Defense, Risk-Aversion and the NBA Draft: Which Prospects are Overrated and Which Prospects are Underrated?


The NBA draft is probably the most important event of the year when it comes to building for a franchise’s future. The difference between drafting Derrick Rose vs. drafting Michael Beasley translates into tens, if not hundreds, of millions of dollars of franchise value (even despite Rose’s recent injury woes). Of course, the NBA draft is nowhere near an exact science – from Evan Turner (2nd overall in 2010) to Manu Ginobili (57th overall in 1999), history illustrates that the draft is filled with uncertainty.

Despite the draft’s inherent variance, public prospect rankings, such as Chad Ford’s rankings at ESPN, are reasonably efficient. In other words, the highly ranked prospects are more likely to perform well in the NBA vs. those below them. This is not necessarily a reflection of the scouting prowess of Ford as it is a reflection of NBA scouts and front office personnel anonymously sharing their opinions and/or leaking inside information on draft prospects to Ford or other mainstream media personalities. Ford even admitted as much in the brief write-up for his latest big board: “Remember, these rankings aren’t based on my opinion. They are based on talking with numerous NBA GMs and scouts. Obviously, each team has its own rankings and they’ll differ from these. However, here’s a consensus of what the NBA as a whole thinks.

While some front offices are more tight-lipped than others – the Spurs stand out as an organization that rarely shares their draft opinions with the media – the reality is that these public rankings, to a large extent, reflect the consensus view among NBA front offices about each class of draft prospects.

With that in mind, year after year, public draft rankings indicate the prevalence of certain biases in front offices that systematically overrate certain prospects and systematically underrate certain prospects. On average, prospects with questionable defensive skills, prospects thought of as “safe,” and prospects lauded for being able to help a team right away have been overrated, with the opposite having been underrated.

Offense vs. Defense

When you watch an NBA game, or any basketball game for that matter, what do you see? If you are like 99% of people, you focus on the ball, and see offensive skill and performance much more clearly than the skill and effort involved on the other side of the ball. The traditional statistics found in the box score only serve to further emphasize offense and deemphasize defense. It’s not surprising then, that defense tends to be under-emphasized and offense over-emphasized in player evaluation. This is especially the case in the draft.

Offense does involve comparatively more skill while defense involves comparatively more effort, communication and ability to stick to principles of a defensive scheme. But overall, x points above average per y possessions on defense is just as valuable as x points above average per y possessions on offense.

If a prospect is undoubtedly skilled and yet puts in so little effort on the defensive end as to let his man blow by him into the paint on every drive or miss every rotation meant to prevent easy layups, unfortunately the negative on the defensive end may overwhelm whatever positive value he is generating on offense. Brandon Jennings stands out as one of the many players who serve as cautionary tales of talented, above average offensive players whose complete lack of effort on the defensive end result in being a net negative relative to league average.

Rajon Rondo’s career can illustrate the effect that effort has on defensive performance. Rondo was, for a number of years, a good defensive player. Length, quickness and Doc Rivers’s well-principled defensive scheme undoubtedly contributed to Rondo’s defensive productivity. But over the last few years, during what should have been the prime of his career, Rondo mysteriously experienced a precipitous defensive decline. While Doc did move to the Clippers, by all accounts Brad Stevens is a very smart coach himself. The bigger issue seemed to stem from Rondo’s 2013 ACL injury. But while part of the decline was undoubtedly physical, a large part of Rondo’s it seemed to stem from his declining willingness to try on the defensive end. After being traded to the Mavericks, Rondo admitted as much himself, as he told reporters that he had not “played defense in a couple of years.”

While defensive effort, or lack thereof, is probably easier to pinpoint than defensive talent, a prospect’s lateral quickness, feel for defensive rotations and overall defensive playmaking ability are also severely underemphasized in the draft. Even if a large portion of Jimmer Fredette’s offensive production at BYU translated to the NBA, most NBA players matched up with Fredette’s lack of lateral quickness will match or exceed that production when the ball is in their hands. The media will always report the player who went off for 40 points in one night. But the players who were guarding the guy who went off are rarely, if ever, mentioned.

