In this series, I'm going to look at players you think are good but aren't. For those who don't know where the title comes from, watch this crazy guy do NFL highlights (NSFW).
David Jones scored 27 goals this year, his first full year in the NHL. He's big, he's from North Vancouver, and plays on a hapless underdog in Colorado. What's not to like?
Let me tell you why that guy can hold my dick.
David Jones scored 27 goals!
Well, yes he did. He also had a less flattering 18 assists. More importantly for us, he had a miserable 67.3 fantasy points on the year. And his monthly splits suggest a very streaky player.
Streaky? All players have streaks - why is Jones being singled out?
If you had David Jones in November or February, you must have thought you were a genius. He had 29 fantasy points between those two months - a 'whopping' (read: just above waiver fodder) 1.2 points per game in those heady days. If you had him in the other 4-1/2 months of the year, his 0.7 points per game average must have been demoralizing, as well as damaging to your 'win' column.
Wait, how does a guy who gets 27 goals get 67 fantasy points?
I already mentioned that he only had 18 assists. In addition, he was a slight minus on the year and only had 153 shots. Plus, he wasn't a PP demon although he did get time there (20% of his points game from the PP).
Then we value shots too much! He scored 27 goals!!
Yeah, which means he shot at a 17% clip, or 3 points higher than Kovalchuk's career percentage (the highest career shooting % in the modern era). If he had shot at league average (~8%), he would have scored 13 goals. Even if we split the difference and call it a 20 goal season, the guy wouldn't have even made it into the top 25 free agents, never mind being a roster player. His 27 goals are not repeatable unless he gets a lot more ice time and a lot more shots. Counting his shots allows year-to-year stability in league scoring and maintains a divide between players who score 27 goals at a reasonable and repeatable 10% shooting, and those that have lucky seasons like David Jones.
Ha! This was his first full year in the NHL, so he probably will get more ice time next year!
It was his first full year, but he was 26 when it started and it was his 4th year playing more than 20 games in the show. In the three years previous he's had a torn ACL and two shoulder surgeries (same shoulder). So he hasn't even been developing somewhere. He's just been rehabbing for three years.
He played for the Coquitlam Express in the early 2000's, so it's hard not to like the guy. But any player who scores considerably more goals than assists (and does it with an elevated shooting percentage) is unlikely to repeat his success year to year. And honestly, his success was very modest. Still, Jones was held by at least 3 teams during the year, and was coveted by many more. I wouldn't be surprised to hear if some managers considered him a potential keeper.
That's why David Jones can hold my dick.
Sunday, 28 August 2011
Sunday, 21 August 2011
2010/11 Draft Review Part 2: Proportional Inter-round variance
In this series, we'll look at how valuable draft picks are by round and to each manager. Who does the best job of drafting, and how likely is any given manager to find a starter in each round?
PART TWO
In part one of this series, we looked at averages by round. We saw that there was a general decline in the average points scored by players selected in each successive round and concluded that we did well in predicting the average fantasy points of skaters.
In this post, we'll look at the rate of selecting high level players in each round. For this analysis, players who scored more than 80 fantasy points on the year are considered 'high level' or 'high impact.' This is a nice round number that represents roughly 1 fantasy point per game over the season. Exactly 1/3 of the skaters selected fall into this category (51 of 153 skaters taken), or an average of just over 4 players of this calibre per team. For comparison, 10 players taken in the whole draft scored 100 fantasy points or more.
We see in the chart above that Round 10 was the most successful by this metric, followed by Rounds 2 through 5. By a slightly adjusted metric, Round 1 is the clear winner, followed by Round 6 (shown below).
We see here the rate* of skaters taken in each round who scored 100 fantasy points or more. Round 1 had three players taken of this caliber, while Round 6 had 2. Only 5 other rounds contained players with 100 or more fantasy points, including the notorious Round 5.
You might remember from Part 1 that the average points of players selected in round 5 was under 57, or roughly 15 fewer than either round 4 or 6. These charts reveal the highly sensitive nature of averages, as 5 of the 12 players selected in that round went on to be 'high level' skaters, versus only three of those from Round 6 scoring more than 80 points (though 2 of those scored more than 100).
The conflict in those two descriptions of Round 5 (average vs. # of high level players) can be explained through injuries. Four players selected in Round 5 had serious injuries that limited them to 30 or fewer fantasy points. As always, injury is a major and mostly unpredictable factor in the success of a player. With that in mind, there is a fair argument for using point-per-game averages to determine successful draft picks. This, of course, suffers from the opposite sensitivity - is David Perron (13.9 points; 1.4 per game) as valuable as Shane Doan (101 pts; 1.4 per game)?
With these limitations (drafting for many reasons and injuries), this data cannot be understood as the likelihood of selecting a high impact player. Instead, we can only understand it as description for now (at least until we look at some of the trends within rounds).
