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		<title>Refining WARP and OFP Pricing</title>
		<link>http://milwaukee.locals.baseballprospectus.com/2017/10/14/refining-warp-and-ofp-pricing/</link>
		<comments>http://milwaukee.locals.baseballprospectus.com/2017/10/14/refining-warp-and-ofp-pricing/#comments</comments>
		<pubDate>Sat, 14 Oct 2017 15:31:54 +0000</pubDate>
		<dc:creator><![CDATA[Nicholas Zettel]]></dc:creator>
				<category><![CDATA[Articles]]></category>
		<category><![CDATA[2013 Baseball Prospectus top prospects]]></category>
		<category><![CDATA[2013 Brewers top prospects]]></category>
		<category><![CDATA[2013 Orioles top prospects]]></category>
		<category><![CDATA[2017 Brewers]]></category>
		<category><![CDATA[2017 Brewers analysis]]></category>
		<category><![CDATA[MLB prospect analysis]]></category>
		<category><![CDATA[MLB trade analysis]]></category>

		<guid isPermaLink="false">http://milwaukee.locals.baseballprospectus.com/?p=10321</guid>
		<description><![CDATA[Throughout the Brewers rebuilding effort, a difficult question occupied my mind: how does one assess a successful rebuild while it is occurring? There is obviously plenty of room for post hoc analysis, and perhaps room to create expectations about a rebuild (for example, one could say, &#8220;the Brewers rebuild is successful if they win 450 [&#8230;]]]></description>
				<content:encoded><![CDATA[<p>Throughout the Brewers rebuilding effort, a difficult question occupied my mind: how does one assess a successful rebuild while it is occurring? There is obviously plenty of room for post hoc analysis, and perhaps room to create expectations about a rebuild (for example, one could say, &#8220;the Brewers rebuild is successful if they win 450 games between 2018 and 2022,&#8221; or &#8220;the Brewers rebuild is successful if they reach the playoffs once,&#8221; etc.). What is much more difficult, and more abstract, is to keep a tally on the development of talent over time, and the value of accumulating talent (as well as the effectiveness in cashing that talent into MLB wins either through trade or successful development). There are countless methodological issues with pricing this type of concern, and attempting to answer the question, not the least of which include the following biases (biases which need not even be consistent, but pull in several different directions):</p>
<ul>
<li>MLB production by known assets will frequently be valued more so than unknown production by future assets (even where numerous scouting accounts and talent assessments are available).</li>
</ul>
<ul>
<li>Trades involving MLB players and prospects will be difficult to assess because immediate production at the MLB level requires a different scale for assessment than numerous contract reserve years for a prospect.</li>
</ul>
<ul>
<li>The existence of six-to-seven years of contract reserve rights for prospects will tempt analysts to value length of control over quality of production (ex., the Brewers traded Martin Maldonado, a superior player, for Jett Bandy, a player with a potentially similar profile but more risk as well as more &#8220;control years&#8221;).</li>
</ul>
<ul>
<li>Analysts, fanbases, and probably even teams will be biased in favor of the value of the players that they currently reserve within their system and undervalue the players that are outside of their system.</li>
</ul>
<p>Throughout the 2016 season and 2016-2017 offseason, I worked on a Benefit-Cost Analysis style pricing system that sought to place MLB Wins Above Replacement Player (WARP), prospect/role Overall Future Potential (OFP), and cash ($$$) on an interactive scale. The culmination in this system was my &#8220;<a href="http://milwaukee.locals.baseballprospectus.com/2017/01/05/translating-ofp/">Translating OFP</a>&#8221; article, which hypothesized that the potential value of a prospect could be calculated by categorizing historical baseball performances. By taking the broadest picture possible (indeed, calculating the WAR/WARP surplus for 18,000 batters and pitchers), I ascribed monetary value to specific prospect classes. Since these classes are interactive, they can effectively be used to test various assumptions (for example, if one wishes to calculate a player&#8217;s full range of 40 OFP-floor-to-60-OFP-ceiling, like the case of Lucas Erceg, one can average that full range of values; or, one can simply focus on highest possible ceiling, likely middle ground, etc., for prospects).</p>
<p>The point is not that there is one way to assess prospects, nor that player value is solely transactional. Instead, the point is that since MLB teams do in fact engage in rebuilding or win-now strategies at varying points in their franchise tenures, and do in fact trade minor league players for MLB players (and vice versa), these player types are indeed interactive even where their value is placed on entirely different scales. Taking inspiration from Benefit-Cost Analysis is important, then, as one can understand that the economic value of logging can indeed be assessed against the value of endangered species that reside within a particular logging habitat, or that the cost of a highway can be assessed in terms of fiscal impact, shipping improvements, commute time improvements, safety for drivers (expressed reducing preventable deaths), etc. Once again, these types of metrics are not absolute, which is why reasonable Benefit-Cost Analysis procedures include post hoc assessments to review assumptions and actual asset performance (compared to expectations). The same can be done for MLB players and minor league prospects insofar as front offices do indeed transact for such players.</p>
<p><em><strong>Series &amp; Revisions:</strong></em><br />
<a href="http://milwaukee.locals.baseballprospectus.com/2017/01/05/translating-ofp/">Translating OFP</a><br />
<a href="http://milwaukee.locals.baseballprospectus.com/2017/01/12/ofp-and-minor-league-pay/">OFP and Minor League Pay</a><br />
<a href="http://milwaukee.locals.baseballprospectus.com/2017/03/21/revisiting-the-sabathia-trade/">Revisiting the CC Sabathia Trade</a><br />
<a href="http://milwaukee.locals.baseballprospectus.com/2017/06/08/update-cashing-out-ofp-2/">Cashing Out OFP 2</a><br />
<a href="http://milwaukee.locals.baseballprospectus.com/2017/07/11/organizational-logic-and-playoff-trades/">Organizational Logic and Playoff Trades</a><br />
