Figure 3.1: Draft Pick Value Chart

Transcription

1 CHAPTER 3. DRAFT PICK VALUE 52 Figure 3.1 is a plot of our results. Figure 3.1: Draft Pick Value Chart Using this chart is fairly straightforward. You find the value of each draft pick involved in the trade and add up the values on each side of the trade. Going back to the original question of this chapter, we find that the 2nd overall pick has a value of 860. So, in order to make a fair o er to trade for the 2nd overall pick, you need to make sure the picks you o er in return add up to something close to 860. Reading numbers o of the plot is a bit di cult, so we ve provided a table of data to assist you (see Table 3.2). Keep in mind that this is not a perfect model, but more of a guide to help you understand trade value of draft picks. 5 You might also wonder why 12th round picks have virtually no value in this model. The answer is because 12th round pick players in fantasy hockey are easily replaceable on the waiver wire. 5 We used a standard 12-team default league in Yahoo as our guide in these simulations. A league with more scoring categories might see a more severe slope to their plot. A league with more physical categories would see a less severe slope.

2 CHAPTER 5. ANALYSIS OF THE NHL SCHEDULE 64 Figure 5.2: NHL Schedule by Day of the Week The bye week will consist of at least five consecutive days in which the players will neither practice nor play hockey. The bye week must be independent from the All-Star break dates. These bye weeks could have a significant impact on head-to-head match-ups in fantasy hockey. We ve compiled all of these bye weeks for you in Table 5.3 so that you can prepare accordingly. The largest impact may be felt in leagues that require a minimum number of goalie starts each week. Imagine owning Jake Allen and Martin Jones. In this scenario, you d get zero goalie starts from February 20 - February 24. But skaters will feel the impact as well. For example, Sidney Crosby does not play a single game in the first seven days of January. 6 While these bye weeks will be important to you during the season, we do not recommend that you craft a draft strategy that incorporates these bye weeks. All of the bye weeks occur long before any of the fantasy hockey playo s begin. 6 Of course this extends to players like Evgeni Malkin, Kris Letang, Phil Kessel, etc. Table 5.3: NHL Bye Weeks Team Days O Bye Week ANA ARI BOS BUF CAR CBJ CGY CHI COL DAL DET EDM FLA LOS MIN MTL NJD NSH NYI NYR OTT PHI PIT SJS STL TBL TOR VAN WSH WPG Rested vs. Tired Games Played One other important method for analyzing the NHL schedule is determining which teams are playing rested and which teams are playing tired. The criterion for determining whether a team is rested or tired is simple: find out if the team played hockey yesterday.

3 CHAPTER 5. ANALYSIS OF THE NHL SCHEDULE 66 Figure 5.3: Rested & Tired Games Played in the NHL

4 CHAPTER 6. KEY INJURIES & ISSUES 69 Matt Beleskey - Boston Bruins Injury: Hand : Had hand surgery on April 14 and is expected to need six weeks for recovery. a a Jamie Benn - Dallas Stars Injury: Core : Underwent surgery to repair a core muscle injury and is expected to need six weeks for recovery. a : Dropped out of the World Cup of Hockey. Dallas Stars GM Jim Nill says Benn will be at 100% to start the season. b a b Nick Bjugstad - Florida Panthers Injury: Hand : Will miss four weeks due to a broken hand. a a Ryan Callahan - Tampa Bay Lightning Injury: Hip : Will miss five months following hip surgery. a : Skated for the first time since surgery. He is expecting a mid-november return. b a b

