{"id":520,"date":"2013-02-07T14:21:35","date_gmt":"2013-02-07T19:21:35","guid":{"rendered":"http:\/\/blog.rotovalue.com\/?p=520"},"modified":"2013-02-07T14:21:35","modified_gmt":"2013-02-07T19:21:35","slug":"comparing-projected-rotovalue-prices","status":"publish","type":"post","link":"https:\/\/blog.rotovalue.com\/index.php\/2013\/02\/07\/comparing-projected-rotovalue-prices\/","title":{"rendered":"Comparing Projected 2012 RotoValue Prices"},"content":{"rendered":"<p>I&#8217;ve previously compared five MLB projection systems for <a href=\"http:\/\/blog.rotovalue.com\/reviewing-five-2012-mlb-projection-systems\/\">batting<\/a>\u00a0and <a href=\"http:\/\/blog.rotovalue.com\/reviewing-pitching-projections\/\">pitching<\/a>\u00a0rate statistics, comparing the projections for 2012 with actual data. This post will compare 4 systems by looking at the RotoValue prices for a given projection stat set and league setup compared with actual 2012 data for the same setup. The four systems I&#8217;m testing will be:<\/p>\n<ul>\n<li><a href=\"http:\/\/www.rlyw.net\/\">CAIRO<\/a>\u00a0&#8211; from S B of the\u00a0<a href=\"http:\/\/www.rlyw.net\/\">Replacement Level Yankees Weblog<\/a>.<\/li>\n<li><a href=\"http:\/\/www.tangotiger.net\/marcel\/\">Marcel<\/a>\u00a0&#8211; the basic projections from Tom Tango, coauthor of\u00a0<a href=\"http:\/\/www.insidethebook.com\/\">The Book<\/a>.<\/li>\n<li><a href=\"http:\/\/steamerprojections.com\/\">Steamer<\/a>\u00a0&#8211; developed by Jared Cross, Dash Davidson, and Peter Rosenbloom.<\/li>\n<li><a href=\"http:\/\/blog.rotovalue.com\/?p=181\">RotoValue<\/a>\u00a0&#8211; my own old projection algorithm.<\/li>\n<\/ul>\n<p>Conspicuously absent is the\u00a0<a href=\"http:\/\/www.baseballthinkfactory.org\/oracle\/discussion\/2012_zips_projections_spreadsheets_v._1\">ZiPS<\/a>\u00a0&#8211; projections from Dan Szymborski of\u00a0<a href=\"http:\/\/www.baseballthinkfactory.org\/\">Baseball Think Factory<\/a>\u00a0and\u00a0<a href=\"http:\/\/search.espn.go.com\/dan-szymborski\/\">ESPN<\/a>, which I included in the other comparisons. I&#8217;ve left ZiPS out, however, because that system makes no serious attempt to project playing time, and it also (or at least the version I got from last season) did not project pitcher saves. This leaves that system at a marked disadvantage relative to other systems, so I thought it best to omit it.<br \/>\nI&#8217;m also including unadjusted 2011 data as another model.<br \/>\nFrom a fantasy perspective, a big use of projections is to help value players and determine how much one should spend on them. While projecting rate stats well is a better indicator of how good a projection system is at reflecting a player&#8217;s current talent level, a fantasy owner cares both about talent level and playing time. RotoValue prices are designed to compare players&#8217; contributions to a fantasy team given its league parameters, so they&#8217;re a good shorthand way to combine both skill and playing time into a single number.<br \/>\nSo let&#8217;s take a look&#8230;<!