Sports

# Which college teams are best at preparing players for the NFL? See where your team ranks.

# Which college teams are best at preparing players for the NFL? See where your team ranks.

# Which college teams are best at preparing players for the NFL? See where your team ranks.

David Bressler

David Bressler

David Bressler

December 28, 2023

December 28, 2023

December 28, 2023

**The analysis in this article was conducted by Formula Bot's Data Analyzer, an AI-powered application that allows users to analyze their data through a simple conversation. No data background necessary.**

Alabama head coach Nick Saban is considered to be the greatest college football coach of all time. As of writing this, he has seven national championships with the potential to win his eighth in the coming weeks.

Saban once said, “I don’t know if I’m different from everybody else, but there’s really only two things to me that are really, really important – recruiting good players in the program and developing those players once they get here.”

But is Saban a good recruiter? How effective is he at developing talent?

We don’t have to look far to see that Saban is an excellent recruiter, seeing that Alabama has ranked 1st or 2nd in recruiting within the past five years, based on average star ratings from 247sports.com.

But how can we objectively measure Saban's success in developing players? Should we say he’s the best at developing talent too, given Alabama has had the most players drafted in the past 10 years (107 total players drafted in the past 10 years, which is 20 more than the next team - LSU)?

Nearly all of those 107 Alabama players that were drafted were four and five stars. 247Sports considers five star players to have “excellent pro-potential” and four star players “will be an impact player for his college team… is projected to play professionally”.

Is it fair to say that Saban is good at developing players if, before they even step foot in Tuscaloosa, they’re already being labeled to be a future NFL player?

No, it’s not fair.

That’s why this article exists. We’ll be examining how well every college team develops players, relative to the caliber of recruits that sign there.

**Methodology**

Every college team’s assessment of developing players is based on how many former players were drafted in the NFL, relative to the caliber of players recruited. Colleges with strong development had more former players get drafted in the NFL versus what was expected of them based on those player’s high school recruiting scores. The recruiting score ranges from 0.69 to 1.0. Players' likelihood to be drafted will be averaged across all teams to compare the ‘expected’ draft rate versus the actual draft rate.

**Data Collection**

High school recruit information and NFL draft results from 2010 to 2020 were gathered from 247Sports.com and DraftHistory.com, respectively.

**Analysis**

Before exploring the results from the model, let’s take a look at some high-level stats that show how the different star ratings compare in terms of their respective draft rates. Results reflective in the chart below.

Percent of All NCAA Players: This calculation shows the percentage total of all NCAA players, ie: 49.5% of all NCAA players from 247Sports.com were 3 stars and only 1.1% were 5 stars.

Draft Rate: This calculation shows what percentage of NCAA players within each star rating group were drafted, ie: Only 2.3% of 2 star players are drafted, compared to 58% of 5 stars.

Percent of All Drafted Players: This calculation shows the percentage total of all drafted players, ie: 49.9% of drafted players are 3 stars, compared to 10.4% of 5 stars.

Looking at the draft rate (orange bar), you can see there’s an exponential increase for every additional star: 0% -> 2.3% -> 6.2% -> 20.7% -> 58% (from 0 stars to 5 stars).

This chart acts as a great visual representation of how well scouts from Rivals.com and 247Sports.com evaluate a player’s potential. Interestingly, both sites evaluate players based on their NFL potential, not their college potential and treat it more like a combine with a focus on size, speed and potential development. A direct quote from the **247Sports website**: “Our ultimate goal is to accurately project college success with an element of raw ability baked in. To that end, we have turned to the NFL Draft as the measuring stick…” This suggests that there should be a higher correlation with a player’s star rating and their NFL success and draftability compared to their collegiate success.

Next, we’ll calculate every player’s propensity/likeliness to be drafted solely based on their recruiting score. Knowing what we know, we’ll expect to see an exponential trend.

(Side note - Where a player is from and what position they played were considered as additional variables to predict a players likelihood of getting drafted, but the results were nearly identical compared to only using the player’s recruiting score as the sole predictor.)

The specific model used was a logistic regression, a statistical method used for analyzing datasets in which there is a binary outcome - either one thing or another, “yes or no,” “pass or fail” or in this case, “drafted or not drafted”.