5 CHAPTER 11. SHOOTING PERCENTAGE AS A TOOL Using SH% in Your Fantasy Draft We will now use the techniques described above to project which NHL players are most likely to see a decline in their SH% (and very likely experience a corresponding decline in overall goal scoring). Note that we chose a cuto requiring the players to have taken at least 150 SOG during the season. It is important to make the distinction here between regression and having a bad season. We are not projecting the players in the table below to necessarily have bad seasons. We are not necessarily telling you to avoid particular players on this list. We are simply projecting the players below to see significant reductions in their shooting percentages that fall more in line with their career averages. this list manages to be on a line with improved linemates in , then his expected drop might be slightly muted by this minor uptick. This is precisely the situation we had in mind when we mentioned early on in the draft guide that we prefer a blend of mathematics complemented by a situational awareness for both individual players and teams. For a powerful 1-2 punch, combine the above list with the fact that most NHL players experience a natural decline in their SH% after the age of Your condensed list would include names such as: Zack Smith, Jannik Hansen, Shane Doan, Brent Seabrook, Matt Cullen, Duncan Keith, Jaromir Jagr, Mikko Koivu, Mats Zuccarello, Nicklas Backstrom, and Shea Weber. History tells us that only 1 or 2 players from the table above will buck the trend of dropping in goal production. Do you really like your odds (0%-10%) of picking that specific player to draft? Table 11.3: Likely Regression Candidates Player Career Zack Smith Jannik Hansen Shane Doan Cody Ceci Brent Seabrook Matt Cullen Duncan Keith J.T. Miller Artem Anisimov Jaromir Jagr Mikko Koivu Mats Zuccarello Nicklas Backstrom Shea Weber Joe Colborne There is evidence that elite players can boost the SH% of their linemates by about 1%. 1 If a forward on Case Studies in Shooting Percentage Claude Giroux: Claude Giroux remained goalless through the first 15 games of the NHL season. By mid- November, he had scored only one goal on 46 shots for a 2.2% shooting percentage. Frustrated by his performance (and that of the entire Flyers team), many fantasy hockey managers gave up on Giroux and either dropped him or traded him for weak returns. At the time, Giroux was a career 12.1% shooter. 3 Using our results from the coin flip discussions earlier in this kit, we know that 68% of the time his season-long shooting percentage should fall within 10% - 14%. 2 shooting-percentage-vs-age 3 His current career average is 11.0%

6 CHAPTER 13. ASSISTS: THEORY 114 Figure 13.2: Drop in Production of Secondary Assists 13.1, it s not nearly as interesting as it looks. 7 The reason this part of the graph looks suspicious is the following: players who earn very few secondary assists in one season (think 1-2 secondary assists) will often see large changes in their totals (positive or negative). Why? Because if you only have one or two of a quantity to begin with, then moving up or down by one or two results in a very large percentage change (two is 100% growth over one, zero is -100% growth over one). It s as simple as that. But wait, you protest! Why doesn t the graph ever go below 7 Actually, it is kind of interesting, it s just not very useful for fantasy hockey managers. -100%? Because once you lose 100% of something, you haven t got anything else to lose. Many of the players who post more than 0.3 secondary assists per game in one season will see drops as large as 50% in the following season. 8 This is exactly what happened to Duncan Keith in His secondary assists per game dropped from 0.44 in (second best of all skaters in the NHL) to only 0.20 in (putting him outside the top 8 Not all of the players will experience drops that big, but Figure 13.1 clearly shows that many of the players see drops on the order of 25% to 50%.

7 CHAPTER 20. THE REPEATABILITY OF FANTASY HOCKEY STATS - PART II 141 Figure 20.2: Year-to-Year Blocked Shots Data The R 2 value for blocked shots has been determined to be 0.86 and is one of the strongest correlations of any stat in fantasy hockey. If you re drafting players based on their ability to blocked shots, you can do so with great confidence. Notice how the majority of the data points are bunched up along a straight line flowing from the lower-left hand side to the upper-right hand side. This tight bunching of the data (almost forming a straight line) will be seen in most data sets with a high R 2 value Basic Scoring Categories Goals Now we ll get into some of the more common scoring categories used in fantasy hockey. The results for goals are shown in Figure While there is a solid relationship between past goals and future goals, our draft kit does not use past goals to predict future goals (more on this later!).