--more--><br \/>\nI ran numbers for the 5 different league configurations\u00a0I highlighted when announcing my first cut <a href=\"http:\/\/blog.rotovalue.com\/2013-mlb-projections-take-1\/\">projections for 2013<\/a>.<br \/>\nFirst up, a <a href=\"http:\/\/www.rotovalue.com\/cgi-bin\/Search?year=2012&amp;league=23&amp;source=RotoValue\">4&#215;4 AL only league<\/a>. The first table shows averages for each player for whom the projection system had some nonzero stats projected. The second table shows the averages only among players projected by every system being compared (counting 2011 as a projection system).<\/p>\n<table>\n<tbody>\n<tr>\n<th>Source<\/th>\n<th>Num<\/th>\n<th>Price<\/th>\n<th>StdDev<\/th>\n<th>MAE<\/th>\n<th>RMSE<\/th>\n<\/tr>\n<tr>\n<td>2012<\/td>\n<td>622<\/td>\n<td>0.832<\/td>\n<td>10.044<\/td>\n<td>0.000<\/td>\n<td>0.000<\/td>\n<\/tr>\n<tr>\n<td>Steamer<\/td>\n<td>576<\/td>\n<td>1.464<\/td>\n<td>9.956<\/td>\n<td>5.880<\/td>\n<td>8.103<\/td>\n<\/tr>\n<tr>\n<td>Marcel<\/td>\n<td>507<\/td>\n<td>2.705<\/td>\n<td>10.145<\/td>\n<td>6.581<\/td>\n<td>9.100<\/td>\n<\/tr>\n<tr>\n<td>2011<\/td>\n<td>484<\/td>\n<td>3.352<\/td>\n<td>10.064<\/td>\n<td>7.007<\/td>\n<td>9.489<\/td>\n<\/tr>\n<tr>\n<td>RotoValue<\/td>\n<td>406<\/td>\n<td>4.832<\/td>\n<td>9.888<\/td>\n<td>7.338<\/td>\n<td>9.669<\/td>\n<\/tr>\n<tr>\n<td>CAIRO<\/td>\n<td>584<\/td>\n<td>1.112<\/td>\n<td>10.525<\/td>\n<td>7.293<\/td>\n<td>9.956<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>382 players projected by all systems<\/p>\n<table>\n<tbody>\n<tr>\n<th>Source<\/th>\n<th>Num<\/th>\n<th>Avg Price<\/th>\n<th>MAE<\/th>\n<th>RMSE<\/th>\n<\/tr>\n<tr>\n<td>2012<\/td>\n<td>382<\/td>\n<td>3.717<\/td>\n<td>0.000<\/td>\n<td>0.000<\/td>\n<\/tr>\n<tr>\n<td>Steamer<\/td>\n<td>382<\/td>\n<td>4.895<\/td>\n<td>6.469<\/td>\n<td>8.684<\/td>\n<\/tr>\n<tr>\n<td>Marcel<\/td>\n<td>382<\/td>\n<td>5.031<\/td>\n<td>7.287<\/td>\n<td>9.611<\/td>\n<\/tr>\n<tr>\n<td>RotoValue<\/td>\n<td>382<\/td>\n<td>5.289<\/td>\n<td>7.510<\/td>\n<td>9.846<\/td>\n<\/tr>\n<tr>\n<td>2011<\/td>\n<td>382<\/td>\n<td>5.113<\/td>\n<td>7.606<\/td>\n<td>9.885<\/td>\n<\/tr>\n<tr>\n<td>CAIRO<\/td>\n<td>382<\/td>\n<td>3.580<\/td>\n<td>7.995<\/td>\n<td>10.648<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>My first observation is that the errors in the second table are all much higher than in the first table, which does make sense to me. While the RotoValue model does allow for negative prices, indeed rather large ones, there is less variation among players who play very little than among those who play often. So projecting more players implies projecting those expected to get less time, which improves the overall average errors. This also matches the changes in RMSE, with CAIRO, which projected the most players, rising the most when I test the smaller set, and RotoValue, which projected the fewest players, rising the least.<br \/>\nI think the second table puts systems on a more equal footing (although systems that project players other systems don&#8217;t do not get credit for that). Steamer, which had the lowest overall errors in projecting pitching percentage stats, does best here, too.