But honestly, hyping up and getting excited for picks I like is a lot of fun so why wouldn't I do it? It's not like our collective opinion matters at all
These people who are like "don't get too excited, statistics say he could bust blah blah blah" are miserable
As a Patriots fan who watched Belichick draft for 20 years, I can personally attest that "reaches" are definitely a thing.
I day dream about having Harrison/Wayne or Hill/Kelce with Brady for 5+ years, he got 1 with a healthy Moss/Welker, and look what happened, and Welker is not in Hill/Kelce/Wayne/Harrisons class at all.
I mean of course, champagne problems.
But a lot of the "Brady = system QB" was just him playing with guys who weren't even Pro Bowl Alternates.
Imagine if from 2001-2006, Brady had Faulk, James, Harrison, Wayne, Clark and Manning had Brown, Patten, Fauria?, Branch.
No one would've been calling Brady a system QB, even though he would've been exactly as talented in that scenario, as he was in the real one.
Manning with Harrison/Wayne/James/Clark from 1999 to 2005 scored the following in his losses:
16, 17, 0, 14, 3, 18
If he had Brown/Patten/Givens/etc, he would've been obviously much worse.
Also the Colts defense had Freeney, Mathias, Sanders, etc. They were very good.
How am I presenting them as facts?
It is my opinion (not a fact) that Manning would score less points with Brown/Patten/Givens than Harrison/Wayne/Clark/James.
Given that 3 of 4 of those players are HOFers, I think it's a reasonable opinion.
Additionally, given that Freeney, Mathias, Sanders were All-Pros at premium positions, seems likely their defense was quite good.
If Tom Brady was throwing to them earlier in his career he'd have been a different player and may not even have won any of the Super Bowls. Additionally, given that stats exist.. Manning did not have a "quite good" defense. Especially when compared to Brady's "quite elite" defense.
Explain how Brady becomes a worse player when he gets to start in a better situation?
Literally everything we know about young QBs shows, a better situation makes a better QB.
Also Colts had 2 Top 3 defenses, and 2 other Top 10 defenses from 2003-2009. Same as the Pats.
summary:
* the tweet says "steals are not a thing"
* the graph says "steals are rare"
* the consensus is that steals are a thing, and maybe they are rare, but they are a thing
* adding final reminder that draft perception and big board do not equal performance
just say you can't understand it
> the tweet says "steals are not a thing"
> the graph says "steals are rare"
Are you not familiar with how people write on twitter? These two have effectively the same meaning in internet shorthand.
Anyways, do you understand that picks that are generally viewed as "steals" are the picks where players were taken far before their big board ranks? This part:
> adding final reminder that draft perception and big board do not equal performance
means that "steals" per big board rank do not equal performance.
This is exactly what OP/tweet author meant by saying "steals are not a thing," which apparently you didn't understand when you called the conclusion drawn by the tweet incorrect.
> "Steals" don't perform above draft expectation, while reaches can/do.
That's incorrect. Reaches outperform **board** expectation. They underperform **draft** expectation. The difference is split for minor reaches, while major reaches are closer to board EV than draft EV.
Put in layman's terms, if someone is 60th on the consensus board and a team drafts them at 30, they are likely to perform better than the 60th best player, but meaningfully worse than the 30th best player.
Whereas, if I'm reading it right, a player who is 30th on the consensus board and drafted at 60 is likely to play at the same level (and even slightly worse) than the 60th best player
> The logic of it is that for a reach to perform above expectation, one team has to have them valued at that higher draft position (the other teams see them as "wrong"). Whereas for a steal to perform above expectation, all the teams that passed on that player have to be "wrong".
I don't think this is the logic of the graph. If a reach outperforms expectation that means all the teams that didn't reach (however many were in realistic position to do so), *and all the big board analysts*, were wrong. A ton of people have to be wrong for a reach to outperform expectation.
The yellow line is really what is important here. I think it would probably be less confusing if they omitted the purple line entirely. With the yellow line you see that when the player is a "steal", they tend to not really do better than you'd expect for their draft position (in fact on average they're a little worse). The grey around it is above 0, so it *does* happen, but the average is definitely below it. I.e. with a steal you probably didn't outsmart anyone (and the reason that makes sense is because to have gotten a steal you have to have had several teams ahead of you be wrong). The purple line there is showing this in more pronounced fashion - when a player is a "steal", they do *really* poorly relative to the board (the thing that is causing them to be defined as a steal). This graph is showing that a "steal" player *virtually never* even meets much less outperforms the expectation of the board and the more they slip the more dramatic that becomes.
On the flip side, with reaches, you again look at the yellow line. There's usually a reason one team decided to reach, so you *do* see a positive value relative to the board at that extreme. However, the yellow line grounds things back to reality - yes, the board was wrong, but generally not by enough to make the reach a good pick - they still underperform expectation for their draft position. That's what is meant by "reaches do exist" - not that reaches do succeed sometimes, but that things that are *percieved to be a reach* (x-axis is perception) also are reaches in reality (y-axis is reality). And the reason that makes sense is because only one team has to be wrong and decide to reach for a guy for it to happen - 31 teams can agree with the board, and a reach can still happen.
It is for sure a confusing graph, though. I stared at it for 5-10 minutes trying to figure out what I was looking at. The most interesting part to me (now that I know how to read it) is how it shows that the bigger the steal, generally the worse the relative-to-actual-position results are - if you can slightly beat the board you might be ok, but if you dramatically beat the board you're probably actually in trouble (on average).
How am I supposed to interpret the yellow line…
Compared to their draft position, every player underperforms regardless of whether they were a steal or reach?
WAR is not a great tool to use for this calculation as it is heavily skewed towards valuing QBs. Most QBs are going to bust because they're taken high, but few of them are steals in a draft as the position gets drafted early.
For example Nick Bosa in 2023 had a WAR grade of .77. The highest graded QB was 2.7 and Jalen Hurts as the 12th best QB was ranked at 1.75.
I don't know which article this graph is from but when Timo did his trade chart he excluded QBs from the analysis for those reasons so I wouldn't be surprised to see them excluded here as well.
Ohh, I was completely lost cause I took "wrong" to mean teams that reach pick busts, but that's not what the chart seemed to show. Thanks, now I love this chart cause this 49ers draft class is like the third most reachiest.
No, were right the first time right. Look at the yellow line on the right side of the graph. That shows that reaches do underperform their draft expectation, and are busts. They just don't underperform as much as the media consensus implies.
Cole's TL;DR there is kind of misleading.
Steals *are* a thing they are just much more rare than reaches.
The article that graphic is plucked from (https://www.pff.com/news/draft-investigating-the-steals-and-reaches-in-the-2021-nfl-draft) lists Jeremiah Owusu-Koramoah (pick 52, rank 17) and Trey Smith (pick 50, rank 20) as "steals" in 2021, and I think most people would agree that those two picks did in fact turn out to be steals.
The TL;DR wasn't even needed because the title of the graph already achieves that and does so more accurately. Such is the "value" of twitter journalism.
The graph also visualizes the potential for steals to exist because the grey spread lines around the yellow average line do get up into positive WAR at the "steal" extreme (left).
It would have been more valuable for the tweet to be a brief explanation of how to read the graph (it's weird, and it took me a while to grasp on my own)
That’s like saying great players don’t exist because the vast majority of players don’t become great, a steal is a steal mainly due to the rarity of it. This whole graph is dumb
No I understand, it’s dumb bc you’re conflating uncommon and doesn’t exist. I don’t need a graph to explain to me that in most cases players fall in the draft for a valid reason lol
Cole and you are using steal in different ways. You are saying that any player that outperforms their draft position is a steal retrospectively. Whereas Cole is talking about saying a player *is a steal* right now based on where they went regardless of whether or not they work out in the future. When someone says Troy Franklin *is* a steal, they are saying that Troy Franklin has a better chance of working out than his 4th round price tag suggests, not that Troy Franklin is guaranteed to outperform his draft position.
Don't care for this analysis but this Moo dude is more smug than Ben Baldwin, which is something I thought was impossible.
