You know what’s been bugging me about some fans’ reactions to the 2013 NFL Draft? They look at the San Francisco 49ers, who have been lauded for their draft results, and feel like the Green Bay Packers’ selections were utterly underwhelming by comparison.
Yes, the 49ers had a great draft. They were able to get some highly regarded players who could definitely make their great team even better. But I have a few counterpoints to the assertion that the Packers had a terrible draft in comparison. First and foremost, the 49ers started out with thirteen picks to the Packers’ eight. According to the traditional trade value chart, San Francisco’s total value of picks was about 1,958 points, compared to Green Bay’s total value of about 1,318 points.
In other words, the 49ers started out with 48.6% more draft value than the Packers. Of course they’re going to be able to get more out of it!
Secondly, these players have yet to play a single down in the pro arena. We should very well know by now that high draft picks can be phenomenal busts, while low draft picks can be hidden diamonds in the rough. It’s worthwhile to compare draft value based on scouting grades and reports; however, it’s rather silly to make concrete future predictions based on that.
Which leads to my third and most important point: a team’s draft picks don’t contribute that much in their rookie season. We call it “draft and develop” because these players don’t come ready-made for the NFL. They have to be coached, and they have to improve their technique and football knowledge in order to be effective at the professional level.
Let’s take the San Francisco 49ers for example. They reached the Super Bowl in 2012, but do you recognize any of these names from their rookie draft class? A.J. Jenkins, LaMichael James, Joe Looney, Darius Fleming, Trent Robinson, Jason Slowey, and Cam Johnson played a combined total of 12 games and zero starts. That means the 49ers were a Super Bowl team in the making over several years and that drafted players take time to really make an impact.
Of course, I don’t want to rest my assertion on that one example. I wanted to make sure that this claim actually has some validation to it, so I started doing some research.
My goal was to look at the Green Bay Packers’ draft classes since Ted Thompson became GM and see how much each one has contributed to the team. How much does a rookie class generally contribute to the team? How long does it take for a given draft class to hit its peak contribution? In other words, when does a team finally see its highest value of return from a single draft?
Before I started compiling and calculating the statistics to answer these questions, I had to determine the best way to measure a draft class’s “value.” The single best measurement I could figure was number of games played and number of games started by each player, averaged out by draft year and sorted by season. It’s not a perfect measurement, I know, but it’s the only one that could be compiled and applied to all players. (Number of snaps played would be similarly effective, but I couldn’t access that kind of data.)
The biggest drawback is that certain players contribute more on a per game basis than others. A good example would be Aaron Rodgers and Mason Crosby. Both players have started in every game they’ve played in for the past five seasons, but we can easily say that Rodger’s starts have more value to the team’s success than Crosby’s.
But again, it’s hard to get around that. Without some complicated formula, how do you compare the stats of a kicker vs. a quarterback? Or a running back vs. a cornerback?
So the best statistics for a player’s general contributions is games played and games started. It’s not perfect, but it should give us a fairly relative idea of how draft classes contribute to specific seasons.
Here are the first two sets of statistics calculated from the raw data. They show the average number of games played and started with relationship to “player year.” That is, in a given season, how many games did the Packers get from drafted rookies, second year players, third year players, and so forth? Also note that since we’re only looking at Ted Thompson’s draft classes, we won’t have a full column of data for each year.
At face value, the data shows something rather interesting. There seems to be a higher correlation with regard to contributions by draft class than contributions by player year. In respect to average games player (AGP), rookies in each season saw between 7.0 to 11.4 games; however, their average games started (AGS) spanned 0.3 to 5.5 games. As we look at the contributions by more veteran players, their numbers are more consistent yet lower. (This makes complete sense when considering player attrition.)
However, a view along the diagonals shows us some interesting data for specific draft classes. I highlighted a few to show this point. The green numbers are from the 2010 draft class, yellow is 2009, and orange is 2006. These three draft classes showed a few of the highest contributions in regard to AGP and AGS. The 2009 class, in particular, showed a very high AGP in their rookie year, while the 2010 class showed an even higher AGP in its second season. And the 2006 draft class had a fairly consistent set of starters from their rookie year through their fourth year.
Even though it is a completely logical conclusion to come to, the strength of a draft has more impact on the team than how much experience the players have.
Which brings me to a reshuffling of the data, so to speak. Below you will see the AGP and AGS numbers sorted by draft class. In simplest terms, it compares how each draft class did in their first year, second year, and so forth. Take a look:
I think this presentation of the data actually reveals some more insight on the trends, especially when looking at the averages by year. In regards to games played, there is a steady decline from the first year on, though some draft classes see spikes in their second or third years. When it comes to games started, however, you can see that the average draft class peaks in years three and four.
This should make sense, as younger players will contribute more on special teams and as second- or third-string players. They’ll play in the games but won’t be starters. As the years continue, the future starters will hit their peak development while those who can’t cut it will be replaced by the new groups.
I highlighted the 2009 draft class, because in addition to being a really strong group, they show this concept clearly. They started out their first year well above-average in games played, but were only about average in games started. The big contributors to this effect were T.J. Lang, Quinn Johnson, Jarius Wynn, Brandon Underwood, and Brad Jones. Yet as guys like Lang and Jones saw increased success and eventually starting roles, the rest were simply replaceable and eventually cut from the team.
One more calculation we can make is what I call the “AGS/AGP Ratio.” It’s essentially a percentage of how many games played were starts. Thus, 1.00 would mean that all the games played by that draft class were also starts, while 0.00 would mean that none of the games played were starts. In other words, it gauges how strong the draft class’s contributions were on a general level.
You’ll notice the obvious trend: the ratio is directly proportional to the number of years played. Aaron Rodgers, the sole remaining player from 2005, starts every game that he plays. You can also look at how individual draft classes compare. Despite being a relatively strong class, the 2009 group doesn’t really compare in this category with the 2006 group. The latter draft class had a much higher AGS/AGP ratio, even though their total games played was rather average.
(Top picks A.J. Hawk, Daryn Colledge, Greg Jennings, and Jason Spitz all saw starting time very quickly in 2006.)
There’s a lot to digest here, but hopefully it will shed some new light on this aspect of a team’s management. That said, this only represents a Ted Thompson-built roster. Were we to do the same data mining with other teams, we could possibly see some different trends.
There’s also the effects of injuries to consider in looking at the numbers. The 2011 draft class didn’t get a lot of chances their first year due to how stacked the team already was, but their second year was further hampered by injuries to Derek Sherrod, Davon House, and D.J. Smith.
Back to my original premise, though, and you can see that it’s generally not common to see rookie draft classes make a big contribution to a team’s success. Yes, particularly strong draft classes can make a difference, but even then it’s mostly in back-up and special teams roles. Aside from the top picks and the sleepers, most players are developed into starting talent, rather than being ready to go on Day One. Even players who start their first year aren’t playing at their ceiling yet.
So while the San Francisco 49ers might have a potentially strong 2013 draft class, we don’t know that for sure yet, and it will still take them a couple years before they hit their peak value. Likewise, we should temper expectations for the Packers’ rookies. Both teams will have to rely on the talent they’ve already been developing for the majority of their success in 2013. Whether that makes you feel better about this season or not is another conversation altogether.——————Follow @ChadToporski