<a href="http://milwaukee.locals.baseballprospectus.com/2017/07/21/historical-warp-and-ofp/">Historical WARP and OFP</a></p>
<p>In a forthcoming post, I will present an update on the 2013 Baseball Prospectus Organizational Top 10 lists, which I began tracking this season in the hopes of designing a realistic time series assessment of prospect value. The ideal in developing this approach is to answer the question, &#8220;How do prospect classes progress over time?&#8221; A related question can then be answered: &#8220;How do prospects of a particular OFP perform over time?&#8221; By the time 2017 started, clear delineations between 50 OFP (average), 60 OFP (first division), and 70 OFP (superstar!) prospects were already forming at the MLB level from the 2013 Organizational Top 10 class. These classifications further solidified during the 2017 season, and the benefit is that there are now five full seasons from the publication of this list through which player value can be assessed.</p>
<p>From the 2013 prospect class, I constructed the following table comparing each prospect category to the average MLB performance from that class, and used those figures to determine a monetary &#8220;price&#8221; for those prospects and MLB production. The difference between each OFP category and the average production from the full prospect class can create a WARP figure that can then be &#8220;monetized,&#8221; thereby translating OFP into a WARP category. &#8220;Risk&#8221; (based on each OFP category&#8217;s frequency of reaching the MLB) can also adjust these WARP and monetary figures. In this case, however, OFP production value is concrete instead of speculative; this is what certain OFP classes <em>actually </em>did at the MLB level (the same goes for these risk classifications, which are also &#8220;actual&#8221;):</p>
<table border="" width="" cellspacing="0" cellpadding="0">
<tbody>
<tr bgcolor="#EDF1F3">
<th align="center">2013 Prospect Org Top 10</th>
<th align="center">MLB</th>
<th align="center">AvgWARP</th>
<th align="center">AvgValue</th>
<th align="center">70Context</th>
<th align="center">70Value</th>
<th align="center">60Context</th>
<th align="center">60Value</th>
<th align="center">50Context</th>
<th align="center">50Value</th>
</tr>
<tr>
<td align="center">2011</td>
<td align="center">3</td>
<td align="center">0.2</td>
<td align="center">$1.2</td>
<td align="center">-0.1</td>
<td align="center">$0.7</td>
<td align="center">0.2</td>
<td align="center">$2.8</td>
<td align="center">-0.2</td>
<td align="center">$0.0</td>
</tr>
<tr>
<td align="center">2012</td>
<td align="center">35</td>
<td align="center">0.0</td>
<td align="center">$0.3</td>
<td align="center">-0.1</td>
<td align="center">-$0.7</td>
<td align="center">0.1</td>
<td align="center">$1.0</td>
<td align="center">0.0</td>
<td align="center">$0.1</td>
</tr>
<tr>
<td align="center">2013</td>
<td align="center">87</td>
<td align="center">0.6</td>
<td align="center">$4.3</td>
<td align="center">0.6</td>
<td align="center">$8.5</td>
<td align="center">0.1</td>
<td align="center">$5.0</td>
<td align="center">-0.2</td>
<td align="center">$2.9</td>
</tr>
<tr>
<td align="center">2014</td>
<td align="center">123</td>
<td align="center">0.8</td>
<td align="center">$5.5</td>
<td align="center">0.2</td>
<td align="center">$7.2</td>
<td align="center">0.3</td>
<td align="center">$7.7</td>
<td align="center">-0.3</td>
<td align="center">$3.5</td>
</tr>
<tr>
<td align="center">2015</td>
<td align="center">157</td>
<td align="center">1.1</td>
<td align="center">$7.4</td>
<td align="center">0.9</td>
<td align="center">$13.6</td>
<td align="center">0.0</td>
<td align="center">$7.1</td>
<td align="center">-0.2</td>
<td align="center">$6.0</td>
</tr>
<tr>
<td align="center">2016</td>
<td align="center">178</td>
<td align="center">1.3</td>
<td align="center">$8.9</td>
<td align="center">1.1</td>
<td align="center">$16.5</td>
<td align="center">-0.2</td>
<td align="center">$7.6</td>
<td align="center">-0.1</td>
<td align="center">$7.9</td>
</tr>
<tr>
<td align="center">2017</td>
<td align="center">173</td>
<td align="center">1.2</td>
<td align="center">$8.7</td>
<td align="center">0.7</td>
<td align="center">$13.3</td>
<td align="center">0.0</td>
<td align="center">$8.5</td>
<td align="center">-0.2</td>
<td align="center">$7.3</td>
</tr>
<tr>
<td align="center">Summary</td>
<td align="center">756</td>
<td align="center">0.7</td>
<td align="center">$5.2</td>
<td align="center">3.3</td>
<td align="center">$82.1</td>
<td align="center">0.5</td>
<td align="center">$43.3</td>
<td align="center">-1.2</td>
<td align="center">$19.3</td>
</tr>
<tr>
<td align="center">Risk</td>
<td align="center">77.9%</td>
<td align="center">0.6</td>
<td align="center">$4.02</td>
<td align="center">96.6%</td>
<td align="center">$45.7</td>
<td align="center">77.2%</td>
<td align="center">$25.0</td>
<td align="center">74.7%</td>
<td align="center">$18.1</td>
</tr>
</tbody>
</table>
<p>Assessing 756 MLB seasons, played from 2011-2017 (with most prospects playing between 2014-2017) by the 2013 BP Organizational Top 10, allows for a broad range of data to be analyzed. This produced time series for each player that can be analyzed, as well as annual summaries and prospect class summaries. From this table, one can compare initial historical OFP estimates with risk-oriented &#8220;bare minimum&#8221; prices and &#8220;top ceiling&#8221; prices:</p>
<table border="" width="" cellspacing="0" cellpadding="0">
<tbody>
<tr bgcolor="#EDF1F3">
<th align="center">Prospect Class</th>
<th align="center">Historical Model (Risk)</th>
<th align="center">Historical Model (Ceiling)</th>
<th align="center">2013 Prospect Model (Risk)</th>
<th align="center">2013 Prospect Model (Ceiling)</th>
</tr>
<tr>
<td align="center">50 OFP</td>
<td align="center">$7.0M (40-50)</td>
<td align="center">$19.5M</td>
<td align="center">$18.1M</td>
<td align="center">$19.3M</td>
</tr>
<tr>
<td align="center">60 OFP</td>
<td align="center">$20.8M (40-60)</td>
<td align="center">$48.9M</td>
<td align="center">$25.0M</td>
<td align="center">$43.3M</td>
</tr>
<tr>
<td align="center">70 OFP</td>
<td align="center">$45.8M (50-75)</td>
<td align="center">$100.0M</td>
<td align="center">$45.7M</td>
<td align="center">$82.1M</td>
</tr>
</tbody>
</table>