It’s easy to pay little attention to defense. After all, that’s what most people have always been doing. An anonymous scout even shared with Grantland that “there are very few players that get drafted because of their defense. That will be Hollis-Jefferson and Willie. The other f—ing 28 guys? It will all be about offense.” But Tim Hardaway Jr., Jimmer Fredette and Austin Rivers are just a few of the players who indicate that the track record of defensive low-effort or low-talent prospects is less-than-stellar at the NBA level. On the other hand, even casual fans by now realize the value of players like Kawhi Leonard, Serge Ibaka, Andrew Bogut and Draymond Green, who contribute most of their value on the defensive end of the floor.

With that in mind, here are a few prospects in the 2015 class who are likely incorrectly valued due to their outlier defensive ability (or lack thereof) with their ranking on Chad Ford’s most recent big board in parentheses:

Underrated Overrated
Justise Winslow (7) Jahlil Okafor (3)
Willie Cauley-Stein (8) Trey Lyles (12)
Rondae Hollis-Jefferson (20)
Christian Wood (30)

Help Right Away and “Safe” vs. Future Value and “High-Risk”

Most people are risk-averse. Due to the short tenures of general managers (and even shorter tenures of head coaches), the tendency of decision-makers to sacrifice the future in favor of the present has been well documented in almost every professional sport. However, without taking into account the fact that you might be fired tomorrow for losing one too many games, the extent of the value left on the table due to this approach in the draft is astounding.

Layne Vashro recently hashed out an excellent argument for taking the best player available in the NBA draft. The crux of the argument revolves around the facts that 1) almost all rookies stink and 2) the majority of a draft pick’s surplus value comes from year 3, year 4 and the tail end of the variance spectrum where the player becomes a superstar and takes a maximum salary deal (at least under the current CBA) which pales in comparison to what he is actually worth.

Valuing prospects in the NBA draft, especially at the top, where the chances of landing a superstar are exponentially greater, should be like valuing call options. Many NBA decision-makers make the mistake of looking for a quick payout from what should be a long-term investment (whether this is their own fault or a result of the lack of job security is a separate issue). The problem is exacerbated by the fact that even the best rookies are worth no more than a few wins – I actually think that the chart in Layne’s article overstates rookie impact, due to the fact that most rookies are terrible defensively, and Win Shares inadequately accounts for defensive production. A 10% chance of landing a superstar and a 90% chance of a complete bust is a better expected value decision than a 100% chance of landing an unspectacular rotation player (at least under the current CBA).

When the bulk of draft pick value comes from the small chance that the player drafted becomes a superstar, acting risk-averse can be a fatal move to a franchise. Dean Demakis, an NBA and NCAA gambler and NBA draft analyst, has written many articles on his website,, pointing out that it is much worse for a franchise to miss out on a superstar than to draft a bust.

So finally, here are a few players who seem to be incorrectly valued, based on the perception of how “safe” they are and/or how soon they can help a team (ironically, 18 year old Devin Booker is perceived as a “help right away” guy due to his excellent three point shooting):

Underrated Overrated
Myles Turner (13) Devin Booker (9)
Kelly Oubre (16) Sam Dekker (14)
Montrezl Harrell (17)

I believe that right now, under the current CBA, the biggest inefficiencies in the NBA draft revolve around defense and correctly valuing future upside against present safety. After acquiring Nerlens Noel, Michael Carter-Williams, Joel Embiid, KJ McDaniels and Jerami Grant through the draft, it seems that the front office of the Philadelphia 76ers, possibly the NBA’s most analytical team, agrees.

image from

Nik Oza
Georgetown Class of 2016

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Running Back Efficiency and the Perils of First Round Backs


Much debate has surrounded the idea of drafting a running back in the first round. Many analysts have succeeded in proving that the value of running backs pales in comparison to that of other positions. Additionally, the rookie wage scale makes teams more inclined to draft positions that tend to produce more value. Another problem that exists when drafting a running back is trying to parse the value of that running back versus the next best running back. Being able to confidently state that Running Back X should be one of the top 5 picks suggests that this player possesses more value than all but four other players in the draft, as well as being clearly superior to the other backs in the draft.

