My motivation for writing this article stems from a chance encounter I had with someone on the Metro a few weeks ago. I noticed that the man next to me was fiddling around on his phone, and even from a distance I could tell he was constructing an NBA lineup on a DFS site.
Naturally, I decided to introduce myself. As it turned out, he had read a few of my DFS articles and said that it had helped him out a lot. What happened next was a bit unexpected. He got really quiet and said: "You must be really good at math."
I have never considered myself to be a math whiz. I was a solid B student and did well enough to pass, but math certainly was not my strongest subject. I replied: "Not really, why do you ask?" He said, "I just have a hard time understanding what you guys talk about sometimes. I guess sometimes I pretend to know what stuff like value and pace mean, but in reality, I don't. Honestly, I feel stupid about it sometimes."
I suddenly had a vision of thousands of DFS players all in a room talking to each other. In each conversation one person is spouting out statistics and formulas and the other person is nodding and agreeing because although he has no idea what the other person is talking about, he doesn't want to look stupid.
The man I met on the Metro left the train before I could help him out, but hopefully he'll read this article along with the rest of you, as we go on a quest. The quest to end looking stupid.
There's a lot of information and noise out there in the online DFS world. At times, it can be overwhelming. You can read advice articles, listen to podcasts, but in the end, all you are getting is another person's opinion. The good news is that some simple math and data analysis can help you manifest your own best advice. True, a lot of these writers (myself included) are using the same formulas and stats that I'll be outlining in this article, but at the very least you'll be able to understand what everyone is talking about when you're reading other advice columns. At best, you'll take these two categories and start putting them to good use.
VALUE
Value is probably the most frequently used word in relation to player selection across all of fantasy sports, and regardless of which sport you're playing, it all works in basically the same way. Since we need to be able to quantify value, we need to find a suitable number to assess players. The most common equation is:
Value = Player's Projected Points divided by (Player's Salary/1000)
We use the 1000 divider as a way to get us to a workable whole number. An example: If LeBron James is expected to score 45 points with a salary of $10,000, then 45/($10,000/1,000) would give him a value of 4.5. The higher the number is, the more value he has in relation to his salary. If this is too much math for you, there is an even simpler way to calculate value, which can tell you the approximate, per-point value of a player. It's also a simpler way to calculate value on DFS sites that have different salary caps (like Yahoo). That equation is:
$ per point = Player's Salary/Player's Projected Points
Utilizing the same salary and projections from the previous example, LeBron's per-point value is $222.22.
Let's assume that to win most 50/50's we need to attain a score of 300. On Yahoo, our salary cap is $200. If we end up using every dollar of that amount, we would need our players to score an average of about 67 cents per point to get to 300.
In the LeBron example above, a $60 price tag on Yahoo would mean that he'd need to score 91 fantasy points to be a good enough value to get to 300, which isn't likely. If his salary was $45 instead, he'd need to score "only" 67 fantasy points to help us get there, which is a much more reasonable expectation.
Keep in mind that there is no absolute right or wrong way to calculate this. As long as you can correlate a player and a number to evaluate him relative to his output and salary, you're fine. I prefer the $ per-point method, personally.
I used LeBron as a static example, but let's use a recent situation to make the problem more relevant. With Justin Holiday out of favor in Chicago, David Nwaba ($14) is expected to take over his role. He's started two games since that development and averaged 31.3 YFP over that span. Let's see what we would need from Nwaba to get us to 300.
.67 = 14(salary)/x(player projection)
x = 20.8
At his current salary, we've already seen evidence that he's producing more than enough to help us reach our target score. All you need from Nwaba to meet the baseline value we want is 20.8 points.
Now comes the hard part. How do you calculate a player's projected points? If you like research, this may actually be the fun part.
Lineup changes like the one above, as well as single-game injury replacements, are obvious sources to make your projections. Many casual DFS players also like to use the Defense versus Position stat to help them make decisions, and it's been made popular by certain sites that list the figure next to each player. Defense vs. Position certainly has value, but I think players who rely on this stat may be putting too many eggs in one basket and are unwilling to do their homework.
While it can sometimes be a decent guideline, using information like Boston's defense is ranked 28th versus point guards is a broad-stroke analysis of how a team has played against a position for the entire season, without taking into account who they were actually defending, how well those players were playing, and how effective the team has recently been on defense.
A far better way to assess an opposing defense is to take a look at the team's last 5 to 10 games and see how well they've kept the position in check. This helps account for injury developments, as well as recent rotational trends. Looking at recent games is also a far better way to assess a current floor and ceiling for a player, rather than looking at the season-long averages. Overall, these are all effective methods, but there is one variable that is the most valuable tool when it comes to predicting a player's output.
PACE AND EFFICIENCY
We all know what the word pace means, but in basketball terminology, pace is measured primarily by the number of possessions a team can produce in any given game (standardized to a 48-minute basis). The more offensive possessions a team has, the more points and assists it can accrue. An uptick on the offensive end can mean more defensive possessions, as well, resulting in more opportunities for rebounds, steals and blocks. Simply put, the more possessions a team generates, the more opportunities there will be for Fantasy points.Although it's entirely predictive, if you're short on time and need to get a broad overview of a game, Las Vegas has already done the job for us by putting out an Over/Under line, which is an estimation of the total number of points that will be scored in a given matchup. Bettors have the option to wager on the game going higher or lower than the selected amount.
Another way to examine this is to actually look at the math yourself and make your own decisions, and here is where we need to take a team's offensive and defensive efficiency into account as a counterpart to their overall pace. To simplify, the statistical sweet spot is to target a player facing a fast-paced team that isn't particularly efficient on defense. I could bore you with a lot of equations about how we reach these numbers, but team pace factor and offensive/defensive efficiency are easy figures to find, not to mention a great deal faster than crunching the numbers yourself. Here are a few points to take into account when looking at these numbers:
- If a fast-paced team is facing a slower-paced team, both of their paces are affected. The wider the pace differential is, the more you should account for an increase/decrease of their original numbers. Oftentimes, when a fast-paced team faces a slow-paced team, it's a battle in which each side tries to force its style on the other. The NBA's slowest team (Memphis) will likely have more possessions when it matches up with the Lakers (the league's fastest team), but the Lakers will likely have fewer positions when they match up with Memphis, rather than, say, New Orleans, which plays at the third-fastest pace.
- These numbers can also be effective in position-specific situations. For example, the lower the opponent's offensive efficiency -- that is, how many points the team produces on a per-100-possessions basis -- the more likely it is that the center you're researching could see more rebound opportunities. The Lakers, for example, would be a good team to target for this specific instance, as they play at a fast pace but rank only 25th in offensive efficiency. In other words, the Lakers generate a high number of possessions, but they don't convert those possessions into points at a high rate -- at least relative to the rest of the NBA.
- Often, you'll notice a stat for rebounding efficiency in tandem with the other efficiency marks. A highly efficient offensive team will also be a good candidate for a point guard to see an uptick in assists, and so on.
- The best way to get accustomed to all of this information is to familiarize yourself with the tools available on sites like NBA.com/stats, Basketball-Reference, RotoWire and other fantasy sites.