8 CHAPTER 34. LEGEND FOR DRAFT KIT SPREADSHEETS 202 Table 34.1: Legend for Skaters Spreadsheet Abbreviation Definition NHLPOS Player s position as defined by the o cial NHL website. YPOS Player s position as defined by the o cial Yahoo fantasy hockey website. ADP Yahoo Average Draft Position. AUC Yahoo Average Auction Value. OWN Yahoo Percentage of all leagues in which player was drafted. EADP ESPN Average Draft Position. EAUC ESPN Average Auction Value. EOWN ESPN Percentage of all leagues in which player was drafted. DAY1AGE Player s age on October 12, CSHPCT Career shooting percentage. LYSHPCT Last year s shooting percentage. AEVTOI Average even-strength time on ice. APKTOI Average penalty kill time on ice. APPTOI Average power play time on ice. ATOI Average time on ice. SHFG Shifts per game. CG Career average goals expressed as a rate per 82 games played. CA Career average assists expressed as a rate per 82 games played. CPTS Career average points expressed as a rate per 82 games played. CSOG Career average shots on goal expressed as a rate per 82 games played. 3YGP 3YG 3YA 3YPTS 3YH 3YBS 3YFOW 3YSHG 3YSHA P G P A P PTS P H P BS P FOW P PIM P PPG P PPA P PPP P AT OI PR Three-year average games played expressed as a rate per 82 games played. Three-year average goals expressed as a rate per 82 games played. Three-year average assists expressed as a rate per 82 games played. Three-year average points expressed as a rate per 82 games played. Three-year average hits expressed as a rate per 82 games played. Three-year average blocked shots expressed as a rate per 82 games played. Three-year average face-o wins expressed as a rate per 82 games played. Three-year average shorthanded goals expressed as a rate per 82 games played. Three-year average shorthanded assists expressed as a rate per 82 games played. Projected goals for the season. Projected assists for the season. Projected points for the season. Projected hits for the season. Projected blocked shots for the season. Projected face-o wins for the season. Projected penalty minutes for the season. Projected power play goal for the season. Projected power play assists for the season. Projected power play points for the season. Projected average time on ice for the season. Performance Rating. An overall score assigned to assess the player s worth.

9 CHAPTER 34. LEGEND FOR DRAFT KIT SPREADSHEETS The Goalies Spreadsheet Table 34.2: Legend for Goalies Spreadsheet Abbreviation Definition ADP Yahoo Average Draft Position. AUC Yahoo Average Auction Value. OWN Yahoo Percentage of all leagues in which player was drafted. EADP ESPN Average Draft Position. EAUC ESPN Average Auction Value. EOWN ESPN Percentage of all leagues in which player was drafted. DAY1AGE Player s age on October 12, EVSVPCT even-strength save percentage. PKSVPCT penalty kill save percentage. PPSVPCT power play save percentage. CGP Career games played. CW Career wins. CGAA Career goals against average. CSVPCT Career save percentage. CSHO Career shutouts. 3YGS 3YW 3YSV 3YGAA 3YSVPCT 3YEVSVPCT 3YPKSVPCT 3YSHO 3YTOI P GS P W P L P OTL P SA P SV P GA P GAA P SVPCT P SHO Three-year games started total. Three-year wins total. Three-year saves total. Three-year goals against average. Three-year save percentage. Three-year even-strength save percentage. Three-year penalty kill save percentage. Three-year shutouts total. Three-year minutes played total. Projected starts for the season. Projected wins for the season. Projected regulation losses for the season. Projected overtime losses for the season. Projected shots against for the season. Projected saves for the season. Projected goals against for the season. Projected goals against average for the season. Projected save percentage for the season. Projected shutouts for the season.

10 CHAPTER 39. BOSTON BRUINS 228 be considered minimal Schedule Details The Boston Bruins have 14 back-to-back sets this season. In Figure 39.1, we ve broken down their schedule by days of the week. Figure 39.1: Boston Bruins Schedule By Day

11 CHAPTER 39. BOSTON BRUINS Player Movement Recent Acquisitions Player Position Former Team David Backes C STL John-Michael Liles D CAR Riley Nash C CAR Anton Khudobin G ANA Players Who Left Player Position New Team Brett Connolly R WSH Chris Kelly C OTT Dennis Seidenberg D UFA Landon Ferraro C STL Lee Stempniak R CAR Loui Eriksson R VAN Matt Irwin D NSH Max Talbot C UFA Zach Trotman D LAK Jonas Gustavsson G EDM 39.7 Projected Lineup Once the season begins, you can find all of the detailed line combinations for the Boston Bruins here: Here is a preview of what the lines might look like in Boston this season: Projected Forwards Left Wing Center Right Wing Brad Marchand Patrice Bergeron David Backes Matt Beleskey David Krejci David Pastrnak Ryan Spooner Dominic Moore Seth Gri th Jimmy Hayes Riley Nash Noel Acciari

12 CHAPTER 39. BOSTON BRUINS 232 Figure 39.2: Boston Bruins Player Usage Chart Overtime Units Player 1 Player 2 Player 3 Frequency (%) PATRICE BERGERON BRAD MARCHAND TOREY KRUG 22 DAVID KREJCI LOUI ERIKSSON TOREY KRUG 7.7 LOUI ERIKSSON ZDENO CHARA DENNIS SEIDENBERG 3.9 PATRICE BERGERON RYAN SPOONER TOREY KRUG 3.6 PATRICE BERGERON RYAN SPOONER ZDENO CHARA 3.3