<br \/>\nNext, a\u00a0<a href=\"http:\/\/www.rotovalue.com\/cgi-bin\/Search?year=2012&amp;league=24&amp;source=RotoValue\">4&#215;4 NL<\/a>\u00a0league:<\/p>\n<table>\n<tbody>\n<tr>\n<th>Source<\/th>\n<th>Num<\/th>\n<th>Price<\/th>\n<th>StdDev<\/th>\n<th>MAE<\/th>\n<th>RMSE<\/th>\n<\/tr>\n<tr>\n<td>2012<\/td>\n<td>707<\/td>\n<td>-0.588<\/td>\n<td>10.138<\/td>\n<td>0.000<\/td>\n<td>0.000<\/td>\n<\/tr>\n<tr>\n<td>Steamer<\/td>\n<td>646<\/td>\n<td>0.195<\/td>\n<td>10.233<\/td>\n<td>5.899<\/td>\n<td>8.270<\/td>\n<\/tr>\n<tr>\n<td>Marcel<\/td>\n<td>575<\/td>\n<td>1.499<\/td>\n<td>10.269<\/td>\n<td>6.526<\/td>\n<td>9.201<\/td>\n<\/tr>\n<tr>\n<td>2011<\/td>\n<td>536<\/td>\n<td>1.757<\/td>\n<td>10.802<\/td>\n<td>6.999<\/td>\n<td>9.670<\/td>\n<\/tr>\n<tr>\n<td>RotoValue<\/td>\n<td>474<\/td>\n<td>3.195<\/td>\n<td>10.349<\/td>\n<td>7.310<\/td>\n<td>9.965<\/td>\n<\/tr>\n<tr>\n<td>CAIRO<\/td>\n<td>656<\/td>\n<td>-0.358<\/td>\n<td>11.095<\/td>\n<td>7.502<\/td>\n<td>10.051<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>455 players projected by all systems<\/p>\n<table>\n<tbody>\n<tr>\n<th>Source<\/th>\n<th>Num<\/th>\n<th>Avg Price<\/th>\n<th>MAE<\/th>\n<th>RMSE<\/th>\n<\/tr>\n<tr>\n<td>2012<\/td>\n<td>455<\/td>\n<td>2.181<\/td>\n<td>0.000<\/td>\n<td>0.000<\/td>\n<\/tr>\n<tr>\n<td>Steamer<\/td>\n<td>455<\/td>\n<td>3.190<\/td>\n<td>6.646<\/td>\n<td>9.075<\/td>\n<\/tr>\n<tr>\n<td>Marcel<\/td>\n<td>455<\/td>\n<td>3.500<\/td>\n<td>7.229<\/td>\n<td>9.986<\/td>\n<\/tr>\n<tr>\n<td>RotoValue<\/td>\n<td>455<\/td>\n<td>3.409<\/td>\n<td>7.391<\/td>\n<td>10.018<\/td>\n<\/tr>\n<tr>\n<td>2011<\/td>\n<td>455<\/td>\n<td>3.261<\/td>\n<td>7.577<\/td>\n<td>10.280<\/td>\n<\/tr>\n<tr>\n<td>CAIRO<\/td>\n<td>455<\/td>\n<td>1.518<\/td>\n<td>7.879<\/td>\n<td>10.647<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>Again projecting more total players gives a lower overall error, so comparing among players projected by all systems gives a better look. This pattern exists in all formats.<br \/>\nNow a <a href=\"http:\/\/www.rotovalue.com\/cgi-bin\/Search?year=2012&amp;league=17&amp;source=RotoValue\">5&#215;5 AL<\/a> league:<\/p>\n<table>\n<tbody>\n<tr>\n<th>Source<\/th>\n<th>Num<\/th>\n<th>Price<\/th>\n<th>StdDev<\/th>\n<th>MAE<\/th>\n<th>RMSE<\/th>\n<\/tr>\n<tr>\n<td>2012<\/td>\n<td>622<\/td>\n<td>0.437<\/td>\n<td>10.205<\/td>\n<td>0.000<\/td>\n<td>0.000<\/td>\n<\/tr>\n<tr>\n<td>Steamer<\/td>\n<td>576<\/td>\n<td>0.702<\/td>\n<td>10.559<\/td>\n<td>5.729<\/td>\n<td>7.727<\/td>\n<\/tr>\n<tr>\n<td>Marcel<\/td>\n<td>507<\/td>\n<td>2.623<\/td>\n<td>10.051<\/td>\n<td>6.308<\/td>\n<td>8.600<\/td>\n<\/tr>\n<tr>\n<td>RotoValue<\/td>\n<td>406<\/td>\n<td>4.805<\/td>\n<td>9.698<\/td>\n<td>7.025<\/td>\n<td>9.045<\/td>\n<\/tr>\n<tr>\n<td>2011<\/td>\n<td>484<\/td>\n<td>3.107<\/td>\n<td>10.117<\/td>\n<td>6.715<\/td>\n<td>9.049<\/td>\n<\/tr>\n<tr>\n<td>CAIRO<\/td>\n<td>584<\/td>\n<td>1.172<\/td>\n<td>10.264<\/td>\n<td>7.119<\/td>\n<td>9.483<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>382 players projected by all