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What Are Their Chances?

Setting the odds for first-year players trying to make the WFT roster

Cincinnati Bengals v Washington Football Team Photo by Greg Fiume/Getty Images

With the preseason underway, excitement is beginning to build as rookie draft picks start to show signs of living up to their draft status, and players on the margin start making a case for a spot on the 53-man roster.

It should really come as little surprise when players selected on days one and two of the draft look like they belong in the NFL. Like many authors and readers on Hogs Haven, though, I get the biggest thrill when the late-round draft picks, undrafted free agents, and other unlikely candidates show that they belong in the league as well. In fact, the hype that these players generate has become such a phenomenon, that the site has created the annual Mason-Brennan Award to celebrate it.

After the first preseason game, two early front runners took the early lead in the hype sweepstakes. The diminutive RB, Jaret Patterson put up eye popping rushing totals against Mid-American Conference defenses at Buffalo, and WFT fans were eager to see if his skills would translate to the NFL. He didn’t disappoint against the New England Patriots’ first, second and third teams, posting 70 all-purpose yards on 10 carries and four receptions. After building even more momentum in the second preseason outing (133 all-purpose yards and a touchdown), it would come as a major surprise if he did not make the final 53.

The other story that is sparking fans’ imaginations is that of Chilean athletic freak, Sammis Reyes, who despite appearing in his first competitive football game at any level, looked like he could emerge as the second-best tight end on the Football Team. That hype train may have taken a pause while Reyes sat out the second preseason game in the concussion protocol, but if he catches another pass or two against the Ravens it will be full steam ahead.

Before we get too carried away by the hype, though, I thought it might be useful to put some numbers around the chances of players in the rookie class earning playing time and starting for the WFT in 2021 and in seasons to come.

Some readers have complained that a few of my recent analytical pieces have been a little hard to follow. The good news is that this time I’m going to keep it very basic, at least until I get to the rookie free agents.


Washington Football Team Mandatory Minicamp Photo by Scott Taetsch/Getty Images

Chances of Drafted Rookies Earning Playing Time and Starting

My approach in this article will be to provide benchmark probabilities for each player, based on comparable players in fairly recent rookie classes.

The most basic way to set an expectation about the chance of a given player earning a certain amount of playing time or starts is to calculate the proportion of comparable players in past rookie classes who achieved the same mark. This can be thought of as a past probability. For this purpose, I will compare each player in the rookie draft class, and one or two promising UDFAs, to players at the same position and similar draft status from the first-year classes from 2009 to 2018.

For each player, I was interested in creating three benchmarks:

  1. The probability of making the 53-man roster/earning playing time as a rookie
  2. The probability of earning starting time as a rookie
  3. The probability of becoming a starter later on

To estimate these probabilities, I used the Pro Football Reference database. Unfortunately, the database does not record ‘making the roster’ as a statistic. Therefore, as a proxy for the first benchmark I used an alternative, criterion: playing in at least one game as a rookie. Think of this as the probability of earning a roster spot throughout the first season.

The second benchmark is the probability of earning starting time as a rookie. As I have discussed previously, deciding on a criterion for what constitutes a “starter” is not simple. Setting the threshold too low, such as one game started, might inadvertently count too many players who just started as emergency injury replacements or who were benched after one game. Conversely, a high threshold, like 16 games started, might rule out players who earned a starting spot later in their rookie seasons or missed a single game due to injury. I decided to err on the low side, and set the threshold at five games started, because many first-year starters earn their starting spots well into their rookie seasons.

The third benchmark is the chance of becoming an eventual starter. Since many players take a few years to earn a starting position, I decided to set the criterion as starting five or more games in a player’s third season. Again, the choice of season was a compromise between competing considerations. Setting the threshold earlier might exclude players who took a few years to earn starting spots; while setting it at, say, five years might risk losing significant numbers of players to attrition through injury and other factors.

To get large enough samples to produce reliable estimates, I calculated probabilities over the decade from 2009 to 2018. This was the most recent I could go and still be able to estimate the probability of starting in players’ third seasons.

You have heard about the Vegas odds. Well now it’s time for the Bris Vegas odds, straight from the glamor capital of the Southern Hemisphere, Brisbane, Australia, host city to the 2032 Olympics.


Purdue v Penn State Photo by Scott Taetsch/Getty Images

First Round

Jamin Davis, Middle Linebacker, pick #19

Since 2009, only three linebackers have been drafted 19th overall (Leighton Vander Esch, Sean Weatherspoon, Jamin). To generate a reasonable-sized sample of players for a probability estimate, I had to compare Jamin’s chances to a larger group of linebackers, selected in a similar range of the draft. I have previously shown that, by the second half of the first round, it is difficult to distinguish career outcomes of players drafted more than a dozen picks apart. That means it should be safe to compare Jamin to all the linebackers selected in the second half of the first round.