The results from the model confirms that there’s an exponential relationship between a player’s recruiting score and their likelihood of getting drafted. On the high end, a player’s chances of getting drafted is 37% but only 1% on the low end. Some notable five star recruits that were drafted include Jadeveon Clowney, Trevor Lawrence, Justin Fields, Leonard Fournette and Bryce Young.

If we aggregate the recruiting scores into their respective star ratings (>=0.98 is a 5, <0.98 and >=0.90 is a 4, <0.90 and >=0.8 is a 3, <0.8 and >=0.7 is a 2, <0.7 is a 1), we can see how the actual draft rate compares to the likelihood to be drafted. The results show that the model is highly accurate for 1 to 4 star players, but undervalues the likelihood of a 5 star player to be drafted. There are many reasons for this differential, like what colleges the player goes to and the margin between a high-end and low-end 5 star, but regardless, it’s directional and the same for all colleges to be examined.

Next, we conducted the same analysis as above but applied that to every college team - comparing actual versus predicted draft rate. Teams above the line have a higher actual draft rate compared to their predicted draft rate (good development) and inversely, teams below the line have a lower than predicted draft rate (poor development).

Powerhouse teams - Alabama, Georgia, Ohio State and LSU, are shown in the top right corner, well above their predicted draft rate. While Alabama has the highest actual draft rate, Georgia has the largest difference between their actual and predicted draft rate (31% actual compared to 18% predicted, netting a differential of +13 percentage points).

The chart below shows every team’s differential between actual draft rate and their predicted draft rate (teams with less than 5 players drafted in 10 years were removed).

The ten best teams in terms of player development are as follows (ranked): Alabama, Georgia, Penn State, Ohio State, LSU, Florida, Clemson, Iowa, Pittsburgh and Louisville.

The ten worst teams in terms of player development are as follows (ranked): Nebraska, Rutgers, Texas, Washington, Marshall, Tennessee, Arizona State, Duke, Toledo and Texas Tech.

The SEC as a whole ranked first in having the highest variance between their actual and predicted draft rate, followed by the Big 10 and the ACC. The Pac-12 and Big-12 had lower actual draft rates compared to their predicted rates.

Lastly, I was curious to see how a team’s actual draft rate correlates to their record over the years (2010 to 2020). There’s a moderately strong correlation of +0.66 between these two variables. Unsurprisingly, the moderately strong correlation suggests that teams are more likely to win games when there's eventual NFL-caliber players on the team. It’s interesting to see teams that are far from the line, like Boise State (top left). Boise State’s success on the field, represented by the win rate, is significantly better than what’s expected based on the percentage of their players being drafted.

I’ll end with a quote by a famous statistician, “All models are wrong, some are useful.” This entire analysis is not supposed to be right or wrong. It’s correlation, not causation. And maybe some of the insights you’ve taken away can be used as conversation starters while watching the College Football Playoffs with your friends and family.

**You can download the files used to conduct the analysis here.**

**The analysis in this article was conducted by Formula Bot's Data Analyzer, an AI-powered application that allows users to analyze their data through a simple conversation. No data background necessary.**

Alabama head coach Nick Saban is considered to be the greatest college football coach of all time. As of writing this, he has seven national championships with the potential to win his eighth in the coming weeks.

Saban once said, “I don’t know if I’m different from everybody else, but there’s really only two things to me that are really, really important – recruiting good players in the program and developing those players once they get here.”

But is Saban a good recruiter? How effective is he at developing talent?

We don’t have to look far to see that Saban is an excellent recruiter, seeing that Alabama has ranked 1st or 2nd in recruiting within the past five years, based on average star ratings from 247sports.com.

But how can we objectively measure Saban's success in developing players? Should we say he’s the best at developing talent too, given Alabama has had the most players drafted in the past 10 years (107 total players drafted in the past 10 years, which is 20 more than the next team - LSU)?

Nearly all of those 107 Alabama players that were drafted were four and five stars. 247Sports considers five star players to have “excellent pro-potential” and four star players “will be an impact player for his college team… is projected to play professionally”.

Is it fair to say that Saban is good at developing players if, before they even step foot in Tuscaloosa, they’re already being labeled to be a future NFL player?

No, it’s not fair.