Calling Harbaugh Joe Judge with better PR for drafting Alt is maybe the most asisine football thing I have ever read.
[That PFF on Stafford clip](https://youtu.be/7AFd-PbbnXI ) still has me fucking heated.
Granted it's not Moo talking about Stafford here but other PFF guys but i've seen some insanely poor takes from him as well.
I guess the "nice" thing about the xitter changes is it's a lot easier to avoid seeing them doubling and tripling down on some things.
Oh I know those guys. I recall watching a pre-draft video from them last year where they argued the Texans should take Levis over Stroud because Stroud lacked the physical upside and ceiling of Levis.
They bashed Pete Carroll for years for having a run first offense with Russ as the QB.
Then Russ in a pass heavy offense was the fiasco we all saw and nothing from them. From my outside point of view the Steelers offense are going to be very run heavy this year. Just watch that Russ is going to be good again.
Ehh...
Russ is far less mobile, and his arm has lost some power. I was never on the 'Let Russ Cook' train, but I think it's fair to say that Russ from 5-6 years ago would have been more capable of running a pass heavy offense than the Russ we saw in Denver.
Every time he piloted an efficient offense it was run heavy.
2015 to 2017 had good volume stats but the efficiency wasn't that good nor was the consistency.
If he sucks this year he is washed but doesn't change the fact that Pete knew it best how to build an offense around him.
You criticized analytics nerds for putting numbers in a model and claiming everything is 100% truth (strawman) in another comment.
You just right here claimed one of your assertions is unfalsifiable.
I also don't think you have enough sample size to draw a very rigorous conclusion of run-heavy offenses helping Wilson. Overall there is a negative correlation between dropbacks per game and efficiency in his 10 seasons as a Seahawk, but this comes from 3 of his 4 worst seasons being his top 3 in dropbacks/game.
So its really just 3 seasons that hold up this correlation, and we can't be *that* confident that his inefficiency in these seasons is specifically caused by the offense being more pass heavy. I've sure you're familiar with the hypothesis that inefficient teams often trail, leading them to pass more, and flipping the direction of the causation.
There's a lot of uncertainty, and as you said in another comment, all these analytics nerds are always 100% certain on models based on small sample size and don't re-evaluate them, something you're definitely far too clever to do.
Football analytics nerds are the worst.
I literally work on my PhD with mathematical modeling and I am working to begin my career in the R&D Field. With every model we have worked we simulate on the computer, collect the results, observe the real results and then according to the real results we modify the models.
These guys just place everything on the computer and think it is 100% truth...
What do you mean 3 years of data in a highly volatile environment with many human factors playing into it and changing rules means our predictions aren’t perfect?
That's the point of PFF. Football is so complex, that a system that looks at every player, on every snap, and assigns a grade, will be way more accurate than just TD/INT or number of catches.
PFF is really just using film to grade players, but in a very objective, standardized way.
People who hate it are similar to the people Billy Beane was fighting against in moneyball
I’m not a PFF hater but comparing it to Beane and baseball metrics is utterly absurd. Baseball’s metrics are completely objective and are on another stratosphere of depth than anything in football. It’s also a more analytically friendly sport in general because of the 1v1 nature of it and the enormous sample size.
PFF grades are very good, good, neutral, bad, very bad on every play and compiling that. It’s not objective because it still relies on the subjective view of the grader on each play.
Again, not a PFF hater - I agree that its grades are generally better than very stupidly basic things like passer rating and it’s pretty much the best thing we’ve got as casual consumers - just found the Beane comparison (real analytics that are actually used in front offices) absurd.
Errors are subjective. Only reason baseball works better is they have more games.
BUT, players only get 3-4 at bats. Max is around 650 at batts.
Whereas at least NFL players get about 1,000 snaps a year.
Errors (an incredibly small portion of at bats anyway) aren’t a counter argument for subjectively grading every at bat on a -2 to 2 scale.
1,000 snaps (which a vast majority of players don’t hit or come close to) a year isn’t a counter argument either when on any given play you can be doing dozens of different things. In baseball it’a more or less 1v1, in the NFL it’s 11v11 with a million different variables at play. And again, it’s *objective stats* not *subjective perceptions with incomplete data.*
It can’t be objective and standardized when you are requiring the opinions of multiple different people all working with incomplete information. The final number calculation may be standardized but the data collection component is not. That is the problem people have with touting PFF as an end all be all. There is a reason why NFL teams don’t care about buying grades from them and why it explicitly says on their website that they sell grades to college teams for recruiting/marketing purposes. The real value of PFF is the actual objective information such as formation tendencies that allow opponent scouting departments to be outsourced in some capacity.
They sell stats to teams. PFF has an awesome repository of advanced stats.
NFL front offices aren’t using the grades for anything other than contract negotiations. The grades are for you and me.
So they went from not using them at all, to using them for contract negotiations?
Seems like they are pretty important to teams then, and likely used for even more than that
Contract negotiations they use every stat in the book. That doesn’t mean they’re using them for *evaluation*, hence why they have player personnel. No one’s using passer rating for evaluation either.
They're used by agents. They have a whole page on their site about a new agent hub. If you want a list of what teams get from PFF, here it is:
[https://media.pff.com/2018/08/PFF-Play-Data-Fields.pdf](https://media.pff.com/2018/08/PFF-Play-Data-Fields.pdf)
I work in ML and have done analytics work for an NFL FO before. You're severely underestimating the work and effort a lot of the models have behind them.
Their audience when blogging is usually not particularly educated on modeling techniques, so they don't always write it up. Some of the guys in the analytics world are morons for sure, I'll be the first person to tell you the issues with a lot of it. But there's definitely a stark divide between those who "get it" and those who don't, and I wouldn't just blindly assume that some data you see in a tweet is from the latter group because it doesn't have the accompanying information you're used to seeing in an R&D or academic setting.
Unfortunately the louder ones are usually in that latter group, and PFF's data, charting, and grades are waaaay better than their analytics guys. But a lot of the actual football analytics world is people with very similar backgrounds producing work at very similar rigor levels to what you'd expect from a good R&D org.
You’re not often going to find the best and brightest minds in stats and data science working on football analytics.
I have a background in sports analytics and currently work in big tech. PFF reached out to me about a role with one of their machine learning teams, and the top end of their salary range was about a 60-70% paycut from what I currently make.
There are some really smart people in the space that love sports and are willing to forego a big payday to follow their passion. But a lot of the top talent has been siphoned to work in more lucrative corners of data science.
Do you, like, think these guys never modify their models and look to improve their methods.
Do you read 1 paragraph tweets and assume they're claiming everything they say as absolute truth?
I think you're attacking a bit of a strawman here. I know that Cole specifically acknowledges a ton of uncertainty in all of his writings.
PFF combines analytics stats with watching the film. They literally watch every player, on every play.
Are they perfect? No.
Are their grades better than 99% of people who shout football opinions? Yes.
22 players x 120 snaps a game x 16 games x 17 weeks = 718,080 snaps
A single player plays about 30 snaps a game.
Naturally that means that weekly grades are going to be flawed, but seasonal grades much more accurate.
Doesn't mean PFF sucks, it means football is complex
Until they stop saying shit like running backs don't matter or that teams should pass on 90% of plays I am not taking them seriously...
They think that Ken Dorsey got scapegoated lmao. I don't care much about EPA or whatever, we ran the ball more and thus our rested defense played better, it wasn't an accident our D improved too when Dorsey was fired. This is what I said above, they don't consider what happens on the field, just what the computer says.
The only thing it has been shown is that they take more punishment than ever (guys don't head hunt anymore but every one is stronger so they absord more punishment each carry), hence they last less.
However saying they don't matter one is a shitty thing to say about someone's job and second is blatantly false and I have some of the many examples.
Tannehill has been a mediocre qb for most of his career but when he had prime King Henry on the backfield he was statistically a top 5 QB.
Healthy Saquon got Daniel Jones a 40M contract, enough said.
Goff was great with Gurley, then ass when Gurley knees gave up. Lions got great backs then Goff became great again.
