Welcome to my 9th-annual "Blue Jays Projected Record" article in which I sum individual projections for the Blue Jays players to project a win-loss record for the Blue Jays before the season starts. (See disclaimer below on accuracy.)
For each player, I projected his Equivalent Average (EqA). For those new to EqA, an average major league hitter has an EqA of .260, and an EqA of .300 represents excellence. Because of the DH rule, the average American League hitter has about a .264 EqA. EqA is directly related to how much the player helps the team score runs.
For projected EqA, in most cases I used a formula (same as last year) that incorporates past major league performance, past minor league performance (when major league data seemed insufficient) and the player's age. The idea is to come up with a middle-of-the-road projection (not to project "breakouts"). Like last year I also made some minor subjective adjustments and rounded to a multiple of .005.
For projected plate appearances (PA), I picked a number in line with the player's playing time history but also considered how the Jays intend to use the player this year.
Here are the individual hitting projections:
Age ProjEqA
Catalanotto LF 31 .265 350 PA
OHudson 2B 27 .260 600 PA
VWells CF 26 .285 650 PA
Koskie 3B 32 .275 450 PA
Hillenbrand DH 29 .260 550 PA
Hinske 1B 27 .255 500 PA
Rios RF 24 .250 550 PA
Zaun C 34 .240 300 PA
RAdams SS 24 .245 450 PA
Age ProjEqA
RJohnson OF 28 .245 450 PA
Gross OF 25 .250 400 PA
McDonald IF 30 .200 300 PA
Menechino IF 34 .255 250 PA
Myers C 39 .240 150 PA
Quiroz C 23 .240 100 PA
Huckaby C 34 .170 100 PA
----
6150 PA
The team offense projects to a .253 EqA. Remembering the 4% adjustment for the DH league, this works out to an offense 10% worse than league average:
(.253/.260)^2.5 / 1.04 = 0.90 (10% below league average)
For example, if you figure an average team will score 5 runs per game, then the Jays would project to score 5*0.90 per game (4.50).
This performance would actually be an improvement from last year's offense which was 14% worse than average (depending on the park factor estimate). Improvements are expected from Hinske, Wells and Catalanotto, all of whom had worse than expected years last year. The bounce back would be expected to be a lot greater if the Jays had retained Delgado.
For projected opponents EqA, while I looked at formula estimates based on the pitchers' runs allowed history and "defense-independent" history (as per McCracken theory) including recent minor league history if major league data seemed insufficient, and while the pitcher's age was also considered, a lot of subjective reasoning went into the final estimate.
For projected innings pitched (IP) and games started (GS), I picked numbers in line with what the pitcher had done in the past (adjusted somewhat based on the Jays' expected use of the player).
In principle, one should adjust for team fielding if its quality is expected to be different than most of the pitchers are used to, but I don't expect a big quality difference from last year.
For those not used to opponents EqA as a pitching stat, remember that .260 is average (like having a 4.50 ERA, or a .500 pitcher). Halladay's runs allowed average in his Cy Young year translated to a .231 opponents EqA. "Replacement level" (what the better triple-A pitchers can probably do) would be about .275.
Here are the individual pitching projections:
Starters:
Age OppEqA
Halladay 28, 210 IP, .240, 32 GS
Lilly 29, 180 IP, .255, 29 GS
Bush 25, 175 IP, .250, 30 GS
Chacin 24, 140 IP, .270, 25 GS
Towers 28, 120 IP, .270, 22 GS
Walker 36, 45 IP, .280, 10 GS
Glynn 30, 30 IP, .280, 7 GS
Downs 29, 15 IP, .290, 4 GS
McGowan 23, 15 IP, .270, 3 GS
----
930 IP
Pen:
Age OppEqA
Batista 34, 90 IP, .260
Frasor 27, 70 IP, .250
Schoeneweis 31, 70 IP, .270
Speier 31, 70 IP, .250
Chulk 26, 80 IP, .270
Ligtenberg 34, 40 IP, .270
League 22, 40 IP, .270
Miller 27, 30 IP, .285
Gaudin 22, 25 IP, .270
---
515 IP
Overall that works out to a projected .260 opponents EqA for the staff, which is league average. This would actually be a slight decline from 2004, when the Jays' pitching & defense was 2% better than average. The decline is mainly from not expecting Lilly to repeat his all-star performance of 2004.
To estimate the projected team winning percentage, we use the Pythagorean formula with an exponent of 1.83:
0.90^1.83 / (0.90^1.83 + 1.00^1.83) = 0.452 wpct -->73 wins, 89 losses
So that's my official projection this year: 73 wins.
73 wins would be 6 more wins than last year's team achieved, and would be 2 more than last year's Pythagorean record.
Toss a fair coin 162 times, and your best bet is to predict 81 heads, but there's only a 6% of chance of that happening, even though it really is the best bet. There's a 5% chance that the fair coin will produce either 68 heads or fewer or 94 heads or more.
Even if this article has accurately estimated the Jays' probability of winning each game, there's just a 6% chance of the projected win total matching the actual. The 95% confidence interval for an "73-win coin" is approximately 61 to 85 wins.
(But we're not claiming to even be 95% sure of a 61 to 85 win season because we can't be sure the errors in the individual projections will all cancel out, and we can't be sure that all the other assumptions of this article are valid.)
Last year's projection was 87 wins and the team just won 67, off by 20. In the previous 7 years, the projection was off by at most 7 wins. What happened last year?
I did a per-player comparison of the 2003 and 2004 Jays in Wins Above Replacement (near the bottom of the 2004 team article), and it found that the returning players, i.e. the players who played for both the 2003 and 2004 teams, were collectively 26 wins worse in 2004 than 2003. If those players had performed in 2004 as in 2003, and if the Pythagorean had evened out, the Jays would have won 97 games in 2004.
In that light, the projection of 87 wins looks somewhat conservative, and I still think it was pretty reasonable given the information at the time. The Jays had an unusual number of things go wrong in 2004.
But if last year was a fluke, then why is this year's projection 14 wins less than last year's? Partly it's from losing Delgado, who might be 5 wins better than his replacements. Most of the rest is from incorporating the information from last year. e.g. for Eric Hinske, the information from before 2004 would suggest a .280 season this year, but the information from 2004 suggests a .235 season this year. The projection method was to average in all years, with more weight on more recent years, which led to the .255 projection above.
Previous year's articles are on the web at
Sources:
-- Stephen Tomlinson http://www.stephent.com/jays/ mailto:stephent@magma.ca Ottawa, Ontario "What is the evidence, and what does it mean?" (Bill James)
Last Updated: 2005 Mar 27
Comments are welcome at comments@stephent.com.