That’s why this article exists. We’ll be examining how well every college team develops players, relative to the caliber of recruits that sign there.

**Methodology**

Every college team’s assessment of developing players is based on how many former players were drafted in the NFL, relative to the caliber of players recruited. Colleges with strong development had more former players get drafted in the NFL versus what was expected of them based on those player’s high school recruiting scores. The recruiting score ranges from 0.69 to 1.0. Players' likelihood to be drafted will be averaged across all teams to compare the ‘expected’ draft rate versus the actual draft rate.

**Data Collection**

High school recruit information and NFL draft results from 2010 to 2020 were gathered from 247Sports.com and DraftHistory.com, respectively.

**Analysis**

Before exploring the results from the model, let’s take a look at some high-level stats that show how the different star ratings compare in terms of their respective draft rates. Results reflective in the chart below.

Percent of All NCAA Players: This calculation shows the percentage total of all NCAA players, ie: 49.5% of all NCAA players from 247Sports.com were 3 stars and only 1.1% were 5 stars.

Draft Rate: This calculation shows what percentage of NCAA players within each star rating group were drafted, ie: Only 2.3% of 2 star players are drafted, compared to 58% of 5 stars.

Percent of All Drafted Players: This calculation shows the percentage total of all drafted players, ie: 49.9% of drafted players are 3 stars, compared to 10.4% of 5 stars.

Looking at the draft rate (orange bar), you can see there’s an exponential increase for every additional star: 0% -> 2.3% -> 6.2% -> 20.7% -> 58% (from 0 stars to 5 stars).

This chart acts as a great visual representation of how well scouts from Rivals.com and 247Sports.com evaluate a player’s potential. Interestingly, both sites evaluate players based on their NFL potential, not their college potential and treat it more like a combine with a focus on size, speed and potential development. A direct quote from the **247Sports website**: “Our ultimate goal is to accurately project college success with an element of raw ability baked in. To that end, we have turned to the NFL Draft as the measuring stick…” This suggests that there should be a higher correlation with a player’s star rating and their NFL success and draftability compared to their collegiate success.

Next, we’ll calculate every player’s propensity/likeliness to be drafted solely based on their recruiting score. Knowing what we know, we’ll expect to see an exponential trend.

(Side note - Where a player is from and what position they played were considered as additional variables to predict a players likelihood of getting drafted, but the results were nearly identical compared to only using the player’s recruiting score as the sole predictor.)

The specific model used was a logistic regression, a statistical method used for analyzing datasets in which there is a binary outcome - either one thing or another, “yes or no,” “pass or fail” or in this case, “drafted or not drafted”.

The results from the model confirms that there’s an exponential relationship between a player’s recruiting score and their likelihood of getting drafted. On the high end, a player’s chances of getting drafted is 37% but only 1% on the low end. Some notable five star recruits that were drafted include Jadeveon Clowney, Trevor Lawrence, Justin Fields, Leonard Fournette and Bryce Young.

If we aggregate the recruiting scores into their respective star ratings (>=0.98 is a 5, <0.98 and >=0.90 is a 4, <0.90 and >=0.8 is a 3, <0.8 and >=0.7 is a 2, <0.7 is a 1), we can see how the actual draft rate compares to the likelihood to be drafted. The results show that the model is highly accurate for 1 to 4 star players, but undervalues the likelihood of a 5 star player to be drafted. There are many reasons for this differential, like what colleges the player goes to and the margin between a high-end and low-end 5 star, but regardless, it’s directional and the same for all colleges to be examined.

Next, we conducted the same analysis as above but applied that to every college team - comparing actual versus predicted draft rate. Teams above the line have a higher actual draft rate compared to their predicted draft rate (good development) and inversely, teams below the line have a lower than predicted draft rate (poor development).

Powerhouse teams - Alabama, Georgia, Ohio State and LSU, are shown in the top right corner, well above their predicted draft rate. While Alabama has the highest actual draft rate, Georgia has the largest difference between their actual and predicted draft rate (31% actual compared to 18% predicted, netting a differential of +13 percentage points).

The chart below shows every team’s differential between actual draft rate and their predicted draft rate (teams with less than 5 players drafted in 10 years were removed).