This analysis looks at the first four years of every running back drafted since 2002 up until 2011 (players from the 2012 NFL Draft will begin their fourth season this year). This ten year window seemed to be the most appropriate as passing became more prevalent in the early to mid-2000s. Recently, the league is seeing more 4000 and 5000 yard passers than ever, so the best thing to do was limit the sample to these backs. I examined how many rush attempts, rushing yards, targets, receiving yards each player had as well as the Approximate Value of every player. I excluded running backs who never made a rushing attempt during a regular season game from the data set, which left 162 players. The average yards per carry for these players was 4.3 yards, while the average number of receiving yards per target was 5.9 yards. Both the total number of yards as well as the Approximate Value were adjusted. That means that a player who rushed 100 times for 430 yards would be an average player. Similarly, a back who was targeted 100 times and gained 590 receiving yards would also be average. I elected not to incorporate touchdowns in might adjustment since the Approximate Value calculation does not include touchdowns in its calculation.

Now, with the Approximate Value adjusted, I determined what adjusted AV we could expect from a player based on their combined number of targets and carries:


The line of this graph reflects the average Adjusted Approximate Value. Essentially, any data point that falls on this line is a running back who did not produce any more or less AV than one could expect from an average player. Points above the line represent players who produced a greater AV than expected, while points below the line performed below the expectations for an average running back.

Categorizing the running backs by the round in which they were drafted shows that, on average, first round running backs have performed the worst compared to the average. The chart below shows the average difference between a running back’s Adjusted AV as compared to that of an average player with the same number of carries:

Figure 1. Net Difference from the Average Adjusted AV based on Round Selection


One explanation for the low figure for first round backs is that a high number of carries would lead to lower efficiency, and consequently, a lower Approximate Value. While I agree that a larger workload would lead to a decline in efficiency, this is not the issue here. The chart below categorizes the same players based on the number of carries and targets they had over their first four years:

Figure 2. Net Difference from the Average Adjusted AV based on Carries and Targets


Actually, players with over a thousand carries and targets saw the largest, positive deviation from the average. The worst range was the 600-799 carry/target group. The graph above shows that a good number of running backs in that carry or target range performed below the average. So why did first round running backs perform so low against the average?

There are two reasons that help explain why the figure is so low for 1st round running backs. The first is that despite my efforts to deflate the effects of receiving yards, it appears that running backs with lower rushes to target ratios tend to perform slightly better. Still, Laurence Maroney, who has one of the higher rush to target ratios with 91.37% of his opportunities coming from rushes, is in the top ten percent of running backs by this metric (Maroney was +4.94 points above the average). The second reason, which is primarily responsible for this, is the extremes we see from first round backs. Of the eight worst backs by this metric, six of them are first rounders. All six backs were -5.97 to -8.80 points below the average. Removing these six backs from the data set would increase the net difference for first rounders up to +1.15, significantly better than any other round.

Those six running backs are not necessarily as bad as the figure may make them out to be. In many instances like these, coaches and general managers insist on continually feeding these backs, despite their performance being average or subpar. Additionally, a team often selects a running back high in the draft to “fix” their running game, when many times, it is the offensive line that needs repair. Cedric Benson is a prime example of this. Benson had the lowest difference of the aforementioned six first rounders with production far below the average. Benson finally got his chance to start for the Chicago Bears in 2007, after sitting behind Thomas Jones his first two years. Unfortunately for him, he played behind the 30th ranked offensive line for run blocking, according to Football Outsiders’ Adjusted Line Yards metric. 2008 would prove to be even more frustrating as he moved to Cincinnati. There, he ran behind the worst offensive line according to that same metric. Benson would go on to rush for 1000 yards in three consecutive seasons as the Bengals continued to upgrade their line. Clearly, a major barrier in evaluating the skills of a running back is analyzing the abilities of his offensive line.

To help normalize the metric by workload, I divided the net difference in Adjusted AV by the number of targets and carries to see what results it would yield. We will call this metric “Efficiency,” as it tells us the value added for every carry/target the player receives. For running backs with a minimum of 100 carries, two former San Diego Charger running backs topped the list for efficiency. Both played for the Chargers at the same time. Most people would be quick to assume LaDainian Tomlinson would be one of the two running backs, but actually the two backs are Darren Sproles and Michael Turner (Tomlinson was drafted in 2001). Sproles and Turner could not have been more different in their backup roles as Michael Turner found most of his opportunities coming from rushing attempts (93.83%), while just over a third of Sproles opportunities came from targets. The attention that Tomlinson drew allowed for more efficient production from Turner and Sproles. In the same way that Peyton Manning made many of his wide receivers look better than they actually were, backs like Tomlinson, Adrian Peterson, and even DeMarco Murray this past year create the same effect.