systems<\/p>\n<table>\n<tbody>\n<tr>\n<th>Source<\/th>\n<th>Num<\/th>\n<th>Avg Price<\/th>\n<th>MAE<\/th>\n<th>RMSE<\/th>\n<\/tr>\n<tr>\n<td>2012<\/td>\n<td>382<\/td>\n<td>3.757<\/td>\n<td>0.000<\/td>\n<td>0.000<\/td>\n<\/tr>\n<tr>\n<td>Steamer<\/td>\n<td>382<\/td>\n<td>4.639<\/td>\n<td>6.088<\/td>\n<td>8.048<\/td>\n<\/tr>\n<tr>\n<td>Marcel<\/td>\n<td>382<\/td>\n<td>5.130<\/td>\n<td>6.956<\/td>\n<td>9.016<\/td>\n<\/tr>\n<tr>\n<td>RotoValue<\/td>\n<td>382<\/td>\n<td>5.310<\/td>\n<td>7.137<\/td>\n<td>9.189<\/td>\n<\/tr>\n<tr>\n<td>2011<\/td>\n<td>382<\/td>\n<td>5.067<\/td>\n<td>7.240<\/td>\n<td>9.353<\/td>\n<\/tr>\n<tr>\n<td>CAIRO<\/td>\n<td>382<\/td>\n<td>3.266<\/td>\n<td>7.646<\/td>\n<td>9.969<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>And a <a href=\"http:\/\/www.rotovalue.com\/cgi-bin\/Search?year=2012&amp;league=17&amp;source=RotoValue\">5&#215;5 NL<\/a> League:<\/p>\n<table>\n<tbody>\n<tr>\n<th>Source<\/th>\n<th>Num<\/th>\n<th>Price<\/th>\n<th>StdDev<\/th>\n<th>MAE<\/th>\n<th>RMSE<\/th>\n<\/tr>\n<tr>\n<td>2012<\/td>\n<td>707<\/td>\n<td>-1.122<\/td>\n<td>10.404<\/td>\n<td>0.000<\/td>\n<td>0.000<\/td>\n<\/tr>\n<tr>\n<td>Steamer<\/td>\n<td>646<\/td>\n<td>-0.348<\/td>\n<td>10.460<\/td>\n<td>5.678<\/td>\n<td>7.901<\/td>\n<\/tr>\n<tr>\n<td>Marcel<\/td>\n<td>575<\/td>\n<td>1.283<\/td>\n<td>10.255<\/td>\n<td>6.375<\/td>\n<td>8.804<\/td>\n<\/tr>\n<tr>\n<td>2011<\/td>\n<td>536<\/td>\n<td>1.496<\/td>\n<td>10.845<\/td>\n<td>6.683<\/td>\n<td>9.237<\/td>\n<\/tr>\n<tr>\n<td>RotoValue<\/td>\n<td>474<\/td>\n<td>3.031<\/td>\n<td>10.338<\/td>\n<td>7.106<\/td>\n<td>9.580<\/td>\n<\/tr>\n<tr>\n<td>CAIRO<\/td>\n<td>656<\/td>\n<td>-0.983<\/td>\n<td>11.412<\/td>\n<td>7.860<\/td>\n<td>10.419<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>455 players projected by all systems<\/p>\n<table>\n<tbody>\n<tr>\n<th>Source<\/th>\n<th>Num<\/th>\n<th>Avg Price<\/th>\n<th>MAE<\/th>\n<th>RMSE<\/th>\n<\/tr>\n<tr>\n<td>2012<\/td>\n<td>455<\/td>\n<td>1.981<\/td>\n<td>0.000<\/td>\n<td>0.000<\/td>\n<\/tr>\n<tr>\n<td>Steamer<\/td>\n<td>455<\/td>\n<td>2.979<\/td>\n<td>6.261<\/td>\n<td>8.516<\/td>\n<\/tr>\n<tr>\n<td>Marcel<\/td>\n<td>455<\/td>\n<td>3.362<\/td>\n<td>7.042<\/td>\n<td>9.517<\/td>\n<\/tr>\n<tr>\n<td>RotoValue<\/td>\n<td>455<\/td>\n<td>3.259<\/td>\n<td>7.192<\/td>\n<td>9.659<\/td>\n<\/tr>\n<tr>\n<td>2011<\/td>\n<td>455<\/td>\n<td>3.076<\/td>\n<td>7.197<\/td>\n<td>9.798<\/td>\n<\/tr>\n<tr>\n<td>CAIRO<\/td>\n<td>455<\/td>\n<td>0.473<\/td>\n<td>8.102<\/td>\n<td>10.844<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>And finally, a <a href=\"http:\/\/www.rotovalue.com\/cgi-bin\/Search?year=2012&amp;league=17&amp;source=RotoValue\">5&#215;5 