Varying Impacts

On the court, not all players contribute to a team equally. Naturally, the best player(s) are going to have the most prominent roles offensively. The goal of a team offensively is to score as many points per possession as possible. Each shot taken has a risk and a reward. Essentially, the probability of the shot equaling or exceeding the team's average offensive efficiency should be greater than the probability of it not.

However, players have different talent levels. This contested shot is going to be more efficient than this contested shot because of the individuals who are shooting them. Depending on talent level, players can be more involved offensively than others and still be efficient enough to help their team. Finding this balance (between usage and efficiency) is key in maximizing a team.

The below graph is of the most efficient players from 2009-2010. The x-axis is usage (% of possessions a player is used while on the court) and the y-axis is offensive rating. I circled four of the best players at each of the four levels of impact.


There will be more on these four players and their respective regions on the graph later.

It is interesting to compare the graph above to the NBA one. The stars in the NBA (high USG) are nearly as efficient as the top role players. This is very different from the NCAA. It is hard to tell why this is. Maybe NBA teams are better at recognizing who exactly should be taking varying shots on the court. Or maybe the stars in the NBA are just that much better at their craft.

Getting to Know Hoop Vision (The Hoop Vision Top 25)

The TFS Community naturally tends to have similar opinions on many teams and players in basketball. At Hoop Vision, there are certain types of teams we enjoy to watch and follow. The top 25 we put together in this post is not the best 25 teams in NCAAB. The idea was borrowed from a Carson Cistulli post at Fangraphs. He introduced a stat for baseball pitchers called NERD (comprised of qualities that stat geeks tend to like). We tried to do that in this top 25. This top 25 is from the 2009-2010 season.

• Component One: Adjusted Efficiency (AdjO-AdjD)


• Component Two: Offense ((eFG%*2)+(OR%)+(TO%))


• Component Three: Defense ((eFG%)+(OR%/2)+(TO%*2))


• Component Four: Luck (Found at kenpom)
  
• Component Five: Conference Dominance ((Pythag) - (Conf AVG Pythag))
  

Note: The offense and defense components are pretty arbitrary. It is what we favor, but can definitely be ambiguous.

These components are not weighted equally. Like Cistulli did at Fangraphs, I found the z-score (standard deviations from the mean) of each component. The final formula is:

(((aEFFz) + (OFFz*2) + (DEFz/2) + (LUCKz*2) + (CONFz*2)) / 2) + 5

This gives almost every team a number from 0-10. The top 2 teams were rounded down to 10 while the bottom three were rounded up to 0. Without further ado, the Hoop Vision 2009-2010 Top 25:

This chart as well as charts for the top three teams in each conference can be found on its own page. You can go there by clicking on the "Hoop Vision Top 25 (2009-2010)" tab at the top of the website.

Getting to Know Hoop Vision (The Hoop Vision Playbook)

Below is a sample article of what could be posted during the season. We plan on making a separate page with The Hoop Vision Playbook to archive various X's and O's. We will feature overall basketball concepts, teams, and players. The below example is a mixture of a team (Utah State) and a player (Jared Quayle).

Moving Without the Ball: Jared Quayle and Utah St.

Utah St. has been an extremely efficient offensive team recently under Coach Stew Morrill. In the last three years, Utah St.'s AdjO have ranked 18, 17, and 44 (from most recent to oldest) nationally. Their offensive scheme is excellent and they have had the right players to execute. Recent graduate Jared Quayle did a great job of moving without the ball. Below are three examples of Quayle and the Aggies during the NCAA Tournament against Texas A&M. Click on images for better views.

This first play is extremely simple yet effective. Quayle passes the ball to the high post and then gets a screen from the opposite high post. If the defender tries to stay right with Quayle and fight through the screen, then Quayle looks backdoor. However, Quayle was able to pop to the wing for a (successful) three.

The second play starts with Quayle on top handling the ball. He passes to the wing, who dribbles to the top. Quayle then replaces the spot where he just passed. Next, Quayle screens down on the low block. The next step uses the "screen for the screener" concept. Quayle's man is naturally focused on the player Quayle just screened for. Quayle comes off the screen to the wing for an efficient three, but in this case the shot rims out.

The final play is off a baseline inbounds. Quayle starts on the block and screens up for option number one. Although unlikely, an easy lay-up would be the ideal result of the initial screen. The next step is a double screen for the screener. Quayle comes off both screens perfectly and forces not only his man to chase but also one of the defenders guarding a screener. Quayle's jump shot is not open, but he hits his teammate who correctly pops out upon realizing his defender has gone to double team. However, another high percentage jump shot is missed in this sequence (a theme during the A&M game).

Utah State did not get the result they would have liked in the first round of the NCAA Tourney, but it wasn't from lack of execution. Unfortunately for Quayle and the Aggies the shots didn't fall. Stew Morrill's team will be relevant again in 2010-2011. The only senior from last year was Quayle, not to mention the arrival of JUCO All-American Antonio Bumpus.

Getting to Know Hoop Vision (Video Charting Overview)

Video Analysis is a technique we will be instituting at Hoop Vision. Video Charting can show different aspects about individual teams. It can show tendencies of how a team functions. For example, how often a team passes and where there shots are coming from. By looking at what happens when a team has success on a possession and what happens on a possession a team does not have success we can make conclusions. However, sample size can play a big role in the charting. The more plays that are charted the more reliable the data is. 82games charted touches/dribbles, rebounds, floor locations, and passes in bulk for the NBA. Great conclusions can be made conceptually for offensive efficiency based on the data.