Browns running game went to shit last year when Chubb got hurt. They were able to acumulate volume stats with Flacco but the efficiency was shit, the defense getting that many stops made them win but is hoping your defense gets 10 stops a game sustainable?
49ers offense went from good with a variety of backs to best in the league with CMC.
> Tannehill has been a mediocre qb for most of his career but when he had prime King Henry on the backfield he was statistically a top 5 QB.
Look at this genius who thinks Henry matters more than AJ Brown. Look at his stats when Henry was still there and AJ Brown was not. Look at Hurts' statistical jump when he got Brown.
> Healthy Saquon got Daniel Jones a 40M contract, enough said.
Its enough said because it allows you to omit that Jones did not have good stats during that year.
> Goff was great with Gurley, then ass when Gurley knees gave up. Lions got great backs then Goff became great again.
Goff was good in 2022 pre-Gibbs. He also had young and healthy 2nd year Gurley pre-McVay. Gurley and Lions RBs played well when the OL played well. You keep doing this thing where you see a good offense and assume that its all happening because the RB has good stats, and when the RB has bad stats you assume the offense plays bad because of that.
You're really bad about assuming causation when you see a correlation. You see some combo of bad OL, bad coaching, bad QB stats, and bad RB stats and give all credit to the RB for the effectiveness or lack thereof.
> 49ers offense went from good with a variety of backs to best in the league with CMC.
Panthers 2022 offense also improved after trading CMC by the way. You'll notice that both teams changed QBs around that time, and CAR changed coach. Those things matter more.
Second half of 2021, Titans had AJ but not King Henry. The offense was ass, they were winning because they had the best defense in the league in that stretch. Tannehill threw away games against the Texans and Steelers, ST won the Saints game, entire team including Tannehill sucked against the Patriots, defense won the Rams, Jaguars and Dolphins games. Tannehill/AJ won the 49ers game to be fair. So the offense was inconsistent without King Henry.
Who cares about Jones stats, the Giants were winning and the offense was effective.
Goff was considerably better in 23 than 22. In 22 they were inconsistent on offense but adding Gibbs made their offense consistent.
Panthers offense improved due to better coaching and Wilks making them run the ball. With Rhule they were very pass heavy, CMC was basically a decoy. And Foreman/Chubba are very underrated.
In 2022-2023 they had Henry but not AJ. Their offense was worse. Also, in 2021 their non-Henry RBs had a higher ypc and rush success rate, so IDK how much you can even credit Henry for their success.
> Who cares about Jones stats, the Giants were winning and the offense was effective.
Their offense was 16th in points/drive. Saquon had at least 13 starts in 2021 and 2023, so they still did plenty of losing with him being healthy. Also, "wins are an RB stat" lmfao.
> Goff was considerably better in 23 than 22
Wrong. Better ANY/A, passer rating, and QBR in 2022. The Lions scored more points/drive in 2022 (2.48, no Gibbs) than 2023 (2.44, with Gibbs.) Gibbs did not matter for improving their offense.
You can't be asked to google basic stats dude, and just spout shit that's verifiably wrong. Quit wasting my time by making me google shit that you should have.
> Panthers offense improved due to better coaching and Wilks making them run the ball.
So, even putting aside that you're assuming rush attempts causes winning rather than winning causing rushing attempts, what does it say about the value of a premier RB that they can replace CMC with a guy that was so underrated he averaged 3.8 ypc in 2023, run the ball more, and score more?
Like, yes! Coaching matters a ton! That's why Goff/Gurley were shit with Fischer and good with McVay!
Wild inconsistent swings of Darnold/Mayfield >>> who plays RB. Mayfield on a heater with Rachaad White >>> Mayfield playing poorly with CMC.
On the other hand, saying Tannehill should be signed as a backup for the Chargers partly because he is experienced at handing the ball off is pretty funny
Joe Judge just needed to find a better PR guy to make the super bowl, have one of the best win % ever, then win a national title? Wow, what an idiot for not doing that!
How the hell do you calculate WAR for football? With how small a sample size you get from each season, and how wildly different the roles and responsibilities of each position can be, I struggle to believe you can calculate WAR in football in any meaningful way
You can’t, there are too many moving pieces on one play to obtain a positive result. Advanced football analytics had an article about this probably 15 years ago. PFF’s WAR calculation makes too many assumptions such as a team of replacement level players would go 3-13 without expanding on that (not to mention there are 17 games now) and is predicated on their grades which are subjective measurements assigned a numerical value.
> How the hell do you calculate WAR for football?
you don't. WAR and similar advanced stats work for baseball because it's (relatively) easy to isolate the performance of an individual player. (think how a batting matchup is distilled down to the pitcher vs. the hitter on a given play.)
you can't do that with football. too many moving pieces - did the play fail because the pass was too far in front of the WR (the QB's fault)? Or maybe the pass was rushed because the LT missed a block (LT's fault). Or perhaps the LT played the right assignment but passed the rusher to the LG, who missed the block (LG's fault). Or maybe the WR rounded out his route too much, causing him to be slow to the point of the catch (WR's fault). Or maybe it was some combination of these factors. Etc. etc.
i fucking hate how certain sites (PFF in particular) try to force some single-metric stat like WAR into a sport that, by its nature, defies the stat
> did the play fail because the pass was too far in front of the WR (the QB's fault)? Or maybe the pass was rushed because the LT missed a block (LT's fault). Or perhaps the LT played the right assignment but passed the rusher to the LG, who missed the block (LG's fault). Or maybe the WR rounded out his route too much, causing him to be slow to the point of the catch (WR's fault). Or maybe it was some combination of these factors. Etc. etc.
There are even more factors, too, which makes what PFF claims to do impossible - for any given one of those scenarios, you also have to account for what they were supposed to do, who decided they were supposed to do that, and why. Generally a QB sets their protection. Did that LT miss a block because the QB misread the defense and called a slide protection that was wrong? Or did the LT just make a mistake? What if the play was wrong because the coach sent them out without the right checks? How do you realistically account for the difference between a rookie who is just running the system they were taught and was sent out there without an answer, vs. a veteran field general like Rodgers who has such command over the system that he can get into a proper play regardless of what was called in the huddle? At least how do you account for that for purposes of "grades" (you'll see results on the field obviously - team success rate will be higher etc., but how do you actually numerically attribute that to the QB?)
The sample size isn't small for the best players. 60 snaps a game x 17 games is 1,020 data points.
Obviously it would be more accurate with 10,000 data points, but that's going to be an issue with any box score stat, not just WAR.
Plus, we know the eye test is very flawed, so for the average fan, WAR is a very good stat to learn about.
1,020 data points may or may not be a lot. It depends on what’s being estimated and how noisy the process generating the data is. For football, it’s going to be very noisy because so many different things happen during a snap. Moreover, a lot of those data points are basically not comparable, for example, comparing a players performance on a run play vs a passing play likely means evaluating different skill sets.
Counting stats are bad because… you don’t watch the games!
Advanced stats are bad because… they just don’t apply ok!
Film grading is bad because… the eye test doesn’t mean anything!
"Don't exist" in this case just means "we're almost always wrong when we call a guy a steal just because he was drafted way lower than big boards predicted". Meanwhile, calling a guy a reach for in the inverse actually tends to be correct.
Obviously guys overperform the expectation of where they were drafted all the time - we're just not very good at predicting that, and there's no correlation with "falling" from a big board prediction and overperforming draft value.
"If we cannot measure it, it doesn't exist." is also why the nerds are so insistent momentum doesn't exist in sports even though every athlete to ever play the game disagrees.
Except he did measure it, and the "doesn't exist" is just attention-grabbing hyperbole to mean "rare".
His actual point is that guys labelled as steals on draft day often don't turn to be that, whereas guys labelled as reaches *do* tend to underperform their pick \#.
I think what he's saying is that a "steal" (a player who fell further in the draft than expected) isn't any more likely to perform above their draft position than a typical draftee. While players who were drafted higher than expected ARE more likely on average to outperform their draft position.
What this graph actually says is the nfl is better at evaluating players than the media. Players are more likely to preform based on where they were selected than where pre draft buzz expected them to go.!
