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What do the Numbers Say? Projecting the Raptors' Win Total for the 2016-17 Season

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Let's take a look at a couple of common catch-all statistics to see what we can predict in terms of wins for the Raptors this coming season.

Dan Hamilton-USA TODAY Sports

The Raptors' off season appears to be over, for the most part, so let's take a look at what they might be able to achieve this regular season.

All the core pieces remain on the team, with two major losses in Bismack Biyombo and Luis Scola, while James Johnson also played meaningful minutes for the team. Their replacements mostly come in the form of larger roles for young players on the team, as well as adding Jared Sullinger to fill in both big man spots.

Given that, it would be pretty safe to predict a similar result to last season. But with ESPN making their early expert predictions, and the Raptors coming in with a five win decrease from last season, it seems the early expectations are a step back for this club.

So, let's see if there's any reason to be slightly more optimistic.

Basketball Reference captures an incredible range of basketball statistics, ranging from box scores to shooting percentages from different distances, to more advanced offerings of all sorts. But they are likely most widely known for their two popular catch-all statistics -- win shares, a box score aggregator of sorts, that mostly measures production, and box plus minus (BPM), an attempt to measure a player's impact.

Win shares are easy to translate into wins -- just add up the win shares for each player and the team total should be how many wins the team achieves. BPM can be translated into a wins over replacement player (WORP) value. Add up the WORP for each player on the team and you'll get how many wins better than a replacement team you'd expect. A replacement team, by my calculations (and based on the definition of "replacement player" by basketball-reference), is expected to earn about 15.5 wins.

So, let's take a quick look at some past data to see how well these statistics align with reality, and how predictive they may be. We'll just use the last two seasons as a sample to give a rough idea how these things have tracked for the Raptors in recent years.

First, here are the actual results from the 2014-15 season.

There you can see the win shares (WS) earned by each player throughout the season, broken into offensive WS and defensive WS, and converted into a per 48 minute rate value as well (which we will use in the projections below). Similarly, the offensive and defensive BPM for each player, and the resultant WORP (including, again, a per 48 minute version).

Taking the sum of the WS for the 2014-15 season, the Raptors' total came to 50.6 wins, 1.6 wins above their actual record of 49-33. Looking at WORP, the total comes to 35.6 wins. Remember, WORP is wins over replacement player, so the win total is how many wins above a replacement team are achieved, with a replacement team defined above as worth roughly 15.5 wins. So the win total from the WORP calculation comes to 51.1 wins, 2.1 wins above the 49-33 record.

Let's take a look at the results of the 2015-16 season now.

Once again, taking the sum of the WS generated, we get a total of 54.5 wins, 1.5 wins below the actual record of 56-26 last season. Doing the same for WORP results in 41.0 WORP, or 56.5 wins. In this case WORP measured the season very accurately, within a half win of the actual total, while WS again showed roughly a 1.5 win error. For both seasons, an error of roughly two wins either way seems to be about the level of accuracy provided.

So, given a degree of confidence (the above is just a demonstration, of course, these statistics have been tested and proofed far beyond what I'm showing here) in the correlation between these measured "win" statistics and the actual win totals for teams, let's move on to projecting future seasons.

Here is the method I've come up with to remove myself (and my biases and assumptions) from the projections as much as possible.

1) Compile the current roster of players on the team.

2) From the previous season, take total minutes played, WS/48 and WORP/48 for each player.

3) Assume all players will play the same minutes they did the previous season.

4) Sum the total minutes played for the team. It should (but won't) be 19,680 (48 minutes times five positions times 82 games).

5) Scale all players' minutes by the ratio of total team minutes to 19,680. For example, if the sum from step 4 is only 17,890 minutes played, all players will see their minutes from the prior season increase by 10% (since 17890 x 1.1 = 19,680).

6) The new sum of adjusted player minutes will equal 19,680.

7) Use the new minute assumptions for each player and multiply by their WS/48 and WORP/48 values to get total WS and WORP numbers.