<p>The same criticisms of using WARP and OFP to assess players obviously apply: MLB players and minor league prospects are dynamic, and at different points of time their WARP or OFP may indeed mean different things; a player can add a new pitch or make a delivery adjustment and improve upon their previous performance (like Jimmy Nelson), or answer a specific set of approach and mechanics questions to achieve a higher grade (compare Josh Hader&#8217;s 2013 Top 10 appearance as a 50 OFP Orioles prospect with his 2017 Top 10 appearance as a near-surefire impact MLB player between 55-60 OFP depending on high-leverage relief or Number 3 starter risk assessments). For 2018, Brewers CF prospect Monte Harrison will be a great example of a prospect whose OFP role has evolved over time, due in part to injuries and also in part to on-field adjustments and advancements; Corey Ray will almost certainly demonstrate this fact in the opposite direction, due to mechanical question marks and growing pains.</p>
<p>So, indeed, WARP and OFP should not be viewed as fixed, or definitive metrics. They <em>should</em> be viewed as reasonable snapshots of a player&#8217;s value or potential at a given time, which MLB teams can indeed use in order to assess transaction value. A common complaint about my method is that MLB teams do not use WARP and OFP to assess players, but I find that this complaint misses the point that teams <em>do</em> boil players down to a &#8220;number&#8221; when they decide to trade, or keep, a player; their &#8220;number&#8221; might be predicated on a blend of proprietary scouting insights, years of mechanical data, and other performative metrics. That MLB teams do not use WARP and OFP to assess trades does not mean that fans and analysts should not use these metrics where other proprietary information is not available; for failing to capitalize on the interaction between Future Potential, Replacement Value, and cash means that the MLB analyst and fan missing one specific constellation with which transactions can be assessed.</p>
<hr />
<p>&nbsp;</p>
<p>Photo Credit: Steve Mitchell, USAToday Sports Images</p>
]]></content:encoded>
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		</item>
		<item>
		<title>OFP and Minor League Pay</title>
		<link>http://milwaukee.locals.baseballprospectus.com/2017/01/12/ofp-and-minor-league-pay/</link>
		<comments>http://milwaukee.locals.baseballprospectus.com/2017/01/12/ofp-and-minor-league-pay/#comments</comments>
		<pubDate>Thu, 12 Jan 2017 13:03:11 +0000</pubDate>
		<dc:creator><![CDATA[Nicholas Zettel]]></dc:creator>
				<category><![CDATA[Articles]]></category>
		<category><![CDATA[minor league pay]]></category>
		<category><![CDATA[MLB historical analysis]]></category>
		<category><![CDATA[MLB labor analysis]]></category>
		<category><![CDATA[MLB prospect analysis]]></category>

		<guid isPermaLink="false">http://milwaukee.locals.baseballprospectus.com/?p=7665</guid>
		<description><![CDATA[Throughout the offseason, I have worked on analysis techniques that place minor league players and MLB players on similar WARP-based monetized scales. This task is important because it helps to iron out some of the necessary wrinkles in assessing trades that involve minor league returns for MLB players, and it also helps to quantify the [&#8230;]]]></description>
				<content:encoded><![CDATA[<p>Throughout the offseason, I have worked on analysis techniques that place minor league players and MLB players on similar WARP-based monetized scales. This task is important because it helps to iron out some of the necessary wrinkles in assessing trades that involve minor league returns for MLB players, and it also helps to quantify the value of each organization&#8217;s assets (so that one might be able to compare the total value of a rebuilding club with the total value of a contending club on the same scales, in order to analyze efficiency). </p>
<p><em><strong>Related Reading</strong></em>: <a href="http://milwaukee.locals.baseballprospectus.com/2017/01/05/translating-ofp/">Historical OFP</a> [Includes historical OFP tables]</p>
<p>One added benefit of monetizing minor league Overall Future Potential value is that minor league players can use their OFP to justify significantly larger paychecks from their parent organizations. While fans might expect that minor league players deserve smaller pay checks because of their risk level <em>and</em> because they can &#8220;recoup&#8221; value once they reach the MLB, those arguments undersell the professional status of minor league players <em>and</em> overlook the reality of suppressed pay at the MLB level. Take Clayton Kershaw, who sat <a href="http://www.baseballprospectus.com/article.php?articleid=5734">atop the Dodgers system in 2007</a> as a potential &#8220;true Number 1 starter&#8221; (so, an 80 OFP). Based on the historical value of 80 OFP players, Kershaw could be reasonably expected to produce at least $587 million in production value, and an average of $845 million in production value; his 80 OFP prospect grade gave the Dodgers organization a whopping $169.1 million in surplus value (ex., Kershaw was so valuable as a prospect that the club would not reasonably trade him for anyone, since the return would be absurd). </p>
<p>Yet, Kershaw himself has served as a criminally underpaid MLB player. The southpaw has produced $389.2 million in production value, amply returning that OFP surplus and then some. First, the Dodgers paid a measly $2.3 million draft bonus to Kershaw, who was the seventh overall pick of the 2006 draft. Minor league contracts are not typically publicized, but it is probably a safe estimate that Kershaw did not earn anywhere near even the MLB league minimum (now $0.5M) as a minor leaguer. Kershaw certainly was not compensated for his organizational surplus value. Prior to signing his $215 million contract extension in 2014, Kershaw earned just over $20 million for a 33.1 performance (worth $211.7 million in savings for the Dodgers). This is a perfect way to look at the seven year extension: Kershaw has been so criminally underpaid that the Dodgers merely offered him their organizational savings from his production value in lieu of his contract extension. </p>
<p>The Dodgers could <em>cut</em> Kershaw tomorrow, paying out the full value of his contract, and still emerge $157.2 million ahead. That&#8217;s 22 WARP, if one values WARP at the common free market assumption of $7 million per win above replacement. </p>
<table width="" border="" cellpadding="0" cellspacing="0">