mixed<\/a> league:<\/p>\n<table>\n<tbody>\n<tr>\n<th>Source<\/th>\n<th>Num<\/th>\n<th>Price<\/th>\n<th>StdDev<\/th>\n<th>MAE<\/th>\n<th>RMSE<\/th>\n<\/tr>\n<tr>\n<td>2012<\/td>\n<td>1309<\/td>\n<td>-12.014<\/td>\n<td>13.278<\/td>\n<td>0.000<\/td>\n<td>0.000<\/td>\n<\/tr>\n<tr>\n<td>Steamer<\/td>\n<td>1202<\/td>\n<td>-12.939<\/td>\n<td>14.912<\/td>\n<td>8.066<\/td>\n<td>10.796<\/td>\n<\/tr>\n<tr>\n<td>Marcel<\/td>\n<td>1064<\/td>\n<td>-7.637<\/td>\n<td>12.006<\/td>\n<td>8.514<\/td>\n<td>11.230<\/td>\n<\/tr>\n<tr>\n<td>2011<\/td>\n<td>1004<\/td>\n<td>-6.590<\/td>\n<td>11.818<\/td>\n<td>8.977<\/td>\n<td>11.692<\/td>\n<\/tr>\n<tr>\n<td>RotoValue<\/td>\n<td>863<\/td>\n<td>-7.053<\/td>\n<td>13.294<\/td>\n<td>9.096<\/td>\n<td>12.184<\/td>\n<\/tr>\n<tr>\n<td>CAIRO<\/td>\n<td>1220<\/td>\n<td>-9.482<\/td>\n<td>12.374<\/td>\n<td>9.198<\/td>\n<td>12.322<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>822 players projected by all systems<\/p>\n<table>\n<tbody>\n<tr>\n<th>Source<\/th>\n<th>Num<\/th>\n<th>Avg Price<\/th>\n<th>MAE<\/th>\n<th>RMSE<\/th>\n<\/tr>\n<tr>\n<td>2012<\/td>\n<td>822<\/td>\n<td>-8.014<\/td>\n<td>0.000<\/td>\n<td>0.000<\/td>\n<\/tr>\n<tr>\n<td>Steamer<\/td>\n<td>822<\/td>\n<td>-7.907<\/td>\n<td>8.442<\/td>\n<td>11.275<\/td>\n<\/tr>\n<tr>\n<td>Marcel<\/td>\n<td>822<\/td>\n<td>-5.020<\/td>\n<td>9.331<\/td>\n<td>11.998<\/td>\n<\/tr>\n<tr>\n<td>2011<\/td>\n<td>822<\/td>\n<td>-4.644<\/td>\n<td>9.565<\/td>\n<td>12.238<\/td>\n<\/tr>\n<tr>\n<td>CAIRO<\/td>\n<td>822<\/td>\n<td>-7.541<\/td>\n<td>9.283<\/td>\n<td>12.284<\/td>\n<\/tr>\n<tr>\n<td>RotoValue<\/td>\n<td>822<\/td>\n<td>-6.630<\/td>\n<td>9.244<\/td>\n<td>12.327<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>When looking at those players projected by all systems, Steamer had the lowest RMSE and MAE in every format, while CAIRO was the highest in each format except the 5&#215;5 MLB. One difference with that format is that it&#8217;s a much shallower league, as it uses <del>270\u00a0<\/del>230\u00a0players total out of both leagues, whereas the NL leagues use <del>270\u00a0<\/del>230 NL only, and the AL uses <del>280\u00a0<\/del>240\u00a0total (one extra DH per fantasy team). So the replacement level for the MLB league is much higher, and that affects pricing (explaining why the average price becomes negative in that format).<br \/>\nCAIRO did much better in projecting rate stats than it did in projecting RotoValue prices, while my old RotoValue model, which was quite poor in projecting rate stats, usually had lower errors than CAIRO in this format. I suspect this may be due in large part to playing time projections. One tweak I did with my model was to adjust players&#8217; projected stats relative to known, preseason injuries. So Ryan Howard, who wasn&#8217;t expected back until at least mid May last year, was only projected for 363 AB in my system, compared to 516 for Marcel and 575 for CAIRO. So the RotoValue prices for him in those projection systems were much higher than mine, and thus even if on average RotoValue&#8217;s percentages were worse than other systems, it made up for some (or even all) of that gap by being closer on playing time. Steamer also had Howard projected for just 394 AB, and thus was less hurt by his poor year (just 260 AB, but also only a .301 wOBA for the time he played). Another Phillie with a preseason injury, Chase Utley, followed a similar pattern: CAIRO projected 381 AB, Marcel 412, and Steamer 494, but RotoValue only had him pegged for 275. CAIRO also was hurt by having the most optimistic projections for stars who disappointed, like Roy Halladay, Mariano Rivera and Chris Carpenter, while its projection for Buster Posey, who rebounded spectacularly from a season-ending injury in 2011, was the least optimistic.