While this does bolster the case for one back getting a larger share of the workload, there seems to be only a few backs who really make this type of impact on an offense. In 2011, Brian Burke wrote an article explaining why a team should not pay Chris Johnson top dollar. He approaches the case by showing the true worth of running backs relative to other positions and the tendency for teams to overvalue running backs. By 2011, Chris Johnson had a combined 1456 attempts/targets that produced a net difference of +2.18 in Adjusted Approximate Value. But let’s say the Titans never picked Chris Johnson, but rather traded that (24th) for two third rounders and a fourth rounder. Combined Jamaal Charles (73rd), Steve Slaton (89th), and Tashard Choice (122nd) had 1610 touches and carries in the same time frame as Johnson. Their aggregate net difference of +6.43 in Adjusted Approximate Value is almost triple the amount Chris Johnson produced. While Charles is a phenomenal running back, it goes to show that running back talent like Johnson is  1) replaceable when touches are distributed more evenly across different backs and 2) replaceable with “cheap” players.

Players like DeMarco Murray (+5.87), Brian Westbrook (+7.16), Ray Rice (+7.53), and Maurice Jones-Drew (+10.10) show us that running back talent is deeper than most front offices think as all four guys landed outside the top 50 picks of their respective drafts. As previously mentioned, a big reason that these running backs were even given the chance to succeed is ultimately tied to the talent of their offensive lines. For those who fail, the situation for each running back clearly affected their play. The chart below shows the running backs with the highest differences and lowest differences from adjusted AV. Marshawn Lynch is on the list, but after his tenure in Buffalo, he has become one of the best running backs in the game. Willis McGahee also found success when he became a backup for Ray Rice in Baltimore. All this being said, it appears that the talent difference among running backs is not only marginal, but very dependent on their team’s offensive structure and how frequently the coach opts to give them touches.

Figure 3. Ranking Running Backs by Difference from Adjusted AV (Min. 100 Carries/Targets)


Image of Willis McGahee against the New York Jets is from the New York Times.
All statistics are from Pro Football Reference, unless noted otherwise.

Nick Barton is a rising Junior in the McDonough School of Business
Twitter: @nbarton94

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FC Porto: The Transfer Market Champions


FC Porto are not the team with the most Portuguese league titles. They are not the team with the most Portuguese cup titles. They are certainly not the team with the most European Cup or Club World Cup titles. Porto might not be the first team that comes to mind when thinking of the sport’s historical top exponents. Over the last decade, however, Porto have consolidated themselves as the undisputed leaders in a very particular area of game: the transfer market. While some teams have acquired fame for their overwhelming spending summer after summer —more often than not thanks to the monetary backing of Eastern European or Middle Eastern investors—, Porto have mastered an investment approach that any Wall Street stockbroker would envy. Their keen eye for scouting young and affordable talents, combined with the nearly top-flight level of soccer to which it exposes its signings in the Portuguese league, allows for Porto to dramatically increase the market value of their players over relatively short periods of time. As a result, FC Porto have tapped into the quick appreciation of their players, generating a whopping $652 million profit over the last decade in transfers alone!

When measuring gains from the transfer market, most sources simply add up the fees received and subtract the fees paid by the club in question, finding a net cash flow for a particular period of time. However, my calculation is based only on the players the club has sold over the last decade —i.e., since the summer of 2005. I then subtracted the original sum paid for each player, regardless of whether the player was bought before or after the summer of 2005. This makes the final figure more realistic. Imagine, for example, that a player was bought in 2003 and sold in 2006. If we only calculated cash inflows and outflows for the last decade, the fee received for the player’s sale would be accounted for, while the fee paid at the time of purchase would not; this would overstate the total gains on transfers. Conversely, if a player was bought in 2014 and hasn’t been sold yet —i.e., he remains a squad player—, only the fee paid for him would be accounted for, thus understating the total gains of transfer. Since it would be unwise to assume that the inflows ignored on one end would roughly offset the outflows on the other, particularly considering the noticeable inflation of transfer fees in recent years, I found my calculation to be more accurate. Table 1 presents such an analysis for FC Porto, sorted based on the net gain on each player, from highest to lowest. (Click on the table to zoom in).