Not exactly. The graph is saying that the aggregate of teams is better than the aggregate of media at judging players pre draft. That's what happens when a player falls and every team has an opportunity to decide they weren't worth drafting. But when one team reaches on a player that is only one team making that decision and that player is typically worse than their draft position would suggest.
It’s really just a measurement issue. When someone falls we can see all the teams that passed on them. We can’t really tell if it’s a reach because once a player is drafted nobody after can draft them. So you don’t know if they would have been picked by the next 5 teams in a row or sat on the board for 2 more rounds
Right we can know that a consensus of NFL teams were lower on a player but we can't know if the consensus of teams were higher on a player. Although given that these players often perform worse than their draft position, I imagine that usually these players are reaches in the eyes of teams as well. Within the top 100 the consensus big board does a pretty good job of predicting draft position all things considered.
An interesting caveat of this is that the graph clearly shows that reaches *do* overall overperform their big board status pretty consistently - they just get reached on too early and underperform their real pick.
> While players who were drafted higher than expected ARE more likely on average to outperform their draft position.
Inverse; they're more likely to *underperform* their draft position. He attributes this to "steals" requiring the collective wisdom of NFL FOs to be wrong, while "reaches" pit just one team's FO against the wisdom of the collective media scouts.
Reaches are more common than steals because a reach requires fewer things to happen, namely you just need a single team to overvalue a player. For a steal to occur you need many teams to pass on a player, either because they don’t need a player at that position or he has some latent talent that hasn’t manifested yet so he is undervalued. The number of teams that need to pass on that player for them to go much later than they should is large most of the time.
However, there’s a lot of problems with this analysis. For example, other users have mentioned issues with the WAR stat (and I agree, football is not baseball and we can’t isolate events well enough to estimate WAR with the data available) that PFF made to try and rank players here. However my bigger issue is that there is no way to prescribe an ordering on football players, especially due to vast positional differences. You can’t compare an offensive lineman and a cornerback, and the position at which players go is highly dependent on what is going on in the league (e.g., RBs are less valuable in the current NFL so they tend to go much later than they used to) and how other prospects are viewed (e.g., if there is only one good RB in the draft and the rest are very obviously shit, the good RB will go sooner than if the class is deep because the cost on missing out on that RB for needy teams is high).
> However, there’s a lot of problems with this analysis. For example, other users have mentioned issues with the WAR stat (and I agree, football is not baseball and we can’t isolate events well enough to estimate WAR with the data available) that PFF made to try and rank players here.
Fair, but
>However my bigger issue is that there is no way to prescribe an ordering on football players, especially due to vast positional differences.
This is the same complaint. WAR is an effort to do exactly this.
>(e.g., RBs are less valuable in the current NFL so they tend to go much later than they used to)
This is reflected in WAR.
Players who are generally considered reaches immediately post draft are usually accurately labeled because it just needs one team to incorrectly evaluate them
Players generally considered steals post draft usually aren't because it requires 31 others teams to be wrong in their evaluation of the player if they aren't going earlier
I don’t really think WAR is a great stat but I disagree with your interpretation. I think what it is saying is that when a player is a reach they are basically always significantly worse than the WAR expectation for a player at that pick.
If the reach player was instead picked where the board ranked them then they would usually outperform than the WAR expectations for that pick and occasionally be worse.
Conversely when a player is a steal they generally do worse than the WAR expected for the pick where they are selected but on occasion they do better.
If the steal player was picked at the pick where the board expected them to be picked (which is above where they would be considered a steal) then they would almost always be significantly worse than expected WAR.
This means that on average steals are not actually steals and reaches are basically always bad. Though because the steal spread goes above expectations it means steals can be good sometimes.
I think what is interesting is that reaches usually outperform their board ranking. To me that says that reaches are generally underrated by the big board but usually the team that reaches for them significantly overrates them.
> I think what is interesting is that reaches usually outperform their board ranking. To me that says that reaches are generally underrated by the big board but usually the team that reaches for them significantly overrates them.
Yeah, teams are blasted for reaches all time, and rightfully so - but the data shows that they *are* actually identifying something the media big boards aren't, they just don't get good value for it. That's rather interesting.
Anyone know what this is? Class? Anyone? Anyone? Anyone seen this before? The Reach-Steal Curve. Anyone know what this says? It says that at this point on the curve, you will get exactly the same amount of benefit as at this point. This is very controversial. Does anyone know what Vice President Bush called this in 1980? Anyone? Something-d-o-o football. "Voodoo" football.
How is the yellow line always below 0?
* Pick is a steal? Does slightly worse than EV of the pick.
* Pick is even with expectation? (actually peaks at a slight steal) Does equal to EV of the pick.
* Pick is a reach? Does a lot worse than the EV of the pick.
Shouldn't the integral of the yellow line with respect to the total number of draft picks at each X value be 0? Don't you have to exceed EV somewhere?
The yellow line is an average line. The light grey is the spread, and is sometimes above 0. That said, the fact that it never exceeds 0 is really the observation here. That you can do worse than expectation, but on average you cannot do better than expectation, is exactly what is meant by the claim that there really is no such thing as a steal. Still, the grey line does exceed 0 which means that there *are* true steals - but when you average them in with everyone else who looked like as big of a steal the average comes to 0 or even worse than that.
I don't think this fully addressed what I said.
Obviously some individual picks exceed expectation.
What I said was that at every (actual-expected,) X value the EV (expected value, not the high end of the spread. I'm perfectly aware what that grey band means, thanks) is 0 or less.
How do 0 (actual-expected) values on the x axis have a significantly positive EV?
My only guess would be that at some point the yellow line barely crosses 0, and that ~95% of the actual picks are in that small (actual-expected) range, causing the total average value among all picks made to be 0.
Steals kind of have to exist for reaches too right? Like anytime a bad pick happens, all following picks are implicitly better. The WAR above expectation for a total draft should add up to 0 or else the expectation was too high
Tbh the graph makes it look like the ideal spot to pick a guy is when they've dropped a few spots, it's just the guys who drop a ton who don't really work as steals.
He's right, but worded it in a confusing way. Simplified:
If 20 teams passed on a perceived top prospect, the likelihood they are all wrong about that prospect being worth their picks is not high. This is shown in the data, that "steals" perform just as well as normal players drafted in that spot.
But if 1 team picks a perceived reach, the likelihood they are wrong is higher. That player may have fallen another 30 picks, because it's easier for 1 team to be wrong than multiple. Reaches perform worse than normal players drafted in that spot.
Thats just bs. A steal doesnt need several teams to be wrong. The guys doesnt understand any risk taking. And dreams that teams drafted based on how good a player is without thinking about his position
There is more to a prospect than film and measurables. They can be bigger stronger faster and look good on game day against lesser competition but if they don't put in the work it will catch up to them.
PFF is not analytics. PFF WAR is not a real stat because it is derived from PFF grade, which is not a stat is a qualitative opinion fudged to look like a stat
Pfft, whatever, nerd. Every pick I like is a steal.
But honestly, hyping up and getting excited for picks I like is a lot of fun so why wouldn't I do it? It's not like our collective opinion matters at all These people who are like "don't get too excited, statistics say he could bust blah blah blah" are miserable
As a Patriots fan who watched Belichick draft for 20 years, I can personally attest that "reaches" are definitely a thing. I day dream about having Harrison/Wayne or Hill/Kelce with Brady for 5+ years, he got 1 with a healthy Moss/Welker, and look what happened, and Welker is not in Hill/Kelce/Wayne/Harrisons class at all.
You poor thing
I mean of course, champagne problems. But a lot of the "Brady = system QB" was just him playing with guys who weren't even Pro Bowl Alternates. Imagine if from 2001-2006, Brady had Faulk, James, Harrison, Wayne, Clark and Manning had Brown, Patten, Fauria?, Branch. No one would've been calling Brady a system QB, even though he would've been exactly as talented in that scenario, as he was in the real one.
Imagine if Manning had the Patriots defense. You saw what happened when he got their kicker.