Despite the clear troubles of sample size, we think charting can give a unique perspective of a game. There are many things we can do with the charting and we will probably be learning as we go. The chart below is the first 10 possessions for Utah St. versus Texas A&M in the NCAA Tourney. With our luck, we picked 10 miserable possessions from a normally efficient team (can't emphasize sample size enough).

Charts with information like this one above will be featured in game recaps. Throughout the year, we will look to provide in depth analysis on keys to success in basketball in general and on a team specific level. Game charting will be one of many ways that we hope to make Hoop Vision unique and insightful.

Getting to Know Hoop Vision (Intro to Stats)

Advanced statistics can sometimes frighten a sports fan. Basketball, however, does not have the complexities of baseball. It has been well documented that the basketball revolution is far behind baseball. This can be a good thing for a fan who has yet to take an interest in advanced statistics. For the most part, basketball stats are conceptual. Reason and logic is just as important as math in most cases. The focus is clear and shouldn't be lost when viewing advanced metrics. Extremely basic questions need to be asked first...

Q: What is the main goal of any competition?
A: WIN

Q: In basketball, how is a win or loss determined?
A: POINTS

Q: In basketball, how do you create points?
A: SCORING (putting the ball in the hoop)

There is no need to invent an advanced statistic to measure how many points a team scored or what the team's record is. These two numbers are not arbitrary. They can be measured with 100% certainty. However, advanced statistics attempt to capture why the result was what it was.

Enter: Dean Oliver. The first thing he recognized was the goal of basketball was not just to score as many points as possible, but to score as many points per possession. Tempo does not get in the way of reality when stats are used on a possession basis. He laid out the crucial Four Factors here. These are the four ways to be as efficient (score as many points per possession) as possible.

1. Shooting
2. Turnovers
3. Rebounding
4. Foul Shooting

*Note: These are used for offense and defense (How you shoot AND how you let your opponent shoot)
*Note: These factors are not all equal. Shooting is the most important (about 40%), turnovers (about 25%), rebounding (about 20%), and free throws (about 15%).

I challenge you to come up with another element of basketball that directly leads to points. Assists are an example of a valuable stat that is not directly represented by the Four Factors. However, an assist leads to a quality shot (or free throws) and avoids a turnover. Diving for a loose ball and other hustle plays all are apart of these factors.

The above chart consists of basketball concepts. The fact that shooting is a big part of efficient scoring is nice, but we have to be able to quantify these factors.

1. Shooting --> eFG% = (.5*3FGM + FGM) / FGA

Essentially FG%, but three pointers are weighted 50% higher than two's.

2. Turnovers --> TO% = TO / Possessions

3. Rebounding --> OR% = OR / ((OR) + (opp DR))

4. Free Throws --> (OFFENSE) FTRate = FTM / FGA

--> (DEFENSE) FTRate = FTA / FGA

Free throws attempted is better defensively, because a defense cannot control if the other teams makes their free throws.

The four factors are excellent tools for evaluating basketball teams. You want proof?

Below is the 2009-2010 Mountain West Conference (conference games only). The x-axis is OEfficiency - DEfficiency. BYU was the best at +22, while Air Force was the worst at -27. The y-axis is what we call Four Factor's Rating. The first step is standardizing all of the four factors. This makes sure unfair weighting isn't given to any of the factors. Next, the standardized versions of the factors are multiplied by the weights mentioned earlier in the post (.4 shooting, .25 turnovers, .2 rebounding, .15 free throws). Again, BYU was the best at +1.0 and Air Force was the worst at -.9. Coincidence? I think not. Although the rankings aren't exactly the same, the correlation between the two is .977. For any further questions on the graph or data of the specific teams in the MWC email us here.

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These stats simply give you a better picture of a basketball team than standard counting stats found in a standard box score. Individual stats were not touched upon here (yet), but for more information on all of this stuff email us and/or look here, here, and here.

Getting to Know Hoop Vision (Outline)

Early June is an interesting day to start an NCAA Basketball blog. Only the hardcore fans are currently looking for information and analysis. At Hoop Vision, however, this is the fan we like and connect with. Our next step is a series of posts which are examples of what we will be giving to you. The list of posts to come is as follows (links to come as posts are published):

1. Intro to Stats
2. Video Charting Overview
3. The Hoop Vision Playbook
4. The Hoop Vision Top 25

Welcome

Welcome to Hoop Vision. This is a college basketball analysis blog. One of the hopefully unique features of the blog will be a stronger focus on each conference and not just the teams commonly shown on ESPN. Naturally, more words will probably be used on the Dukes of the world, but we will do our best to represent all 31 conferences. Ultimately, the game of basketball is what we are setting out to explore. Posts will be specifically devoted to the college basketball season, but also to exploring basketball concepts and strategies.

Questions or Comments? We want to hear from you. Email us here.

Coming soon to Hoop Vision

In the coming weeks we will be previewing typical features to come during and leading up to the college basketball season. Our goal is to find what you the reader is interested in. We have some great ideas to enhance your college basketball experience and are excited to see what you think. Plus, who wouldn't want to review the great moments from the 2009-2010 season?