The list contains some remarkable names, with Colombian stars James Rodríguez (Real Madrid) and Falcao (AS Monaco) as the most notable. The list also includes Portuguese center backs Ricardo Carvalho (AS Monaco), Pepe (Real Madrid), and Bruno Alves (Fenerbahçe), Brazilian star Hulk (Zenit St. Petersburg), young Argentinian talents Juan Iturbe (AS Roma) and Nicolás Otamendi (Valencia), and former FC Barcelona legend Deco. Recognizing these names is now an easy task, after such great players have proven their talent across Europe’s most prominent leagues, as well as in international competitions. However, in most cases, they were rather fameless before signing with Porto. This is evidenced by the relatively low transfer fees that the Portuguese club had to pay for the players. Notice for example that the club only paid more than $20 million for one player in the last ten years —$27.9M to Japan’s Tokyo Verdy, for the services of then 21-year-old Hulk. Other than Hulk, Porto has paid under $20M for all the players it has sold in the last decade, including James Rodríguez and Falcao, who have an estimated current market value of $52.8 million and $39.6 million, respectively.

The Portuguese club’s secret to success was, undoubtedly, its ability to pinpoint which players in less prominent leagues had shown great potential and were on the verge of a rapid performance burst. Exposing these players to the relatively competitive Portuguese league not only aided such a burst, but it also served as a way to showcase the rising talents that would allure the clubs with higher purchasing power across Europe. This quick increase in market value is measured in the right-most column of Table 1, which calculates the yearly dollar appreciation of each player —i.e., the net gain (loss) on the player divided by the number of years the player was at the club. Notice, for example, that Falcao was bought for just under $8M and sold for $58.7M after only two years, yielding an annual appreciation of over $25M per year —mainly due to the record 17 goals he scored that helped Porto clinch the 2011 UEFA Europa League title. Other noteworthy cases are those of defender Aly Cissokho, who became $23.3M more expensive in the one year he played for Porto, and playmaker James Rodríguez, who picked up $18.4M per year before being sold to AS Monaco for over $66M in the summer of 2013, after 3 years in Portugal.

Of course, the greatness of FC Porto’s numbers can only be praised in context, when compared to those of other clubs. I selected four similar teams, in terms of their budget, high-selling transfer history, and level of domestic and international success.

Porto 2

Porto 3

These are Atlético de Madrid (Spain), Tottenham Hotspur (England), AC Milan (Italy), and —as the closest point of comparison— Benfica (Portugal). After performing the same calculations for all of these clubs, it became clear that Porto’s fame of transfer market masterminds is well deserved. In the last decade’s worth of transfers, Porto outperformed Portuguese archrivals Benfica by almost $200M —not to say that Benfica’s $457.7M gains from the transfer market are not staggering as well. Atlético de Madrid made $93.6M, closely followed by Tottenham Hotspur with $91.1M. Meanwhile, AC Milan, renowned for multiple expensive sales in the last decade, actually lost $104.4M from their transfer market activity. FC Porto’s dominance is exhibited in almost all key statistics presented in Table 2. Not only did they have the highest percentage of positive transfers —i.e., when a player was sold for more than what he was purchased—, but they also led the group in terms of average gain per player and average annual appreciation per player. Most remarkably, they were the club with the highest percentage of transfers yielding $20M+ gains and the club with the lowest percentage of transfers yielding $5M+ losses; talk about maximizing profit and minimizing losses!