Twelve middle linebackers were selected from pick numbers 17 to 32 in the decade from 2009 to 2018. The Pro Football Reference database provides poor separation between ILB’s, OLB’s and DE’s, but since there were only 12 players, I was able to sort them manually. All twelve played at least one game in their rookie seasons. Ten of the twelve started at least five games as rookies. And eight of the twelve started at least five games in their third playing season. Therefore, the benchmark probabilities for Jamin are:

Probability of earning a roster spot (playing at least one game in 2021) = 12/12 = 1.00

Probability of starting as a rookie = 10/12 = 0.83

Probability of starting by third season = 8/12 = 0.67

It will come as a big surprise if Jamin doesn’t start this season.

What could be interesting here is that the proportion of comparable players who started more than five games in their third seasons is lower than in their rookie seasons. It would be tempting to speculate that some linebackers picked in this range start early because of their draft status and don’t stick. Perhaps, but we are only looking at 12 players here, so it might just be the kind of fluky variations that can occur with small samples. Let’s see if any patterns emerge when we look at the players drafted later.

Second Round

Sam Cosmi, OT, pick #51

Starting with Sam, I calculated probabilities for all players at the same position drafted in the same round. The Pro Football Reference database does not distinguish between Left and Right tackles, so they are all grouped together. That might be appropriate, because we don’t yet know what position Cosmi will eventually play.

There were 27 OTs drafted in the second round from 2009 to 2018. All played at least one game as rookies. Of those 27, 18 started at least five games as rookies, and 19 of 27 started at least five games in their third season, giving the following benchmark probabilities:

Probability of earning a roster spot = 1.00

Probability of starting as a rookie = 0.67

Probability of starting by third season = 0.70

Cosmi is also a roster lock and has a decent chance of starting as rookie. Unlike first-round linebackers, that chance increases slightly with development by the third season.

Third Round

Benjamin St-Juste, CB, pick #74

18 cornerbacks were drafted in the third round from 2009 to 2018. All played at least one game as rookies. Six of 18 started at least five games as rookies, increasing to nine by their third seasons.

Probability of earning a roster spot = 1.00

Probability of starting as a rookie = 0.33

Probability of starting by third season = 0.50

A day two cornerback is going to see the field as a rookie. His chance of earning a starting spot as a rookie, however, is much lower than the first and second-round picks.

What I find most interesting here is that there is a much greater proportional increase in the chance of starting from year one to year three than for the first and second-round picks.

Dyami Brown, WR, pick # 82

48 wide receivers were drafted in the third round in the decade. 47 of them played at least one game as rookies. 11 out of 48 started at least five games as rookies, increasing to 23 out of 48 by their third seasons.

Probability of earning a roster spot = 0.98

Probability of starting as a rookie = 0.23

Probability of starting by third season = 0.48

The story for third round wide receivers is pretty similar to cornerbacks, although the chance of starting as a rookie is slightly lower. The proportional increase in chance of starting with development is even greater for wide receivers than cornerbacks, more than doubling from the rookie season to the third year.

I’d say it’s reasonable to expect Dyami to contribute as a rookie. The average wide receiver drafted in this range has about even odds of developing into a starter by his third season. But we all know that Dyami was an amazing steal in the third round, so his chances should be greater than that, right?

Fourth Round

John Bates, TE, pick # 124

24 tight ends were drafted in the fourth round from 2009 to 2018, all of whom played in at least one game as rookies. 12 of 24 started at least five games as rookies, increasing slightly to 13 of 24 by their third seasons.

Probability of earning a roster spot = 1.00

Probability of starting as a rookie = 0.50

Probability of starting by third season = 0.54

There might be something to the idea that you shouldn’t pick tight ends in the first round, if there’s a 50% chance of landing a year-one starter in the fourth round. I have no idea what to make of the flat development trajectory between the first and third seasons. It doesn’t seem to fit the narrative that tight ends take a long time to develop. Also, tight ends selected in the fourth round seem to do better as rookies than cornerbacks and wide receivers selected a round earlier. It is an odd position in many ways, but that bodes well for Bates’ rookie season.

Fifth Round

Darrick Forrest, S, pick # 163

Unfortunately, the Pro Football Reference database does not list season stats for special-teams specialists, which is likely to be Darrick’s primary role early in his career. I am therefore forced to base the benchmark probabilities on his listed draft position, safety.