Manning with Harrison/Wayne/James/Clark from 1999 to 2005 scored the following in his losses: 16, 17, 0, 14, 3, 18 If he had Brown/Patten/Givens/etc, he would've been obviously much worse. Also the Colts defense had Freeney, Mathias, Sanders, etc. They were very good.
You make up these fake hypotheticals and present them as real facts.
How am I presenting them as facts? It is my opinion (not a fact) that Manning would score less points with Brown/Patten/Givens than Harrison/Wayne/Clark/James. Given that 3 of 4 of those players are HOFers, I think it's a reasonable opinion. Additionally, given that Freeney, Mathias, Sanders were All-Pros at premium positions, seems likely their defense was quite good.
If Tom Brady was throwing to them earlier in his career he'd have been a different player and may not even have won any of the Super Bowls. Additionally, given that stats exist.. Manning did not have a "quite good" defense. Especially when compared to Brady's "quite elite" defense.
Explain how Brady becomes a worse player when he gets to start in a better situation? Literally everything we know about young QBs shows, a better situation makes a better QB. Also Colts had 2 Top 3 defenses, and 2 other Top 10 defenses from 2003-2009. Same as the Pats.
I don't think they make violins small enough to accompany this post
Better to spend on the D when you have a QB like Brady. Same is happening with Mahomes right now.
He made up for it by cheating
I don't know if it's just me, but that graph tells me nothing.
I looked at this draft like I understood it. Fake it till you make it!
the conclusion drawn from it is completely wrong as well. I wish I could get paid for being so outwardly wrong while standing my ground
Welcome to your new job as a weatherman or NFL ref
Due to the author saying literally the same thing as in the tweet, please explain why?
The conclusion drawn is supported by a correct reading of the graph. Just say you can't understand it
summary: * the tweet says "steals are not a thing" * the graph says "steals are rare" * the consensus is that steals are a thing, and maybe they are rare, but they are a thing * adding final reminder that draft perception and big board do not equal performance just say you can't understand it
> the tweet says "steals are not a thing" > the graph says "steals are rare" Are you not familiar with how people write on twitter? These two have effectively the same meaning in internet shorthand. Anyways, do you understand that picks that are generally viewed as "steals" are the picks where players were taken far before their big board ranks? This part: > adding final reminder that draft perception and big board do not equal performance means that "steals" per big board rank do not equal performance. This is exactly what OP/tweet author meant by saying "steals are not a thing," which apparently you didn't understand when you called the conclusion drawn by the tweet incorrect.
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> "Steals" don't perform above draft expectation, while reaches can/do. That's incorrect. Reaches outperform **board** expectation. They underperform **draft** expectation. The difference is split for minor reaches, while major reaches are closer to board EV than draft EV.
Put in layman's terms, if someone is 60th on the consensus board and a team drafts them at 30, they are likely to perform better than the 60th best player, but meaningfully worse than the 30th best player.
Whereas, if I'm reading it right, a player who is 30th on the consensus board and drafted at 60 is likely to play at the same level (and even slightly worse) than the 60th best player
Correct
> The logic of it is that for a reach to perform above expectation, one team has to have them valued at that higher draft position (the other teams see them as "wrong"). Whereas for a steal to perform above expectation, all the teams that passed on that player have to be "wrong". I don't think this is the logic of the graph. If a reach outperforms expectation that means all the teams that didn't reach (however many were in realistic position to do so), *and all the big board analysts*, were wrong. A ton of people have to be wrong for a reach to outperform expectation. The yellow line is really what is important here. I think it would probably be less confusing if they omitted the purple line entirely. With the yellow line you see that when the player is a "steal", they tend to not really do better than you'd expect for their draft position (in fact on average they're a little worse). The grey around it is above 0, so it *does* happen, but the average is definitely below it. I.e. with a steal you probably didn't outsmart anyone (and the reason that makes sense is because to have gotten a steal you have to have had several teams ahead of you be wrong). The purple line there is showing this in more pronounced fashion - when a player is a "steal", they do *really* poorly relative to the board (the thing that is causing them to be defined as a steal). This graph is showing that a "steal" player *virtually never* even meets much less outperforms the expectation of the board and the more they slip the more dramatic that becomes. On the flip side, with reaches, you again look at the yellow line. There's usually a reason one team decided to reach, so you *do* see a positive value relative to the board at that extreme. However, the yellow line grounds things back to reality - yes, the board was wrong, but generally not by enough to make the reach a good pick - they still underperform expectation for their draft position. That's what is meant by "reaches do exist" - not that reaches do succeed sometimes, but that things that are *percieved to be a reach* (x-axis is perception) also are reaches in reality (y-axis is reality). And the reason that makes sense is because only one team has to be wrong and decide to reach for a guy for it to happen - 31 teams can agree with the board, and a reach can still happen. It is for sure a confusing graph, though. I stared at it for 5-10 minutes trying to figure out what I was looking at. The most interesting part to me (now that I know how to read it) is how it shows that the bigger the steal, generally the worse the relative-to-actual-position results are - if you can slightly beat the board you might be ok, but if you dramatically beat the board you're probably actually in trouble (on average).
How am I supposed to interpret the yellow line… Compared to their draft position, every player underperforms regardless of whether they were a steal or reach?
WAR is not a great tool to use for this calculation as it is heavily skewed towards valuing QBs. Most QBs are going to bust because they're taken high, but few of them are steals in a draft as the position gets drafted early. For example Nick Bosa in 2023 had a WAR grade of .77. The highest graded QB was 2.7 and Jalen Hurts as the 12th best QB was ranked at 1.75.
I don't know which article this graph is from but when Timo did his trade chart he excluded QBs from the analysis for those reasons so I wouldn't be surprised to see them excluded here as well.
WAR doesn’t exist in football so that’s an immediate fault
Ohh, I was completely lost cause I took "wrong" to mean teams that reach pick busts, but that's not what the chart seemed to show. Thanks, now I love this chart cause this 49ers draft class is like the third most reachiest.
No, were right the first time right. Look at the yellow line on the right side of the graph. That shows that reaches do underperform their draft expectation, and are busts. They just don't underperform as much as the media consensus implies.
Gotcha, I think I get it now. Have to hate this chart now though.
Cole's TL;DR there is kind of misleading. Steals *are* a thing they are just much more rare than reaches. The article that graphic is plucked from (https://www.pff.com/news/draft-investigating-the-steals-and-reaches-in-the-2021-nfl-draft) lists Jeremiah Owusu-Koramoah (pick 52, rank 17) and Trey Smith (pick 50, rank 20) as "steals" in 2021, and I think most people would agree that those two picks did in fact turn out to be steals.
The TL;DR wasn't even needed because the title of the graph already achieves that and does so more accurately. Such is the "value" of twitter journalism. The graph also visualizes the potential for steals to exist because the grey spread lines around the yellow average line do get up into positive WAR at the "steal" extreme (left). It would have been more valuable for the tweet to be a brief explanation of how to read the graph (it's weird, and it took me a while to grasp on my own)
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That’s like saying great players don’t exist because the vast majority of players don’t become great, a steal is a steal mainly due to the rarity of it. This whole graph is dumb
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No I understand, it’s dumb bc you’re conflating uncommon and doesn’t exist. I don’t need a graph to explain to me that in most cases players fall in the draft for a valid reason lol
Cole and you are using steal in different ways. You are saying that any player that outperforms their draft position is a steal retrospectively. Whereas Cole is talking about saying a player *is a steal* right now based on where they went regardless of whether or not they work out in the future. When someone says Troy Franklin *is* a steal, they are saying that Troy Franklin has a better chance of working out than his 4th round price tag suggests, not that Troy Franklin is guaranteed to outperform his draft position.
Don't care for this analysis but this Moo dude is more smug than Ben Baldwin, which is something I thought was impossible. Calling Harbaugh Joe Judge with better PR for drafting Alt is maybe the most asisine football thing I have ever read.