8) Sum the WS and WORP numbers for the entire team to get the projected win total.

This process has no assumptions about roles, minutes, usage or fit. Its only assumption is that the best indicator of future role, minutes, etc, is the previous season. There are certainly cases where this is not likely. For example, perhaps Norman Powell or Lucas Nogueira will get a larger role this season than last. But perhaps not. Perhaps Lowry will see his minutes reduced. But perhaps not. In any case, this is the method I've chosen to remove myself from the process as much as possible.

Let's take it for a test drive. First, by using the data from 2014-15 to retroactively "predict" how 2015-16 should have gone. Here is the information outlined in the 8 steps above used to predict 2015-16.

In this case, the total minutes for the team when simply assembled from the prior season was 18,809. So the total minutes load for each player was assumed to increase by roughly 5%, as seen in the change from the "MP total" column to the "MP adj" column.

The predicted win totals for last season using this methodology were 54 WS and 38.4 WORP (53.9 wins). The two projections are very close together, which is nice but probably a simple coincidence. More importantly, both models predicted roughly 54 wins -- only two wins off the actual result of 56-26, and far above (and therefore more accurate than) the predictions of most pundits and analysts prior to last season.

Now that we have an example of this prediction method showing predictive results in line with the measurement accuracy shown after the fact for the last two seasons (an error of roughly two wins for both models), let's go ahead with the projection for this coming season.

Once again, like last year's projection, we have a minutes deficit, so once again players get a minutes boost. Right away we can say this is unlikely, so a little further down I'll allow myself to modify some stuff to avoid obvious problems like Lowry playing 3,300 minutes (40 MPG). But for now, the raw results of the projection look pretty nice. By WS, the team projects to have 55.5 wins, right in line with last season's results. By WORP, the team projects to an incredible 63.2 wins. That's an inflated number due to those Lowry minutes, but still, that's a pretty nice starting point for a projection, a win range of 55-63 wins.

Let's make those reasonable changes though. Lowry will almost certainly not play more minutes than he did last season, and nor will DeRozan. Meanwhile, we'd expect many more minutes for Carroll and Valanciunas due to lack of injury. So if we simply take the minutes increase allocated to DeRozan and Lowry and instead allocate it to Carroll and Valanciunas, we end up with Valanciunas playing 2,267 minutes (the equivalent of playing last season's minutes but for 77 games instead of 60) and Carroll playing 1,368 minutes (the equivalent of playing last season's minutes but for 46 games instead of 26). That's as small and reasonable a change as I can make to preserve the integrity of the analysis and prevent outlier inputs like huge minutes for the Raptors' star guards.

Given those changes, we see a reduction in Lowry's production from 13.5 to 11.6 WS, and from 19.8 to 17 WORP. While DeRozan decreases from 11.5 to 9.9 WS, and from 7.5 to 6.5 WORP. Valanciunas sees an increase from 8.0 to 10.0 WS, and from 3.8 to 4.7 WORP, and Carroll sees an increase from 1.4 to 2.1 WS and from 1.3 to 1.9 WORP. All told, the team total slides down to 54.7 wins (by WS) and 60.9 wins (by WORP). While having a minute distribution that is feasible.

These are still very nice projections. Considering that both WORP and WS have seemed limited to small errors (roughly two wins), both in the after-the-fact measurements and the sample projection we looked at, the simplest way to minimize the error for both measures is to settle nicely in the middle. Which means the final projected record for the team as constructed, with as few assumptions as possible on my part, is 58-24.

Yep. 58 wins. In all likelihood the team doesn't quite reach that, for various reasons, including hopefully a more restricted minute load for DeRozan and Lowry, and a larger role for the young players on the team. But for those who are thinking this off season represents a significant downgrade in talent from last season, or that a player like Bismack Biyombo disproportionately contributed to the team winning so many games: It really doesn't look that way at all.

All stats from basketball-reference.com, just a tremendous site for basketball stats and has been for some time. Make sure to pay them a visit, especially if you want a more in-depth explanation of WS or BPM.