A predictive model can be applied, however, and we see below the rate of selecting high impact skaters as well as a prediction of that rate if we ignore alternative motivations for drafting.
The orange line is the average rate of selecting a high impact player over all 14 rounds (1/3). The blue line is the actual rate of selecting those players.* Remember that some rounds had goalies selected as well, changing this graph slightly from the one above which simply counts the number of high impact players taken. Finally, the black line is what we might expect to see if we were reasonably successful at predicting the incidence of high-impact players and selected them accordingly.
Interestingly, somewhere in round 4 this predictive model suggests we should start selecting high impact players at a lower than average rate. More simply, the likelihood of selecting a high-level player after round 4 is below average. To re-phrase again, picks in the top four rounds can be seen as categorically (read: in a different category) better than those that come in the rounds to follow.
Taken as a whole, however, these graphs do not suggest a lot of hope for winning using the draft. On an average draft, a manager should expect to get between 4 and 5 players who score more than 1.0 fantasy points per game over a season, including between 0 and 1 player who reaches 100 fantasy points. Assuming 8 high impact keepers, that's between 12 and 13 skaters of high impact on your roster.
Still, with the unexpected variability in how many high impact players are taken in each round, we haven't yet resolved how valuable having high round picks can be in achieving an above average draft. Going by this data alone, we might conclude that Round 10 is the most valuable round, though our predictive model and Part One show a more logical connection between round of selection and performance. Next we'll look at the heart of each round (ignoring the first and last few picks) to see if there is an appreciable difference over the course of the draft.
*Rate (in this case) is the number of high impact players taken divided by the total number of players taken.
PART TWO
In part one of this series, we looked at averages by round. We saw that there was a general decline in the average points scored by players selected in each successive round and concluded that we did well in predicting the average fantasy points of skaters.
In this post, we'll look at the rate of selecting high level players in each round. For this analysis, players who scored more than 80 fantasy points on the year are considered 'high level' or 'high impact.' This is a nice round number that represents roughly 1 fantasy point per game over the season. Exactly 1/3 of the skaters selected fall into this category (51 of 153 skaters taken), or an average of just over 4 players of this calibre per team. For comparison, 10 players taken in the whole draft scored 100 fantasy points or more.
As we continue to delve into different ways of determining the value of draft picks and the value of a given draft pick relative to another, it's important to remember that with each pick choice become more constrained. Often we imagine that process being one of the best players going first and the worst players going last. Statistically, we expect to see a decline in the quality of players selected round to round, as well as to see the best players chosen earliest.
In reality, choice is made on a number of different variables (age, position, personal taste etc.) and is not always rational. We see in the chart below that the number of players with >80 points selected in each round is a not a very clear downward trend. This can be left as somewhat of a mystery for now, but keep in mind that some of these picks (eg. 3 of the first 4 picks overall) were chosen for their potential to be high level players in the long-term future, rather than for their likelihood of making an immediate fantasy impact.
We see in the chart above that Round 10 was the most successful by this metric, followed by Rounds 2 through 5. By a slightly adjusted metric, Round 1 is the clear winner, followed by Round 6 (shown below).
You might remember from Part 1 that the average points of players selected in round 5 was under 57, or roughly 15 fewer than either round 4 or 6. These charts reveal the highly sensitive nature of averages, as 5 of the 12 players selected in that round went on to be 'high level' skaters, versus only three of those from Round 6 scoring more than 80 points (though 2 of those scored more than 100).
The conflict in those two descriptions of Round 5 (average vs. # of high level players) can be explained through injuries. Four players selected in Round 5 had serious injuries that limited them to 30 or fewer fantasy points. As always, injury is a major and mostly unpredictable factor in the success of a player. With that in mind, there is a fair argument for using point-per-game averages to determine successful draft picks. This, of course, suffers from the opposite sensitivity - is David Perron (13.9 points; 1.4 per game) as valuable as Shane Doan (101 pts; 1.4 per game)?
With these limitations (drafting for many reasons and injuries), this data cannot be understood as the likelihood of selecting a high impact player. Instead, we can only understand it as description for now (at least until we look at some of the trends within rounds).
A predictive model can be applied, however, and we see below the rate of selecting high impact skaters as well as a prediction of that rate if we ignore alternative motivations for drafting.
Interestingly, somewhere in round 4 this predictive model suggests we should start selecting high impact players at a lower than average rate. More simply, the likelihood of selecting a high-level player after round 4 is below average. To re-phrase again, picks in the top four rounds can be seen as categorically (read: in a different category) better than those that come in the rounds to follow.
Taken as a whole, however, these graphs do not suggest a lot of hope for winning using the draft. On an average draft, a manager should expect to get between 4 and 5 players who score more than 1.0 fantasy points per game over a season, including between 0 and 1 player who reaches 100 fantasy points. Assuming 8 high impact keepers, that's between 12 and 13 skaters of high impact on your roster.