Dude said Stafford was a replacement level quarterback for years and then got quiet after he won a Super Bowl
[That PFF on Stafford clip](https://youtu.be/7AFd-PbbnXI ) still has me fucking heated. Granted it's not Moo talking about Stafford here but other PFF guys but i've seen some insanely poor takes from him as well. I guess the "nice" thing about the xitter changes is it's a lot easier to avoid seeing them doubling and tripling down on some things.
Oh I know those guys. I recall watching a pre-draft video from them last year where they argued the Texans should take Levis over Stroud because Stroud lacked the physical upside and ceiling of Levis.
They bashed Pete Carroll for years for having a run first offense with Russ as the QB. Then Russ in a pass heavy offense was the fiasco we all saw and nothing from them. From my outside point of view the Steelers offense are going to be very run heavy this year. Just watch that Russ is going to be good again.
Ehh... Russ is far less mobile, and his arm has lost some power. I was never on the 'Let Russ Cook' train, but I think it's fair to say that Russ from 5-6 years ago would have been more capable of running a pass heavy offense than the Russ we saw in Denver.
And if he still sucks will you admit that he's just cooked and that it being run-heavy had nothing to do with his aging curve?
Every time he piloted an efficient offense it was run heavy. 2015 to 2017 had good volume stats but the efficiency wasn't that good nor was the consistency. If he sucks this year he is washed but doesn't change the fact that Pete knew it best how to build an offense around him.
You criticized analytics nerds for putting numbers in a model and claiming everything is 100% truth (strawman) in another comment. You just right here claimed one of your assertions is unfalsifiable. I also don't think you have enough sample size to draw a very rigorous conclusion of run-heavy offenses helping Wilson. Overall there is a negative correlation between dropbacks per game and efficiency in his 10 seasons as a Seahawk, but this comes from 3 of his 4 worst seasons being his top 3 in dropbacks/game. So its really just 3 seasons that hold up this correlation, and we can't be *that* confident that his inefficiency in these seasons is specifically caused by the offense being more pass heavy. I've sure you're familiar with the hypothesis that inefficient teams often trail, leading them to pass more, and flipping the direction of the causation. There's a lot of uncertainty, and as you said in another comment, all these analytics nerds are always 100% certain on models based on small sample size and don't re-evaluate them, something you're definitely far too clever to do.
being smug is a pre-requisite for any blogger
Football analytics nerds are the worst. I literally work on my PhD with mathematical modeling and I am working to begin my career in the R&D Field. With every model we have worked we simulate on the computer, collect the results, observe the real results and then according to the real results we modify the models. These guys just place everything on the computer and think it is 100% truth...
What do you mean 3 years of data in a highly volatile environment with many human factors playing into it and changing rules means our predictions aren’t perfect?
That's the point of PFF. Football is so complex, that a system that looks at every player, on every snap, and assigns a grade, will be way more accurate than just TD/INT or number of catches. PFF is really just using film to grade players, but in a very objective, standardized way. People who hate it are similar to the people Billy Beane was fighting against in moneyball
I’m not a PFF hater but comparing it to Beane and baseball metrics is utterly absurd. Baseball’s metrics are completely objective and are on another stratosphere of depth than anything in football. It’s also a more analytically friendly sport in general because of the 1v1 nature of it and the enormous sample size. PFF grades are very good, good, neutral, bad, very bad on every play and compiling that. It’s not objective because it still relies on the subjective view of the grader on each play. Again, not a PFF hater - I agree that its grades are generally better than very stupidly basic things like passer rating and it’s pretty much the best thing we’ve got as casual consumers - just found the Beane comparison (real analytics that are actually used in front offices) absurd.
Errors are subjective. Only reason baseball works better is they have more games. BUT, players only get 3-4 at bats. Max is around 650 at batts. Whereas at least NFL players get about 1,000 snaps a year.
Errors (an incredibly small portion of at bats anyway) aren’t a counter argument for subjectively grading every at bat on a -2 to 2 scale. 1,000 snaps (which a vast majority of players don’t hit or come close to) a year isn’t a counter argument either when on any given play you can be doing dozens of different things. In baseball it’a more or less 1v1, in the NFL it’s 11v11 with a million different variables at play. And again, it’s *objective stats* not *subjective perceptions with incomplete data.*
It can’t be objective and standardized when you are requiring the opinions of multiple different people all working with incomplete information. The final number calculation may be standardized but the data collection component is not. That is the problem people have with touting PFF as an end all be all. There is a reason why NFL teams don’t care about buying grades from them and why it explicitly says on their website that they sell grades to college teams for recruiting/marketing purposes. The real value of PFF is the actual objective information such as formation tendencies that allow opponent scouting departments to be outsourced in some capacity.
1) They sell grades to teams. You have zero proof they don't. 2) Just because they aren't perfect, doesn't mean they are bad
They sell stats to teams. PFF has an awesome repository of advanced stats. NFL front offices aren’t using the grades for anything other than contract negotiations. The grades are for you and me.
So they went from not using them at all, to using them for contract negotiations? Seems like they are pretty important to teams then, and likely used for even more than that
Contract negotiations they use every stat in the book. That doesn’t mean they’re using them for *evaluation*, hence why they have player personnel. No one’s using passer rating for evaluation either.
They're used by agents. They have a whole page on their site about a new agent hub. If you want a list of what teams get from PFF, here it is: [https://media.pff.com/2018/08/PFF-Play-Data-Fields.pdf](https://media.pff.com/2018/08/PFF-Play-Data-Fields.pdf)
I work in ML and have done analytics work for an NFL FO before. You're severely underestimating the work and effort a lot of the models have behind them. Their audience when blogging is usually not particularly educated on modeling techniques, so they don't always write it up. Some of the guys in the analytics world are morons for sure, I'll be the first person to tell you the issues with a lot of it. But there's definitely a stark divide between those who "get it" and those who don't, and I wouldn't just blindly assume that some data you see in a tweet is from the latter group because it doesn't have the accompanying information you're used to seeing in an R&D or academic setting. Unfortunately the louder ones are usually in that latter group, and PFF's data, charting, and grades are waaaay better than their analytics guys. But a lot of the actual football analytics world is people with very similar backgrounds producing work at very similar rigor levels to what you'd expect from a good R&D org.
You’re not often going to find the best and brightest minds in stats and data science working on football analytics. I have a background in sports analytics and currently work in big tech. PFF reached out to me about a role with one of their machine learning teams, and the top end of their salary range was about a 60-70% paycut from what I currently make. There are some really smart people in the space that love sports and are willing to forego a big payday to follow their passion. But a lot of the top talent has been siphoned to work in more lucrative corners of data science.
Do you, like, think these guys never modify their models and look to improve their methods. Do you read 1 paragraph tweets and assume they're claiming everything they say as absolute truth? I think you're attacking a bit of a strawman here. I know that Cole specifically acknowledges a ton of uncertainty in all of his writings.
PFF combines analytics stats with watching the film. They literally watch every player, on every play. Are they perfect? No. Are their grades better than 99% of people who shout football opinions? Yes.
>They literally watch every player, on every play. They *say* they do, but there have been quite a few examples that cast doubt on this claim
22 players x 120 snaps a game x 16 games x 17 weeks = 718,080 snaps A single player plays about 30 snaps a game. Naturally that means that weekly grades are going to be flawed, but seasonal grades much more accurate. Doesn't mean PFF sucks, it means football is complex
Until they stop saying shit like running backs don't matter or that teams should pass on 90% of plays I am not taking them seriously... They think that Ken Dorsey got scapegoated lmao. I don't care much about EPA or whatever, we ran the ball more and thus our rested defense played better, it wasn't an accident our D improved too when Dorsey was fired. This is what I said above, they don't consider what happens on the field, just what the computer says.
The last 10 years have proven them right on running backs
The only thing it has been shown is that they take more punishment than ever (guys don't head hunt anymore but every one is stronger so they absord more punishment each carry), hence they last less. However saying they don't matter one is a shitty thing to say about someone's job and second is blatantly false and I have some of the many examples. Tannehill has been a mediocre qb for most of his career but when he had prime King Henry on the backfield he was statistically a top 5 QB. Healthy Saquon got Daniel Jones a 40M contract, enough said. Goff was great with Gurley, then ass when Gurley knees gave up. Lions got great backs then Goff became great again. Browns running game went to shit last year when Chubb got hurt. They were able to acumulate volume stats with Flacco but the efficiency was shit, the defense getting that many stops made them win but is hoping your defense gets 10 stops a game sustainable? 49ers offense went from good with a variety of backs to best in the league with CMC.