<tr bgcolor="#EDF1F3">
<th align="center">OFP</th>
<th align="center">Value</th>
<th align="center">Percentile</th>
<th align="center">Depreciated Value</th>
</tr>
<tr>
<td align="center">40 OFP</td>
<td align="center">$0.5M</td>
<td align="center">7th to 8th</td>
<td align="center">$0.1M</td>
</tr>
<tr>
<td align="center">45 OFP</td>
<td align="center">$7.0M</td>
<td align="center">66th</td>
<td align="center">$1.4M</td>
</tr>
<tr>
<td align="center">50 OFP</td>
<td align="center">$97.3M</td>
<td align="center">88th to 91st</td>
<td align="center">$19.5M</td>
</tr>
<tr>
<td align="center">55 OFP</td>
<td align="center">$170.8M</td>
<td align="center">Approx. 94th</td>
<td align="center">$34.2M</td>
</tr>
<tr>
<td align="center">60 OFP</td>
<td align="center">$244.3M</td>
<td align="center">97th to 98th</td>
<td align="center">$48.9M</td>
</tr>
<tr>
<td align="center">65 OFP</td>
<td align="center">$359.8M</td>
<td align="center">99th</td>
<td align="center">$72.0M</td>
</tr>
<tr>
<td align="center">70-75 OFP</td>
<td align="center">$499.8M</td>
<td align="center"></td>
<td align="center">$100.0M</td>
</tr>
<tr>
<td align="center">80 OFP</td>
<td align="center">$845.6M</td>
<td align="center"></td>
<td align="center">$169.1M</td>
</tr>
</table>
<p>One need not use elite players to make this point, however. Scooter Gennett, my recent favorite 50 OFP prospect, is a perfect example of the MLB&#8217;s terrible compensation system: selected in the 16th round of the 2009 draft, the Brewers paid Gennett a $260,000 bonus, and the prospect earned a <a href="http://www.baseballprospectus.com/article.php?articleid=19393">top OFP of 50 as late as 2013</a>. Once again, one must speculate that Gennett did not earn anywhere near league minimum salary in the minors, and the 4.0 WARP player has thus far been underpaid by as much as $26 million in his career despite returning strong historical value on that 50 OFP (Gennett resides within the 91st percentile of every single MLB player in history in terms of his replacement value). </p>
<p>The Brewers have criminally underpaid Gennett, which makes a much better point than Kershaw: it is easy to dream of Kershaw as underpaid because it is easy to dream about a team paying him $400 million on the free market (which is much closer to his actual value than $215 million). Gennett&#8217;s underpaid status is more difficult to discern, since it is difficult to imagine the all-hit second baseman earning $28 million over the last four years. Even if one considers that a team would not maximize a player&#8217;s total surplus via contract (so that they might sign a contract and retain some trade value), halving that figure to $14 million still readily makes the point that Gennett is criminally underpaid. </p>
<table width="" border="" cellpadding="0" cellspacing="0">
<tr bgcolor="#EDF1F3">
<th align="center">OFP for MiLB Pay</th>
<th align="center">Historical Production</th>
<th align="center">Historical OFP Price</th>
<th align="center">Minor League Salary</th>
</tr>
<tr>
<td align="center">40</td>
<td align="center">$0.5M</td>
<td align="center">$0.1M</td>
<td align="center">$0.020M minor league minimum</td>
</tr>
<tr>
<td align="center">45</td>
<td align="center">$7.0M</td>
<td align="center">$1.4M</td>
<td align="center">$0.140M base</td>
</tr>
<tr>
<td align="center">50</td>
<td align="center">$97.3M</td>
<td align="center">$19.5M</td>
<td align="center">$0.195M base</td>
</tr>
<tr>
<td align="center">55</td>
<td align="center">$170.8M</td>
<td align="center">$34.2M</td>
<td align="center">$0.342M base</td>
</tr>
<tr>
<td align="center">60</td>
<td align="center">$244.3M</td>
<td align="center">$48.9M</td>
<td align="center">$0.489M base</td>
</tr>
<tr>
<td align="center">65</td>
<td align="center">$359.8M</td>
<td align="center">$72.0M</td>
<td align="center">$0.720M base</td>
</tr>
<tr>
<td align="center">70-75</td>
<td align="center">$499.8M</td>
<td align="center">$100.0M</td>
<td align="center">$1.000M base</td>
</tr>
<tr>
<td align="center">80</td>
<td align="center">$845.6M</td>
<td align="center">$169.1M</td>
<td align="center">$1.691M base</td>
</tr>
</table>
<p>Enter OFP as a bargaining chip for minor league players: if a player&#8217;s OFP suggests that his historical worth is a certain monetary amount, that amount must also be diminished due to the risk of developing minor league players. In my previous analysis of historical OFP, I crudely sliced historical OFP values by 80 percent to reflect the basic fact that approximately 20 percent of minor leaguers might make the MLB. This produces a chart of values that works quite well in assessing transactional values in trades (for example, Khris Davis&#8217;s depreciated value was approximately $35 million surplus prior to his trade, and Jacob Nottingham and Bubba Derby (55 OFP and 45 OFP, respectively) combined to a historical value of $35.6 million &#8212; not bad, David Stearns!).</p>
<p>If a player offers that type of transactional value to their parent organization; that is, if a player like Jacob Nottingham or Bubba Derby can be used to net a player like Khris Davis in trade, those prospects should be paid according to their OFP value. Using a basic sliding scale percentage commission, this would return a 55 OFP prospect like Nottingham $342,000 in minor league salary, and Derby $140,000 in minor league salary. One could protest that paying a player like Derby $140,000 in minor league salary over the course of a few seasons would quickly deplete that $1.4 million OFP surplus value. I&#8217;d counter that risk slices both ways: why should minor league players bear the bulk of professional development risk through their below-living-wage salaries? </p>
<p>[Again, if this sounds ridiculous, look at it this way: Nottingham is among the very best catching prospects in a <a href="http://www.forbes.com/sites/maurybrown/2016/12/05/mlb-sees-record-revenues-approaching-10-billion-for-2016/#1ced61cd1845">near-$10 billion industry</a>. His skillset is such that he can potentially start at catcher and offer an above average power grade, both of which are strong professional feats. The idea of Nottingham earning, say, $1.5 million in salary over five minor league seasons prior to entering the majors should not be absurd, given the revenue scope of the game and the young prospect&#8217;s advanced status and OFP.]</p>