Only 11 safeties were drafted in the fifth round from 2009 to 2018, 10 of whom played in at least one game as rookies. Two of the fifth-round safeties started at least five games as rookies, increasing to four by their third seasons.

Probability of earning a roster spot = 0.91

Probability of starting as a rookie = 0.18

Probability of starting by third season = 0.36

Safety seems to continue the trend that was interrupted by tight ends in the fourth round. By this point in the draft, a player’s chance of earning starting time as a rookie is getting pretty small. But again, like the third-round players, the chance of starting doubles by the third season. I am kind of surprised that 91% of safeties selected in the fifth round seem to be sticking on rosters for at least their rookie seasons.

Sixth Round

Camaron Cheeseman, LS, pick #225, TRADE TARGET

I am deeply disappointed that the Pro Football Reference database does not list season stats for long snappers. This, together with the fact that they do not list fullbacks separately from running backs makes me question why I even pay for a subscription.

I am sadly unable to provide benchmark probabilities for the Cheese. But it’s safe to say that the probability of a long snapper who was targeted in a trade making the 53-man roster must be astronomically high. Imagine how stupid the GM would look who traded up for a long snapper and then released him during preseason. Long snapper isn’t really considered a starting position, so I’d say his chances there hinge on whether he can also play another position, like linebacker or tight end. But that kind of positional versatility would seem to be somewhat antithetical to the long snapper concept, arguably the most specialized position in all professional sports.

Seventh Round

Will Bradley-King, DE, pick # 240

Shaka Toney, DE, pick # 246

Ron Rivera loves to draft pass rushers like Mike Shanahan loved to draft running backs. Here’s hoping that Riverboat Ron is as good at finding late-round gems at his favorite position as Shanny was. From 2009 to 2018, 39 defensive ends were selected in the seventh round. Unfortunately, the Pro Football Reference does not distinguish between edge-rushing 4-3 DEs and 5-technique 3-4 DEs, so these numbers will include a combination of players at the two fairly different positions.

Nevertheless, a remarkably high 30 of the 39 seventh-round DEs played in at least one game as rookies. But none of the 39 managed to start at least five games at DE in his rookie season. Bruce Miller, drafted as a DE by the 49ers in 2011 converted to FB in camp and started eight games as a rookie. That was a better time, when FB was listed as a starting position. As glorious an achievement as that was, I’m not counting it as a lone first-year starting DE. By their third seasons, six of the 39 seventh-round DEs, excluding Miller, were starting at least five games.

Probability of earning a roster spot = 0.77

Probability of starting as a rookie = 0.00

Probability of starting by third season = 0.15

The chance of a DE picked in the 7th round starting on the average team is already zero, and Bradley-King and Toney are playing behind Chase Young Montez Sweat. It’s just not going to happen for them as rookies, and there is a small chance one of them might eventually earn a starting spot. If we get solid contributions from either player as a role player, these picks were good value.

Dax Milne, WR, pick # 258

We round up the draft class with almost Mr. Irrelevant, Dax Milne, the guy who made Zach Wilson the second overall pick.

Dax compares to 54 wide receivers drafted in the seventh round in the decade of interest. 39 of 54 managed to earn playing time as rookies. Only four of the 54 managed to start at least five games as rookies, and by their third seasons that number dropped to three.

Probability of earning a roster spot = 0.72

Probability of starting as a rookie = 0.07

Probability of starting by third season = 0.06

Having watched Zach Wilson’s highlight reels, featuring Dax making spectacular catches, I have to believe his chances are higher than that, but the numbers don’t paint an encouraging picture. Milne has a good chance to make the roster, but his chance of doing more than becoming a backup is not worth betting on. And his chance of earning starting time doesn’t seem to improve with time.

Undrafted Free Agents

Jaret Patterson, RB

It is much harder to calculate benchmark probabilities for undrafted players because no one tracks the total numbers of UDFAs that try out and sign with NFL teams each season. Consequently, it is impossible to calculate the proportion of the total UDFA pool who earn playing and starting time, as I did for drafted players.

The Pro Football Reference Database only lists undrafted players who recorded a stat, and therefore earned playing time. To generate benchmark probabilities for Jaret, I have to assume that he will earn playing time as a rookie. Based on his performance in the first two preseason games, I think that’s a safe assumption. With that act of faith, I can then calculate the proportions of UDFAs on NFL rosters who earned starting time as rookies and third-year players as my benchmarks for Jaret.

This is not quite the same as the benchmarks I used for the drafted players, but it is the best I can do with the available data.