> Tannehill has been a mediocre qb for most of his career but when he had prime King Henry on the backfield he was statistically a top 5 QB. Look at this genius who thinks Henry matters more than AJ Brown. Look at his stats when Henry was still there and AJ Brown was not. Look at Hurts' statistical jump when he got Brown. > Healthy Saquon got Daniel Jones a 40M contract, enough said. Its enough said because it allows you to omit that Jones did not have good stats during that year. > Goff was great with Gurley, then ass when Gurley knees gave up. Lions got great backs then Goff became great again. Goff was good in 2022 pre-Gibbs. He also had young and healthy 2nd year Gurley pre-McVay. Gurley and Lions RBs played well when the OL played well. You keep doing this thing where you see a good offense and assume that its all happening because the RB has good stats, and when the RB has bad stats you assume the offense plays bad because of that. You're really bad about assuming causation when you see a correlation. You see some combo of bad OL, bad coaching, bad QB stats, and bad RB stats and give all credit to the RB for the effectiveness or lack thereof. > 49ers offense went from good with a variety of backs to best in the league with CMC. Panthers 2022 offense also improved after trading CMC by the way. You'll notice that both teams changed QBs around that time, and CAR changed coach. Those things matter more.
Second half of 2021, Titans had AJ but not King Henry. The offense was ass, they were winning because they had the best defense in the league in that stretch. Tannehill threw away games against the Texans and Steelers, ST won the Saints game, entire team including Tannehill sucked against the Patriots, defense won the Rams, Jaguars and Dolphins games. Tannehill/AJ won the 49ers game to be fair. So the offense was inconsistent without King Henry. Who cares about Jones stats, the Giants were winning and the offense was effective. Goff was considerably better in 23 than 22. In 22 they were inconsistent on offense but adding Gibbs made their offense consistent. Panthers offense improved due to better coaching and Wilks making them run the ball. With Rhule they were very pass heavy, CMC was basically a decoy. And Foreman/Chubba are very underrated.
In 2022-2023 they had Henry but not AJ. Their offense was worse. Also, in 2021 their non-Henry RBs had a higher ypc and rush success rate, so IDK how much you can even credit Henry for their success. > Who cares about Jones stats, the Giants were winning and the offense was effective. Their offense was 16th in points/drive. Saquon had at least 13 starts in 2021 and 2023, so they still did plenty of losing with him being healthy. Also, "wins are an RB stat" lmfao. > Goff was considerably better in 23 than 22 Wrong. Better ANY/A, passer rating, and QBR in 2022. The Lions scored more points/drive in 2022 (2.48, no Gibbs) than 2023 (2.44, with Gibbs.) Gibbs did not matter for improving their offense. You can't be asked to google basic stats dude, and just spout shit that's verifiably wrong. Quit wasting my time by making me google shit that you should have. > Panthers offense improved due to better coaching and Wilks making them run the ball. So, even putting aside that you're assuming rush attempts causes winning rather than winning causing rushing attempts, what does it say about the value of a premier RB that they can replace CMC with a guy that was so underrated he averaged 3.8 ypc in 2023, run the ball more, and score more? Like, yes! Coaching matters a ton! That's why Goff/Gurley were shit with Fischer and good with McVay! Wild inconsistent swings of Darnold/Mayfield >>> who plays RB. Mayfield on a heater with Rachaad White >>> Mayfield playing poorly with CMC.
On the other hand, saying Tannehill should be signed as a backup for the Chargers partly because he is experienced at handing the ball off is pretty funny
Joe Judge just needed to find a better PR guy to make the super bowl, have one of the best win % ever, then win a national title? Wow, what an idiot for not doing that!
How the hell do you calculate WAR for football? With how small a sample size you get from each season, and how wildly different the roles and responsibilities of each position can be, I struggle to believe you can calculate WAR in football in any meaningful way
You can’t, there are too many moving pieces on one play to obtain a positive result. Advanced football analytics had an article about this probably 15 years ago. PFF’s WAR calculation makes too many assumptions such as a team of replacement level players would go 3-13 without expanding on that (not to mention there are 17 games now) and is predicated on their grades which are subjective measurements assigned a numerical value.
> How the hell do you calculate WAR for football? you don't. WAR and similar advanced stats work for baseball because it's (relatively) easy to isolate the performance of an individual player. (think how a batting matchup is distilled down to the pitcher vs. the hitter on a given play.) you can't do that with football. too many moving pieces - did the play fail because the pass was too far in front of the WR (the QB's fault)? Or maybe the pass was rushed because the LT missed a block (LT's fault). Or perhaps the LT played the right assignment but passed the rusher to the LG, who missed the block (LG's fault). Or maybe the WR rounded out his route too much, causing him to be slow to the point of the catch (WR's fault). Or maybe it was some combination of these factors. Etc. etc. i fucking hate how certain sites (PFF in particular) try to force some single-metric stat like WAR into a sport that, by its nature, defies the stat
> did the play fail because the pass was too far in front of the WR (the QB's fault)? Or maybe the pass was rushed because the LT missed a block (LT's fault). Or perhaps the LT played the right assignment but passed the rusher to the LG, who missed the block (LG's fault). Or maybe the WR rounded out his route too much, causing him to be slow to the point of the catch (WR's fault). Or maybe it was some combination of these factors. Etc. etc. There are even more factors, too, which makes what PFF claims to do impossible - for any given one of those scenarios, you also have to account for what they were supposed to do, who decided they were supposed to do that, and why. Generally a QB sets their protection. Did that LT miss a block because the QB misread the defense and called a slide protection that was wrong? Or did the LT just make a mistake? What if the play was wrong because the coach sent them out without the right checks? How do you realistically account for the difference between a rookie who is just running the system they were taught and was sent out there without an answer, vs. a veteran field general like Rodgers who has such command over the system that he can get into a proper play regardless of what was called in the huddle? At least how do you account for that for purposes of "grades" (you'll see results on the field obviously - team success rate will be higher etc., but how do you actually numerically attribute that to the QB?)
The sample size isn't small for the best players. 60 snaps a game x 17 games is 1,020 data points. Obviously it would be more accurate with 10,000 data points, but that's going to be an issue with any box score stat, not just WAR. Plus, we know the eye test is very flawed, so for the average fan, WAR is a very good stat to learn about.
1,020 data points may or may not be a lot. It depends on what’s being estimated and how noisy the process generating the data is. For football, it’s going to be very noisy because so many different things happen during a snap. Moreover, a lot of those data points are basically not comparable, for example, comparing a players performance on a run play vs a passing play likely means evaluating different skill sets.
The eye test is flawed which is why you should not take PFF grades as gospel. All they do is eye test.
Counting stats are bad because… you don’t watch the games! Advanced stats are bad because… they just don’t apply ok! Film grading is bad because… the eye test doesn’t mean anything!
Bingo!
Just because you need multiple teams to be wrong doesn’t mean steals don’t exist. That’s a silly take. Teams are “wrong” all of the time.
Teams are wrong in every single draft. It's rare that a team nails all their picks.
"Don't exist" in this case just means "we're almost always wrong when we call a guy a steal just because he was drafted way lower than big boards predicted". Meanwhile, calling a guy a reach for in the inverse actually tends to be correct. Obviously guys overperform the expectation of where they were drafted all the time - we're just not very good at predicting that, and there's no correlation with "falling" from a big board prediction and overperforming draft value.
"If we cannot measure it, it doesn't exist." is also why the nerds are so insistent momentum doesn't exist in sports even though every athlete to ever play the game disagrees.
Except he did measure it, and the "doesn't exist" is just attention-grabbing hyperbole to mean "rare". His actual point is that guys labelled as steals on draft day often don't turn to be that, whereas guys labelled as reaches *do* tend to underperform their pick \#.
