I started this player value site a couple of years ago but never really “released” or publicized it. But over the past month, I’ve finally made some long-wanted changes and thought I would do a quick post to explain the site in case it is interesting or helpful to others.
Here’s the link to the site: https://phillycovercorner.com/draft/index.html
Why I made the site…
I actually think this may be the best freely available draft and player value site out there.
If you have read my stuff, you will know I often use data like draft hit rates, player value, positional costs and free agency prices. To get this data, there isn’t a great or easy-to-use place to get it and I found myself manually pulling data and using it either in Excel or Python.
So, I decided to build a site that would give me what I wanted. And as a (personal) bonus, it allows me to stay sharp technically for my real job.
What you can find on the site
I have to give credit to Pro Football Reference for their work on Approximate Value (AV) which is one of the best single metrics of player value across any position. And it’s what I use as a basis for player value (but I have continually improved the valuation model on top of it) which weaves through so much of the site. You can find more detail on AV on their site here.
The actual analytics site is a responsive site and is mobile friendly, but the below images of the site included here will be small on a mobile device as I captured the desktop site for samples. If you want to see it better, just head to the site and navigate around.
Draft value
Here you can see player values for all drafts since 2000 and filter by year, position, and team.
And beyond player value, this page will show a draft pick’s value vs. expected value given their draft location. In 2020, Chase Young and Jonathan Greenard have similar career value but Young is 13% below expected value for the 2nd overall pick while Greenard was a draft hit, outperforming pick 90’s expected value by 33%.
Team performance and trends
This shows teams draft performance and free agency spend including their record trend, draft hit rates, if they exceeded or fell short of expected draft value, and how much they spend in free agency.
Clicking on a team takes you to a more detailed team page which shows:
- Positional investment – how they invest in the draft and free agency for each position compared to the rest of the league
- Draft performance – by year, the total player value obtained in the draft compared to their expected value and league average
- Free agency spend – by year, what they have added and lost in free agency broken apart by free agency tiers (top, middle, bottom free agents)
Below is an example of the team positional investment view:
General Manager performance and traits
One of my recent – and favorite – adds to the site, you can see how GMs have led their teams, draft performance, how they spend in free agency, and their philosophy and what they value.
Like the Team page, clicking on any GM will take you to a more detailed page showing:
- Philosophy – a summary of what they believe in running their teams including relevant quotes.
- Draft performance – a similar view as the Teams page, this shows how much value they gained by year in the draft vs. expected, although this will only show years that they were a GM
- Positional prioritization – which positions they have drafted by round and how that compares to the league
- Free agency spend – again, a similar view as the Teams page with how they have spent in free agency
Player value
This page allows searching for any drafted player (UDFAs are not loaded yet, but something I am working on) and shows various aspects of a players value including:
- Value percentile – a single number showing a player’s overall value percentile
- Playing time adjust value – value percentile adjusted based on their playing time which will show good players that may have missed time due to injury
- Draft capital – amount of draft capital used on the player
- Value vs. expected – a player’s value vs. the expected value for their pick location
- Career duration – view on how long the player has played
- Total career value – while value percentile is independent of how long a player has played, Total Career Value measures a player’s cumulative career value
Positional trends
Another page I recently completely re-did and one I love, this shows draft and free agency trend information across positions including draft hit rates and draft capital usage, average free agency prices, and how both draft capital and free agency prices have been changing.
Clicking on any position will take you to a more detailed positional information page which includes:
- Draft statistics – draft capital used over time and how many elite, above average, average, or poor players came from each class
- Free agency – how free agency prices for the position have changed compared to the overall salary cap growth rate, both for all free agents and different tiers
- Team positional investment – if you are curious which teams have invested in a position, here you can see every team’s investment in both the draft and free agency
Below is an example of the team positional investment view from the detail page.
Insights
Various one-off insight pages on various topics, including how free agency contract prices growth with the salary cap, draft prospects ages and trends, punter value, and others.
Below is the view on the salary cap vs. free agent prices which I have used often to project new deals and show that player prices (rightly) keep going up.
How to use
And lastly, there’s a page dedicated to a deeper explanation of the various fields, player value metrics, and the model changes I have made over the years to improve it including positional value adjustments, handling QB overvaluation, and smoothing yearly anomalies.
If you check it out, I hope you enjoy it and find value in it. I will continue to improve it and add to it.
Go Birds.
wow, this is great.have to dig deeper, but love the enthusiasm to get it done. thanks for putting in the work.
this is extremely cool. I’ve always wanted to see GM rankings like this- kudos for going out and building it.
I must say, I’m somewhat confused by the underlying metrics here and how they compare to the eye test. For example:
-Milton Williams has negative value vs expected (-5.0%); a 3rd round pick who just got a $26M contract in free agency. Feels like the Eagles got a ton of value out of his cheap rookie deal, but the metrics say otherwise?
-Jalyx Hunt was the 94th pick and he’s ranked as the second best Edge in his class, yet Value vs Exp. is negative at -2.2%
-Mojo Ojomo is only +2.9% over expected; I know his counting stats are low, but for pick 249, that still seems low
I legit appreciate taking an analytics approach to GM evaluation, an am open to the idea that “Howie SZN” is more of a meme than a reality. That said: Philly had the #1 defense last year, and 7 of the 11 starters were on rookie deals. Yet according to these numbers, his draft value over expected is bottom half of the league over the last three years. Just seems hard to square those two things.
what am I missing?
Really good questions and things I have dug into a lot. Couple of points:
– First, no analytic is perfect and not saying these are, there are definitely individuals that are off but over time these are hard to argue with
– Rookies are tough, the small sample size will be off – Nolan Smith was too low last year but after 2nd year is more in line
– Milt stood out to me but when you dig in, his 2024 was really high value but prior 3 seasons were much lower (pressure rate below 10% each of the 3 seasons, snap counts were mid-level first two seasons) – play time affects this so much and he really had 1-1.5 really strong seasons. He will look better next year
– Ojomo is similar, he only played 68 snaps last year so effectively his value is cut in half with almost not playing.
Questions on guys with low play time is the biggest question I get (just got asked by a Falcons fan why Penix is so low, he only played 5 games). I have played with this and did add the Playing Time Adjusted Value but that really helps when missing time due to injury, not on the 53 but just not playing (like Ojomo or Milt who registered full seasons of games). But really, if you aren;t on the field you aren’t providing value.
This is why Howie’s drafts are lower than expected, until 2024 they really play rookies much less than other teams. It works out over time and in a weird way, it is a strength that they don’t HAVE to play rookies.
Been thinking on this more, I am playing with incorporating grading data into the model and there are some players where there is a discrepancy and this improves it (Milt is one). More to come… need to make it not a manual effort which is always the problem with this stuff. Thanks for the prompt on this.