Still, with the unexpected variability in how many high impact players are taken in each round, we haven't yet resolved how valuable having high round picks can be in achieving an above average draft. Going by this data alone, we might conclude that Round 10 is the most valuable round, though our predictive model and Part One show a more logical connection between round of selection and performance. Next we'll look at the heart of each round (ignoring the first and last few picks) to see if there is an appreciable difference over the course of the draft.
*Rate (in this case) is the number of high impact players taken divided by the total number of players taken.
Upcoming in this series:
- Part 3: Inter-Round Variance Using Thirdiles and Interquartiles
- Part 4: Drafted versus Undrafted Skaters and Goalies
- Part 5: Inner-Round Variance by Round
- Part 6: Inner-Round Variance by Manager
2010/11 Draft Review Part 1: Absolute Inter-round variance
In this series, we'll look at how valuable draft picks are by round and to each manager. Who does the best job of drafting, and how likely is any given manager to find a starter in each round?
Goalies score more points than player, so including goalies in any average would considerably skew the graph. I've separated them out below.
Only 15 total goalies were selected, and as you can see, no goalies were selected in rounds 1, 4, 5, and 13. Thus, their averages aren't that meaningful. Still, we see that the round you select a goalie is not a clear indicator of the quality of goalie you get. In fact, the best goalie drafted (Carey Price) was selected in round 11, along with Dan Ellis and Antti Niemi. The best four goalies selected were taken in rounds 3, 6, 9 and 11.
In other words, in a very small sample size (15), we did a poor job of predicting the fantasy outcomes of goalies. For Shame!
Upcoming in this series:
- Part 2: Proportional Inter-Round Variance
- Part 3: Inter-Round Variance Using Thirdiles and Interquartiles
- Part 4: Drafted versus Undrafted Skaters and Goalies
- Part 5: Inner-Round Variance by Round
- Part 6: Inner-Round Variance by Manager
PART ONE
No draft pick comes with the guarantee of success. Injury and shifting roles can derail the fantasy production of even the best in the game. For us, that manifests in hits and misses, successes and failures in our drafts - a binary designation we sometimes have to wait a full 25 weeks to assign.
Well, it's been almost 48 weeks since we drafted our squads for the 2010/11 Definitely Offside season. It's about time we start finding the winners and losers.
Our draft comes with the wrinkle of having 96 players kept from season to season, effectively condensing the variance from the top of the draft board to the bottom. That said, the first overall pick was Taylor Hall, and the last pick was Igor Makarov. You know, the 24 year old with a point in the AHL for every year of his life.
We begin our analysis with that question of condensed variance. What is the difference in value in draft picks of different rounds? Is there an appreciable advantage to having a 1st round pick over a 2nd, or a 12th rounder over a 13th?
Now to tickle my favorite g-spot - GRAPHS!
In general we see a downward trend in average points per round, suggesting we selected the best players early and the worse players later. Duh, right? Well, it means we did a solid job of predicting fantasy point production as a group. Imagine comparing it to a draft in which players are randomly assigned to rounds. If that meant anything to you, you know we did a pretty good job.
The consequence of our collective success is that each successive round appears to hold a lower likelihood of selecting a high impact player than the round previous. In the graph above, the relation is not linear (Round 5 holds a disproportionate number of injuries, for example), reflecting the reality that the actual difference between the last pick of one round and the first pick of the next is just one player. Segregation by round is thus artificial. Moreover, round by round averages hide the success of each manager within the round. These are limitations I will return to in future posts on our draft. For now, lets stay at a macro-level and maintain our imposed round-by-round analysis for the sake of clarity.
 |
| Above: The average fantasy points scored by the skaters selected in each round |
The consequence of our collective success is that each successive round appears to hold a lower likelihood of selecting a high impact player than the round previous. In the graph above, the relation is not linear (Round 5 holds a disproportionate number of injuries, for example), reflecting the reality that the actual difference between the last pick of one round and the first pick of the next is just one player. Segregation by round is thus artificial. Moreover, round by round averages hide the success of each manager within the round. These are limitations I will return to in future posts on our draft. For now, lets stay at a macro-level and maintain our imposed round-by-round analysis for the sake of clarity.
Goalies score more points than player, so including goalies in any average would considerably skew the graph. I've separated them out below.
 |
| Above: The average fantasy points scored by skaters in each round again (blue) next to the average fantasy points scored by goalies selected in each round (red) |
In other words, in a very small sample size (15), we did a poor job of predicting the fantasy outcomes of goalies. For Shame!
Upcoming in this series:
- Part 2: Proportional Inter-Round Variance
- Part 3: Inter-Round Variance Using Thirdiles and Interquartiles
- Part 4: Drafted versus Undrafted Skaters and Goalies
- Part 5: Inner-Round Variance by Round
- Part 6: Inner-Round Variance by Manager
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