<p>The risk of professional development ought to be spread much more evenly, since it is risky for both minor league players and organizations to embark on professional baseball development; this, of course, has the added difficulty of forcing MLB teams to admit that minor league players <em>are</em> <strong>professionals</strong> (and they are professionals. Minor league baseball players <em>are</em> professional baseball players!).</p>
<p>There are several hidden issues here:<br />
(1) There is no labor system in place for delivering such salaries to minor league players.<br />
(2) There is a certain point where certain league minimum MLB players could indeed earn less than the very best prospects. </p>
<p>Regarding (1), first and foremost the MLBPA must step up and represent minor league ballplayers as a part of the baseball profession. The problematic salaries minor leaguers are paid are not solely the fault of greedy owners &#8212; they are also the fault of a certain class of players that <a href="http://milwaukee.locals.baseballprospectus.com/2016/07/18/mlbpa-elitism-and-minor-league-pay/">are unduly profiting from a professional schism</a>. Once the MLBPA represents all players in affiliated ball, quite an easy mechanism can be put in place to adjust salaries: annual arbitration or salary schedules for minor league and MLB players alike. Regarding (2), some replacement MLB players are not worth a prorated portion of a league minimum salary, 45 grade prospects (that might become replacement players) <em>are</em> worth $140,000. </p>
<p>A more crude system, absent the MLBPA representing minor leaguers, would offer minor league players free agency after two years of organizational development: if you protest, just remember that MLB teams used the argument that players are simply &#8220;seasonal apprentices,&#8221; so setting those apprentices free every other year should allow them to vastly increase their earnings by creating a free market for MILB talent among teams. If one is inclined to argue that a team should not have to lose a development asset after two years of minor league play, that should provide significant incentive for improving pay by allowing that player the option to work with the organization that will pay them the best (or perhaps, provide the best pay and development strategy combination). What do you think the Cubs would have paid to keep seasonal apprentice Kris Bryant after the 2014 minor league season, for example? Analysts should not shy away from supporting this method: the fact that, say, Trent Clark or Demi Orimoloye are far removed from the MLB and do not yet have clear roles does not mean that the Brewers do not have their value precisely priced; they are two of the 2015 draft prospects that would have immensely benefited from free agency after 2016. </p>
<p>Given the existence of industry sources such as BaseballAmerica and BaseballProspectus that evaluate prospects, there is certainly an independent scouting infrastructure available that could operate an arbitration system to compensate prospects based on their OFP. Such a system could also have the benefit of establishing a much higher salary floor for minor league players; even if a $20,000 salary more accurately reflects the value of an organizational depth player, that salary is not necessarily life changing but will offer more financial support than current minor league salaries (and would be slightly more in line with entry level professional salaries for other fields). </p>
<p>It is deeply problematic that such rich analytic tools exist in the field of baseball, and yet player compensation lags so far behind its justifiable salary levels. Of course, there is a certain extent to which <a href="http://milwaukee.locals.baseballprospectus.com/2016/04/26/the-new-professional-orthodoxy/">analytical tools are meant specifically to drive down player costs</a> and return revenue to owners. Given the ease of implementing improved compensation &#8212; again, there is already quite a strong administrative system in place for arbitration, and there is are representative bodies such as the MLBPA that can assist with matters of compensation &#8212; the real issue is political feasibility due to the lack of willpower from MLB ownership and MLBPA. This lack of willpower leaves members of the analytic community to place more pressure on that infrastructure to begin justly compensating baseball players. </p>
<p>Prospects need not only have OFP grades for show: if MLB clubs can trade players for MLB value based on a player&#8217;s OFP, they can also justly compensate that prospect by paying them a commission based on their ceiling. OFP need not merely be transactional, or rather, the extent to which OFP is transactional should be expanded to include compensation. </p>
]]></content:encoded>
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		<title>Translating OFP</title>
		<link>http://milwaukee.locals.baseballprospectus.com/2017/01/05/translating-ofp/</link>
		<comments>http://milwaukee.locals.baseballprospectus.com/2017/01/05/translating-ofp/#comments</comments>
		<pubDate>Thu, 05 Jan 2017 16:31:45 +0000</pubDate>
		<dc:creator><![CDATA[Nicholas Zettel]]></dc:creator>
				<category><![CDATA[Articles]]></category>
		<category><![CDATA[Brewers top prospects]]></category>
		<category><![CDATA[Brewers trade analysis]]></category>
		<category><![CDATA[MLB history]]></category>
		<category><![CDATA[MLB prospect analysis]]></category>
		<category><![CDATA[MLB trade value]]></category>
		<category><![CDATA[MLB value]]></category>
		<category><![CDATA[prospect analysis]]></category>
		<category><![CDATA[prospect trade value]]></category>

		<guid isPermaLink="false">http://milwaukee.locals.baseballprospectus.com/?p=7620</guid>
		<description><![CDATA[After seeing the scouting strengths and weaknesses, as well as the Overall Future Potential (OFP) and realistic floors, for the Brewers system, one can begin the New Year with a great sense of the &#8220;what if&#8230;?&#8221; that is the current state of the rebuilt farm system. There is no question that the Brewers front office [&#8230;]]]></description>