<br \/>\nI should add plenty of caveats about drawing overly strong conclusions from limited data. While I did compare prices five different scoring systems, it was only based on 2012 projection data. Steamer performed better than than the other systems in all formats, and Marcel was usually the second best. But the gap in error rates between Marcel and other systems was much smaller than that between it and Steamer. My old projection model looks better in this sort of comparison than in earlier comparisons, which suggests that the playing time adjustments I do added value. So I&#8217;ll be curious to see how my modified model performs in 2013.<br \/>\n<em><strong>Update 2\/8\/2013:<\/strong>\u00a0<\/em>I&#8217;ve rerun the tables after double-checking the league parameters that I was using. My intention was to use a $0 minimum bid and no bench players, because that removes a potential discontinuity in prices that would occur in the pricing model (it assumes all projected \u00a0bench players are worth only the minimum price, and it does not allow prices between 0 and the minimum bid). The particular error numbers and price values are different, but the overall comparisons and orderings are essentially the same.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>I&#8217;ve previously compared five MLB projection systems for batting\u00a0and pitching\u00a0rate statistics, comparing the projections for 2012 with actual data. This post will compare 4 systems by looking at the RotoValue prices for a given projection stat set and league setup compared with actual 2012 data for the same setup. The four systems I&#8217;m testing will&hellip; <a class=\"more-link\" href=\"https:\/\/blog.rotovalue.com\/index.php\/2013\/02\/07\/comparing-projected-rotovalue-prices\/\">Continue reading <span class=\"screen-reader-text\">Comparing Projected 2012 RotoValue Prices<\/span><\/a><\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[6,11,13],"tags":[],"_links":{"self":[{"href":"https:\/\/blog.rotovalue.com\/index.php\/wp-json\/wp\/v2\/posts\/520"}],"collection":[{"href":"https:\/\/blog.rotovalue.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.rotovalue.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.rotovalue.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.rotovalue.com\/index.php\/wp-json\/wp\/v2\/comments?post=520"}],"version-history":[{"count":0,"href":"https:\/\/blog.rotovalue.com\/index.php\/wp-json\/wp\/v2\/posts\/520\/revisions"}],"wp:attachment":[{"href":"https:\/\/blog.rotovalue.com\/index.php\/wp-json\/wp\/v2\/media?parent=520"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.rotovalue.com\/index.php\/wp-json\/wp\/v2\/categories?post=520"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.rotovalue.com\/index.php\/wp-json\/wp\/v2\/tags?post=520"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}