Out of 404 RBs who played in at least one game in their rookie seasons from 2009 to 2018, 231 were drafted, leaving 173 UDFAs. During this period, 69 RBs started five or more games in their rookie seasons, of which 53 were drafted, leaving 16 UDFA rookie starters.

Probability of starting as a rookie = 16/173 = 0.09

On first thought, after his breakout preseason performance, that figure seems low. But then again, given Jaret’s size and capabilities, he is probably best suited to a role as a number two back and return specialist, neither of which is a starting position. If we think of this as the chance of beating out Antonio Gibson for the lead back role, it starts to seem about right.

To generate a benchmark for Jaret’s chance of becoming a starter by his third season, I compared him to the 86 RBs who started 5 or more games in their third playing seasons from 2011 to 2020 (i.e. two years after their presumed first seasons from 2009 to 2018).

To do this calculation, we have to make another assumption that all 86 of these players came from the rookie classes of 2009 to 2018, containing 231 drafted RBs and 173 UDFAs. That’s almost certainly not true, since a fair number of players miss seasons. But, if the proportions of drafted and undrafted players does not change very much from year to year, inclusion of players from other draft classes should not have too much of a corrupting influence, making this a reasonable approximation.

Of the 86 RBs who started 5 or more games in their third seasons, 64 were drafted, leaving 22 UDFAs. Therefore, Jaret’s benchmark probability is:

Probability of starting by third season = 22/173 = 0.13

While that figure seems high relative to the most comparable player, seventh round WR Dax Milne (0.06), bear in mind that in Jaret’s case I’ve had to assume that he is already over the first hump – making the 53 man roster/earning playing time as a rookie. That means he is starting from a more favorable position than Milne, as a player who has already made an NFL roster.

As you can see, the calculations for UDFAs become more complicated and require making more questionable assumptions than drafted rookies. So I think it’s about time to stop… but not before discussing the most enigmatic first-year player still on the WFT’s preseason roster.

Sammis Reyes, TE

This article would not seem complete without taking a shot at benchmarking the Chilean phenom’s probability of earning a roster spot and starting time. Sadly, though, while there is precedent for basketball players who have never played a down of competitive football making it in the NFL, there does not appear to be any source of stats on the total number of these types of prospects who try out for NFL teams.

Therefore, in Reyes’ case, I’m just going to have to let the hype run its course unabated by any benchmark statistics. And that’s probably how it should be.


COLLEGE FOOTBALL: OCT 05 Texas at West Virginia Photo by Frank Jansky/Icon Sportswire via Getty Images

Closing Thoughts

At one level, the benchmark probabilities I have calculated for the WFT’s first-year players making team and starting as rookies really just confirm what most of us already knew. Players drafted on the first two days of the draft are going to see the field as rookies, and have a high (first round) to decent (third round) chance of starting early. As the draft continues, the chance of becoming a starter drops off sharply, and by the seventh round it is close to zero.

Three things stood out that did not make obvious sense:

  1. The chance of linebackers drafted in the second half of the first round earning starting time declines from their first to third seasons.
  2. The chance of drafted players earning roster spots as rookies remains high right through the third day of the draft, despite the fact that the probabilities of players drafted in this range becoming eventual starters diminish to around zero.
  3. The chance of tight ends drafted in the fourth round starting does not change much from their first to third seasons.

I think I can make sense of the first two observations, but the flat development of fourth round tight ends remains a mystery.

The first two observations seem to be all about the expectations that teams have for their drafted players. Players drafted in the first and second round are expected to start early. First and second round picks, like Jamin Davis and Sam Cosmi will start early unless they are flagrant busts, because of the expectations associated with their draft status.

By the third-round, and later, players have to earn their starting time based on their performance on the field. This is why we start to see the chance of starting increase from players’ first to third seasons in this range, as players improve with development.

Nevertheless, I suspect that teams have higher expectations for their own draft picks than later round players picked by other teams and UDFA’s, which might explain why the chance of later round draft picks earning roster spots remains as high as it is.

Acknowledgement:

Thanks to James Dorsett for editorial assistance


Poll

Which first year player is most liley to defy the benchmark probability as a rookie?

This poll is closed

  • 10%
    Sam Cosmi – doesn’t start five games
    (84 votes)
  • 30%
    Benjamin St-Juste – starts at least five games
    (240 votes)
  • 28%
    Dyami Brown – starts at least five games
    (222 votes)
  • 2%
    Shaka Toney – starts at least five games
    (20 votes)
  • 9%
    Dax Milne – doesn’t play in a regular season game
    (78 votes)
  • 17%
    Jaret Patterson – starts at least five games
    (140 votes)
  • 0%
    Someone else – explain in the comments
    (7 votes)
791 votes total Vote Now