				<content:encoded><![CDATA[<p>After seeing the scouting strengths and weaknesses, as well as the Overall Future Potential (OFP) and realistic floors, for the Brewers system, one can begin the New Year with a great sense of the &#8220;what if&#8230;?&#8221; that is the current state of the rebuilt farm system. There is no question that the Brewers front office has assembled, and now will try to develop, quite a deep array of talent. Yet, there is a serious question about how this talent will translate into the MLB: what is the likelihood of Brewers prospects reaching their ceilings? How many will surpass their respective ceilings? Are the floors good enough to built a contending team (or trade for players who can contend)? </p>
<p>In framing expectations, it is worth investigating the strengths and weaknesses of MLB players as summarized in their overall replacement value. For this exercise, I will use Baseball Reference Wins Above Replacement (WAR) instead of BaseballProspectus WARP, since I used the Play Index to construct sets of 18,848 total MLB careers evident in batting and positional searches of the Play Index (this is remarkably close to the 18,918 players that have worked in MLB since 1871). The benefit of taking this longview is to assess what it actually means to accumulate wins above replacement players &#8212; that is, what it means to be a better MLB player than the readily available person that a club could simply land off of the waiver wires or recall from the minor leagues. Using &#8220;replacement theory&#8221; to judge MLB players has many flaws that can be criticized at length, but in this case one of the strengths of WAR will be seen in the ability to categorize extremely large numbers of players that have played across nearly 150 seasons. </p>
<p>My goal in presenting these charts is to problematize OFP. Earlier this week, <a href="http://milwaukee.locals.baseballprospectus.com/2017/01/02/assessing-roster-moves-iv-prospect-value/">I discussed the difficulties in assessing prospect value</a> in order to judge transactions, since there are so many vantage points from which to assess prospect value. Yet, one will notice that in that assessment, there is quite a close range of value for prospects from Grades 40-45 to Grades 55-60. By clustering MLB players according to WAR, I hypothesize that one can translate OFP onto a wider landscape of value, which will allow one to truly capture the distance between different groups of prospects. This exercise is purely abstract insofar as I will link potential OFP ranks to WAR figures, rather than judging whether (or how) players from specific OFP classes surpassed, met, or failed to met their respective ceilings. </p>
<p>Starting with position players (I excluded pitchers from batting WAR conversations), expectations for assessing a 50 OFP, or potential league average player, are deflated: nearly 58 percent of MLB position players earned between -1.0 and 1.0 WAR in their respective careers, and a player that has assessed 2.0 WAR is easily better than 66 percent of all MLB position players in history. But is this what we mean when we describe a 50 OFP prospect, someone who will play for any given amount of time and assess two wins above replacement? I suspect not, and have tried this experiment:</p>
<table width="" border="" cellpadding="0" cellspacing="0">
<tr bgcolor="#EDF1F3">
<th align="center">Positional WAR</th>
<th align="center">Total Players</th>
<th align="center">Recent Example</th>
<th align="center">Past Example</th>
<th align="center">Percentage</th>
<th align="center">Percentile</th>
<th align="center">OFP? (Value)</th>
</tr>
<tr>
<td align="center">-1.1 and lower</td>
<td align="center">838</td>
<td align="center">Ronny Cedeno</td>
<td align="center">Dale Sveum</td>
<td align="center">8.29</td>
<td align="center">8th</td>
<td align="center">40 ($0.5M)</td>
</tr>
<tr>
<td align="center">-1.0 to 1.0</td>
<td align="center">5834</td>
<td align="center">Alex Presley</td>
<td align="center">Angel Echevarria</td>
<td align="center">57.70</td>
<td align="center">66th</td>
<td align="center">45 ($7.0M)</td>
</tr>
<tr>
<td align="center">1.1 to 13.9</td>
<td align="center">2198</td>
<td align="center">Yasiel Puig</td>
<td align="center">Rob Deer</td>
<td align="center">21.74</td>
<td align="center">88th</td>
<td align="center">50 ($97.3M)</td>
</tr>
<tr>
<td align="center">14.0 to 27.9</td>
<td align="center">664</td>
<td align="center">Freddie Freeman</td>
<td align="center">Jim Gantner</td>
<td align="center">6.57</td>
<td align="center">94th</td>
<td align="center">55 ($195.3M)</td>
</tr>
<tr>
<td align="center">28.0 to 41.9</td>
<td align="center">284</td>
<td align="center">Andrew McCutchen</td>
<td align="center">Curt Flood</td>
<td align="center">2.81</td>
<td align="center">97th</td>
<td align="center">60-65 ($293.3M)</td>
</tr>
<tr>
<td align="center">42.0 to 65.9</td>
<td align="center">203</td>
<td align="center">Ryan Braun</td>
<td align="center">Dick Allen</td>
<td align="center">2.01</td>
<td align="center">99th</td>
<td align="center">65-70 ($461.3M)</td>
</tr>
<tr>
<td align="center">66.0 to 79.9</td>
<td align="center">54</td>
<td align="center">Carlos Beltran</td>
<td align="center">Lou Whitaker</td>
<td align="center">0.53</td>
<td align="center"></td>
<td align="center">75-80 ($559.3M)</td>
</tr>
<tr>
<td align="center">80.0 to 93.9</td>
<td align="center">10</td>
<td align="center">Adrian Beltre</td>
<td align="center">Ken Griffey Jr.</td>
<td align="center">0.10</td>
<td align="center"></td>
<td align="center">80 ($657.3M)</td>
</tr>
<tr>
<td align="center">94 to 107.9</td>
<td align="center">11</td>
<td align="center">Albert Pujols</td>
<td align="center">Eddie Mathews</td>
<td align="center">0.11</td>
<td align="center"></td>
<td align="center">80 ($755.3M)</td>
</tr>
<tr>
<td align="center">108.0 to 121.9</td>
<td align="center">4</td>
<td align="center">Alex Rodriguez</td>
<td align="center">Rickey Henderson</td>
<td align="center">0.04</td>
<td align="center"></td>
<td align="center">80 ($853.3M)</td>
</tr>
<tr>
<td align="center">122.0 to 135.9</td>
<td align="center">6</td>
<td align="center">Stan Musial</td>
<td align="center">Tris Speaker</td>
<td align="center">0.06</td>
<td align="center"></td>
<td align="center">80 ($951.3M)</td>
</tr>
<tr>
<td align="center">136.0 to 159.9</td>
<td align="center">3</td>
<td align="center">Hank Aaron</td>
<td align="center">Willie Mays</td>
<td align="center">0.03</td>
<td align="center"></td>
<td align="center">80 ($1115.1M)</td>
</tr>
<tr>
<td align="center">160.0 and above</td>
<td align="center">2</td>
<td align="center">Barry Bonds</td>
<td align="center">Babe Ruth</td>