The ten best teams in terms of player development are as follows (ranked): Alabama, Georgia, Penn State, Ohio State, LSU, Florida, Clemson, Iowa, Pittsburgh and Louisville.

The ten worst teams in terms of player development are as follows (ranked): Nebraska, Rutgers, Texas, Washington, Marshall, Tennessee, Arizona State, Duke, Toledo and Texas Tech.

The SEC as a whole ranked first in having the highest variance between their actual and predicted draft rate, followed by the Big 10 and the ACC. The Pac-12 and Big-12 had lower actual draft rates compared to their predicted rates.

Lastly, I was curious to see how a team’s actual draft rate correlates to their record over the years (2010 to 2020). There’s a moderately strong correlation of +0.66 between these two variables. Unsurprisingly, the moderately strong correlation suggests that teams are more likely to win games when there's eventual NFL-caliber players on the team. It’s interesting to see teams that are far from the line, like Boise State (top left). Boise State’s success on the field, represented by the win rate, is significantly better than what’s expected based on the percentage of their players being drafted.

I’ll end with a quote by a famous statistician, “All models are wrong, some are useful.” This entire analysis is not supposed to be right or wrong. It’s correlation, not causation. And maybe some of the insights you’ve taken away can be used as conversation starters while watching the College Football Playoffs with your friends and family.

**You can download the files used to conduct the analysis here.**

**The analysis in this article was conducted by Formula Bot's Data Analyzer, an AI-powered application that allows users to analyze their data through a simple conversation. No data background necessary.**

Alabama head coach Nick Saban is considered to be the greatest college football coach of all time. As of writing this, he has seven national championships with the potential to win his eighth in the coming weeks.

Saban once said, “I don’t know if I’m different from everybody else, but there’s really only two things to me that are really, really important – recruiting good players in the program and developing those players once they get here.”

But is Saban a good recruiter? How effective is he at developing talent?

We don’t have to look far to see that Saban is an excellent recruiter, seeing that Alabama has ranked 1st or 2nd in recruiting within the past five years, based on average star ratings from 247sports.com.

But how can we objectively measure Saban's success in developing players? Should we say he’s the best at developing talent too, given Alabama has had the most players drafted in the past 10 years (107 total players drafted in the past 10 years, which is 20 more than the next team - LSU)?

Nearly all of those 107 Alabama players that were drafted were four and five stars. 247Sports considers five star players to have “excellent pro-potential” and four star players “will be an impact player for his college team… is projected to play professionally”.

Is it fair to say that Saban is good at developing players if, before they even step foot in Tuscaloosa, they’re already being labeled to be a future NFL player?

No, it’s not fair.

That’s why this article exists. We’ll be examining how well every college team develops players, relative to the caliber of recruits that sign there.

**Methodology**

Every college team’s assessment of developing players is based on how many former players were drafted in the NFL, relative to the caliber of players recruited. Colleges with strong development had more former players get drafted in the NFL versus what was expected of them based on those player’s high school recruiting scores. The recruiting score ranges from 0.69 to 1.0. Players' likelihood to be drafted will be averaged across all teams to compare the ‘expected’ draft rate versus the actual draft rate.

**Data Collection**

High school recruit information and NFL draft results from 2010 to 2020 were gathered from 247Sports.com and DraftHistory.com, respectively.

**Analysis**

Before exploring the results from the model, let’s take a look at some high-level stats that show how the different star ratings compare in terms of their respective draft rates. Results reflective in the chart below.

Percent of All NCAA Players: This calculation shows the percentage total of all NCAA players, ie: 49.5% of all NCAA players from 247Sports.com were 3 stars and only 1.1% were 5 stars.

Draft Rate: This calculation shows what percentage of NCAA players within each star rating group were drafted, ie: Only 2.3% of 2 star players are drafted, compared to 58% of 5 stars.

Percent of All Drafted Players: This calculation shows the percentage total of all drafted players, ie: 49.9% of drafted players are 3 stars, compared to 10.4% of 5 stars.

Looking at the draft rate (orange bar), you can see there’s an exponential increase for every additional star: 0% -> 2.3% -> 6.2% -> 20.7% -> 58% (from 0 stars to 5 stars).