Did we really need to run some sort of statistical model to tell us that it is harder to get a steal than draft a bust?
You'd be surprised how many surface level takes need to be verified with "empirical analysis" by PFF or someone else for people to finally believe it
I think what he's saying is that a "steal" (a player who fell further in the draft than expected) isn't any more likely to perform above their draft position than a typical draftee. While players who were drafted higher than expected ARE more likely on average to outperform their draft position.
What this graph actually says is the nfl is better at evaluating players than the media. Players are more likely to preform based on where they were selected than where pre draft buzz expected them to go.!
Not exactly. The graph is saying that the aggregate of teams is better than the aggregate of media at judging players pre draft. That's what happens when a player falls and every team has an opportunity to decide they weren't worth drafting. But when one team reaches on a player that is only one team making that decision and that player is typically worse than their draft position would suggest.
It’s really just a measurement issue. When someone falls we can see all the teams that passed on them. We can’t really tell if it’s a reach because once a player is drafted nobody after can draft them. So you don’t know if they would have been picked by the next 5 teams in a row or sat on the board for 2 more rounds
Right we can know that a consensus of NFL teams were lower on a player but we can't know if the consensus of teams were higher on a player. Although given that these players often perform worse than their draft position, I imagine that usually these players are reaches in the eyes of teams as well. Within the top 100 the consensus big board does a pretty good job of predicting draft position all things considered.
An interesting caveat of this is that the graph clearly shows that reaches *do* overall overperform their big board status pretty consistently - they just get reached on too early and underperform their real pick.
Sink cost fallacy has something to do with that.
> While players who were drafted higher than expected ARE more likely on average to outperform their draft position. Inverse; they're more likely to *underperform* their draft position. He attributes this to "steals" requiring the collective wisdom of NFL FOs to be wrong, while "reaches" pit just one team's FO against the wisdom of the collective media scouts.
No because (1) it’s pretty straight forward (2) you can probably prove it analytically with some mild modeling assumptions
Cool, now can one of you draft/analytics nerds explain this to me in layman's English?
Reaches are more common than steals because a reach requires fewer things to happen, namely you just need a single team to overvalue a player. For a steal to occur you need many teams to pass on a player, either because they don’t need a player at that position or he has some latent talent that hasn’t manifested yet so he is undervalued. The number of teams that need to pass on that player for them to go much later than they should is large most of the time. However, there’s a lot of problems with this analysis. For example, other users have mentioned issues with the WAR stat (and I agree, football is not baseball and we can’t isolate events well enough to estimate WAR with the data available) that PFF made to try and rank players here. However my bigger issue is that there is no way to prescribe an ordering on football players, especially due to vast positional differences. You can’t compare an offensive lineman and a cornerback, and the position at which players go is highly dependent on what is going on in the league (e.g., RBs are less valuable in the current NFL so they tend to go much later than they used to) and how other prospects are viewed (e.g., if there is only one good RB in the draft and the rest are very obviously shit, the good RB will go sooner than if the class is deep because the cost on missing out on that RB for needy teams is high).
> However, there’s a lot of problems with this analysis. For example, other users have mentioned issues with the WAR stat (and I agree, football is not baseball and we can’t isolate events well enough to estimate WAR with the data available) that PFF made to try and rank players here. Fair, but >However my bigger issue is that there is no way to prescribe an ordering on football players, especially due to vast positional differences. This is the same complaint. WAR is an effort to do exactly this. >(e.g., RBs are less valuable in the current NFL so they tend to go much later than they used to) This is reflected in WAR.
Players who are generally considered reaches immediately post draft are usually accurately labeled because it just needs one team to incorrectly evaluate them Players generally considered steals post draft usually aren't because it requires 31 others teams to be wrong in their evaluation of the player if they aren't going earlier
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I don’t really think WAR is a great stat but I disagree with your interpretation. I think what it is saying is that when a player is a reach they are basically always significantly worse than the WAR expectation for a player at that pick. If the reach player was instead picked where the board ranked them then they would usually outperform than the WAR expectations for that pick and occasionally be worse. Conversely when a player is a steal they generally do worse than the WAR expected for the pick where they are selected but on occasion they do better. If the steal player was picked at the pick where the board expected them to be picked (which is above where they would be considered a steal) then they would almost always be significantly worse than expected WAR. This means that on average steals are not actually steals and reaches are basically always bad. Though because the steal spread goes above expectations it means steals can be good sometimes. I think what is interesting is that reaches usually outperform their board ranking. To me that says that reaches are generally underrated by the big board but usually the team that reaches for them significantly overrates them.
> I think what is interesting is that reaches usually outperform their board ranking. To me that says that reaches are generally underrated by the big board but usually the team that reaches for them significantly overrates them. Yeah, teams are blasted for reaches all time, and rightfully so - but the data shows that they *are* actually identifying something the media big boards aren't, they just don't get good value for it. That's rather interesting.
Anyone know what this is? Class? Anyone? Anyone? Anyone seen this before? The Reach-Steal Curve. Anyone know what this says? It says that at this point on the curve, you will get exactly the same amount of benefit as at this point. This is very controversial. Does anyone know what Vice President Bush called this in 1980? Anyone? Something-d-o-o football. "Voodoo" football.
Yes, because several teams being wrong is impossible
It's just less likely. Some reaches do work out, just fewer than non-reaches.
How is the yellow line always below 0? * Pick is a steal? Does slightly worse than EV of the pick. * Pick is even with expectation? (actually peaks at a slight steal) Does equal to EV of the pick. * Pick is a reach? Does a lot worse than the EV of the pick. Shouldn't the integral of the yellow line with respect to the total number of draft picks at each X value be 0? Don't you have to exceed EV somewhere?
The yellow line is an average line. The light grey is the spread, and is sometimes above 0. That said, the fact that it never exceeds 0 is really the observation here. That you can do worse than expectation, but on average you cannot do better than expectation, is exactly what is meant by the claim that there really is no such thing as a steal. Still, the grey line does exceed 0 which means that there *are* true steals - but when you average them in with everyone else who looked like as big of a steal the average comes to 0 or even worse than that.
I don't think this fully addressed what I said. Obviously some individual picks exceed expectation. What I said was that at every (actual-expected,) X value the EV (expected value, not the high end of the spread. I'm perfectly aware what that grey band means, thanks) is 0 or less. How do 0 (actual-expected) values on the x axis have a significantly positive EV? My only guess would be that at some point the yellow line barely crosses 0, and that ~95% of the actual picks are in that small (actual-expected) range, causing the total average value among all picks made to be 0.
Brock Purdy was a steal, every team was wrong at least seven times
Steals kind of have to exist for reaches too right? Like anytime a bad pick happens, all following picks are implicitly better. The WAR above expectation for a total draft should add up to 0 or else the expectation was too high
Tbh the graph makes it look like the ideal spot to pick a guy is when they've dropped a few spots, it's just the guys who drop a ton who don't really work as steals.
WAR is simply not a viable football stat.
How can we know a player is a "reach" unless we know where they were on all 32 teams draft board?
Idk Hamilton and linderbaum feel like steals so far
He's right, but worded it in a confusing way. Simplified: If 20 teams passed on a perceived top prospect, the likelihood they are all wrong about that prospect being worth their picks is not high. This is shown in the data, that "steals" perform just as well as normal players drafted in that spot. But if 1 team picks a perceived reach, the likelihood they are wrong is higher. That player may have fallen another 30 picks, because it's easier for 1 team to be wrong than multiple. Reaches perform worse than normal players drafted in that spot.
This graph can't stop me cause I can't read it.
Thats just bs. A steal doesnt need several teams to be wrong. The guys doesnt understand any risk taking. And dreams that teams drafted based on how good a player is without thinking about his position
There is more to a prospect than film and measurables. They can be bigger stronger faster and look good on game day against lesser competition but if they don't put in the work it will catch up to them.
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PFF is not analytics. PFF WAR is not a real stat because it is derived from PFF grade, which is not a stat is a qualitative opinion fudged to look like a stat
I fucking hate the nerdification of the draft