<td align="center">0.02</td>
<td align="center"></td>
<td align="center">80 ($1120.0M+)</td>
</tr>
<tr>
<td align="center"></td>
<td align="center">10111</td>
<td align="center"></td>
<td align="center"></td>
<td align="center">100.00</td>
<td align="center"></td>
<td align="center"></td>
</tr>
</table>
<p>I ascribed 50 OFP to the 1.1 to 13.9 WAR group because this group may most effectively encompass the ideal of serving as an above average player for a short period of time (say, Scooter Gennett, my recent favorite example) or a long period of time (if a player averages 2.0 WARP for five or six seasons, that&#8217;s quite a good career, but probably someone who is generally average in any given season). I also favor using this method because it captures the fact that the 300 ranked organizational prospects, or even the 300 ranked plus 150 &#8220;just interesting&#8221; prospects, comprise between four and six percent of all minor league players to begin with; in 2016 BaseballProspectus lists, for example, the 300 top organizational prospects included approximately 100 55+ OFP prospects and only 51 60+ OFP prospects. It stands to reason that although 60+ OFP prospects are severely rare in the minor leagues (0.7 percent of all minor leaguers), those ranks would occupy more MLB rosters over an extended period of time because those players would stick as solid-to-great players while MLB teams shuffled through 40-55 OFP prospects to find roster value. So, I don&#8217;t think it&#8217;s ridiculous to suggest that &#8220;only&#8221; 12 percent of MLB players in history should be assessed as 55+ OFP in terms of translating WAR, and I <em>certainly</em> believe that 70+ OFP players should only occupy the top percentile of MLB position players. </p>
<p>Judging pitchers, the results are rather similar. You will undoubtedly notice, by the way, that pitchers and position players add to more MLB careers than total MLB players from 1871-present. This is undoubtedly due to position players that have pitched. However, attempting to remove these players is quite difficult from this survey, since more than seven percent (!!!) of all MLB pitchers have worked fewer than two games in their respective careers. Even double-checking this type of list would be a monumental task for this type of survey. So, the position players that pitched stay, for now&#8230;</p>
<table width="" border="" cellpadding="0" cellspacing="0">
<tr bgcolor="#EDF1F3">
<th align="center">Pitching WAR</th>
<th align="center">Total Players</th>
<th align="center">Recent Example</th>
<th align="center">Past Example</th>
<th align="center">Percentage</th>
<th align="center">Percentile</th>
<th align="center">OFP? (Value)</th>
</tr>
<tr>
<td align="center">-1.1 and lower</td>
<td align="center">642</td>
<td align="center">Dana Eveland</td>
<td align="center">Randy Lerch</td>
<td align="center">7.03</td>
<td align="center">7th</td>
<td align="center">40 ($0.5M)</td>
</tr>
<tr>
<td align="center">-1.0 to 1.0</td>
<td align="center">5352</td>
<td align="center">Blaine Boyer</td>
<td align="center">Seth McClung</td>
<td align="center">58.63</td>
<td align="center">66th</td>
<td align="center">45 ($7.0M)</td>
</tr>
<tr>
<td align="center">1.1 to 13.9</td>
<td align="center">2322</td>
<td align="center">Ivan Nova</td>
<td align="center">Ricky Bones</td>
<td align="center">25.44</td>
<td align="center">91st</td>
<td align="center">50-55 ($97.3M)</td>
</tr>
<tr>
<td align="center">14.0 to 27.9</td>
<td align="center">498</td>
<td align="center">Jake Arrieta</td>
<td align="center">Joaquin Andujar</td>
<td align="center">5.46</td>
<td align="center">97th</td>
<td align="center">55-60 ($195.3M)</td>
</tr>
<tr>
<td align="center">28.0 to 41.9</td>
<td align="center">159</td>
<td align="center">Johnny Cueto</td>
<td align="center">Freddie Fitzsimmons</td>
<td align="center">1.74</td>
<td align="center">98th</td>
<td align="center">60-65 ($293.3M)</td>
</tr>
<tr>
<td align="center">42.0 to 55.9</td>
<td align="center">82</td>
<td align="center">Bartolo Colon</td>
<td align="center">Vida Blue</td>
<td align="center">0.90</td>
<td align="center">99th</td>
<td align="center">65-70 ($391.3M)</td>
</tr>
<tr>
<td align="center">56.0 to 69.9</td>
<td align="center">45</td>
<td align="center">Mariano Rivera</td>
<td align="center">Luis Tiant</td>
<td align="center">0.49</td>
<td align="center"></td>
<td align="center">75-80 ($489.3M)</td>
</tr>
<tr>
<td align="center">70.0 to 83.9</td>
<td align="center">10</td>
<td align="center">Mike Mussina</td>
<td align="center">Bob Gibson</td>
<td align="center">0.11</td>
<td align="center"></td>
<td align="center">80 ($587.3M)</td>
</tr>
<tr>
<td align="center">84.0 to 99.9</td>
<td align="center">10</td>
<td align="center">Pedro Martinez</td>
<td align="center">Warren Spahn</td>
<td align="center">0.11</td>
<td align="center"></td>
<td align="center">80 ($685.3M)</td>
</tr>
<tr>
<td align="center">100.0 to 113.9</td>
<td align="center">4</td>
<td align="center">Randy Johnson</td>
<td align="center">Lefty Grove</td>
<td align="center">0.04</td>
<td align="center"></td>
<td align="center">80 ($783.3M)</td>
</tr>
<tr>
<td align="center">114.0 to 127.9</td>
<td align="center">2</td>
<td align="center">Pete Alexander</td>
<td align="center">Kid Nichols</td>
<td align="center">0.02</td>
<td align="center"></td>
<td align="center">80 ($881.3M)</td>
</tr>
<tr>
<td align="center">128.0 to 141.9</td>
<td align="center">1</td>
<td align="center">Rogers Clemens</td>
<td align="center"></td>
<td align="center">0.00</td>
<td align="center"></td>
<td align="center">80 ($979.3M)</td>
</tr>
<tr>
<td align="center">142.0 to 165.9</td>
<td align="center">1</td>
<td align="center">Walter Johnson</td>
<td align="center"></td>
<td align="center">0.00</td>
<td align="center"></td>
<td align="center">80 ($1077.3M)</td>
</tr>
<tr>
<td align="center">166.0 and above</td>
<td align="center">1</td>
<td align="center">Cy Young</td>
<td align="center"></td>
<td align="center">0.00</td>
<td align="center"></td>
<td align="center">80 ($1175.3M)</td>
</tr>
<tr>
<td align="center"></td>
<td align="center">9129</td>
<td align="center"></td>
<td align="center"></td>
<td align="center">100.00</td>
<td align="center"></td>
<td align="center"></td>
</tr>
</table>