This chart acts as a great visual representation of how well scouts from Rivals.com and 247Sports.com evaluate a player’s potential. Interestingly, both sites evaluate players based on their NFL potential, not their college potential and treat it more like a combine with a focus on size, speed and potential development. A direct quote from the **247Sports website**: “Our ultimate goal is to accurately project college success with an element of raw ability baked in. To that end, we have turned to the NFL Draft as the measuring stick…” This suggests that there should be a higher correlation with a player’s star rating and their NFL success and draftability compared to their collegiate success.

Next, we’ll calculate every player’s propensity/likeliness to be drafted solely based on their recruiting score. Knowing what we know, we’ll expect to see an exponential trend.

(Side note - Where a player is from and what position they played were considered as additional variables to predict a players likelihood of getting drafted, but the results were nearly identical compared to only using the player’s recruiting score as the sole predictor.)

The specific model used was a logistic regression, a statistical method used for analyzing datasets in which there is a binary outcome - either one thing or another, “yes or no,” “pass or fail” or in this case, “drafted or not drafted”.

The results from the model confirms that there’s an exponential relationship between a player’s recruiting score and their likelihood of getting drafted. On the high end, a player’s chances of getting drafted is 37% but only 1% on the low end. Some notable five star recruits that were drafted include Jadeveon Clowney, Trevor Lawrence, Justin Fields, Leonard Fournette and Bryce Young.

If we aggregate the recruiting scores into their respective star ratings (>=0.98 is a 5, <0.98 and >=0.90 is a 4, <0.90 and >=0.8 is a 3, <0.8 and >=0.7 is a 2, <0.7 is a 1), we can see how the actual draft rate compares to the likelihood to be drafted. The results show that the model is highly accurate for 1 to 4 star players, but undervalues the likelihood of a 5 star player to be drafted. There are many reasons for this differential, like what colleges the player goes to and the margin between a high-end and low-end 5 star, but regardless, it’s directional and the same for all colleges to be examined.

Next, we conducted the same analysis as above but applied that to every college team - comparing actual versus predicted draft rate. Teams above the line have a higher actual draft rate compared to their predicted draft rate (good development) and inversely, teams below the line have a lower than predicted draft rate (poor development).

Powerhouse teams - Alabama, Georgia, Ohio State and LSU, are shown in the top right corner, well above their predicted draft rate. While Alabama has the highest actual draft rate, Georgia has the largest difference between their actual and predicted draft rate (31% actual compared to 18% predicted, netting a differential of +13 percentage points).

The chart below shows every team’s differential between actual draft rate and their predicted draft rate (teams with less than 5 players drafted in 10 years were removed).

The ten best teams in terms of player development are as follows (ranked): Alabama, Georgia, Penn State, Ohio State, LSU, Florida, Clemson, Iowa, Pittsburgh and Louisville.

The ten worst teams in terms of player development are as follows (ranked): Nebraska, Rutgers, Texas, Washington, Marshall, Tennessee, Arizona State, Duke, Toledo and Texas Tech.

The SEC as a whole ranked first in having the highest variance between their actual and predicted draft rate, followed by the Big 10 and the ACC. The Pac-12 and Big-12 had lower actual draft rates compared to their predicted rates.

Lastly, I was curious to see how a team’s actual draft rate correlates to their record over the years (2010 to 2020). There’s a moderately strong correlation of +0.66 between these two variables. Unsurprisingly, the moderately strong correlation suggests that teams are more likely to win games when there's eventual NFL-caliber players on the team. It’s interesting to see teams that are far from the line, like Boise State (top left). Boise State’s success on the field, represented by the win rate, is significantly better than what’s expected based on the percentage of their players being drafted.

I’ll end with a quote by a famous statistician, “All models are wrong, some are useful.” This entire analysis is not supposed to be right or wrong. It’s correlation, not causation. And maybe some of the insights you’ve taken away can be used as conversation starters while watching the College Football Playoffs with your friends and family.

**You can download the files used to conduct the analysis here.**

Formula Bot is a set of AI-powered data analytics tools that helps users convert text into formulas, analysis, data visualizations, advanced data models and more.

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Data Connectors

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Data Connectors

Formula Bot is a set of AI-powered data analytics tools that helps users convert text into formulas, analysis, data visualizations, advanced data models and more.

Free Tools

Data Connectors