat value min = minimum value of data set max = maximum value of data set

A team’s overall score is determined using the following formula:

T = (weight1)*(stat1) + (weight2)*(stat2) + ... + (weightn)*(statn)

Where T is the overall score for a given team. The individual stats are multiplied by their corresponding weights given by the sliders. If a slider is set at zero, this stat does not contribute to the team’s overall score. All of the weighted stats are then summed to give the team’s overall score.

The weight you give an individual stat has less effect on the overall score as more stats are given weights. For example, if I picked the following weights for these two stats:

6 - Seed 2 - Rebound MarginThe overall score equation would be:

T = (6)*(Seed) + (2)*(Rebound Margin)

The “Seed” stat has 75% (6/8) of the influence in the overall score compared to “Rebound Margin” which only has 25% (2/8). But if i were to add weights to a couple of other stats:

6 - Seed 2 - Win % 2 - SoS 2 - Free Throw % 2 - Offense Rating 2 - Rebound %The overall score equation would be:

T = (6)*(Seed) + (2)*(Win %) + (2)*(SoS) + (2)*(Free Throw %) + (2)*(Offensive Rating) + (2)*(Rebound %)

The Seed’s influence has dropped to 37.5% (6/16) and the other 5 stats each only account for 12.5% of the final score (2/16).

For each matchup, the winning team has a certainty percentage that is determined by the difference between the two team's overall scores. The higher the percentage value, the greater the difference between the teams overall scores based on the stat-weights you chose.

For example, if you were to only use the "Seed" slider and look at the matchup between a 1 and a 16 seed, you would see a certainty percentage of 100%.

A 16 seed carries a normalized value of 0 and a 1 seed has a normalized value of 1, therefore the difference between their overall scores would be 100%.

Explanation of Stats (all normalized):

- Seed - Team's position in the bracket. 1 seeds have the "easiest" path to the final four. This stat is ranked inversely- the lowest value is ranked the highest.
- Win % - Team's Wins / Total Games prior to the tournament. An undefeated team would have a win percentage of 100%.
- SoS - Strength of Schedule. A ranking of the team's opponents. A team who plays harder opponents will have a higher strength of schedule.
- Pts / Game - Average points a team scores per game.
- Opp Pts / Game - Average points a team's opponent scores per game. This stat is ranked inversely- the lowest value is ranked the highest.
- FG % - Team Field Goal Percentage.
- 3Pt FG % - Team 3-Point Field Goal Percentage.
- Free Throw % - Team's Free Throw shooting percentage.
- Offense Rating - Estimate of points scored by a team per 100 possessions. Offensive Rating is different than points per game in that it eliminates the influence of a team's pace. A slow paced team will have less possessions per game and less opportunity to score, resulting in a lower points per game stat. However, if this team scores on almost every possession, they will have a high offensive rating.
- Defense Rating - Estimate of points a team allowed their opponents to score per 100 possessions. This stat is ranked inversely- the lowest value is ranked the highest.
- Adj. Score Margin - Difference between a team's offense rating and defense rating. The Scoring Margin after 100 possessions.
- Rebound % - Percentage of available rebounds a team grabs during a game.
- Off. Rebound % - Percentage of available offensive rebounds a team grabs during a game. Offensive rebounds are important because they keep a possession alive and allow a team to get more chances at scoring.
- Effective FG % - Team's Total Field Goal percentage adjusted for the fact that a 3-point field goal is worth more than a 2-point field goal.
- True Shooting % - Team's combined shooting efficiency that takes into account 3 pointers, 2 point field goals, and free throws.
- Opp. True Shoot % - Opponent's combined shooting efficiency that takes into account 3 pointers, 2 point field goals, and free throws. A measure of how good a team is at making their opponent's miss. This stat is ranked inversely- the lowest value is ranked the highest.
- Pace - Estimate of the number of possessions a team has per 40 minute game. Ranked by fastest paced teams. If you prefer slow paced teams, do not use this slider.
- Turnover % - Estimate of turnovers a team commits per 100 offensive possessions. This stat is ranked inversely- the lowest value is ranked the highest.
- Opp. Turnover % - Estimate of turnovers a team forces their opponents to have per 100 defensive possessions.
- Turnover Margin - Difference between the number of times a team loses the ball vs times their opponent loses the ball.
- Assist % - Percentage of team's field goals that were assisted. Shows how well the team shares the ball.
- Assists / Turnover - Number of assists per turnover a team has.
- FT / FGA - Free Throws made per Field Goal Attempt. Shows how effective a team is at getting fouled and making their free throws. A higher free throw rate mean's a team plays more aggressively and to draw contact in the paint and get fouled.
- Opp. FT / FGA - Opponent's Free Throws made per Field Goal Attempt. Shows a team's ability to avoid fouling their opponent. A low opponent's free throw rate means that a team is good at not fouling their opponent. This stat is ranked inversely- the lowest value is ranked the highest.