Porto 4

Benfica’s statistics, the only ones remotely close to Porto’s, show that a transfer policy of careful scouting and continuous reinvestment of transfer market gains is almost inherent to top Portuguese teams. Atlético de Madrid and Tottenham Hotspur, belonging to the more competitive Spanish and English leagues, respectively, usually seek somewhat older and more consolidated players. With slightly higher budgets than Porto and Benfica, they can afford to pay marginally higher transfer fees for players who have shown promise in nearly top-flight leagues like —you guessed it— the Portuguese league. Case in point, it was Atlético de Madrid that bought Falcao from Porto in 2011 for $58.7M. Clearly, maximizing the market value of moderately popular players in their mid-twenties is more difficult than doing so for 19-, 20-, or 21-year-olds on the rise. Thus, neither Atlético nor Tottenham embrace that strategy. They rely more heavily on their budgets than their transfer market gains when signing players season after season. Still, those following the transfer market in the last couple of years will know that Tottenham, despite making the sale with the highest fee in the world ($137.9M) and the highest gain among the selected clubs ($116.3M), both for Welshman Gareth Bale, have done a poor job at using such high gains to maintain a competitive squad.

AC Milan have also made multiple notorious high-grossing sales in the last decade, such as those of Kaká to Real Madrid ($95.3M), Andriy Shevchenko to Chelsea ($63.5M), and Thiago Silva to Paris Saint-Germain ($61.6M). However, their poor performance in terms of transfer market gains is mostly due to their policy of retaining first squad players for many years. The “Average Years at Club” statistic does not reveal this fact directly, because it accounts for the sale of rotation and incoming youth squad players who leave the club after three years or less. However, we can see that nearly 10% of AC Milan’s players sold in the last decade spent 7 or more years at the club —Nesta, Seedorf, Pirlo, and Gattuso being some relevant examples. This represents a far higher percentage than those of all other selected teams, and it also implies that players are sold when they are much older and their market value has decreased. Although they clearly do not yield high monetary gains, these players do provide the more abstract benefit given by their many years of service; they amortize through time, sort of say.

Given their current squad, FC Porto’s dominance in the transfer market will certainly continue in the coming years. If we perform a similar analysis on the players of the current squad as the one performed on only those who had been sold in the last decade, we are able to account for the money spent by Porto in players that have not yet been sold.

Porto 5

This analysis, presented in Table 4, calculates the potential gains or losses on each player if they were sold today at their estimated current market value. If sold today at market value, 30 out of 38 players would bring in a net gain to the club —i.e., they have become more valuable in their time at Porto. Considering that most current squad players have been in the club for less than three years, it is most impressive that Porto have already managed to appreciate their squad to a net unrealized profit of over $150M, representing an 88.44% potential gain! Porto’s most valuable players, namely Jackson Martínez, Alex Sandro, and Yacine Brahimi, as well as many youngsters in the team, could and probably will be sold at a premium in the coming years.

Porto 6Finally, and just for fun, here is what Porto’s squad could look like today if they had been able to retain all their top players from the last few years. This is obviously a pointless experiment, as the gains from some players’ transfers clearly allowed for the purchase of other players. However, it still speaks to the club’s unparalleled ability to find and develop future world talents —an ability that has made them the clear champions of the transfer market in the past and will continue to do so in years to come.

Image of Jackson Martinez is from

Juan Posada is a rising Junior in the McDonough School of Business.
Twitter: @JuanDiegoPosada

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Spain v Holland

“Casillas is a living legend,” “He has led Spain to several titles,” “He is a symbol of Real Madrid…” Phrases like these are a recurring narrative among Spanish sports journals and a devastatingly large portion of soccer enthusiasts around the globe. Let me just start by saying that nobody can deny that Iker Casillas was once a great goalkeeper. However, this does not mean that he continues to be one today. All of Casillas’ ‘miraculous’ performances —continuously recalled by his supporters in an attempt to reinforce his legend— happened during or before 2010. His interventions in the 2002 Champions League Final vs. Bayer Leverkusen were indeed crucial. The penalty saves he had in the 2008 Eurocup vs. Italy were also prominent. His two magnificent saves vs. Netherlands’ Arjen Robben in the 2010 World Cup Final undoubtedly gave Spain the title. Once again, there is no doubting Casillas’ notable record for club and country over the first decade of the current century. However, the story is remarkably different ever since. After the 2010 World Cup, his performance has been mediocre, with many more costly mistakes than praiseworthy interventions. Read more of this post

Analyzing the Darrelle Revis Signing

Staying true to his increasingly-accurate reputation of being a mercenary of sorts in the NFL, cornerback Darrelle Revis decided to leave the New England Patriots—where he won a Super Bowl in his first season with the team—to return to the team that drafted him, and where he made a name for himself: the New York Jets. Revis agreed to a 5-year, $70 million deal with Gang Green on Tuesday night, with $39 million guaranteed. His decision adds to a slew of moves orchestrated by New England’s AFC East rivals that are casting doubt in the minds of many that the Pats can roll through the AFC East next season like they always do. Read more of this post

Introducing Expected Contract Value Part 5: Frequently Asked Questions


How large is your sample size?