<p>While I was constructing the pitching list, I realized that a category discrepancy emerged between 42.0 and 65.9 WAR for position players, and 42.0 and 55.9 WAR for pitchers. This affected 47 position players in that survey, and probably muddied up the 65 OFP and 70 OFP grades to some extent. But, by that point it&#8217;s splitting hairs among the top three percent of position players in history, so I left my mistake unharmed (if you protest about the range between Johnny Damon and Willie Randolph, I understand). </p>
<p>Coupled together, pitching and positional WAR provide a much wider range between 40 OFP and 80 OFP. While the total monetized value of these WAR ranges appear problematic for judging prospects, one can simply correct for the fact that approximately 20 percent of prospects make the MLB (or so). Using this type of harsh depreciation, one can construct a relatively strong transactional value marker for MLB prospects:</p>
<table width="" border="" cellpadding="0" cellspacing="0">
<tr bgcolor="#EDF1F3">
<th align="center">OFP</th>
<th align="center">Value</th>
<th align="center">Percentile</th>
<th align="center">Depreciated Value</th>
</tr>
<tr>
<td align="center">40 OFP</td>
<td align="center">$0.5M</td>
<td align="center">7th to 8th</td>
<td align="center">$0.1M</td>
</tr>
<tr>
<td align="center">45 OFP</td>
<td align="center">$7.0M</td>
<td align="center">66th</td>
<td align="center">$1.4M</td>
</tr>
<tr>
<td align="center">50 OFP</td>
<td align="center">$97.3M</td>
<td align="center">88th to 91st</td>
<td align="center">$19.5M</td>
</tr>
<tr>
<td align="center">55 OFP</td>
<td align="center">$170.8M</td>
<td align="center">Approx. 94th</td>
<td align="center">$34.2M</td>
</tr>
<tr>
<td align="center">60 OFP</td>
<td align="center">$244.3M</td>
<td align="center">97th to 98th</td>
<td align="center">$48.9M</td>
</tr>
<tr>
<td align="center">65 OFP</td>
<td align="center">$359.8M</td>
<td align="center">99th</td>
<td align="center">$72.0M</td>
</tr>
<tr>
<td align="center">70-75 OFP</td>
<td align="center">$499.8M</td>
<td align="center"></td>
<td align="center">$100.0M</td>
</tr>
<tr>
<td align="center">80 OFP</td>
<td align="center">$845.6M</td>
<td align="center"></td>
<td align="center">$169.1M</td>
</tr>
</table>
<p>Does it work? Let&#8217;s use an eyeball test with Ryan Braun&#8217;s expected trade value, using both depreciated and non-depreciated versions of Braun&#8217;s value (reflecting the range of values teams may apply to Braun):</p>
<table width="" border="" cellpadding="0" cellspacing="0">
<tr bgcolor="#EDF1F3">
<th align="center">Braun Trade Value</th>
<th align="center">Total Surplus</th>
<th align="center">Historical Depreciation</th>
</tr>
<tr>
<td align="center">Depreciated Braun</td>
<td align="center">$45.8M</td>
<td align="center">65-70 OFP</td>
</tr>
<tr>
<td align="center">Non-Depreciated Braun</td>
<td align="center">$97.3M</td>
<td align="center">65-70 OFP</td>
</tr>
<tr>
<td align="center">40 OFP</td>
<td align="center"></td>
<td align="center">$0.1M</td>
</tr>
<tr>
<td align="center">45 OFP</td>
<td align="center"></td>
<td align="center">$1.4M</td>
</tr>
<tr>
<td align="center">50 OFP</td>
<td align="center"></td>
<td align="center">$19.5M</td>
</tr>
<tr>
<td align="center">55 OFP</td>
<td align="center"></td>
<td align="center">$34.2M</td>
</tr>
<tr>
<td align="center">60 OFP</td>
<td align="center"></td>
<td align="center">$48.9M</td>
</tr>
<tr>
<td align="center">65 OFFP</td>
<td align="center"></td>
<td align="center">$72.0M</td>
</tr>
<tr>
<td align="center">70-75 OFP</td>
<td align="center"></td>
<td align="center">$100.0M</td>
</tr>
<tr>
<td align="center">80 OFP</td>
<td align="center"></td>
<td align="center">$169.1M</td>
</tr>
</table>
<p>This model appears to be fairly intuitive in this case. If a team uses a depreciated version of Braun&#8217;s performance and applies it to his contractual situation, Braun&#8217;s trade value would be worth approximately two 50 OFP prospects, <em>maybe</em> a 50 OFP and 55 OFP package if a team really wants Braun or has some value discrepancy with one of their prospects, or one 60 OFP prospect. If teams take Braun&#8217;s production value and contractual situation at face value, the veteran is worth approximately two 60 OFP prospects, or a 55 OFP and 60 OFP prospect at the very least. This works remarkably well compared to the theoretical models discussed earlier this week. Let&#8217;s run another test, using the Carlos Gomez-Mike Fiers trade (with value assessed on the day of the trade, rather than in hindsight):</p>
<table width="" border="" cellpadding="0" cellspacing="0">
<tr bgcolor="#EDF1F3">
<th align="center">Gomez-Fiers Trade</th>
<th align="center">Total Surplus</th>
<th align="center">Historical Depreciation</th>
</tr>
<tr>
<td align="center">Carlos Gomez</td>
<td align="center">$67.6M</td>
<td align="center">n/a</td>
</tr>
<tr>
<td align="center">Mike Fiers</td>
<td align="center">$39.2M</td>
<td align="center">n/a</td>
</tr>
<tr>
<td align="center">Domingo Santana (50 OFP)</td>
<td align="center"></td>
<td align="center">$19.5M</td>
</tr>
<tr>
<td align="center">Brett Phillips (60 OFP)</td>
<td align="center"></td>
<td align="center">$48.9</td>
</tr>
<tr>
<td align="center">Josh Hader (&#8220;On the Rise&#8221;)</td>
<td align="center"></td>
<td align="center">$19.5M</td>
</tr>
<tr>
<td align="center">Adrian Houser (45 OFP)</td>
<td align="center"></td>
<td align="center">$1.4M</td>
</tr>
</table>
<p>This model gets relatively close to capturing equilibrium. The trouble is assessing Fiers&#8217;s contract, of course, since four arbitration years of control means that Houston can cut Fiers without paying a dime (which vastly inflates Fiers&#8217;s value). Taking Fiers&#8217;s performance value of $19.6M and Gomez&#8217;s total surplus, their value of $87.2M was countered with a prospect value that returns a historical depreciation value of $89.3M, which is much closer to equilibrium. Obviously, in the actual circumstances of a trade, it is arguable that teams are not trying to return equilibrium value, or rather, that teams are trying to return &#8220;equilibrium value&#8221; that suits their organizational needs to the greatest extent possible. Even with this caveat, it appears that stratifying the history of MLB according to WAR performance levels, and then grading each percentile with an &#8220;OFP&#8221; actually crates quite a useful &#8220;at a glance&#8221; model for analyzing trades in Cost-Benefit Analysis style.</p>
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