The initial sample size used to run the regression analysis was approximately 1,500 “contract seasons.” Each contract season is a single input record. So if a given player’s contract covered five seasons from 2005-2009, this resulted in five different contract seasons for the purpose of creating input records (even if the player was released after three seasons). Read more of this post

Introducing Expected Contract Value Part 4: Salary Cap Budgeting

Trent Cole

In addition to enabling the valuation of a contract from the perspective of the amount of money that the player can expect to earn, Expected Contract Value also enables teams to budget for the contract from the perspective of the amount of salary cap space that the player can be expected to account for. This objective can be accomplished by applying the expected outcome to the scheduled cap number in the relevant contract season, rather than to the amount of money that could potentially be earned by the player.

There are two conceptual ways to approach this exercise. The simpler way, what we will refer to as “Either/Or Cap Budgeting,” involves looking at the expected outcome, rounding up or down, and then selecting either the player’s cap number or his dead money number, whichever is applicable. For example, let’s take a look at Trent Cole’s contract from the perspective of Either/Or Cap Budgeting. Read more of this post

Introducing Expected Contract Value Part 3: Contract Comparison

ryan kalil

In order to expand upon Part 1 and Part 2, and demonstrate how Expected Contract Value can be helpful in comparing contracts, let’s take a look at an article from in June 2014 in which Jason compared the recent large contracts of centers Maurkice Pouncey, Alex Mack, and Ryan Kalil. This article is the archetype of the insightful subjective analysis we identified in Part 1 that could be enhanced by Expected Contract Value.

Jason first correctly points out that the face values of contracts can be misleading, and that they should not be determinative in the comparison at hand. He then goes on to refer to “dead money protections” for the various deals. This is a concept addressed by Expected Contract Value through the inputs Save:Cap and Save:Avg. Jason goes on to refer to Kalil’s three-year payout as “virtually guaranteed.” While that may be true, Expected Contract Value allows us to assign a numerical value to the descriptive term “virtually.” Read more of this post

Introducing Expected Contract Value Part 2: Inputs And Outputs

 Richard Sherman

As we described yesterday, Expected Contract Value is an objective metric that enables valuation and comparison of contracts, as well as team salary cap budgeting, by using regression analysis to identify the influence on team-decision making of the relationships among various contract characteristics. Today, we will describe both the inputs and outputs of the metric.

Save:Cap: This input is a ratio of (i) the amount of cap savings that the team would realize upon releasing a player to (ii) the player’s cap number if the team does not release him. A team may be more enticed to save $1 million in cap room by releasing a player who will count $3 million against the cap than it would be by releasing a player who will count $10 million against the cap. Furthermore, a team may be dissuaded from releasing an overpaid and underperforming player if doing so would result in a larger cap hit than refraining from doing so. This input can be thought of in the following way: How beneficial (or detrimental) would it be from a salary cap perspective to release this player? Read more of this post

Introducing Expected Contract Value Part 1: Justification, Theory, & “Contract Analytics”

Andrew Luck

NFL contracts are extremely difficult to accurately value, compare, and budget. This difficulty arises primarily from two factors: (1) the generally non-guaranteed nature of the contracts and (2) the variety of types of components which comprise the contracts (signing bonus, roster bonus, base salary, etc.)

Because NFL contracts are generally not guaranteed, the face value of a contract is largely irrelevant, as it is not determinative of either (i) the amount of money that the player will earn under the contract or (ii) the amount of cap room that the team will allocate to the player over the life of the contract. Because NFL contracts may contain a variety of types of components, each having different salary cap implications, NFL contracts lack uniformity of style, as NFL teams are able to structure contracts in many different ways. Read more of this post


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